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The effects of strenuous exercise on cardiovascular function in healthy humans Coté, Anita Theresa 2013

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THE EFFECTS OF STRENUOUS EXERCISE ON CARDIOVASCULAR FUNCTION IN HEALTHY HUMANS  by  Anita Theresa Coté  A THESIS SUBMITTED IN PARTIAL FULFILLMENT OF THE REQUIREMENTS FOR THE DEGREE OF  DOCTOR OF PHILOSOPHY in The Faculty of Graduate Studies  (Human Kinetics)  THE UNIVERSITY OF BRITISH COLUMBIA (Vancouver)  March 2013  © Anita Theresa Coté, 2013  Abstract RATIONALE: Strenuous exercise has been shown to elicit transient reductions in ventricular systolic and diastolic function, as well as impaired autonomic function. The effects of training status and sex on the development of these acute alterations are not known. The aim of these studies was to examine vascular adjustments, cardiac mechanics and autonomic function as the result of strenuous exercise in healthy, endurance-trained (ET) and normally active (NA), males and females. Statistical significance was set at p < 0.05. The first investigation explored sex differences in the cardiovascular response to an ultra-marathon in 25 runners. Ventricular function was reduced similarly in men and women. Novel associations of life-time ultra-marathons and degree of longitudinal strain were found, demonstrating the absence of cumulative stress on the heart with long-term prolonged strenuous exercise. The second investigation assessed ventricular function following high-intensity interval exercise (HIT) in 39 men and women. Changes in cardiac mechanics were not differentiated by training status, however, lower baseline arterial stiffness was associated with twist augmentation. Men demonstrated greater reductions in contractility and higher arterial elastance post-exercise than women. The third investigation assessed autonomic function following HIT and orthostatic stress in 33 men and women. Throughout the intervention, women displayed greater strain, strain rate, and baroreflex sensitivity, but there were no interactions of condition by sex. Autonomic function decreased to a greater degree in ET, but also improved most rapidly in recovery. Thus, it would appear that the cardiac and autonomic stability of ET and women during an orthostatic challenge is not compromised in the face of HIT. The fourth investigation analyzed post-exercise hypotension (PEH) following HIT in 21 ii  individuals. Hypotension occurred similarly in all individuals however, men experienced greater reductions in stroke volume. These findings suggest men engage a different mechanism of PEH compared to women. The fifth investigation explored cognitive function in recovery from HIT. Cognition was improved post-exercise and persisted for four hours post-exercise. SUMMARY: Together, these studies provide novel findings pertaining to the effects of sex and training status on the cardiovascular responses to strenuous exercise.  iii  Preface This thesis was written by me, Anita Coté. The research was designed and actualized under the leadership of Dr. Shannon Bredin and Dr. Darren Warburton with significant contributions from Dr. Michael Koehle and Dr. Matthew White. I conducted all data collection with the help of a technician and two research assistants (hired by Drs. Bredin and Warburton), in addition to performing all data analysis and statistical analysis for this dissertation. I received specialized training for these analyses from my supervisors, leading international academic researchers, echocardiography specialists, and representatives from GE Healthcare. Ethical approval was obtained from the University of British Columbia Clinical Research Ethics Board (H08-00607 and H10-00475). A version of chapter 3 is being prepared for submission (Training Status Differentiates the Cardiovascular Response to a 160-kilometer Ultra-marathon). As part of on-going research in our research group, I defined this specific research question, developed the protocols, and wrote the initial draft of the manuscript. All co-authors provided editorial content and edited the manuscript. A version of chapters 4, 5 and 6 are being prepared for submission (An Analysis of Sex and Training Status on Left Ventricular Mechanics Following High-Intensity Interval Exercise; Recovery of Baroreflex Function Following Brief Strenuous Exercise: Effect of Training Status; High-intensity Interval Exercise Elicits Marked Post-exercise Hypotension in Healthy Men and Women). My contribution to these studies started from defining the research questions to writing the manuscripts. Darren Warburton and iv  Shannon Bredin directed and provided input to all aspects of this work. All co-authors have been involved in editing of the manuscripts. A version of chapter 7 is being prepared for submission (Improved Cognitive Performance Following High-intensity Interval Exercise). This study was designed and implemented under the leadership of Shannon Bredin. I refined the research question, analyzed and the data, and wrote the initial draft of the manuscript. Shannon Bredin edited the manuscript.  v  Table of Contents Abstract ......................................................................................................................... ii Preface .......................................................................................................................... iv Table of Contents ........................................................................................................ vi List of Tables ................................................................................................................ x List of Figures .............................................................................................................. xi List of Abbreviations................................................................................................. xiii Acknowledgements ..................................................................................................... xv Chapter 1: Introduction .............................................................................................. 1 1.1 STATEMENT OF THE PROBLEM.................................................................... 2 1.2 OVERVIEW ......................................................................................................... 3 Chapter 2: Literature Review ..................................................................................... 4 2.1 NON-INVASIVE ASSESSMENT OF CARDIAC FUNCTION ........................ 5 2.1.1 Autonomic Function ....................................................................................... 5 2.1.2 Left Ventricular Function .............................................................................. 8 2.1.3 Arterial-ventricular coupling ......................................................................... 9 2.2 SEX DIFFERENCES IN CARDIOVASCULAR FUNCTION ......................... 10 2.2.1 Autonomic Function ..................................................................................... 10 2.2.2 Left Ventricular Structure and Function ..................................................... 11 2.3 CHRONIC TRAINING ON CARDIOVASCULAR FUNCTION ……………12 2.3.1 Autonomic Function ..................................................................................... 12 2.3.2 Left Ventricular Structure and Function ..................................................... 13 2.4 MECHANISMS OF EXERCISE-INDUCED CARDIAC FATIGUE ............... 14 2.4.1 Myocardial stunning and damage ............................................................... 14 2.4.2 β-adrenergic down-regulation ..................................................................... 15 2.4.3 Oxidative Stress ........................................................................................... 16 2.4.4 Elevated Free Fatty Acids............................................................................ 17 vi  2.5 CONCLUSIONS ................................................................................................ 17 Chapter 3: Sex Differences in Cardiac Function Following Prolonged Strenuous Exercise ....................................................................................................................... 18 3.1 INTRODUCTION .............................................................................................. 18 3.2 METHODS ......................................................................................................... 19 3.2.1 Participants and Ethical Approval .............................................................. 19 3.2.2 Experimental Protocol ................................................................................. 20 3.2.3 Procedures and Analysis ............................................................................. 20 3.3 STATISTICAL ANALYSIS .............................................................................. 23 3.4 RESULTS ........................................................................................................... 24 3.4.1 Participant Characteristics.......................................................................... 24 3.4.2 Participant Performance ............................................................................. 24 3.4.3 Physiological and Cardiovascular Outcomes ............................................. 25 3.5 DISCUSSION..................................................................................................... 33 3.6 LIMITATIONS .................................................................................................. 37 3.7 CONCLUSIONS ................................................................................................ 38 Chapter 4: Effects of Sex and Training Status on the Cardiovascular Responses to an Acute Bout of High Intensity Interval Exercise ............................................. 39 4.1 INTRODUCTION .............................................................................................. 39 4.2 METHODS ......................................................................................................... 41 4.2.1 Participants and Ethical Approval .............................................................. 41 4.2.2 Experimental Protocol ................................................................................. 41 4.2.3 Procedures and Analysis ............................................................................. 42 4.3 STATISTICAL ANALYSIS .............................................................................. 45 4.4 RESULTS ........................................................................................................... 46 4.4.1 Participant Characteristics.......................................................................... 46 4.4.2 Hydration, Catecholamines and Haemodynamic Parameters .................... 46 4.4.3 Cardiac Function and Arterial-Ventricular Coupling................................. 47 4.4 DISCUSSION..................................................................................................... 57 4.5 LIMITATIONS .................................................................................................. 60 4.6 CONCLUSIONS ................................................................................................ 61 vii  Chapter 5: Cardiac and Autonomic Function in Recovery from High-Intensity Interval Exercise ......................................................................................................... 62 5.1 INTRODUCTION .............................................................................................. 62 5.2 METHODS ......................................................................................................... 63 5.2.1 Participants and Ethical Approval .............................................................. 63 5.2.2 Experimental Protocol ................................................................................. 64 5.2.3 Procedures ................................................................................................... 65 5.2.4 Data Analysis ............................................................................................... 67 5.3 STATISTICAL ANALYSIS .............................................................................. 68 5.4 RESULTS ........................................................................................................... 68 5.4.1 Participant Characteristics.......................................................................... 68 5.4.2 Cardiovascular Responses to Exercise and Lower Body Negative Pressure ................................................................................................................................... 69 5.4.3 Baroreflex Function with Exercise and Lower Body Negative Pressure .... 70 5.5 DISCUSSION..................................................................................................... 81 5.5.1 The Sex Factor ............................................................................................. 82 5.5.2 The Training Factor..................................................................................... 84 5.5.3 Other Considerations ................................................................................... 85 5.5.4 Cardiovascular Risk .................................................................................... 86 5.6 LIMITATIONS .................................................................................................. 86 5.7 CONCLUSIONS ................................................................................................ 88 Chapter 6: Post-exercise Hypotension in Men and Women Following HighIntensity Interval Exercise ........................................................................................ 89 6.1 INTRODUCTION .............................................................................................. 89 6.2 METHODS ......................................................................................................... 90 6.2.1 Participants and Ethical Approval .............................................................. 90 6.2.2 Experimental Protocol ................................................................................. 91 6.2.3 Procedures and Analysis ............................................................................. 91 6.3 STATISTICAL ANALYSIS .............................................................................. 95 6.4 RESULTS ........................................................................................................... 95 6.5 DISCUSSION................................................................................................... 107 viii  6.6 LIMITATIONS ................................................................................................ 111 6.7 CONCLUSIONS .............................................................................................. 111 Chapter 7: The Effects of High Intensity Exercise on Cognitive Function in Healthy Young Adults.............................................................................................. 112 7.1 INTRODUCTION ............................................................................................ 112 7.2 METHODS ....................................................................................................... 114 7.2.1 Participants and Ethical Approval ............................................................ 114 7.2.2 Experimental Protocol ............................................................................... 114 7.2.3 Procedures ................................................................................................. 115 7.3 STATISTICS .................................................................................................... 119 7.4 RESULTS ......................................................................................................... 119 7.5 DISCUSSION................................................................................................... 125 7.6 LIMITATIONS ................................................................................................ 129 7.7 CONCLUSIONS .............................................................................................. 130 Chapter 8: General Summary and Conclusions ................................................... 131 8.1 INTEGRATION AND INTERPRETATION OF MAJOR FINDINGS .......... 131 8.2 FUTURE STUDIES ......................................................................................... 136 References ................................................................................................................. 138 Appendices ................................................................................................................ 159 A: PHYSICAL ACTIVITY READINESS QUESTIONNAIRE FOR EVERYONE (PAR-Q+) ............................................................................................................... 160 B: FAT DOG 100 ULTRA-MARATHON QUESTIONNAIRE ........................... 164 C: SCHEMATIC OF PROTOCOLS ...................................................................... 166  ix  List of Tables Table 2.1 Typical Heart Rate Variability and Baroreceptor Sensitivity Values for Healthy Individuals................................................................................................................... 6 Table 3.1 Participant Characteristics and Baseline Cardiovascular Measures ................. 26 Table 3.2 Cardiac Dimensions and Global Systolic Function .......................................... 27 Table 3.3 Doppler Flow Velocities ................................................................................... 28 Table 3.4 Tissue Doppler Imaging and Strain .................................................................. 29 Table 3.5 Significant Correlations .................................................................................... 30 Table 4.1 Participant Characteristics and Baseline Cardiovascular Measures ................. 49 Table 4.2 Effects of Exercise on Systolic and Diastolic Function .................................... 50 Table 4.3 Peak Left Ventricular Mechanics and Rest and During Exercise ..................... 51 Table 5.1 Participant Characteristics ................................................................................ 71 Table 5.2 Indices of Left Ventricular Systolic and Diastolic Function ............................ 76 Table 6.1 Participant Characteristics ................................................................................ 97 Table 6.2 Baseline and Post-Exercise Haemodynamics ................................................... 98 Table 6.3 Baseline and Post-Exercise Autonomic Parameters ......................................... 99 Table 6.4 Select Correlations .......................................................................................... 