Health and Social Development, Faculty of (Okanagan)
Health and Exercise Sciences, School of (Okanagan)
DSpace
UBCO
Tallon, Christine Marie
Doctor of Philosophy - PhD
University of British Columbia
Despite extensive literature on cerebral blood flow (CBF) regulation and cerebrovascular function in adults, there is very limited knowledge for the healthy child. Equally, as children’s daily sedentary behaviour increases, relationships between sedentary behaviour, physical activity, and cerebral hemodynamics are also poorly understood. This thesis aimed to determine the impact of sedentary behaviour on cerebrovascular function in healthy children. To achieve this objective four studies were conducted. An initial study (Chapter 3) explored relationships between habitual sedentary behaviour, physical activity, maturation, and CBF at rest in 78 children and adolescents (6 – 17 years), observing a lower internal carotid artery (ICA) shear rate in participants who engaged in >452 min of total sedentary behaviour per day. The second and third studies focused on the measurement of cerebrovascular function in children compared to adults and investigated cerebrovascular reactivity [CVR] to inspired carbon dioxide (F₁CO₂; 6%), indexed by temporal blood velocity changes (v) within the middle cerebral artery (MCA; Chapter 4) and blood flow in the ICA (QICA; Chapter 5), per unit of change in the end-tidal partial pressure of CO₂. Findings of Chapter 4 indicate similar CVR MCAv in children (n=21) and adults (n=20), but a significantly slower onset response to CO₂ in children compared to adults. Similarly, findings of Chapter 5 indicate a similar CVR ICA between children (n=14) and adults (n=17) but a slower onset response in the child. Applying knowledge of the relationship identified in Chapter 3, and the methodology used in Chapters 4 and 5, the fourth study (Chapter 6) investigated whether an acute bout of prolonged sitting (3 h) would alter cerebrovascular function and whether interrupting prolonged sitting with exercise breaks (10 min each hour) affords defence against any sitting-induced cerebrovascular disruption in children (n=31). Findings of Chapter 6 indicate an acute bout of prolonged sitting compromises QICA CVR and the MCAv onset response; however, when sitting was interrupted with exercise breaks these declines were prevented. The findings from this thesis have provided novel evidence of the negative impact sedentary behaviour and prolonged sitting have on cerebrovascular function in the child.
THE IMPACT OF SEDENTARY BEHAVIOUR AND PHYSICAL ACTIVITY ON CEREBROVASCULAR HEMODYNAMICS, CEREBROVASCULAR REACTIVITY, AND NEUROVASCULAR COUPLING IN CHILDREN by Christine Marie Tallon B.H.K., The University of British Columbia, 2015 A THESIS SUBMITTED IN PARTIAL FULFILLMENT OF THE REQUIREMENTS FOR THE DEGREE OF DOCTOR OF PHILOSOPHY in THE COLLEGE OF GRADUATE STUDIES (Kinesiology) THE UNIVERSITY OF BRITISH COLUMBIA (Okanagan) September 2022 © Christine Marie Tallon, 2022 ii The following individuals certify that they have read, and recommend to the College of Graduate Studies for acceptance, a thesis/dissertation entitled: The impact of sedentary behaviour and physical activity on cerebrovascular hemodynamics, cerebrovascular reactivity, and neurovascular coupling in children submitted by Christine Marie Tallon in partial fulfillment of the requirements of the degree of Doctor of Philosophy. Dr. Ali McManus, School of Health and Exercise Sciences Supervisor Dr. Phil Ainslie, School of Health and Exercise Sciences Supervisory Committee Member Dr. Alan Barker, University of Exeter Supervisory Committee Member Dr. Christine Voss, Faculty of Medicine, Southern Medical Program University Examiner Dr. Karin Pfeiffer, Michigan State University External Examiner iii Abstract Despite extensive literature on cerebral blood flow (CBF) regulation and cerebrovascular function in adults, there is very limited knowledge for the healthy child. Equally, as children’s daily sedentary behaviour increases, relationships between sedentary behaviour, physical activity, and cerebral hemodynamics are also poorly understood. This thesis aimed to determine the impact of sedentary behaviour on cerebrovascular function in healthy children. To achieve this objective four studies were conducted. An initial study (Chapter 3) explored relationships between habitual sedentary behaviour, physical activity, maturation, and CBF at rest in 78 children and adolescents (6 – 17 years), observing a lower internal carotid artery (ICA) shear rate in participants who engaged in >452 min of total sedentary behaviour per day. The second and third studies focused on the measurement of cerebrovascular function in children compared to adults and investigated cerebrovascular reactivity [CVR] to inspired carbon dioxide (FICO2; 6%), indexed by temporal blood velocity changes (v) within the middle cerebral artery (MCA; Chapter 4) and blood flow in the ICA (QICA; Chapter 5), per unit of change in the end-tidal partial pressure of CO2. Findings of Chapter 4 indicate similar CVR MCAv in children (n=21) and adults (n=20), but a significantly slower onset response to CO2 in children compared to adults. Similarly, findings of Chapter 5 indicate a similar CVR ICA between children (n=14) and adults (n=17) but a slower onset response in the child. Applying knowledge of the relationship identified in Chapter 3, and the methodology used in Chapters 4 and 5, the fourth study (Chapter 6) investigated whether an acute bout of prolonged sitting (3 h) would alter cerebrovascular function and whether interrupting prolonged sitting with exercise breaks (10 min each hour) affords defence against any sitting-induced cerebrovascular disruption in children (n=31). Findings of Chapter 6 indicate an acute bout of prolonged sitting compromises QICA CVR and the MCAv onset response; however, when sitting was interrupted with exercise breaks these declines were prevented. The findings from this iv thesis have provided novel evidence of the negative impact sedentary behaviour and prolonged sitting have on cerebrovascular function in the child. v Lay Summary Excessive sedentary behaviour has been shown to lead to negative health consequences in childhood. The aim of this thesis was to investigate the impact sedentary behaviour has on brain blood flow in healthy children. Four studies were undertaken. First, the relationship between sedentary behaviour and resting brain blood flow was examined. Two studies focused on the assessment of the regulation of brain blood flow and these techniques were then used in a final experimental manipulation of prolonged, uninterrupted sitting. The main findings were: 1) increased sedentary time was associated with poorer metrics of blood flow to the brain, 2) the onset and steady-state brain artery response to carbon dioxide may provide sensitive measures of brain blood flow regulation in children, and 3) children have a decreased brain artery response to carbon dioxide following acute prolonged uninterrupted sitting, whereas breaking up sitting with exercise protects against this decline. vi Preface Chapter 1: Christine Tallon drafted a majority of this Chapter with extensive feedback from Prof. Ali McManus Chapter 2: Aspects of Chapter 2 have been accepted for publishing. McManus AM, Tallon CM. Exercise and the brain. In: Armstrong N (ed.) Oxford textbook of children’s sport and exercise medicine. 4th edition. Oxford University Press, 2023. Christine Tallon drafted a majority of this Chapter with extensive feedback from Prof. Ali McManus. Chapter 3: A version of Chapter 3 has been published. Tallon CM, Smith KJ, Nowak-Flück D, Koziol AV, Rieger MG, Lutes LD, Green DJ, Tremblay MS, Ainslie PN, McManus AM. (2021). The influence of sex and maturation on carotid and vertebral artery hemodynamics and associates with free-living (in)activity in 6-17-year-olds. J Appl Physiol. 131(5), 1575-1583. The permission to include this work in the present thesis has been granted by the publisher. The protocol of this study was approved by the University of British Columbia Clinical Research Ethics Board (H16-01281 & H17-00570). Prof. Ali McManus wrote the study design and the ethics application. Christine Tallon was involved in all recruitment, organization, testing of the participants, and performed all analysis. The candidate prepared the first version of the manuscript, and coordinated edits from co-authors. The candidate submitted the manuscript, prepared the response to the reviewer comments, and revised the manuscript accordingly. Chapter 4: A version of Chapter 4 has been published. Tallon CM, Barker AR, Nowak-Flück D, Ainslie PN, McManus AM. (2019). The influence of age and sex on cerebrovascular reactivity and ventilatory response to hypercapnia in children and adults. Exp Physiol. 105(7), 1090-1101. The permission to include this work in the present thesis has been granted by the publisher. The protocol of this study was approved by the University of British Columbia Clinical vii Research Ethics Board (H16-01281). Prof. Ali McManus wrote the study design and the ethics application. Christine Tallon was involved in all recruitment, organization, testing of the participants, and performed all analyses. The candidate prepared the first version of the manuscript, and coordinated edits from co-authors. The candidate submitted the manuscript, prepared the response to the reviewer comments, and revised the manuscript accordingly. Chapter 5: A version of Chapter 5 has been published. Tallon CM, Talbot JS, Smith KJ, Lewis N, Nowak-Flück D, Stembridge M, Ainslie P, McManus AM. (2022). Dynamic onset response of the internal carotid artery to hypercapnia Is blunted in children compared with adults. Physiol Reports. 10(6), e15406. The protocol of this study was approved by the University of British Columbia Clinical Research Ethics Board (H16-01281). The study was designed by Prof. Ali McManus. Christine Tallon was involved in all recruitment, organization, testing of the participants, and performed all analyses. The candidate prepared the first version of the manuscript, and coordinated edits from co-authors. The candidate submitted the manuscript, prepared the response to the reviewer comments, and revised the manuscript accordingly. Chapter 6: Aspects of this Chapter have been presented within the Cerebral Blood Flow Virtual Seminar Series in August 2020. No aspect of Chapter 6 is currently under review for consideration for publication. The protocol of this study was approved by the University of British Columbia Clinical Research Ethics Board (H16-01324). Prof. Ali McManus wrote the study design and the ethics application. Christine Tallon was involved in all recruitment, organization, testing of the participants, performed all analyses and created figures. The candidate drafted a majority of this manuscript with extensive feedback from Dr. McManus. Chapter 7: No aspect of Chapter 7 is currently under review for consideration for publication. Christine Tallon drafted the majority of this Chapter with extensive feedback from Prof. Ali McManus viii Appendix A: A version of Appendix A has been published. Accepted author manuscript version reprinted, by permission, from Pediatric Exercise Science, 2019, 31(3): 290-295, https://doi.org/10.1113/EP088293. © Human Kinetics, Inc. Tallon CM, Simair RG, Koziol AV, Ainslie PN, & McManus AM. (2019). Intra-cranial vascular responses to high-intensity interval exercise and moderate-intensity steady-state exercise in children. Pediatr Exerc Sci. 31(3), 290-295. The protocol of this study was approved by the University of British Columbia Clinical Research Ethics Board (H15-02104). Prof. Ali McManus and Simair RG wrote the study design and the ethics application. Christine Tallon performed all analysis, prepared the first version of the manuscript and coordinated edits from co-authors, submitted the manuscript, prepared the response to the reviewer comments, and revised the manuscript accordingly. Appendix B: A version of Appendix B has been published. Tallon CM, Smith KJ, Lewis N, McManus AM. Examining blood vessels with sound waves. Front Young Minds. 2021; DOI: 10.3389/frym.2021.618465. Accepted author manuscript version reprinted under the Creative Commons Attribution License. Copyright © Tallon, Smith, Lewis and McManus. Christine Tallon prepared the first draft. Christine Tallon coordinated edits from co-authors, submitted the manuscript, prepared the response to reviewer comments, and revised the manuscript accordingly. ix Table of Contents Abstract .................................................................................................................................... iii Lay Summary ............................................................................................................................ v Preface ..................................................................................................................................... vi Table of Contents .................................................................................................................... ix List of Tables ......................................................................................................................... xiii List of Figures ........................................................................................................................ xiv List of Equations ................................................................................................................... xvi List of Abbreviations ............................................................................................................ xvii Acknowledgements ............................................................................................................... xix Dedication .............................................................................................................................. xxi Chapter 1: Introduction ............................................................................................................ 1 Chapter 2: Literature Review ................................................................................................... 5 2.1 Cerebral metabolism during childhood and adolescence .............................................. 5 2.2 Cerebral perfusion during development ........................................................................ 8 2.3 Assessment of cerebral hemodynamics and cerebrovascular function ........................ 10 2.3.1 Cerebral hemodynamics and ultrasound ................................................................ 10 2.3.1.1 Transcranial Doppler ultrasound ................................................................ 12 2.3.1.2 Duplex ultrasound ...................................................................................... 14 2.4 Regulation of cerebral blood flow ................................................................................ 15 2.4.1 Arterial blood gases: Carbon dioxide ...................................................................... 15 2.4.2 Arterial blood gases: Oxygen .................................................................................. 17 2.4.3 Blood pressure ....................................................................................................... 17 2.4.4 Metabolism ............................................................................................................. 18 2.5 Exercise, aerobic fitness, physical activity, sedentary behaviour, and the developing brain............................................................................................................................ 18 2.5.1 Acute exercise ........................................................................................................ 19 2.5.2 Aerobic fitness and exercise training ...................................................................... 22 2.5.3 Physical activity and sedentary behaviour .............................................................. 23 2.6 Summary .................................................................................................................... 25 Chapter 3: The Influence of Sex and Maturation on Carotid and Vertebral Artery Hemodynamics and Associations with Free-living Sedentary Behaviour and Physical Activity in 6–17-year-olds .............................................................................. 26 x 3.1 Background................................................................................................................. 26 3.2 Methods ...................................................................................................................... 28 3.2.1 Study design .......................................................................................................... 28 3.2.2 Measures ............................................................................................................... 28 3.2.2.1 Anthropometrics and maturation ................................................................ 28 3.2.2.2 Cerebrovascular measures ........................................................................ 29 3.2.2.3 Accelerometry ............................................................................................ 30 3.2.3 Statistical analysis .................................................................................................. 31 3.3 Results ........................................................................................................................ 32 3.4 Discussion .................................................................................................................. 35 3.4.1 Age, maturation and cerebrovascular development ................................................ 36 3.4.2 Age, maturation, physical activity and sedentary behaviour .................................... 38 3.4.3 Potential mechanistic pathway ............................................................................... 39 3.4.4 Limitations .............................................................................................................. 41 3.4.5 Summary ................................................................................................................ 41 Chapter 4: The Influence of Age and Sex on Cerebrovascular Reactivity and Ventilatory Response to Hypercapnia in Children and Adults ...................................................... 43 4.1 Background................................................................................................................. 43 4.2 Methods ...................................................................................................................... 45 4.2.1 Ethical approval ...................................................................................................... 45 4.2.2 Study design .......................................................................................................... 45 4.2.3 Measures ............................................................................................................... 46 4.2.3.1 Anthropometrics and maturation ................................................................ 46 4.2.3.2 Cardiorespiratory measures ....................................................................... 47 4.2.3.3 Cerebrovascular measures ........................................................................ 47 4.2.4 Data processing ..................................................................................................... 47 4.2.4.1 Baseline and steady-state responses to hypercapnia ................................ 47 4.2.4.2 Dynamic onset responses to hypercapnia.................................................. 49 4.2.5 Statistical analysis .................................................................................................. 49 4.3 Results ........................................................................................................................ 50 4.3.1 Baseline and steady-state responses to hypercapnia ............................................. 50 4.3.2 Dynamic onset responses to hypercapnia. ............................................................. 55 4.4 Discussion .................................................................................................................. 57 4.4.1 Child to adult differences in reactivity to CO2 ......................................................... 57 xi 4.4.2 Potential mechanism(s) .......................................................................................... 59 4.4.3 Sex differences in MCAv ........................................................................................ 60 4.4.4 Methodological considerations ............................................................................... 62 4.4.5 Summary ................................................................................................................ 64 Chapter 5: Dynamic Onset Response of the Internal Carotid Artery to Hypercapnia is Blunted in Children Compared with Adults ................................................................. 66 5.1 Background................................................................................................................. 66 5.2 Methods ...................................................................................................................... 68 5.2.1 Ethical approval ...................................................................................................... 68 5.2.2 Participants ............................................................................................................ 68 5.2.3 Experimental protocol ............................................................................................. 68 5.2.4 Measurements........................................................................................................ 69 5.2.4.1 Anthropometrics and maturation ................................................................ 69 5.2.4.2 Extra-cranial arterial measures .................................................................. 69 5.2.4.3 Cardiorespiratory measures ....................................................................... 70 5.2.5 Data processing ..................................................................................................... 71 5.2.5.1 Baseline and response to four minutes of hypercapnia .............................. 71 5.2.5.2 Dynamic onset responses to hypercapnia.................................................. 71 5.2.6 Statistical analysis .................................................................................................. 72 5.3 Results ........................................................................................................................ 72 5.3.1 Baseline and steady state response to hypercapnia ............................................... 73 5.3.2 Dynamic onset responses to hypercapnia .............................................................. 75 5.4 Discussion .................................................................................................................. 78 5.4.1 Comparison of child and adult responses to steady state hypercapnia ................... 79 5.4.2 Comparison of child and adult ICA response kinetics to hypercapnia ..................... 80 5.4.3 Strengths & Limitations ........................................................................................... 81 5.4.4 Summary ................................................................................................................ 82 Chapter 6: Cerebrovascular Response Compromised Following an Acute Bout of Uninterrupted Prolonged Sitting in Healthy Children: A Randomized Cross-over Trial ................................................................................................................................ 83 6.1 Background................................................................................................................. 83 6.2 Methods ...................................................................................................................... 85 6.2.1 Participants ............................................................................................................ 85 6.2.2 Study design and procedures ................................................................................. 86 6.2.3 Measures ............................................................................................................... 88 xii 6.2.3.1 Body composition and maturation .............................................................. 88 6.2.3.2 Accelerometry ............................................................................................ 89 6.2.3.3 Identification of the intensity of the exercise breaks ................................... 89 6.2.3.4 Cardiovascular measures .......................................................................... 90 6.2.3.5 Cerebrovascular function ........................................................................... 90 6.2.4 Statistical Analysis .................................................................................................. 93 6.3 Results ........................................................................................................................ 93 6.3.1 Neurovascular Coupling ......................................................................................... 94 6.3.2 Baseline and steady-state responses to hypercapnia ............................................. 95 6.3.3 Dynamic onset response to hypercapnia ................................................................ 98 6.4 Discussion .................................................................................................................. 99 6.4.1 Limitations ............................................................................................................ 101 6.4.2 Summary .............................................................................................................. 102 Chapter 7: General discussion ............................................................................................ 103 7.1 Summary of experimental findings ............................................................................ 103 7.2 Implications of this work ............................................................................................ 105 7.3 Limitations of this thesis ............................................................................................ 106 7.3.1 Recruitment of participants ................................................................................... 106 7.3.2 Research with pediatric populations ..................................................................... 107 7.3.3 Assessment and analysis of cerebrovascular function .......................................... 108 7.3.4 Sex and maturation considerations....................................................................... 109 7.3.5 Study population and sample size ........................................................................ 110 7.4 Prospects for future research .................................................................................... 111 7.4.1 Design of prolonged sitting and interruptions ........................................................ 111 7.5 Conclusion ................................................................................................................ 112 References ............................................................................................................................ 114 Appendices ........................................................................................................................... 133 Appendix A Intracranial Vascular Responses to High-Intensity Interval Exercise and Moderate-Intensity Steady-State Exercise in Children............................................... 133 Appendix B Examining blood vessels using sound waves .................................................. 148 xiii List of Tables Table 1. Boundaries defining groups of daily average and 7-day aggregate physical activity and sedentary behaviour variables. ................................................................................................. 31 Table 2. Carotid and vertebral artery diameter and hemodynamic parameters by sex and maturation. ............................................................................................................................... 33 Table 3. Physical activity and sedentary behaviour by sex and maturation. .............................. 34 Table 4. Ventilatory, cardiovascular, and cerebrovascular data at baseline and in the final 30s of hypercapnia in children and adults and by sex. ........................................................................ 51 Table 5. Middle cerebral artery, partial pressure of end-tidal carbon dioxide, and ventilation kinetic responses at the onset of hypercapnia in children and adults. ....................................... 55 Table 6. Baseline and hypercapnic cardiovascular, respiratory, and vascular responses in children and adults. .................................................................................................................. 74 Table 7. End-tidal carbon dioxide and internal carotid artery response kinetics to hypercapnia in children and adults. .................................................................................................................. 76 Table 8. Participants’ demographic and anthropometrics. ......................................................... 93 Table 9. Cardiovascular and cerebral neurovascular coupling parameters Pre and Post both experimental conditions. ........................................................................................................... 94 Table 10. Assessment of intra- and extra-cranial arteries using duplex ultrasound while participants rested supine breathing room air. .......................................................................... 96 Table 11. Absolute and relative cerebrovascular reactivity Pre and Post experimental conditions. ................................................................................................................................................. 98 Table 12. Dynamic responses at the onset of hypercapnia Pre and Post the experimental conditions. ................................................................................................................................ 98 Table 13. Summary of participant recruitment efforts, attrition, and completion rate for Chapter 6. ............................................................................................................................................ 107 xiv List of Figures Figure 1. Assessing cerebral metabolism in children using the Kety-Schmidt nitrous oxide technique. ................................................................................................................................... 6 Figure 2. Schematic of the extra-cranial cerebrovasculature tree.............................................. 10 Figure 3. Schematic of the Circle of Willis ................................................................................. 11 Figure 4. A young participant wearing a transcranial Doppler ultrasound headpiece during exercise. ................................................................................................................................... 12 Figure 5. The relationship between average time spent sedentary per day and internal carotid artery shear rate at rest, covarying for maturation and the average number of steps taken per day. .......................................................................................................................................... 35 Figure 6. Relative and absolute cerebrovascular reactivity of the middle cerebral artery to hypercapnia by age and by sex. ............................................................................................... 52 Figure 7. Hypercapnic ventilatory and cardiovascular reactivity by age and by sex. ................. 54 Figure 8. Dynamic onset response of middle cerebral artery blood velocity in representative child and adult subjects. ........................................................................................................... 56 Figure 9. Relative and absolute cerebrovascular reactivity of the internal carotid artery to hypercapnia by age. ................................................................................................................. 75 Figure 10. The response to hypercapnia of a representative adult and child subject. ............... 77 Figure 11. Mean response time to hypercapnia in children and adults. ..................................... 78 Figure 12. Progression of participants from the point of recruitment until completion of randomized experimental conditions. ........................................................................................ 86 Figure 13. Experimental design of the two conditions. .............................................................. 87 Figure 14. Relative cerebrovascular reactivity of the internal carotid artery Pre and Post experimental conditions. ........................................................................................................... 97 Figure 15. Middle cerebral artery tau Pre and Post experimental conditions. ............................ 99 Figure 16. A schematic of experimental protocols: high-intensity interval and moderate-intensity exercise. ................................................................................................................................. 137 Figure 17. Heart rate, expressed as a percent of maximum, during each stage of high-intensity interval and moderate-intensity steady state exercise. ............................................................ 140 Figure 18. The relative change in middle cerebral artery blood velocity during each stage of high-intensity interval and moderate-intensity steady state exercise. ...................................... 141 xv Figure 19. Middle cerebral artery blood velocity (panel A) and partial pressure of end-tidal carbon dioxide (panel B) following completion of high-intensity interval and moderate-intensity steady state exercise conditions. ............................................................................................ 142 Figure 20. Blood vessels make two loops within the body. ..................................................... 148 Figure 21. Short and long wavelength sound waves. .............................................................. 149 Figure 22. How an ultrasound machine examines blood vessels. ........................................... 151 xvi List of Equations Equation 1. Calculation of volumetric cerebral blood flow ......................................................... 29 Equation 2. Calculation of shear rate ........................................................................................ 29 Equation 3. Absolute cerebrovascular reactivity........................................................................ 48 Equation 4. Relative cerebrovascular reactivity......................................................................... 48 Equation 5. Hypercapnic ventilatory response .......................................................................... 48 Equation 6. Mean arterial blood pressure reactivity to carbon dioxide ....................................... 48 Equation 7. Heart rate reactivity to carbon dioxide .................................................................... 48 Equation 8. Monoexponential function ...................................................................................... 49 Equation 9. Cerebrovascular conductance ............................................................................... 71 Equation 10. Mean response time ............................................................................................ 72 xvii List of Abbreviations aPHV – age at peak height velocity BDNF – brain-derived neurotrophic factor BMI – body mass index Bout<0.5 – total time sedentary in bouts lasting less than 30 min Bout0.5-1 – total time sedentary in bouts lasting between 30 min and 60 min Bout1-2 – total time sedentary in bouts lasting between 1 h and 2 h Bout>2 – total time sedentary in bouts lasting longer than 2 h BP – blood pressure CCA(d, SR, or v) – common carotid artery (diameter, shear rate, or blood velocity) gCBF – (global) CBF CMR(O2) – cerebral metabolic rate (of oxygen uptake) CO – cardiac output CO2 – carbon dioxide CVC(MCA) – cerebrovascular conductance of the middle cerebral, internal carotid, or posterior cerebral artery CVR(Abs or Rel) – cerebrovascular reactivity (in absolute or relative terms) CVRiMCA – cerebrovascular resistance index of the middle cerebral artery FICO2 – fraction of inspired carbon dioxide HCVR – hypercapnic ventilatory response HIIE – high-intensity interval exercise HR(Max) – heart rate (expressed as a percentage of maximum) ICA(d, SR, or v) – internal carotid artery (diameter, shear rate, or blood velocity) MAP – mean arterial pressure MCA(v) – middle cerebral artery (blood velocity) MISS – moderate-intensity steady state exercise xviii MRI – magnetic resonance imaging MRT – mean response time NVC – neurovascular coupling PaCO2 – partial pressure of arterial carbon dioxide PaO2 – partial pressure of arterial oxygen PCA(v) – posterior cerebral artery (blood velocity) PET – positron emission tomography PETCO2 – partial pressure of end-tidal carbon dioxide PETO2 – partial pressure of end-tidal oxygen Q(CCA, ICA, or VA) – volumetric blood flow (of the common carotid, internal carotid, or vertebral artery) RMR – resting metabolic rate RR – respiration rate SedTime – total daily sedentary time in minutes per day StepCount – total number of steps per day TCD – transcranial Doppler ultrasound TD – delay term VA(d, SR, or v) – vertebral artery (diameter, shear rate, or blood velocity) VE – ventilation VT – tidal volume xix Acknowledgements The completion of this thesis is the product of the support from countless people in my life, all of whom I am lucky enough to have been able to lean on throughout this process. Without their support, the work within this thesis would not have come to fruition. First, with the utmost gratitude, I would like to thank my supervisor, Dr. Ali McManus, for her unwavering support and guidance over the years. My independence and research skills have flourished under your mentorship. I have grown as a direct result of your continuous push to pursue opportunities, our countless conversations, and your encouragement to take a break once in a while. I will be forever grateful. I would like to thank my committee members, Drs. Phil Ainslie and Alan Barker, for their patience, time, and guidance at various times throughout this degree, and my external examiners, Drs. Karin Pfeiffer and Christine Voss. I would like to thank Dr. Sarah Moore for her time and efforts through my Comprehensive Examination process, and her continuous encouragement when I could not see the finish line. I would like to thank every co-author and collaborator on the projects comprising this thesis and completed during my time at UBCO. Quite literally, none of this work could have been completed without your time, efforts, and intellect. To each of the members of PERL, both past and present, all of you have contributed to creating an experience I will look back on fondly, thank you. To every friend who either entered this journey alongside me or entered my life along the way, I am appreciative of you. The knowledge I have gained over the course of this journey has been a result of the acts of friendship and support I have received from all of you as I have progressed through the Ph.D. These years have been filled with moments of friendship complete xx with laughter, tears, and conversations over shared food, drink, and many walks. My gratitude for each of you runs deep, as every moment has contributed to my experience. And finally, to my family – Thank You – for every moment of unwavering support as I strive to reach this goal, for guiding me through the days when I have been buried under the stress of deadlines, for your help when I brought Charlie home (stubbornly thinking I could raise her alone), and for answering the colossal number of phone calls which rarely have a purpose. Being raised in this family is why I am at this point and everything I have accomplished is a result of your support. xxi Dedication For my family – for without your support I would not have achieved this milestone. Chapter 1: Introduction The public health significance of an increasingly sedentary population cannot be overestimated. Sedentary behaviour is a form of physical inactivity defined as ‘sitting without otherwise moving’ (Owen et al., 2011) and characterized by periods of time spent seated, reclining or lying, with correspondingly low levels of energy expenditure (Tremblay et al., 2017). The annual economic burden of sedentary behaviour in Canada is estimated to be $5.6 billion (Lee et al., 2012). In British Columbia alone, the percentage of health care spending associated with lifestyle-related chronic conditions comprises 80% of the medical services and care budget (Colman & Walker, 2004). Yet, children are growing up in an environment where spontaneous physical activity has been engineered out of their daily lives and instead sedentary behaviour is ubiquitous. Current guidelines recommend children should minimize daily sedentary time by limiting screen-based entertainment and other sedentary activities such as transport in motorized vehicles and extended sitting (Tremblay et al., 2016). Nonetheless, Canadian children under 10 years of age are spending up to five hours per day with seated screen-based entertainment, which rises to more than 7 hours per day in 12–18-year-old Canadian youngsters (Leatherdale & Ahmed, 2011; Saunders et al., 2014). This is particularly concerning given the increasing body of epidemiological evidence that shows too much sitting is an independent risk factor for cardiovascular disease in both children and adults and is associated with an increase in all-cause mortality in adults (Hamilton et al., 2008; Saunders et al., 2014). A modest 10% reduction in sedentary time has the potential to reduce direct health care costs nationally by $150 million a year (Katzmarzyk et al., 2000). It is likely that if a 10% reduction in sedentary activities could be achieved, the risk factors for heart disease and stroke by 10% would also be decreased. 