104 Table 7.1 Participant Characteristics .............................................................................. 120  x  List of Figures Figure 3.1 Change in Baroreceptor Sensitivity with Prolonged Exercise ........................ 30 Figure 3.2 Association of Lifetime Ultra-marathons to Longitudinal Strain.................... 31 Figure 3.3 Association of Race-Pace to Longitudinal Strain ............................................ 32 Figure 4.1 Effect of Exercise on Diastolic Longitudinal Strain Rate. .............................. 53 Figure 4.2 Time Course of Left Ventricular Twist and Twist Rates. ............................... 54 Figure 4.3 Relationship of Baseline Pulse Wave Velocity to Exercise-Induced Change in Left Ventricular Twist............................................................................................... 55 Figure 4.4 Arterial Ventricular Coupling Indexed to Body Surface Area ........................ 56 Figure 5.1 Stroke Volume and Cardiac Ouput Responses ................................................ 72 Figure 5.2 Sex Differences in Haemodynamic Response to Lower Body Negative Pressure and Exercise ............................................................................................... 73 Figure 5.3 Diastolic Filling Across Lower Body Negative Pressure Before and After Exercise ..................................................................................................................... 74 Figure 5.4 Heart Rate Across Lower Body Negative Pressure Before and After Exercise ................................................................................................................................... 75 Figure 5.5 Ejection Fraction Across Lower Body Negative Pressure Before and After Exercise ..................................................................................................................... 75 Figure 5.6 Septal Wall Tissue Velocity and Filling Pressures.......................................... 77 Figure 5.7 Longitudinal Strain and Diastolic Strain Rate ................................................. 78 Figure 5.8 Training Group Differences in Autonomic Indices ......................................... 79 Figure 5.9 Sex Differences in Autonomic Indices ............................................................ 80 Figure 6.1 Effect of Exercise on Blood Pressure ............................................................ 100 xi  Figure 6.2 Exercise Haemodynamics ............................................................................. 101 Figure 6.3 Effects of Exercise on Fractional Shortening ................................................ 102 Figure 6.4 Effect of High-Intensity Interval Exercise on Indices of Baroreceptor Sensitivity ............................................................................................................... 103 Figure 6.5 Relationship of Aerobic Capacity to Percent Change in Stroke Volume ...... 105 Figure 6.6 Association of Left Ventricular Mass to Change in Stroke Volume ............. 105 Figure 6.7 Association of Change in Stroke Volume to Baseline Stroke Volume ......... 106 Figure 7.1 Individual Results for Change in Heart Rate ................................................. 120 Figure 7.2 Individual Results for the Comparison of Simple Reaction Time ................ 122 Figure 7.3 Individual Results for the Comparison of Choice Reaction Time ................ 122 Figure 7.4 Individual Results for Working Memory Duration ....................................... 123 Figure 7.5 Change in Dopamine with Exercise .............................................................. 123 Figure 7.6 Relationship of the Change in Dopamine to the Change in Working Memory Duration .................................................................................................................. 124 Figure 7.7 Relationship of Baseline Dopamine Values to Large Artery Compliance .... 124 Figure 7.8 Relationship of Baseline Working Memory Duration to Systolic Blood Pressure ................................................................................................................... 125  xii  List of Abbreviations Symbol  Definition  BMI  Body Mass Index  BRS  Baroreceptor Sensitivity  BSA  Body Surface Area  CI  Cardiac Index  CVP  Central Venous Pressure  DBP  Diastolic Blood Pressure  DNA  Deoxyribonucleic acid  DXA  Dual X-ray Absorptiometry  E:A  Ratio of Early to Atrial Ventricular Filling Velocity  EA  Arterial Elastance  ECG  Electrocardiogram  EDV  End Diastolic Volume  EF  Ejection Fraction  ELV  Ventricular Elastance  ESP  End Systolic Pressure  ESV  End Systolic Volume  ET  Endurance-trained  FS  Fractional Shortening  HF  High Frequency  HIT  High Intensity Interval Exercise  HRV  Heart Rate Variability xiii  IVRT  Isovolumetric Relaxation Time  LAC  Large Artery Compliance  LBNP  Lower Body Negative Pressure  LF  Low Frequency  LV  Left Ventricle  LVM  Left Ventricular Mass  MAP  Mean Arterial Pressure  MSNA  Muscle Sympathetic Nerve Activity  NA  Normally Active  NADPH  Nicotinamide adenine dinucleotide phosphate-oxidase  PEH  Post-exercise Hypotension  PWV  Pulse-wave Velocity  RMSSD  Root of the Mean of Squared Differences Between Successive RR intervals  RV  Right Ventricle  SAC  Small Artery Compliance  SBP  Systolic Blood Pressure  SVI  Stroke Volume Index  TPR  Total Peripheral Resistance  VO2  Oxygen Consumption  WS  Wall Stress  xiv  Acknowledgements I wish to extend my most heartfelt appreciation to the faculty, staff and students who assisted me during my PhD studies. In particular, I wish to acknowledge the dedication and support I received from my supervisors Dr. Shannon Bredin and Dr. Darren Warburton. I marvel at their accomplishments and am honoured to be able to contribute in a small way to their research programs. Notably, Darren’s execution of novel research ideas and Shannon’s attention to detail were important contributors to my work. I would like to thank them for all they have taught me during my graduate studies. Dr. Matthew White was instrumental in the development of my knowledge acquired during my doctoral studies and I thank him for that. In particular he dedicated a great deal of time to advancing my understanding of grant writing and research skills. I am grateful to have been mentored by a leading expert in environmental physiology, an area for which I am passionate about and hope to continue researching in the future. I am also indebted to the tremendous support I received from Dr. Michael Koehle. His expertise and common sense approach were welcome attributes throughout this dissertation. Michael is a role model both academically and personally and I am fortunate to have his involvement in my work. Future collaborations would be an honour. In addition to the expertise from my supervisors and committee, PhD candidate Aaron Phillips was an integral part of my PhD efforts. Aaron assisted me with new research techniques and provided me with the additional motivation I needed to accomplish my various research objectives. I am forever grateful for our research partnership and his friendship.  xv  A special acknowledgement is reserved for Dr. Jack Taunton (Chief Medical Officer 2010 Winter Olympic and Paralympic Games) and GE Healthcare for providing me with the specialized equipment and technical assistance required to execute my research. To all my fellow lab mates and graduate students, I thank them for sharing their experiences and laughter. There are too many to mention here, but each of them served as important role models and friends. Finally, I am extremely appreciative for the support of my family. They were extremely patient and facilitated my achievements through their understanding and love.  xvi  Chapter 1: Introduction The benefits of regular physical activity on cardiovascular risk have been clearly shown [1]. Furthermore, strong evidence exists revealing a dose-response, in which intensity of activity is positively correlated to health benefits [2]. Thus, physical activity in the form of exercise is an effective means to improve health and cardiovascular risk. Recently, strenuous forms of exercise such as high-intensity interval training and ultraendurance events have gained popularity particularly in non-athlete populations [3, 4]. Moreover, accumulating evidence supports the use of high-intensity interval exercise as more effective for health and fitness benefits when compared to traditional moderateintensity aerobic exercise. Protocols typically involve brief (i.e., six seconds to four minutes) near maximal efforts (in excess of 90% maximal capacity) interspersed with low intensity recovery exercise or rest [4]. Chronic adaptations to high-intensity interval training include increased aerobic and anaerobic fitness [5-14], increased skeletal muscle capacity for fatty acid oxidation and glycolytic enzyme content [9, 15, 16], and increased insulin sensitivity [6, 12, 14]. However, the efficacy and safety of this type of exercise has yet to be determined [17]. Prolonged strenuous exercise encompasses exercise bouts from a wide range of endurance durations (i.e., half-marathons and triathlons to multi-day events). Prolonged strenuous events, traditionally dominated by trained athletes, now include a large recreational contingent a population older than in previous years [3]. In a recent analysis of performance trends in 161-km ultra-endurance events, it was revealed that the top performances have remained fairly stable over the last twenty years, however  1  participation rates increased with more individuals focused on finishing and participating in multiple events [18]. Both prolonged strenuous and high-intensity interval exercise have been linked to altered cardiovascular function such as cardiac fatigue. Exercise-induced cardiac fatigue is characterized by a reduction in left ventricular systolic and diastolic function subsequent to exercise in healthy humans [19]. The literature has demonstrated transient alterations in cardiac dynamics indicative of cardiac fatigue as a result of prolonged strenuous exercise [20]; however, only recently has high-intensity interval exercise also been associated with exercise-induced cardiac fatigue [21]. The clinical significance of cardiac fatigue is uncertain. Post-exercise impairments in right and left ventricular function are thought to be of limited short-term concern clinically; however, the longterm effects of these transient impairments in cardiac function remain unknown. 1.1 STATEMENT OF THE PROBLEM There is considerable evidence supporting the health benefits of moderate-to-vigorous intensity exercise [1]. However, there is also an acute increase in the risk for cardiac events during and following vigorous intensity activities in comparison to inactive periods in apparently healthy individuals [22] and in those individuals with underlying cardiac anomalies [23]. This transient risk is particularly prevalent in previously inactive individuals who engage in activities that are six metabolic equivalents or greater [24]. Given the popularity of high-intensity interval exercise within the spectrum from athlete to patient populations, as well as the increased participation by recreationally active individuals in ultra-endurance events, the examination of cardiovascular responses to 2  strenuous work warrants further investigtion. While our understanding of the acute response to high-intensity exercise is advancing, we have yet to discern clearly the effects of chronic training and the subsequent cardiovascular adaptations, known as the athlete’s heart [25] on cardiovascular risk. Furthermore, women have been underrepresented in exercise and clinical research. Recently, evidenced-based recommendations were presented advocating for the inclusion of women in clinical cardiovascular trials in equal numbers to that of men [26]. Accordingly, the purpose of this series of five investigations was to examine the effects of sex and training status on the cardiovascular responses to strenuous exercise. 1.2 OVERVIEW Chapter 2 is a review of the literature pertaining to cardiac function in healthy individuals; the impact of sex and endurance training, as well as potential mechanisms responsible for cardiac fatigue. The first investigation is presented in Chapter 3 where sex differences in cardiovascular function following an ultra-marathon are examined. Chapter 4 presents novel findings of sex differences following an acute bout of highintensity interval training in men and women of different fitness levels. Chapter 5 investigates baroreceptor sensitivity in men and women during an orthostatic challenge following high-intensity interval exercise. Chapter 6 examines the post-exercise hypotension response to high-intensity interval exercise, and Chapter 7 explores how post-exercise haemodynamics relate to measures of cognitive performance. Finally, Chapter 8 integrates the findings of these investigations, discusses their relevance and impact, and finally provides recommendations for further study. 3  Chapter 2: Literature Review Exercise places an increased demand on the cardiovascular system as it works to regulate the metabolic processes called upon to meet greater oxygen needs. The performance of the left ventricle plays an integral role in the effective performance of this system. The optimal performance of the left ventricle depends on a compliant chamber that supports diastolic filling under low atrial pressures, as well as effective ejection of blood (stroke volume) in systole at arterial pressures [27]. In addition, adequate diastolic filling ensures normal stroke volume according to the Frank-Starling mechanism [28]. Exercise-induced cardiac fatigue is a phenomenon shown to occur in the healthy heart as the result of strenuous exercise, and is characterized by a reduction in left ventricular systolic and diastolic function [19]. Systolic dysfunction represents impaired ejection of blood from the left ventricle, often due to a loss of cardiac inotropy (i.e., decreased contractility) [29]. Diastolic dysfunction represents inadequate ventricular filling with abnormal increases in diastolic pressures; alterations in the transmitral pressure gradient produced by changes in elastic recoil (suction), the rate of myocardial relaxation, chamber compliance, and left atrial pressure [27]. To date, the reported post-exercise depressions in ventricular function appear to be transient and small in clinical terms, however, the clinical relevance is not known [30]. Thus, the reliable assessment of ventricular and autonomic function is of key importance for establishing the impact of strenuous exercise on heart function. As such, this narrative review will provide a rationale for the non-invasive autonomic and left-ventricular assessments utilized in this dissertation research, provide a background of what is known pertaining to the impact of  4  sex and endurance training on these indices of cardiac function, and potential mechanisms underpinning reduced cardiac function with strenuous exercise. 2.1 NON-INVASIVE ASSESSMENT OF CARDIAC FUNCTION 2.1.1 Autonomic Function The autonomic nervous system plays a key role in cardiovascular control [31]. Increased activity in the sympathetic branch of the autonomic nervous system increases heart rate and constricts blood vessels, whereas an increase in parasympathetic activity opposes these actions [32]. The study of cardiovascular variability provides insight into cardiovascular control mechanisms [33] via analysis of heart rate variability, blood pressure variability, and/ or baroreflex function. Heart rate variability is a method of quantifying cardiac autonomic modulation through the examination of beat-to-beat fluctuations in heart rate, and is an independent predictor of morbidity and premature mortality (e.g., the incidence of disease and death rates increase in the presence of autonomic imbalance) [34, 35]. Heart rate variability reflects the time intervals between the peaks in the electrocardiogram (ECG) or normalto-normal (NN or RR) intervals. The variations in heart rate may be evaluated by time domain or frequency domain (spectral) measures. The time domain measures are derived from either direct measurements of the RR intervals or from the differences between RR intervals and spectral measures reflect how power (variance) distributes as a function of frequency [36]. The low frequency band (LF = 0.04 - 0.15 Hz) is suggested to reflect sympathetic control of the heart [37] with the high frequency band (HF = 0.16 - 0.4Hz)  5  representing respiration-driven vagal modulation of sinus arrhythmia [36]. Typical values in healthy humans are shown in Table 2.1.  Time Domain of Heart Rate Variability  Sedentary Trained  MeanNN (ms)  SDNN (ms)  rMSSD (ms)  pNN50 (%)  800 1100  70 95  40 70  20 40  Total Power (ms2)  LF (ms2)  HF (ms2)  1200-4000 1200-5000  200-900 800-1200  250-600 500-2500  Frequency Domain of Heart Rate Variability  Sedentary Trained Baroreflex Sensitivity  Healthy  BRS (ms/mmHg)  αLF (ms2)  αHF (ms2)  6 – 23  7 - 23  8 - 25  Table 2.1 Typical Heart Rate Variability and Baroreceptor Sensitivity Values for Healthy Individuals MeanNN = Normal to normal interval; SDNN = standard deviation of the RR intervals; rMSSD = square root of the mean squared successive differences between adjacent RR intervals; pNN50 = percentage of successive interval differences larger than 50 ms; LF = low frequency of HRV; HF = high frequency of HRV; αLF = low frequency of spectral BRS; αHF = high frequency of spectral BRS Table adapted from Aubert [33] and La Rovere [38]  The baroreflexes are neurocardiovascular reflexes that operate in a negative feedback fashion, in an attempt to maintain circulatory homeostasis. The baroreceptors are highly specialized stretch-sensitive nerve endings distributed throughout various regions of the cardiovascular system, which transmit neural impulses associated with their 6  activation/deactivation to the central nervous system [39]. Arterial (high pressure) baroreceptors refer to those located in the aortic arch (monitoring blood pressure to the systemic circuit) and carotid sinuses of the left and right internal carotid arteries (monitoring the blood pressure to the brain) [40]. Cardiopulmonary (low-pressure) baroreceptors are found in large systemic veins, pulmonary vessels, in the walls of the right atrium and ventricles of the heart, and are involved with the regulation of blood volume [41]. When an increase in blood pressure is sensed by the baroreceptors, efferent sympathetic outflow is inhibited and parasympathetic outflow is increased. As a result of this efferent response, bradycardia, decreased cardiac contractility, and decreased peripheral resistance and venous return ensues. When blood pressure decreases, an increase in sympathetic activity and vagal inhibition result in tachycardia, increased contractility, increased vascular resistance, and increased venous return [42]. The sympathetic arm of the baroreflex can be measured by changes in sympathetic outflow (i.e., muscle sympathetic nerve activity) in response to changes in baroreceptor input (i.e., a change in BP). The cardiac arm of the baroreflex influences prolongation or shortening of cardiac period in response to changes in baroreceptor input and is referred to as the cardiovagal baroreflex [43]. The cardiovagal baroreflex can be quantitatively assessed by deriving the slope or gain of the relationship between the R-R interval length and systolic arterial blood pressure [38]. Also termed baroreceptor sensitivity, lower levels of this baroreflex gain has been associated with an increased risk of cardiovascular related mortality [44, 45]. Baroreflex function decreases with age and this decline appears to be partially explained by agerelated increases in arterial stiffness [46]. The evaluation of baroreflex function by cross7  spectral analysis allows the assessment of the relationship between arterial blood pressure and R-R changes within the same frequency range (LF and HF as described above) and typical values found in Table 2.1. 