2 Early deterioration in vascular function, particularly alterations in endothelial integrity, is significant in the development of cardiovascular disease, (Aggoun et al., 2005; Belcher et al., 2015). In various models of enforced physical inactivity, evidence indicates that acute bouts of sedentary behaviour contribute to vascular deconditioning in adults (Thijssen et al., 2010; Boyle et al., 2013). Recent experimental findings indicate that three hours of uninterrupted sitting causes a substantial disruption to peripheral vascular function in adults and children, which can be counteracted by taking regular exercise breaks (McManus et al., 2015; Thosar et al., 2015). Sitting-induced decrements in the peripheral vasculature may be accompanied by altered cerebrovascular function in childhood. Sedentary aging in adulthood is associated with a longitudinal decline in cerebrovascular blood flow (Ainslie et al., 2008; Barnes et al., 2013), cerebrovascular reactivity (CVR) (Bakker et al., 2004; Bailey et al., 2013), and autoregulation (Purkayastha et al., 2014), impairments that increase the risk of cognitive decline, dementia (Lautenschlager et al., 2012) and stroke (Okazawa et al., 2003). In contrast, exercise activates metabolic pathways that appear to impact positively on cognitive function (Davis et al., 2011; Herting & Nagel, 2013). The influence sedentary behaviour has on cerebrovascular outcomes in children has not been addressed; however, there is some evidence that taking short (10–20 min) exercise breaks from seated cognitive work results in greater attention scores in children (Janssen et al., 2014). Cognitive function appears to be sensitive to changes in the hemodynamic state; explanations for the improved attention scores following acute exercise breaks include improved neurovascular coupling (NVC), in other words, increases in cerebral blood flow (CBF) in response to a cognitive task (Bakker et al., 2014), or improved CVR, the cerebral arterial dilatory response to a given stimulus, usually carbon dioxide (CO2). The physiological consequences of sedentary behaviour on the cerebrovasculature of the child have yet to be described. Additionally, there is very limited information on cerebrovascular 3 function at rest or during exercise in healthy children. Reduced CVR is apparent in obese hypertensive children and is associated with poorer executive function (Kupferman et al., 2013). Clinically this is important as reductions in CVR to changes in CO2 are associated with stroke risk, at least in adults (Markus & Cullinane, 2001; Portegies et al., 2014). Studies have linked exercise to aspects of brain development and health such as neurogenesis (Chaddock et al., 2010; Meijer et al., 2020; Chaddock-Heyman et al., 2021), stimulation of neurotrophic factor expression (Mora-Gonzalez et al., 2019), and improvement in cognitive function (Donnelly et al., 2016; Hsieh et al., 2020), but the immediate impact of sedentary behaviour on cerebral perfusion and its regulation remains unknown. Therefore, the overall goal of this thesis was to examine the impact sedentary behaviour has on cerebral perfusion and its regulation in children and determine whether physical activity affords protection against any sedentary-related dysfunction. This Chapter is followed by a review of the literature, focusing on the changing metabolic demands of the developing brain and the corresponding shifts in perfusion to meet these demands. An outline of the primary mechanisms responsible for regulating CBF at rest is provided, alongside a brief overview of techniques commonly used to assess cerebral blood velocity and blood flow, as well as cerebrovascular function. The consequences of exercise-induced increases in CBF in children are discussed, with a review of the extant literature on acute cerebrovascular responses to exercise in children and adolescents, as well as consideration of the impact chronic physical activity or sedentary behaviour may exert on cerebrovascular function, are all outlined in Chapters 2. Subsequently, four empirical studies are presented in Chapters 3, 4, 5, and 6. These four studies seek to answer the following questions: (i) What are the relationships between habitual sedentary behaviour, physical activity, maturation, and cerebral hemodynamics at rest?, (ii) Are there development differences in CVR of the intra and extra-cranial arteries and can these be described by both steady-state and dynamic onset responses to CO2?, and (iii) Does prolonged uninterrupted sitting 4 alter cerebral perfusion, NVC and CVR in children and does interrupting prolonged sitting with exercise breaks defend against any sitting-induced cerebrovascular disruption?. Finally, a discussion and summary of the implications of the key findings of this work is presented in Chapter 7. 5 Chapter 2: Literature Review This Chapter provides an overview of the extant literature describing the development of cerebrovascular function in children, and the possible relations between physical activity, sedentary behaviour, and cerebrovascular function in children. Sections 2.1 and 2.2 describe the changes in cerebral metabolism and cerebral perfusion that occur during childhood. Section 2.3 discusses the methods used to assess CBF. Section 2.4 provides an overview of important regulatory pathways that are known to influence CBF. Section 2.5 integrates our understanding of physical activity, sedentary behaviour, and cerebrovascular health outcomes in adults and children. 2.1 Cerebral metabolism during childhood and adolescence Richard Scammon’s classic treatise on ‘the measurement of the body in childhood’ documented growth in postnatal life and provided much of our current understanding of the order of growth of various organs and systems (Scammon, 1930). Scammon documented the percentage of total postnatal growth of multiple organs and systems including brain mass, body mass, and testes mass by age from birth to 20 years. Growth in brain mass occurs earliest, with the most rapid period of growth between birth and about 4 years of age; by which point brain mass is already 80% of total postnatal growth. Growth in brain mass slows considerably in childhood, approaching adult mass by 10–12 years of age, conversely body mass and testes mass growth accelerate as brain mass growth slows. Remarkably, nearly 90 years after Scammon’s work was published, intra-cranial four-dimensional magnetic resonance imaging (MRI) provided volumetric measures that confirmed brain volume is indeed ~80–85% of adult volume by 4–6 years of age and commensurate with adult volume by 10–12 years (Wu et al., 2016). These volumetric increases reflect metabolically costly dynamic changes to the brain across childhood that include ongoing myelination (Bray et al., 2015; Corrigan et al., 2021), 6 synaptic plasticity (Bray et al., 2015), increases in white matter volume (Deoni et al., 2012), as well as declines in grey matter from childhood to adolescence (Giedd et al., 1999). Figure 1. Assessing cerebral metabolism in children using the Kety-Schmidt nitrous oxide technique. This illustration depicts a child under a transparent hemisphere and legs restrained to the bed, breathing a nitrous oxide gas, with a peripheral venous catheter, a peripheral arterial catheter, and a jugular catheter. Reproduced from (Kennedy & Sokoloff, 1957) with permission. Early evidence of a higher cerebral metabolism in childhood was provided by Kennedy and Sokoloff (1957) who documented cerebral metabolic rate of oxygen (CMRO2) using the highly invasive modified Kety-Schmidt nitrous oxide technique in a small group of non-anesthetized children (Figure 1). CMRO2 values were approximately 1.3 times higher in the nine healthy 3–11-year-olds (5.17 ± 0.23 cc·100g-1·min-1) compared to the 12 young adults (4.18 ± 0.47 cc·100g-1·min-1). The Kety-Schmidt technique is invasive, requiring a peripheral venous catheter, a peripheral arterial catheter, and a jugular catheter inserted up to the jugular bulb, therefore subsequent CMRO2 values in childhood have been obtained using alternative less invasive 7 imaging techniques. Data obtained from positron emission tomography (PET) and the C15O2, 15O2, and 15CO2 isotopic inhalation method in a small group of 10-day-old to 16-year-old participants established regional CMRO2 was lower in neonates than in children, with CMRO2 peaking mid-childhood, before the growth spurt when synaptic proliferation is peaking (Takahashi et al., 1999). Further work using PET scanning in 29 children (birth–15.5 years of age) provided evidence that brain glucose consumption does not peak in the immediate postnatal period when relative brain mass is highest, rather it peaks at 5 years of age, at 167 g·day-1 in males, and 146 g·day-1 in females (Kuzawa et al., 2014). These values are estimated to be 1.88 and 1.82 times higher than adult male and female brain glucose consumption, respectively, and require on average 66% of resting metabolic rate (RMR). Kuzawa et al. (2014) suggested that this high metabolic need, met by the peak brain glucose consumption is inversely related to physical activity energy expenditure, which is lowest during the preschool years. More recent use of arterial spin-labelled perfusion MRI estimated brain glucose consumption in 824 8–21-year-olds (Vandekar et al., 2019). Glucose consumption was highest in the 8-year-olds, at around 120 g·day-1 in the females and 135 g·day-1 in the males. These values declined in early adolescence and were lower in females until about 18 years of age (Vandekar et al., 2019). Similar to Kuzawa et al. (2014), Vandekar et al. (2019) also show brain glucose consumption is inversely related to the metabolic demand for somatic growth, with the proportion of RMR required by the brain diminishing from 40–25% RMR between the ages of 8–14 years in females and 45–20% RMR between the ages of 8–16 years in males. Although glucose is the primary metabolic substrate for the brain, other substrates are metabolized by the brain under certain circumstances, such as ketones during starvation or lactate during exercise (Quistorff et al., 2008; van Hall et al., 2009; Dienel, 2019). Brain metabolism during maturation is highly complex and the extant literature is limited (Cremer, 1982; Goyal et al., 2014; Benveniste et al., 2018). However, techniques, such as proton magnetic resonance spectroscopy provide much promise for building a more in-depth understanding of the 8 complex metabolic pathways of glucose, lactate, and ketones (Benveniste et al., 2018), but these approaches are expensive and largely inaccessible. In contrast, CBF is an accessible surrogate for cerebral metabolism given it reflects the supply of nutrients and removal of waste products and can be quantified using global or regional non-invasive measures of blood flow (as well as blood velocity, which is a surrogate for blood flow). 2.2 Cerebral perfusion during development The changing metabolic needs of the brain during development are met through circulatory adjustments that match cerebral perfusion to metabolism. This is elegantly illustrated by the age-related changes in the fraction of cardiac output (CO) contributing to cerebral perfusion. Wu et al. (2016) assessed resting ascending and descending aortic outflow using four-dimensional (4D) flow MRI, alongside an MRI measure of total CBF. The CBF to ascending aortic outflow ratio [( !"#"$#%& $&(() *&(+%,!"-).-/ %(#0.! (10*&(+)*100] was highest around 4 years of age at 46%, declining steadily through later childhood and adolescence to adult values of about 15%. Neuroimaging methods have provided further evidence of a parallel pattern of change in CBF and metabolism through childhood and adolescence. Longitudinal findings using arterial spin labelling MRI show CBF increases by 3.21 mL·100 g·min-1 per year from 2–7 years of age (Paniukov et al., 2020), with similar CBF developmental trajectories for females and males. It would appear from these data that CBF continues to increase past 7 years of age. Further work using arterial spin labelling MRI in 922 8–22-year-olds showed a consistent decline in CBF in multiple brain regions from age 8 years onwards (Satterthwaite et al., 2014). Although cross-sectional, it would appear from these data that CBF peaks around 7–9 years of age and declines thereafter. Notable sex-specific cerebral perfusion developmental trajectories were apparent from 8 years of age (Satterthwaite et al., 2014), with a lower CBF in females up to 13 years of age. In males there is a rapid decline in CBF between 8–13 years, which results in CBF being lower in 9 males than females by mid-adolescence (Satterthwaite et al., 2014). When this cohort was grouped by the stages of maturity described by Tanner, the declines in early puberty (Tanner stages 1–3) were similar in males and females but differed mid- (Tanner stage 4) and post- (Tanner stage 5) puberty, with dramatic declines in males and an actual increase in CBF in females (Satterthwaite et al., 2014). There are obvious limitations in grouping Tanner stages 1 through 3 together as ‘early pubertal’ and aligning girls and boys based on pubic hair development. The assumption is that the timing of the appearance of pubic hair, as well as the tempo, is homogenous across the sexes but stages are not equivalent; stage length is unknown, and the presence of asynchronous sexual maturation of pubic hair, breast, and genitalia compounds the problem (Malina, 2017). Only longitudinal data will confirm the true influence of age, sex, and maturation on the development trajectories of resting CBF. While neuroimaging techniques of cerebral perfusion are indispensable, they have generally been incompatible with exercise. Recent work has demonstrated the feasibility of dynamic pseudo-continuous arterial spin labelling MRI for quantifying total and tissue-specific cerebral perfusion during cycle ergometry (Mast et al., 2022). Exercise-induced changes in cerebral perfusion were dependent on region, with the greatest increases in perfusion at the cerebral cortex. This technique is in its infancy but holds much promise for building a more thorough understanding of cerebral perfusion during exercise. In the absence of a direct measure of cerebral tissue perfusion, the extant exercise literature has assessed global and regional CBF using ultrasound. Therefore, for the remainder of this Chapter only transcranial and duplex ultrasound will be considered and a brief overview of each is provided alongside the associated limitations. 10 2.3 Assessment of cerebral hemodynamics and cerebrovascular function 2.3.1 Cerebral hemodynamics and ultrasound Ultrasound techniques have been used extensively for the assessment of resting and exercise brain blood velocity and flow in adults, with emergent literature in children. The developmental changes noted in resting CBF across age using arterial spin labelling and BOLD MRI are mirrored using both Transcranial Doppler ultrasound (TCD) and Duplex ultrasound. For example, TCD derived middle cerebral artery blood velocity (MCAv) peaks around 6–8 years of age (~92 cm·s-1), then declines into adulthood. Anterior cerebral artery blood velocity peaks earlier, between 1–5 years of age at ~60 cm·s-1, again followed by a gradual decline with ensuing age (Bode & Wais, 1988). Similar age-related changes in global CBF [gCBF; the sum of flow volumes from both sides of the internal carotid artery (ICA) and vertebral artery (VA)] derived from Duplex ultrasound have been noted, with gCBF increases from 500–600 mL·min-1 to 800–1000 mL·min-1 noted between the ages of 3–7 years, thereafter declining to adult levels (~700 mL·min-1) by 15 years of age (Schoning & Hartig, 1996). Figure 2. Schematic of the extra-cranial cerebrovasculature tree. The internal carotid arteries supply the anterior part of the brain and bilaterally account for ~70% of global cerebral blood flow (gCBF). The vertebral arteries primarily support the posterior regions of the brain, delivering ~30% of gCBF. Reproduced from (Thomas et al., 2015) with permission. 11 There are well-established guidelines for the use of ultrasound to document cerebrovascular anatomy and function (Willie et al., 2011; Thomas et al., 2015), but these are predicated on knowledge of the cerebrovascular arterial tree which begins at the level of the heart at the aortic arch (see Figure 2) and ends at the pial vessels penetrating the pial matter, the site of cerebral metabolism. The brachiocephalic artery is the first branch off of the aortic arch, giving rise to the right VA and right common carotid artery (CCA). The left subclavian artery, the second branch off the aortic arch, gives rise to the left VA. Bilaterally, the VA ascends through the transverse foramina of the cervical vertebrae, commonly at the level of cervical vertebra six; however, in a subset of the population, the VA may enter the transverse foramen at the level of the fourth, fifth, or seventh cervical vertebrae (Campero et al., 2011). The left and right VA account for ~30% of resting gCBF (Zarrinkoob et al., 2016). They enter the cranium through the foramen magnum, fusing along the ventral surface of the medulla oblongata until the level of the pons where they anastomose into the left and right basilar arteries. The basilar arteries emerge at the base of the brain where they ramify into a collating ring, the Circle of Willis (Figure 3), a point of accumulation of oxygenated blood that allows for compensatory flow across the intra-cranial arterial network. Of note, post-mortem studies have shown a majority of brains have variations in the size and number of segments comprising the Circle of Willis (Alpers et al., 1959; Saeki & Rhoton, 1977; Iqbal, 2013). From the basilar arteries, the left and right posterior cerebral arteries emerge. The posterior cerebral artery (PCA), the primary source of blood flow supplying the occipital lobe, is commonly assessed using TCD. Figure 3. Schematic of the Circle of Willis This anatomical structure provides collateral flow during periods of regional hypoperfusion. Reproduced from (Vavilala et al., 2002b) with Permission. 12 The left CCA is a direct branch from the aortic arch supplying the cephalic structures. On each side of the neck, the CCA bifurcates at the mandible, into the ICA and external carotid artery. Bilaterally, the ICA is responsible for delivering blood to the anterior portion of the brain, supplying approximately 70% of the resting gCBF (Zarrinkoob et al., 2016). The external carotid arteries supply the face and are important for thermoregulation of the face during exercise (Mast et al., 2022). At the level of the optic nerve, the right and left ICA divide into the MCA that supply the midbrain and lateral surfaces of the cerebral hemispheres, the ophthalmic artery and the anterior cerebral arteries. The MCA is commonly assessed with TCD, while the anterior cerebral artery is less commonly assessed. The anterior cerebral arteries also emerge from both the right and left ICA and supply frontal and parietal lobes. They are connected via the anterior communicating artery. The anterior portion of the Circle of Willis is completed by these midbrain and anterior cerebral vessels. 2.3.1.1 Transcranial Doppler ultrasound TCD was first used as a measurement technique to assess intra-cranial blood vessels in adults by Aaslid et al. (1982), providing a quantitative assessment of the velocity of blood within the intra-cranial vessels via specific acoustic windows (Willie et al., 2011). Six years later TCD was first used to assess the intra-cranial blood velocities of children, reporting decreasing blood velocities with increasing age (Bode & Wais, 1988; Grolimund & Seiler, 1988; Bode & Eden, 1989). The use of TCD requires at least one of four possible acoustic windows: transorbital, transfrontal, transtemporal, and transoccipital bone windows (Robba et al., 2019). The Figure 4. A young participant wearing a transcranial Doppler ultrasound headpiece during exercise. In this instance, insonation of either the middle cerebral artery or the posterior cerebral artery occurred through the transtemporal acoustic window. Parental permission was obtained. 13 acoustic windows are susceptible to attenuation, with increasing age, bone thickness, and soft tissue thickness resulting in increased attenuation and subsequent acoustic window failure (Marinoni et al., 1997; Robba et al., 2019; He et al., 2022). The transtemporal window (Figure 4) being the most commonly used, anterolateral to the ear at the temporal mandibular joint, allows for the assessment of the anterior cerebral artery, MCA, and PCA depending on the angle of the ultrasound transducer (Willie et al., 2011). The benefit of TCD is not only the compatibility with cycle ergometry exercise given the minimal movement artifact even at maximal exercise, but in children attenuation is minimal, leading to greater ease insonating. Although TCD provides a practical means by which intra-cranial arterial blood velocity can be indexed during progressive upright exercise, the method is confounded by its inability to directly measure vessel diameter and as a result, volumetric blood flow. Instead, when using blood velocity as a surrogate, the underlying assumption is that vessel diameter remains constant so blood velocity is proportional to blood flow. There is, however, evidence of vasodilation of the intra-cranial arteries with hypercapnia, the extent of which is driven by the magnitude of the increase in end-tidal CO2 (PETCO2). For example, significant vasodilation of the MCA was noted in adults after an increase in PETCO2 from 36.9 ± 3.8 mmHg at baseline to 51.0 ± 4.5 mmHg, but no significant dilation with a subtler increase in PETCO2 from baseline to 45.0 ± 3.8 mmHg (Verbree et al., 2014). It is not known whether vasomotion of the MCA changes in the same way in children as adults, however, in children exercise PETCO2 values have been shown to remain similar to resting values up until the respiratory compensation point (Ellis et al., 2017) or show a small increase of ~3 mmHg prior to the respiratory compensation point (Weston et al., 2021). A decline in PETCO2 from rest to a maximum of about 4 to 5 mmHg has been noted for children (Ellis et al., 2017; Weston et al., 2021). In adolescents, a larger rise in PETCO2 of about 4 to 5 mmHg has been noted up until the respiratory compensation point, with a decline of about 5 mmHg from rest to maximum. It is unlikely these small changes in PETCO2 would stimulate a vasomotor response, but if there is 14 dilation or constriction of the intra-cranial arteries this will result in an underestimation or overestimation of blood flow from blood velocity respectively. 2.3.1.2 Duplex ultrasound High resolution duplex ultrasound provides an assessment of blood flow by combining two-dimensional Brightness mode (B mode) images of the vessel diameter and pulsed wave Doppler assessment of blood velocity through the cardiac cycle (Thomas et al., 2015). The primary advantage of this technique is the ability to quantify changes to both diameter and velocity, allowing the quantification of volumetric CBF. Commonly, the VA and ICA are insonated during exercise studies in adults, but to date, there are no studies of extra-cranial hemodynamics during exercise in children. An additional advantage of duplex ultrasound is the quantification of shear rate (SR), which is an estimation of the frictional force of the blood flow on the endothelial lining within a blood vessel (i.e. shear stress) (Thosar et al., 2012). There is evidence in children that increases in systemic blood flow during exercise augments shear stress, upregulating vascular nitric oxide bioavailability and vasodilation, and is believed to be an important stimulus for arterial structural remodelling (Mills et al., 2013). Shear stress has been shown to be a potent vasodilator of the ICA in adults (Carter et al., 2016; Hoiland et al., 2017), but this has yet to be demonstrated in children or adolescents. Duplex ultrasound is highly dependent on the skills of the operator and the established technical recommendations must be used (Thomas et al., 2015). One of the drawbacks of Duplex ultrasound is that exercise is limited to supine and semi-supine positions to reduce head and neck movement and it becomes progressively more difficult to acquire good quality images as exercise intensity increases. An additional challenge when working with younger children is an inability to assess vessels bilaterally. Due to the small circumference of the child’s neck, when bilateral 15 duplex ultrasound assessment is attempted the transducer on one side will be impacted by interference feedback from the contralateral side. Only unilateral insonation of the vessel of choice can be completed and, it should be noted, that there can be sizable variation in the left and right VA and ICA in adults (Hoiland et al., 2019). 2.4 Regulation of cerebral blood flow The brain has a very limited substrate storage capacity and given the high metabolic demand precise regulation of CBF is crucial. Primary regulators of CBF include arterial blood gases, blood pressure (BP), metabolism, and neural mechanisms and although these are distinct, there is interplay across these regulatory mechanisms as well as redundancy. Extensive reviews have been published on the regulation of CBF at rest (Willie et al., 2014) and during exercise in adults (Smith & Ainslie, 2017) but there is a paucity of research on the typically developing child or adolescent. As such, we present an overview of the key regulators of resting CBF from the extant adult literature, accompanied by findings in children and adolescents where possible. 2.4.1 Arterial blood gases: Carbon dioxide The partial pressure of arterial CO2 (PaCO2) plays a primary role in the regulation of CBF, at least during wakefulness (Hoiland et al., 2019). It is well-established that elevations or reductions in PaCO2, or the surrogate PETCO2, results in vasodilation or constriction respectively across the entire cerebrovascular tree (Willie et al., 2014) and an increase in CBF. This vasomotor response or CVR is well established in healthy adults but there are far fewer studies in healthy children and the available evidence is conflicting. CVR has been documented using a plethora of methodological and analysis techniques, commonly varying in steady-state and rebreathing methodological approaches, and linear and non-linear analysis approaches (Willie et al., 2014). Linear analysis assesses cerebral hemodynamic reactivity to a given change in PaCO2, from baseline to steady-state over a given 16 period of time. Increases above eupnoeic PaCO2 (i.e. hypercapnia) leads to increases of 3–6 %·mmHg-1 change in hemodynamics, while decreases below eupnoeic PaCO2 (i.e. hypocapnia) lead to decreases of 1–3 %·mmHg-1 change in hemodynamics (Willie et al., 2014). The dynamic, or kinetic, response assesses the speed of the response of the CBF to a step increase in PaCO2. This approach has been used to interrogate the integration of cerebrovascular and ventilatory responses to hypercapnia (Poulin et al., 1996; Poulin et al., 1998). At least in adults, there is a close coupling of MCAv and PaCO2 onset responses (Ogoh et al., 2008; Ainslie & Duffin, 2009). To date, limited data has explored the steady-state responses to hypercapnia in children and none to the dynamic response. Using arterial spin labelling with prospective gas targeting, Leung et al. (2016) alternated 60 s of normoxic isocapnia (PETCO2 40 mmHg) with 45 s of normoxic hypercapnia (PETCO2 45 mmHg). A lower hypercapnic CVR was found in children, with CVR rising through adolescence before declining in adulthood. However, Leung et al. (2016) did not account for physical maturation, and included only 3 boys and 4 girls under the age of 12 years thereby limiting conclusions regarding child-adult differences in CVR. In adults, the average CVR elicited after 4-min breathing a fixed concentration of CO2 is between 3–4 %·mmHg-1 (Hoiland et al., 2019). It is unknown whether the CVR over 4 minutes of hypercapnia in the child would differ from the adult response. Comparison of studies is confounded by the differing methodological approaches used. Using a fixed concentration of inhaled CO2 does not allow for precise manipulation of PETCO2, and steady state in adults is not reached until 1–2 min (Hoiland et al., 2019). Conversely, steady state is reached within 1–15 s using the prospective gas targeting technique, the method utilised by Leung et al. (2016). The fixed concentration method does however allow interactions between CVR and ventilation (VE) to be explored (Hoiland et al., 2019), which is discussed in more detail in the Section 2.5.1 Acute exercise. 17 2.4.2 Arterial blood gases: Oxygen In comparison to PaCO2, the cerebrovasculature is less responsive to changes in the partial pressure of arterial oxygen (PaO2). High levels of PaO2 (hyperoxia) induce mild reductions in CBF, but these are largely related to the increase in VE and subsequent drop in PaCO2. Isocapnic hyperoxia does not result in increases in CBF (Willie et al., 2012; Smith et al., 2016). Increases in CBF are only evident with hypoxia when PaO2 falls to about ~50–60 mmHg from normal resting values of 100 mmHg (Willie et al., 2014; Hoiland et al., 2016). A preferential dependence for increases in anterior cerebral perfusion has been shown in response to hypoxia in children (Gavlak et al., 2013; Morris et al., 2017). Under normoxic conditions the distribution of anterior and posterior blood flow is similar in children and adults (Schoning et al., 1993) and extra-cranial vessel diameter and relative dilation in response to hypoxia is also similar (Morris et al., 2017). The increases in anterior perfusion with hypoxia are therefore not explained by differences in vessel structure, and although speculative, it is possible that local metabolic demand is lower in the brainstem region and higher in the frontal cortex in children – hence the reason for lower relative increase in posterior compared to anterior CBF. 2.4.3 Blood pressure The brain and cerebral blood vessels are encased in a rigid cranium and are therefore subjected to intra-cranial pressure. The resulting cerebral perfusion pressure, the difference between mean arterial pressure (MAP) and intra-cranial pressure, acts as a pressure gradient in the regulation of CBF. When arterial BP drops or increases cerebral arteriolar diameter increases or decreases, respectively, to protect the brain from under and over perfusion. Early work suggested that this autoregulatory mechanism operated within tight MAP limits, with changes in BP between 60–150 mmHg having a minimal effect on CBF (Lassen, 1959). However, contemporary understanding however shows that CBF is much more dynamic in response to changes in BP, even within these pressure limits (Claassen et al., 2021). At least in adults, the 18 autoregulatory effectiveness of maintaining CBF is dependent on the speed of change in BP. When changes in BP are gradual, CBF is held constant but when changes in BP are rapid and CBF is altered, tracking BP changes. There are few studies of cerebral autoregulation in the healthy, non-anaesthetised child (Udomphorn et al., 2008), with findings indicating autoregulation is similar between children and adults (Vavilala et al., 2003). Whether rapid changes in arterial BP induce changes in CBF has yet to be determined in children. 2.4.4 Metabolism CBF is tightly coupled to cerebral metabolism, but the exact alignment of the vascular responses to neuronal action (i.e. NVC) is complex and likely involves both feedforward and feedback mechanisms (Iadecola, 2017). A variety of techniques have been used to assess NVC, the interplay between CBF and a task that increases neuronal activity. When NVC has been assessed using cognitive tasks (Groen et al., 2012) or visual stimulation (Rosengarten et al., 2003), few differences have been reported between children, adolescents, and adults. Again, purposeful experiments and longitudinal work are required to fully elucidate the NVC response from childhood through adolescence and the neurovascular responsiveness to other challenges such as exercise or sedentary behaviour. 2.5 Exercise, aerobic fitness, physical activity, sedentary behaviour, and the developing brain The integrated physiological response to exercise is quite remarkable in its complexity, incorporating a multitude of respiratory, cardiovascular, and metabolic processes to support the exercising muscle. Extensive work in adults has established that this coordinated response also implicates cerebral metabolism and by association CBF, given key mechanisms that regulate cerebral perfusion are altered with exercise (Smith & Ainslie, 2017). In children and youth, various studies have linked exercise to aspects of brain development and health such as neurogenesis 19 (Chaddock et al., 2010; Meijer et al., 2020; Chaddock-Heyman et al., 2021), stimulation of neurotropic factor expression (Mora-Gonzalez et al., 2019), and improvement in cognitive function (Donnelly et al., 2016; Hsieh et al., 2020), but the immediate impact of exercise on cerebral perfusion and its regulation remains a much under-studied area. Far less is understood about the impact physical activity or sedentary behaviour may have on cerebrovascular structure and function in the developing brain and the implications for healthy brain aging into adult life. A recent meta-analysis suggests long-term physical activity positively impacts neurophysiological function in children, with improvements to executive function and attention (Meijer et al., 2020). One explanation for these improvements in post-exercise cognitive markers is an increase in post-exercise CBF; however, to date data have not supported this supposition. Pontifex et al. (2018) reported that a single bout of 20 min of aerobic exercise did not elicit an increase in post-exercise CBF and therefore concluded that the post-exercise augmentation in cognition and neural activation were unlikely to relate to changes in cerebral perfusion. Likewise, Tallon et al. (2019) (see Appendix A) show increases in MCAv at the onset of moderate-intensity steady-state exercise did not persist with continued moderate-intensity exercise or post-exercise. Recent interventional work found no impact of aerobic and cognitively demanding exercise training on brain structure or function in children (Meijer et al., 2020), but the authors concluded that the exercise prescription may not have been optimal for eliciting such improvements. It is also possible that exercise-induced changes in cerebral hemodynamics mediate other outcomes that account for post-exercise improvements in cognitive function, such as post-exercise elevations in cerebral oxygen consumption or increased arousal. 2.5.1 Acute exercise The biphasic CBF response to incremental exercise to exhaustion has been well-defined in adults. During mild- to moderate-intensity exercise (~20–60% of maximum oxygen uptake) CBF 20 increases by about 20–30%. As exercise intensity increases beyond the ventilatory threshold toward maximum, CBF declines back to baseline values (Smith & Ainslie, 2017). Studies on the impact acute exercise has upon cerebral hemodynamics in children are scarce, but extant findings show that the pattern of the response in both children and adolescents is similar to adults; with an initial rise in cerebral blood velocity with low- to moderate-intensity exercise and a decline toward baseline as exercise intensity approaches maximum (Ellis et al., 2017; Weston et al., 2021). Nonetheless, the magnitude of the increase is about half in children when compared to adolescents or adults. In a study of 13 prepubertal children and 13 sex-matched adults, the average peak increase in MCAv was 10% in the children and 20% in the adults during cycle ergometry exercise to exhaustion (Ellis et al., 2017). Similarly, Weston et al. (2021) reported a ~10–15% peak increase in MCAv in 9-year-olds during cycle ergometry exercise. A similar amplitude of approximately 25% in MCAv was noted for adolescents and adults (Weston et al., 2021). Consistent across studies, the increase in MCAv peaked by the ventilatory threshold and a significant decline toward baseline in MCAv was noted from the respiratory compensation point. Exercise exerts considerable influence on end-tidal gases, BP, cerebral metabolism, and neuronal activity, which are all regulators of CBF. Smith and Ainslie (2017) pooled CBF data from 13 different studies that had assessed CBF at varying intensities of exercise and concluded that despite changes in various regulatory factors with exercise, PETCO2 was the primary regulator of CBF during progressive exercise. Indeed, the pattern of change in cerebral blood velocity throughout progressive exercise to exhaustion in adults closely resembles the changes observed in PETCO2 (Smith & Ainslie, 2017); however, Ellis et al. (2017) demonstrated that, unlike adults, during exercise PETCO2 and MCAv were not correlated in children and the change in MCAv during exercise did not mimic the changes in PETCO2 to the same extent as in adults. A weaker relationship between PETCO2 and MCAv during exercise was also noted by Weston et al. (2021) 21 in children compared to adolescents and adults, suggesting age-dependent mechanisms regulate CBF during exercise. The interaction between VE and CBF regulation has been a topic of much debate in the adult literature, with evidence that VE exerts a direct influence on the CVR to CO2 (Ogoh et al., 2019), as well as evidence that VE contributes little to CBF or CO2 CVR (Howe et al., 2020; Carr et al., 2021). Children have a lower ventilatory sensitivity threshold for CO2 (Springer et al., 1988), with a greater VE for a given change in PETCO2 in children compared to adults at both rest and during exercise (Gratas-Delamarche et al., 1993). Ellis et al. (2017) suggest that the higher VE noted in the children up to the point of ventilatory threshold may account for the smaller increases in cerebral blood velocity. Likewise, Weston et al. (2021) note that the slope describing VE relative to CO2 production was greater in children. Further, the magnitude of the VE/CO2 production slope was negatively correlated with MCAv amplitude during exercise. These findings suggest that the immature ventilatory response to exercise is associated with the reduced MCAv during exercise in children. Conversely, the attenuated MCAv response during moderate-intensity exercise in children may be influencing the central ventilatory CO2 chemoreflex, altering ventilatory efficiency. In an attempt to elucidate the relationship between MCAv and VE in adults, Ogoh et al. (2009) manipulated PETCO2 at rest to compare the onset response of the MCAv and VE response to CO2. MCA t was tightly coupled to PETCO2 t in adults, with pulmonary VE t in lag, supporting the premise that CVR influences the central ventilatory CO2 chemoreflex. Whether there is an age dependence of the central ventilatory CO2 chemoreflex – CBF interaction is currently unknown. Future experimental work that manipulates PETCO2 is needed to fully elucidate this proposition. Incremental exercise also results in alterations in BP, with MAP rising with exercise intensity in a similar manner in children as adults up to the respiratory compensation point, when MAP was greater in adults (Ellis et al., 2017). Importantly no relationship has been found between 22 MAP and the percentage change in MCAv in children at any exercise intensity. Cerebrovascular resistance, calculated as MAP divided by MCAv, is lower in children at rest and during exercise compared to adults (Ellis et al., 2017). Given children have a higher absolute MCAv than adults, the lower cerebrovascular resistance may be a consequence of developmental differences in hemodynamic properties, such as cerebrovascular tone of the resistance vessels or the higher levels of cerebral perfusion, which means the child is operating at their vasodilatory limits when exercising. Collectively these findings suggest the mechanisms underpinning the cerebrovascular response to exercise in the child are developmentally distinct and remain unanswered. 2.5.2 Aerobic fitness and exercise training Evidence of the impact of aerobic fitness on cerebrovascular function in adults comes largely from ex-post facto studies. The relationship between MCAv and aerobic fitness was explored in healthy sedentary (n=153) and endurance-trained (n=154) men between the ages of 18 –79 years (Ainslie et al., 2008). MCAv was found to be 17% greater in the endurance-trained men across this age range (Ainslie et al., 2008). In a subsequent study, comparing trained younger and older men to sedentary peers, both the younger and older aerobically fitter men had higher resting cerebral blood velocity and improved CVR than their sedentary counterparts (Bailey et al., 2013). This beneficial impact of aerobic fitness on resting blood velocity and cerebrovascular function was subsequently shown in a mixed-sex population (Barnes et al., 2013). To date, there are no comparisons of cerebrovascular hemodynamics in trained and untrained children or youth. Exercise training studies are less common but findings indicate that 12–weeks of exercise training in ten young and ten older previously sedentary adults did not impact resting cerebral blood velocity but did improve CVR to CO2 (Murrell et al., 2013). More recent interventional work 23 in over 200 previously sedentary adults demonstrated that 6–months of aerobic exercise increases MCAv and cerebrovascular conductance during submaximal exercise (Lake et al., 2022). Again, there are, to date, no exercise training studies that explore cerebrovascular outcomes in children or adolescents. 2.5.3 Physical activity and sedentary behaviour A recent meta-analysis suggests a small positive effect of physical activity on brain structure, albeit from only four studies in the healthy child (Meijer et al., 2020). Habitual daily physical activity may cause an increase in endothelial SR, which, as discussed in Section 2.3.1.2 Duplex ultrasound, is an estimation of the frictional force of blood cells on the endothelial lining of the blood vessel (Thosar et al., 2012). An increase in SR is beneficial as it may in turn upregulate neurotrophic factors and lead to improvements in cognitive markers of brain health, such as attention. Conversely, if excessive sedentary behaviour blunts endothelial SR this may be reflected in poorer cognitive outcomes. To give further support to this contention, there is evidence that walking enhances BDNF expression in children with obesity (Mora-Gonzalez et al., 2019). There is also in vitro evidence from the culturing of endothelial cells that were exposed to low and high shear stress conditions (Prigent-Tessier et al., 2013), that exercise-induced high shear stress causes BDNF to increase by >400% (Prigent-Tessier et al., 2013). This is an enticing conjecture, but future research is needed to confirm the physical activity – sedentary behaviour – cerebrovascular SR relationships. The use of experimental models of sedentary behaviour can extend pre-existing epidemiological research showing that increasing levels of sedentary time are associated with increasing cerebrovascular risk. Sitting as a laboratory model of sedentary behaviour is highly relevant given the elevated levels of sitting noted in children (Saunders, 2014; Adamo et al., 2015). Various protocols have been utilized in adults, with different durations of sitting (e.g., 3 to 24 8 hours) and various intensities and frequencies of breaks (Taylor et al., 2022). The use of experimental models of sitting in children and adolescents are scarce. There has been one study of adolescents, which did not find any deficits in insulin, glucose or lipids following 8 hours of sitting (Saunders et al., 2013). More recent findings in healthy weight children have found individualized, moderate-intensity exercise breaks are effective in offsetting metabolic and vascular dysfunction created by an acute period of sitting for three hours (Belcher et al., 2015; McManus et al., 2015). Breaking up the three hours of sitting with three minutes of exercise at an individualized moderate-intensity every 30 minutes resulted in a 32% reduction in insulin (area under the curve) compared to continuous sitting in 7–11-year-olds (Belcher et al., 2015). Likewise, a relative decline of 33% in superficial femoral artery flow-mediated dilation (an index of vascular health) was shown following three hours of sitting in 7–10-year-old girls. This decline was prevented by taking a 10-minute moderate-intensity exercise break each hour (McManus et al., 2015). In adults, a recent systematic review, inclusive of 45 studies, concluded the effect of breaking up prolonged sitting improves cardiovascular parameters (da Silva et al., 2022). However, as highlighted by da Silva et al. (2022), the impact of breaking up prolonged sitting on the CBF varies. In young, healthy adults 2 min of walking every 30 min prevented a decrease in MCAv in comparison to uninterrupted sitting in healthy young adults (Carter et al., 2018). While, in older adults with a weight status ranging from overweight to obese (BMI of participants was ≥25 𝑘𝑔 ∙ 𝑚9: ), MCAv was maintained following 30 min of moderate-intensity exercise in the morning and with 3 min walking interruptions every 30 min adults throughout an 8 h prolonged sitting protocol (Wheeler et al., 2019). Conversely, older adults with a similar weight status as the previous study underwent either 3 h 40 min prolonged uninterrupted sitting or prolonged sitting interrupted with 30 min positional changes (i.e. 30 min standing, 30 min sitting) (Perdomo et al., 2019). Perdomo et al. (2019) found the positional interruptions provided no protective benefit to 25 MCAv, which decreased over the 3 h 40 min in a similar manner as was seen in the uninterrupted sitting protocol. Although each of these studies probed the impact of interruptions to prolonged sitting on MCAv, the findings were not consistent. While the influence of breaking up prolonged sitting on the cerebrovasculature of children has yet to be investigated, it will be imperative for future research to consider the modality, frequency, duration, and intensity of the breaks in order to maximize potential benefits with ecological validity for the child. 2.6 Summary Despite a vast literature on CBF regulation and cerebrovascular function in adults, there is very limited knowledge on the impact of age, maturation, or sex on cerebrovascular function in healthy children. Equally, relationships between sedentary behaviour, physical activity, and cerebral hemodynamics are poorly understood and the impact prolonged sitting has on the cerebrovasculature has not yet been explored in childhood. In order to address these gaps in the literature, four empirical studies are presented in the following four chapters. The first study explores the relationships between habitual sedentary behaviour, physical activity, maturation, and resting cerebral hemodynamics. The second and third studies focus on the assessment of CVR in children both in intra- and extra-cranial arteries. Specifically, these studies consider development differences in CVR and whether these be described by both steady-state and dynamic onset responses to CO2. The goal is to use these measures in the final experimental study. The final study is a randomized cross-over trial that explores the impact an acute bout of uninterrupted sitting has on cerebral perfusion, NVC and CVR in children and the potential protection afforded by interrupting sitting with exercise breaks. 26 Chapter 3: The Influence of Sex and Maturation on Carotid and Vertebral Artery Hemodynamics and Associations with Free-living Sedentary Behaviour and Physical Activity in 6–17-year-olds 3.1 Background Emerging evidence shows acute and chronic free-living physical activity of varying intensities has a positive influence on neurophysiological function in children (Meijer et al., 2020). Although the mechanisms underlying these physical activity-induced benefits are not well understood, associations between physical activity, CBF, markers of brain metabolism and brain neurotrophic factors are apparent in adults and children (Arnardottir et al., 2016; Engeroff et al., 2018; Mora-Gonzalez et al., 2019). Daily engagement in free-living physical activity is accompanied by engagement in sedentary behaviour, where sedentary behaviour is characterised by periods of time spent seated, reclining or lying, with correspondingly low levels of energy expenditure (Tremblay et al., 2017). Many children and adolescents spend up to half of their waking hours sedentary (Contardo Ayala et al., 2018). Even though there is evidence of associations between physical activity and CCA function (Haapala et al., 2017; Lima et al., 2021), the findings are mixed and the focus of prior research has largely been on CCA structure. Associations between sedentary behaviour and cerebrovascular hemodynamics have yet to be explored in children and adolescents. Habitual sedentary time has been associated with lower CBF to the lateral and medial frontal cortex, but not the medial temporal cortex in older adults (Zlatar et al., 2019). Conversely, when total sedentary time was reduced over a 16-week period, an increase in intra-cranial blood velocity of the anterior circulation was noted in older adults (Hartman et al., 2021). It is well-established that it is the manner in which sitting is accumulated that impacts health, with prolonged, uninterrupted bouts of sitting the most detrimental (Dunstan et al., 2021), including to 27 the cerebrovasculature. Evidence from the acute manipulation of sitting in adults has shown reductions in CBF velocity following three hours of uninterrupted sitting, again in the anterior cerebral circulation, with reductions that were countered by shortening the bout of prolonged sitting with activity breaks (Carter et al., 2018; Hartman et al., 2021). Although the negative impact of prolonged uninterrupted sitting on CBF in adults is becoming clearer, whether there are regional differences remains undetermined. Likewise, the mechanisms underlying sedentary-induced cerebrovascular alterations remain unknown. In this regard, there is growing interest in the potential role that shear stress plays in cerebrovascular adaptations (Carr & Ainslie, 2020). In adults, there is evidence of a shear-mediated dilation of the ICA in response to various stimuli including exercise, hypercapnia, and intermittent hypoxia (Carter et al., 2016; Hoiland et al., 2017; Iwamoto et al., 2018; Smith et al., 2019; Carr et al., 2020). It is possible that the noted reductions in anterior CBF with excessive sitting (Carter et al., 2018; Zlatar et al., 2019; Hartman et al., 2021) result in a concomitant reduction in arterial wall shear-stress, but this has yet to be described. Any exploration of the relationships between habitual sedentary patterns and cerebrovascular function in childhood and adolescence requires equal consideration of the changes in these parameters that might occur with normal development. Therefore, the primary aim of this study was to examine the influence of sex and maturation on resting carotid (both CCA and ICA) and VA hemodynamics, habitual physical activity and sedentary behaviour, and explore the associations between carotid and VA hemodynamics, physical activity and sedentary behaviour in children and adolescents 6-17 years of age. We had three specific hypotheses, including: (i) the diameter of the CCA, ICA, and VA will all increase with maturation, with boys having larger vessels than girls; (ii) sedentary time and the time spent in uninterrupted bouts of sitting of longer durations, will increase with maturation, while steps per day will decline with maturation, with no differences by sex when participants are aligned by maturation; and (iii) the 28 time spent in uninterrupted bouts of sitting of longer durations, but not sedentary time, will be associated with reduced flow (Q) and SR in the CCA, ICA, and VA and reduced gCBF. 3.2 Methods 3.2.1 Study design Experimental procedures and protocols were approved by the University of British Columbia Clinical Research Ethics Board (H16-01281 & H17-00570). Written informed consent was obtained from parents of participants, written and oral informed assent was obtained from participants. Children and adolescents (6 to 17 years) were recruited through local school and community groups and were eligible to participate if they did not have any medical condition that would influence CBF or limit physical activity. Parents reported their child’s sex assigned at birth. Participants (n=88; 42 girls) were tested on one occasion and asked to fast >1 hour prior to arrival (8 AM to 2 PM). Following anthropometric assessment, participants rested quietly while seated for 5 min and had heart rate (HR) and BP assessed. Following 5 min of supine rest, duplex ultrasound assessment of blood vessel diameter and blood velocity of the CCA, ICA, VA was completed. At the end of the visit participants were fitted with an accelerometer for seven days of continuous wear and instructed to participate in all usual activities. 3.2.2 Measures 3.2.2.1 Anthropometrics and maturation Body mass was measured in light clothing, barefoot to the nearest 0.1 kg with an electronic scale (Tanita; Tanita Corp, Arlington Heights, IL). Stature and seated height were measured barefoot to the nearest 0.1 cm with a stadiometer (Seca Portable; Seca, Hamburg, Germany). BMI was calculated and weight status classified in an age and sex specific manner using the 29 World Health Organization (WHO) growth standards for children 5 to 19 years (de Onis et al., 2007). Maturation was assessed from predicted age at peak height velocity (aPHV) offset, using the Mirwald equation (Mirwald et al., 2002). Predicted aPHV estimates the maturity offset, either the time before, at or after peak height velocity from somatic measures. A negative offset negative value (£ -1.0) indicates the participant has yet to reach aPHV; a score > -1.0 but < 1.0 indicates the participant is at aPHV i.e., within the year that aPHV occurs, and a positive offset value (³ 1.0), means the participant has already passed aPHV. In this study, participants were categorised as pre-PHV (offset score £ -1.0) or peri-PHV (offset score > -1.0) (Malina, 2017). HR was assessed using a three-lead electrocardiogram and BP using an automated cuff (Tango+; SunTech, Morrisville, NC). MAP was subsequently calculated as [(:;·diastolic pressure) + (<;·systolic pressure)] (Gauer, 1960). 3.2.2.2 Cerebrovascular measures Blood velocity and vessel diameter of the cervical arteries were measured on the right side using a 15-MHz multi-frequency array vascular ultrasound (Terason T3200, Teratech, Burlington, MA). B-mode imaging was used to measure arterial diameter, while pulse-wave mode was used to simultaneously measure the peak envelope velocity of blood through the vessel. Technical recommendations were followed for vessel recording and offline analysis (Woodman et al., 2001; Thomas et al., 2015). Synchronized diameter and velocity recordings allowed calculation of Q and SR with the following formulas, respectively. Equation 1. Calculation of volumetric cerebral blood flow 𝑄 (𝑚𝑙.𝑚𝑖𝑛9<) = 𝑝𝑒𝑎𝑘 𝑒𝑛𝑣𝑒𝑙𝑜𝑝𝑒 𝑣𝑒𝑙𝑜𝑐𝑖𝑡𝑦2 ∗ [𝜋(0.5 ∗ 𝑑𝑖𝑎𝑚𝑒𝑡𝑒𝑟):] Equation 2. Calculation of shear rate 𝑆𝑅 (𝑠9< ) = (4 ∗ 𝑉𝑒𝑙𝑜𝑐𝑖𝑡𝑦𝐷𝑖𝑎𝑚𝑒𝑡𝑒𝑟 ) 30 Subsequently, QICA and QVA were used to estimate gCBF as two times the sum of QICA and QVA. 3.2.2.3 Accelerometry The activPAL micro-accelerometer (PAL Technologies Limited; Glasgow, Scotland, UK) was used for an objective assessment of physical activity and sedentary behaviour. Leg-worn devices are the gold standard for the assessment of sedentary behaviour, and the activPAL has been validated for step-based activity and posture in children (Aminian & Hinckson, 2012; Ridley et al., 2016). Participants wore the device on the anterior aspect of the right thigh, placed within a flexible nitrile sleeve and attached using Tegaderm Transparent Film (3M Health Care; St. Paul, MN, USA). Participants were asked to wear the device continuously for seven consecutive days; no issues were reported (e.g., skin irritation). ActivPAL data inclusion criteria included: (i) 24 hours of wear time per day, and (ii) ≥3 weekdays and ≥1 weekend days (Trost et al., 2000). A sampling frequency of 20 Hz was used and data were interpolated in 2 second bins. Waking time was defined as the duration of time between the first steps or standing in the morning and the cessation of steps or standing in the evening. Daily StepCount and SedTime averages were calculated using a 7-day weighted (5:2 weekday to weekend day) average and inflating individual data that was less than 5 weekdays or 2 weekend days using the individual means. To assess the pattern of sedentary behaviour, bouts of uninterrupted sitting were categorized by duration as: (i) uninterrupted bouts lasting less than 30 mins (Bout<0.5); (ii) uninterrupted bouts lasting 30 minutes to 1 hour (Bout0.5-1); (iii) uninterrupted bouts lasting one to two hours (Bout1-2); (iv) uninterrupted bouts lasting more than two hours (Bout>2). The total time spent in each of these bout categories was summed across the week to provide a 7-day aggregate. Tertiles were created for StepCount, SedTime, Bout<0.5, and Bout0.5-1. For the longer bout categories (Bout1-2 and Bout>2), not all participants had time spent in these bouts. Therefore, three groups were created by taking those 31 with 0 time as group I; then using a split plot of the remaining participants to create two remaining groups. Table 1 included the boundaries for all groups. Table 1. Boundaries defining groups of daily average and 7-day aggregate physical activity and sedentary behaviour variables. Group I Group II Group III Girls n Boys n Total n Boundary Girls n Boys n Total n Boundary Girls n Boys n Total n Boundary StepCount (steps/day) 11 15 26 ³ 12727 13 13 26 9982 – 12726 18 8 26 £ 9981 SedTime (min/day) 11 15 26 £ 452.14 16 10 26 452.15 – 534.26 15 11 26 ³ 534.27 Bout<0.5 (h/week) 13 13 26 £ 39.66 12 14 26 39.67 – 44.48 17 9 26 ³ 44.49 Bout0.5-1 (h/week) 12 14 26 £ 6.56 16 10 26 6.57 – 13.48 14 12 26 ³ 13.49 Bout1-2 (h/week) 9 7 16 = 0 18 13 31 1.00 – 5.07 15 16 31 ³ 5.08 Bout>2 (h/week) 30 28 58 = 0 7 3 10 2.00 – 4.36 5 5 10 ³ 4.37 Abbreviations: StepCount, average steps per day; SedTime, average minutes per day spent sedentary; Bout<0.5, sum of uninterrupted bouts lasting less than 30mins in a week; Bout0.5-1, sum of uninterrupted bouts lasting 30 minutes to 1 hour in a week; Bout1-2, sum of uninterrupted bouts lasting one to two hours in a week; Bout>2, sum of uninterrupted bouts lasting more than two hours in a week. 3.2.3 Statistical analysis We present descriptive statistics as means and standard deviations. Two-way ANOVAs were used to compare measures of resting cervical artery hemodynamics (v, diameter, SR, Q, and gCBF); physical activity (StepCount); sedentary time (SedTime); and patterns of sedentary behaviour (Bout<0.5, Bout0.5-1, Bout1-2, and Bout>2) by sex and maturation. Analysis of covariance (ANCOVA) was used to examine associations between arterial outcomes, StepCount (controlling for SedTime) and sedentary behaviour parameters (controlling for StepCount). Covariates included maturation and/or sex and were informed by the initial ANOVA analyses. Bonferroni post-hoc comparisons of estimated means were used to deconstruct the main effects. Statistical significance was set a priori at p<.05 and all analyses were performed using SPSS (Version 27, SPSS; Chicago, IL). 32 3.3 Results Ten participants were excluded because of insufficient number of days of activPAL data (i.e. either <3 weekdays and/or 0 weekend days). Of the seventy-eight participants (42 girls) with activPAL data, 79% wore the device for at least six days, 20% for five days and 1% for four days. The girls and boys were similar in age (girls: 11.4 ± 2.5 years; boys: 10.9 ± 2.5 years, p=0.410), stature (girls: 1.48 ± .14 m; boys: 1.49 ± .17 m, p=0.928), and mass (girls: 42.9 ± 14.3 kg; boys: 41.8 ± 15.4 kg, p=0.720). However, the girls were more mature than the boys (-0.5 ± 2.1 vs. -2.5 ± 2.0 years offset aPHV, p<0.001). The BMI was similar between girls and boys (19.0 ± 3.9 vs. 18.2 ± 3.7 kg·m-2, p=0.363), with eleven participants (6 boys) classified as thinness grade 1; 53 participants (23 boys) were classified as being healthy weight; eleven participants (6 boys) were classified as being over-weight; and three participants (1 boy) were classified as being obese. Resting cardiovascular assessment was not completed on five children. Therefore, assessment was completed on 39 girls and 34 boys, 41 of whom were pre-PHV and 32 peri-PHV. Resting HR was higher in girls than boys (83 ± 12 vs. 78 ± 10 bpm, respectively; p=0.009), and higher in pre-PHV children (82 ± 12 bpm) than peri-PHV children (79 ± 11 bpm; p=0.037). Systolic BP was similar in the girls and the boys (112 ± 12 vs. 107 ± 8 mmHg, respectively; p=0.100) and did not differ between pre-PHV and peri-PHV groups (112 ± 12 vs. 107 ± 8 mmHg, respectively; p=0.121). Girls and boys had similar diastolic BP (64 ± 9 vs. 65 ± 8 mmHg, p=0.317), however, the pre-PHV children had lower diastolic BP (61 ± 9 mmHg) than their peri-PHV peers (68 ± 7 mmHg; p=0.001). A sex by maturation interaction was significant (p=0.009). Follow-up analyses revealed, pre-PHV girls had significantly lower diastolic BP (57 ± 8 mmHg) than peri-PHV girls (69 ± 7 mmHg; p<0.001). Mean arterial BP was similar between girls and boys (80 ± 8 vs. 79 ± 6 mmHg, respectively; p=0.634) and higher in the peri-PHV children (83 ± 6 mmHg) compared to 33 their pre-PHV peers (77 ± 6 mmHg; p<0.001). A sex by maturation interaction was significant (p=0.001), with follow-up analyses revealing, pre-PHV girls had significantly lower mean arterial BP (73 ± 4 mmHg) than peri-PHV girls (84 ± 6 mmHg; p<0.001). The relationship of sex and maturation on resting carotid and VA parameters are provided in Table 2. The ANOVA analyses indicated main effects of puberty for CCAd, but not for ICAd or VAd; however, all three cervical arteries were significantly larger in boys than girls. ICAv, ICASR, VAv, and VASR were all significantly higher in pre-PHV compared to peri-PHV participants. The QCCA and QICA were higher in boys than girls. A similar gCBF was found pre-PHV and peri-PHV children (see Table 2), but gCBF was significant higher in boys compared to girls (p=0.013). Table 2. Carotid and vertebral artery diameter and hemodynamic parameters by sex and maturation. ANOVA main effects (P-value) n Girls n Boys n Pre-PHV n Peri-PHV Sex Maturation Sex ´ maturation CCAd (mm) 42 5.87 ± .46 35 6.18 ± .46 45 5.90 ± .50 32 6.16 ± .43 0.001 0.001 0.685 CCAv (cm·s-1) 42 48.1 ± 7.5 35 48.8 ± 9.4 45 50.4 ± 8.8 32 45.6 ± 6.9 0.778 0.025 0.422 CCASR (s-1) 42 328.2 ± 68.5 35 318.7 ± 80.0 45 344.8 ± 81.1 32 294.6 ± 49.5 0.139 0.002 0.393 QCCA (ml·min-1) 42 400.5 ± 68.9 35 451.3 ± 68.5 45 425.1 ± 64.1 32 421.4 ± 84.7 0.002 0.334 0.783 ICAd (mm) 36 4.73 ± .62 28 5.15 ± .53 38 4.90 ± .67 26 4.93 ± .54 0.009 0.345 0.420 ICAv (cm·s-1) 36 49.9 ± 8.7 28 53.0 ± 8.2 38 54.2 ± 7.5 26 47.0 ± 8.2 0.812 0.002 0.772 ICASR (s-1) 36 429.1 ± 96.5 28 417.1 ± 88.6 38 450.9 ± 95.2 26 384.4 ± 74.0 0.143 0.003 0.729 QICA (ml·min-1) 36 269.6 ± 77.2 28 337.8 ± 78.6 38 314.6 ± 88.7 26 276.8 ± 73.6 0.018 0.274 0.235 VAd (mm) 41 3.57 ± .39 33 3.76 ± .37 42 3.62 ± .36 32 3.70 ± .42 0.015 0.117 0.883 VAv (cm·s-1) 41 27.7 ± 5.3 33 27.6 ± 7.7 42 28.9 ± 7.4 32 26.1 ± 4.6 0.457 0.045 0.522 VASR (s-1) 41 310.6 ± 59.6 33 282.6 ± 64.6 42 309.8 ± 68.6 32 282.8 ± 52.0 0.011 0.012 0.880 QVA (ml·min-1) 41 86.3 ± 27.6 33 100.8 ± 58.4 42 96.9 ± 53.4 32 87.4 ± 28.3 0.327 0.500 0.455 gCBF (ml·min-1) 36 709.0 ± 175.8 26 882.5 ± 193.6 36 820.9 ± 214.5 26 727.6 ± 171.1 0.013 0.203 0.122 Abbreviations: CCA, common carotid artery; ICA, internal carotid artery; VA, vertebral artery; d, diameter; v, velocity; SR, shear rate; Q, volumetric blood flow; gCBF, global cerebral blood flow; PHV, peak height velocity. Bold indicates significance. Average daily physical activity and sedentary behaviour, as well as the 7-day aggregate for prolonged sedentary bouts are summarized in Table 3. StepCount was lower in peri-PHV participants, who took approximately 4000 fewer steps per day than pre-PHV participants. SedTime was significantly higher in the peri-PHV group, who spent about 100 min per day more sedentary than the pre-PHV group. All participants engaged in uninterrupted SedTime bouts 34 lasting less than 30 minutes (Bout<0.5) and in at least one uninterrupted bout lasting 30 minutes to one hour (Bout0.5-1). Sixteen participants did not engage in a single Bout1-2 and 58 participants did not engage in a single Bout>2. Peri-PHV participants spent more time in Bout0.5-1 and Bout1-2 than their pre-PHV counterparts. No main effect of maturation was apparent for Bout>2. Sex differences were only apparent in Bout1-2, where boys spent approximately 1.5 hours more than girls. Table 3. Physical activity and sedentary behaviour by sex and maturation. ANOVA main effects (P-value) n Girls n Boys n Pre-PHV n Peri-PHV Sex Maturation Sex ´ maturation Averaged daily activity and sedentary behaviour StepCount (steps/day) 42 10842 ± 2404 36 12729 ± 3842 45 13174 ± 3224 33 9720 ± 2078 0.280 0.001 0.504 SedTime (min/day) 42 501.4 ± 81.0 36 496.6 ± 96.5 45 460.0 ± 75.2 33 552.6 ± 75.6 0.095 0.001 0.448 7-day aggregate of sedentary bouts Bout<0.5 (h/week) 42 42.5 ± 7.0 36 41.5 ± 6.1 45 42.2 ± 6.0 33 41.9 ± 7.3 0.652 0.872 0.158 Bout0.5-1 (h/week) 42 10.4 ± 4.8 36 9.7 ± 5.3 45 7.6 ± 4.6 33 13.3 ± 3.4 0.271 0.001 0.537 Bout1-2 (h/week) 33 5.4 ± 3.3 29 7.0 ± 6.0 32 5.1 ± 4.1 30 7.3 ± 5.2 0.034 0.011 0.372 Bout>2 (h/week) 12 4.4 ± 2.5 8 4.7 ± 2.1 6 4.1 ± 1.8 14 4.7 ± 2.5 0.380 0.339 0.521 Abbreviations: StepCount, average steps per day; SedTime, average minutes per day spent sedentary; Bout<0.5, weekly sum of time spent in uninterrupted bouts lasting less than 30mins in a week; Bout0.5-1, weekly sum of time spent in uninterrupted bouts lasting 30 minutes to 1 hour; Bout1-2, weekly sum of time spent in uninterrupted bouts lasting one to two hours; Bout>2, weekly sum of time spent in uninterrupted bouts lasting more than two hours. Associations between hemodynamic parameters of the carotid and vertebral arteries, as well as gCBF, daily averaged physical activity and sedentary behaviour, including 7-day aggregate of time spent in uninterrupted sedentary bouts were examined using ANCOVA. Results revealed no significant associations with any of the hemodynamic parameters of the carotid and vertebral arteries or gCBF and prolonged sedentary bouts. Analysis of ICASR by SedTime tertiles, covarying for maturation and StepCount, revealed a significant main effect for SedTime (p=0.016; see Figure 5). Those with the least SedTime had significantly higher ICASR (473.7 SE 19.5 s-1; CI: 434.6 – 512.8) than those with moderate SedTime (401.1 SE 17.5 s-1; CI: 366.2 – 436.1, p=0.028) or high SedTime (389.8 SE 20.8 s-1; CI 348.2 – 431.5, p=0.030). No associations were found between any of the cervical hemodynamic parameters or gCBF and StepCount. Of note, CCASR by StepCount tertiles, covarying for SedTime and maturation, did not reach the threshold for 35 significance (p=0.055). Group I, who had the highest average daily steps, had a mean CCASR of 353.0 s-1 (CI: 324.5 – 381.6 s-1), compared to those in Group III with a mean CCASR of 300.1 s-1 (CI: 270.586 – 329.526; p=0.06); however, this was not significantly different. Figure 5. The relationship between average time spent sedentary per day and internal carotid artery shear rate at rest, covarying for maturation and the average number of steps taken per day. Group I (n = 23) engaged in the lowest SedTime. Group II (n = 22) engaged in a moderate amount of SedTime. Group III (n = 19) engaged in the highest SedTime. Closed circle represents the mean adjusted for covariates. The error bars indicate the lower and upper 95th confidence intervals.*P<0.05 3.4 Discussion We explored the influence of sex and maturation on cervical artery hemodynamics (CCA, ICA, and VA), free-living physical activity and sedentary behaviour participation and the relationship between these in children and adolescents 6-17 years of age. Contrary to our hypothesis we found similar ICAd and VAd between pre-PHV and peri-PHV groups, although we I II III300350400450500550SedTime (min/day)ICA SR (s-1)✱✱ 36 did find a significantly larger CCAd in the peri-PHV group. Of note, boys had larger diameters in all three arteries. In support of our secondary hypothesis, free-living sedentary behaviour increased while StepCount decreased with maturation; with peri-PHV participants accumulating 100 min per day more sedentary behaviour, and taking approximately 3500 fewer steps per day than the pre-PHV participants. We did not find any relationships between Q and SR of the cervical arteries and StepCount or prolonged bouts of sedentary behaviour; however, we did observe an association between ICASR and SedTime, after covarying for StepCount and maturation. 3.4.1 Age, maturation and cerebrovascular development We have shown that CCAd increases with maturation and in a sex dependent manner, with larger CCAd in boys compared to girls. These findings are similar to previous work noting increases in CCAd with age (Ishizu et al., 2004; Semmler et al., 2021), and larger diameters in boys up to 14-15 years of age (Semmler et al., 2021). The relationship between chronological age, global, and regional CBF has been assessed using perfusion MRI in a large cross-sectional cohort of 1098 children (Vandekar et al., 2019). Boys had greater gCBF than girls through childhood to adolescence, with higher levels of perfusion in boys in the frontal brain region, but similar perfusion in boys and girls in the posterior region (Vandekar et al., 2019). Our findings complement these regional differences where we report higher gCBF, QCCA and QICA in boys, whereas QVA, supplying the posterior region, did not differ by sex. There is scant information on the change in sedentary patterns across childhood and adolescence, with the only longitudinal study categorizing bouts of uninterrupted sitting of just short duration (>5, >10, >20 min) (Contardo Ayala et al., 2018). We show an increase in bout duration >20 min with increasing age, alongside a decline in breaks from sitting. Decreasing time spent being physically active has been documented in both boys and girls in adolescence, with the rate of decline steeper in girls leading to an increasingly larger gap between the boys and girls 37 (Cairney et al., 2014). However, when boys and girls are aligned by maturation these difference are no longer apparent (Sherar et al., 2010). Developmental data on the cervical arteries in healthy children and adolescents are also sparse. Increases in CCAd have been shown with age (Ishizu et al., 2004; Semmler et al., 2021), and there is evidence of larger CCAd in boys compared to girls (Semmler et al., 2021). A substantial increase in the ICAd with age has been reported in children, with larger ICAd in 10-19 year old youth compared to 4-9 year old children (Seong et al., 2005). In contrast, Morris et al. (2017) found girls (9.9 ± 1.7 years) and women (43.9 ± 3.5 years) had similar sized ICAd and VAd. Global CBF also increases with age up until about 8-10 years, then decreases through adolescence to adult values (Wu et al., 2016). Evidence of an association between maturation and CBF is limited. In a study of over 900 pubertal youngsters, maturational differences in CBF, indexed by arterial spin labeling MRI were noted (Satterthwaite et al., 2014). Notably, when adolescents are categorised by maturation rather than by chronological age, the decline in gCBF remained in early puberty in both males and females, but by mid puberty a decline in gCBF was only apparent in males, with gCBF actually increasing in females (Satterthwaite et al., 2014). These results highlight markedly differing developmental patterns of gCBF between males and females and underpin the importance of accounting for maturation and sex. With these findings in mind, it was surprising we found no differences in QCCA, QICA, and QVA with increasing maturation, however, this may relate to differences in the assessment of maturation. In the aforementioned study of 900 youngsters (Satterthwaite et al., 2014), maturational groups were created from self-reported Tanner stages (Marshall & Tanner, 1969; Marshall & Tanner, 1970). Tanner stage 1, 2, and 3 were collapsed together as ‘early pubertal’, Tanner stage 4 was ‘mid-pubertal’, and Tanner stage 5 was ‘post-pubertal’. Tanner staging uses the appearance of secondary sexual characteristics (i.e., lack or presence of pubic hair, breasts, or male genitalia growth) (Marshall & Tanner, 1969; Marshall & Tanner, 1970), whereas our measure, predicted aPHV, is a somatic measure of maturation and 38 aPHV aligns to Tanner staging in a sex differentiated manner (Malina, 2017). Pre-puberty is usually defined as Tanner stage 1, where there is an absence of secondary sexual characteristics, so collapsing Tanner stages 1 to 3, combined with self-report, which is known to lead to over-estimation in boys and under-estimation in girls (Rasmussen et al., 2015) may limit our understanding of the relationship between pubertal stage and CBF. Moreover, a predicted aPHV offset score less than -1 does not ensure pre-pubertal status either (Malina, 2017). Only longitudinal work with multiple metrics, including hormonal measures will provide a more thorough understanding of how maturation relates to the development of the cerebral vasculature. 3.4.2 Age, maturation, physical activity and sedentary behaviour There is limited information on changes to sedentary behaviour patterns and total time sedentary across childhood and adolescence. To the best of our knowledge, the only longitudinal study that included uninterrupted bouts of sitting found an increase in bout duration >20 min with increasing age (Contardo Ayala et al., 2018). Although our data are cross-sectional, our findings build upon this previous research categorizing bouts of sedentary behaviour of longer durations and considering the influence of maturation. We found no differences between pre-PHV and peri-PHV children in the quantity of time each group engaged in short uninterrupted sedentary bouts (those <30 min); however, pubertal children spent significantly more time in longer uninterrupted sedentary bouts lasting 30-60 min and 60-120 min duration. A recent systematic review highlights the complexity of studying maturational timing, the age at which children enter puberty, potential relationships with engagement in physical activity and sedentary behaviour (Moore et al., 2020a). There is a lack of agreement on if/how maturational timing relates to habitual physical activity, but a moderate agreement for an association between early maturation and increased sedentary behaviour. Whilst assessing maturational timing is beyond the scope of this present study, we did find that in comparison to the pre-PHV group, the peri-PHV group sat for an additional 6 h/week in uninterrupted sedentary bouts lasting 30 – 60 min in duration, as well as sitting for an additional 39 2 h/week in uninterrupted bouts lasting 60 – 90 min. Uninterrupted sedentary bouts of three hours or more have been linked to decrements in flow-mediated dilation of the superficial femoral artery in girls (McManus et al., 2015) and higher post-prandial glucose in adolescents (Fletcher et al., 2018). Although the majority of youngsters in our study only engaged in shorter periods of uninterrupted sitting, we did find that exceeding 452 min of total sedentary behaviour per day was predictive of a lower ICASR, after controlling for maturation and physical activity. While the implications of a sedentary behaviour induced decrease in ICASR on long-term cerebrovascular function are beyond the scope of the present study, it seems reasonable to speculate that if excessive sedentary behaviour persists over time, the lower shear stress will decrease the availability of nitric oxide and increase the production of vasoconstrictors (i.e. endothelin 1) (Thosar et al., 2012). 3.4.3 Potential mechanistic pathway The role intra-arterial shear stress plays in the regulation of conduit artery endothelial-dependent vasoreactivity is well-established in adults (Kooijman et al., 2008; Green et al., 2017). Recently, increases in QVA and QICA have been shown during a bout of moderate-intensity exercise, which induced increases of ~15% and 20% in VASR and ICASR, respectively (Smith et al., 2019). It is interesting to note that these relative changes in SR in response to moderate-intensity exercise are similar in magnitude to the decrease in ICASR seen in the participants in this study with moderate (Group II ~18%) and high (Group III ~22%) levels of sedentary behaviour. Positive associations have also been observed between habitual physical activity (assessed from total accelerometer counts) and perfusion in lateral and medial frontal brain regions (supplementary motor area, superior medial gyrus, left inferior frontal gyrus, left precentral gyrus and left/right superior medial gyrus), and it was concluded that cerebral perfusion was more sensitive to total physical activity, than to specific intensities derived from accelerometer cut-points (Zlatar et al., 2019). It is plausible habitual daily physical activity mediates shear-rate- 40 induced upregulation of atheroprotective vasodilators and neurotrophic factors, whereas excessive sedentary behaviour blunts these. To investigate this speculation, cultured endothelial cells were exposed to low and high shear stress conditions using hypertension and exercise. Within the exercise-induced high shear stress condition there was a >400% increase in brain-derived neurotrophic factor (BDNF) (Prigent-Tessier et al., 2013). Research also indicates an association between time spent active, specifically walking at a slow to medium cadence, and BDNF expression in obese children (Mora-Gonzalez et al., 2019). In contrast, (Arvidsson et al., 2018) reported no relationship between physical activity and BDNF; however, this study only considered moderate-to-vigorous and vigorous intensity physical activity (Arvidsson et al., 2018). Additionally, following a 22-week exercise intervention, which included 4 sessions/week of either aerobic, resistance, or combined aerobic and resistance exercise in overweight and obese adolescents, serum BDNF levels remained similar to baseline levels and did not differ from the control group (Goldfield et al., 2018). In line with the previous discussion, it is possible brain neurotrophic factors are more sensitive to total physical activity, which comprises mostly light intensity physical activity in children and adolescents (Júdice et al., 2020). It is worth noting that although we did not find a significant association (p=0.055), between CCASR and physical activity, we were likely underpowered to detect a significant association. Previous studies have not assessed CCASR, but findings suggest sedentary behaviour is not related to other markers of CCA function (Haapala et al., 2017; Gomez-Garcia et al., 2021). Additionally, associations between CCA hemodynamics and physical activity are inconsistent. An association between cumulative time spent in physical activity and markers of CCA hemodynamics has been found (Haapala et al., 2017; Lima et al., 2021); equally others found no relationships between physical activity and CCA function, only structure (Gomez-Garcia et al., 2021). It is possible that these inconsistent findings reflect the differing arterial functional measures used, and/or differences in the physical activity assessment. Future intervention studies 41 that manipulate physical activity of specific intensities over time and relate this to cerebrovascular SR and brain neurotrophic factors will help to determine the optimal intensity of physical activity for SR modifications and the link between SR and brain neurotrophic factors. 3.4.4 Limitations While this study is strengthened by the large sample size and the quantitative assessment of cervical hemodynamics, it is important to acknowledge this study is not without some limitations that need to be discussed. First, this is an association study and we cannot infer causation; however, we believe these preliminary data are novel and support the need for future longitudinal and experimental trials. Additionally, we did not control for differences in aerobic fitness, which may be important given the association between aerobic fitness and cerebrovascular function noted in adults (Smith et al., 2021). Although the activPAL device has excellent validity for postural positions, it is less accurate in the differentiation of different stepping intensities, which may have led to over- or under-reporting of participant StepCount (Aminian & Hinckson, 2012). We did not take vascular measures in the fasted state, although we did ask participants to avoid foods that could influence vascular function and not to eat a large meal >1 hour prior to measurement. Last, menarche was not assessed and we did not control for medication use, such as oral contraception. We acknowledge this is a limitation given group III likely had menarchal girls (Rosen, 2004). There is evidence that ICA shear mediated dilation increases from the low to the high estradiol phase of the menstrual cycle (Iwamoto et al., 2021), therefore changes in estradiol across the normal monthly cycle in the females may have also influenced ICA hemodynamics. 3.4.5 Summary This study adds to a sparse body of literature investigating associations between physical activity, sedentary behaviour, and cerebrovascular hemodynamics in healthy children and adolescents. We found CCA, ICA, and VA hemodynamics to be related to sex and maturation, 42 whereas engagement in free-living physical activity and sedentary behaviour was related to maturation but not sex. Importantly we found an association between SedTime and ICASR. Establishing the mechanistic pathways that link sedentary behaviour with vasoreactivity of the cerebrovasculature during the developmental years should be a future priority and could help inform future public health guidelines related to sedentary behaviours, separate from physical activity and exercise. 