2.1.2 Left Ventricular Function A non-invasive means of assessing ventricular function is via echocardiography. Left ventricular (LV) systolic function assessed via echocardiography in earlier research typically included the evaluation of ejection fraction, fractional shortening and velocity of circumferential fibre shortening, all considered indices of global left ventricular contractility [47]. These measures are highly dependent on changes in preload and afterload, thus data should be represented relative to loading. When invasive measures are not available, many studies use end-diastolic volume/diameter as a means to indicate preload, and arterial blood pressure or wall stress as an indicator of afterload [19]. Diastolic function may be assessed via global and regional indices. The ratio of early (E) to late (A) peak diastolic filling velocities is commonly employed as a global measure of diastolic function. With these Doppler derived transmitral filling velocities one can also ascertain the timing of the isovolumetric relaxation period and time of deceleration in early filling from peak velocity to baseline. The detection of altered filling characteristics of the LV can be enhanced by also examining the pulmonary venous flow velocities [48]. However, both mitral and pulmonary flow velocities are problematic as they are load and heart rate dependant [49]. Tissue Doppler imaging (TDI) measures the velocity of a given segment of the myocardium, providing an index of relaxation and contraction [50]. Pulsed-wave TDI for 8  peak myocardial velocity is typically measured at the mitral valve annulus, and colour TDI provides mean longitudinal myocardial velocities typically from the basal septal segment. The myocardial velocities obtained are reported for early diastole (Eˈ) and late diastole (Aˈ), in addition to the Eˈ/Aˈ ratio. The E/ Eˈ ratio has been shown to correlate with pulmonary wedge pressure [50-52]. As with the flow velocities, tissue velocities are also heart rate dependent [53]. More recently, the advent of 2D strain and strain rate analysis via speckle-tracking has provided regional motion analysis of the myocardium in the longitudinal, radial and circumferential planes [54]. Further, assessing rotational strain and strain rate at the base and apical levels of the LV using this technique may be used to determine twist and untwist [55]. LV rotation is an indicator of active diastolic relaxation [56] and shows promise as an early detection tool in various cardiovascular diseases [57]. 2.1.3 Arterial-ventricular coupling While alterations in cardiovascular performance in health or disease may be isolated to the arteries or heart, the effect of this impairment or enhancement will affect the net function of the complete system. Arterial-ventricular coupling allows for the assessment of the interaction of the arterial system and left ventricle. The arterial elastance (EA) component is calculated from end-systolic pressure / stroke volume (ESP/SV) while ventricular elastance (ELV) is derived from end-systolic pressure / end-systolic volume (ESP/ESV). Through this novel means, the ratio of EA/ELV provides an index of cardiac energetic efficiency versus cardiac mechanical efficiency [58]. For example, during exercise, EA/ELV will decrease in order to ensure adequate blood supply to the tissues, but 9  at the expense of energetic efficiency [59]. Arterial-ventricular coupling can be measured non-invasively; most simply via echocardiography and systolic brachial blood pressure providing mechanistic insights into the pathophysiology of various conditions [58]. A measurement in the range of 0.6 - 1.2 at rest is considered optimal, reflecting an ideal balance between mechanical efficacy and energetic efficiency [28]. 2.2 SEX DIFFERENCES IN CARDIOVASCULAR FUNCTION 2.2.1 Autonomic Function Increased vagal tone, or parasympathetic activity, is considered to be protective against cardiac events, whereas increased sympathetic activity is associated with higher risk of perturbing the heart [60, 61]. Significant sex differences have been identified with respect to autonomic function at rest. Work examining the influence of sex on HRV has revealed women demonstrate greater parasympathetic and less sympathetic control of heart rate than males (i.e., a lower LF/HF power ratio) [62-66] a factor potentially linked to the lower cardiovascular risk and increased longevity in females [64]. It is speculated that hormones may be partially responsible for the sex differences in autonomic function as sex differences in HF cardiac modulation are less apparent after the onset of menopause [67] and hormone-dependent afferent receptor stimulation, central reflex transmission, efferent nervous system, and postsynaptic signaling are dissimilar between the sexes [68]. With respect to blood pressure regulation women have been shown to have similar [69-71] or lower [71-76] cardiovagal baroreflex compared to men. Fluctuations in female hormones throughout the menstrual cycle have not been shown to influence baroreceptor 10  sensitivity; however oral contraceptive use does appear to affect the response [77, 78]. Of the aforementioned studies, only the work of Beske and colleagues [76] controlled for oral contraceptive use, in addition to other potentially confounding factors such as age, hypertension, smoking, obesity and aerobic fitness. As a result of controlling for these factors, the authors speculate that lower levels of carotid artery distensibility in women may be involved in attenuating the baroreflex response, as these factors were shown to be closely related in earlier work [79]. While the mechanism of this sex-based difference is not known, the age-related decline in baroreflex function appears to occur at similar rates in men and women [75]. 2.2.2 Left Ventricular Structure and Function Males have a greater cardiac size and volumes than females, associated directly with the larger body size of males. However, even after adjusting for body surface area, these differences in cardiac dimensions and volumes remain [80, 81]. Despite lower cardiac volumes in women, improved systolic function with a higher left ventricular ejection fraction for a given end-diastolic volume has been demonstrated [82]. Thus, it appears women have an advantage over men with respect to systolic function. To further support this notion, clinical research has revealed that in the progression to heart failure in older age, women tend to show impaired diastolic function whereas men predominately display systolic heart failure. In a study of healthy volunteers, diastolic function as measured by long-axis tissue velocities was reduced in women compared with men only for the older age group (>60 y) [83]. These sex differences may be related to hormones. LV relaxation falls below that of males around 45-55 years of age, in line with natural menopause [84]. 11  Reasons for this impaired relaxation are speculative. The vasodilatory effect of estrogen on the arterial system is a likely mechanism [85]; however, hormone replacement therapy has not led to improved cardiovascular function post-menopause [86, 87]. Despite this change in cardiac function in aging women, sex does not appear to augment LV rotation and twist across the lifespan [83, 88]. 2.3 CHRONIC TRAINING ON CARDIOVASCULAR FUNCTION 2.3.1 Autonomic Function Athletes typically display higher heart rate variability values than sedentary individuals. Long-term endurance training has been shown to positively influence autonomic nervous system activity via increases in heart rate variability, increased parasympathetic activity, and a decreased sympathetic activity of the heart at rest [62, 8993]. The mechanism for this reduced sympathetic control of heart rate is thought to result from reduced efferent sympathetic neural outflow to the sinoatrial node with endurance training [92, 94, 95]. Heart rate variability typically declines with age [96, 97]; however, sustained endurance training over many years may attenuate this decline [98, 99]. A comparison of aerobically trained and sedentary individuals is shown in Table 2.1. More typically used as a clinical indicator of health, these non-invasive autonomic indices have been used to assess the response to a physiological stress such as weightlessness [100], changes in central blood volume through lower body negative pressure [101], and/or exercise [102, 103]. Following exercise, parasympathetic activity is reduced; however, slow parasympathetic recovery may indicate autonomic imbalance [104]. In athletic populations, parasympathetic activity monitoring via heart rate 12  variability is often being used to reflect the state of recovery. When athletes are overreaching or over-trained (resulting when both training and non-training stressors overwhelms the body’s ability to recover adequately)[105], parasympathetic activity is reduced compared to baseline values [106]. Recently, baseline heart rate variability has been suggested to relate positively to the degree of adaptation in response to a 28-week training program in recreational runners [107]. Thus, the literature supports the use of heart rate variability as a simple, yet powerful method of assessing cardiovascular control. 2.3.2 Left Ventricular Structure and Function Chronic endurance training may cause an enlargement of the heart in some individuals, known as the athlete’s heart [25]. Unlike the pathologically induced ventricular hypertrophy seen in the ailing heart, training induces a physiological adaptation that is thought to be relatively benign [108]. Characteristic adaptations include increased chamber dimensions, increased left ventricular mass, and right ventricular dilatation all in the presence of enhanced systolic and diastolic function [109, 110]. While this eccentric hypertrophy is seen as normal adaptation to chronic endurance training, the similarity to hypertrophic cardiomyopathy or arrhythmogenic right ventricular dysplasia (linked to increased risk of sudden death in athletes) [111] warrants a better understanding of how to differentiate between these two states. Upper normal limits of chamber and wall dimensions (<66 mm and <15 mm, respectively) have been defined according to a meta-analysis [112]. Importantly, not all athlete cohorts present the classic features of the athlete’s heart likely due to sport-specific myocardial adaptations [113]. 13  Regular endurance training elicits an improvement in maximal aerobic power (VO2max) [114] largely due to cardiovascular adaptations. Vascular adaptations with endurance training result in benefits upstream [115] where the trained heart may experience less stress and produce a more efficient ejection [116] potentially reducing the required LV strain and twist observed in endurance athletes at rest [117, 118]. Further, under stress of intense exercise, an enhanced LV untwisting during exercise would be an important means of increasing the rate of LV filling when diastolic time is reduced [119, 120]. 2.4 MECHANISMS OF EXERCISE-INDUCED CARDIAC FATIGUE 2.4.1 Myocardial stunning and damage Exercise-induced cardiac fatigue has been proposed to cause transient ischaemia resulting from myocardial stunning [121] and subsequently causing disruptions in contractile function such as impaired myocyte relaxation [122]. Impaired LV function has been shown to be a transient phenomenon in which normal function is restored within hours following the exercise stress [123]; however to date, exercise-induced cardiac fatigue as the result of myocardial ischemia remains to be corroborated [20]. Myocardial damage has been a topic of much interest in the last decade as increased cellular protein levels have been detected following prolonged exercise. Cardiac troponin T and cardiac troponin I are specific markers of myocardial damage shown to be elevated post myocardial infarction [124]. However, the investigations to date have produced conflicting findings. Studies have either found no evidence of elevated levels of cardiac troponins [125, 126], elevated levels in the occasional participant [127, 128], or elevated 14  levels in 10-60% of participants [129-133]. Shorter duration high intensity exercise (e.g., 30 minutes of intense running) has also revealed elevated cardiac troponin T [134]. However, analysis of the true incidence of post-exercise myocardial injury is hampered by small sample sizes and methodological variation. Cardiac troponin is released into circulation around 3-4 h post-exercise and peaks at approximately 12-18 h post-exercise [125] thus many investigations may have been unable to detect transient changes in these biomarkers. In a recent meta-analysis, Shave et al. [135] (encompassing 26 investigations) found exercise-induced cardiac troponin T was elevated in half of the participants studied. Further, these occurred in shorter endurance events (such as the marathon). While much remains unknown, given the available data, the validity of elevated troponin levels post-exercise representing myocardial injury has been questioned [136]. 2.4.2 β-adrenergic down-regulation Pharmacological interventions such as isoproterenol and dobutamine have demonstrated a reduced cardiac β-responsiveness following prolonged strenuous exercise [137-141]. This reduced β-adrenergic sensitivity may contribute to the attenuated LV systolic function demonstrated with prolonged strenuous exercise [138] and appears to be affected by sex [139] and age [142]. A prolonged increase in circulating catecholamines may be related to this altered sympathoadrenal response. Catecholamines support the sympathetic system in modifying the circulation during exercise, increasing heart rate, contractile force and cardiac output by stimulation of the adrenergic β-1-receptors in the myocardium [143]. It is thought that elevated circulating catecholamines from strenuous 15  exercise lead to decreased functional activity of cardiac β1-adrenergic receptors and thus to marked desensitization of the heart to inotropic β-adrenergic stimulation [144]. Catecholamine levels have been positively associated with exercise intensity [145] and thus parallels findings of greater reductions in β-adrenergic sensitivity with higher exercise intensity in animals [146] and very recently, in humans [141]. However recent work in an animal model of prolonged strenuous exercise found no change in cardiac response to beta-receptor stimulation in isolated rat hearts, but rather found evidence of oxidative stress [147]. These researchers suggest that by using an isolated perfused rat heart model, intrinsic myocardial fatigue can be introduced without potential confounders such as catecholamines and altered loading conditions. Further work is required to ascertain the role of β-adrenergic receptors in the mechanism of cardiac fatigue [148]. 2.4.3 Oxidative Stress Cardiac oxidative stress may impair cardiac function through oxidative damage to cellular proteins and membranes [149, 150]. Chronic increases in oxygen radical production in the mitochondria as seen in myocardial remodelling and heart failure, can lead to a catastrophic cycle of mitochondrial DNA damage as well as functional decline, further oxygen radical generation, and cellular injury [151]. Nicotinamide adenine dinucleotide phosphate-oxidase (NADPH), a source of reactive oxygen species is well  known for its role in cardiac dysfunction [152] and is increased in response to tachycardia or exercise [153]. Recently, an increase in oxidative stress was shown in myocardial rat tissue after prolonged strenuous exercise, a response not seen when NADPH oxidase was  16  inhibited [147]. These authors propose this oxidative stress may initiate the transient vascular and/ or cellular alterations observed in myocardial stunning. 2.4.4 Elevated Free Fatty Acids Implicated as having a role in exercise-induced cardiac fatigue elevated free fatty acids have been reported to be significantly elevated following prolonged exercise [154] [155]. Through a cascade of metabolic events, free fatty acids are thought to reduce the efficiency of mitochondrial respiration [156]. However, elevations in free fatty acids reported following prolonged strenuous exercise was deemed too low to have had an impact in the exercise-induced cardiac fatigue presented [157]. More recently, elevated free fatty acids were shown to have no effect on LV performance in heart failure patients with Type II diabetes [158], thus the propensity of free fatty acids altering ventricular function in healthy individuals does not appear to be likely. 2.5 CONCLUSIONS Advances in echocardiography have improved our ability to assess cardiac function in a variety of situations and populations. As recreational exercise evolves to include more extreme pursuits, our ability to monitor the physiological impact of these activities in ‘ordinary’ individuals becomes more important. The literature herein has provided a brief review of current concepts in acute and chronic responses and adaptations to strenuous exercise in healthy men and women. However, significant gaps persist with respect to the etiology of exercise-induced cardiac fatigue and how various factors impact its development. Further the cardiovascular adaptations occurring during recovery from strenuous exercise remains to be fully elucidated. 17  Chapter 3: Sex Differences in Cardiac Function Following Prolonged Strenuous Exercise  3.1 INTRODUCTION Exercise-induced cardiac fatigue is characterized by a reduction in left ventricular systolic and diastolic function subsequent to exercise in healthy humans [19] and becomes evident following bouts of prolonged strenuous exercise [20]. These reductions in left ventricular performance have been found to occur despite the absence of underlying cardiovascular pathologies [154, 159-161], and appear to be transient in nature with normal function restored typically within 48 h [123]. Notwithstanding, given the association of an increased incidence of sudden cardiac events with acute exercise in those at risk [162], the clinical relevance of exercise-induced cardiac fatigue warrants further study [163-165], particularly considering the appreciable increase in ultraendurance participation over recent years [3]. The average age of winning ultramarathoners are older than the typical age of winning marathoners [18]. This may be interpreted to suggest that in order to perform well in ultra-endurance events, accumulating greater years of training may be beneficial. However, our understanding of the cumulative effects of chronic ultra-endurance training is limited. Another emerging trend is the increase in female participants in ultra-endurance events. A recent analysis of the participation trends in ultra-marathons revealed a 20% increase in the percentage of female finishers [166]. Despite this increase in female competitors, the literature to date has yielded limited information regarding the cardiovascular consequences of ultra-endurance exercise in women. Our research group 18  has found that both men and women experienced a reduction in LV systolic function as a consequence of a half-ironman triathlon, with a greater reduction exhibited in the males [139]. Prolonged strenuous exercise has been shown to significantly increase plasma catecholamines [167] a marker of sympathetic activity. Phenotypical evidence of sex differences in cardiac norepinephrine transporter function [168] suggests that males exhibit differences in cardiac-specific sympathetic activity. As such, greater sympathetic activity in males may be responsible for the greater reductions in cardiac function shown following prolonged-strenuous exercise in males versus females [139]. However, further work is required to substantiate these earlier findings using assessments of regional myocardial function, such as strain and strain rate imaging, that allows for a more thorough analysis of left ventricular function [169]. In addition, sex differences have not been investigated following a longer duration event such as an ultra-marathon. Accordingly, the purpose of this investigation was to evaluate sex differences in cardiac function following an ultra-endurance running race. We hypothesized that following an ultra-marathon men would display evidence of marked exercise-induced cardiac fatigue compared with women. 3.2 METHODS 3.2.1 Participants and Ethical Approval Thirty-four competitors (43.4 ± 8.2 y; 13 F) participating in a mountain trail running ultra-marathon (Fat Dog 100) volunteered to participate in this research. This field study occurred mid-summer in British Columbia, Canada. Runners were exposed to temperature fluctuations ranging from 6 to 30 degrees Celsius between day and night19  time hours. The terrain was very mountainous with ascents of 600 – 2300 m over two race distances (100 km and 160 km). Prior to testing, all participants completed the Physical Activity Readiness Questionnaire for Everyone (PAR-Q+; Appendix A) and provided written informed consent in exact accordance with the guidelines established by the Clinical Research Ethics Review Board at the University of British Columbia. 3.2.2 Experimental Protocol Baseline testing occurred one to two days prior to the start of the race in dedicated research space on site. Advance testing at the University of British Columbia was completed in four participants at four days prior to the race. Participants completed a training history questionnaire (Appendix B) for the determination of training volume and race experience. Assessments included basic anthropometrics, arterial compliance, baroreflex function, and echocardiography. At the completion of the race, participants were directed to the research site for repeat assessments, within 30 minutes from crossing the finish line. Runners were to complete a minimum of 50 km to be included in post-race analysis. 3.2.3 Procedures and Analysis Anthropometrics, Autonomic and Arterial Compliance Assessments. Following the collection of body height and mass, participants were prescribed five minutes of seated rest and were measured for three consecutive measures of seated resting blood pressure (BP-TRU, VSM Medical, Vancouver, BC). Post-race, measures of body mass and blood pressure were conducted at the race finish line prior to transportation to the on-site  20  research testing facility. Body surface area was calculated as BSA (m2) = SQR RT ([Height(cm) x Weight(kg)]/ 3600 ) [170]. At the research testing facility, autonomic function and arterial compliance were evaluated following five minutes of supine rest. Baroreceptor sensitivity (BRS) was determined from the simultaneous assessment of beat-by-beat blood pressure and ECG. Five minutes of continuous blood pressure data was collected using finger photoplethysmography (Finapres, Ohmeda Inc, Englewood, CO), calibrated using an automated blood pressure device (Bp-TRU 100, Coquitlam, Canada) along with threelead electrocardiography (I, II, III) on Chart software (Version 5.5.6). During this assessment, participants remained supine while wearing industrial strength ear protectors to block-out the ambient noise in the room. BRS analysis occurred off-line after the race at the Cardiovascular Physiology & Rehabilitation Laboratory at UBC. A minimum of 140 s of continuous cardiac cycles were evaluated to determine HRV and BRS. Power spectral evaluations of HRV and BRS were conducted by the same investigator using Nevrokard BRS software (Version 6.1.0, Nevrokard, Kiauta, Slovenia) as described previously [171]. The investigator was blinded to participant testing conditions during this analysis through blinded coding of file names. Arterial compliance was measured non-invasively via applanation tonometry with the HDI CR-2000 (Hypertension Diagnostics, Eagan, Minnesota) for diastolic pulse contour analysis. After stabilizing the wrist and maximizing signal strength, radial artery tonometry measurements were collected using the right wrist with the automated sphygmomanometer affixed to the upper left arm. Measurements were taken in duplicate with the average used for analysis. The calculations of small and large arterial 21  compliance are accomplished by the software of the applanation tonometry unit using a paradigm described in detail elsewhere [172] which divides total systemic resistance into individual components using mathematical modeling. This technique has been validated with invasive and non-invasive testing [173, 174]. Echocardiographic Assessments. Two-dimensional transthoracic and pulse-Doppler imaging was used to assess LV function using a commercially available portable ultrasound system (Vivid i, GE Medical Systems, Israel) with simultaneous ECG and a 2.5-MHz transducer. Participants were positioned in the left lateral decubitus position for imaging. Cardiac images were acquired by a single clinically certified sonographer according to the American Society of Echocardiography guidelines [175]. Apical two and four-chamber views were acquired for the assessment of stroke volume (SV), LV longitudinal strain (S) and strain rate (SR). Transmitral pulsed Doppler recordings assessed early (E) and late (A) diastolic filling, and pulmonary venous flow velocities were obtained. Myocardial tissue velocities were assessed at the mitral annulus of the LV septal wall (Eˈseptal) and lateral wall (Eˈ lateral), as well as the right ventricular lateral wall (EˈRV). Parasternal short axis views obtained at the basal level were obtained to derived circumferential and radial strain and SR data as described in detail elsewhere [176]. Briefly, the basal level was defined as the level of the first appearance of the superior surface of the papillary muscle when imaged down from the mitral valve and imaged at high frame rates (70-90 frames per second). Ventricular volumes and diameters were analyzed off-line (EchoPAC, GE Healthcare, v. 110.1.1) in accordance with the recommendations of the American Society of Echocardiography [175]. Left ventricular mass was determined using the formula: LV 22  Mass (g) = 0.8 (1.04 ([LVIDD + PWTD + IVSTD]3- [LVIDD]3))+ 0.6 [177]. Enddiastolic volume (EDV) and end-systolic volume (ESV) using Simpson’s bi-plane method for which 3 consecutive beats were measured and analyzed. Stroke volume was calculated by EDV-ESV. Cardiac output (CO) was calculated as SV x HR. Ejection fraction (EF) was calculated as a percentage of EDV. Fractional shortening (FS) was calculated from ventricular diameters using the parasternal long axis window and expressed as a percent. Total peripheral resistance (TPR) was derived from dividing CO into MAP. End-systolic meridional wall stress (WS) was determined non-invasively as WS (g.cm-2) = 0.334(SBP)(LVESD) /PW(1 + PW) / LVESD, where SBP is systolic blood pressure, LVESD is left ventricular end-systolic diameter, and PW is left ventricular systolic posterior wall thickness [178]. Evaluation of E/Eˈ for both the septal and lateral walls provided an estimate of LV filling pressures. 3.3 STATISTICAL ANALYSIS Between sex characteristics were analyzed using Student’s unpaired t tests. A twoway analysis of variance (ANOVA) was used to evaluate the effect of sex on changes in cardiac function with exercise (repeated factor). The change in LV functional measures from pre- to post-race (∆) was correlated with age, baseline vascular and autonomic indices, in addition to performance and training variables, using Pearson correlation. Linear regression analysis was used to determine the factors responsible for the change in cardiac function. Significance for all tests was set a priori at p<0.05. All analyses were performed using SPSS software (version 20.0; SPSS IBM, Chicago, IL). Results are reported as mean ± SD. 23  3.4 RESULTS 3.4.1 Participant Characteristics Thirty-four participants completed baseline assessments, while 25 individuals (8 F; 32%) returned for follow-up testing (n = 21 of European ethnicity, 3 Asian and 1 Metis). Attrition was due to participants dropping out of the race and decided not to continue with the study. Training volume, race experience, and race practices did not differ between the sexes. Participants trained on average 5 ± 1 d/wk, running 86.0 ± 34.6 km/wk. The group averaged 5.1 ± 3.4 years of competing in ultra-marathons (range 1 to 15 years). Total number of lifetime ultra-marathons averaged 14.2 ± 12.6 (range 0 to 53), with the last reported event occurring 51.5 ± 52.9 days prior to this event. Number of ultra-marathons completed in the year prior to this investigation was 2.5 ± 1.9. Runners reported an average taper of 14.3 ± 11.3 days and 9.7 ± 9.5 days since their last training session. Eighty-four percent of the participants reported ingesting sodium supplements during the race and regularly do so in training. Maximal aerobic power (VO2max) was assessed in four males and three females (VO2max = 48.2 mL.kg.-1min-1; range = 41 - 56 mL.kg.-1min-1) who volunteered to have this assessed approximately 4 weeks post-race (to allow for adequate recovery). As these seven individuals represented 28% of the participants, this information is presented for information purposes only. Participant characteristics and baseline cardiovascular measures are found in Table 3.1. 3.4.2 Participant Performance All 25 individuals met the minimum distance criteria, with an average race distance of 134.1 ± 48.8 km completed for the group, over a time course of 27.6 ± 8.9 h (9.0 to 41.9 24  h). Our sample represented 43% of total race entrants. Our 19 finishers represented 59% of total race finishers placing 1st to 16th for the men (n = 14) and 3rd to 15th for the women (n = 5). As such, our participants represented the upper end of the ultra-endurance athlete continuum. While our sample of women was small relative to the men and consisted of 32% of our total sample, this was in proportion to the total women entered in the race (8 out of 19F; 33%). There were no significant differences between sex for race completion time (29.0 ± 8.6 vs. 25.9 ± 9.7 h), race pace (4.7 ± 1.1 vs. 4.8 ± 0.7 km/h) or race distance completed (141.8 ± 50.4 vs. 121.1 ± 48.4 km) for men and women, respectively. 3.4.3 Physiological and Cardiovascular Outcomes From pre-race baseline, body weight decreased an average of 1.5 ± 3.1 kg (p = 0.02). At the finish line, blood pressure and heart rate responses did not differ by sex. In comparison to baseline, seated blood pressure was not significantly reduced post-race: SBP from 116.2 ± 12.9 to 114.2 ± 14.2 mmHg, respectively; DBP from 76.5 ± 7.2 to 76.1 ± 11.0 mmHg, respectively. The HR assessed at the finish line was significantly higher than observed at pre-race (89.6 ± 13.7 vs. 62.3 ± 8.2 bpm, respectively p < 0.001). There were no interactions found for the cardiac variables measured over time (pre-, postexercise) and sex. Between subject differences were found for baseline cardiac structure and global function where men displayed larger LV diameters and volumes, cardiac output, and lower total peripheral resistance (p < 0.05; Table 3.2). Due to the lack of sexbased interactions, the pooled findings (across sexes) are shown in Tables 3.3 and 3.4 to illustrate the effects of exercise on the remaining cardiac variables. No between sex, or sex by time interactions, were found for the EAI/ELVI ratio (pre-exercise: 0.52 ± 0.14, 25  post-exercise: 0.58 ± 0.22, p = 0.245). Changes in BRS with exercise, is represented in Figure 3.1. Statistically significant bivariate correlations are displayed in Table 3.5. Change in body mass, HR, SBP, ESP/EDV, and E/A were not correlated with any of the cardiovascular outcomes. Change in longitudinal strain was significantly correlated with life-time ultra-marathons (Figure 3.2) and race-pace (Figure 3.3).  Table 3.1 Participant Characteristics and Baseline Cardiovascular Measures Variable  Men (n = 17)  Women (n = 8)  p value  Age, y Height, cm Body Mass, kg BMI, kg.m2 LVM, g LVM/BSA, g.m-2 SBP, mmHg DBP, mmHg HR, bpm CO, L.min-1 LAC, mL.mmHg.10 SAC, mL.mmHg.100 RRI LF/HF BRS, ms.mmHg  44.8 ± 6.6 177.8 ± 6.3 77.6 ± 9.3 24.5 ± 2.4 214.7 ± 47.1 109.6 ± 22.5 128.4 ± 7.9 73.0 ± 7.0 63.5 ± 7.1 5.14 ± 1.21 18.3 ± 6.0 9.7 ± 3.1 2.25 ± 1.32 18.5 ± 11.6  45.9 ± 10.2 162.7 ± 5.1 58.9 ± 3.6 22.3 ± 1.4 160.8 ± 30.7 98.5 ± 18.0 120.8 ± 12.5 69.3 ± 7.1 59.6 ± 5.2 4.00 ± 0.80 14.0 ± 3.2 6.0 ± 2.1 0.88 ± 0.92 25.0 ± 17.6  0.758 0.000 0.000 0.023 0.007 0.235 0.073 0.230 0.221 0.026 0.074 0.006 0.022 0.310  Abbreviations: BMI = body mass index; LVM = left ventricular mass; BSA = body surface area; SBP = systolic blood pressure; DBP = diastolic blood pressure; HR = heart rate; CO = cardiac output; LAC = large artery compliance; SAC = small artery compliance; RRI = ratio of low frequency to high frequency of RR intervals; BRS = baroreceptor sensitivity The effect of sex on participant characteristics was analyzed by unadjusted general linear models for continuous variables. BOLD p values denotes statistically significant  26  Table 3.2 Cardiac Dimensions and Global Systolic Function Pre-exercise  Post-exercise  Variable  LVPWd, cm LVIVSd, cm LVEDD, cm ¥ LVPWs, cm ¥ LVIVSs, cm ¥ LVESD, cm LVEDV, mL ¥ LVESV, mL ¥ SV, mL ¥ SVI, mL/BSA EF, % CO, L.min-1 ¥ CI, L.min-1/BSA FS, % SBP/ESV ¥ TPR, mmHg .L.min-1 ¥ Wall Stress, x103 dyn.cm2  Men  Women  Men  Women  0.98 ± .18 1.3 ± .20 4.81 ± .35 1.74 ± .18 1.88 ± .16 2.86 ± .41 138.4 ± 25.1 46.7 ± 13.0 91.7 16.0 46.9 ± 7.8 66.4 5.2 5.19 ± 1.19 2.65 ± 0.55 40.9 ± 6.4 2.91 ± 0.69 18.6 ± 5.0 67.7 ± 4.0  0.89 ± .25 1.2 ± .16 4.41 ± .43 1.53 ± .26 1.61 ± .23 2.54 ± .39 100.9 ± 7.1 34.0 ± 8.9 66.9 8.4 41.2 ± 6.3 66.4 8.3 4.01 ± 0.80 2.47 ± 0.55 42.5 ± 6.5 3.89 ± 1.60 22.6 ± 6.3 67.3 ± 7.0  1.1 ± .27 1.4 ± .30 4.44 ± .52 1.74 ± .28 1.84 ± .24 2.91 ± .33 111.5 ± 16.0* 40.1 ± 10.2* 71.4 14.7* 36.9 ± 8.9* 63.8 7.8 5.16 ± 1.31 2.65 ± 0.68 34.1 ± 7.6* 3.17 ± 0.72* 17.7 ± 5.2 64.0 ± 5.9  0.95 ± .18 1.2 ± .13 4.21 ± .33 1.39 ± .25 1.50 ± .22 2.75 ± .32 87.8 ± 11.1* 30.4 ± 11.2* 57.4 12.0* 35.2 ± 7.1* 65.5 11.6 4.24 ± 1.09 2.60 ± 0.66 34.6 ± 7.9* 4.40 ± 2.09* 20.2 ± 4.7 67.0 ± 4.8  Abbreviations: LV = left ventricular; PWd = posterior wall in diastole; IVSd = intraventricular septum in diastole; EDD = enddiastolic diameter; PWs = posterior wall in systole; IVSs = intraventricular septum in systole; ESD = end-systolic diameter; EDV = end-diastolic volume; ESV = end-systolic volume; SV = stroke volume; SVI = stroke volume index; EF = ejection fraction; CO = cardiac output; CI = cardiac index; FS = fractional shortening; SBP = systolic blood pressure; TPR = total peripheral resistance Effect of exercise obtained using general linear models adjusted for sex. * p<0.05 from baseline; ¥ P<0.05 between men and women 27  Table 3.3 Doppler Flow Velocities  Variable E, m/s A, m/s E/A DecT, ms IVRT, ms S, m/s D, m/s S/D Ar, m/s Ar Duration, ms  Men  Pre-exercise Women  0.81 ± 0.20 0.53 ± 0.10 1.28 ± 0.68 216.9 ± 40.4 84.4 ± 14.9 0.56 ± 0.12 0.50 ± 0.13 1.02 ± 0.46 0.24 ± 0.03 142.8 ± 34.5  0.84 ± 0.18 0.57 ± 0.13 1.55 ± 0.51 206.0 ± 35.7 89.8 ± 11.7 0.52 ± 0.08 0.47 ± 0.11 1.13 ± 0.13 0.25 ± 0.04 133.4 ± 25.9  Men  Post-exercise Women  0.68 ± 0.13 0.55 ± 0.11 1.26 ± 0.33 206.4 ± 38.7 83.1 ± 10.4 0.51 ± 0.17 0.43 ± 0.07 1.17 ± 0.28 0.24 ± 0.05 123.5 ± 29.3  0.84 ± 0.08 0.67 ± 0.12 1.30 ± 0.27 189.9 ± 22.2 73.5 ± 19.4 0.50 ± 0.15 0.47 ± 0.08 1.05 ± 0.21 0.26 ± 0.04 119.6 ± 12.0  *  p value #  €  0.096 0.093 0.299 0.092 0.045 0.433 0.343 0.602 0.995 0.030  0.108 0.248 0. 