43 Chapter 4: The Influence of Age and Sex on Cerebrovascular Reactivity and Ventilatory Response to Hypercapnia in Children and Adults 4.1 Background The PaCO2 plays the primary role in the regulation of CBF during wakefulness (Hoiland et al., 2019). It is well known that elevations or reductions in PaCO2 result in vasodilation or constriction, respectively, of the entire cerebrovascular tree from the extra- and intra-cranial arteries, to the pial vessels [reviewed extensively here (Willie et al., 2014)]. This vasomotor mechanism is termed CVR and provides a marker of the dynamic regulation of CBF and cerebrovascular reserve capacity (Fierstra et al., 2013; Willie et al., 2014). The extensive neuronal development that occurs during childhood is reflected in a cerebral metabolic demand that is about twice that of adults (Vandekar et al., 2019). Meeting this metabolic demand requires tight regulation of CBF. Although CVR has been extensively documented in adults [reviewed in: (Hoiland et al., 2019)], far less is known about this response in healthy children and adolescents (Brouwers et al., 1990; Leung et al., 2016). There is, however, emerging evidence that age, sex, and maturity may impact CBF during childhood and adolescence. Developmental trajectories reported from a large-scale (n=922) study of 8–22-year-olds reveal that resting cerebral perfusion (assessed from arterial spin labeling MRI) peaks between the ages of 8 to 10 years, with values approximately 30% higher than adults; these CBF elevations are commensurate with the higher cerebral metabolic needs of this age group (Satterthwaite et al., 2014). Resting CBF declines from early to late puberty in boys; however, in girls, declines are only evident in early puberty, with increases in CBF mid to late puberty (Vandekar et al., 2019). When intra-cranial blood velocity of the anterior and posterior cerebral circulation was compared between girls and boys (4-8 years), middle and basilar cerebral artery velocities were higher in the girls compared to the boys (Tontisirin et al., 2007). In contrast, cerebral autoregulation, 44 indexed from changes in cerebral blood velocity in response to changes in BP, did not differ by sex (Tontisirin et al., 2007). Sex differences have also been noted in women compared to men, with higher cerebral blood velocities reported in women (Vriens et al., 1989; Marinoni et al., 1998). Leung et al. (2016) have reported the development of grey and white matter CVR in a group (n=34) between 9 to 30 years of age. Here, CVR was lowest in the youngest children, with increases of ~33% and 50% in grey and white matter CVR respectively between the ages of 9 to 15 years. These differences declined with age and, in comparison to young adults, children had grey and white matter CVR values ~20% and 30% lower, respectively. Higher levels of resting cerebral perfusion noted in the younger child may limit the capacity for further vasodilation, as such a lower cerebrovascular reserve, and may account for the blunted CVR observed by Leung et al. (2016). Higher levels of resting cerebral blood velocity have been observed in girls compared to boys (Tontisirin et al., 2007). However, whether there are sex differences in CVR in the healthy child is currently unknown. It is also possible that the blunted CVR of children compared to adults may relate to a heightened hypercapnic ventilatory response (HCVR; the change in VE in response to hypercapnia) that has been reported in children (Gratas-Delamarche et al., 1993; Marcus et al., 1994). It is thought that the elevated ventilatory sensitivity is due to the activation of the central chemoreflex increasing the drive to breathe in order to ‘blow off’ the CO2 [reviewed in (Ainslie & Duffin, 2009)]. In adults, there is some evidence that a blunted CVR is reflected in elevations in the ventilatory sensitivity to CO2 (Xie et al., 2006); however, this is not a universal finding (Hoiland et al., 2015). Onset, or dynamic responses, to hypercapnia have also been used to interrogate the integration of cerebrovascular and ventilatory responses to hypercapnia. At least in adults, close coupling of MCAv and PaCO2 onset responses, in comparison to a slower onset in VE, may infer CVR to CO2 modulates the central ventilatory chemoreflex (Ogoh et al., 2008; Ainslie & Duffin, 2009). 45 The integrated CBF and ventilatory response to changes in PETCO2 has yet to be defined in children and has implications for understanding the control of VE and CBF during development. If an interaction exists between the chemoreceptor regulation of breathing and CBF, changes in response to hypercapnia would be anticipated to be developmentally-dependent. Therefore, the purpose of this study was to compare intra-cranial CVR (indexed from the MCAv) between children and adults and explore the dynamic response of MCAv, VE and PETCO2 by characterizing the kinetic onset responses to hypercapnia. Our primary hypotheses were (i) in response to hypercapnia, a blunted CVR in children would be reflective of an increased HCVR CO2 when compared to adults; (ii) the dynamic response of VE to an increase in hypercapnia would be faster in children compared to adults, whereas the dynamic response of the MCAv response to hypercapnia would be slower in children compared to adults; and (iii) females will have greater baseline MCAv than males in both children and adults. 4.2 Methods 4.2.1 Ethical approval All experimental procedures and the protocols were approved by the University of British Columbia Clinical Research Ethics Board (H16-01281) and the study conformed to the standards set by the Declaration of Helsinki, except for registration in a database. Written informed consent was obtained from the adults and the parents of the children. Additionally, written and oral informed assent was obtained from each child. 4.2.2 Study design Twenty–four children (13 females, 11 males; aged 8.3 to 10.8 years) and 26 young adults (14 females, 12 males; aged 20.8 to 27.8 years) participated in this experimental study. Adult participants were recruited from the University of British Columbia Okanagan and children were recruited from a local elementary school. 46 Following baseline screening, participants visited the laboratory on one occasion. Per recommendations (Ainslie & Duffin, 2009), participants were asked to refrain from eating high fat foods, consuming caffeine or alcohol, or exercising strenuously 24 hours prior to testing. Additionally, room temperature and time of day were held constant for all participants, and no visual stimulation was allowed during the protocol. Upon arrival, anthropometric measures were completed and the participants were instrumented. After instrumentation, the protocol consisted of a 10-minute supine rest period breathing room air, and four-minutes of hypercapnia in the same supine position. Prior work in adults has demonstrated a steady-state response to hypercapnia using a fixed CO2 concentration is achieved between 2 to 3 minutes (Fisher, 2016), therefore we chose a fixed concentration of 6% inspired CO2 (FICO2) over 4 minutes to quantify the responses of MCAv and VE to hypercapnia in children and adults. During hypercapnia, 6% CO2 was administered in 21% oxygen (balance nitrogen). A 3-way Hans Rudolph valve allowed inspiratory gases to be switched from room air to the 6% CO2 mixture (using a 20L Douglas bag). Throughout the protocol MCAv, PETCO2, end-tidal O2 (PETO2), HR, BP, VE and its components tidal volume (VT) and respiratory rate (RR) were assessed continuously. 4.2.3 Measures 4.2.3.1 Anthropometrics and maturation Body mass and stature were measured barefoot in light clothing to the nearest 0.1 kg and 0.1 cm respectively. Physical maturation was assessed from predicted aPHV, using the Mirwald equation (Mirwald et al., 2002) and from parental report of Tanner stage for pubic hair and genitalia (Rasmussen et al., 2015). All children were >-1 year from aPHV (mean aPHV: -2.3 ± 0.9 years). Fourteen of the 20 children were Tanner stage 1 and 6 were Tanner stage 2 (3 boys, 3 girls). Tanner stage 1 is defined by the lack of secondary sexual characteristics i.e., no pubic hair, breast or genitalia development and considered pre-pubertal. Tanner stage 2 marks the onset of secondary sex characteristics i.e., sparse pubic hair, breast buds or onset of male genitalia growth 47 and is considered early-pubertal (Marshall & Tanner, 1969; Marshall & Tanner, 1970). Sex assigned at birth was identified by parental report. 4.2.3.2 Cardiorespiratory measures Beat-by-beat BP was assessed using a Finometer Pro (Finapres Medical Systems). HR was assessed using a 3-lead electrocardiogram (ECG; ADInstruments BioAmp ML132). VE, RR, VT, PETCO2 and PETO2 were assessed breath by breath, using a metabolic cart (Oxycon Pro, Carefusion, USA). The metabolic cart was calibrated prior to each test using gases of a known concentration, in addition to calibration of volume. Respiratory variables were interpolated in second-by-second intervals and time-aligned with MCAv, HR, and BP. We excluded data if there was relative hypocapnia at baseline – this was defined as PETCO2 >2 standard deviations (SD) below the child or adult mean. 4.2.3.3 Cerebrovascular measures MCAv (right side) was assessed using a 2-MHz TCD ultrasound (Spencer Technologies). The TCD probe was secured via attachment to a headpiece (child-adapted and adult M600 bilateral head frame; Spencer Technologies). MCA insonation was performed through the trans-temporal window following previously described guidelines (Willie et al., 2011). Our between-day coefficient of variation for resting MCAv insonation is 4.7%. 4.2.4 Data processing 4.2.4.1 Baseline and steady-state responses to hypercapnia Baseline values were calculated from 120 seconds of the supine rest. Response values were taken in the final 30s of the four-minute test and differences from baseline to hypercapnia (∆) was calculated for HR, MAP, MCAv, VE, VT, RR, PETCO2 and PETO2. 48 Cerebrovascular resistance index (CVRiMCA) was calculated as MAP divided by MCAv (mmHg∙cm-1∙s-1) at baseline and during the last 30 seconds of hypercapnia. There is no standardized analytical approach for the calculation of CVR (Willie et al., 2012; Skow et al., 2013); therefore, CVR was calculated both in absolute (cm∙s-1∙mmHg-1) and relative (%∙mmHg-1) terms: Equation 3. Absolute cerebrovascular reactivity 𝐴𝑏𝑠𝑜𝑙𝑢𝑡𝑒 𝐶𝑉𝑅 (𝐶𝑉𝑅^$,) = (𝑟𝑒𝑠𝑝𝑜𝑛𝑠𝑒 ℎ𝑒𝑚𝑜𝑑𝑦𝑛𝑎𝑚𝑖𝑐𝑠 − 𝑏𝑎𝑠𝑒𝑙𝑖𝑛𝑒 ℎ𝑒𝑚𝑜𝑑𝑦𝑛𝑎𝑚𝑖𝑐𝑠)(𝑟𝑒𝑠𝑝𝑜𝑛𝑠𝑒 𝑃bc𝐶𝑂: − 𝑏𝑎𝑠𝑒𝑙𝑖𝑛𝑒 𝑃bc𝐶𝑂:) Equation 4. Relative cerebrovascular reactivity 𝑅𝑒𝑙𝑎𝑡𝑖𝑣𝑒 𝐶𝑉𝑅 (𝐶𝑉𝑅e"&) = f𝑟𝑒𝑠𝑝𝑜𝑛𝑠𝑒 ℎ𝑒𝑚𝑜𝑑𝑦𝑛𝑎𝑚𝑖𝑐𝑠 − 𝑏𝑎𝑠𝑒𝑙𝑖𝑛𝑒 ℎ𝑒𝑚𝑜𝑑𝑦𝑛𝑎𝑚𝑖𝑐𝑠𝑏𝑎𝑠𝑒𝑙𝑖𝑛𝑒 ℎ𝑒𝑚𝑜𝑑𝑦𝑛𝑎𝑚𝑖𝑐𝑠 g(𝑟𝑒𝑠𝑝𝑜𝑛𝑠𝑒 𝑃bc𝐶𝑂: − 𝑏𝑎𝑠𝑒𝑙𝑖𝑛𝑒 𝑃bc𝐶𝑂:) ∗ 100 HCVR (L∙min-1∙mmHg-1) was calculated as: Equation 5. Hypercapnic ventilatory response 𝐻𝐶𝑉𝑅 = (𝑟𝑒𝑠𝑝𝑜𝑛𝑠𝑒 𝑉b − 𝑏𝑎𝑠𝑒𝑙𝑖𝑛𝑒 𝑉b)(𝑟𝑒𝑠𝑝𝑜𝑛𝑠𝑒 𝑃bc𝐶𝑂: − 𝑏𝑎𝑠𝑒𝑙𝑖𝑛𝑒 𝑃bc𝐶𝑂:) We also examined MAP (mmHg∙mmHg-1) and HR (beats∙min-1∙mmHg-1) reactivity to CO2 to account for the impact changes in FICO2 may have on cardiovascular function: Equation 6. Mean arterial blood pressure reactivity to carbon dioxide 𝑀𝐴𝑃 𝑟𝑒𝑎𝑐𝑡𝑖𝑣𝑖𝑡𝑦 = (𝑟𝑒𝑠𝑝𝑜𝑛𝑠𝑒 𝑀𝐴𝑃 − 𝑏𝑎𝑠𝑒𝑙𝑖𝑛𝑒 𝑀𝐴𝑃)(𝑟𝑒𝑠𝑝𝑜𝑛𝑠𝑒 𝑃bc𝐶𝑂: − 𝑏𝑎𝑠𝑒𝑙𝑖𝑛𝑒 𝑃bc𝐶𝑂:) Equation 7. Heart rate reactivity to carbon dioxide 𝐻𝑅 𝑟𝑒𝑎𝑐𝑡𝑖𝑣𝑖𝑡𝑦 = (𝑟𝑒𝑠𝑝𝑜𝑛𝑠𝑒 𝐻𝑅 − 𝑏𝑎𝑠𝑒𝑙𝑖𝑛𝑒 𝐻𝑅)(𝑟𝑒𝑠𝑝𝑜𝑛𝑠𝑒 𝑃bc𝐶𝑂: − 𝑏𝑎𝑠𝑒𝑙𝑖𝑛𝑒 𝑃bc𝐶𝑂:) 49 4.2.4.2 Dynamic onset responses to hypercapnia Previous studies investigating dynamic cerebrovascular responses to various stimuli including hypercapnia and exercise, have utilized monoexponential modelling, providing a robust fit for MCAv, VE and PETCO2 responses (Ogoh et al., 2009; Billinger et al., 2017). Likewise, we conducted exploratory analyses of the kinetic response of MCAv, VE and PETCO2 to hypercapnia using an iterative least-squares non-linear regression procedure, with corresponding 95% confidence intervals (95% CIs) to establish the precision of the estimate (GraphPad Prism Version 8.0.2, GraphPad Software, San Diego, CA). The MCAv, VE and PETCO2 onset responses for each participant were modelled using a monoexponential function including a delay term: Equation 8. Monoexponential function 𝑦(𝑡) = 𝑦0 + ∆^ (1 − 𝑒 − 𝑡 − 𝑇𝐷𝜏 ) where y(t), y0, ∆A, TD and t are the response at a given time, the baseline value, the baseline corrected change in amplitude from baseline to asymptote, the time delay and the time-constant of the response, respectively. Each participant’s response was modelled from the onset of the 6% CO2 stimulus (t = 0 s). Goodness of fit (r2>0.50) and normality of residuals were used to determine model acceptability. 4.2.5 Statistical analysis Statistical analyses were performed using SPSS (version 25, SPSS; Chicago IL). Normality was checked and verified using the Shapiro-Wilk test normality test for all variables. Two-way analyses of variance (ANOVA) were used to compare baseline and responses to hypercapnia by age and sex. T-tests were used to deconstruct the ANOVA main and interaction effects. One-way ANOVA was used to compare onset kinetic responses by age. Pearson product moment correlation coefficients were computed to assess the relationship between CVR, HCVR, 50 HR and MAP reactivity. Statistical significance for main effects and interactions was set a priori at p£0.05. Data are presented as mean ± SD unless stated otherwise. 4.3 Results Of the 24 children and 26 adults recruited, four children and five adults were excluded from analyses. Three children were excluded who had a PETCO2 <31.2 mmHg at baseline and the MCA could not be insonated in one child. Of the five adults who were excluded from the analysis, two were excluded due to low PETCO2 (<34.7 mmHg) at baseline. The MCA could not be insonated in two adults and the signal acquisition for VE was too poor for data to be processed in one adult. The data presented are from 20 children (11 females, 9 males) and 21 adults (10 females, 11 males). Age of the children was 9.9 ± 0.7 years (stature: 1.42 ± .07 m; body mass: 33.4 ± 6.2 kg), while the age of the adults was 24.4 ± 2.0 years (height: 1.72 ± .06 m; body mass: 72.9 ± 10.4 kg). 4.3.1 Baseline and steady-state responses to hypercapnia Absolute values for all variables (HR, MAP, MCAv, CVRiMCA, VE, VT, RR, PETCO2, and PETO2) at baseline and during the last 30s of 4 minutes of CO2 administration are presented in Table 4. There were significant child-adult differences at baseline in HR, MAP, MCAv, CVRiMCA, VT, RR, PETCO2, and PETO2. An age difference remained for the ∆ response to hypercapnia only for HR, CVRiMCA, VT and RR (see Table 4). The ∆HR response to hypercapnia was significantly greater in children compared to adults, while the CVRiMCA decline was much greater in the adults compared to children. There was no difference in VE at baseline or in response to hypercapnia, but children achieved a similar VE at all time points with a smaller VT and faster RR. A main effect for sex was apparent for MCAv, MAP, CVRi, VE, PETCO2, and PETO2 (see Table 4). The MCAv values were higher in adult females compared to males at baseline (p≤0.05) 51 and in the final 30s of hypercapnia (p≤0.05). Baseline MCAv values were similar in girls and boys, but greater in the final 30s of hypercapnia in the girls (p≤0.05). Table 4. Ventilatory, cardiovascular, and cerebrovascular data at baseline and in the final 30s of hypercapnia in children and adults and by sex. Values are means ± SD. HR, heart rate; MAP, mean arterial blood pressure; CVRiMCA, cerebrovascular resistance index; MCAv, middle cerebral artery mean velocity; VE, ventilation; VT, tidal volume; RR, respiratory rate; PETCO2, end-tidal carbon dioxide; PETO2, end-tidal oxygen; BL, baseline; HC, hypercapnia; ∆, absolute change between the pre-stimulus baseline to the last 30s of hypercapnia. There was a main effect for sex for the MAP response to hypercapnia, with follow up analyses revealing a greater MAP response to hypercapnia in adult females compared to males (p£0.05), but not children. The CVRiMCA response to hypercapnia also differed by sex in the adults only, decreasing more in the females than the males (p£0.05). Ventilatory responses to hypercapnia (absolute and ∆VE) were greater in adult males compared to females (p£0.05), but not in children. All males had a higher baseline PETCO2, and a smaller ∆PETCO2 in response to hypercapnia (p≤0.05), whereas all females had a higher baseline PETO2, but a smaller hypercapnic ∆PETO2 (p≤0.05). Absolute and relative CVR are presented in Figure 6. There was no main effect for age in absolute CVR (see Figure 6, panel A and B), with values of 3.38 ± 0.89 cm·s-1·mmHg-1 in children CHILDREN ADULTS ANOVA main effects(P-value) Female (n = 11) Male (n = 9) All Children (n = 20) Female (n = 10) Male (n = 11) All Adults (n = 21) Age Sex Age × Sex HR (beats·min-1) BL HC ∆ 78 ± 8 93 ± 10 16 ± 6 78 ± 7 92 ± 6 13 ± 6 78 ± 8 92 ± 8 14 ± 6 69 ± 15 73 ± 14 4 ± 4 62 ± 12 66 ± 8 5 ± 6 65 ± 14 69 ± 12 4 ± 5 .001 .001 .001 .377 .189 .526 .292 .427 .492 MAP (mmHg) BL HC ∆ 78 ± 10 87 ± 10 8 ± 6 78 ± 10 83 ± 12 5 ± 6 78 ± 9.5 85 ± 11 7 ± 6 88 ± 12 97 ± 13 9 ± 6 82 ± 9 87 ± 10 6 ± 7 85 ± 11 92 ± 12 7 ± 6 .040 .034 .687 .270 .048 .079 .384 .403 .957 MCAv (cm·s-1) BL HC ∆ 94.1 ± 9.5 129.9 ± 11.9 35.8 ± 8.0 90.5 ± 9.8 118.1 ± 13.3 27.6 ± 7.7 92.7 ± 9.5 125.6 ± 12.7 32.9 ± 9.6 79.6 ± 15.4 115.8 ± 14.8 36.2 ± 9.7 64.0 ± 7.4 88.2 ± 11.6 24.2 ± 6.2 71.4 ± 14.1 101.7 ± 19.4 29.9 ± 10.0 .001 .001 .548 .008 .001 .001 .086 .053 .456 CVRiMCA (mmHg·cm-1·s-1) BL HC ∆ 0.84 ± 0.16 0.67 ± 0.08 -0.24 ± 0.17 0.86 ± 0.12 0.70 ± 0.08 -0.16 ± 0.07 0.85 ± 0.14 0.68 ± 0.08 -0.17 ± 0.09 1.17 ± 0.22 0.70 ± 0.22 -0.48 ± 0.28 1.29 ± 0.19 .88 ± 0.24 -0.41 ± 0.15 1.24 ± 0.21 0.80 ± 0.25 -0.44 ± 0.22 .001 .001 .394 .143 .033 .478 .252 .138 .698 VE (L·min-1) BL HC ∆ 8.0 ± 1.5 22.9 ± 5.4 15.0 ± 5.2 7.7 ± 1.3 27.0 ± 7.7 19.3 ± 8.3 7.9 ± 1.3 24.8 ± 6.7 16.9 ± 7.0 8.2 ± 1.6 20.7 ± 4.1 12.6 ± 3.4 8.8 ± 1.9 29.3 ± 11.7 20.5 ± 11.4 8.5 ± 1.8 25.3 ± 9.8 16.7 ± 9.3 .196 .978 .812 .637 .014 .016 .366 .369 .468 VT (L) BL HC ∆ 0.42 ± 0.10 0.88 ± 0.14 0.46 ± 0.16 0.48 ± 0.15 0.94 ± 0.21 0.46 ± 0.23 0.45 ± 0.10 0.91 ± 0.17 0.46 ± 0.19 0.72 ± 0.07 1.41 ± 0.18 0.69 ± 0.21 0.91 ± 0.31 1.87 ± 0.41 .96 ± 0.32 0.82 ± 0.25 1.66 ± 0.40 0.84 ± 0.31 .001 .001 .001 .037 .003 .084 .253 .021 .087 RR (bpm) BL HC ∆ 20 ± 4 28 ± 9 8 ± 7 18 ± 4 32 ± 11 14 ± 11 19 ± 4 30 ± 9 11 ± 10 12 ± 3 16 ± 3 4 ± 3 11 ± 3 16 ± 6 6 ± 6 11 ± 3 16 ± 5 5 ± 5 .001 .001 .010 .142 .373 .110 .461 .532 .325 PETCO2 (mmHg) BL HC ∆ 36.0 ± 2.7 46.4 ± 1.8 10.4 ± 2.3 37.4 ± 1.4 46.2 ± 1.9 8.8 ± 1.5 36.6 ± 2.7 46.3 ± 1.8 9.7 ± 2.1 38.2 ± 2.0 49.24± 1.8 11.1 ± 1.1 40.2 ± 2.2 50.1 ± 2.2 9.9 ± 2.0 39.3 ± 2.3 49.7 ± 2.0 10.5 ± 1.7 .001 .001 .121 .017 .641 .016 .676 .485 .801 PETO2 (mmHg) BL HC ∆ 100.9 ± 4.1 132.9 ± 4.3 32.0 ± 3.0 96.6 ± 2.3 133.0 ± 5.6 37.4 ± 5.7 98.5 ± 4.3 132.9 ± 4.3 34.4 ± 5.1 96.1 ± 5.3 125.7 ± 4.6 29.6 ± 4.0 92.8 ± 4.9 127.2 ± 5.4 34.5 ± 6.4 94.4 ± 5.4 126.5 ± 4.6 32.1 ± 5.8 .009 .001 .094 .004 .567 .002 .482 .610 .870 52 and 2.89 ± 0.85 cm·s-1·mmHg-1 in adults. A main effect of sex was apparent (p=0.04), with follow-up analyses indicated absolute CVR was greater (p≤0.05) in females (3.27 ± .86 cm·s-1·mmHg-1) than males (2.53 ± .70 cm·s-1·mmHg-1). When expressed in relative terms, no main effect for age or sex were found (see Figure 6, panel C and D), with values of 3.71 ± 1.17 %·mmHg-1 in children and 4.12 ± 1.32 %·mmHg-1 in adults. Figure 6. Relative and absolute cerebrovascular reactivity of the middle cerebral artery to hypercapnia by age and by sex. A, absolute CVR in children and adults. B, absolute CVR in males and females. C, relative CVR in children and adults. D, relative CVR in males and females. P values indicate the main effects for age and sex from ANOVA analyses. Children Adults02468CVRAbs (cm⋅s-1⋅mmHg-1 )p=0.084AChildren Adults02468CVRRel (%⋅mmHg-1 )p=0.260CFemales Males02468p=0.040BFemales Males02468p=0.419D 53 The HCVR, MAP and HR reactivity are presented in Figure 7. There was no main effect for age for absolute HCVR (see Figure 7, panel A). A main effect for sex was present (see Figure 7, panel B), with follow-up analyses indicating a higher ventilatory reactivity in adult males (2.33 ± 1.66 L∙min-1∙mmHg-1) compared to females (1.15 ± 0.37 L∙min-1∙mmHg-1; p≤0.05), but not in children (males: 2.32 ± 1.21 L∙min-1∙mmHg-1; females 1.53 ± 0.67 L∙min-1∙mmHg-1; p=0.07). There was no main effect for age or sex for absolute MAP reactivity (see Figure 7, panel C and D). There was however, a main effect for age for absolute HR reactivity (see Figure 7, panel E), but not sex. HR reactivity was 1.05 beats∙min-1∙mmHg-1 higher in children than in adults. 54 Figure 7. Hypercapnic ventilatory and cardiovascular reactivity by age and by sex. A, hypercapnic ventilatory reactivity (HCVR) in children and adults. B, HCVR in males and females. C, mean arterial pressure (MAP) reactivity in children and adults. D, MAP reactivity in males and females. E, HR reactivity in children and adults. F, HR reactivity in males and females. P values indicate the main effects for age and sex from ANOVA analyses. Children Adults0246HCVR (L⋅min-1⋅mmHg-1 )p=0.597AChildren Adults-20246MAP reactivity (mmHg⋅mmHg-1 ) p=0.995CChildren Adults-10123HR reactivity (beat⋅min-1⋅mmHg-1 ) p≤0.001EFemales Males 0246p=0.007BFemales Males-20246p=0.163DFemales Males-10123p=0.700F 55 There were no significant relationships between CVR, HCVR, MAP or HR reactivity in children or adults, when expressed in either absolute or relative terms. 4.3.2 Dynamic onset responses to hypercapnia. The estimated kinetic responses at the onset of hypercapnia are shown in Table 5. Of the 20 children and 21 adults, acceptable models for MCAv and PETCO2 were determined in 14 children and 16 adults. Acceptable model fit for VE was only achieved in 8 children and 10 adults. Given the smaller sample size of the dynamic responses, only a main effect for age was explored using one-way ANOVAs. Table 5. Middle cerebral artery, partial pressure of end-tidal carbon dioxide, and ventilation kinetic responses at the onset of hypercapnia in children and adults. Children (n = 14) Adults (n = 16) ANOVA Main effect (P-value) Age MCAv ∆A (cm·s-1) TD (s) t (s) 35.2± 8.1 11 ± 5 74 ± 28 29.2 ± 8.5 5 ± 4 34 ± 18 .081 .023 .001 PETCO2 ∆A (cm·s-1) TD (s) t (s) 10.7 ± 1.6 8 ± 2 31 ± 11 9.7 ± 2.3 4 ± 2 27 ± 16 .321 .006 .622 n = 8 n = 10 VE ∆A (cm·s-1) TD (s) t (s) 16.6 ± 6.0 11 ± 8 102 ± 40 26.9 ± 14.3 13 ± 7 98 ± 24 .127 .652 .891 Values are means ± SD. MCAv, middle cerebral artery mean velocity; PETCO2, end-tidal carbon dioxide; VE, ventilation; ∆A, delta amplitude; TD, time delay; t, time constant. Bold signifies significance, P<0.05. A typical MCAv response profile for a child and an adult at the onset of hypercapnia is shown in Figure 8. One-way ANOVA analyses revealed significant main effects for age for MCAv TD and t (see Table 5), but not ∆A. Children responded with a t that was on average 42 s slower than adults. The MCAv TD was longer in children, as was the PETCO2 TD. There were no age differences in any of the VE onset parameters. 56 Figure 8. Dynamic onset response of middle cerebral artery blood velocity in representative child and adult subjects. The continuous black and red lines represent the monoexponential function in a representative child (open circles) and adult (red squares), respectively. The dark grey shaded area from -60 s to 0 s signifies baseline; time = 0 signifies the onset of the hypercapnic stimulus. MCAv and VE t values did not differ significantly in children (p=0.383), but MCAv t was considerably slower than PETCO2 t (mean difference 43 s; p£0.001). In contrast, MCAv t was on average 59 s faster than VE t in adults (p£0.001), with no significant differences between MCAv and PETCO2 t values (p=0.299). 0 60 120 180 240-10010203040Time (s)Δ MCAv (cm⋅s-1) 57 4.4 Discussion This study is the first to report the impact of age and sex on CVR, HCVR and the dynamic onset response of MCAv, VE and PETCO2 to hypercapnia in children and adults. In contrast to our primary hypothesis, we did not find a blunted MCAv CVR in children, or child-adult differences in HCVR. We do, however, observe a markedly attenuated MCAv t in children compared to adults. In partial keeping with our final hypothesis, we did find sex differences in MCAv at baseline, but only in adults, with higher MCAv values in females. Sex differences in the MCAv response to hypercapnia were however apparent in both children and adults, with a greater MCAv response to 6% CO2 in females compared to males. 4.4.1 Child to adult differences in reactivity to CO2 The CVR of 3.8 %·mmHg-1 we reported in 9–10-year-old children was similar to the adult CVR of 4.1 %·mmHg-1. These values are similar to the average adult TCD derived MCAv CVR of between 3 to 4 %·mmHg-1 (Hoiland et al., 2019) and would suggest that cerebrovascular reserve is similar in healthy children and adults. Leung et al. (2016) estimated white and grey matter CVR in children to be about 20 to 30% lower compared to adults of similar ages to those in our study, concluding this may indicate a reduced cerebrovascular reserve in the child. However, previous work by Leung et al. (2016) did not account for physical maturation and only 3 boys and 4 girls were under the age of 12 years, limiting conclusions regarding child-adult differences in CVR. Given the influence age and maturation have on CBF, our study adds to the scant literature on the development of CVR. Comparison of these two studies is limited because of methodological differences in the approaches used; however, the methodologies used and the impact they may have on the interpretation of the findings are important and discussed in more detail under Section ‘4.4.4 Methodological considerations’. 58 We hypothesized that HCVR would be amplified in children because of the striking developmental differences in the chemoreceptive responsivity to CO2 previously demonstrated. We failed to find developmental differences in HCVR or a relationship between CVR and HCVR. This study was designed to explore the potential effect of CVR on the central ventilatory CO2 chemoreflex, but the rise in VE with hypercapnia resulted in elevations in PETO2 in both children and adults. The failure to maintain an iso-oxic hypercapnic stimulus is a limitation given increases in PETCO2 and PETO2 induce peripheral and central respiratory chemoreflex loops. An alternative approach is the use of hyperoxic gas administration to blunt the peripheral chemoreceptor response and thus isolate the central VE chemoreflex. Although the evidence is limited, the impact of hyperoxic hypercapnia is not uniform in children and adults. Using a step protocol comprising a single breath of 15% CO2 in 85% O2, Gozal et al. (1994) demonstrate the slope of the ventilatory response to step hypercapnic stimuli (VE vs PETCO2) was 0.507 in children compared to 0.182 in adults. Further work is needed that explores the impact of iso-oxic and hyperoxic administration of CO2, as well as modified re-breathing techniques (Keir et al., 2019) to further probe the possible interplay between CVR and HCVR in children. Inclusion of the posterior cerebral circulation will be also important, given the central chemoreceptors are located near the ventral surface of the medulla and disparate blood flow regulation has been shown in the brainstem and cortex of adults (Willie et al., 2012; Skow et al., 2013). An intriguing finding was the markedly slower MCAv kinetic response in children compared to adults. The model fit was acceptable with normality residuals and mean r2 of .78, .71 and .91 for MCAv, VE and PETCO2 respectively. In adults, similar to prior work (Ogoh et al., 2009), MCAv t was tightly coupled to PETCO2 t, with VE in lag, supporting the premise that CVR influences the central ventilatory CO2 chemoreflex. In contrast, in children this does not appear to be the case. The MCAv t was 42 seconds slower than PETCO2 t, and similar to VE t. These disparate findings suggest developmentally distinct regulatory mechanisms, which are discussed below. 59 4.4.2 Potential mechanism(s) Increasing FICO2 has been shown to increase MAP and thereby cause increases in cerebral perfusion pressure (Battisti-Charbonney et al., 2011). We found an 8-9% increase in MAP with the increased FICO2 in both children and adults, a similar MAP reactivity to hypercapnia, no relationship between CVR and MAP reactivity, but a smaller decline in CVRiMCA with hypercapnia in children. It is possible that child-adult differences in autonomic regulation and/or cerebral autoregulation during hypercapnia exist and influence the onset response of MCAv, but further investigations are needed to substantiate this proposition. Alternatively, sex differences in the MAP response may have impacted the MAP reactivity–CVR relationship since cerebral autoregulation is attenuated with hypercapnia and in females (Edgell et al., 2012; Perry et al., 2014; Labrecque et al., 2019). A notable difference between the children and adults in the current study was the elevated HR in children with the increased FICO2. It is possible that this relates to altered sympathetic or parasympathic nervous activity with hypercapnia, but this is yet to be determined in children. Of note, the fraction of CO delivered to the brain is highest during childhood, declining into adulthood (Wu et al., 2016). Total CBF to aortic outflow ratio is about 10% higher in 8–10-year-old children compared to adults (Wu et al., 2016). As result of the increased cerebral oxygen consumption at this age (Vandekar et al., 2019), it is possible that the increased HR reflects the role CO plays in meeting increased cerebrovascular demands in the child. This possibility, however, needs to be confirmed in future studies. In adults, there is evidence that transitory increases in FICO2 causes shear mediated vasodilation in the conduit extra-cranial vasculature, independent of changes in MAP, CO or HR that often accompany sustained hypercapnia (Hoiland et al., 2017). At least in adults, dilation of the MCA has been shown to occur with elevations in PETCO2 >10 mmHg (Coverdale et al., 2014). 60 Half of our participants had an increase in PETCO2 between 10-12 mmHg and it is possible this caused vasodilation of the MCA. If in fact hypercapnic hyperemia caused shear-mediated vasodilation in our participants, we are likely underestimating the change in cerebral perfusion. However, previous research has shown only increases of PETCO2 approximately 15 mmHg led to significant dilation of the MCA (Verbree et al., 2014), in which case it is likely no significant dilation occurred in the present study (see discussion within Section 4.4.4 Methodological considerations). Future work will need to properly document the impact of hypercapnia on the cerebral vasculature vasomotion in children using volumetric techniques to help discern whether dilation occurs and if so whether hypercapnic hyperemia is shear mediated in this population. 4.4.3 Sex differences in MCAv Women were found to have a significantly higher baseline MCAv than men, however, baseline MCAv was similar in girls and boys (see Table 4). The sex difference found in adults confirms our hypothesis and aligns with previous literature where significant sex differences were found in MCAv of adults at rest (Vriens et al., 1989; Marinoni et al., 1998). However, the similarity between the girls (94.1 ± 9.5 cm·s-1) and boys (90.5 ± 9.8 cm·s-1) included in this data set is contrary to the tertiary hypothesis of the present study. The age of the sample population may provide a reasonable explanation for this finding. Using TCD, Tontisirin et al. (2007) report higher levels of resting MCAv in girls (99 ± 11 cm·s-1) compared to boys (92 ± 13 cm·s-1) in 48 children between the age of 4 and 8 years old. However, prior research reports no sex difference in baseline MCAv in 76 children between any of the four age categories: 2-4 years; 5-9 years; 10-14 years; 15-19 years (Brouwers et al., 1990). As the present study includes a range of children 8 to 11 years of age, an older population than those included by Tontisirin et al. (2007), yet within range of those included by Brouwers et al. (1990), it is reasonable that our results mirror the latter. However, future longitudinal work is needed to fully understand the influence of age on sex differences in resting intra-cranial blood velocities. 61 A number of reasons have been proposed for the elevated cerebral blood velocity response to hypercapnia in all females, including sex hormones, hemoglobin, cerebral metabolism, and shear stress (Vavilala et al., 2002a). Within the present study there was a lack of control for menstrual phase in adult females. However, our findings are similar to others who detected sex differences in CVR without controlling for menstrual phase (Minhas et al., 2018), but estrogen is known to impact vasodilation (Krause et al., 2006) and we do not account for this. Additionally, estrogen has been linked to greater carotid artery compliance and distensibility in women compared to men (Marlatt et al., 2013). Albeit within the peripheral vasculature, there is evidence of sex differences in vascular smooth muscle in children who were classified as Tanner stage 2 (McCue et al., 2012). Despite only six of our participants being Tanner stage 2, the remaining 14 were Tanner stage 1, suggests other factors alongside sex hormones may account for the sex differences noted. It is also important to consider whether sex differences in cerebral metabolic rate (CMR) account for the an elevated hypercapnic MCAv response in the girls. In an early study of CMR using a modified Kety Schmidt procedure, Kennedy and Sokoloff (1957) report higher CMRs in children up to 11 years of age compared to adults. Tontisirin et al. (2007) also report an elevated MCAv in girls compared to boys. In contrast, a recent investigation of sex differences in CMR in a large cohort of children and adolescents, showed a lower global CMR (expressed as a % of whole body RMR) and lower cerebral glucose consumption in girls in comparison to boys (Vandekar et al., 2019). This latter study highlighted the increased CMR in children compared to adults, alongside increased cerebral perfusion in the younger participants. The higher baseline perfusion and lower CVRiMCA we note in the children compared to the adults is most likely an outcome of the higher CMR in the child. 62 4.4.4 Methodological considerations How the CO2 challenge is delivered is important given the impact this has on the time required to reach a steady state cerebrovascular response and the (in)ability to target end-tidal gases and standardize the PETCO2 to PaCO2 gradient [reviewed in (Hoiland et al., 2019)]. The present study implemented elevations in FICO2 to experimentally manipulate PaCO2. The benefit of this approach being it allows interactions between CVR and VE to be explored since the PETCO2 to PaCO2 gradients are able to vary (Hoiland et al., 2019). Leung et al. (2016) used prospective targeting of PETCO2, alternating 60s of normoxic isocapnia [PETCO2 of 40 mmHg] with 45s of normoxic hypercapnia [PETCO2 of 45 mmHg]). Previous work in adults shows the time to steady state differs substantially between these two methods, with steady state attained during the prospective targeting technique within 1-15s, compared to the 1 to 2 minutes required when using a fixed concentration FICO2 (Mark et al., 2010; Fisher, 2016). Our dynamic onset data reveal a distinctly slower MCAv onset in children compared to adults, and it will be valuable to understand differences in steady state between the FICO2 and prospective targeting of PETCO2 in children. Of note, we were only able to fit the monoexponential model to the ventilatory data in 8 children and 10 adults. The ventilatory response to CO2 usually requires more than four minutes to attain steady-state and it is likely our protocol was of insufficient length for the kinetic modelling of VE (Ogoh et al., 2009). While using a fixed FICO2 does allow the interactions between CVR and VE to unfold, it does not permit precise control of the change in PETCO2 (or PETO2) and shifts in the PaCO2 to PETCO2 gradient can result (Hoiland et al., 2019). It is important to note that resting PETCO2 closely reflects PaCO2 in both children and adults and is an acceptable, non-invasive surrogate (Ohuchi et al., 1999). The baseline PETCO2 and PETO2 values we report for children (Table 4: 36.6 ± 2.7 / 98.5 ± 4.3 mmHg) are similar to those found in previous published work from our group (Ellis et al., 2017) and others (MacLean et al., 2016) reporting PETCO2 36.1 ± 3.8 and PETO2 102.2 ± 10.1 63 mmHg in healthy 9–12-year-olds. Hypercapnia can increase the physiological deadspace to VT ratio that can inflate PETCO2 to a greater extent than PaCO2 and modify the MCAv response. Interestingly, the response of PETCO2 and PETO2 to four minutes of increased FICO2 in our study were similar between the children and adults. Although inter-individual variability in the PaCO2 to PETCO2 gradient is unavoidable using the fixed FICO2 approach, this does not appear to have resulted in differences in the PETCO2 response to hypercapnia between the children and adults in this study. It is worth noting also, similar to our previous findings (Ellis et al., 2017), the pattern of response in MCAv in children did not mirror the response pattern in PETCO2; however, the changes in PETCO2 and MCAv seems to be aligned in adults. In order to properly discern the trajectory of change in CVR throughout childhood from methodology it will be important for future work to carefully consider the impact the experimental approach to delivery of CO2, as well as the technique used to assess CBF or velocity has on the CVR response. The implementation of TCD to assess of cerebral blood velocity has both limitations and benefits. TCD does not account for vessel diameter, only providing an assessment of blood velocity not blood flow (Hoiland et al., 2019). As CO2 is a known vasodilator, without a measure of vessel diameter the assessment of the change in CBF cannot be conducted and therefore the change in cerebral perfusion could be underestimated (Ainslie & Hoiland, 2014). Literature on the vasomotion of the MCA with hypercapnia is convoluted, although it has been suggested that there is subtle vasodilation of the MCA with hypercapnia (Hoiland & Ainslie, 2016). However, the degree of the increase in PETCO2 matters. For example, in an MRI Verbree et al. (2014), reported significant vasodilation of the MCA after an increase in PETCO2 from 36.9 ± 3.8 mmHg at baseline to 51.0 ± 4.5 mmHg in adults. However, no significant change in MCA diameter occurred with an increase from baseline values to 45.0 ± 3.8 mmHg (Verbree et al., 2014), suggesting the magnitude of the change above baseline values influences the extent of vasomotion of the MCA. It is also unknown how the vasculature within the child reacts to hypercapnia and whether the 64 vasomotion of the MCA changes in the same pattern as the adults. In the current study, the increase in PETCO2 averaged 10.2 ± 1.9 mmHg within all participant values; however, PETCO2 values of 49.7 ± 2.0 mmHg were reached in the adults (compared to 46.3 ± 1.8 mmHg in the children) due to their slightly higher resting PETCO2 at baseline. It would seem reasonable that it is the delta change – rather than absolute value – in PaCO2 that might influence the MCA diameter; therefore, both adults and children would have had the same vasomotion stimulus. Despite the noted limitations of both the fixed FICO2 experimental approach and TCD for measurement of cerebral blood velocity, they do provide robust and commonly used methods for assessing CVR that are applicable to a paediatric population (Hoiland et al., 2019). We explored the link between cerebral blood velocity and VE by insonating the MCA. The MCA is one of the two most commonly insonated vessels, the other being PCA, these vessels supply blood to the anterior and posterior regions of the brain, respectively. If a change (either increase or decrease) in VE were expected to influence cerebral blood velocity through an interaction with the respiratory centers (e.g. via an influence on local metabolism), this would be expected to manifest within the posterior not anterior circulation. Therefore, insonation solely of the MCA as per this study, may not fully capture potential relationships between ventilatory and cerebrovascular control. At least in adults, studies have reported no differences in CVR to hypercapnia between posterior and anterior circulations (Willie et al., 2012; Hoiland et al., 2015); however, if any regional differences are present in children should be considered in future studies. 4.4.5 Summary These are the first findings to provide insight into the dynamic onset response of the MCAv to hypercapnia in children compared to adults and to explore the impact sex may have on CVR in the child. We show a similar CVR, but markedly attenuated MCAv onset response in the child, that may relate to differences in cerebral perfusion pressure, autonomic control or cerebral 65 metabolism. Identifying which factors account for age, sex, and maturation differences in the MCAv response to hypercapnia is challenging, but has relevant application to clinical settings when interpreting cerebral hemodynamic abnormalities in children. Future work will require careful consideration of the impact of the methodological approach employed, examination of regional differences in CVR in children and a longitudinal design to fully understand the development of cerebrovascular regulation. 66 Chapter 5: Dynamic Onset Response of the Internal Carotid Artery to Hypercapnia is Blunted in Children Compared with Adults 5.1 Background Cerebrovascular hyperemia induced by hypercapnia is a defining trait of CVR and provides a marker of cerebrovascular regulation (Fierstra et al., 2013; Willie et al., 2014). Evidence of developmental trajectories of CVR are limited and conflicting. In comparison to adults, grey and white matter hypercapnic CVR has been shown to be attenuated in children in response to brief bouts (45 s) of hypercapnic stimulus, suggestive of the high CBF in the child resulting in a reduced reserve capacity (Leung et al., 2016). In contrast, CVR estimated from the MCAv response after 4-minutes of a step increase in inspired CO2 in Chapter 4 demonstrated similar values in children and adults (Tallon et al., 2020). The pattern of the onset response of CBF to a given stimuli can be derived from kinetic modelling and has been exploited in healthy young and older adults, as well as in post-stroke patients (Poulin et al., 1996; Ogoh et al., 2009; Billinger et al., 2017; Kempf et al., 2019). A single exponential model with delay term effectively describes the MCAv onset response to step increases in hypercapnia, hypoxia, and exercise, thereby providing valuable information into the speed (i.e., delay term, t, and MRT), as well as the magnitude (i.e. DA) of the response (Poulin et al., 1996; Ogoh et al., 2009; Billinger et al., 2017; Kempf et al., 2019). The interaction between the MCAv and respiratory chemoreflex in response to hypercapnia has been explored using response kinetics in adults (Ogoh et al., 2009) and more recently Chapter 4 observed comparisons between children and adults (Tallon et al., 2020). In children, MCAv t was in lag to the PETCO2 t (Tallon et al., 2020). This delay was not present in adults, confirming previous indications of developmentally distinct regulatory mechanisms in response to hypercapnia (Ellis et al., 2017). Chapter 4 also noted a much slower MCAv t (~42 s slower) in children compared 67 to adults, despite comparable increases in PETCO2 and in MCAv amplitude (Tallon et al., 2020). The mechanisms that account for these child-adult disparities in the onset response kinetics of the MCAv to hypercapnia are unclear, but it is likely that cerebrovascular vasomotion (changes in blood vessel diameter) plays an important role given the carotid branch arteries and intra-cranial arteries act as resistors to aortic outflow, protecting the cerebral microvasculature from high pulsatile energy (Zarrinkoob et al., 2016). Adults demonstrate dilation of the ICA in response to hypercapnia (Carter et al., 2016; Hoiland et al., 2017; Smith et al., 2019; Carr et al., 2020), and this is independent of changes in MAP and HR when using a transient 30 s bolus of inspired CO2 (Carter et al., 2016; Carr et al., 2020). Furthermore, the temporality of the responses indicate that dilation is shear-mediated and therefore implies endothelial dependence. In older adults, shear-mediated dilation of the ICA in response to hypercapnia is attenuated (Iwamoto et al., 2018), but the trajectory of change in ICA shear mediated dilation across the lifespan is undetermined since, to the best of our knowledge, the responsiveness of the ICA to increases in SR in children has yet to be assessed. Kinetic modelling of ICAv, volumetric blood flow (QICA), SR (ICASR), and diameter (ICAd) to hypercapnia provides information on the responses prior to steady state and potentially allows interrogation of the temporality of ICA vasomotion. Therefore, the purpose of this study was to compare child hypercapnic hyperemic ICA responses and their temporal order with adult responses. We hypothesized that (i) in response to 4 min of steady state hypercapnia the magnitude of the increase in ICAv, QICA, and ICASR would not differ between children and adults; and (ii) that 4 min of sustained hypercapnia would result in similar increases in ICAd in adults and children; however, (iii) modelling of the dynamic onset response would result in a slower MRT for ICAd, QICA and ICASR in children compared to adults and (iv) the MRT for ICASR would precede ICAd in both children and adults. 