379 0.713 0.082 0.723 0.310 0.151 0.604 0.678  0.039 0.153 0.433 0.091 0.129 0.341 0.191 0.277 0.871 0.015  Abbreviations: E = peak early transmitral flow velocity; A = peak late flow velocity; DecT = E wave deceleration time; IVRT = isovolumetric relaxation time; S = peak systolic pulmonary venous flow velocity; D = peak diastolic pulmonary venous flow velocity; Ar = peak atrial reverse pulmonary artery flow velocity BOLD p values denotes statistically significant Effect of exercise obtained using general linear models adjusted for sex. * from pre-exercise; # sex by time interaction; € from pre-exercise (pooled data – all subjects)  28  Table 3.4 Tissue Doppler Imaging and Strain Variable Tissue Velocities E’ septal, m/s E/E’ septal E’ lateral, m/s E/E’ lateral E’ RV, m/s Strain / Strain Rate Longitudinal S, % Longitudinal SRsys, s-1 Longitudinal SRdia, s-1 Circumferential S, % Circumferential SRsys, s-1 Circumferential SRdia, s-1 Radial S, % Radial SRsys, s-1 Radial SRdia, s-1  Pre-exercise Men  Women  Post-exercise Men Women  0.13 ± 0.03 5.10 ± 3.25 0.17 ± 0.03 3.91 ± 2.10 0.15 ± 0.03  0.12 ± 0.03 7.24 ± 1.81 0.16 ± 0.04 5.63 ± 1.98 0.15 ± 0.03  0.11 ± 0.02 5.96 ± 1.03 0.15 ± 0.04 4.64 ± 0.89 0.15 ± 0.03  -21.02 ± 1.98 -1.05 ± 0.13 1.37 ± 0.24 -17.64 ± 5.02 -1.06 ± 0.31 1.16 ± 0.49 -1.87 ± 1.15 1.77 ± 0.44 -2.04 ± 0.50  -20.28 ± 1.90 -1.00 ± 0.11 1.47 ± 0.24 -18.39 ± 5.24 -1.04 ± 0.32 1.32 ± 0.58 -4.06 ± 4.02 1.61 ± 0.46 -1.88 ± 0.72  -18.44 ± 1.87 -1.08 ± 0.18 1.29 ± 0.30 -17.69 ± 4.95 -1.25 ± 0.33 1.15 ± 0.43 -4.57 ± 4.95 1.94 ± 0.46 -2.06 ± 0.67  *  p value #  0.11 ± 0.02 8.24 ± 2.02 0.15 ± 0.04 5.67 ± 1.27 0.14 ± 0.03  0.008 0.121 0.021 0.331 0.390  0.946 0.899 0.156 0.391 0.729  0.005 0.100 0.004 0.172 0.420  -18.44 ± 2.34 -1.02 ± 0.22 1.52 ± 0.31 -18.49 ± 4.59 -1.10 ± 0.25 1.44 ± 0.56 -2.10 ± 1.52 1.84 ± 0.51 -2.38 ± 0.50  0.001 0.606 0.854 0.933 0.112 0.639 0.751 0.125 0.198  0.518 0.920 0.329 0.976 0.404 0.544 0.058 0.798 0.238  0.000 0.546 0.565 0.937 0.036 0.810 0.603 0.109 0.381  €  Abbreviations: Eˈ = myocardial tissue velocity; E = peak early transmitral flow velocity; RV = right ventricle; S = strain; SR = strain rate; sys = systolic; dia = diastolic Effect of exercise obtained using general linear models adjusted for sex. BOLD p values denotes statistically significant * from pre-exercise; # sex by time interaction; € from pre-exercise (pooled data- all subjects)  29  45 40 35 30 25  *  *  Men  20  Women  15 10 5 0 Baseline  Post-exercise  Figure 3.1 Change in Baroreceptor Sensitivity with Prolonged Exercise * p<0.05 between rest and exercise  Table 3.5 Significant Correlations Associated Variables  Pearson r  p value  Age, Δ Longitudinal Strain Race Pace, Δ Longitudinal Strain LAC, Δ Longitudinal Strain Total Ultras, Δ Longitudinal Strain Δ HR, Δ Fractional Shortening preLF/HF, Δ Longitudinal Strain LAC, Lifetime Ultras  -0.40 0.49 0.59 0.42 0.69 -0.41 0.47  0.048 0.012 0.002 0.035 0.000 0.049 0.017  Abbreviations: Δ = change; LAC = large artery compliance; HR = heart rate; BRS = baroreceptor sensitivity; SR = strain rate; dia = diastolic; sys = systolic; LF = low frequency; HF = high frequency Data obtained from Pearson’s Correlation analysis  30  60  Lifetime Ultra-marathons (#)  50  40  30  20  10  0 -8.00  -6.00  -4.00  -2.00  0.00  2.00  4.00  Change in Longitudinal Strain (%) Figure 3.2 Association of Lifetime Ultra-marathons to Longitudinal Strain Pearson r=0.423, p=0.035 Linear Regression r2=0.21, Std Beta=0.438 (adjusted for sex) p=0.031  31  8.00 7.00  Race Pace (km/hr)  6.00 5.00 4.00 3.00 2.00 1.00 0.00 -8.00  -6.00  -4.00  -2.00  0.00  2.00  4.00  Absolute Change in Longitudinal Strain (%)  Figure 3.3 Association of Race-Pace to Longitudinal Strain Pearson r=0.493, p=0.012  32  3.5 DISCUSSION We aimed to compare the cardiovascular response to prolonged strenuous exercise between men and women. The major findings of this investigation are that 1) men and women displayed similar indications of exercise-induced cardiac fatigue following an ultra-marathon, and 2) more experienced runners displayed less exercise-induced cardiac fatigue. This paper represents the first comparison of the cardiovascular response to an ultra-marathon between men and women. Following an ultra-marathon, we showed evidence of systolic and diastolic impairment, confirming previous findings in ultra-marathons [157, 176, 179] and other forms of prolonged exercise [180-182]. Other than fractional shortening, decrements in systolic function as indicated by post-exercise reductions of longitudinal strain, and myocardial wall velocities, were unrelated to a change in loading conditions (HR, and indirect measures of preload and afterload). Furthermore, the reductions in peak early transmitral flow velocity and pulmonary vein atrial reverse flow duration in the current investigation, is evidence of impaired LV relaxation [182]. Contrary to our hypothesis, we did not find sex to influence the response to an ultramarathon. Early diastolic filling appears to have reduced to a greater extent in the men but may not have reached statistical significance due to our small sample size. The issue of sample size is addressed further in the limitations section. To our knowledge, only an earlier investigation from our laboratory had the objective of comparing sex differences in the acute response to ultra-endurance exercise in triathletes [139]. In this prior work, contractility was found to differ among men and women. However, in the present  33  investigation, we did not find a sex difference with our indicators of contractility. La Gerche et al. [180] studied a similar sample of men and women to that of our previous work; however, they did not report any sex differentiation other than pre-race characteristics. Other than sample size considerations, the discrepant findings between our current and past work may be explained by differences in the exercise stimulus employed involving different exercise intensity (estimated from running pace to be 80 vs. 50% of maximum capacity), and duration (6 vs.29 h) for the half-ironman triathlon and ultra-marathon, respectively. The combined impact of intensity and duration on exerciseinduced cardiac fatigue is unclear. The varied intensities and competitive situations within the literature make isolating any dose-response difficult [19]; however we speculate that exercise-induced cardiac fatigue may present differently in response to varied exercise intensities and durations. Despite the lack of interactions between exercise-induced cardiac fatigue and sex, we did find a number of between group sex differences. As expected, men had greater LV mass, greater cardiac dimensions and volumes, with most differences disappearing when indexed for body surface area. Men also showed greater resting small artery compliance and a trend of higher large artery compliance. Arterial compliance has been shown to relate to artery diameter [183] and possibly explains the sex difference. Another commonly used indicator of cardiovascular health is that of RRI LF/HF. Women typically demonstrate greater parasympathetic and less sympathetic control of heart rate than males (i.e., a lower LF/HF power ratio) [62-66] a factor potentially linked to the lower cardiovascular risk and increased longevity in females [64]. Our results are in  34  agreement with this; however, the relevance of the positive association between this ratio and baseline radial systolic strain rate is unclear. The lack of marked exercise-induced cardiac impairment was unexpected considering the significant duration and volume of exercise engaged in by our participants. This is particularly salient as exercise duration has previously been shown to be associated with exercise-induced cardiac fatigue [161, 184] most notably in exercise sessions longer than 6 h [160]. In particular, only longitudinal strain was reduced significantly from baseline. Similar investigations have found reductions in radial, circumferential and longitudinal strain, in addition to reductions in strain rates [176, 181]. Our findings of reduced LV tissue velocities are in agreement with these findings; however, the lack of altered strain rate was unexpected. We propose two possible explanations for the lower degree of exercise-induced cardiac fatigue in our results: temperature and intensity. While our race was similar in duration to the ultra-marathon of the Western States Endurance Race, the California racers would have had much higher thermal strain to contend with than our temperate mountain race. Heat stress translocates blood volume from the centre to the periphery for which the demand for skin blood flow is met in part by an increase in cardiac output [185]. Severe heat stress during whole body exercise pushes the cardiovascular system to its regulatory limit, where cardiac output and blood flow to exercising limb muscles and skin cannot be maintained for a longer duration. It has been postulated that a small attenuation in the myocardial perfusion-to-work relationship may occur, leading to impaired myocardial function, as oxygen (extraction) reserve is too small to compensate  35  for a significant blunting in oxygen supply [186]. Thus, we cannot rule out the effects of thermal strain field measures of cardiac function. Another consideration relative to the magnitude of cardiac fatigue is the extreme mountainous terrain of the Fat Dog 100 where four major ascents /descents may have induced considerable neuromuscular fatigue [187] and as a result lowered exercise intensity enough to spare cardiovascular fatigue. Mattsson and colleagues [188] recently showed that when exercise duration exceeds 24 h, cardiac work (stroke work x heart rate) and myocardial oxygen consumption decrease, likely as a physiological adaptation to maintain cardiac output when total energy expenditure demands are high. A novel finding in our work is that runners who have run more ultra-marathons in their lifetime demonstrated less evidence of exercise-induced cardiac fatigue in this ultramarathon. This correlation is intriguing considering the efficacy and potential risks of long-term ultra-endurance training are not yet understood clearly [165]. It has been hypothesized that repetitive strenuous exercise could lead to fibrous replacement of the myocardium potentially propagating arrhythmias [189]. We hypothesize that this finding is related to fitness, as we also found the degree of EICF correlated strongly with race pace. Thus, the individuals capable of running faster actually experienced less cardiac fatigue. This initially appears to contradict our intensity hypothesis; yet if we consider the terrain of the race course, it is possible that the cardiovascular strain of this race was not as severe for highly trained as compared to less trained individuals. Cardiac output and perfusion pressure are compromised in untrained individuals when both the metabolic and thermoregulatory demands are high [186]. Further, in a meta-analysis reviewing LV function with ultra-endurance exercise, one of the factors influencing a decline in systolic 36  function was poor training status [123]. In an analysis of performance trends in ultramarathons, Hoffman et al. found an increase in recreational pursuits with the goal of finishing [18]. The small sample of individuals from our cohort who participated in VO2max testing possessed low aerobic capacity relative to athletic norms [190]. Longitudinal studies are warranted to determine the nature of cardiac fatigue and training status. 3.6 LIMITATIONS The following limitations must be considered in this investigation. First, the smaller sample size representing our female subjects increases the probability of making a Type II error. Recruitment of participants in field studies is limited to those runners who wish to participate. As ultra-endurance competitors are typically only 20% female [166] it becomes increasingly difficult to study females when there are so few available. After attrition, females represented 32% of our cohort. However, this is in proportion to the female racers participating in the event. In concert with the same recruitment issues, it is also not possible to recruit based on fitness. Our sample included the first place finisher completing the race in 28 h with our last finisher coming in at 41 h. As logistical issues limited the assessment of each participant’s aerobic capacity, we are unable to determine if the men and women were equal with respect to relative VO2max. As such cannot rule out the possible effect of fitness in the sex response to prolonged strenuous exercise [165]. Another consideration pertains to sodium. Sodium supplementation was quite prevalent in our sample of ultra-marathoners. In this field research we were unable to 37  control for the form, quantity, and frequency of sodium ingested. Sodium loading has been shown to increase plasma volume at rest and reduce physiological strain in warm conditions, significantly improving exercise capacity [191]. How sodium effects exerciseinduced cardiac fatigue is not known and should be the focus of future investigations exploring exercise-induced cardiac fatigue. 3.7 CONCLUSIONS The results of this investigation demonstrate that in response to an acute bout of prolonged strenuous exercise, adjustments in cardiac function are similar in men and women. Our results support the idea that cardiac fatigue occurs after prolonged strenuous exercise and advances our knowledge by showing that increased experience in ultraendurance events may induce a cardioprotective effect. However, further research is required to assess the impact of duration and intensity of exercise on exercise-induced cardiac fatigue in both men and women.  38  Chapter 4: Effects of Sex and Training Status on the Cardiovascular Responses to an Acute Bout of High Intensity Interval Exercise  4.1 INTRODUCTION The nature of exercise-induced cardiac fatigue following high-intensity interval exercise has yet to be determined. The transient impairments in ventricular function that are characteristic of exercise-induced cardiac fatigue [19] have been shown to result from various forms of prolonged exercise [139, 154, 159, 182, 192-198], the magnitude of which has been suggested to be duration dependant [161]. Recently, Scott and colleagues [21] reported reduced ventricular function following an acute bout of high intensity interval exercise in endurance-trained males, a phenomenon not shown in normally active men, supporting the role of exercise intensity in the development of exercise-induced cardiac fatigue. High-intensity interval exercise has been shown to be an effective alternate to traditional endurance training, enhancing physiological, health and performance-related components [199]. Chronic adaptations to high-intensity interval training include increased aerobic and anaerobic fitness [7, 8], increased skeletal muscle capacity for fatty acid oxidation and glycolytic enzyme content [9, 15, 16], and increased insulin sensitivity [6, 12, 14]. Despite these numerous benefits, the safety of this strenuous form of exercise has yet to be determined [17]. Compared with inactive periods, there is an transient increased risk of sudden cardiac death during and immediately after vigorous exertion in apparently healthy individuals [22] and athletes [200]. Supramaximal exercise shifts sympathovagal balance more toward sympathetic dominance as compared to less intense 39  forms of exercise [201]. Furthermore, myocardial damage and cardiac fibrosis have been identified in marathon runners [202, 203] which may be a substrate for an increased susceptibility to arrhythmias in response to increased exercise-related catecholamine levels [162]. However, it should be highlighted that the risk of sudden cardiac death following high intensity exercise is markedly lower in individuals that engage in routine physical activity and exercise [24]. Catecholamines are elevated significantly in trained versus untrained males following intense exercise [204-207]. This is thought to be due to a greater oxygen demand and substrate degradation, stimulating higher sympathoadrenal activation in trained individuals [207]. Thus, differences in sympathetic activity between endurance-trained and normally active men following high-intensity exercise may be responsible for the presence of exercise-induced cardiac fatigue shown in those endurance-trained only [21]. However, there has been no evidence of a training effect on catecholamine response in women [208-211]. As such, it is unclear how high-intensity interval exercise would impact left ventricular function in females, endurance-trained and untrained. Accordingly, the purpose of this investigation was to evaluate the effects of high-intensity interval exercise on cardiac mechanics and plasma catecholamines in endurance-trained and normally active males and females. We hypothesized that endurance-trained males would be most susceptible to an acute bout of high-intensity interval exercise as evidence by greater alterations in left ventricular strain and twist mechanics, and higher catecholamine levels.  40  4.2 METHODS 4.2.1 Participants and Ethical Approval We recruited 39 healthy, non-smoking men and women between the ages of 20 – 45 y (21 males, 18 females). ‘Normally active’ participants were considered active at anticipated population-based levels, but were not engaged in any formal endurance training program. Endurance-trained athletes required a VO2max >55mL.kg.min-1 and participated in endurance training ≥ 10 hours/week for a minimum of two years. Maximal aerobic capacity was evaluated in our laboratory and training volume was determined through a questionnaire. Individuals were also pre-screened via the PAR-Q+ (Appendix A). Approval for this research was obtained via the Clinical Research Ethics Board at the University of British Columbia and conformed to the standards set by the latest revision of the Declaration of Helsinki. 4.2.2 Experimental Protocol Participants visited the laboratory on two separate occasions. The first testing day involved the acquisition of baseline vascular measures (height, body mass, arterial compliance, and pulse wave velocity) and the determination of maximal aerobic power (VO2max). The second testing day consisted of the exercise protocol. Cardiac function was assessed prior to and immediately following a high-intensity interval session. A minimum of 1 week separated the two test sessions. All participants were instructed to abstain from caffeine, exercise, and alcohol for 24 hours prior to testing.  41  4.2.3 Procedures and Analysis Anthropometrics, Pulse Wave Velocity, and Arterial Compliance. Height and body mass were measured to the nearest 0.1 cm and 0.1 kg, respectively. Body surface area was calculated as BSA (m2) = SQR RT ([Height(cm) x Weight(kg)]/ 3600 ) [170]. Baseline vascular measures were assessed following 10 minutes of supine rest. Participants were instrumented with an ECG and finger plethysmography secured to the middle finger, using a beat-by-beat blood pressure device (Finapres; Ohmeda Inc, Englewood, CO). Automated blood pressure measurements were obtained by brachial occlusion (BpTRU 100, Coquitlam, Canada) for calibration and collected in duplicate. In addition, pulse wave contours were collected at the carotid and femoral arteries using infrared photoelectric sensors (ADInstruments, Colorado Springs, CO). Continuous recordings were sent to a data acquisition system (PowerLab/16SP ML 795, ADInstruments, Colorado Springs, CO) and displayed using Chart (version 7.0, ADInstruments, Colorado Springs, CO). Pulse wave velocity was determined via postcollection analysis as previously described [212]. Briefly, a minimum of 30 consecutive cardiac cycles were averaged to calculate the foot-to-foot pulse transit time between the carotid artery and femoral artery. The shortest distances between the sites of pulse contour collection were measured to the nearest 0.5 cm using a standard measuring tape and this distance was divided by the corresponding pulse transit time in order to calculate pulse wave velocity. Arterial compliance was measured non-invasively via applanation tonometry with the HDI CR-2000 (Hypertension Diagnostics, Eagan, Minnesota) for diastolic pulse contour analysis. This method of vascular assessment using waveform shape analysis is 42  considered optimal for measuring systemic compliance [213] and is based on a modified Windkessel model which allows for estimation of large (capacitive) artery and small (oscillatory) artery compliance. After stabilizing the wrist and maximizing signal strength, radial artery tonometry measurements were collected using the right wrist with the automated sphygmomanometer affixed to the upper left arm. Measurements were taken in duplicate with the average used for analysis. VO2max. An incremental bike test to exhaustion (Velotron Dynafit Pro, RacerMate Inc, Seattle, USA) was used for the assessment of VO2max. The protocol began at a workload of 80-100 watts and increased 25 watts every 2 minutes until volitional fatigue. Participants donned a face mask (Oro-nasal 7400 Vmask with Headgear, Hans Rudolph, Kansas, USA) for the collection of expired gases analyzed by metabolic cart (Medisoft Ergocard, Sorinnes, Belgium). In addition, heart rate and arterial haemoglobin saturation were measured continuously using a pulse oximeter (Masimo Radical, Irvine, CA, USA) attached to the participant’s right index finger. Echocardiography. Echocardiographic assessments were performed by a trained clinical sonographer using a portable ultrasound unit (Vivid i, GE Medical Systems, Israel) with simultaneous ECG and a 2.5-MHz transducer. Participants were positioned in the left lateral decubitus position for imaging. Apical two- and four-chamber views were acquired for the assessment of left ventricular (LV) volumes, LV longitudinal strain and strain rate, in addition to transmitral pulsed Doppler flow velocities and tissue Doppler mitral annular velocities. Optimal parasternal short axis views obtained at the base (mitral valve) and apex (before apical obliteration) were acquired for the assessment of left ventricular rotation, rotation rate, twist, circumferential and radial strain, and strain 43  rate. All strain imaging was acquired at high frame rates (80-90 frames per second). Ventricular volumes and diameters were analyzed offline (EchoPAC, GE Healthcare, v. 110.1.1) in accordance with the recommendations of the American Society of Echocardiography [175]. Left ventricular mass was determined using the formula: LV Mass (g) = 0.8 (1.04 ([LVIDD + PWTD + IVSTD]3- [LVIDD]3))+ 0.6 [177]. Enddiastolic volume (EDV) and end-systolic volume (ESV) using Simpson’s bi-plane method for which 3 consecutive beats were measured and analyzed. Stroke volume (SV) was calculated by EDV-ESV. Cardiac output (CO) was calculated as SV x HR. Ejection fraction (EF) was calculated as a percentage of EDV. Fractional shortening (FS) was calculated from ventricular diameters using the parasternal long axis window and expressed as a percent. Total peripheral resistance (TPR) was derived from dividing CO into MAP. LV wall stress was determined non-invasively as calculated as 0.133 x P x R/2T x (1 + T/2R), where P is systolic blood pressure, R is left ventricular end-systolic diameter, and T is left ventricular systolic posterior wall thickness [178]. Speckle tracking echocardiography was used to assess all of the LV strain, rotation and twist parameters using EchoPAC. Twist and twist velocity were obtained by subtracting apical from basal rotation and rotation rates [214]. Arterial elastance was calculated as EA = ESP/SV where ESP = 0.9 x SBP. Ventricular elastance was calculated via the formula ELV = ESP/ESV. Arterial-ventricular coupling was then determined as the ratio of arterial and ventricular elastance (EA/ELV). High Intensity Interval Exercise. An incremental bike test to exhaustion (Velotron Dynafit Pro, RacerMate Inc, Seattle, USA) was used for the assessment of VO2max. The protocol began at a workload of 80-100 watts and increased 25 watts every 2 minutes 44  until volitional fatigue. Participants donned a face mask (Oro-nasal 7400 Vmask with Headgear, Hans Rudolph, Kansas, USA) for the collection of expired gases analyzed by metabolic cart (Medisoft Ergocard, Sorinnes, Belgium). In addition, heart rate and arterial haemoglobin saturation were measured continuously using a pulse oximeter (Masimo Radical, Irvine, CA, USA) attached to the participant’s right index finger. Hydration Assessment. A urine sample was collected prior to the interval session. A drop of urine was analyzed for urine specific gravity (Atago Pocket Refractometer, PAL10S, Japan), which has been shown to be a valid means of assessing hydration status [215]. A result <1.02 served as the threshold of hydration status acceptable to commence testing [216, 217]. Once adequate hydration was verified, a measure of body mass was recorded to the nearest 0.1 kg using a digital scale (Seca, Birmingham, UK) and measured again post-exercise. Blood Sampling. Pre- and post-exercise blood samples (6 mL each) were drawn from a medial cubital vein using a needle (23-gauge butterfly) and Vacutainer system to EDTA tube. The blood was centrifuged and to remove plasma. Serum samples were stored at 80°C until analysis. Epinephrine and norepinephrine concentrations were derived from immunoassay (TriCat Elisa RE59395, IBL Diagnostics, Hamburg, Germany). 4.3 STATISTICAL ANALYSIS Data are presented as mean ± standard deviation. Baseline characteristics between sex and training status were assessed using a 2-way ANOVA. The effect of exercise on dependent variables were analyzed using a mixed-model ANOVA with between (sex; training status) and repeated (condition) factors. Pearson’s correlation analysis was used 45  to find associations between significant factors. Significance for all tests was set a priori at p<0.05. All analyses were performed using SPSS software (version 20.0; SPSS IBM, Chicago, IL). Results are reported as mean ± SD. 4.4 RESULTS 4.4.1 Participant Characteristics The endurance-trained (ET) group represented 20 category 1 and 2 competitive cyclists (9 F) who reported an average training frequency and volume of 5.2 ± 1.0 days and 231.0 ± 129.3 km of training per week. The normally active (NA) group consisted of 19 individuals (9 F) who reported moderate levels of physical activity (i.e., yoga, resistance training, recreational level soccer) 3.9 ± 1.5 d/wk. Participant characteristics including vascular assessments are presented in Table 4.1. Sex differences (p<0.05) were found for height, body mass, arterial compliance, left ventricular mass (LVM), stroke volume, and cardiac output (indexed for body size). Endurance-trained differed from NA participants for VO2max, heart rate, large artery compliance, left ventricular mass, stroke volume, and cardiac output (p<0.05). 4.4.2 Hydration, Catecholamines and Haemodynamic Parameters Prior to the interval session, urine specific gravity was within the range considered to represent adequate hydration [215] averaging 1.012 ± 0.01. Body mass decreased 0.27 ± 0.47 kg following exercise and this response was unaffected by sex or training status. Epinephrine baseline values were not different by group (0.74 ± 0.18 nmol.l-1); but increased to a greater extent in ET than NA (3.38 ± 0.57 nmol.l-1 and 2.87 ± 0.54, respectively; p=0.016). Norepinephrine increased from 2.56 ± 0.50 to 22.90 ± 4.43 46  nmol.l-1 (p<0.001) and was not different between groups. Heart rate was significantly increased post-exercise (57.0 ± 9.0 to 76.7 ± 10.5 bpm; p<0.001) as was cardiac index (CI; 2.65 ± 0.75 to 2.91 ± 0.66 L.min-1/m2; p=0.031). The ET displayed greater reductions in absolute stroke volume (-17.9 ± 15.2%) compared to NA (-14.6 ± 19.4%; p=0.031) as well as stroke volume indexed to body size (SVI; ET, -16.6 ± 12.9; NA, -15.3 ± 19.9, p=0.024). There was also an effect of sex for SVI as men experienced greater reductions post-exercise than women (Men: 51.3±12.9 to 39.7±9.0 mL/m2; Women: 41.8±9.2 to 36.6±7.1 mL/m2, p=0.028). 4.4.3 Cardiac Function and Arterial-Ventricular Coupling Indices of systolic and diastolic function were reduced post-exercise (Table 4.2). An interaction was only present for early diastolic filling (E), whereby NA began with higher baseline E but post-exercise, displayed lower early diastolic filling than ET. Longitudinal, circumferential, and radial strain and strain rate, in addition to rotation and twist parameters (Table 4.3) were similar regardless of sex or training status, except for longitudinal diastolic strain rate. Diastolic longitudinal strain rate was reduced to a greater extent post-exercise in men compared with women (p=0.011; Figure 4.1). Time to peak twist and time to peak untwisting rate were delayed post-exercise (p<0.001 and p=0.002, respectively; Figure 4.2). A significant association was found for baseline pulse wave velocity and alterations in cardiac twist with exercise (Figure 4.3). Individuals with higher pulse wave velocity (greater arterial stiffness) were less likely to increase twist following exercise. No correlations were found for changes in heart rate, strain rate,  47  diastolic filling, pressures, or volumes. In addition, changes in catecholamines were not associated with the any cardiac parameters. Ventricular-vascular coupling results showed endurance-trained individuals displayed lower EA and ELV than NA, and women had higher ELV than men (Figure 4.4). An interaction was revealed between sex and time for EA (p=0.034) where arterial elastance increased in men post-exercise and plateaued in women. A strong correlation was observed for the change in arterial elastance and the change in stroke volume index (r=0.875, p<0.001) indicating the greater the decrease in stroke volume, the greater the increase in arterial elastance.  48  Table 4.1 Participant Characteristics and Baseline Cardiovascular Measures Males  Age, y Height, cm Body Mass, kg VO2max, ml.kg.min-1 SBP, mmHg DBP, mmHg HR, bpm PWV, cm/s LAC, ml.mmHg.10 SAC, ml.mmHg.10 LVM/BSA,g/m2 SVI, mL/m2 CI, L.min-1/m2  Females  p value  NA n=10  ET n=11  NA n=9  ET n=9  sex  group  28.50 ± 5.90 179.80 ± 6.50 77.00 ± 7.40 46.90 ± 5.30 112.60 ± 6.60 66.20 ± 5.60 56.50 ± 4.70 557.50 ± 49.50 18.50 ± 3.10 9.90 ± 2.30 101.20 ± 15.20 43.40 ± 12.10 2.60 ± 0.83  33.00 ± 5.60 178.50 ± 8.00 74.50 ± 8.50 59.60 ± 4.10 109.20 ± 10.40 66.70 ± 7.40 50.90 ± 6.50 567.00 ± 156.10 23.60 ± 7.10 12.20 ± 5.00 122.10 ± 20.90 58.50 ± 9.00 3.20 ± 0.57  29.40 ± 4.60 164.10 ± 8.60 62.30 ± 13.30 44.80 ± 4.50 106.00 ± 4.50 64.70 ± 4.60 58.00 ± 7.90 629.30 ± 145.30 17.90 ± 3.60 8.90 ± 3.10 78.40 ± 11.10 37.30 ± 8.60 2.10 ± 0.53  29.10 ± 4.30 167.90 ± 4.20 59.30 ± 5.70 56.40 ± 3.90 108.90 ± 4.30 66.40 ± 6.20 53.30 ± 7.40 557.60 ± 136.10 20.00 ± 4.20 8.40 ± 2.00 105.80 ± 11.80 46.30 ± 7.90 2.60 ± 0.71  0.468 0.001 0.001 0.081 0.136 0.648 0.383 0.584 0.028 0.036 0.001 0.006 0.019  0.170 0.569 0.355 0.001 0.907 0.562 0.023 0.430 0.028 0.400 0.001 0.001 0.019  Abbreviations: NA=normally active; ET=endurance-trained; SBP=systolic blood pressure; DBP=diastolic blood pressure; HR=heart rate; PWV=pulse wave velocity; LAC=large artery compliance; SAC=small artery compliance; LVM=left ventricular mass; BSA=body surface area; SVI=stroke volume index; CI=cardiac index The effects of sex and training status on participant characteristics were analyzed by unadjusted general linear models. BOLD p values denotes statistically significant  49  Table 4.2 Effects of Exercise on Systolic and Diastolic Function Males  Females  NA  ET  NA  ET  Systolic  Baseline  Post-Exercise  Baseline  Post-Exercise  Baseline  Post-Exercise  Baseline  Post-Exercise  EF, %  59.0 ± 7.6  55.0 ± 4.5  65.4 ± 9.7  61.6 ± 7.7  62.6 ± 9.2  63.3 ± 4.1  61.2 ± 7.7  60.3 ± 6.4  FS, % *  39.1 ± 6.3  36.3 ± 7.2  37.3 ± 8.2  33.7 ± 8.9  34.8 ± 5.7  36.4 ± 5.0  36.5 ± 4.8  30.9 ± 6.2  Wall Stress *  136.2 ± 19.9  117.9 ± 28.9  136.5 ± 55.2  116.9 ± 47.1  76.3 ± 23.0  60.3 ± 15.8  99.6 ± 24.9  99.3 ± 32.7  SBP/ESV  2.08 ± 0.64  2.14 ± 0.56  2.08 ± 0.81  1.98 ± 0.73  2.91 ± 1.08  3.28 ± 0.99  2.31 ± 0.88  2.31 ± 0.65  EF/EDV *  0.43 ± 0.10  0.48 ± 0.10  0.45 ± 0.12  0.49 ± 0.17  0.65 ± 0.20  0.78 ± 0.20  0.51 ± 0.15  0.54 ± 0.10  E' septal, m/s*  0.14 ± 0.02  0.11 ± 0.02  0.12 ± 0.02  0.11 ± 0.02  0.13 ± 0.02  0.12 ± 0.02  0.13 ± 0.02  0.13 ± 0.01  E' lateral, m/s*  0.19 ± 0.02  0.16 ± 0.04  0.17 ± 0.03  0.15 ± 0.03  0.18 ± 0.03  0.18 ± 0.02  0.17 ± 0.02  0.15 ± 0.02  E' RV, m/s  0.17 ± 0.02  0.15 ± 0.03  0.15 ± 0.02  0.14 ± 0.02  0.15 ± 0.02  0.14 ± 0.02  0.15 ± 0.02  0.15 ± 0.06  E, m/s ¥  0.83 ± 0.13  0.70 ± 0.09  0.81 ± 0.12  0.72 ± 0.12  0.87 ± 0.16  0.75 ± 0.14  0.82 ± 0.14  0.77 ± 0.11  DecT, ms  Diastolic 242.2 ± 57.3  227.7 ± 22.7  219.4 ± 58.9  220.1 ± 46.4  210.9 ± 23.1  200.9 ± 33.5  208.7 ± 47.2  205.5 ± 27.3  IVRT, ms *  76.7 ± 7.9  67.8 ± 10.6  77.9 ± 10.6  63.5 ± 8.0  67.8 ± 9.8  59.6 ± 10.4  73.9 ± 11.0  65.1 ± 8.8  E/E' septal  6.05 ± 1.20  6.42 ± 1.08  6.85 ± 1.34  6.91 ± 1.71  6.80 ± 1.42  6.27 ± 0.86  6.24 ± 1.39  6.14 ± 0.90  E/E' lateral  4.44 ± 0.80  4.47 ± 1.09  4.80 ± 0.97  4.81 ± 1.08  4.89 ± 1.10  4.32 ± 0.85  4.82 ± 0.83  5.12 ± 0.95  Abbreviations: EF=ejection fraction; FS=fractional shortening; SBP=systolic blood pressure; ESV=end-systolic volume; EDV=end diastolic volume; E=early diastolic filling; DecT=deceleration time; IVRT=isovolumetric relaxation time; E'=mitral annular tissue velocity; RV=right ventricle Effect of exercise obtained using general linear models adjusted for sex and training status. * p<0.05 from baseline; ¥ training status by time interaction  * 50 ǂ  Table 4.3 Peak Left Ventricular Mechanics and Rest and During Exercise Males  Females  NA Rest  Post-Exercise  ET Rest  NA  Post-Exercise  Rest  Post-Exercise  ET Rest  Post-Exercise  Peak (systole) Basal Rotation (°) Apical Rotation (°)  -11.71 ± 21.27  -5.85 ± 2.20  -5.76 ± 1.68  -6.12 ± 2.71  -6.75 ± 3.21  -7.11 ± 2.71  12.94 ± 5.16  15.01 ± 2.79  12.20 ± 3.93  11.69 ± 4.55  11.80 ± 5.91  12.63 ± 5.64  11.45 ± 4.86  12.21 ± 5.32  17.79 ± 6.15  19.82 ± 3.26  17.36 ± 4.94  16.65 ± 7.13  17.77 ± 8.06  18.74 ± 6.85  15.88 ± 6.27  16.94 ± 6.29  94.30 ± 9.39  109.83 ± 11.23  89.30 ± 5.72  97.01 ± 9.95  94.27 ± 14.24  105.71 ± 13.79  98.14 ± 26.26  103.28 ± 13.02  -18.95 ± 2.90  -16.79 ± 2.41  -18.51 ± 2.06  -16.47 ± 1.79  -20.13 ± 2.84  -18.80 ± 1.61  -18.85 ± 2.14  -17.77 ± 2.15  40.95 ± 10.33  28.74 ± 12.60  56.82 ± 13.71  43.10 ± 19.25  45.70 ± 35.32  38.66 ± 11.47  31.97 ± 20.13  29.99 ± 11.08  10.37 ± 8.96  13.69 ± 9.98  10.96 ± 11.90  15.20 ± 9.52  17.91 ±18.40  16.95 ± 17.99  11.41 ± 8.26  13.01 ± 8.98  Basal Level  -16.33 ± 5.29  -13.63 ± 3.21  -16.60 ± 4.25  -16.06 ± 4.40  -13.72 ± 3.55  -14.03 ± 3.02  -13.29 ± 2.86  -14.33 ± 1.40  Apical Level  -26.39 ± 10.23  -23.05 ± 10.39  -25.92 ± 10.72  -26.59 ± 6.83  -26.94 ± 6.37  -25.64 ± 7.02  -28.82 ± 3.62  -26.58 ± 6.32  -68.54 ± 11.81  -65.83 ± 27.68  -53.43 ± 21.72  -62.75 ± 21.67  -64.34 ± 19.63  -71.60 ± 22.12  -54.80 ± 16.89  -63.14 ± 12.76  72.06 ± 17.85  94.52 ± 27.33  54.79 ± 16.43  68.02 ± 19.68  63.90 ± 23.34  75.10 ± 18.45  74.51 ± 32.95  78.18 ± 43.25  111.13 ± 31.88  121.77 ± 26.42  101.63 ± 21.39  101.23 ± 45.50  119.81 ± 36.78  128.70 ± 32.98  96.89 ± 26.30  102.90 ± 36.07  -1.01 ± 0.17  -0.96 ± 0.16  -0.89 ± 0.11  -0.89 ± 0.10  -1.08 ± 0.18  -1.05 ± 0.12  -0.92 ± 0.08  -0.91 ± 0.09  1.90 ± 0.84  1.93 ± 1.25  1.53 ± 0.20  1.58 ± 0.26  1.66 ± 0.63  1.49 ± 0.30  1.70 ± 0.82  1.54 ± 0.27  1.03 ± 0.46  1.40 ± 0.65  1.10 ± 0.57  1.30 ± 0.46  1.07 ± 0.52  1.36 ± 0.60  0.82 ± 0.23  1.01 ± 0.45  -1.04 ± 0.31  -1.01 ± 0.23  -0.98 ± 0.17  -1.00 ± 0.23  -0.86 ± 0.17  -0.98 ± 0.19  -0.81 ± 0.18  -0.97 ± 0.11  -2.02 ± 0.51  -1.77 ± 0.57  -1.78 ± 0.54  -1.82 ± 0.68  -1.67 ± 0.53  -1.90 ± 0.68  -1.72 ± 0.34  -1.71 ± 0.60  Twist (°) Time to Peak Twist (% sys) * Longitudinal Strain (%) * Radial Strain (%) Basal Level Apical Level  5.21 ± 2.69  -6.11 ± 2.09  Circumferential Strain (%)  . -1  Basal Rot. Velocity (° s ) Apical Rot. Velocity (°. s-1)* Twist Velocity (°. s-1) Strain Rate (s-1) Longitudinal Radial Basal Radial Apical* Circumferential Basal Circumferential Apical  51  MALES  FEMALES  NA Rest  Peak (diastole) Basal Rot. Velocity (°. s-1) Apical Rot. Velocity (°. s-1)* . -1  Untwisting Velocity (° s ) Strain Rate (s-1) Longitudinal ǂ Radial Basal Radial Apical Circumferential Basal * Circumferential Apical  ET  Post-Exercise  Rest  NA  Post-Exercise  Rest  Post-Exercise  ET Rest  Post-Exercise  65.02 ± 22.61  66.18 ± 12.60  56.82 ± 17.57  72.74 ± 21.89  71.41 ± 19.48  76.14 ± 17.32  67.04 ± 30.63  75.13 ± 18.69  -85.57 ± 30.71  -108.57± 30.40  -70.56 ± 25.23  -89.39 ± 23.81  -79.92 ± 47.44  -106.38± 49.76  -75.03 ± 20.46  -84.71 ± 40.54  -139.86± 44.45  -128.05± 23.09  -108.71± 32.99  -120.22± 41.61  -112.19± 44.75  -135.61± 57.85  -123.98± 41.94  -130.12± 62.00  1.58 ± 0.14  1.32 ± 0.29  1.36 ± 0.17  1.24 ± 0.17  1.69 ± 0.28  1.67 ± 0.28  1.56 ± 0.21  1.59 ± 0.25  -1.58 ± 0.39  -1.66 ± 0.51  -1.48 ± 0.44  -1.65 ± 0.41  -1.55 ± 0.57  -1.59 ± 0.64  -1.50 ± 0.35  -1.62 ± 0.66  -1.36 ± 0.70  -1.96 ± 1.34  -1.24 ± 0.53  -1.73 ± 1.09  -1.83 ± 1.12  -1.77 ± 0.70  -1.75 ± 1.09  -1.64 ± 0.81  1.16 ± 0.53  1.08 ± 0.35  1.11 ± 0.29  1.42 ± 0.35  1.11 ± 0.39  1.38 ± 0.35  1.05 ± 0.26  1.24 ± 0.19  2.72 ± 0.96  2.32 ± 1.40  2.94 ± 1.08  3.15 ± 1.3  2.80 ± 0.77  3.27 ± 1.27  3.11 ± 0.84  3.15 ± 0.85  Effect of exercise obtained using general linear models adjusted for sex and training status. * p<0.05 from baseline; ǂ p<0.05 sex by time interaction  52  2.3  2.1  Diastolic Longitdinal Strain Rate (s-1)  1.9  1.7  NA men NA women  1.5  ET men ET women 1.3  1.1  0.9  0.7  Baseline  Post-exercise  Figure 4.1 Effect of Exercise on Diastolic Longitudinal Strain Rate. Diastolic longitudinal strain rate was reduced post-exercise in men, but not women (p=0.011) regardless of training status.  53  Women Pre-Ex Women Post-Ex Men Pre-Ex Men Post-Ex  20  A 15  Twist (degrees)  10  5  0 0  20  40  60  80  100  120  140  160  180  -5  120  B  100 80  Twist Rate (deg..s-1)  60 40 20 0 -20 0  20  40  60  80  100  120  -40 -60 -80 -100 -120  Systole (%)  Figure 4.2 Time Course of Left Ventricular Twist and Twist Rates. Time to peak twist (A) was delayed post-exercise (p<0.001) and was not different based on sex or training status. Time to peak twist rate (B) was not significantly different from baseline, however, time to peak untwist rate (B) was significantly delayed (p=0.002) but not this response was not different among groups. 