68 5.2 Methods 5.2.1 Ethical approval The study fully conformed with the principles of the Declaration of Helsinki (excluding registry in a database) and was approved by the Clinical Research Ethics Board of the University of British Columbia (H16-01281). All adult participants and parents/guardians of the children provided written informed consent. In addition, written and oral informed assent were obtained from each child. 5.2.2 Participants Fifty-two participants were recruited for this study: 26 young adults (14 females; age range: 20.8 to 27.8 y) from the University of British Columbia, Okanagan campus; and 26 children (15 females; age range: 8.3 to 10.9 y) from a local elementary school. Participants were eligible if they did not have any medical condition that would influence cerebrovascular or cardiopulmonary responses. 5.2.3 Experimental protocol Participants visited the laboratory on one occasion to complete a CVR assessment of the ICA. As per recommendations from Ainslie and Duffin (2009) participants were asked to refrain from eating high fat foods, consuming caffeine or alcohol, or strenuous exercise for a minimum 24 h prior to testing. Room temperature and time of day were held constant for all participants and no visual stimulation was allowed during the protocol. Upon arrival anthropometric measures were completed. Participants were then fully instrumented and rested supine for 10 min prior to recording baseline measures. Participants remained supine for the entirety of the protocol. Following the 10 min rest, data collection consisted of a 2 min baseline while breathing room air and four-minutes of a hypercapnic stimulus, 69 consisting of a fixed concentration of 0.06 FICO2 in 0.21 fractional inspired oxygen, balance nitrogen. Elevations in FICO2 were achieved using an open-circuit Douglas bag containing 6% CO2, in 21% oxygen, balance nitrogen. A 3-way Hans Rudolph valve allowed FICO2 to be switched from room air to the Douglas bag. Measures of ICAd and ICAv were made using high-resolution Duplex ultrasound, alongside the assessment of PETCO2, PETO2, HR, and MAP. 5.2.4 Measurements 5.2.4.1 Anthropometrics and maturation Body mass was assessed to the nearest 0.1 kg using a beam balance scale (Detecto, USA), stature and sitting height to the nearest 0.1 cm using a portable stadiometer (Seca Portable; Seca, Germany) barefoot and in light clothing. BMI was calculated and weight status classified in an age and sex specific manner using the World Health Organization standards (de Onis et al., 2007). None of the participants were obese. Of the children one classified as thinness grade 1 and one overweight. Of the adults, four were classified as over-weight. Child maturation-status was assessed via two established methods: calculating predicted aPHV using the Mirwald equation (Mirwald et al., 2002); and parental report of Tanner stage for pubic hair and genitalia (Rasmussen et al., 2015). Briefly, Tanner stage 1, or pre-pubertal status, is defined by the lack of secondary sexual characteristics (i.e. no pubic hair, breast or genitalia development), and Tanner stage 2, or early-pubertal status, is defined by the onset of secondary sexual characteristics (i.e. sparse pubic hair, breast buds or onset of male genitalia growth) (Marshall & Tanner, 1969; Marshall & Tanner, 1970). Sex assigned at birth was collected via parental report. 5.2.4.2 Extra-cranial arterial measures The participants were supine while their right ICA was assessed throughout the baseline period and four min hypercapnic challenge using a 15 MHz multi-frequency array vascular ultrasound (Terason T3200, Teratech, Burlington, MA). Blood velocity was assessed using 70 pulsed-wave mode and vessel diameter using B-mode imaging. Test-retest reliability for ICAd was 1.5 %. All measures of extra-cranial arteries followed established technical recommendations (Thomas et al., 2015). Recordings of the ICA were screen captured and stored as video files for offline analysis (Woodman et al., 2001). Recordings of the ICA were visually inspected before analysis and excluded if there was: (i) occurrence of an overt angle change; (ii) excessive movement of the vessel as a result of high VE; or (iii) overall poor image quality (e.g. unclear vessel walls). Synchronized ICAv and ICAd, recordings allowed for calculation of volumetric blood flow (according Equation 1) and ICASR (according to Equation 2). All parameters of the ICA (ICAv, ICAd, QICA, and ICASR) were down sampled at 1 Hz and exported into Excel for subsequent data processing. 5.2.4.3 Cardiorespiratory measures Beat-by-beat BP was assessed using a Finometer Pro (Finapres Medical Systems) and HR was assessed using a three-lead electrocardiogram (ECG; ADInstruments BioAmp ML132). Both BP and HR were sampled continuously at 1 kHz via an analog-to-digital converter (Powerlab, ADInstruments Colorado Springs, Colorado) and exported using LabChart at 1 Hz. A metabolic cart (Oxycon Pro, Carefusion, USA) was used to assess PETCO2 and PETO2. The metabolic cart was calibrated prior to each test, calibrating the volume sensor using a 3 L syringe and gas analyzers using gases of a known concentration. Data were collected breath by breath and interpolated in second-by-second bins and time aligned with HR, MAP, and ICA parameters. We excluded participants if there was relative hypocapnia at baseline, defined as a baseline value >2 SD below the child or adult mean. 71 5.2.5 Data processing 5.2.5.1 Baseline and response to four minutes of hypercapnia Baseline values were calculated from 1 min of supine rest and steady state values were taken from the final 30 s of the 4 min test. Subsequently, absolute change scores from baseline to hypercapnia (∆) were calculated for QICA, ICAv, ICASR, and ICAd, as well as for PETCO2, PETO2, HR, and MAP. At both baseline and hypercapnia cerebrovascular conductance (CVC) of the ICA (CVCICA) was calculated: Equation 9. Cerebrovascular conductance 𝐶𝑒𝑟𝑏𝑟𝑜𝑣𝑎𝑠𝑐𝑢𝑙𝑎𝑟 𝑐𝑜𝑛𝑑𝑢𝑐𝑡𝑎𝑛𝑐𝑒 = 𝐶𝐵𝐹𝑀𝐴𝑃 CVR in response to elevations in PETCO2 was calculated in both absolute (CVRAbs) and relative (CVRRel) terms, according to Equation 3 and Equation 4 respectively. 5.2.5.2 Dynamic onset responses to hypercapnia Prior to analysis of the dynamic response, the ICA hemodynamic bins (1 Hz) were passed through a median filter (with a rank of 7). This filter has been detailed previously in analysis of adult ICA responses to hypercapnia (Carter et al., 2016), and implemented in subsequent adult investigations by others (Hoiland et al., 2017; Iwamoto et al., 2018; Carr et al., 2020) Similar to previous experiments, mono-exponential modelling with a delay term (Equation 8) was used to explore the onset response of PETCO2, QICA, ICAv, ICASR, and ICAd to hypercapnia (GraphPad Prism v.9.0.1; GraphPad Software, San Diego, CA, USA). The response to hypercapnia of each participant was modelled from the onset of the 6% CO2 stimulus (0 s). Outliers within each participants’ modelled response were detected and removed to optimize fit of the mono-exponential model using the robust regression and outlier 72 removal method within the GraphPad software (Motulsky & Brown, 2006). Goodness of fit (r2 > 0.50) and normality of residuals were used to determine model acceptability. The MRT was calculated for QICA, ICAv, ICASR, and ICAd, as: Equation 10. Mean response time 𝑀𝑒𝑎𝑛 𝑟𝑒𝑠𝑝𝑜𝑛𝑠𝑒 𝑡𝑖𝑚𝑒 = 𝑇𝐷 + 𝜏 5.2.6 Statistical analysis Data normality was checked using the Shapiro-Wilk test (Ghasemi & Zahediasl, 2012) and subsequently verified from skewness and kurtosis for all data at baseline. Factorial ANOVAs were used to compare baseline to 4 min hypercapnic responses by time (BL vs. hypercapnia) and age (children vs. adults). Paired and unpaired t tests were used to deconstruct the ANOVA main effects and interactions where necessary. CVR was compared between age groups and sex using one-way ANOVAs. The kinetic parameters (DA, t, and MRT) were compared between age groups using one-way ANOVAs. Statistical significance was set a priori at P≤0.05. Statistical analyses were performed using SPSS (version 25, SPSS; Chicago, IL). Data are presented as mean ± SD, unless otherwise stated. 5.3 Results Data are presented for 31 of the 52 participants recruited: 14 children (6 males, 8 females) and 17 adults (10 males, 7 females). Of the 12 children who were excluded from analyses, 3 had baseline PETCO2 >2 SD below the child mean, 1 refused the duplex ultrasound assessment, 2 did not complete the hypercapnic challenge and 6 were excluded as a result of poor image quality of the vessel during the hypercapnic challenge (e.g. unclear vessel walls, excessive ICA movement). Of the adults excluded, 1 was a result of < 60 s of resting data, 5 had baseline PETCO2 >2 SD below the adult mean and 3 as a result of poor ICA image quality. 73 The mean age of the children was 9.8 ± 0.7 years (8.2 – 10.8 years). Stature was 142.4 ± 7.6 cm and mass was 33.9 ± 6.7 kg. Ten (5 girls, 5 boys) of the 14 children were Tanner stage 1 and 4 children (3 girls, 1 boy) were Tanner stage 2. Offset from aPHV ranged from -3.9 to -0.9 y, with a mean of -2.4 ± 1.0 y. The mean age of the 17 adults was 24.5 ± 1.8 y (20.8 - 27.5 y), stature was 172.3 ± 6.4 cm and mass was 70.9 ± 10.4 kg. 5.3.1 Baseline and steady state response to hypercapnia Values for all variables at baseline, during the last 30 s of the hypercapnic challenge, and the absolute delta (∆) are presented in Table 4. At baseline, children had a significantly higher HR and lower MAP than adults. Baseline PETCO2 was lower in children than adults. Baseline QICA, ICAv, ICASR, and CVC were all significantly higher in children. All variables (HR, MAP, PETCO2, PETO2, QICA, ICAv, ICAd, ICASR, CVCICA) increased in response to hypercapnia; however, the delta response was similar for children and adults, with the exception of ∆HR, that increased significantly more in children (see Table 4). 74 Table 6. Baseline and hypercapnic cardiovascular, respiratory, and vascular responses in children and adults. ANOVA main effects (P-value) Time Children (n = 14) Adults (n = 17) Age Time Age ´ Time HR (beats·min-1) BL HC ∆ 76 ± 7 90 ± 8 14 ± 6 66 ± 14 70 ± 12 5 ± 5* 0.016 0.001 0.001 MAP (mmHg) BL HC ∆ 75 ± 9 82 ± 11 7 ± 7 85 ± 11 91 ± 12 6 ± 6 0.018 0.001 0.738 PETCO2 (mmHg) BL HC ∆ 36.8 ± 2.3 46.2 ± 2.0 9.4 ± 2.3 39.3 ± 2.4 49.8 ± 2.1 10.4 ± 1.8 0.001 0.001 0.172 PETO2 (mmHg) BL HC ∆ 98.1 ± 4.6 133.3 ± 4.2 35.1 ± 5.1 95.0 ± 5.4 126.7 ± 4.3 31.7 ± 6.3 0.001 0.001 0.112 QICA (mL·min-1) BL HC ∆ 253.8 ± 55.1 385.7 ± 65.9 131.9 ± 44.3 210.0 ± 41.7 327.6 ± 63.2 117.6 ± 48.4 0.014 0.001 0.535 ICAv (cm·s-1) BL HC ∆ 59.7 ± 5.3 87.0 ± 9.4 27.3 ± 8.0 44.8 ± 8.5 67.0 ± 14.7 22.1 ± 10.0 0.001 0.001 0.142 ICAd (mm) BL HC ∆ 4.99 ± .43 5.09 ± .43 0.10 ± .14 5.15 ± .52 5.29 ± .52 0.14 ± .17 0.298 0.001 0.535 ICASR (s-1) BL HC ∆ 481.0 ± 61.3 690.0 ± 106.5 209.0 ± 72.2 353.9 ± 85.4 515.5 ± 139.7 161.7 ± 79.6 0.001 0.001 0.144 CVCICA (mL·min-1·mmHg-1) BL HC ∆ 3.44 ± .93 4.68 ± .85 1.24 ± .42 2.51 ± .59 3.62 ± .69 1.11 ± .38 0.001 0.001 0.352 Values are mean ± SD. Abbreviations: BL, baseline; HC, hypercapnia; ∆, absolute change between baseline and final 30 s of hypercapnia; HR, heart rate; MAP, mean arterial pressure; PETCO2, partial pressure of end-tidal carbon dioxide; PETO2, partial pressure of end-tidal oxygen; QICA, internal carotid artery blood flow; ICAv, internal carotid artery velocity; ICAd, internal carotid artery diameter; ICASR, internal carotid artery shear rate; CVCICA, internal carotid artery vascular conductance. Bold text indicates p<.05. * denotes a significant difference between children and adults, p<.05. There were no main effects of age for CVRAbs (children: 14.0 ± 7.1 ml·min-1·mmHg-1 vs. adults: 11.1 ± 4.1 ml·min-1·mmHg-1, p=0.130; Figure 9, panel a) or for CVRRel (children: 5.6 ± 2.5 %·mmHg-1 vs. adults: 5.4 ± 2.1 %·mmHg-1, p=0.792; Figure 9, panel b). 75 Figure 9. Relative and absolute cerebrovascular reactivity of the internal carotid artery to hypercapnia by age. A, Absolute CVR (CVRAbs) in children and adults. B, Relative CVR (CVRRel) in children and adults. 5.3.2 Dynamic onset responses to hypercapnia The typical hypercapnic onset response for PETCO2, ICASR, ICAv, and QICA for a representative child and adult are shown in Figure 10 and the mean response variables are provided in Table 7. The model fit was poor for ICAd and as a result we do not report the mono-exponential model. The model fit for the other variables was acceptable, with exclusion of data when r2 < 0.5. Two children and 1 adult had r2 < 0.5 for PETCO2, 1 adult had r2 < 0.5 for QICA, ICAv and ICASR. For these cases, a mean replacement imputation was used, resulting in imputation of 5.5% of the data (17 of 310 data points). Children Adults010203040CVRAbs (mL⋅min-1⋅mmHg-1 )Ap=0.130Children Adults051015CVRRel (%⋅mmHg-1 )Bp=0.792 76 Table 7. End-tidal carbon dioxide and internal carotid artery response kinetics to hypercapnia in children and adults. Children Adults ANOVA main effect (P-value) Parameter (n = 14) (n = 17) Age PETCO2 ∆A (mmHg) 𝜏 (s) 10.5 ± 1.9 28.5 ± 13.5 10.2 ± 1.5 29.8 ± 15.9 0.555 0.818 QICA ∆A (mL·min-1) 𝜏 (s) 143.0 ± 70.2 94.7 ± 56.7 120.5 ± 52.2 59.3 ± 37.4 0.313 0.046 ICAv ∆A (cm·s-1) 𝜏 (s) 29.4 ± 7.8 101.9 ± 57.1 21.9 ± 9.5 45.4 ± 29.7 0.025 0.001 ICASR ∆A (s-1) 𝜏 (s) 205.3 ± 72.6 70.4 ± 21.5 163.9 ± 81.3 40.7 ± 34.1 0.149 0.009 Values are mean ± SD. Abbreviations: PETCO2, partial pressure of end-tidal carbon dioxide; QICA, internal carotid artery blood flow; ICAv, internal carotid artery velocity; ICASR, internal carotid artery shear rate; ∆A, the change in amplitude from baseline to asymptote; 𝜏, the time constant of the response. Bold text indicates p<0.05. Children and adults reached a similar PETCO2 ∆A, with a comparable PETCO2 𝜏. There was an age difference for QICA 𝜏, with the child 𝜏 on average 35 s slower than adults. Despite a slower response in the children, the ∆A for QICA was similar between children and adults. Similarly, the ICAv 𝜏 was markedly slower in children; however, the ICAv ∆A was greater in children compared to adults. 77 Figure 10. The response to hypercapnia of a representative adult and child subject. The continuous black and red lines represent the monoexponential function in the children (open circles) and adults (red squares), respectively. The dark grey shaded area from -60 s to 0 s signifies baseline; time = 0 signifies the onset of the hypercapnic stimulus. Figure 11 illustrates a similar MRT in children and adults for PETCO2, but significantly slower ICAv, ICASR and QICA MRT in the children compared to the adults. ⋅0 60 120 180 240-5051015Δ PETCO2 (mmHg)Adult τChild τA0 60 120 180 240-1000100200300400Δ ICA SR (s-1)Adult τ Child τB0 60 120 180 240-1001020304050Time (s)Δ ICAv (cm⋅s-1)Adult τ Child τC0 60 120 180 240-50050100150200250Time (s)Δ QICA (ml⋅min-1)Child τAdult τD 78 Figure 11. Mean response time to hypercapnia in children and adults. Symbols represent individual data. Children are open circles, adults are open squares. Horizontal lines are mean values. *Significant difference between children and adults, p<0.05 5.4 Discussion This is the first study to explore ICA hemodynamic responses to hypercapnia in healthy children. We show ICAv, QICA and ICASR increased with steady state hypercapnia in both children and adults and the magnitude of these responses were similar after 4 min. The ICAd also increased in response to hypercapnia in both children and adults. Although ICAd could not be modelled, the analyzed kinetics did highlight a developmental-dependency on the temporal hemodynamic responses of the ICA to hypercapnia, with slower onset responses (𝜏 and MRT) for QICA, ICAv, and ICASR in children. A similar ∆A was noted for ICASR and QICA, but ∆A ICAv was greater in children than adults. 0100200300Mean Response Time (s)PETCO2 ICAv ICASR QICA✱✱✱ 79 5.4.1 Comparison of child and adult responses to steady state hypercapnia Baseline measures of ICAd, ICAv, QICA and ICASR in children in the present study align with those reported previously (Flück et al., 2017; Morris et al., 2017), as do the adult values (Smith et al., 2019; Carr et al., 2020). The magnitude of the hyperemic response following 4 min of steady state hypercapnia did not differ between children and adults. The corresponding values for CVR provide further support for this contention with no differences in absolute or relative CVR values between children and adults. Minimal research exists pertaining to the changes in extra-cranial vessel diameters that occur with growth and development. In the present study, we show similar baseline ICAd in children and adults. Previous work assessing ICAd from angiograms, at a similar site in relation to the carotid bifurcation as analyzed in our video recordings, found ICAd was considerably smaller in the young children (aged 3 – 9 y) compared to older children and adolescents (aged 10 – 19 y), who had similar ICAd to the adult group (Seong et al., 2005). A limitation of the Seong et al. (2005) work is the small sample – 36 participants, with only 6 in the 3-9 y age group, 7 in the 10-19 y age group, and 14 in the adult (20-36 y) group. Additionally, the 10-19 y age group likely included individuals of widely varying maturational status. While the present study has a similar number of adults, the larger number of children within a narrower age and maturity band suggest that ICAd is no different to adult size by 8-10 y of age. A larger longitudinal study of the morphology and ensuing hemodynamic properties of the extra-cranial arteries is needed to confirm this. Neither Seong and colleagues (2005) or this current study considered sex differences; as such, it would be imperative that hormonal changes and markers of maturation be included in future work. The average delta diameter during steady state hypercapnia was small, just 2.0% in children and 2.7% in adults. These values are similar to those previously reported for the ICA 80 (Hoiland et al., 2017; Carr et al., 2020) and were not significantly different between children and adults. Dilation of the cerebrovascular arteries is complex given there are many factors that may influence the diameter of the vessel during a hypercapnic challenge, such as changes in cerebrovascular tone due to increases in MAP (Battisti-Charbonney et al., 2011), which was noted in both children and adults in the current study. It is likely that, in keeping with prior findings (Hoiland et al., 2017), the sustained hypercapnic increase in MAP, as well as HR in the children, confounded the ability to discern the role shear stress plays in the regulation of ICAd. Additionally, we show an increase in PETO2 with steady state hypercapnia. Although PETO2 levels >250mmHg may cause a slight reduction in CBF (Willie et al., 2012), it is unlikely that the small changes in the current study would have any influence. It is clear that future studies in children will need to use alternative experimentation to hold PETO2 constant during hypercapnia and explore alternative protocols such as the transient hypercapnic test utilized in adults (Hoiland et al., 2019) so that changes in PETCO2 are not accompanied by increases in MAP and HR. 5.4.2 Comparison of child and adult ICA response kinetics to hypercapnia Although we were unable to interrogate the temporal sequence of blood flow, SR and dilation of the ICA, the response kinetics have provided unique insight into similarities and differences in the regulation of QICA in response to hypercapnia across developmental stages. The QICA MRT was considerably slower in children compared to young adults; however, this did not influence the magnitude of the QICA response, where the amplitude was commensurate with adult values. This dissociation between the amplitude and the MRT for QICA in children is intriguing. The rapid onset of response in QICA with hypercapnia in adults adequately washes out the CO2 and resulting H+ stimulus (Ogoh et al., 2009; Hoiland et al., 2019). The high baseline QICA in children may also enable washout of CO2 / H+ in response to the initial rise in FICO2 without any need for a rapid increase in QICA. With continued exposure to increased FICO2, QICA increases, albeit more slowly than in adults, and it is possible this reflects regulatory processes that reduce 81 pulsatile stress in an already highly perfused child brain (Zarrinkoob et al., 2016). Pulsatile flow in the MCA was about 50% of the PI in the carotid artery in 10 y old children (Lefferts et al., 2018) and pulsatile dampening is increased in more compliant arterial beds (Zarrinkoob et al., 2016). As such, the attenuated QICA onset response may reflect a greater preference for dampening pulsatile flow in the child brain. Future investigations of cerebral pulsatility in childhood and adolescence during alterations in FICO2 are needed, and should consider the complexity of cerebral arterial physiology by considering arterial stiffness, pulse wave forms in distal and proximal cerebral arterial beds and changes in pulsatile dampening with age, maturation and sex (Lefferts & Smith, 2021). Further, very little is known about development changes in the mechanisms of endothelial dependent or independent dilation of the conduit or resistance arteries. The magnitude of flow-mediated conduit artery dilation and SR stimuli is related in adults, but unrelated in children (Thijssen et al., 2009). Age-dependent changes in the primary mediators of dilation of the conduit and microcirculation have been noted in isolated arteries and arterioles, evolving from prostaglandins in childhood to nitric oxide in adults (Charpie et al., 1994; Beyer et al., 2017). In adults, non-endothelial dependent dilation of the MCA occurs in response to sublingual sodium nitroglycerin administration, but without increases in blood velocity, suggesting no alterations in the downstream cerebral vascular bed (Schulz et al., 2018). The influence differing vasoactive substances may have on the onset dilatory response of the ICA in children is unknown, and pharmacologic intervention with, for example, sodium nitroglycerin or indomethacin may provide insight into the role of the prostaglandins and nitric oxide. 5.4.3 Strengths & Limitations The findings presented here are, to the best of our knowledge, the first to assess the response of the ICA to hypercapnia in children in comparison to an adult group, implementing 82 mono-exponential analysis to investigate the temporal response in children. It is important to acknowledge this study is not without its limitations. Twenty-one participants were excluded from analysis, and while this data loss was nearly 40% of the data collected, the rigorous criteria of scan acceptability and exclusion criteria allows the authors to have confidence in these preliminary findings. Weaknesses include using a fixed concentration of CO2, which does not provide precise targeting of the desired increased in PETCO2 nor the ability to hold PETO2 constant (Hoiland et al., 2019). Future investigations would benefit from using an end-tidal forcing system or prospective gas targeting. Furthermore, bi-lateral and regional cerebrovascular heterogeneity has not been explored. The right and left ICA are not identical: the left is closer to the heart, arising directly from the aortic arch, whereas the right ICA originates from brachiocephalic arch. Whether this anatomical difference induces downstream morphological and hemodynamic differences is not known. Last, we do not consider how sex differences may influence ICA hemodynamics in the children or adults. There is evidence that ICA dilation increases from the low to the high estradiol phase of the menstrual cycle (Iwamoto et al., 2021) and assessment of monthly hormonal changes, albeit challenging, would be valuable for a more thorough developmental understanding of CBF regulation. 5.4.4 Summary These novel findings broaden our insight into the hemodynamic response to hypercapnia in children. We showed a similar steady state ICA reactivity in children, and hyperemic vasodilation. Kinetic modelling of the ICA hypercapnic onset response did not help interrogate the temporality between hemodynamic responses and dilation of the ICA, but does provide insight into developmental similarities and differences in the regulation of QICA. 83 Chapter 6: Cerebrovascular Response Compromised Following an Acute Bout of Uninterrupted Prolonged Sitting in Healthy Children: A Randomized Cross-over Trial 6.1 Background Sedentary behaviour had reached alarming levels in childhood before the COVID-19 pandemic (Saunders, 2014), but as children transitioned to a largely seated digital environment for schooling, as well as for social interaction during country-wide lockdowns and restrictions, sedentary time increased by an average of 160 minutes per day (Runacres et al., 2021). The health impact of increases in sedentary behaviour in childhood is not yet known, but this is worrisome given the evidence that excessive sedentary time is an independent risk factor for cardiovascular disease in both children and adults (Hamilton et al., 2008; Saunders et al., 2014). The muscular inactivity that accompanies excessive sedentary time, which is time largely spent seated or lying, results in well-documented deleterious outcomes, including detrimental shifts in metabolic processes, particularly glucose metabolism and alterations in cardiovascular function (Hamilton, 2018). In various models of enforced sitting, evidence indicates that acute bouts of sitting contribute to peripheral vascular deconditioning in adults and children (McManus et al., 2015; Thosar et al., 2015) and at least in adults these reductions are related to reduced shear stress, suggesting sitting alters endothelial integrity (Thosar et al., 2015). Far less is understood about the cerebrovascular changes that may accompany bouts of prolonged sitting, however, reductions in MCAv of 2.5% to 5.5% have been documented in adults following an acute bout of enforced sitting (Carter et al., 2018; Wheeler et al., 2019). Importantly, these declines were prevented by taking exercise breaks. To date, no study has examined the impact of a bout of prolonged sitting on CBF or cerebrovascular function in children, but Chapter 3 has shown a lower extracranial arterial shear rate was associated with high levels of sedentary behaviour in 84 children (>452 min of per day) (Tallon et al., 2021). This level of sedentary behaviour has become common among some populations during (Runacres et al., 2021) and given the evidence that lower shear stress decreases the availability of nitric oxide and increases the production of vasoconstrictors (Thosar et al., 2012), the impact of prolonged sitting on cerebrovascular vasodilatory function must be determined in children. In contrast to excessive sitting, light to moderate-intensity exercise activates metabolic pathways that appear to impact positively on brain perfusion [(Ellis et al., 2017; Tallon et al., 2019) see Appendix A] and cognitive function in children (Hillman et al., 2015). At least in adults, there is evidence that breaking up sitting with light intensity exercise increases cognitive function (Mullane et al., 2017), however, an exercise-induced increase in cognitive function has not been found to relate to alterations in brain blood flow in children (Pontifex et al., 2018). More sensitive markers of cerebrovascular function may be needed when examining relationships between excessive sitting, sedentary behaviour, and exercise. We [(Tallon et al., 2020), see Chapter 4] and others (Billinger et al., 2017; Weston et al., 2022) have shown that kinetic modelling of the onset response of the intra- and extra-cranial arteries to various stimuli, including CO2 and exercise, provides additional insight into the regulation of CBF, which may be important for understanding the impact of prolonged sitting on cerebrovascular function, as well as any protective effect breaking up sitting with exercise, may impart. Taken together, the extant literature would suggest prolonged sitting poses a significant health risk, but little is known about the effect of an acute bout of prolonged sitting on CBF or cerebrovascular function in children and importantly whether any sitting-induced cerebrovascular decrements can be prevented by exercise breaks. The purpose of this study, therefore, was to examine the effect of an acute bout of prolonged sitting on cerebrovascular blood flow and function in children and determine whether exercise breaks afford protection against sitting-induced dysfunction. We hypothesized that controlling for maturation, (i) 3 hours of uninterrupted 85 sitting in 8–11-year-old children will result in decreased cerebrovascular function (assessed from NVC and CVR), whereas 3 hours of sitting interrupted by hourly 10-minute exercise breaks will prevent these declines. 6.2 Methods 6.2.1 Participants Forty-two children and adolescents were recruited from the local community to participate in this study. Individuals were excluded if they were unable to exercise on a stationary exercise bike, had known congenital abnormalities or respiratory disease, had known high blood pressure, dyslipidemia or high insulin, or could not understand English. Written informed consent was obtained from the parents of the participants, alongside written and oral and written informed assent from the participants. All experimental procedures and protocols were approved by the University of British Columbia Clinical Research Board (H16-01324). 86 Figure 12. Progression of participants from the point of recruitment until completion of randomized experimental conditions. 6.2.2 Study design and procedures Figure 12 depicts the cross-over trial design with the following two experimental conditions: (i) uninterrupted sitting (Sit), in which participants remained seated for 3 h; and (ii) breaks in sitting time (Cycle), in which participants completed an identical 3 h bout of sitting as Sit, except they cycled for 10 min at a moderate-intensity one per each hour. The two conditions were completed on two separate days less than 28 days apart, the order of which was randomized. Participants visited the laboratory on three separate occasions, at the same time on each occasion. They were asked to report to the laboratory 2 hours after eating the same light, low fat meal at a scheduled time (between 8 AM and 10 AM) and asked to refrain from caffeine or alcohol, and strenuous exercise 24 hours before testing (Ainslie & Duffin, 2009). 42 Familiarization, Anthropometrics, & Exercise Test2 Lost to follow-up 2 Lost to follow-up17 Uninterrupted Sitting 18 Sitting + Cycling35 Entered cross-over trialand randomized7 Not studied further4 Lost to follow-up3 Excluded15 Sitting + Cycling16 Uninterrupted Sitting31 Included in data analysis 87 The first visit consisted of familiarization to the laboratory and to the protocols involved in the experimental conditions. Participants completed a baseline assessment of body composition and anthropometrics, followed by an exercise test on a cycle ergometer used to determine the intensity of the exercise breaks. They returned to the laboratory on two subsequent occasions, with a minimum of 24 hours between each visit, to complete the two experimental conditions. Figure 13. Experimental design of the two conditions. The two experimental conditions consisted of: I. Sit: Supervised uninterrupted sitting. Participants sat for 3 h with their feet on the ground and knees bent at 90 degrees. If a bathroom break was required, participants were pushed in an office chair on wheels to the bathroom to minimize movement. II. Cycle: Supervised interrupted sitting. Participants also sat for 3 h, but sitting was interrupted with a 10 min cycle ergometer exercise break each hour, cycling at an individualized moderate-intensity (90% of ventilatory threshold, determined from the exercise test). Three cycling breaks were completed at minutes 25-35, 85-95, and 145- 88 155. When not cycling, participants returned to sitting under the same guidelines as followed in the SIT condition noted above. Assessment of cerebrovascular function was completed before (Pre) and following (Post) each of the experimental conditions (see Figure 13). Following the Pre assessments, participants were taken to a mock sitting room, with comfortable seating and access to colouring books and iPads with a choice of parentally approved apps. These sources of entertainment were available to participants to increase the ecological validity of the study by replicating the home environment. Once seated, Pre circumference of the right calf at the widest point (Norton K & Olds, 1996) was recorded as an approximation of venous pooling that may have occurred during the sustained seated posture. For the duration of the two experimental conditions participants wore an activPAL micro-accelerometer to quantify total sitting time and total cycling time. Following the attachment of the micro-accelerometer to the thigh, the 3 h experimental condition commenced. Upon completion of the 3 h experimental condition, calf circumference was recorded and participants were wheeled in an office chair into the laboratory where Post assessment of cerebrovascular function was completed. 6.2.3 Measures 6.2.3.1 Body composition and maturation Assessment of body mass, stature and sitting height was completed with participants barefoot and in light clothing. Body mass was recorded to the nearest 0.1 kg (Tanita electronic scale; Tanita Corp, Arlington Heights, IL) and both stature and sitting height were recorded to the nearest 0.1 cm (Seca Portable Stadiometer; Seca, Hamburg, Germany). Right calf circumferences were measured to the nearest 0.1 cm, using an anthropometric tape, following the ISAK protocol (Norton & Olds, 1996). Body composition (fat mass and fat-free mass) was 89 assessed from a whole-body dual-energy X-ray absorptiometry (DXA) scan (Horizon DXA System, Hologic Canada ULC, Mississauga, Canada). Maturation was assessed from predicted aPHV using the Mirwald equation (Mirwald et al., 2002), which provides estimates of maturity offset from somatic measures. A negative offset value (≤ –1.0) indicates the participant has yet to reach aPHV (pre-PHV), a score between -1.0 and 1.0 indicates the participant is within the year that aPHV occurs (peri-PHV), and a positive offset value (≥ 1.0) indicates the participant has already passed aPHV (post-PHV). 6.2.3.2 Accelerometry Total sitting and cycling time during the experimental conditions was recorded using the activPAL micro-accelerometer (PAL Technologies Limited; Glasgow, Scotland, UK). Participants wore the device on the anterior aspect of the right thigh, placed within a flexible nitrile sleeve and attached using Tegaderm Transparent Film (3M Health Care; St. Paul, MN, USA). Leg-worn devices are the gold standard for the assessment of sedentary behaviour, and the activPAL has been validated for sedentary behaviour, step-based activity and posture in children (Aminian & Hinckson, 2012; Ridley et al., 2016). The activPAL micro-accelerometer was set at a sampling frequency of 20 Hz and data were interpolated in 2s bins using PALanalysis software (version 8, PAL Technologies, Glasgow, UK). The accelerometry data recorded during the experimental conditions was analyzed for total sitting time and total time cycling within the two experimental conditions. 6.2.3.3 Identification of the intensity of the exercise breaks Ventilatory threshold was identified using a ramp exercise test on a child sized, electro-magnetically braked cycle ergometer (Lode Pediatric Corival, Groningen, Netherlands). Following a three-minute unloaded warm-up, the increments were height dependent: 10 W increments for participants’ 110-125 cm in stature; or 15 W increments for participants 125-150 cm in stature. 90 Participants were asked to maintain a cadence of 70 – 80 revolutions per minute. Ventilatory threshold was confirmed using the V-slope method (Beaver et al., 1986) and the wattage (W) at 90% of ventilatory threshold was used as the intensity for the Cycle condition. 6.2.3.4 Cardiovascular measures Heart rate (HR) and blood pressure were measured continuously during PRE and POST assessments. HR was assessed using a three-lead electrocardiogram (ADInstruments BioAmp ML132, Colorado Springs, Colorado, USA), while blood pressure was assessed using a Finometer Pro (Finapres Medical Systems, Enschede, The Netherlands). All variables were sampled continuously at 1 kHz via an analog-to-digital converter (Powerlab, 16.30, ADInstruments, Colorado Springs, CO, USA) and down-sampled for processing at 1 Hz. MAP was calculated as: [(:; 𝐷𝐵𝑃) + (<; 𝑆𝐵𝑃)] (Gauer, 1960). 6.2.3.5 Cerebrovascular function The following describes the cerebrovascular assessments undertaken Pre and Post experimental conditions. The order presented below matches the order in which participants completed these measures. Data processing was completed blinded to the time point and condition. The NVC test was used to assess the temporal and spatial coupling of regional intra-cranial blood velocity and metabolic demand (Phillips et al., 2016). Intra-cranial blood velocity of the left PCA and right MCA was assessed using a 2 MHz transcranial Doppler (TCD) ultrasound (Spencer Technologies, Seattle, USA). Two TCD probes were attached to a headpiece (child-adapted M600 bilateral head frame; Spencer Technologies, Redmond, Washington, USA) and secured in order to insonate the blood vessels through the trans-temporal window by following established guidelines (Willie et al., 2011). Activation of the visual cortex was used to allow for 91 assessment of changes to the PCAv, in comparison to an assessment of regional comparison to the MCAv. The change in PCAv and MCAv from baseline in response to activation of the visual cortex was recorded over five cycles of repeating and alternating 30 s of exposure to eyes-closed, and 30 s of an eyes-open using a visual searching task. The visual searching task involved looking for Where’s Waldo characters (Smirl et al., 2016) and was presented via a PowerPoint presentation (Microsoft Office), automatically switching between a black screen and a random Where’s Waldo illustration. In order to standardize the transition an auditory cue was used at the transition point between eyes-open and eyes-closed to cue the children. The PCAv and MCAv response to the five cycles were averaged and analyzed using custom software developed in MATLAB (Phillips et al., 2016). A 40 s average before the start NVC test was used as baseline and a 25 s average during the eyes-closed / eyes-open cycles were used to calculate percent change from baseline. The hypercapnic reactivity protocol utilised in this study has previously been described in Chapter 4, see Section 4.2.3.3 (Tallon et al., 2020) and Chapter 5, see Section 5.2.4.2 (Tallon et al., 2022). In brief, following a 10 min period of resting supine, participants breathed room air for 2 min followed by 4 min of breathing a fixed concentration of 6% inspired CO2, administered in 21% O2, remainder N2. A three-way Hans Rudolph valve was used to switch between room air and a 20 L Douglas bag containing the 0.06 FICO2 Cardiorespiratory measures (PETCO2, PETO2, and VE) were assessed on a breath-by-breath basis and time-aligned with the cerebrovascular measures. The metabolic cart was calibrated prior to each test using gases of a known concentration and a 3-L syringe for volume calibration. Cerebrovascular measures included intra-cranial blood velocity of the MCA and PCA as described above and volumetric assessment of the ICA, A 15 MHz multi-frequency array vascular ultrasound probe (Terason T3200, Teratech, Burlington, MA) was used unilaterally (right side) for volumetric assessment of ICA blood velocity and vessel diameter. B-mode imaging was 92 used to measure arterial diameter, while pulse-wave mode was used to simultaneously measure peak blood velocity. Recordings were screen captured and stored as video files for offline analysis (Woodman et al., 2001). Technical recommendations were followed for all ICA measures (Thomas et al., 2015), including visual inspection before analysis. Exclusion of recordings was based on three criteria: i) the occurrence of an overt angle change, ii) excessive movement of the vessel as a result of high VE, and iii) overall poor image quality (e.g. unclear vessel walls). Synchronized diameter and velocity recordings allowed the calculation of QICA (and ICASR. Volumetric blood flow was calculated using Equation 1. gCBF was calculated as twice the sum of 𝑄st^ and 𝑄u^, and SR was calculated using Equation 2. Baseline values were calculated from the two minutes of supine rest and response values were averaged across the final 30 s of the four-minute hypercapnic test. Steady state CVR of the MCAv, PCAv, and QICA to the hypercapnic stimulus were computed as previously described in Chapter 4, see Section 4.2.4.1 (Tallon et al., 2020) and Chapter 5, see Section 5.2.5.1 (Tallon et al., 2022). Both absolute and relative steady state CVR were calculated using Equation 3 and Equation 4, respectively. The dynamic intra- and extra-cranial onset response to hypercapnia was calculated as previously described in Chapter 4, see Section 4.2.4.2 (Tallon et al., 2020), and Chapter 5, see Section 5.2.5.2 (Tallon et al., 2022). In brief the ICA hemodynamic bins (1 Hz) were passed through a median filter (with a rank of 7). A mono-exponential model with a delay term (Equation 8) was used to explore the onset response of MCAv, PCAv, QICA, and ICASR, to hypercapnia (GraphPad Prism v.9.0.1; GraphPad Software, San Diego, CA, USA). Subsequently, the MRT was calculated using Equation 10. 