54  900 800  Pulse Wave Velocity (cm/s)  700 600 500 400 300 200 100 0 -15  -10  -5  0  5  10  15  20  25  Change in Twist (%)  Figure 4.3 Relationship of Baseline Pulse Wave Velocity to Exercise-Induced Change in Left Ventricular Twist Individuals with higher pulse wave velocity (greater arterial stiffness) were less likely to increase twist following exercise. Pearson r=-0.51, p=0.001  55  ǂ 6  EaI (mmHg/ml/m2)  5 4  Ψ  3 2 1 0  *  8  *  ELVI (mmHg/ml/m2)  7 6  Ψ  5 4 3 2 2  NA m  1.8  ET m  1.6  NA f  *  EaI/ELVI  1.4  ET f  1.2 1 0.8 0.6 0.4 0.2 0 Pre  Post  Post30  Figure 4.4 Arterial Ventricular Coupling Indexed to Body Surface Area Abbreviations: Pre = baseline; Post=immediately post-exercise; Post30=30 min post-exercise ǂ p<0.05 condition by sex; * p<0.05 from baseline; p<0.05 Ψ between group 56  4.4 DISCUSSION  *  The aim of this investigation was to evaluate the effects of sex and training status on cardiovascular function following high-intensity interval exercise. Our results show that exercise-induced cardiac fatigue is not limited to prolonged exercise, as both systolic and diastolic function were depressed following acute high-intensity interval exercise. Cardiac mechanics were similar between all four groups with the exception of altered diastolic longitudinal strain rate and ventricular-vascular coupling in males compared with females. Aside from significantly different haemodynamics, only early diastolic filling, differentiated training status. Alterations in systolic and diastolic parameters illustrate the impact of high-intensity interval exercise on the heart. Prior work assessing very short duration, supra-maximal efforts such as the Wingate [218], and strenuous exercise of six to eight minutes failed to show any LV functional decline [194, 219]. It is plausible that some intensity-duration threshold is required to alter cardiac dynamics to which previous work did not meet. Similar to other forms of strenuous exercise [123], we found reduced function in traditional systolic indices such as fractional shortening and wall stress, in addition to novel strain and twist mechanics. Specifically, we showed reductions in peak longitudinal strain and peak systolic tissue velocities, which are indicative of altered myocardial contractility [220, 221]. Furthermore, the delayed twist mechanics occurring during a shortened isolvolumetric relaxation phase, likely impacted diastolic suction [181] as evidenced by reduced early diastolic filling. These reductions in strain, tissue velocities and delayed twist may reflect altered intrinsic myocardial relaxation properties as a result of fatigue-induced impaired metabolism within cardiomyocytes [181, 182]. Thus, our data clearly shows that high-intensity interval exercise is a 57  sufficient stimulus to cause impairment of both relaxation and contraction of the left ventricle, as shown in clinical diastolic dysfunction [50]. We found a novel association of baseline arterial stiffness and change in twist mechanics with high-intensity exercise. Pulse wave velocity is established as the gold standard for estimating vascular stiffness [213]. An elastic vascular system reduces cardiac demand [222]. As such, this relationship infers that those individuals with lower arterial stiffness were better able to augment cardiac twist in the face of increased demands. An inability to increase twist during exercise has been shown in several clinical populations to also be related to increased arterial stiffness [223]. Our study, using a diverse yet healthy population, is the first to show this relationship directly, and supports the emerging literature showing that ventricular-vascular interactions are a crucial mediator of cardiac function [224]. Arterial-ventricular coupling is a common technique for relating the LV and arterial system, and is expressed as a ratio of arterial and ventricular elastance (EA/ELV). At rest, normal values representing optimal function range from 0.7 to 1.0 [225]. Following exercise, EA/ELV increased similarly in all groups, resulting from a reduction in ventricular elastance in combination with a rise in arterial elastance, while remaining in the optimal range. Furthermore, an interaction of sex and arterial elastance was found. In recovery from exercise, the men in our study demonstrated an increase in EA that was not observed in the women. The arterial component of this coupling is said to parallel increases in arterial stiffness [226, 227] and is derived by the ratio of end-systolic pressure to stroke volume. As end-systolic pressure did not differ between men and women, the change in stroke volume was the mediator of this effect. A greater sympathetic vasoconstrictor outflow opposing peripheral vasodilatation in men may be responsible as cardiac output was maintained in both groups despite significantly larger decrements in stroke volume in the men 58  [228]. Sympathetically mediated increases in arterial elastance could raise myocardial oxygen consumption for a given stroke volume [229]. With respect to the ventricular component, women across all ages have been shown to have a higher ELV than age-matched males [230] suggesting this higher LV contractility may allow women to tolerate cardiovascular stress better than men [82]. Our women not only displayed higher ELV, they also showed less alteration in this component over the intervention. Given the women also presented a higher EF for a given EDV, together these findings are indicative of enhanced systolic function. This investigation is the first to assess sex differences in cardiac mechanics with highintensity interval exercise. Only longitudinal diastolic strain rate differed between men and women, with reductions post-exercise experienced by the males whereas females did not change from baseline. Ventricular dysfunction has been suggested to begin in the longitudinal plane while circumferential and radial compensations remain to preserve ejection fraction in individuals with cardiovascular risk factors [231]. Thus, while this parameter provides an indication that males could exhibit cardiac mechanical limitations compared with women in response to strenuous exercise, further evidence is required in order to ascertain its validity. With respect to training status, we found endurance-trained participants displayed greater alterations in haemodynamics than untrained, typical of chronic endurance training. Early diastolic filling was reduced to a lesser degree in endurance-trained individuals following exercise, likely a reflection of superior diastolic suction to that of their normally active counterparts [30]. The greater elevations in epinephrine following exercise in endurance-trained participants support previous work reporting higher catecholamine concentrations in trained individuals following high-intensity exercise [145]. However, these changes were not associated 59  with any cardiac function measures. By contrast to the findings of Scott et al. [21] we did not find ventricular responses between the groups to differ between training groups, with the aforementioned greater reduction in early diastolic filling. Both investigations employed a similar protocol and population, thus the nature of the discrepant findings are unclear. Certain parameters of cardiac mechanics may be quite variable between individuals and this may be a factor worth consideration. 4.5 LIMITATIONS In this study our objective was to assess cardiac function as close to the cessation of exercise, as possible. We did not attempt to image the heart during exercise as obtaining quality images at such high work rates are exceptionally difficult. While we accomplished our objective in this regard we did not include a follow-up assessment (with the exception of ventricular-vascular coupling) by which the persistence of altered ventricular function could be determined. Recently, Goodman et al. [232] demonstrated a preserved left ventricular function during prolonged strenuous exercise that became significantly reduced in the recovery period. Thus, it is possible that further ventricular alterations may have occurred given a longer recovery time. The work of Scott et al. [21] included two post-exercise cardiac assessments and found ventricular dysfunction to persist for certain measures at the second assessment (approximately 38 minutes post-exercise) however, the authors did not detect any further depressions. Thus, we do not expect further evidence of cardiac fatigue would have been realized with follow-up assessments in our study.  60  4.6 CONCLUSIONS Our results show that high-intensity interval exercise can provoke cardiac fatigue in healthy individuals. Our findings showing an association of arterial stiffness and twist mechanics, and the sex differences in arterial-ventricular coupling are novel and deserve further study to ascertain their role in the development of cardiovascular disease risk, exercise tolerance, and performance. In addition, future research pertaining to cardiac function and strenuous exercise should involve sex comparisons to delineate the findings thus far.  61  Chapter 5: Cardiac and Autonomic Function in Recovery from High-Intensity Interval Exercise  5.1 INTRODUCTION The use of non-invasive autonomic indices such as heart rate variability and baroreflex sensitivity have been shown to be strong prognostic indicators for the development of cardiovascular disease [233-235] and risk of ventricular fibrillation and cardiac events [38, 236]. Endurance training and female sex have both been shown to affect positively resting cardiac autonomic modulation as evidenced by greater cardiac parasympathetic activity at rest, a trait associated with a reduced risk of sudden cardiac death [62-66, 237, 238]. These factors positively influence blood pressure in females, mediated by changes in baroreflex sensitivity [239]. Acute exercise results in transient reductions in autonomic function, to which exercise intensity exacerbates the response [240]. Reductions in cardiac vagal tone with strenuous exercise have been proposed to be associated with the pathogenesis of ventricular arrhythmias and sudden cardiac death [22, 241]. However, the improved autonomic profile in females does not appear to mitigate the acute exercise response. Athletes have demonstrated higher sympathoadrenal activation with intense exercise when compared with untrained individuals [242] and it has also been shown recently that following a single bout of supramaximal exercise, women experienced greater shifts to sympathetic dominance than men despite a more favourable initial resting profile [66]. Exercise presents a significant orthostatic stressor due to venous pooling in the legs [243] and persistent vasodilatation related to altered sympathetic outflow and transduction of sympathetic activity to vascular resistance [244]. Thus, it is plausible that following strenuous exercise, an increased cardiac sympathetic drive is required to maintain 62  blood pressure in these individuals. Notably, females and endurance trained individuals have demonstrated reduced tolerance to an orthostatic challenge [171, 245-247]. Lower body negative pressure (LBNP) is a gravitational stress that alters loading conditions to the heart [248] and provides a unique stimulus whereby sympathetic vasomotor tone is drastically increased [249]. Cardiac baroreflex sensitivity is reduced as lower body negative pressure unloads the baroreceptors [250, 251]. Additionally, baroreflex sensitivity is markedly reduced during dynamic exercise due to resetting of the baroreceptors allowing the baroreflex function to move to a new operational point [252, 253]. Thus, when combining exercise with a gravitational challenge the onset of orthostatic intolerance can be expedited [254] and as such, greater autonomic compensation maybe required [255]. Endurance trained individuals demonstrate accelerated heart rate recovery post-exercise than untrained [256-259] indicating a more rapid reversal of sympathetic activation. To investigate this, we sought to evaluate the effects of training and sex on the autonomic responses to combined strenuous exercise and LBNP. We hypothesized that as a result of high intensity interval exercise: 1) greater reductions in autonomic function would occur in endurance-trained individuals following exercise, yet they would display superior recovery during post-exercise lower body negative pressure, and 2) women would display greater baseline autonomic function, greater post-exercise reductions, and a more rapid recovery to baseline than men. 5.2 METHODS 5.2.1 Participants and Ethical Approval We recruited thirty-three (13 F) healthy individuals, normally active or endurance-trained, between the ages of 20 and 45 y. Normally active participants were considered physically active 63  but were not engaged in any formal endurance training program. Endurance-trained athletes required a VO2max >55mL.kg.min-1 and participated in endurance training ≥ 10 hours/week for a minimum of two years. All were screened using the new Physical Activity Readiness Questionnaire for Everyone (PAR-Q+) to determine eligibility to participate: free from chronic disease and no contraindications to exercise. Ethical approval was obtained through the University of British Columbia Clinical Ethics Board in exact accordance with the Declaration of Helsinki, and all participants provided written informed consent. 5.2.2 Experimental Protocol Participants participated in two days of testing. On the first day participants were assessed for height, body mass and aerobic capacity (VO2max). On the second day of testing (occurring a minimum of one week later) the following assessments were conducted: 1) baseline cardiovascular assessments, 2) pre-exercise autonomic and cardiac assessments during graded LBNP, 3) high-intensity interval exercise on a cycle ergometer, and 4) post-exercise autonomic and cardiac assessments during LBNP. Following baseline assessments, the LBNP challenge was initiated at -20 mmHg below atmospheric pressure for five minutes. Subsequent five-minute stages were performed at -40 and -60 mm Hg. The negative pressure was terminated if the participant encountered symptoms of presyncope (drop in systolic blood pressure of 15 mmHg, and a drop in heart rate of 15 beats per minute, dizzy, lightheaded, or nauseous) or at participant request. Beat-by-beat blood pressure, ECG, and echocardiographic assessments were established during each stage. Individual responses to LBNP, including heart rate variability responses, have been shown to be highly reproducible within the same individual [237, 238]. A 30-minute  64  washout period preceded the high-intensity interval session and repeat LBNP pressure was subsequently performed. A schematic of the protocol can be found in Appendix C. 5.2.3 Procedures VO2max. Height and body mass was measured to the nearest 0.1 cm and 0.1 kg, respectively. An incremental bike test to exhaustion (Velotron Dynafit Pro, RacerMate Inc, Seattle, USA) was used for the assessment of maximal aerobic power (VO2max). The protocol began at a workload of 80-100 watts and increased 25 watts every 2 minutes until volitional fatigue. Participants donned a face mask (Oro-nasal 7400 Vmask with Headgear, Hans Rudolph, Kansas, USA) for the collection of expired gases analyzed by a metabolic cart (Medisoft Ergocard, Sorinnes, Belgium). In addition, HR and arterial oxyhaemoglobin saturation were measured continuously using a pulse oximeter (Masimo Radical, Irvine, CA, USA) attached to the participant’s right index finger. Hydration Assessment. A urine sample was collected prior to the interval session. A drop of urine was analyzed for urine specific gravity (Atago Pocket Refractometer, PAL-10S, Japan) which has been shown to be a valid means of assessing hydration status [215]. A result <1.02 served as the threshold of hydration status acceptable to commence testing [216, 217]. Once adequate hydration was verified, a measure of body mass was recorded to the nearest 0.1 kg using a digital scale (Seca, Birmingham, UK) and measured again post-exercise. Baroreflex Sensitivity. Baseline autonomic measures were assessed following ten minutes of supine rest. Participants were instrumented with an ECG and finger plethysmography secured to the middle finger, using a beat-by-beat blood pressure device (Finapres; Ohmeda Inc, Englewood, CO). Automated blood pressure measurements were obtained by brachial occlusion 65  (BpTRU 100, Coquitlam, Canada) for calibration and collected in duplicate. Continuous recordings were sent to a data acquisition system (PowerLab/16SP ML 795, ADInstruments, Colorado Springs, CO) and displayed using Chart (version 7.0, ADInstruments, Colorado Springs, CO). Echocardiography. Echocardiographic assessments were performed by a trained clinical sonographer using a portable ultrasound unit (Vivid i, GE Medical Systems, USA) with simultaneous ECG and a 2.5-MHz transducer. Participants were positioned in the left lateral decubitus position for imaging. Apical two- and four-chamber views were acquired for the assessment of left ventricular (LV) volumes, LV longitudinal strain and strain rate, in addition to transmitral pulsed Doppler flow velocities and tissue Doppler mitral annular velocities. All strain imaging was acquired at high frame rates (80-90 frames per second). End-diastolic volume (EDV) and end-systolic volume (ESV) using Simpson’s bi-plane method for which three consecutive beats were measured and analyzed. Ventricular volumes, diameters, and strain analyses were performed offline (EchoPAC, GE Healthcare, v. 110.1.1) in accordance with the recommendations of the American Society of Echocardiography [175]. High Intensity Interval Exercise. Pre- and post-exercise blood pressure was measured in the seated position (BpTRU 100, Coquitlam, Canada) after five minutes of quiet sitting. The test began after five minutes of warm up followed by two minutes of inactive rest while seated on the bike. The interval exercise involved fifteen one-minute maximal work bouts interspersed with two-minute recovery periods on a stationary cycle ergometer (Velotron Dynafit Pro, RacerMate Inc, Seattle, USA). The workload was assigned in watts equivalent to the final power output obtained during the VO2max test. The recovery periods were active rest at 50 W. Participants  66  were allowed to drink water ad libitum. The test ended with one minute of active recovery totalling 44 minutes of exercise. 5.2.4 Data Analysis Body surface area was calculated as BSA (m2) = SQR RT ([Height(cm) x Weight(kg)]/ 3600 ) [170]. Mean arterial pressure (MAP) was calculated as DBP + 1/3 (SBP – DBP). All twodimensional and Doppler data were analyzed off-line by taking an average of three consecutive beats. Left ventricular mass was determined using the formula: LV Mass (g) = 0.8 (1.04 ([LVIDD + PWTD + IVSTD]3- [LVIDD]3))+ 0.6 [177]. Stroke volume was calculated as EDVESV, and cardiac output was calculated as stroke volume x heart rate. Ejection fraction (EF) was calculated as stroke volume as a percentage of EDV. Total peripheral resistance (TPR) was derived from dividing cardiac output into MAP. An index of left ventricular filling pattern was assessed by calculating the ratio of early (E) to late (A) diastolic filling (E/A). The ratio of transmitral flow to transmitral tissue velocity (E΄; E/E΄), provides an estimation of LV filling pressures. Baroreceptor sensitivity was analyzed by selecting a clean five-minute segment of the Chart file via specialized programmed to exclude ectopic beats (Nevrokard NKFP 8.7.0 and BRS 5.7.0, Nevrokard, Izola, Slovenia). The sequence method was derived from the calculation of the slope between changes in R-R interval (RRI) and changes in systolic blood pressure, and the alpha coefficient in the low frequency (LF) or high frequency (HF) bands represented the crossspectral method of baroreflex sensitivity analysis [38]. For the sequence method, inclusion criteria was set as: a RR interval variation of greater than 5 ms, blood pressure changes greater than 0.5 mmHg, minimum sequence duration of four beats, sequence correlation coefficient 67  greater than 0.85, and a one beat delay between SBP and RR interval. For the spectral method, the fast Fourier transformation was used to power spectral density of blood pressure and RR interval. The spectral gain of oscillations was set to fixed signal bandwidths of low frequency (0.04 – 0.15 Hz, LF) and high frequency (0.15 – 0.45 Hz, HF) as per current recommendations [38]. In the data analysis the sequence method values were labeled BRS, and the spectral components αLF and αHF. The ratio of LF to HF of the RRI as a measure of heart rate variability was labeled RRI LF/HF. Finally, the LF of blood pressure variability was labeled SBP LF was expressed as a percent of total power. 