93 6.2.4 Statistical Analysis Statistical analyses were performed using SPSS 28.0 (SPSS, Chicago, IL, USA). All data are reported as mean ± standard deviation (SD). Normality was checked and verified using the Shapiro–Wilk normality test for variables at baseline. A Student’s t-test was used to compare baseline characteristics between boys and girls. Repeated measures analyses of variance (RM ANOVA) were used to examine the main effects of time (Pre and Post) and condition (Sit and Cycle), as well as interactions for the primary outcome variables. RM ANOVA analyses were completed with the inclusion of maturation (aPHV) as a covariate. Where necessary, main effects and interactions were deconstructed using paired samples t-tests. Statistical significance was set at p≤0.05. 6.3 Results Of the 35 participants randomized, 31 (age range: 7.8 to 13.1 years; 15 girls) completed the experimental conditions (Figure 12). Table 8 presents baseline characteristics. Boys were less mature than girls as indicated by the difference in predicted aPHV (p=0.004). Subsequent analyses included aPHV as a covariate. Boys had a lower body fat than the girls (p=0.003), but none of the participants were overweight or obese. Table 8. Participants’ demographic and anthropometrics. All Girls Boys Age, y 10.3 ± 1.4 10.1 ± 1.5 10.5 ± 1.3 Stature, cm 146.4 ± 11.7 143.6 ± 10.9 149.0 ± 12.1 Mass, kg 41.4 ± 13.6 42.3 ± 14.8 40.6 ± 12.7 Body Mass Index, m·kg-2 18.9 ± 4.13 20.0 ± 4.4 18.0 ± 3.7 aPHV (years offset) -2.1 ± 1.5 -1.3 ± 1.4 -2.8 ± 1.2 † Waist circumference*, cm 65.6 ± 9.1 64.2 ± 7.2 66.7 ± 10.5 BMC, kg 1.3 ± 0.3 1.2 ± 0.3 1.3 ± 0.3 Fat mass, kg 10.2 ± 6.6 11.9 ± 6.8 8.5 ± 6.1 Lean mass, kg 29.4 ± 8.3 28.6 ± 8.3 30.1 ± 7.8 Body Fat, % 23.3 ± 7.2 27.1 ± 5.2 19.8 ± 7.1 † Values are mean ± SD unless otherwise specified. Abbreviations: aPHV, predicted age at peak height velocity; BMC, bone mineral content. *Waist circumference was not recorded for two girls (n = 13). †p<0.05. 94 During the Cycle condition participants cycled at a mean intensity of 41.5 ± 13.6 W, and engaged in significantly less time sitting (146.9 ± 6.3 vs 178.4 ± 4.3 min, p<.001). There was no main effect for time (p=.643) or condition (p=.977) for calf circumference (Pre Cycle 30.2 ± 4.5 cm, Post Cycle 30.4 ± 4.4 cm vs. Pre Sit 30.2 ± 4.5 cm, Post Sit 30.5 ± 4.5 cm). 6.3.1 Neurovascular Coupling Of the 31 children who completed the experimental conditions, twelve did not complete the NVC test Pre and Post both experimental conditions, therefore data from the NVC test is presented on 19 participants (eight girls). Baseline and peak response did not differ significantly across time or by condition for any variable (Table 9). When accounting for baseline and assessing the change in both absolute and percentage terms, there was no significant difference across time or by condition for any variable. Table 9. Cardiovascular and cerebral neurovascular coupling parameters Pre and Post both experimental conditions. Pre Sit Post Sit Pre Cycle Post Cycle ANOVA main effects (P-value) Time Condition Time × Condition MAP (mmHg) BL Peak ΔAbs Δ% 70.0 ± 16.8 74.9 ± 18.6 4.9 ± 2.8 7.4 ± 3.8 65.5 ± 19.5 70.5 ± 19.1 5.0 ± 4.4 10.1 ± 11.0 65.5 ± 17.8 69.9 ± 18.6 4.4 ± 3.3 7.7 ± 7.2 65.6 ± 16.2 71.0 ± 17.1 5.4 ± 4.9 9.7 ± 11.4 .401 .474 .566 .117 .643 .653 .956 .990 .488 .407 .508 .841 HR (bpm) BL Peak ΔAbs Δ% 85 ± 11 92 ± 8 7 ± 5 8.7 ± 6.1 81 ± 11 88 ± 11 7 ± 4 9.7 ± 5.2 84 ± 9 91 ± 8 7 ± 6 8.9 ± 7.5 83 ± 10 92 ± 12 9 ± 8 12.1 ± 10.8 .506 .848 .708 .685 .912 .602 .389 .503 .267 .136 .490 .492 PCAv (cm.s-1) BL Peak ΔAbs Δ% 41.4 ± 10.9 52.5 ± 12.9 11.1 ± 4.2 28.1 ± 10.3 40.8 ± 10.0 52.6 ± 12.3 11.8 ± 3.5 29.9 ± 8.8 41.3 ± 10.4 52.7 ± 12.8 11.4 ± 3.7 28.3 ± 8.6 40.9 ± 10.9 51.6 ± 13.8 10.8 ± 4.5 27.2 ± 9.3 .969 .610 .273 .685 .995 .922 .740 .599 .929 .675 .316 .449 PCACVC (cm·s-1·mmHg-1) BL Peak ΔAbs Δ% 0.65 ± .32 0.88 ± .52 0.23 ± .21 34.7 ± 17.1 0.71 ± .36 0.94 ± .39 0.23 ± .12 36.1 ± 16.1 0.69 ± .27 0.93 ± .46 0.25 ± .21 33.9 ± 16.4 0.68 ± .31 0.86 ± .33 0.17 ± .14 29.3 ± 14.1 .174 .372 .670 .740 .976 .887 .689 .351 .598 .388 .278 .358 MCAv (cm·s-1) BL Peak ΔAbs Δ% 70.6 ± 7.4 78.4 ± 10.8 7.8 ± 5.1 11.2 ± 6.7 69.4 ± 8.9 78.0 ± 10.0 8.6 ± 3.6 13.0 ± 5.8 67.4 ± 18.0 75.2 ± 20.2 7.8 ± 5.2 11.4 ± 8.1 70.9 ± 9.0 77.3 ± 9.9 6.4 ± 3.7 9.7 ± 6.1 .723 .594 .071 .089 .786 .596 .155 .159 .287 .616 .353 .396 MCACVC (cm·s-1·mmHg-1) BL Peak ΔAbs Δ% 1.12 ± .46 1.31 ± .69 0.19 ± .24 15.8 ± 13.3 1.24 ± .67 1.44 ± .71 0.20 ± .16 19.0 ± 12.9 1.14 ± .56 1.32 ± .68 0.18 ± .21 15.2 ± 13.5 1.17 ± .36 1.30 ± .40 0.13 ± .20 12.5 ± 10.8 .212 .334 .808 .709 .888 .697 .387 .266 .679 .559 .470 .243 Values are mean ± SD. Abbreviations: MAP, mean arterial pressure; HR, heart rate; PCAv, posterior cerebral artery mean blood velocity; PCACVC, posterior cerebral artery cerebrovascular conductance index; MCAv, middle cerebral artery mean blood velocity; MCACVC, middle cerebral artery cerebrovascular conductance index; BL, baseline; ΔAbs, absolute change from baseline value to peak value; Δ%, change to peak relative to baseline value. 95 6.3.2 Baseline and steady-state responses to hypercapnia Absolute values for all variables at baseline and during the last 30 s of the 4 min hypercapnic challenge are presented in Table 10. Nine participants did not complete the hypercapnic challenge Pre and Post both experimental conditions. Of the 22 who did complete the hypercapnic challenge at all four points, two participants were excluded due to baseline data exceeding resting values (i.e. HR > 140 bpm, PETO2 > 130 mmHg, or PETCO2 < 25 mmHg) at 3 or more of the assessments. Additionally, of the 20 participants (8 girls) included in the analysis, not all participants had MCA, PCA, and ICA data collected, therefore the n for each vessel is presented in Table 10. Baseline HR, MAP, PETO2, PETCO2, MCAv, PCAv, ICASR, or ICAd revealed no significant effect of time, condition, or interaction at baseline (Table 10). A significant time by condition interaction was identified for baseline ICAv (p=0.029) and QICA (p=0.011), but not for hypercapnia. 96 Table 10. Assessment of intra- and extra-cranial arteries using duplex ultrasound while participants rested supine breathing room air. n PRE SIT POST SIT PRE CYCLE POST CYCLE ANOVA main effects (P-value) Time Condition Time × Condition HR 20 BL 78 ± 10 76 ± 12 78 ± 13 78 ± 11 .305 .764 .658 (beats·min-1) HC 91 ± 10 90 ± 13 90 ± 13 92 ± 13 .977 .883 .307 Δ 13 ± 5 13 ± 4 12 ± 6 14 ± 5 .272 .627 .411 MAP (mmHg) 20 BL 74.6 ± 10.3 72.9 ± 9.9 74.5 ± 13.1 75.8 ± 12.3 .513 .643 .399 HC 79.5 ± 9.6 77.8 ± 10.9 79.2 ± 11.6 79.5 ± 12.3 .827 .820 .567 Δ 4.9 ± 8.9 4.9 ± 3.7 4.7 ± 4.7 3.6 ± 6.8 .108 .379 .909 PETCO2 20 BL 44.1 ± 4.5 44.1 ± 4.7 44.6 ± 5.9 44.4 ± 4.9 .170 .807 .651 (mmHg) HC 52.9 ± 4.3 52.8 ± 4.1 53.5 ± 5.2 52.8 ± 4.6 .230 .864 .375 Δ 8.9 ± 1.5 8.7 ± 2.3 8.8 ± 2.7 8.4 ± 1.9 .828 .756 .724 PETO2 (mmHg) 20 BL 102.1 ± 4.4 98.4 ± 4.6 100.1 ± 5.8 98.4 ± 4.9 .450 .483 .161 HC 138.6 ± 6.4 138.5 ± 5.8 138.2 ± 6.1 138.8 ± 5.9 .682 .958 .418 Δ 36.6 ± 4.4 40.2 ± 4.7 38.5 ± 5.7 40.4 ± 6.0 .458 .460 .272 MCAv (cm·s-1) 19 BL 84.7 ± 14.5 83.7 ± 12.1 83.7 ± 15.5 84.7 ± 13.4 .517 .995 .622 HC 110.9 ± 17.3 109.1 ± 15.0 109.8 ± 20.4 108.2 ± 20.0 .798 .852 .966 Δ 26.2 ± 13.0 25.4 ± 12.6 26.1 ±14.0 23.6 ± 16.8 .466 .791 .770 PCAv (cm·s-1) 15 BL 51.6 ± 15.7 52.3 ± 16.5 49.9 ± 15.5 51.0 ± 16.3 .514 .781 .922 HC 67.1 ± 21.1 70.6 ± 28.5 62.6 ± 20.3 63.5 ± 21.5 .353 .465 .630 Δ 15.5 ± 9.6 18.3 ± 14.1 12.7 ± 6.7 12.4 ± 7.3 .336 .195 .308 ICAv (cm·s-1) 12 BL 57.1 ± 7.0 61.0 ± 8.5 59.1 ± 8.6 56.7 ± 10.3 .444 .743 .029 HC 78.5 ± 9.0 78.5 ± 8.7 79.5 ± 16.8 78.2 ± 8.9 .512 .931 .781 Δ 21.4 ± 5.2 17.5 ± 7.8 20.4 ± 13.0 21.2 ± 7.2 .831 .617 .269 ICASR (s-1) 12 BL 467.8 ± 73.5 485.4 ± 65.2 482.0 ± 92.7 469.5 ± 101.0 .853 .978 .325 HC 626.6 ± 109.1 618.3 ± 113.7 626.3 ± 159.6 616.1 ± 89.8 .713 .976 .968 Δ 158.8 ± 49.8 132.9 ± 68.4 144.3 ± 107.6 146.6 ± 58.8 .747 .988 .440 ICAd (mm) 12 BL 4.93 ± .40 5.02 ± .39 4.95 ± .41 4.95 ± .37 .532 .900 .498 HC 5.08 ± .41 5.10 ± .48 5.16 ± .39 5.12 ± .41 .460 .725 .633 Δ 0.16 ± .18 0.08 ± .28 0.22 ± 0.20 0.16 ± .14 .744 .355 .827 QICA 12 BL 240.5 ± 53.3 267.9 ± 64.6 253.6 ± 47.8 234.2 ± 46.1 .610 .613 .011 (mL·min-1) HC 337.1 ± 59.7 336.7 ± 82.1 353.4 ± 70.9 333.9 ± 71.8 .720 .790 .523 Δ 96.6 ± 36.2 68.8 ± 64.5 99.9 ± 49.5 99.7 ± 48.9 .927 .346 .243 Values are mean ± SD. Abbreviations: HR, heart rate; MAP, mean arterial blood pressure; MCA, middle cerebral artery; PCA, posterior cerebral artery; ICA, internal carotid artery. Bold indicates a significant main effect or interaction. 97 Figure 14. Relative cerebrovascular reactivity of the internal carotid artery Pre and Post experimental conditions. Circles represent the Sit condition and diamonds represent the Cycle condition. The CVRRel 𝑄st^of each participant is represented by a single colour at all assessments. **p=0.001 In both absolute and relative terms, there was no significant main effect of time or conditions on the CVR of the MCAv or PCAv (Table 11). There was a significant time by condition interaction of CVRRel 𝑄st^ (p=.049), with a lower CVRRel 𝑄st^ following Sit (CI: 0.8 – 2.8 %×mmHg-1, p=0.001; see Figure 14). PreSitPostSitPreCyclePostCycle-505101520CVRRel QICA (%⋅mmHg-1 )✱✱ 98 Table 11. Absolute and relative cerebrovascular reactivity Pre and Post experimental conditions. ANOVA main effects (P-value) n PRE SIT POST SIT PRE CYCLE POST CYCLE Time Condition Time × Condition MCAv CVRAbs (cm×s-1×mmHg-1) 19 2.9 ± 1.2 2.9 ± 1.0 3.1 ± 1.6 2.9 ± 2.1 .515 .817 .867 CVRRel (%×mmHg-1) 19 3.6 ± 1.5 3.5 ± 1.3 3.8 ± 2.5 3.5 ± 2.7 .356 .817 .792 PCAv CVRAbs (cm×s-1×mmHg-1) 15 1.8 ± 1.0 2.0 ± 1.3 1.6 ± 1.1 1.5 ± .9 .457 .346 .370 CVRRel (%×mmHg-1) 15 3.2 ± 1.3 3.7 ± 1.6 3.2 ± 1.6 3.0 ± 1.6 .798 .458 .441 𝑄st^ CVRAbs (cm×s-1×mmHg-1) 12 11.5 ± 4.9 8.3 ± 7.1 11.1 ± 6.1 12.0 ± 6.7 .916 .419 .184 CVRRel (%×mmHg-1) 12 5.0 ± 2.4 3.3 ± 2.8 4.4 ± 2.3 5.3 ± 3.4 .788 .459 .049 Values are mean ± SD. Abbreviations: MCAv, middle cerebral artery mean blood velocity; PCAv, posterior cerebral artery mean blood velocity; QICA, internal carotid artery blood flow; CVRAbs, absolute cerebrovascular reactivity; CVRRel, relative cerebrovascular reactivity. Bold indicates significance p<.05. 6.3.3 Dynamic onset response to hypercapnia The inclusion criteria of r2>0.5 was not met for the MCAv dynamic onset response of six participants, the PCAv dynamic onset response of five participants, or the ICASR and QICA dynamic onset response of four participants. There was no significant main effect of time, condition, or interaction for the 𝜏, ∆𝐴, or MRT of the PCAv, ICASR, or QICA (Table 12). A significant time by condition interaction was present for MCAv 𝜏 (p=0.05), with a slower 𝜏 following SIT (CI: -43.7 – 4.6 s, p=0.05; see Figure 15). Table 12. Dynamic responses at the onset of hypercapnia Pre and Post the experimental conditions. n PRE SIT POST SIT PRE CYCLE POST CYCLE ANOVA main effects (P-value) Time Condition Time × Condition MCAv ΔA (cm s-1) 13 29.8 ± 11.9 28.6 ± 11.2 27.4 ± 13.4 26.7 ± 11.4 .720 .583 .926 𝜏 (s) 13 57.2 ± 32.6 76.7 ± 55.2 64.1 ± 40.4 52.3 ± 28.8 .547 .529 .051 MRT (s) 13 60.1 ± 31.1 77.8 ± 55.2 77.0 ± 47.0 63.4 ± 42.5 .784 .934 .100 PCAv ΔA (cm s-1) 8 15.1 ± 6.5 13.7 ± 9.8 11.7 ± 6.2 13.6 ± 5.5 .495 .612 .227 𝜏 (s) 8 51.3 ± 34.7 34.7 ± 26.5 40.2 ± 34.0 21.3 ± 8.6 .439 .214 .906 MRT (s) 8 54.0 ± 32.0 35.5 ± 25.8 47.4 ± 35.7 25.2 ± 9.6 .296 .386 .855 ICASR ΔA (s-1) 8 176.1 ± 71.3 137.8 ± 35.3 206.6 ± 91.0 181.2 ± 57.2 .986 .075 .812 𝜏 (s) 8 79.8 ± 44.7 34.2 ± 23.1 63.1 ± 50.7 44.9 ± 31.2 .371 .372 .828 MRT (s) 8 90.9 ± 53.1 40.8 ± 23.0 85.4 ± 59.5 61.5 ± 43.5 .243 .673 .437 QICA ΔA (ml min-1) 8 116.5 ± 40.4 111.9 ± 38.8 132.5 ± 46.4 123.4 ± 55.5 .945 .402 .900 𝜏 (s) 8 68.1 ± 57.6 64.1 ± 40.9 71.1 ± 48.6 48.6 ± 31.0 .895 .683 .602 MRT (s) 8 72.1 ± 56.4 69.1 ± 39.9 88.3 ± 64.7 82.0 ± 56.0 .851 .424 .938 Values are mean ± SD. Abbreviations: MCA, middle cerebral artery; PCA, posterior cerebral artery; ICA, internal carotid artery; Q, volumetric blood flow; v, blood velocity; SR, shear rate; ΔA, amplitude; 𝜏, tau; MRT, mean response time. 99 Figure 15. Middle cerebral artery tau Pre and Post experimental conditions. Circles represent the Sit condition and diamonds represent the Cycle condition. The MCAv tau of each participant is represented by a single colour at all assessments. *p≤.05 6.4 Discussion This is the first study to demonstrate that 3 hours of uninterrupted sitting reduces CVR to CO2 and slows the onset response time (t) to hypercapnia in children. Importantly, when the 3 hours of sitting was broken up with a 10-minute exercise break each hour, these declines were prevented. Although we did not find a decline in intra-cranial blood velocity or extra-cranial blood flow, in support of our hypothesis, 3 hours of uninterrupted sitting reduced QICA CVR from 5.0% to 3.3% and slowed the MCAv hypercapnic onset response t by, on average, 19.5 s. PreSitPostSitPreCyclePostCycle050100150200MCAv τ (s)✱ 100 Previous work with adults has only shown a decline in MCAv, but not CVR, and concluded that the cerebrovasculature has a better functional capacity to resist sitting-induced vasodilatory deficits (Carter et al., 2018). Our prior findings that increased sedentary time was associated with a decline in SR suggested cerebrovascular vasodilatory function may be impacted by prolonged sitting in children, however, the decline in QICA CVR and correspondingly slower MCAv t we report were not accompanied by any change in SR. It has been proposed that sitting induced venous pooling in the lower limb, which in turn reduces stroke volume and may account for declines in cerebrovascular function (Hachiya et al., 2010); however, our surrogate measure of blood pooling, calf circumference, was unchanged during the intervention. It is most likely that sitting causes cardiometabolic changes in respiratory, cardiac and muscular function that in turn influence cerebrovascular processes (Chandrasekaran et al., 2021)(). These same parameters are positively impacted by exercise and is likely the reason when sitting is broken up with exercise the declines noted in MCAv and CVR by us and others are prevented (Carter et al., 2018; Wheeler et al., 2019). Impairments in CVR have been linked to cognitive decline in adults (Sabayan et al., 2012; Yang et al., 2017). The young brain has a high metabolic demand, that is met by a correspondingly high level of cerebral perfusion to meet this demand (Vandekar et al., 2019). As a result, it has been suggested that sitting-induced declines in CVR may predispose the child to greater cognitive maladaptation (Griffiths et al., 2021). We did not assess cognitive function in this study but we did assess NVC, which is thought to track cognitive function, but there was no impact of sitting on any of the NVC outcomes. It should be noted that in order to maintain ecological validity and compliance of the children, participants were allowed to entertain themselves as they pleased (i.e. personal electronic devices, colouring, homework, etc.). If the occipital lobe was continually being stimulated throughout the sitting bout, this maybe is enough to protect against the impact 101 of prolonged sitting and if this is the case, an important future question is what determines “good” and “bad” sitting. The participants of this present study were otherwise healthy, normal-weight children, and how these findings extend to other groups will require further investigation. Hypertensive, obese children have a reduced CVR, compared to peers, which was associated with poorer executive function (Kupferman et al., 2013). In addition, children who are obese experience significantly longer sedentary bouts and fewer active breaks compared to children of a healthy weight (McManus et al., 2011; Colley et al., 2013). Whether hypertensive, obese children would experience greater detriment to their cerebrovascular function following an acute bout of prolonged sitting, and whether this could be mitigated when prolonged sitting is interrupted is unknown. Furthermore, while we controlled for maturation as a covariate within analyses, the population within this study was comprised mostly of pre-PHV participants. Whether the impact of sitting varies throughout growth and development in childhood and adolescents will be important to establish. 6.4.1 Limitations This was a demanding and time-consuming project for the children and the families involved: comprised of three visits totalling approximately 15 h. As expected, there was a loss of participants from intake through completion of the study, however, despite the intensive protocol, the attrition rate is similar to other groups who have completed randomized cross-over trials in this population (Belcher et al., 2015). To maintain compliance, make involvement enjoyable, and maintain the ecological validity of the protocol the participants were allowed to use personal electronic devices or paper activities while sitting which likely impacted the NVC measure. Additionally, the use of fixed concentration of hypercapnia has limitations with regards to 102 individual variation in the change in PETCO2, and the inability to hold PETO2 constant (for a detailed discussion of this see Chapter 4 (Tallon et al., 2020)). 6.4.2 Summary This is the first to investigate the impact of an acute bout of prolonged sitting on the cerebrovascular function of children and to determine whether exercise breaks afforded any protection. While there were no significant decreases in NVC, there were thought-provoking detriments following an acute uninterrupted bout of sitting with a slowed MCAv dynamic onset response and a decreased CVRRel QICA. Whether fitness status or weight status in children would be influential to these detriments to cerebrovascular function is unknown. This is an important area to move forward and continue exploring as children sit more and more. 103 Chapter 7: General discussion 7.1 Summary of experimental findings The goals of this thesis were: (i) to examine relationships between habitual sedentary behaviour, physical activity, maturation, and resting cerebral hemodynamics; (ii) to investigate development differences in CVR and determine whether these be described by both steady state and dynamic onset responses to CO2; and (iii) to experimentally manipulate sitting time to assess the impact of uninterrupted sitting has on cerebral perfusion and cerebrovascular function, as well as the potential protection afforded by interrupting sitting with exercise breaks. This thesis provided novel findings that began in Chapter 3 with an initial exploration into the influence of sex and maturation on QCCA, QICA, QVA, and physical activity and sedentary behaviour in 78 children between the ages of 6–17 years. When co-varying for sex and pubertal status (indexed by aPHV) QICA and QVA showed no relationship to free-living physical activity. However, after controlling for sex and pubertal status (indexed by aPHV), a lower ICASR was reported in participants who engaged in more than 452 min of total sedentary behaviour per day (Tallon et al., 2021). To further probe the impact of sedentary behaviour on cerebrovascular function, gaining an understanding of the cerebrovascular function of children was imperative. Comparing the CVR of the MCA of children to adults is detailed in Chapter 4, whereas comparisons of the CVR of the ICA are detailed in Chapter 5. Chapter 4 found a similar steady-state CVR of the MCAv in children and adults, however, comparisons of the onset response of the MCAv and VE response to CO2 found several differences between children and adults. MCAv t was tightly coupled to PETCO2 t in adults, with VE t in lag, supporting the premise that CVR influences the central ventilatory CO2 chemoreflex (Ogoh et al., 2009). But this was not the case in the children, with MCAv t 42 s slower 104 than PETCO2 t, but similar to V̇x t. Indeed, Tallon et al. (2020) reported the onset MCAv response to hypercapnia using a mono-exponential kinetic model and showed a markedly slower MCAv t of 74 ± 28 s in 9–10-year-olds compared to 34 ± 18 s in the adults. This observation suggests an age dependence of the central ventilatory CO2 chemoreflex – cerebral blood flow interaction. Previously, research has shown increases in PETCO2 of approximately 15 mmHg led to significant dilation of the MCA (Verbree et al., 2014). While observing the CVR of the MCA in Chapter 4, if the documented hypercapnic hyperemia caused shear-mediated vasodilation in participants, then these results may be underestimating the change in cerebral perfusion. Therefore, while implementing the same hypercapnic protocol as described in Chapter 4, Chapter 5 endeavoured to compare the ICA response to hypercapnia in children compared to adults, accounting for ICAv, ICAd, ICASR, QICA. The CVR of the ICA was similar between children and adults, however, the ICAv, ICASR, and QICA t were slower in children, with the child QICA 𝜏 on average 35 s slower than adults, but with similar ∆A for QICA. These findings further support an age-dependent response to hypercapnia as observed in Chapter 4. With a better understanding of the assessment of cerebrovascular function in children gained through Chapter 4 and Chapter 5, combined with the relationship identified in Chapter 3 between ICASR and SedTime, Chapter 6 strived to understand the impact an acute bout of prolonged sitting has on cerebrovascular function in children. Implementing a randomized cross-over trial design, participants completed a 3 h acute bout of prolonged sitting and a 3 h acute bout of prolonged sitting with hourly exercise breaks. There was no impact of uninterrupted or interrupted sitting on NVC. In contrast, and of most interest, is the observed significant decrease in the CVR of the QICA following the uninterrupted bout of prolonged sitting, which was prevented when breaking up sitting with exercise breaks. Further, children experienced a significant slowing 105 of the MCAv t to CO2 following a 3 h acute bout of prolonged sitting, which again was not observed when sitting was interrupted with exercise breaks. 7.2 Implications of this work Before the COVID-19 Pandemic, sedentary behaviour had reached alarming levels in childhood (Saunders, 2014). During the first (Moore et al., 2020b) and second (Moore et al., 2021) waves of the pandemic, Canadian children were continually found to not be achieving the 24-hour movement guidelines, as families were restricted by the public health measures, closures and cancellations of active spaces (Riazi et al., 2021). As a result of public health measures, a transition to a largely seated, digital environment for schooling and social interactions occurred, resulting in sedentary time increasing by an average of 160 minutes per day (Runacres et al., 2021). The impact of this increasingly sedentary life has yet to be fully elucidated, but the findings from this thesis suggest cerebrovascular function may be compromised. Observations in Chapter 3 revealed, after controlling for sex and pubertal status (i.e. aPHV), a lower ICASR in participants who engaged in >452 min of total sedentary behaviour per day (Tallon et al., 2021). Furthermore, an acute bout of prolonged uninterrupted sitting in Chapter 6 resulted in a slowed MCAv onset response and a lowered CVR QICA, both markers of CBF regulation. Fortunately, this is prevented when breaking up sitting with exercise breaks, which suggests exercise breaks will be an important intervention in counteracting excessive sedentary behaviour. While the changes in cerebrovascular function noted in Chapter 6 are acute and likely transient, it is reasonable to consider from Chapter 3, that repeated exposure to sedentary behaviour in childhood may have important implications for long-term brain health. Sedentary aging in adulthood is associated with a longitudinal decline in CBF (Ainslie et al., 2008; Barnes et al., 2013), CVR (Bakker et al., 2004; Bailey et al., 2013), and autoregulation (Purkayastha et al., 2014), these impairments are known to increase the risk of cognitive decline, dementia 106 (Lautenschlager et al., 2012) and stroke (Okazawa et al., 2003). Recently, the cognitive function of young and older adults was resistant to a pharmacologically induced lowering of MCAv (31% below baseline) using indomethacin (Shoemaker et al., 2021). The authors associated this resilience of adult cognition with elevated cardiorespiratory fitness levels, suggesting habitual activity is protective. To date, there are no data documenting the impact of exercise training on cerebrovascular function in children or adolescents. 7.3 Limitations of this thesis The limitations of each study within this thesis have been discussed in detail within the experimental Chapters (Chapters 3, 4, 5, and 6). However, there are several overarching limitations present in this thesis deserving of further discussion. 7.3.1 Recruitment of participants Recruitment of participants within this thesis occurred based on two primary methods for recruitment: partnership with schools within the community or cold-calling from a database curated through previous research involvement or community events. Recruitment for Chapter 3, Chapter 4, and Chapter 5 were completed in partnership with local primary schools and this was a successful synergy. For example, participants included within Chapter 3 were a subset from a larger study which reported that of the 383 participants presented with consent and assent forms at a local school (i.e. the initial contact with guardians), 346 (90%) participants subsequently completed the study protocol and were included in data analysis (Koziol, 2021). In contrast, recruitment for Chapter 6 relied on a database of local families willing to be contacted for future involvement. A summary of the recruitment efforts of Chapter 6 is presented in Table 13. This study found that less than 40% of those initially contacted completed the study and were included in the data analysis, a dramatic decrease from Chapter 3. Despite a poorer uptake, Chapter 6 saw a similar attrition rate to other research within this population 107 (Belcher et al., 2015). It is important for future studies wishing to implement a protocol that requires multiple visits and greater time commitment from participants and their families to consider the recruitment methods and whether there is a better way to partner with community organizations which may lead to greater participant uptake and completion rates. Table 13. Summary of participant recruitment efforts, attrition, and completion rate for Chapter 6. Year Initial contact (n) Further information requested (n) Participants attending Visit 1 (n) Participants attending Visit 2 (n) Completed study and included in analysis (n) Percentage of completions over initial contact (%) 2017 22 12 10 10 8 36% 2018 46 33 26 19 16 35% 2019 14 9 7 7 7 50% Total 82 54 43 36 31 38% In order to increase success in recruitment through both partnerships with community organizations and, especially, when using a database curated through previous research involvement or community events, purposeful efforts in knowledge translation are essential for building interest and willingness to participate. Writing and publishing research findings and reviews in an age-appropriate manner may aid in fostering a reputation within the community, a reputation that will create community-wide interest in research and increase participation in research. An example of this is provided in Appendix B. Appendix B was prepared during the studies presented in this thesis, and it is hoped that it will achieve these goals for future work with children. 7.3.2 Research with pediatric populations Protocols tolerated by children and those that are ethical differ from those that can be implemented in adult studies. There are several considerations unique to working with the pediatric population that require special ethical guidance, as well as ensuring overall protection 108 of the child in a laboratory setting (Weikle, 2021). These ethical considerations influence the techniques that can be implemented in a pediatric population. For example, in adults a direct measure of PaCO2 can be made, alongside assessment of arterio-venous oxygen or CO2 difference using invasive techniques, this is simply not possible in children and PETCO2 remains the surrogate for PaCO2 in the child. Additionally, pharmaceutical interventions that have been used to probe mechanistic questions in adults around the regulation of CBF, such as the use of indomethacin to lower resting CBF, are unlikely to gain ethical approval in children. Within the pediatric research environment, it is of the utmost importance that researchers are cognizant of the autonomy of the child (Weikle, 2021). In an act of recognizing and respecting the child’s developing autonomy (Rossi et al., 2003), informed assent from the child is gathered to start their participation in research and continually obtained throughout the protocol. As reported throughout Chapter 6, there were several times that participants would complete the protocol on Visit 2, but revoke consent to a specific protocol on Visit 3. The child’s often unpredictable cooperation is difficult for the researcher given the downstream impact on analysis, but the autonomy of the child must be respected and always comes first. 7.3.3 Assessment and analysis of cerebrovascular function The primary method used within the thesis to investigate cerebrovascular function in children was CVR, using a 6% FICO2 challenge, in 21% O2 and remainder N2. This inspired CO2 challenge was coupled with both transcranial Doppler and Duplex ultrasound to assess the intra-cranial blood velocity and extra-cranial volumetric blood flow respectively. As highlighted in the comprehensive discussion of Chapter 4, within Section ‘4.4.4 Methodological considerations’, using a FICO2 stimulus is beneficial as an accessible and well-tolerated method for manipulation of gases, however, without the ability to hold PaO2 constant, investigations are unable to untangle chemoreceptive control. Future investigations, if possible, should consider holding PaO2 constant, 109 with the use of prospective gas targeting, to further probe an age-dependent chemoreceptive response. Additionally, prospective gas targeting could be used to probe the cerebrovascular response through a range of hypocapnic and hypercapnic stimuli to truly understand the role CO2 plays in the regulation of CBF in children. For the first time in children when probing CVR, data processing within Chapters 4, 5, and 6 included the implementation of dynamic onset kinetics to assess the onset response hypercapnic hemodynamic responses of the intra and extra-cranial vasculature. The dynamic onset analysis was largely exploited to understand the volume of oxygen uptake kinetic response. Various methodological studies have some certainty that for the kinetic response of the volume of oxygen uptake, multiple repeat trials are needed to account for the intra-individual variation of the response (Poole & Jones, 2012). This has yet to be confirmed when applied to the cerebrovascular response, but it is worth noting that intra-individual variation has been shown in the onset response of MCAv in adults (Poulin et al., 1996; Poulin et al., 1998). Future investigations will need to confirm the intra-individual response of children to a step increase in PaCO2. 7.3.4 Sex and maturation considerations The studies presented within this thesis used either assessment of predicted aPHV, or parental report of Tanner stage for pubic hair and genitalia for assessing maturation of participants. Maturation, when assessed from predicted aPHV offset using the Mirwald equation (Mirwald et al., 2002), estimates the maturity offset as either the time before reaching aPHV (i.e. a negative offset value, £ -1.0), the time at aPHV (i.e. a score > -1.0 but < 1.0) or the time after aPHV (i.e. a positive offset value, ³ 1.0). These estimates are made from somatic measures and should only be interpreted within ± 1.0. We therefore classified participants as pre-PHV (offset score £ -1.0) or peri-PHV (offset score > -1.0) (Malina, 2017). We also considered parental report 110 of Tanner stage for pubic hair and genitalia (Rasmussen et al., 2015). Tanner stage 1 is defined by the lack of secondary sexual characteristics i.e., no pubic hair, breast or genitalia development and considered pre-pubertal. Tanner stage 2 marks the onset of secondary sex characteristics i.e., sparse pubic hair, breast buds or onset of male genitalia growth and is considered early-pubertal (Marshall & Tanner, 1969; Marshall & Tanner, 1970). There are obvious limitations in grouping Tanner stages 1 through 3 together as ‘early pubertal’ given Tanner stage 3 is fairly well advanced in the appearance of secondary sexual characteristics. There are also problems with aligning girls and boys on the basis of pubic hair development. The assumption is that the timing of the appearance of pubic hair, as well as the tempo, is homogenous across the sexes. But stages are not equivalent, stage length is unknown, and the presence of asynchronous sexual maturation of pubic hair, breast, and genitalia compounds the problem (Malina, 2017). Only longitudinal data will confirm the true influence of age, sex, and maturation on the development trajectories of resting CBF and multiple methods for assessing maturation should be employed. 7.3.5 Study population and sample size The study populations within each of the four experimental Chapters was comprised of an overall health group of children (Chapter 3, 4, 5, and 6) and adults (Chapter 4 and 5). As a result, the results within this thesis may not be generalizable to other groups, if looking to apply the findings of this thesis to children with higher levels of body fat or a disease state (i.e. vascular disease). Notably, an effort was made to recruit large sample sizes for each of the studies within the experimental Chapters of this thesis. For example, the sample size within Chapter 4 and 5 was more than double the sample sizes comprising research into cerebrovascular function of adults. However, it should be noted that despite these efforts to achieve large sample sizes, the methods of analysis used in Chapter 4, 5, and 6, especially the monoexponential model analysis, resulted in a decrease in participants maintained through analysis. This led to low numbers and the results should be interpreted with caution as these smaller sample sizes may have impacted 111 the statistical power to detect real change and the generalizability of the findings. Future work will need to be completed to build on the findings of this thesis. Importantly, future research will need to be completed with a larger and more diverse sample population to fully elucidate the impact of physical activity and sedentary behaviour on cerebrovascular function in children. 7.4 Prospects for future research This thesis includes one of the first studies to reveal a detriment to cerebrovascular function following an acute bout of prolonged sitting in childhood. These novel findings presented within this thesis elicit numerous possibilities for future research to continue to develop and understanding of both cerebrovascular development across childhood and adolescence and the impact of both sedentary behaviour and physical activity. As discussed within the thesis, the chemoreceptive influence on CBF regulation will be best untangled through the use of prospective gas targeting by hold PaO2 steady and elevate PaCO2. Moving forward it will be critical to critique the techniques used within this thesis, and continue to find novel ways of exploring the impact of sedentary behaviour in both healthy children and those with various clinical conditions, with appropriate consideration given to the influence of sex and maturation. 7.4.1 Design of prolonged sitting and interruptions It will be crucial to probe the duration an acute bout of prolonged sitting has to be to adversely impact the cerebrovasculature. Future work should determine if there is a threshold, below which there are no detriments to cerebrovascular function. To date, adult research has used experimental designs with an acute bout prolonged sitting varying in duration from 3 h 40 min duration (Perdomo et al., 2019) to 4 h duration (Carter et al., 2018) and to 8 h duration (Wheeler et al., 2019). We used a 3 h periods of uninterrupted sitting for our experimental work. In the free-living scenario, we show a lower ICASR was associated with total sedentary time, but only when it exceeded 7.5 hours per day. This most likely includes longer periods of uninterrupted 112 sitting, but bouts of sitting of differing durations were not association with ICASR. In Chapter 3 we show that healthy children seldom engage in uninterrupted bouts of sitting for more than 2 h in duration. Indeed, our findings revealed that all participants experienced uninterrupted sitting for <0.5 h and 0.5-1 h; 80% of participants have uninterrupted sitting for 1-2 h in duration, but only 25% sat uninterrupted for more than 2 hours. It will also be important to translate the impact that single acute bouts of sitting have upon the cerebrovasculature to chronic sitting in a free-living setting. It will also be important to probe the modality, duration, and intensity of exercise breaks that may provide the best benefit – either for maintaining baseline cerebrovascular function, or for improvement above baseline levels. Adult research has implemented 2 min breaks, 10 min breaks, 5 min breaks, extending from positional changes from sitting to standing, light intensity walking breaks, to moderate-intensity cycling breaks, but findings are inconsistent. To date, no exercise training study, with the goal of improving cerebrovascular function, has been conducted with children and there is need for pediatric research to better understand the role exercise plays on cerebrovasculature both acutely and chronically. 7.5 Conclusion The work presented in this thesis suggests sedentary behaviour impacts cerebrovascular function in the child and adolescent. The scarceness of evidence on acute and chronic cerebrovascular responses to sedentary behaviour or exercise in the child or adolescent means the true impact on brain structure and function and future brain health has yet to be fully understood. The findings from this thesis have provided a novel foundation of an age dependent CVR response, and the impact of habitual and acute sedentary behaviour on cerebrovascular function. This is an emerging and exciting area of integrative paediatric exercise physiology and future investigations will provide insight into the mechanisms underlying cerebrovascular 113 adaptions to exercise and interactions with other physiological responses to exercise, as well as enriching our understanding of the potential pathways that link exercise to long-term brain health. 114 References Aaslid R, Markwalder TM & Nornes H. (1982). Noninvasive transcranial doppler ultrasound recording of flow velocity in basal cerebral arteries. J Neurosurg 57, 769-774. Adamo KB, Colley RC, Hadjiyannakis S & Goldfield GS. (2015). Physical activity and sedentary behavior in obese youth. J Pediatr 166, 1270-1275. Aggoun Y, Szezepanski I & Bonnet D. (2005). Noninvasive assessment of arterial stiffness and risk of atherosclerotic events in children. Pediatr Res 58, 173-178. Ainslie PN, Cotter JD, George KP, Lucas S, Murrell C, Shave R, Thomas KN, Williams MJ & Atkinson G. (2008). Elevation in cerebral blood flow velocity with aerobic fitness throughout healthy human ageing. J Physiol 586, 4005-4010. Ainslie PN & Duffin J. (2009). Integration of cerebrovascular co2 reactivity and chemoreflex control of breathing: Mechanisms of regulation, measurement, and interpretation. Am J Physiol Regul Integr Comp Physiol 296, R1473-1495. Ainslie PN & Hoiland RL. (2014). Transcranial doppler ultrasound: Valid, invalid, or both? J Appl Physiol 117, 1081-1083. Alpers BJ, Berry RG & Paddison RM. (1959). Anatomical studies of the circle of willis in normal brain. Arch Neurol Psychiatry 81, 409-418. Altenburg TM, Chinapaw MJ & Singh AS. (2016). Effects of one versus two bouts of moderate intensity physical activity on selective attention during a school morning in dutch primary schoolchildren: A randomized controlled trial. J Sci Med Sport 19, 820-824. Aminian S & Hinckson EA. (2012). Examining the validity of the activpal monitor in measuring posture and ambulatory movement in children. Int J Behav Nutr Phys Act 9, 1-9. Arnardottir NY, Koster A, Domelen DRV, Brychta RJ, Caserotti P, Eiriksdottir G, Sverrisdottir JE, Sigurdsson S, Johannsson E, Chen KY, Gudnason V, Harris TB, Launer LJ & Sveinsson T. (2016). Association of change in brain structure to objectively measured physical activity and sedentary behavior in older adults: Age, gene/environment susceptibility-reykjavik study. Behav Brain Res 296, 118-124. Arvidsson D, Johannesson E, Andersen LB, Karlsson M, Wollmer P, Thorsson O & Dencker M. (2018). A longitudinal analysis of the relationships of physical activity and body fat with nerve growth factor and brain-derived neural factor in children. J Phys Act Health 15, 620-625. Atkinson CL, Carter HH, Dawson EA, Naylor LH, Thijssen DH & Green DJ. (2015). Impact of handgrip exercise intensity on brachial artery flow-mediated dilation. Eur J Appl Physiol 115, 1705-1713. Bailey DM, Marley CJ, Brugniaux JV, Hodson D, New KJ, Ogoh S & Ainslie PN. (2013). Elevated aerobic fitness sustained throughout the adult lifespan is associated with improved cerebral hemodynamics. Stroke 44, 3235-3238. 115 Bakker MJ, Hofmann J, Churches OF, Badcock NA, Kohler M & Keage HAD. (2014). Cerebrovascular function and cognition in childhood: A systematic review of transcranial doppler studies. BMC Neurol 14, 1-12. Bakker SL, de Leeuw FE, den Heijer T, Koudstaal PJ, Hofman A & Breteler MM. (2004). Cerebral haemodynamics in the elderly: The rotterdam study. Neuroepidemiology 23, 178-184. Barker AR, Williams CA, Jones AM & Armstrong N. (2011). Establishing maximal oxygen uptake in young people during a ramp cycle test to exhaustion. Br J Sports Med 45, 498-503. Barnes JN, Taylor JL, Kluck BN, Johnson CP & Joyner MJ. (2013). Cerebrovascular reactivity is associated with maximal aerobic capacity in healthy older adults. J Appl Physiol 114, 1383-1387. Battisti-Charbonney A, Fisher J & Duffin J. (2011). The cerebrovascular response to carbon dioxide in humans. J Physiol 589, 3039-3048. Beaver WL, Wasserman K & Whipp BJ. (1986). A new method for detecting anaerobic threshold by gas exchange. J Appl Physiol 60, 2020-2027. Belcher BR, Berrigan D, Papachristopoulou A, Brady SM, Bernstein SB, Brychta RJ, Hattenbach JD, Tigner IL, Jr., Courville AB, Drinkard BE, Smith KP, Rosing DR, Wolters PL, Chen KY & Yanovski JA. (2015). Effects of interrupting children's sedentary behaviors with activity on metabolic function: A randomized trial. J Clin Endocrinol Metab 100, 3735-3743. Benveniste H, Dienel G, Jacob Z, Lee H, Makaryus R, Gjedde A, Hyder F & Rothman DL. (2018). Trajectories of brain lactate and re-visited oxygen-glucose index calculations do not support elevated non-oxidative metabolism of glucose across childhood. Front Neurosci 12, 631. Beyer AM, Zinkevich N, Miller B, Liu Y, Wittenburg AL, Mitchell M, Galdieri R, Sorokin A & Gutterman DD. (2017). Transition in the mechanism of flow-mediated dilation with aging and development of coronary artery disease. Basic Res Cardiol 112, 5. Billinger SA, Craig JC, Kwapiszeski SJ, Sisante JV, Vidoni ED, Maletsky R & Poole DC. (2017). Dynamics of middle cerebral artery blood flow velocity during moderate-intensity exercise. J Appl Physiol 122, 1125-1133. Bode H & Eden A. (1989). Transcranial doppler sonography in children. J Child Neurol 4, S68-S76. Bode H & Wais U. (1988). Age dependence of flow velocities in basal cerebral arteries. Arc Dis Child 63, 606-611. Bond B, Hind S, Williams CA & Barker AR. (2015). The acute effect of exercise intensity on vascular function in adolescents. Med Sci Sports Exerc 47, 2628-2635. Boyle LJ, Credeur DP, Jenkins NT, Padilla J, Leidy HJ, Thyfault JP & Fadel PJ. (2013). Impact of reduced daily physical activity on conduit artery flow-mediated dilation and circulating endothelial microparticles. J Appl Physiol 115, 1519-1525. 116 Bray S, Krongold M, Cooper C & Lebel C. (2015). Synergistic effects of age on patterns of white and gray matter volume across childhood and adolescence. eNeuro 2, 1-13. Brouwers PJAM, Vriens EM, Musbach M, Wieneke GH & van Huffelen AC. (1990). Transcranial pulsed doppler measurements of blood flow velocity in the middle cerebral artery: Reference values at rest and during hyperventilation in healthy children and adolescents in relation to age and sex. Ultrasound in Med & Biol 16, 1-8. Cairney J, Veldhuizen S, Kwan M, Hay J & Faught BE. (2014). Biological age and sex-related declines in physical activity during adolescence. Med Sci Sports Exerc 46, 730-735. Campero A, Rubino PA & Rhoton AL, Jr. (2011). Anatomy of the vertebral artery. In Pathology and surgery around the vertebral artery, ed. George B, Brunea M & Spetzler RF, pp. 29-40. Springer, France. Carr JMJR & Ainslie PN. (2020). Shearing the brain. J Appl Physiol 129, 599-602. Carr JMJR, Caldwell HG & Ainslie PN. (2021). Cerebral blood flow, cerebrovascular reactivity, and their influence on ventilatory sensitivity. Exp Physiol 106, 1425-1448. Carr JMJR, Hoiland RL, Caldwell HG, Coombs GB, Howe CA, Tremblay JC, Green DJ & Ainslie PN. (2020). Internal carotid and brachial artery shear-dependent vasodilator function in young healthy humans. J Physiol 598, 5333-5350. Carter HH, Atkinson CL, Heinonen IH, Haynes A, Robey E, Smith KJ, Ainslie PN, Hoiland RL & Green DJ. (2016). Evidence for shear stress-mediated dilation of the internal carotid artery in humans. Hypertension 68, 1217-1224. Carter SE, Draijer R, Holder SM, Brown L, Thijssen DHJ & Hopkins ND. (2018). Regular walking breaks prevent the decline in cerebral blood flow associated with prolonged sitting. J Appl Physiol 125, 790-798. Chaddock L, Erickson KI, Prakash RS, Kim JS, Voss MW, Vanpatter M, Pontifex MB, Raine LB, Konkel A, Hillman CH, Cohen NJ & Kramer AF. (2010). A neuroimaging investigation of the association between aerobic fitness, hippocampal volume, and memory performance in preadolescent children. Brain Res 1358, 172-183. Chaddock-Heyman L, Weng TB, Loui P, Kienzler C, Weisshappel R, Drollette ES, Raine LB, Westfall D, Kao SC, Pindus DM, Baniqued P, Castelli DM, Hillman CH & Kramer AF. (2021). Brain network modularity predicts changes in cortical thickness in children involved in a physical activity intervention. Psychophysiology 58, e13890. Chandrasekaran B, Pesola AJ, Rao CR & Arumugam A. (2021). Does breaking up prolonged sitting improve cognitive functions in sedentary adults? A mapping review and hypothesis formulation on the potential physiological mechanisms. BMC Musculoskelet Disord 22, 274. Charpie JR, Schreur KD, Papadopoulos SM & Webb RC. (1994). Endothelium dependency of contractile activity differs in infant and adult vertebral arteries. J Clin Invest 93, 1339-1343. 117 Claassen J, Thijssen DHJ, Panerai RB & Faraci FM. (2021). Regulation of cerebral blood flow in humans: Physiology and clinical implications of autoregulation. Physiol Rev 101, 1487-1559. Colley RC, Garriguet E, Janssen I, Wong SL, Saunders TJ, Carson V & Tremblay MS. (2013). The association between accelerometer-measured patterns of sedentary time and health risk in children and youth: Results for the canadian health measures survey. BMC Public Health 13, 1-9. Colman R & Walker S. (2004). The cost of physical inactivity in british columbia, pp. 1-27. GPI Atlantic. Contardo Ayala AM, Salmon J, Dunstan DW, Arundell L, Parker K & Timperio A. (2018). Longitudinal changes in sitting patterns, physical activity, and health outcomes in adolescents. Children 6, 1-10. Corrigan NM, Yarnykh VL, Hippe DS, Owen JP, Huber E, Zhao TC & Kuhl PK. (2021). Myelin development in cerebral gray and white matter during adolescence and late childhood. Neuroimage 10.1016/j.neuroimage.2020.117678. Coverdale NS, Gati JS, Opalevych O, Perrotta A & Shoemaker JK. (2014). Cerebral blood flow velocity underestimates cerebral blood flow during modest hypercapnia and hypocapnia. J Appl Physiol 117, 1090-1096. Cremer JE. (1982). Substrate utilization and brain development. J Cereb Blood Flow Metab 2, 394-407. Curtelin D, Morales-Alamo D, Torres-Peralta R, Rasmussen P, Martin-Rincon M, Perez-Valera M, Siebenmann C, Pérez-Suárez I, Cherouveim E, Sheel AW, Lundby C & Calbet JAL. (2017). Cerebral blood flow, frontal lobe oxygenation and intra-arterial blood pressure during sprint exercise in normoxia and severe acute hypoxia in humans. J Cereb Blood Flow Metab 38, 136-150. da Silva GO, Santini LB, Farah BQ, Germano-Soares AH, Correia MA & Ritti-Dias RM. (2022). Effects of breaking up prolonged sitting on cardiovascular parameters: A systematic review. Int J Sports Med 43, 97-106. Davis CL, Tomporowski PD, McDowell JE, Austin BP, Miller PH, Yanasak NE, Allison JD & Naglieri JA. (2011). Exercise improves executive function and achievement and alters brain activation in overweight children: A randomized, controlled trial. Health Psychol 30, 91-98. Dawson EA, Cable NT, Green DJ & Thijssen DHJ. (2018). Do acute effects of exercise on vascular function predict adaptation to training? Eur J Appl Physiol 118, 523-530. de Onis M, Onyango AW, Borghi E, Siyam A, Nishida C & Siekmann J. (2007). Development of a who growth reference for school-aged children and adolescents. Bull World Health Organ 85, 660-667. 118 Deoni SC, Dean DC, 3rd, O'Muircheartaigh J, Dirks H & Jerskey BA. (2012). Investigating white matter development in infancy and early childhood using myelin water faction and relaxation time mapping. Neuroimage 63, 1038-1053. Dienel GA. (2019). Brain glucose metabolism: Integration of energetics with function. Physiol Rev 99, 949-1045. Donnelly JE, Hillman CH, Castelli D, Etnier JL, Lee S, Tomporowski P, Lambourne K & Szabo-Reed AN. (2016). Physical activity, fitness, cognitive function, and academic achievement in children: A systematic review. Med Sci Sports Exerc 48, 1223-1224. Drollette ES, Shishido T, Pontifex MB & Hillman CH. (2012). Maintenance of cognitive control during and after walking in preadolescent children. Med Sci Sports Exerc 44, 2017-2024. Dunstan DW, Dogra S, Carter SE & Owen N. (2021). Sit less and move more for cardiovascular health: Emerging insights and opportunities. Nat Rev Cardiol 18, 637-648. Edgell H, Robertson AD & Hughson RL. (2012). Hemodynamics and brain blood flow during posture change in younger women and postmenopausal women compared with age-matched men. J Appl Physiol 112, 1482-1493. Ellis LA, Ainslie PN, Armstrong VA, Morris LE, Simair RG, Sletten NR, Tallon CM & McManus AM. (2017). Anterior cerebral blood velocity and end-tidal co2 responses to exercise differ in children and adults. Am J Physiol Heart Circ Physiol 312, H1195-H1202. Engeroff T, Fuzeki E, Vogt L, Fleckenstein J, Schwarz S, Matura S, Pilatus U, Deichmann R, Hellweg R, Pantel J & Banzer W. (2018). Is objectively assessed sedentary behavior, physical activity and cardiorespiratory fitness linked to brain plasticity outcomes in old age? Neuroscience 388, 384-392. Fierstra J, Sobczyk O, Battisti-Charbonney A, Mandell DM, Poublanc J, Crawley AP, Mikulis DJ, Duffin J & Fisher JA. (2013). Measuring cerebrovascular reactivity: What stimulus to use? J Physiol 591, 5809-5821. Fisher JA. (2016). The co2 stimulus for cerebrovascular reactivity: Fixing inspired concentrations vs. Targeting end-tidal partial pressures. J Cereb Blood Flow Metab 36, 1004-1011. Fisher JP, Hartwich D, Seifert T, Olesen ND, McNulty CL, Nielsen HB, van Lieshout JJ & Secher NH. (2013). Cerebral perfusion, oxygenation and metabolism during exercise in young and elderly individuals. J Physiol 591, 1859-1870. Fisher JP, Ogoh S, Young CN, Raven PB & Fadel PJ. (2008). Regulation of middle cerebral artery blood velocity during dynamic exercise in humans: Influence of aging. J Appl Physiol 105, 266-273. Fletcher EA, Salmon J, McNaughton SA, Orellana L, Wadley GD, Bruce C, Dempsey PC, Lacy KE & Dunstan DW. (2018). Effects of breaking up sitting on adolescents' postprandial glucose after consuming meals varying in energy: A cross-over randomised trial. J Sci Med Sport 21, 280-285. 119 Flück D, Morris LE, Niroula S, Tallon CM, Sherpa KT, Stembridge M, Ainslie PN & McManus AM. (2017). Ubc-nepal expedition: Markedly lower cerebral blood flow in high-altitude sherpa children compared with children residing at sea level. J Appl Physiol 123, 1003-1010. Gauer OH. (1960). Kreislauf des blutes. In Lehrbuch der physiologie des menschen, ed. Landois L & Rosemann HU, pp. 95. Urban & Schwarzenberg, Munich. Gavlak JC, Stocks J, Laverty A, Fettes E, Bucks R, Sonnappa S, Cooper J, Grocott MP, Levett DZ, Martin DS, Imray CH & Kirkham FJ. (2013). The young everest study: Preliminary report of changes in sleep and cerebral blood flow velocity during slow ascent to altitude in unacclimatised children. Arch Dis Child 98, 356-362. Ghasemi A & Zahediasl S. (2012). Normality tests for statistical analysis: A guide for non-statisticians. Int J Endocrinol Metab 10, 486-489. Giedd JN, Blumenthal J, Jeffries NO, Castellanos FX, Liu H, Zijdenbos A, Paus T, Evans AC & Rapoport JL. (1999). Brain development during childhood and adolescence: A longitudinal mri study. Nat Neurosci 2, 861-863. Goldfield GS, Kenny GP, Prud'homme D, Holcik M, Alberga AS, Fahnestock M, Cameron JD, Doucette S, Hadjiyannakis S, Tulloch H, Tremblay MS, Walsh J, Guerin E, Gunnell KE, D'Angiulli A & Sigal RJ. (2018). Effects of aerobic training, resistance training, or both on brain-derived neurotrophic factor in adolescents with obesity: The hearty randomized controlled trial. Physiol Behav 191, 138-145. Gomez-Garcia M, Bia D & Zocalo Y. (2021). Physical activity, sedentary behavior and sleep time: Association with cardiovascular hemodynamic parameters, blood pressure and structural and functional arterial properties in childhood. J Cardiovasc Dev Dis 8, 1-25. Goyal MS, Hawrylycz M, Miller JA, Snyder AZ & Raichle ME. (2014). Aerobic glycolysis in the human brain is associated with development and neotenous gene expression. Cell Metab 19, 49-57. Gozal D, Arens R, Omlin KJ, Marcus CL & Keens TG. (1994). Maturational differences in step vs. Ramp hypoxic and hypercapnic ventilatory responses. J Appl Physiol 76, 1968-1975. Gratas-Delamarche A, Mercier J, Ramonatxo M, Dassonville J & Préfaut C. (1993). Ventilatory response of prepubertal boys and adults to carbon dioxide at rest and during exercise. Eur J Appl Physiol 66, 25-30. Green DJ, Hopman MT, Padilla J, Laughlin MH & Thijssen DH. (2017). Vascular adaptation to exercise in humans: Role of hemodynamic stimuli. Physiol Rev 97, 495-528. Griffiths TD, Talbot JS, Douglas AJM, Richards CT & Lord RN. (2021). Exercised state of mind: A perspective on ageing, cerebral blood flow and cognition. J Physiol 599, 2523-2524. Groen MA, Whitehouse AJ, Badcock NA & Bishop DV. (2012). Does cerebral lateralization develop? A study using functional transcranial doppler ultrasound assessing lateralization for language production and visuospatial memory. Brain Behav 2, 256-269. 120 Grolimund P & Seiler RW. (1988). Age dependence of the flow velocity in the basal cerebral arteries: A transcranial doppler ultrasound study. Ultrasound in Med & Bio 14, 191-198. Haapala EA, Vaisto J, Veijalainen A, Lintu N, Wiklund P, Westgate K, Ekelund U, Lindi V, Brage S & Lakka TA. (2017). Associations of objectively measured physical activity and sedentary time with arterial stiffness in pre-pubertal children. Pediatr Exerc Sci 29, 326-335. Hachiya T, Walsh ML, Saito M & Blaber AP. (2010). Delayed vasoconstrictor response to venous pooling in the calf is associated with high orthostatic tolerance to lbnp. J Appl Physiol 109, 996-1001. Hamilton MT. (2018). The role of skeletal muscle contractile duration throughout the whole day: Reducing sedentary time and promoting universal physical activity in all people. J Physiol 596, 1331-1340. Hamilton MT, Healy GN, Dunstan DW, Zderic TW & Owen N. (2008). Too little exercise and too much sitting: Inactivity physiology and the need for new recommendations on sedentary behavior. Curr Cardiovasc Risk Rep 2, 292-298. Hartman YAW, Tillmans LCM, Benschop DL, Hermans ANL, Nijssen KMR, Eijsvogels TMH, Willems P, Tack CJ, Hopman MTE, Claassen J & Thijssen DHJ. (2021). Long-term and acute benefits of reduced sitting on vascular flow and function. Med Sci Sports Exerc 53, 341-350. He L, Wu DF, Zhang JH, Zheng S, Li Y & He W. (2022). Factors affecting transtemporal window quality in transcranial sonography. Brain Behav 12, e2543. Herting MM & Nagel BJ. (2013). Differences in brain activity during a verbal associative memory encoding task in high- and low-fit adolescents. J Cogn Neurosci 25, 595-612. Hillman CH, Khan NA & Kao SC. (2015). The relationship of health behaviors to childhood cognition and brain health. Ann Nutr Metab 66 Suppl 3, 1-4. Hillman CH, Pontifex MB, Raine LB, Castelli DM, Hall EE & Kramer AF. (2009). The effect of acute treadmill walking on cognitive control and academic achievement in preadolescent children. Neuroscience 159, 1044-1054. Hoiland RL & Ainslie PN. (2016). Crosstalk proposal: The middle cerebral artery diameter does change during alterations in arterial blood gases and blood pressure. J Physiol 594, 4073-4075. Hoiland RL, Ainslie PN, Wildfong KW, Smith KJ, Bain AR, Willie CK, Foster G, Monteleone B & Day TA. (2015). Indomethacin-induced impairment of regional cerebrovascular reactivity: Implications for respiratory control. J Physiol 593, 1291-1306. Hoiland RL, Bain AR, Rieger MG, Bailey DM & Ainslie PN. (2016). Hypoxemia, oxygen content, and the regulation of cerebral blood flow. Am J Physiol Regul Integr Comp Physiol 310, R398-413. 121 Hoiland RL, Fisher JA & Ainslie PN. (2019). Regulation of the cerebral circulation by arterial carbon dioxide. Compr Physiol 9, 1101-1154. Hoiland RL, Smith KJ, Carter HH, Lewis NCS, Tymko MM, Wildfong KW, Bain AR, Green DJ & Ainslie PN. (2017). Shear-mediated dilation of the internal carotid artery occurs independent of hypercapnia. Am J Physiol Heart Circ Physiol 313, H24-H31. Howe CA, Caldwell HG, Carr J, Nowak-Fluck D, Ainslie PN & Hoiland RL. (2020). Cerebrovascular reactivity to carbon dioxide is not influenced by variability in the ventilatory sensitivity to carbon dioxide. Exp Physiol 105, 904-915. Hsieh SS, Chueh TY, Morris TP, Kao SC, Westfall DR, Raine LB, Hopman RJ, Pontifex MB, Castelli DM, Kramer AF & Hillman CH. (2020). Greater childhood cardiorespiratory fitness is associated with better top-down cognitive control: A midfrontal theta oscillation study. Psychophysiology 57, e13678. Iadecola C. (2017). The neurovascular unit coming of age: A journey through neurovascular coupling in health and disease. Neuron 96, 17-42. Iqbal S. (2013). A comprehensive study of the anatomical variations of the circle of willis in adult human brains. J Clin Diagn Res 7, 2423-2427. Ishizu T, Ishimitsu T, Yanagi H, Seo Y, Obara K, Moriyama N, Watanabe S & Yamaguchi I. (2004). Effect of age on carotid arterial intima-media thickness in childhood. Heart Vessels 19, 189-195. Iwamoto E, Bock JM & Casey DP. (2018). Hypercapnia-induced shear-mediated dilation in the internal carotid artery is blunted in healthy older adults. Am J Physiol Heart Circ Physiol 315, H1279-H1286. Iwamoto E, Sakamoto R, Tsuchida W, Yamazaki K, Kamoda T, Neki T, Katayose M & Casey DP. (2021). Effects of menstrual cycle and menopause on internal carotid artery shear-mediated dilation in women. Am J Physiol Heart Circ Physiol 320, H679-H689. Janssen M, Toussaint HM, van Mechelen W & Verhagen EALM. (2014). Effects of acute bouts of physical activity on children’s attention: A systematic review of the literature. SpringerPlus 3. Júdice PB, Hetherington-Rauth M, Northstone K, Andersen LB, Wedderkopp N, Ekelund U, Sardinha LB & International Children's Accelerometry Database C. (2020). Changes in physical activity and sedentary patterns on cardiometabolic outcomes in the transition to adolescence: International children's accelerometry database 2.0. J Pediatr 225, 166-173. Katzmarzyk PT, Gledhill N & Shephard RJ. (2000). The economic burden of physical inactivity in canada. CMAJ 163, 1435-1440. Keir DA, Duffin J, Millar PJ & Floras JS. (2019). Simultaneous assessment of central and peripheral chemoreflex regulation of muscle sympathetic nerve activity and ventilation in healthy young men. J Physiol 597, 3281-3296. 122 Kempf KS, Whitaker AA, Lui Y, Witte E, Perdomo SJ, Ward JL, Eickmeyer S, Ledbetter L, Abraham M & Billinger SA. (2019). The effect of stroke on middle cerebral artery blood flow velocity dynamics during exercise. J Neurol Phys Ther 43, 212-219. Kennedy C & Sokoloff L. (1957). An adaptation of the nitrous oxide method to the study of the cerebral circulation in children; normal values for cerebral blood flow and cerebral metabolic rate in childhood. J Clin Invest 36, 1130-1137. Kooijman M, Thijssen DH, de Groot PC, Bleeker MW, van Kuppevelt HJ, Green DJ, Rongen GA, Smits P & Hopman MT. (2008). Flow-mediated dilatation in the superficial femoral artery is nitric oxide mediated in humans. J Physiol 586, 1137-1145. Koziol AV. (2021). Using thigh-worn accelerometry to explore the effects of day of the week, age, sex, and maturation on children and adolescent’s physicoal activity, posture, and time in bed patterns. In School of Health and Exercise Sciences. University of British Columbia, Kelowna, Canada. Krause DN, Duckles SP & Pelligrino DA. (2006). Influence of sex steroid hormones on cerebrovascular function. J Appl Physiol 101, 1252-1261. Kupferman JC, Lande MB, Adams HR & Pavlakis SG. (2013). Primary hypertension and neurocognitive and executive functioning in school-age children. Pediatr Nephrol 28, 401-408. Kuzawa CW, Chugani HT, Grossman LI, Lipovich L, Muzik O, Hof PR, Wildman DE, Sherwood CC, Leonard WR & Lange N. (2014). Metabolic costs and evolutionary implications of human brain development. Proc Natl Acad Sci USA 111, 13010-13015. Labrecque L, Rahimaly K, Imhoff S, Paquette M, Le Blanc O, Malenfant S, Drapeau A, Smirl JD, Bailey DM & Brassard P. (2019). Dynamic cerebral autoregulation is attenuated in young fit women. Physiol Rep 7, e13984. Lake SL, Guadagni V, Kendall KD, Chadder M, Anderson TJ, Leigh R, Rawling JM, Hogan DB, Hill MD & Poulin MJ. (2022). Aerobic exercise training in older men and women-cerebrovascular responses to submaximal exercise: Results from the brain in motion study. Physiol Rep 10.14814/phy2.15158. Lassen NA. (1959). Cerebral blood flow and oxygen consumption in man. Physiol Rev 39, 183-238. Lautenschlager NT, Cox K & Cyarto EV. (2012). The influence of exercise on brain aging and dementia. Biochim Biophys Acta 1822, 474-481. Leatherdale ST & Ahmed R. (2011). Screen-based sedentary behaviours among a nationally representative sample of youth: Are canadian kids couch potatoes? Chronic Dis Inj Can 31, 141-146. Lee IM, Shiroma EJ, Lobelo F, Puska P, Blair SN & Katzmarzyk PT. (2012). Effect of physical inactivity on major non-communicable diseases worldwide: An analysis of burden of disease and life expectancy. The Lancet 380, 219-229. 123 Lefferts WK, DeBlois JP, Gump BB & Heffernan KS. (2018). Carotid artery stiffness and cerebral pulsatility in children. Artery Res 22, 64-67. Lefferts WK & Smith KJ. (2021). Let's talk about sex, let's talk about pulsatility, let's talk about all the good things and the bad things of mcav. J Appl Physiol 130, 1672-1674. Leung J, Kosinski PD, Croal PL & Kassner A. (2016). Developmental trajectories of cerebrovascular reactivity in healthy children and young adults assessed with magnetic resonance imaging. J Physiol 594, 2681-2689. Lima NS, Krishna H, Gerber BS, Heffernan KS, Gump BB & Lefferts WK. (2021). Physical activity is associated with lower pulsatile stress but not carotid stiffness in children. J Hum Hypertens 10.1038/s41371-021-00506-7. MacLean JE, DeHaan K, Fuhr D, Hariharan S, Kamstra B, Hendson L, Adatia I, Majaesic C, Lovering AT, Thompson RB, Nicholas D, Thebaud B & Stickland MK. (2016). Altered breathing mechanics and ventilatory response during exercise in children born extremely preterm. Thorax 71, 1012-1019. Malina RM. (2017). Assessment of biological maturation. In Oxford textbook of children’s sport and exercise medicine, 3rd edn, ed. Armstrong N & van Mechelen W, pp. 3-24. Oxford University Press, Oxford. Marcus C, Glomb W, Basinski D, Ward SD & Keens T. (1994). Development of hypercapnic and hypoxic ventilatory responses from childhood to adulthood. J Appl Physiol 76, 314-320. Marinoni M, Ginanneschi A, Forleo P & Amaducci L. (1997). Techical limits in transcranial doppler recording: Inadequate acoustic windows. Ultrasound in Med & Biol 23, 1275-1277. Marinoni M, Ginanneschi A, Inzitari D, Mugnai S & Amaducci L. (1998). Sex-related differences in human cerebral hemodynamics. Acta Neurologica Scandinavica 97, 324-327. Mark CI, Slessarev M, Ito S, Han J, Fisher JA & Pike GB. (2010). Precise control of end-tidal carbon dioxide and oxygen improves bold and asl cerebrovascular reactivity measures. Magn Reson Med 64, 749-756. Markus H & Cullinane M. (2001). Severely impaired cerebrovascular reactivity predicts stroke and tia risk in patients with carotid artery stenosis and occlusion. Brain 124, 457-467. Markus HS & Boland M. (1992). “Cognitive activity” monitored by non-invasive measurement of cerebral blood flow velocity and its application to the investigation of cerebral dominance. Cortex 28, 575-581. Marlatt KL, Kelly AS, Steinberger J & Dengel DR. (2013). The influence of gender on carotid artery compliance and distensibility in children and adults. J Clin Ultrasound 41, 340-346. Marshall WA & Tanner JM. (1969). Variations in pattern of pubertal changes in girls. Arch Dis Child 44, 291-303. Marshall WA & Tanner JM. (1970). Variations in the pattern of pubertal changes in boys. Arch Dis Child 45, 13-23. 124 Martin DJ, Wells ITP & Goodwin CR. (2015). Physics of ultrasound. Anaesth Intensive Care Med 16, 132-135. Mast IH, Baas KPA, Jorstad HT, Wood JC, Nederveen AJ & Bakermans AJ. (2022). Dynamic mr imaging of cerebral perfusion during bicycling exercise. Neuroimage 10.1016/j.neuroimage.2022.118961. McCue MC, Marlatt KL, Kelly AS, Steinberger J & Dengel DR. (2012). Evaluation of gender differences in endothelium-independent dilation using peripheral arterial tonometry. Clin Physiol Funct Imaging 32, 94-98. McManus AM, Ainslie PN, Green DJ, Simair RG, Smith K & Lewis N. (2015). Impact of prolonged sitting on vascular function in young girls. Exp Physiol 100, 1379-1387. McManus AM, Chu EY, Yu CC & Hu Y. (2011). How children move: Activity pattern characteristics in lean and obese chinese children. Journal of Obesity 2011, 679328. Meijer A, Konigs M, Vermeulen GT, Visscher C, Bosker RJ, Hartman E & Oosterlaan J. (2020). The effects of physical activity on brain structure and neurophysiological functioning in children: A systematic review and meta-analysis. Dev Cogn Neurosci 45, 1-15. Mills A, Rosenberg M, Stratton G, Carter HH, Spence AL, Pugh CJ, Green DJ & Naylor LH. (2013). The effect of exergaming on vascular function in children. J Pediatr 163, 806-810. Minhas JS, Panerai RB & Robinson TG. (2018). Sex differences in cerebral haemodynamics across the physiological range of paco2. Physiol Meas 39, 105009-105018. Mirwald RL, Baxter-Jones ADG, Bailey DA & Beunen GP. (2002). An assessment of maturity from anthropometric measurements. Med Sci Sports Exerc 34, 689-694. Moore SA, Cumming SP, Balletta G, Ramage K, Eisenmann JC, Baxter-Jones ADG, Jackowski SA & Sherar LB. (2020a). Exploring the relationship between adolescent biological maturation, physical activity, and sedentary behaviour: A systematic review and narrative synthesis. Ann Hum Biol 47, 365-383. Moore SA, Faulkner G, Rhodes RE, Brussoni M, Chulak-Bozzer T, Ferguson LJ, Mitra R, O'Reilly N, Spence JC, Vanderloo LM & Tremblay MS. (2020b). Impact of the covid-19 virus outbreak on movement and play behaviours of canadian children and youth: A national survey. Int J Behav Nutr Phys Act 17, 85. Moore SA, Faulkner G, Rhodes RE, Vanderloo LM, Ferguson LJ, Guerrero MD, Brussoni M, Mitra R, O'Reilly N, Spence JC, Chulak-Bozzer T & Tremblay MS. (2021). Few canadian children and youth were meeting the 24-hour movement behaviour guidelines 6-months into the covid-19 pandemic: Follow-up from a national study. Appl Physiol Nutr Metab 46, 1225-1240. Mora-Gonzalez J, Migueles JH, Esteban-Cornejo I, Cadenas-Sanchez C, Pastor-Villaescusa B, Molina-Garcia P, Rodriguez-Ayllon M, Rico MC, Gil A, Aguilera CM, Escolano-Margarit MV, Gejl AK, Andersen LB, Catena A & Ortega FB. (2019). Sedentarism, physical activity, steps, and neurotrophic factors in obese children. Med Sci Sports Exerc 51, 2325-2333. 125 Morris LE, Fluck D, Ainslie PN & McManus AM. (2017). Cerebrovascular and ventilatory responses to acute normobaric hypoxia in girls and women. Physiol Rep 5, 1-9. Motulsky HJ & Brown RE. (2006). Detecting outliers when fitting data with nonlinear regression - a new method based on robust nonlinear regression and the false discovery rate. BMC Bioinformatics 7, 123. Mullane SL, Buman MP, Zeigler ZS, Crespo NC & Gaesser GA. (2017). Acute effects on cognitive performance following bouts of standing and light-intensity physical activity in a simulated workplace environment. J Sci Med Sport 20, 489-493. Mundel T, Perry BG, Ainslie PN, Thomas KN, Sikken EL, Cotter JD & Lucas SJ. (2015). Postexercise orthostatic intolerance: Influence of exercise intensity. Exp Physiol 100, 915-925. Murrell CJ, Cotter JD, Thomas KN, Lucas SJ, Williams MJ & Ainslie PN. (2013). Cerebral blood flow and cerebrovascular reactivity at rest and during sub-maximal exercise: Effect of age and 12-week exercise training. Age (Dordr) 35, 905-920. Norton K & Olds T, ed. (1996). Anthropometrica: A textbook of body measurement for sports and health courses. UNSW Press, Sydney, Australia. Norton K & Olds T, ed. (1996). Anthropometrica: A textbook of body measurement for sports and health courses. UNSW Press, Sydney, Australia. Ogoh S, Ainslie PN & Miyamoto T. (2009). Onset responses of ventilation and cerebral blood flow to hypercapnia in humans: Rest and exercise. J Appl Physiol 106, 880-886. Ogoh S, Hayashi N, Inagaki M, Ainslie PN & Miyamoto T. (2008). Interaction between the ventilatory and cerebrovascular responses to hypo- and hypercapnia at rest and during exercise. J Physiol 586, 4327-4338. Ogoh S, Suzuki K, Washio T, Tamiya K, Saito S, Bailey TG, Shibata S, Ito G & Miyamoto T. (2019). Does respiratory drive modify the cerebral vascular response to changes in end-tidal carbon dioxide? Exp Physiol 104, 1363-1370. Ohuchi H, Kato Y, Tasato H, Arakaki Y & Kamiya T. (1999). Ventilatory response and arterial blood gases during exercise in children. Pediatr Res 45, 389-396. Okazawa H, Yamauchi H, Toyoda H, Sugimoto K, Fujibayashi Y & Yonekura Y. (2003). Relationship between vasodilatation and cerebral blood flow increase in impaired hemodynamics: A pet study with the acetazolamide test in cerebrovascular disease. J Nucl Med 44, 1875-1883. Owen N, Sugiyama T, Eakin EE, Gardiner PA, Tremblay MS & Sallis JF. (2011). Adults' sedentary behavior determinants and interventions. Am J Prev Med 41, 189-196. Paniukov D, Lebel RM, Giesbrecht G & Lebel C. (2020). Cerebral blood flow increases across early childhood. Neuroimage 204, 116224. 126 Perdomo SJ, Gibbs BB, Kowalsky RJ, Taormina JM & Balzer JR. (2019). Effects of alternating standing and sitting compared to prolonged sitting on cerebrovascular hemodynamics. Sport Sci Health 15, 375-383. Perry BG, Lucas SJ, Thomas KN, Cochrane DJ & Mundel T. (2014). The effect of hypercapnia on static cerebral autoregulation. Physiol Rep 2. Phillips AA, Chan FH, Zheng MM, Krassioukov AV & Ainslie PN. (2016). Neurovascular coupling in humans: Physiology, methodological advances and clinical implications. J Cereb Blood Flow Metab 36, 647-664. Pontifex MB, Gwizdala KL, Weng TB, Zhu DC & Voss MW. (2018). Cerebral blood flow is not modulated following acute aerobic exercise in preadolescent children. Int J Psychophysiol 134, 44-51. Poole DC & Jones AM. (2012). Oxygen uptake kinetics. Compr Physiol 2, 933-996. Portegies ML, de Bruijn RF, Hofman A, Koudstaal PJ & Ikram MA. (2014). Cerebral vasomotor reactivity and risk of mortality: The rotterdam study. Stroke 45, 42-47. Poulin MJ, Liang P-J & Robbins PA. (1996). Dynamics of the cerebral blood flow response to step changes in end-tidal pco2 and po2 in humans. J Appl Physiol 81, 1084-1095. Poulin MJ, Liang P-J & Robbins PA. (1998). Fast and slow components of cerebral blood flow response to step decreases in end-tidal pco2 in humans. J Appl Physiol 85, 388-397. Prigent-Tessier A, Quirie A, Maguin-Gate K, Szostak J, Mossiat C, Nappey M, Devaux S, Marie C & Demougeot C. (2013). Physical training and hypertension have opposite effects on endothelial brain-derived neurotrophic factor expression. Cardiovasc Res 100, 374-382. Purkayastha S, Fadar O, Mehregan A, Salat DH, Moscufo N, Meier DS, Guttmann CR, Fisher ND, Lipsitz LA & Sorond FA. (2014). Impaired cerebrovascular hemodynamics are associated with cerebral white matter damage. J Cereb Blood Flow Metab 34, 228-234. Quistorff B, Secher NH & Van Lieshout JJ. (2008). Lactate fuels the human brain during exercise. FASEB J 22, 3443-3449. Rasmussen AR, Wohlfahrt-Veje C, Tefre de Renzy-Martin K, Hagen CP, Tinggaard J, Mouritsen A, Mieritz MG & Main KM. (2015). Validity of self-assessment of pubertal maturation. Pediatrics 135, 86-93. Rauber SB, Boullosa DA, Carvalho FO, de Moraes JF, de Sousa IR, Simoes HG & Campbell CS. (2014). Traditional games resulted in post-exercise hypotension and a lower cardiovascular response to the cold pressor test in healthy children. Front Physiol 5, 1-7. Riazi NA, Wunderlich K, Gierc M, Brussoni M, Moore SA, Tremblay MS & Faulkner G. (2021). "You can't go to the park, you can't go here, you can't go there": Exploring parental experiences of covid-19 and its impact on their children's movement behaviours. Children (Basel) 8. 127 Ridley K, Ridgers ND & Salmon J. (2016). Criterion validity of the activpaltm and actigraph for assessing children's sitting and standing time in a school classroom setting. Int J Behav Nutr Phys Act 13, 1-5. Robba C, Goffi A, Geeraerts T, Cardim D, Via G, Czosnyka M, Park S, Sarwal A, Padayachy L, Rasulo F & Citerio G. (2019). Brain ultrasonography: Methodology, basic and advanced principles and clinical applications. A narrative review. Intensive Care Med 10.1007/s00134-019-05610-4. Rosen DS. (2004). Physiologic growth and development during adolescence. Pediatr in Rev 25, 194-200. Rosengarten B, Aldinger C, Spiller A & Kaps M. (2003). Neurovascular coupling remains unaffected during normal aging. J Neuroimaging 13, 43-47. Rossi WC, Reynolds W & Nelson RM. (2003). Child assent and parental permission in pediatric research. Theor Med Bioeth 24, 131-148. Runacres A, Mackintosh KA, Knight RL, Sheeran L, Thatcher R, Shelley J & McNarry MA. (2021). Impact of the covid-19 pandemic on sedentary time and behaviour in children and adults: A systematic review and meta-analysis. Int J Environ Res Public Health 18. Sabayan B, Jansen S, Oleksik AM, van Osch MJ, van Buchem MA, van Vliet P, de Craen AJ & Westendorp RG. (2012). Cerebrovascular hemodynamics in alzheimer's disease and vascular dementia: A meta-analysis of transcranial doppler studies. Ageing Res Rev 11, 271-277. Saeki N & Rhoton AL, Jr. (1977). Microsurgical anatomy of the upper basilar artery and the posterior circle of willis. J Neurosurg 46, 563-578. Satterthwaite TD, Shinohara RT, Wolf DH, Hopson RD, Elliott MA, Vandekar SN, Ruparel K, Calkins ME, Roalf DR, Gennatas ED, Jackson C, Erus G, Prabhakaran K, Davatzikos C, Detre JA, Hakonarson H, Gur RC & Gur RE. (2014). Impact of puberty on the evolution of cerebral perfusion during adolescence. PNAS 111, 8643-8648. Saunders TJ. (2014). The health impact of sedentary behaviour in children and youth. Applied Physiology, Nutrition, and Metabolism 39, 402-402. Saunders TJ, Chaput JP, Goldfield GS, Colley RC, Kenny GP, Doucet E & Tremblay MS. (2013). Prolonged sitting and markers of cardiometabolic disease risk in children and youth: A randomized crossover study. Metabolism 62, 1423-1428. Saunders TJ, Chaput JP & Tremblay MS. (2014). Sedentary behaviour as an emerging risk factor for cardiometabolic diseases in children and youth. Can J Diabetes 38, 53-61. Scammon RE. (1930). The measurement of the body in childhood. In The measurement of man, ed. Harris JA, Jackson CM, Paterson DG & Scammon RE. University of Minnesota Press, Minnesota. Schoning M & Hartig B. (1996). Age dependence of total cerebral blood flow volume from childhood to adulthood. J Cereb Blood Flow Metab 16, 827-833. 128 Schoning M, Staab M, Walter J & Niemann G. (1993). Transcranial color duplex sonography in childhood and adolescence. Age dependence of flow velocities and waveform parameters. Stroke 24, 1305-1309. Schulz JM, Al-Khazraji BK & Shoemaker JK. (2018). Sodium nitroglycerin induces middle cerebral artery vasodilatation in young, healthy adults. Exp Physiol 103, 1047-1055. Semmler L, Weberruss H, Baumgartner L, Pirzer R & Oberhoffer-Fritz R. (2021). Vascular diameter and intima-media thickness to diameter ratio values of the carotid artery in 642 healthy children. Eur J Pediatr 180, 851-860. Seong J, Lieber BB & Wakhloo AK. (2005). Morphological age-dependent development of the human carotid bifurcation. J Biomech 38, 453-465. Sherar LB, Cumming SP, Eisenmann JC, Baxter-Jones AD & Malina RM. (2010). Adolescent biological maturity and physical activity: Biology meets behavior. Pediatr Exerc Sci 22, 332-349. Shoemaker LN, Wilson LC, Lucas SJE, Machado L, Walker RJ & Cotter JD. (2021). Indomethacin markedly blunts cerebral perfusion and reactivity, with little cognitive consequence in healthy young and older adults. J Physiol 599, 1097-1113. Skow RJ, MacKay CM, Tymko MM, Willie CK, Smith KJ, Ainslie PN & Day TA. (2013). Differential cerebrovascular co(2) reactivity in anterior and posterior cerebral circulations. Respir Physiol Neurobiol 189, 76-86. Smirl JD, Wright AD, Bryk K & van Donkelaar P. (2016). Where's waldo? The utility of a complicated visual search paradigm for transcranial doppler-based assessments of neurovascular coupling. J Neurosci Methods 270, 92-101. Smith EC, Pizzey FK, Askew CD, Mielke GI, Ainslie PN, Coombes JS & Bailey TG. (2021). Effects of cardiorespiratory fitness and exercise training on cerebrovascular blood flow and reactivity: A systematic review with meta-analyses. Am J Physiol Heart Circ Physiol 321, H59-H76. Smith KJ & Ainslie PN. (2017). Regulation of cerebral blood flow and metabolism during exercise. Exp Physiol 102, 1356-1371. Smith KJ, Hoiland RL, Grove R, McKirdy H, Naylor L, Ainslie PN & Green DJ. (2019). Matched increases in cerebral artery shear stress, irrespective of stimulus, induce similar changes in extra-cranial arterial diameter in humans. J Cereb Blood Flow Metab 39, 849-858. Smith KJ, Wildfong KW, Hoiland RL, Harper M, Lewis NC, Pool A, Smith SL, Kuca T, Foster GE & Ainslie PN. (2016). Role of co2 in the cerebral hyperemic response to incremental normoxic and hyperoxic exercise. J Appl Physiol 120, 843-854. Springer C, Cooper DM & Wasserman K. (1988). Evidence that maturation of the peripheral chemoreceptors is not complete in childhood. Respir Physiol 74, 55-64. 129 Szabo-Reed AN, Willis EA, Lee J, Hillman CH, Washburn RA & Donnelly JE. (2017). Impact of three years of classroom physical activity bouts on time-on-task behavior. Med Sci Sports Exerc 49, 2343-2350. Taddei S, Virdis A, Ghiadoni L, Magagna A & Salvetti A. (1998). Vitamin c improves endothelium-dependent vasodilation by restoring nitric oxide activity in essential hypertension. Circulation 97, 2222-2229. Takahashi T, Shirane R, Sato S & Yoshimoto T. (1999). Developmental changes of cerebral blood flow and oxygen metabolism in children. Am J Neuroradiol 20, 917-922. Tallon CM, Barker AR, Nowak-Flück D, Ainslie PN & McManus AM. (2020). The influence of age and sex on cerebrovascular reactivity and ventilatory response to hypercapnia in children and adults. Exp Physiol 105, 1090-1101. Tallon CM, Simair RG, Koziol AV, Ainslie PN & McManus AM. (2019). Intracranial vascular responses to high-intensity interval exercise and moderate-intensity steady-state exercise in children. Pediatr Exerc Sci 31, 290-295. Tallon CM, Smith KJ, Nowak-Fluck D, Koziol AV, Rieger MG, Lutes LD, Green DJ, Tremblay MS, Ainslie PN & McManus AM. (2021). The influence of sex and maturation on carotid and vertebral artery hemodynamics and associations with free-living (in)activity in 6-17-year-olds. J Appl Physiol 131, 1575-1583. Tallon CM, Talbot JS, Smith KJ, Lewis N, Nowak-Fluck D, Ainslie PN & McManus AM. (2022). Dynamic onset response of the internal carotid artery to hypercapnia is blunted in children compared with adults. Physiol Rep 10, e15406. Taylor FC, Pinto AJ, Maniar N, Dunstan DW & Green DJ. (2022). The acute effects of prolonged uninterrupted sitting on vascular function: A systematic review and meta-analysis. Med Sci Sports Exerc 54, 67-76. Thijssen DH, Bullens LM, van Bemmel MM, Dawson EA, Hopkins N, Tinken TM, Black MA, Hopman MT, Cable NT & Green DJ. (2009). Does arterial shear explain the magnitude of flow-mediated dilation?: A comparison between young and older humans. Am J Physiol Heart Circ Physiol 296, H57-64. Thijssen DH, Maiorana AJ, O'Driscoll G, Cable NT, Hopman MT & Green DJ. (2010). Impact of inactivity and exercise on the vasculature in humans. Eur J Appl Physiol 108, 845-875. Thomas KN, Lewis NC, Hill BG & Ainslie PN. (2015). Technical recommendations for the use of carotid duplex ultrasound for the assessment of extracranial blood flow. Am J Physiol Regul Integr Comp Physiol 309, R707-720. Thosar SS, Bielko SL, Mather KJ, Johnston JD & Wallace JP. (2015). Effect of prolonged sitting and breaks in sitting time on endothelial function. Med Sci Sports Exerc 47, 843-849. Thosar SS, Johnson BD, Johnston JD & Wallace JP. (2012). Sitting and endothelial dysfunction: The role of shear stress. Med Sci Monit 18, RA173-180. 130 Tontisirin N, Muangman SL, Suz P, Pihoker C, Fisk D, Moore A, Lam AM & Vavilala MS. (2007). Early childhood gender differences in anterior and posterior cerebral blood flow velocity and autoregulation. Pediatrics 119, e610-615. Tremblay MS, Aubert S, Barnes JD, Saunders TJ, Carson V, Latimer-Cheung AE, Chastin SFM, Altenburg TM, Chinapaw MJM & Participants STCP. (2017). Sedentary behavior research network (sbrn) - terminology consensus project process and outcome. Int J Behav Nutr Phys Act 14, 75. Tremblay MS, Carson V, Chaput JP, Connor Gorber S, Dinh T, Duggan M, Faulkner G, Gray CE, Gruber R, Janson K, Janssen I, Katzmarzyk PT, Kho ME, Latimer-Cheung AE, LeBlanc C, Okely AD, Olds T, Pate RR, Phillips A, Poitras VJ, Rodenburg S, Sampson M, Saunders TJ, Stone JA, Stratton G, Weiss SK & Zehr L. (2016). Canadian 24-hour movement guidelines for children and youth: An integration of physical activity, sedentary behaviour, and sleep. Appl Physiol Nutr Metab 41, S311-327. Trost SG, Pate RR, Freedson PS, Sallis JF & Taylor WC. (2000). Using objective physical activity measures with youth: How many days of monitoring are needed? Med Sci Sports Exerc 32, 426-431. Udomphorn Y, Armstead WM & Vavilala MS. (2008). Cerebral blood flow and autoregulation after pediatric traumatic brain injury. Pediatr Neurol 38, 225-234. van Hall G, Stromstad M, Rasmussen P, Jans O, Zaar M, Gam C, Quistorff B, Secher NH & Nielsen HB. (2009). Blood lactate is an important energy source for the human brain. J Cereb Blood Flow Metab 29, 1121-1129. Vandekar SN, Shou H, Satterthwaite TD, Shinohara RT, Merikangas AK, Roalf DR, Ruparel K, Rosen A, Gennatas ED, Elliott MA, Davatzikos C, Gur RC, Gur RE & Detre JA. (2019). Sex differences in estimated brain metabolism in relation to body growth through adolescence. J Cereb Blood Flow Metab 39, 524-535. Vavilala MS, Lee LA & Lam AM. (2002a). Cerebral blood flow and vascular physiology. Anesthesiology Clin N Am 20, 247-264. Vavilala MS, Lee LA & Lam AM. (2003). The lower limit of cerebral autoregulation in children during sevoflurane anesthesia. J Neurosurg Anesthesiol 15, 307-312. Vavilala MS, Newell DW, Junger E, Douville CM, Aaslid R, Rivara FP & Lam AM. (2002b). Dynamic cerebral autoregulation in healthy adolescents. Acta Anaesth Scand 46. Verbree J, Bronzwaer A, van Buchem MA, Daemen M, van Lieshout JJ & van Osch M. (2017). Middle cerebral artery diameter changes during rhythmic handgrip exercise in humans. J Cereb Blood Flow Metab 37, 2921-2927. Verbree J, Bronzwaer AS, Ghariq E, Versluis MJ, Daemen MJ, van Buchem MA, Dahan A, van Lieshout JJ & van Osch MJ. (2014). Assessment of middle cerebral artery diameter during hypocapnia and hypercapnia in humans using ultra-high-field mri. J Appl Physiol 117, 1084-1089. 131 Vogel RA, Corretti MC & Plotnick GD. (1997). Effect of a single high-fat meal on endothelial function in healthy subjects. Am J Cardiol 79, 350-354. Vriens EM, Kraaier V, Musbach M, Wieneke GH & van Huffelen AC. (1989). Transcranial pulsed doppler measurements of blood velocity in the middle cerebral artery: Reference values at rest and during hyperventilation in healthy volunteers in relation to age and sex. Ultrasound in Med & Bio 15, 1-8. Weikle N. (2021). The use of sonography in pediatrics: The bioethical concerns in clinical and research practice. J Diagn Med Sonogr 37, 510-512. Weston ME, Barker AR, Tomlinson OW, Coombes JS, Bailey TG & Bond B. (2021). Differences in cerebrovascular regulation and ventilatory responses during ramp incremental cycling in children, adolescents, and adults. J Appl Physiol 131, 1200-1210. Weston ME, Barker AR, Tomlinson OW, Coombes JS, Bailey TG & Bond B. (2022). The effect of exercise intensity and cardiorespiratory fitness on the kinetic response of middle cerebral artery blood velocity during exercise in healthy adults. J Appl Physiol 10.1152/japplphysiol.00862.2021. Wheeler MJ, Dunstan DW, Smith B, Smith KJ, Scheer A, Lewis J, Naylor LH, Heinonen I, Ellis KA, Cerin E, Ainslie PN & Green DJ. (2019). Morning exercise mitigates the impact of prolonged sitting on cerebral blood flow in older adults. J Appl Physiol 126, 1049-1055. Williams D. (2012). The physics of ultrasound. Anaesth Intensive Care Med 13, 264-268. Willie CK, Colino FL, Bailey DM, Tzeng YC, Binsted G, Jones LW, Haykowsky MJ, Bellapart J, Ogoh S, Smith KJ, Smirl JD, Day TA, Lucas SJ, Eller LK & Ainslie PN. (2011). Utility of transcranial doppler ultrasound for the integrative assessment of cerebrovascular function. J Neurosci Methods 196, 221-237. Willie CK, Macleod DB, Shaw AD, Smith KJ, Tzeng YC, Eves ND, Ikeda K, Graham J, Lewis NC, Day TA & Ainslie PN. (2012). Regional brain blood flow in man during acute changes in arterial blood gases. J Physiol 590, 3261-3275. Willie CK, Tzeng YC, Fisher JA & Ainslie PN. (2014). Integrative regulation of human brain blood flow. J Physiol 592, 841-859. Woodman RJ, Playford DA, Watts GF, Cheetham C, Reed C, Taylor RR, Puddey IB, Beilin LJ, Burke V, Mori TA & Green D. (2001). Improved analysis of brachila artery ultrasound using a novel edge-detection software system. J Appl Physiol 91, 929-937. Wu C, Honarmand AR, Schnell S, Kuhn R, Schoeneman SE, Ansari SA, Carr J, Markl M & Shaibani A. (2016). Age-related changes of normal cerebral and cardiac blood flow in children and adults aged 7 moths to 61 years. J Am Heart Assoc DOI: 10.1161/JAHA.115.002657. Xie A, Skatrud JB, Morgan B, Chenuel B, Khayat R, Reichmuth K, Lin J & Dempsey JA. (2006). Influence of cerebrovascular function on the hypercapnic ventilatory response in healthy humans. J Physiol 577, 319-329. 132 Yang T, Sun Y, Lu Z, Leak RK & Zhang F. (2017). The impact of cerebrovascular aging on vascular cognitive impairment and dementia. Ageing Res Rev 34, 15-29. Zarrinkoob L, Ambarki K, Wahlin A, Birgander R, Carlberg B, Eklund A & Malm J. (2016). Aging alters the dampening of pulsatile blood flow in cerebral arteries. J Cereb Blood Flow Metab 36, 1519-1527. Zlatar ZZ, Hays CC, Mestre Z, Campbell LM, Meloy MJ, Bangen KJ, Liu TT, Kerr J & Wierenga CE. (2019). Dose-dependent association of accelerometer-measured physical activity and sedentary time with brain perfusion in aging. Exp Gerontol 125, 1-21. 133 Appendices Appendix A Intracranial Vascular Responses to High-Intensity Interval Exercise and Moderate-Intensity Steady-State Exercise in Children Accepted author manuscript version reprinted, by permission, from Pediatric Exercise Science, 2019, 31(3): 290-295, https://doi.org/10.1113/EP088293. © Human Kinetics, Inc. Background Excessive levels of sedentariness have reached alarming levels in children (Leatherdale & Ahmed, 2011). This is particularly concerning given the evidence that sedentary aging augments the risk of cognitive decline and dementia (Lautenschlager et al., 2012). Breaking up sedentary activities with physical activity has been shown to be an effective way of not only increasing physical activity, but also improving attention and time-on-task (Altenburg et al., 2016; Szabo-Reed et al., 2017). While multiple mechanisms have been proposed for post-exercise cognitive benefits in the child, one explanation is cognitive enhancements are linked to exercise-induced increases in cerebral perfusion (Hillman et al., 2009; Drollette et al., 2012). Cerebral perfusion during exercise has been well-defined in adults (Smith & Ainslie, 2017), but there is limited evidence on the impact exercise has upon cerebral hemodynamics in children. Ellis et al. (2017) show in an incremental exercise test to exhaustion the rise in intra-cranial blood velocity, as indexed using MCAv, was ~12% in children, in comparison to ~25% in adults. The peak increase in MCAv in children occurred at 50% of the ventilatory threshold and was maintained up to and including the respiratory compensation point. Absolute values for MCAv were higher in the children than in the adults, as noted elsewhere (Satterthwaite et al., 2014), which may account for the attenuated exercise response. 134 The regulation of CBF at rest is dependent on multiple factors: arterial blood gases (in particular, the PaCO2, cerebral metabolism, arterial BP, neurogenic activity and CO. However, as reviewed elsewhere, the influence each factor has on CBF during exercise is unclear, it appears that PaCO2 is the primary influencing factor during exercise, at least in adults (Smith & Ainslie, 2017). Unlike adults, Ellis et al. (2017) demonstrated in children that the PETCO2 (a surrogate measure of PaCO2) and MCAv during exercise were not correlated, and the change in MCAv during exercise did not mimic the changes in PETCO2 to the same extent as in adults. While little is known about the primary regulators of CBF during exercise in children, there is evidence in children that increases in systemic blood flow during exercise augments shear stress, upregulating vascular nitric oxide bioavailability and vasodilation, even in the non-exercising limb (Mills et al., 2013). Exercise induced changes in vasomotor tone within the peripheral vasculature appears to be intensity dependent and bi-phasic (Dawson et al., 2018). Post-exercise blood flow in the non-exercising limb was reduced immediately after a single bout of high-intensity interval exercise (HIIE), but not moderate-intensity steady state exercise (MISS) on a cycle ergometer in adults and adolescents, with subsequent vasodilatory upregulation or normalization resulting in an increase in blood flow one or more hours after the cessation of HIIE, but not MISS (Atkinson et al., 2015; Bond et al., 2015). Recently shear stress was confirmed as a potent vasodilator of the extra-cranial cerebral arteries (Carter et al., 2016; Hoiland et al., 2017) and it is feasible that post exercise up-regulation of vasomotor tone in non-exercising peripheral conduit arteries extends to the cerebrovasculature. Therefore, the objective of this study was to explore how acute HIIE and MISS impacts intra-cranial blood velocity in the child. Our primary hypotheses were: (i) increases in MCAv would be greater during MISS compared to HIIE and (ii) MCAv would be lower than baseline immediately post HIIE, increasing above baseline values 30 minutes post exercise following HIIE, but would return to baseline post MISS. 135 Methods Study Population Fifteen prepubertal children (mean age: 9.99 ± 1.73 years, 8 girls and 7 boys) were recruited to the study. Of the fifteen recruited, eight children were included in the final analysis. Five were Tanner Stage 1 (4 boys, 1 girl) and three were Tanner Stage 2 (3 girls), as determined by parental assessment of secondary sex characteristics, as outlined by Tanner (Rasmussen et al., 2015). Mean age of the eight was 10.0 ± 1.9 years (6.0 to 11.8 years). As age-related differences in CBF have been documented with advancing maturity, early pubertal children were recruited (Satterthwaite et al., 2014). Children were excluded from the study if training >10 hours/week in sport or competition and had any medical condition that would influence cerebral perfusion or the ability to exercise. Only participants with a BMI within 1 standard deviation (±) of the World Health Organization (WHO) growth standard median were included. Written informed consent was obtained from the parents of the children, and written assent from the children. The study was cleared by the Clinical Research Ethics Board of the University of British Columbia (H15-02104). Experimental Design & Procedures We conducted a randomized cross-over trial with two experimental exercise conditions (HIIE and MISS) on an electronically braked cycle ergometer (Lode Pediatric Corival). Participants visited the laboratory on three occasions, each separated by a minimum 48h period. During the first visit, they completed anthropometric measurements and a maximal exercise test. They returned to the laboratory at the same time of day on two further occasions to complete the HIIE and MISS conditions. They were asked to arrive 2h fasted, well hydrated, and to have refrained from caffeine and vigorous exercise 24h prior to each visit. Parents were asked to provide identical food on testing days and avoid foods containing fat and vitamin C, which may acutely effect vascular function (Vogel et al., 1997; Taddei et al., 1998). 136 Each of the two conditions began immediately following an unloaded (0 Watt; W) 3-minute warm-up. The HIIE condition consisted of six 1-minute sprint intervals at 90% Watt maximum (Wmax), each separated by 1-minute of active recovery, pedaling at 20% Wmax. This protocol was modelled on the work completed by Bond and colleagues with adolescents (Bond et al., 2015), however they used eight sprints which, when piloted within our laboratory, the children were unable to complete. Following the same warm-up, the MISS condition entailed cycling at a cadence of 70-90 rpm. The two conditions were matched for total external work, calculated using the square wave method. This entails summing the total external work for the HIIE sprint and rest intervals (90%, 20%, 90%, 20%, etc.), then calculating the exercise time and wattage to give an equivalent external load. This resulted in 15 minutes of exercise time for MISS at 44% Wmax, providing identical total external work (796 ± 163 arbitrary units). To account for the difference in exercise time between protocols, data from the MISS protocol were processed in twelve 75s bins which paired with the twelve 60s bins of the HIIE protocol. The order of conditions was counterbalanced. Figure 16 provides a schematic of the study design and measurements. During the two experimental conditions participants completed pre-exercise HR, mean arterial pressure (MAP), end-tidal carbon dioxide (PETCO2) and MCAv assessment in a semi-supine position, followed by the exercise conditions. MCAv and HR were assessed continuously throughout the exercise conditions. HR, MAP, PETCO2, and MCAv were assessed post (<10 minutes), and 30 minutes post (post 30) exercise with the child remaining in the semi-supine position. PETCO2 was assessed as a non-invasive surrogate of the PaCO2. 137 Figure 16. A schematic of experimental protocols: high-intensity interval and moderate-intensity exercise. A, HIIE. B, MISS. Order of the completion of experimental protocols was randomized for each participant. Measurements Body mass was measured to the nearest 0.1 kg with an electronic scale (Tanita TBF-410GS, Arlington Heights, Illinois). Stature was measured to the nearest 0.1 cm with a stadiometer (Seca 213 Portable, Hamberg, Germany). Participants completed a ramp maximal exercise test with supramaximal verification to determine maximal oxygen uptake (V̇O2max) and Wmax. The test began with 3-minutes of unloaded pedaling followed by a workload increase depending on the stature of the child (<110cm 5 W·min-1, 110-125cm 10 W·min-1, 125-150cm 15 W·min-1, >150cm 20 W·min-1). A pedal cadence between 70-80 rpm was maintained throughout the test and continued until volitional exhaustion, which was defined as a decrease in cadence below 60 rpm for 5 consecutive seconds. At the end of the test the children pedaled unloaded for 5-minutes, then rested for 10-minutes before the supramaximal verification of maximum. The supramaximal test began with a 2-minute warm-up 90% WMAX44% WMAX20% WMAXBaselineHR, MAP, PETCO2, MCAvWarm-up0 WattPOSTHR, MAP, PETCO2, MCAvPOST 30HR, MAP, PETCO2, MCAvHIIEHR, MCAvMISSHR, MCAvBaselineHR, MAP, PETCO2, MCAvWarm-up0 WattPOSTHR, MAP, PETCO2, MCAvPOST 30HR, MAP, PETCO2, MCAvAB 138 followed by a ‘step’ transition to 105% of the Wmax achieved during the ramp test. This intensity was maintained until exhaustion at which point a 3-minute unloaded cool-down was completed. Oxygen uptake and ventilation during the maximal test were assessed breath-by-breath using an online gas analyzer (Oxycon Pro, Carefusion). V̇O2max was defined as less than 5% difference in the slope of increase in V̇O2 between the maximal and supramaximal tests (Barker et al., 2011). PETCO2 was recorded using a calibrated online gas analyzer (ML206; ADInstruments, Colorado Springs, CO) pre and post the exercise conditions for 5 minutes at each time point (baseline, post, and post 30). Data were interpolated to 15s bins. Intra-cranial blood velocity was recorded continuously in the left MCA from rest throughout the exercise and recovery using a 2 MHz transcranial Doppler ultrasound (TCD; Spencer Technologies, Seattle, WA). The probe was attached using a pediatric-sized headband, and the MCA was insonated through the trans-temporal window using standardized methods previously described by our laboratory (Willie et al., 2011). MCAv data were recorded using an analog-to-digital converter (Powerlab, 16/30; ADInstruments, Colorado Springs, CO) for storage and off-line analysis. The coefficient of variation for day-to-day reproducibility of MCAv in children in our laboratory is 4.3%. HR was measured continuously using HR telemetry (Polar Vantage NV, Polar Electro Oy). BP was assessed using sphygmomanometry to the nearest 2 mmHg, twice in the right arm and a third measurement if the readings were 5 mmHg apart. MAP was subsequently calculated [(2/3·diastolic pressure)+(1/3·systolic pressure)]. Statistics Shapiro-Wilk test of normality was performed for all variables and normality of distribution was confirmed. Descriptive data are shown as mean ± standard deviation. The impact of HIIE and MISS on MCAv was examined using a condition (HIIE, MISS) by time (13 time points) 139 repeated measures analyses of variance (RM ANOVA). Main effects and interactions for MCAv and PETCO2 during the recovery periods were examined using a condition (HIIE, MISS) by time (baseline, post, post 30) RM ANOVA. Where necessary, main effects were deconstructed using paired samples t-tests with Bonferroni correction. Mean differences in HR during the HIIE and MISS conditions were assessed using paired samples t-test. Mean differences in HR and MAP from baseline to recovery (post and post 30) were assessed using paired samples t-test. Statistical significance was set at p≤0.05. Statistical analyses were performed using SPSS 22.0 (SPSS, Chicago, IL, USA). Results Of the 15 children recruited, data are presented on eight. Those excluded from analyses include two who did not complete the HIIE condition, one who did not complete the MISS condition and four who had incomplete MCAv data. Of those included in the analyses, mean height was 143.9 ± 12.4 cm (118.0 to 153.5 cm) and mean body mass was 37.2 ± 10.3 kg (18.2 to 50.5 kg). HR and MCAv responses during HIIE and MISS HR, expressed as a percentage of maximum (HRMax), during both the HIIE and MISS conditions are provided in Figure 17. Percentage HRMax was significantly higher during each exercise interval of HIIE (stage 1, 3, 5, 7, 9, and 11) compared to the corresponding MISS stage (p<0.001; see Figure 17) with a mean % HRMax of 82 ± 4% and 69 ± 4% in the HIIE exercise intervals and corresponding MISS stages respectively (t=10.350; p<0.001). 140 Figure 17. Heart rate, expressed as a percent of maximum, during each stage of high-intensity interval and moderate-intensity steady state exercise. For the HIIE (red circle) condition every odd stage (S1, S3, S5, etc.) represents an exercise interval, whereas even stages (S2, S4, S6, etc.) represent active recovery intervals. MISS represented by blue square. *p<0.05 between exercise conditions. Baseline MCAv for HIIE and MISS was 75.6 ± 6.0 and 76.2 ± 4.2 cm/s, respectively. Following the warm-up, values were unchanged at 76.7 ± 8.4 for HIIE and 76.3 ± 5.3 for MISS. When expressed as a relative change from baseline, there was a main effect of time on MCAv (p<0.001), and an interaction (p=0.003; see Figure 18). Follow-up analyses revealed a significant increase in MCAv above baseline during stage two of the MISS condition of 5.8 ± 3.9% (p=0.004), however, no significant increase during HIIE. There was a significant decrease in MCAv below baseline of 10.7 ± 4.1% during the 6th sprint (stage eleven) of the HIIE condition (p=0.004), however, no corresponding decline during MISS (see Figure 18). S1 S2 S3 S4 S5 S6 S7 S8 S9 S10 S11 S125060708090100HRMax (%)****** 141 During the fifth and seventh stages (third and fourth sprint of the HIIE condition), MCAv during HIIE was significantly lower compared to MISS (p=0.001). However, this between group difference was not noted at any other stage. Figure 18. The relative change in middle cerebral artery blood velocity during each stage of high-intensity interval and moderate-intensity steady state exercise. For the HIIE condition (red circle), every odd stage (1,3,5 etc.) represents an exercise interval, whereas even stages (2,4,6 etc.) represent active recovery intervals. MISS condition represented by blue squares. § p<0.05 within MISS condition from baseline. † p<0.05 within HIIE condition from baseline. *p<0.05 between exercise conditions. MCAv following HIIE and MISS Baseline and post exercise MCAv are shown in Figure 19, panel A. There was a main effect of time (p<0.05) for post exercise MCAv. Follow-up analyses revealed a significant decrease below baseline in MCAv in both HIIE and MISS conditions immediately following exercise (p<0.001). MCAv returned to baseline values 30 minutes post exercise following HIIE and MISS. S1 S2 S3 S4 S5 S6 S7 S8 S9 S10 S11 S12-20-1001020MCA V (%)* *§ † 142 Figure 19. Middle cerebral artery blood velocity (panel A) and partial pressure of end-tidal carbon dioxide (panel B) following completion of high-intensity interval and moderate-intensity steady state exercise conditions. The relative change in MCAv (%) immediately from baseline (BL) following (Post), and 30 minutes post exercise (Post 30) HIIE (red circles) and MISS (blue squares). Absolute changes in PETCO2 from BL, Post, and Post 30. § P < 0.05 within MISS condition from baseline. † P < 0.05 within HIIE condition from baseline. -20-1001020MCA V (%)A§†BL Post Post 3030354045P ETCO2 (mmHg)B† 143 PETCO2 following HIIE and MISS Baseline and post exercise PETCO2 are illustrated in Figure 19, panel B. There was a main effect of time (p<0.05) for post exercise PETCO2. Simple effects revealed a significant decline in PETCO2 immediately after HIIE of 3.4 mmHg (p<0.05), returning to baseline values 30 minutes post exercise. PETCO2 remained unchanged from baseline following MISS at all recovery time points. HR and MAP following HIIE and MISS Resting baseline HR in a semi-supine position was 77 bpm. HR was significantly elevated immediately post-exercise from baseline during both MISS (90 bpm; p=0.008) and HIIE (102 bpm; p<0.001) conditions. HR returned to baseline values post 30 following the MISS condition, but remained significantly elevated above baseline values post 30 (85 bpm; p=0.019) following HIIE. Of the eight children included in the analyses, we were unable to obtain satisfactory manual BP at the various post-exercise time points for all children. MAP was elevated above baseline post [HIIE: (n=4): 77.3 to 89.8 mmHg, p=0.001; MISS (n=3): 79.1 to 91.1 mmHg, p=0.057] and remained elevated post 30 [HIIE (n=4): 76.4 to 83.8 mmHg, p=0.046; MISS (n=5): 77.0 to 84.0, p=0.003]. Discussion This study is the first to report the impact of an acute bout of HIIE and MISS on intra-cranial blood velocity in children. While we show that there is an increase in MCAv at the onset of MISS, contrary to our primary hypothesis the increase found in MISS was no greater than HIIE. The increase in MCAv at the onset of MISS was not sustained, with values returning to baseline after 4 minutes. At the onset of HIIE, the MCAv response varied among participants and with an increasing number of high-intensity intervals MCAv declined below baseline. Upon cessation of both HIIE and MISS, contrary to our hypothesis we found MCAv was reduced below baseline in 144 both conditions, but normalized 30 minutes post-exercise to baseline values. MAP was elevated post-exercise, while PETCO2 fell below baseline following HIIE but not MISS. Although MAP remained elevated above baseline 30 minutes post-exercise, PETCO2 returned to baseline. Increases in cerebral perfusion during submaximal exercise have been reported in young adults, but largely during shorter duration steady state exercise (Fisher et al., 2008; Billinger et al., 2017). In a review of 17 studies, Smith and Ainslie (2017) demonstrate relative increases in cerebral perfusion from baseline range from 11% to 40% during moderate-intensity exercise. We show increases in MCAv during the first 150 seconds of MISS of a similar magnitude (~11%) to Fisher et al. (2013), before returning back to baseline values within 4 minutes (Billinger et al., 2017). The greater response noted by others may be an outcome of a differing exercise mode and/or intensity, or simply a reflection of age differences in the intra-cranial response to exercise noted previously (Ellis et al., 2017). Fluctuations in response to prolonged stimulus in the MCAv that have been noted in previous experiments have been countered by altering the stimulus, and it is possible that this is necessary in children if maintained increases in MCAv are desired during MISS (Smith et al., 2019). There is scant information on the intra-cranial blood velocity response to high-intensity exercise. In adults, Curtelin et al. (2017), note MCAv was 10% below baseline values at the end of an all-out 30s Wingate test sprint. Comparably, we also show MCAv values were 10.7% below baseline by the 6th high-intensity interval. The HIIE protocol used in the current experiment was matched for total external work with the MISS protocol and elicited a higher cardiovascular response than MISS. Percentage of HRMax during the first two sprints of HIIE was 72 and 78%, respectively, rising to 82-88% of maximum during the third, fourth, fifth, and sixth sprint (see Figure 19). During a high-intensity interval exercise trial using 8 intervals, Bond and colleagues show %HRMax in adolescents to be 77±6% (Bond et al., 2015), marginally lower than the average %HRMax achieved here. Future experiments may consider assessing additional measures to 145 monitor intensity, such as a fatigue index during each sprint, and declines in speed (RPM). Importantly, our HIIE protocol resulted in a higher intensity workload compared to the MISS, causing increases in MCAv in some, but not all of the children in the initial interval and a reduction in MCAv by the final interval. In both HIIE and MISS, MAP remained elevated above baseline immediately following exercise. Elevated BP has been seen elsewhere in children post exercise. Rauber et al. (2014) report significantly elevated systolic and diastolic BP 2 minutes post exercise of varying intensities when compared to rest. However, BP recovered by 30 minutes post exercise (Rauber et al., 2014). Such findings are in contrast to data in adults where post exercise hypotension has been reported following short bouts of both moderate and higher intensity exercise (Mundel et al., 2015; Curtelin et al., 2017). Interestingly, despite a drop-in MAP post exercise in adults, MCAv remained at baseline values (Mundel et al., 2015). Upon cessation of both HIIE and MISS a significant decline in MCAv was noted in the present study, accompanied by a decline in PETCO2 following HIIE, but not MISS. This dissociation of MCAv and PETCO2 immediately following MISS, but not HIIE suggests that the primary regulatory mechanisms of the intra-cranial blood velocity post exercise may vary with exercise intensity and mode. Factors such as sympathetic drive may be more influential following MISS, whereas hyperventilation induced hypocapnia during HIIE may drive the drop in MCAv upon cessation of HIIE. There is evidence in adults of vasoconstriction of the large intra-cranial arteries with handgrip exercise, which supports the concept of exercise-induced sympathetic regulation of intra-cranial blood flow (Verbree et al., 2017). Future research confirming whether or not vasoconstriction of the large intra-cranial arteries also accompanies exercise in children would be valuable. Improvements in cognitive function following exercise, at least in adults, have been linked to exercise-induced increases in cerebral perfusion (Markus & Boland, 1992). Hillman et al. (2009) showed increases in cognition following exercise of similar intensity (60% HRMax) and duration 146 (20 minutes) to our MISS condition. The exercise-induced increases in MCAv present at the onset of MISS shown in the present study did not persist with either continued MISS or into recovery, suggesting that post-exercise increases in cognition do not appear to be related to increased post-exercise intra-cranial blood velocity. There may be other changes that occur following the cessation of moderate-intensity exercise, such as post-exercise elevations in cerebral oxygen consumption. Release of BDNF or increased arousal that might account for the post-exercise improvements in cognitive function shown in children (Hillman et al., 2009). Strengths and Limitations Strengths of this study include the use of a cross-over study design and the HIIE and MISS protocols were created to ensure equivalent total external work completed by participants. This study is also strengthened by the assessment of recovery cerebrovascular data, a first for this age group, furthering understanding of the effects of acute HIIE and MISS exercise on cerebral perfusion. The study is not without limitations. We present preliminary data with a small sample who are mixed sex. That said, much of the work of this kind in adults have similar small samples and are generally mixed sex (Fisher et al., 2008; Fisher et al., 2013; Billinger et al., 2017). The children in the present study are either pre or early pubertal. Cerebral perfusion, at least at rest, is similar between girls and boys in early puberty, diverging mid puberty (Satterthwaite et al., 2014). Future work with a larger sample that would allow analysis of sex and maturity related influences on the exercise response in mid-pubertal youngsters is needed. The MCAv response to HIIE display larger variance in comparison to the MISS response and a larger sample size could help characterize MCAv responses to exercise. TCD provides a measure of velocity as opposed to blood flow and assumes no dilation in the MCA. Recent evidence using MRI has shown that the diameter of the MCA increases in response to changes in PETCO2 greater than ~8 mmHg (Coverdale et al., 2014; Verbree et al., 2014). A large reduction in PETCO2 may result in 147 constriction of the MCA diameter by ~4% (Coverdale et al., 2014). However, the changes in PETCO2 immediately following the HIIE and MISS conditions in the current experiment were relatively minor and are unlikely to have elicited either constriction or dilation in the MCA. Alternatively, exercise-induced sympathetic stimulation may also impact vessel diameter, and cannot be accounted for using TCD (Verbree et al., 2017). We only assessed MAP and PETCO2 at baseline and following exercise, not during exercise. Exploring the relationships between MAP, PETCO2 and MCAv during MISS and HIIE would have strengthened the study, however, acquiring the quality of data needed non-invasively during exercise is challenging. Conclusion This study shows that HIIE and MISS elicit differing intra-cranial vascular responses, both during and following exercise. These preliminary findings are thought-provoking and suggest further studies are needed to clarify the impact exercise may have upon sympathetic drive, PETCO2, BP and intra-cranial vessel caliber both during and following exercise in childhood. 148 Appendix B Examining blood vessels using sound waves Accepted author manuscript version reprinted under the Creative Commons Attribution License. Copyright © Tallon, Smith, Lewis and McManus. Tallon C, Smith K, Lewis N and McManus A (2021). Examining Blood Vessels Using Sound Waves. Front. Young Minds. 9:618465. DOI: 10.3389/frym.2021.618465 Blood and blood vessels have important jobs Just like water travelling through a garden hose in your backyard, blood flows through blood vessels in your body. Blood vessels are the tubes that allow blood to flow out from the heart, around the body, and back to the heart. Blood is made up of four main components: red blood cells, white blood cells, platelets, and plasma – each with important jobs to do! Red blood cells carry oxygen to all your other cells, to fuel them, and they carry carbon dioxide (a waste product) away. White blood cells help your body fight infections. Platelets help to form clots, which plug the holes in blood vessel walls when you get injured. Plasma, made up mostly of water, helps blood cells flow through the blood vessels, just like water through a garden hose. Plasma also transports nutrients and important proteins throughout the body. Figure 20. Blood vessels make two loops within the body. Within the shaded grey box is the small loop, made up of blood vessels that connect the heart to the lungs, where blood can receive oxygen and get rid of carbon dioxide waste. The larger loop is very complex, and it moves blood to and from the heart and all other parts of the body, including the brain, other organs like the liver and kidneys, and the muscles. The figure was created using Mind the Graph platform. 149 Blood vessels make two loops within the body: a small one and a large one (Figure 20). In the small loop, blood that is low in oxygen flows from the heart to the lungs, where it receives oxygen. Blood with high levels of oxygen travels from the lungs back to the heart, ready to be pumped to all other parts of the body along the larger loop. Blood vessels in this large loop range in size, with the largest vessels located closest to the heart and the smallest located furthest away from the heart. The largest blood vessels are the arteries, which have strong muscular walls. The smallest blood vessels are the capillaries, which have thin walls so the blood can easily exchange oxygen, nutrients, and carbon dioxide through them. Veins are blood vessels that carry blood back toward the heart, and they do not have strong muscular walls like arteries. Because blood vessels are so important for keeping us alive, it is important for doctors and scientists to be able to measure whether they are working properly, particularly as we get older and the blood vessels start to change. One easy method to examine blood vessels involves using sound waves to create images of them, with a technique called ultrasound. To understand how this technique works, let’s first talk about sound waves. What is a sound wave? Sound waves are created when an object vibrates the air around it, and that vibration travels through the air, away from the source of the sound, as a wave. Sound waves have two Figure 21. Short and long wavelength sound waves. A, This sound wave has a long wavelength. Long wavelength represents a low frequency sound, which we hear as a lower pitch, like thunder booming in a storm. B, This sound wave has a shorter wavelength and higher frequency, resulting in a higher pitch, like a whistle in gym class. 150 important characteristics: wavelength and frequency (Figure 21). Picture ocean waves rising up to a peak before falling to a low point, while also rolling closer to the beach. The space that one sound wave cycle takes as it rolls up and down horizontally is called its wavelength. Sound waves can also be measured by their speed, which is known as frequency. The frequency of sound waves is a count of how many complete wave cycles occur in one second. Frequency determines the pitch of the sound: high pitch corresponds to high frequency and low pitch to low frequency. Sound waves with higher frequencies have shorter wavelengths. The unit for measuring frequency is hertz (Hz). One Hz is one complete sound wave cycle per second. Human ears can only hear sounds between 20 and 20,000 Hz. Sounds less than 20 Hz are called infrasound, while sounds higher than 20,000 Hz are called ultrasound. Ultrasound is the type of sound used to look inside our bodies. To create images of blood vessels, ultrasound requires sound waves with frequencies of 2–20 megahertz. A megahertz is made up of 1,000,000 Hz! How can we use ultrasound to examine blood vessels? When a doctor or scientist wants to look at the blood vessels, an ultrasound machine is used. This machine looks like a computer, with a display screen and a small hand-held device called a transducer. The transducer sends out sound waves and waits for their return Figure 22. Information from the returning waves is used to create the image. But how? An ultrasound image is made up of a variety of pixels, like those of an image from your favorite video game. The location of each pixel on the screen is based upon the time it takes for the sound wave to return to the transducer. The deeper the sound wave travels into the body, the more time it will take for it to return, causing the pixel to be placed near the bottom of the screen. In comparison, a sound wave that does not have to travel as far will return to the transducer faster and be placed near the top of the image. 151 As a sound wave travels through the body, the strength of the wave decreases with the distance traveled, in a process called attenuation. Think of a time you have gone swimming, running, or walking. The farther you go, the more tired you become. Similarly, a sound wave loses strength the farther it travels from the transducer. Sound waves that travel only a short distance and experience minimal attenuation will appear as brighter, whiter pixels on the image, while sound waves that travel farther and experience large amounts of attenuation will appear as duller and darker pixels on the screen. Examining blood vessels using ultrasound can help doctors diagnose certain problems. For instance, increased blood flow can might mean that there is an infection. When blood flow is slower than normal this might mean that the blood vessels are getting narrower or even becoming blocked. These images of the blood vessels and the speed of the blood flow that ultrasound measures can tell doctors and scientists about the health of the blood vessel wall, and whether there are any health problems. When we are young it is rare a doctor might want to use ultrasound to image our blood vessels. More common is for a scientist to use ultrasound to study how blood vessels function. These studies provide an opportunity for scientists to compare blood vessels between children and adults. It is more common for a doctor to want to measure our blood vessels Figure 22. How an ultrasound machine examines blood vessels. A, An ultrasound machine sends electrical pulses to the transducer. B, The pulses stimulate a crystal within the transducer, which converts electrical energy into sound waves that can travel through the skin. C, When the sound waves meet a tissue, like a blood vessel, they bounce back to the transducer. D, The crystal in the transducer converts the sound waves back into electrical pulses, which are displayed on the screen to create an image. E, The size of the blood vessels and the speed of the blood can be determined from the image. 152 when we are older. When we get older the walls of our blood vessels can become weaker and there can be a higher risk of having blockages within the vessels. Eating a healthy diet can help protects us against blockages and being physically active can help keep the walls of our blood vessels strong. How can we measure the speed of the blood? Sometimes doctors need to know about the velocity (speed) of the blood moving through a patient’s vessels. Knowing the velocity of the blood allows doctors and scientists to calculate the amount of blood flowing through a blood vessel over a unit of time. This is important because the amount of blood flowing can be a sign the heart is pumping properly and that there are no blockages in the system. A special type of ultrasound called Doppler ultrasound can be used to measure this, using principles of the Doppler effect (Williams, 2012; Martin et al., 2015). To understand the Doppler effect, think about an ambulance traveling towards you with its siren blaring. The sound of the siren gets louder and higher pitched (higher frequency) as it approaches you. As the ambulance passes you and gets farther away, the siren gets quieter and lower pitched (lower frequency). This is due to the Doppler effect: an increase or decrease in the frequency of a sound as the source moves towards or away from the observer. In Doppler ultrasound, the speed of the red blood cells flowing past the sound waves changes the frequency of the reflected sound waves that are received by the transducer. This change in frequency can be used to calculate the blood velocity. Ultrasound of blood vessels helps to keep people healthy! The heart and the blood vessels support the functions of the entire body. As we grow and age, blood vessels grow and age, too. It is important to maintain a healthy heart and blood vessels as we age. If we don’t take steps to keep them healthy, blood vessel walls can become stiff, making it harder for the blood to move through the body. Ultrasound is one of the techniques 153 doctors and scientists can use to examine whether the blood vessels are healthy. Ultrasound can answer many questions, such as, “Are the walls of the blood vessels strong and healthy?”; “How much blood is being pumped by the heart through the blood vessels?”; and “Are the blood vessels blocked?” Scientists can use ultrasound of blood vessels to better understand whether our daily activities, such as exercising or sitting, change either the blood vessels or the velocity of the blood. For example, the amount of blood flowing to the brain was found to decrease when adults do not take regular breaks from sitting. We can all do things to keep our blood vessels working properly! Regular exercise helps blood vessels to stay healthy, by increasing the amount of blood flowing through the vessels. This helps strengthen the vessel walls. Poor eating habits, such as a diet containing excess saturated fats and high levels of refined sugar, could lead to stiffer blood vessel walls, which increases the difficulty the heart faces to pump blood and is a precursor to vascular disease. Saturated fats are mainly found in fatty meats, butter, cheese, and also in some plant-based oils such as coconut oil. Try eating low fat cheese and cook with plant oils like olive oil and not butter. Refined sugar is the white sugar we often used to bake, but is also found in many other things we eat and drink like sodas, fruit yoghurt, ice cream, candies, cookies and even French fries. We don’t have to cut these out of our diets, just make them special treats that you have occasionally and instead choose whole grains, low sugar breakfast cereals or plain yogurt with real fruit. Together, regular exercise, a healthy diet, and ultrasound technology can help us maintain the health of our blood vessels throughout our entire lives.
Thesis/Dissertation
eng
Kinesiology
Vancouver : University of British Columbia Library
Attribution-NonCommercial-NoDerivatives 4.0 International
Graduate
McManus, A. M. (Alison M.)
The impact of sedentary behaviour and physical activity on cerebrovascular hemodynamics, cerebrovascular reactivity, and neurovascular coupling in children
Text