5.3 STATISTICAL ANALYSIS A four-way mixed model ANOVA was used to compare differences in haemodynamic measures between sex (male, female) and group (NA=normally active, ET=endurance trained) over time (stage of LBNP) by condition (pre-exercise, post-exercise) with Bonferroni adjustment for multiple comparisons (SPSS v20, IBM). Pearson’s correlation analysis was used to find associations between significant factors. Significance for all tests was set a priori at p<0.05. All analyses were performed using SPSS software (version 20.0; SPSS IBM, Chicago, IL). Results are reported as mean ± SD. 5.4 RESULTS 5.4.1 Participant Characteristics All 33 recruited participants completed this study with no exercise-related adverse events. Participant characteristics are found in Table 5.1. Endurance-trained individuals reported engaging in aerobic training four to six d/week and consisted of 12 cyclists, four tri-athletes, two cross-country skiers, and one runner. The ET participants had higher LV mass and stroke volume 68  at baseline. Men displayed higher EDV and ESV than women. When indexed for body surface area, volumes remained greater in athletes (EDVI, p=0.005; ESVI, p=0.047; SVI, p=0.002) with sex differences only remaining for ESVI (p=0.036). 5.4.2 Cardiovascular Responses to Exercise and Lower Body Negative Pressure Stroke volume was reduced post-exercise compared to baseline. Throughout lower body negative pressure, stroke volume was reduced to a greater extent before exercise than with LBNP post-exercise, and this effect was greater in males. Stroke volume and cardiac output (indexed for body surface area) began at higher values but decreased to a greater degree in ET compared with NA (Figure 5.1). An interaction of condition by LBNP by sex was also found for stroke volume index. Mean arterial pressure did not change with LBNP however, women displayed lower MAP post-exercise compared to men (Figure 5.2). Total peripheral resistance significantly increased with LBNP (p<0.001) and was lower post-exercise (p=0.023; Figure 5.2). Diastolic filling determined from Doppler flow is shown in Figure 5.3. Early diastolic filling decreased with LBNP but more so post-exercise. There were no significant alterations in late diastolic filling. An interaction was revealed for the E/A ratio in which normally active females maintained a higher E/A ratio, particularly during early post-exercise LBNP. Heart rate was altered less during LBNP post-exercise than occurred pre-exercise and was not different by sex or group (Figure 5.4). Main effects were found for ejection fraction and LBNP (p=0.003) and ejection fraction by condition (p<0.001), with higher values in women versus men (Figure 5.5). As one group, the cardiac responses to LBNP pre and post-exercise are reported in Table 5.2. Of these variables, only myocardial tissue velocity of the septal segment (E septal) presented an interaction (Figure 5.6). Normally active females had higher tissue velocity, with endurance69  trained females suffering a greater reduction post-exercise from baseline values. A surrogate for filling pressure, E/Eˈ was not affected by lower body negative pressure, but there was an interaction of sex and group pre and post-exercise (Figure 5.6). Endurance-trained females appeared to reduce filling pressures post-exercise compared to before exercise, whereas, endurance-trained males did not. Finally, LV strain and diastolic strain rate were reduced with exercise (p=0.001) and LBNP (p<0.001) but there were no interactions (Figure 5.7). Women displayed higher strain and strain rates than men throughout the intervention. 5.4.3 Baroreflex Function with Exercise and Lower Body Negative Pressure Baroreflex function revealed training status differences with an interaction of condition by LBNP by group (Figure 5.8). Pre-exercise, ET show greater reductions in αLF with lower body negative pressure compared to normally active, whereas post-exercise, αLF was reduced similarly in all groups. Furthermore, alterations as demonstrated throughout LBNP pre-exercise were attenuated post-exercise. The LF/HF of heart rate variability was altered with LBNP and with exercise but there was no interaction with sex or group. Pearson correlation analysis revealed significant correlations for absolute VO2max and post-exercise baroreflex sensitivity (r=-0.38, p=0.04) and post-exercise αLF (r=-0.50, p=0.004), as well as for relative VO2max and post-exercise αLF (r=-0.41, p=0.023). Between sex differences were evident for all measures with women possessing higher sequence baroreflex sensitivity (p=0.014), higher αLF (p=0.016) lower RRI LF/HF (p=0.049) and lower absolute SBP LF (p=0.048) than men. When expressed as percent of total spectral power, a three-way interaction was displayed where after exercise women showed a drop in SBP LF (%) at the most severe lower body negative pressure stage where before exercise this had increased at that time point, similar to the men (Figure 5.9). 70  Table 5.1 Participant Characteristics  Males  Females  NA n=8  ET n = 12  NA n=6  ET n=7  Age, y  29.50 ± 4.6  29.9 ± 5.7  29.7 ± 5.7  29.9 ± 5.8  Height, cm ¥  182.1 ± 4.8  178.2 ± 5.5  162.1 ± 4.1  168.5 ± 4.7  Body Mass, kg ¥  79.8 ± 4.9  73.6 ± 6.8  58.5 ± 5.4  58.4 ± 6.3  VO2max, mL.kg.-1.min-1 ǂ  46.8 ± 5.4  58.5 ± 4.0  45.0 ± 4.2  56.4 ± 4.4  SBP, mmHg  111.6 ± 6.9  107.3 ± 10.6  104.2 ± 5.9  104.3 ± 4.4  DBP, mmHg  66.4 ± 5.3  63.7 ± 5.9  65.3 ± 5.2  65.4 ± 4.4  LV Mass, kg ¥ ǂ  200.4 ± 25.9  215.5 ± 43.0  122.6 ± 17.5  175.7 ± 26.2  EDV, mL ¥  145.4 ± 32.4  164.0 ± 31.6  97.5 ± 25.3  114.9 ± 17.8  ESV, mL ¥  60.5 ± 8.4  60.0 ± 23.1  37.8 ± 13.5  43.9 ± 14.8  SV, mL ǂ  84.9 ± 28.6  104.0 ± 17.7  59.7 ± 18.2  71.0 ± 9.9  Abbreviations: SBP=systolic blood pressure; DBP=diastolic blood pressure; LV=left ventricle; EDV=end diastolic volume; ESV=end-systolic volume; SV=stroke volume The effects of sex and training status on participant characteristics were obtained via unadjusted linear models. ¥ p<0.01 between sex; ǂ p<0.01 between group  71  NA men  70  Stroke Volume Index (mL/m2)  NA women  α §  60  ET men ET women  50 40 30 20 10 0  4  α  Cardiac Index (L.min-1/m2)  3.5 3 2.5 2 1.5 1 0.5 0 0  20  40  60  0  Pre-exercise  20  40  60  Post-exercise  Lower Body Negative Pressure (mm Hg)  Figure 5.1 Stroke Volume and Cardiac Ouput Responses § p<0.05 condition x LBNP x sex; α p<0.05 LBNP x group  72  men women  95  MAP (mm Hg)  90 85 80 75 70  Δ  65 60 55  TPR (mm Hg/ L.min-1)  50 50 45 40 35 30 25 20 15 10 5 0  ^ ɵ  0  20  40 Pre-exercise  60  0  20  40  60  Post-exercise  Lower Body Negative Pressure (mm Hg)  Figure 5.2 Sex Differences in Haemodynamic Response to Lower Body Negative Pressure and Exercise Δ p<0.05 condition x sex; ^ p<0.05 condition; ɵ p<0.05 LBNP MAP=mean arterial pressure; TPR=total peripheral resistance  73  Late Diastolic Filling (m/s)  Early Diastolic Filling (m/s)  1.2  *  *  1 0.8 0.6 0.4 0.2 0 0.6 0.5 0.4  0.3 0.2 0.1 0 NA men  β  3  NA women  E/A ratio  2.5  ET men  2  ET women  1.5 1 0.5 0 0  20  40 Pre-exercise  60  0  20  40  60  Post-exercise  Lower Body Negative Pressure (mmHg)  Figure 5.3 Diastolic Filling Across Lower Body Negative Pressure Before and After Exercise * p=0.002 condition x LBNP; β p=0.014 condition x LBNP x sex x group 74  Heart Rate (bpm)  100 90 80 70 60 50 40 30 20 10 0  NA men NA women ET men ET women  0  20  40  60  0  Pre-exercise  20  40  60  Post-exercise  Lower Body Negative Pressure (mmHg)  Figure 5.4 Heart Rate Across Lower Body Negative Pressure Before and After Exercise p=0.008 condition x LBNP  80 Ejection Fraction (%)  70 60 50 40 30 20  Men  10  Women  0 0  20  40  60  Pre-exercise  0  20  40  60  Post-exercise  Lower Body Negative Pressure (mmHg)  Figure 5.5 Ejection Fraction Across Lower Body Negative Pressure Before and After Exercise p=0.003 condition; p=0.000 LBNP; p=0.006 between sex 75  Table 5.2 Indices of Left Ventricular Systolic and Diastolic Function  Pre-Exercise 0 mmHg  Post-Exercise  -20 mmHg  -40 mmHg  -60 mmHg  0 mmHg  -20 mmHg  -40 mmHg  -60 mmHg  EDVI, mL/m2 ^ɵ  74.36 ± 16.45  55.23 ± 17.95  56.19 ± 11.26  45.56 ± 14.81  63.76 ± 12.80  53.16 ± 10.31  46.45 ± 15.79  39.00 ± 18.61  ESVI, mL/m2 ^ɵ  28.63 ± 9.40  24.62 ± 10.40  26.97 ± 7.45  22.67 ± 8.24  25.57 ± 8.18  25.32 ± 6.67  23.59 ± 8.13  20.11 ± 10.19  EF, % ^ ɵ  61.65 ± 8.50  55.97 ± 8.04  52.33 ± 6.93  51.35 ± 8.02  58.66 ± 7.90  52.48 ± 6.69  49.10 ± 4.97  48.48 ± 7.58  Eˈ sep, cm/s ǂ  11.8 ± 2.3  11.6 ± 2.3  11.0 ± 2.6  10.0 ± 2.6  11.7 ± 1.8  11.2 ± 2.0  9.4 ± 2.3  8.8 ± 1.9  Eˈ lat, cm/s ^ ɵ  17.5 ± 2.9  15.4 ± 2.5  14.9 ± 3.2  14.0 ± 3.8  15.3 ± 3.0  15.2 ± 2.0  13.8 ± 3.2  11.9 ± 3.8  Eˈ RV, cm/s *  14.7 ± 2.8  13.3 ± 2.4  13.2 ± 3.0  12.6 ± 2.6  13.4 ± 2.4  11.4 ± 2.1  11.2 ± 2.7  10.4 ± 2.4  E/Eˈ septal €  6.05 ± 1.46  5.61 ± 1.29  5.32 ± 1.57  5.64 ± 1.67  6.31 ± 1.17  6.17 ± 1.39  5.94 ± 1.62  6.27 ± 1.40  E/Eˈ lateral * LV Strain, % ^ɵ  4.14 ± 1.03  4.13 ± 1.00  4.17 ± 1.16  4.38 ± 1.95  4.83 ± 1.01  4.46 ± 0.79  4.02 ± 1.50  4.92 ± 1.90  -17.41 ± 2.27  -14.67 ± 2.70  -13.20 ± 2.10  -13.01 ± 3.46  -16.50 ± 2.40  -14.56 ± 2.24  -13.78 ± 2.78  -12.64 ± 2.83  -1  -1.01 ± 0.14  -1.34 ± 0.15  -0.88 ± 1.62  -0.87 ± 1.70  -0.87 ± 0.16  -0.81 ± 1.04  -0.80 ± 0.17  -0.80 ± 0.15  -1  1.44 ± 0.23  1.18 ± 0.33  1.07 ± 0.23  1.00 ± 0.24  1.35 ± 0.28  1.17 ± 0.28  1.03 ± 0.30  0.97 ± 0.22  LV sSR, s  LV dSR, s ^ ɵ  Abbreviations: EDVI=end-diastolic volume index; ESVI=end-systolic volume index; EF=ejection fraction; E'=mitral annular tissue velocity; sep=septal wall of left ventricle; lat=lateral wall of left ventricle; RV=right ventricle; E=early diastolic filling; LV=left ventricle; sSR=systolic strain rate; dSR=diastolic strain rate Effect of exercise obtained using general linear models adjusted for sex and training status. * p<0.05 condition x LBNP; ^ p<0.05 condition; ɵ p<0.05 LBNP  76  Septal Annular Velocity (m/s) E/E' Septal  NA men NA women ET men ET women  β  0.18 0.16 0.14 0.12 0.1 0.08 0.06 0.04 0.02 0  β  9 8 7 6 5 4 3 2 1 0  €  0  20  40  60  0  Pre-exercise  20  40  60  Post-exercise  Lower Body Negative Pressure (mmHg)  Figure 5.6 Septal Wall Tissue Velocity and Filling Pressures β p=0.022 condition x LBNP x sex x group; € p=0.016 condition x sex x group  77  0 -2  Men  -4  Women  Longitudinal Strain (%)  -6 -8 -10 -12  ^ɵ¥  -14 -16  -18 -20 -22  Longitudinal dSR (s-1)  2  1.8 1.6 1.4 1.2 1 0.8 0.6 0.4 0.2 0  ^ɵ ¥  0  20  40 Pre-exercise  60  0  20  40  60  Post-exercise  Lower Body Negative Pressure (mmHg)  Figure 5.7 Longitudinal Strain and Diastolic Strain Rate ^ p<0.05 condition; ɵ p<0.05 LBNP; ¥ p<0.05 between sex; dSR = diastolic strain rate  78  NA ET  BRS (ms/mm Hg)  60 50 40 30  #  20 10 0  aLF (ms/mm Hg)  40  #  30  #  20  ɵ^  10 0  RRI LF/HF  30  20 10 0 -10 100  SBP LF (%)  80  60 40 20 0 0  20  40  60  Pre-exercise  p0  p20  p40  p60  Post-exercise  Lower Body Negative Pressure (mm Hg)  Figure 5.8 Training Group Differences in Autonomic Indices # p<0.05 condition x LBNP x group; ɵ p<0.05 LBNP; ^ condition 79  men women  30  RRI LFHF  25 20  15  Δɵ  10 5 0 -5  120  SBP LF (%)  100  80  §  60 40 20 0 0  20  40  60  p0  Pre-exercise  p20  p40  p60  Post-exercise  LBNP (mm Hg)  Figure 5.9 Sex Differences in Autonomic Indices § p<0.05 condition x LBNP x sex; Δ p<0.05 condition x sex; ɵ p<0.05 LBNP  80  5.5 DISCUSSION This investigation aimed to determine the effects of endurance training and sex on cardiac and autonomic responses to high intensity interval exercise. We observed significant independent effects of sex and training status on the response to exercise and lower body negative pressure. The main findings of this investigation are that 1) women exhibit altered autonomic and cardiac function at rest compared to men and maintained this throughout the intervention; 2) endurance-trained individuals presented enhanced cardiac and autonomic function at rest however at intense levels of lower body negative pressure (> -40 mmHg) showed significant reductions compared with normally active individuals; and 3) endurance-trained individuals demonstrated a more rapid recovery in autonomic indices post-exercise despite greater reductions in left ventricular function than normally active participants. Our investigation supports previous work showing enhanced resting autonomic function in women [260] and endurance-trained individuals [62, 89-93], as well as their susceptibility to an orthostatic challenge [73, 247, 261, 262]. Our work is novel wherein it shows that under an aggregate physiological stress, those with improved training status have increased capacity to rebound (i.e., improve back to baseline) autonomic control more quickly, despite undergoing more significant reductions in cardiac function. Before exercise, endurance-trained individuals demonstrated the traditional response to lower body negative pressure where measures of cardiac and baroreflex function reduced drastically with intense lower body negative pressure. Sex affected this response as endurance-trained women held diastolic function until the later stages of lower body negative pressure, where ET women fell to values similar to ET males. Also, throughout 81  lower body negative pressure, ET displayed lower heart rates but at -60 lower body negative pressure, mean heart rate in ET females increased sharply to the heart rates of the untrained individuals. Post-exercise, NA females showed the least reductions from baseline of left ventricular function, heart rate variability and baroreflex sensitivity and maintained their values better than the other groups. Thus, we show an interaction of sex and training status in our intervention, where normally active females represented the best tolerance to lower body negative pressure and exercise, and endurance trained males faired the poorest. Finally, despite ET males showing greater depressions in E/A ratio, ejection fraction, tissue velocities and higher filling pressures, they demonstrated a significantly improved recovery of baroreflex function over the other groups as shown by their improved αLF in severe lower body negative pressure post-exercise. 5.5.1 The Sex Factor Potential mechanisms previously associated with sex differences to orthostasis include greater venous compliance [73], lower blood volume, impaired baroreflex function [75] and lower resting SV [263] in women. However, the women we examined tolerated the orthostatic stress quite well particularly due to the resiliency of the normally active women. Further, this ability to tolerate orthostatic stress persisted into the post-exercise lower body negative pressure intervention. This was unexpected as the compensation required to maintain blood pressure after exercise is considerably more than what is needed to an orthostatic challenge independently [264]. Exercise-induced reductions in blood volume [265], and blood pooling in the extremities with the cessation of the skeletal muscle pump [244] are exacerbated with lower body negative pressure. Our 82  observations reveal that women did not experience any greater reductions in venous return than the men based on stroke volume and cardiac output. In fact, our endurance trained men experienced the greatest reductions in stroke volume in either lower body negative pressure condition, which supports our previous findings in women [171] that suggests that the rate of change in stroke volume is a more valid indication of orthostatic intolerance than absolute stroke volume. Thus, considering the women in this study did not experience greater orthostatic intolerance than the men, it is plausible to assume autonomic function was not challenged beyond capacity. Previous work indicates that the sympathovagal balance of women may be more vulnerable to the effects of strenuous exercise than men [66, 266]. Certainly autonomic indices were markedly reduced (baroreflex sensitivity and αLF) or elevated (RRI LF/HF and SBP LF) post-exercise, however this did not occur to a greater extent in women. Only one sex-response was evident (higher RRI LF/HF ratio) for the men, thus opposing this previous work. In support of our findings, other work has demonstrated females to be more resilient to exercise induced alterations in cardiac autonomic modulation [267, 268]. The inclusion of highly trained participants is likely responsible for our findings as training status has been shown to further protect against cardiac autonomic modulations [267]. The low frequency component of systolic blood pressure (SBP LF) did not change markedly with lower body negative pressure and less so following exercise. The SBP LF measure is considered a broad index of the vascular sympathetic modulation; one of the multiple, non-invasive autonomic indices that might be useful in the clinical management of conditions characterized by disturbed autonomic regulation such as hypertension or 83  diabetes [269]. We observed higher SBP LF values in men, indicating greater systemic sympathetic vascular tone [270] during post-exercise LBNP, likely in response to the greater post-exercise fall in cardiac output. Kimmerly et al. [271] found men had greater heart rate and sympathetic responses during 35mmHg LBNP. This was associated with greater changes in forebrain activity, leading to the postulation that forebrain regions may be involved with the generation of sex-specific differences in baroreflex-mediated sympathetic and cardiovascular responses to LBNP. 5.5.2 The Training Factor Our study revealed greater haemodynamic and baroreflex alterations in endurancetrained subjects. In addition, both load dependent (Doppler transmitral flow velocities) and less load-dependent measures of cardiac function (tissue Doppler and strain indices) [196] revealed an effect of training status on response to lower body negative pressure to which there was an interaction with sex. Similar to previous work from our laboratory, peak early transmitral filling and diastolic strain rate were reduced with LBNP in the endurance trained individuals suggesting greater reductions in left atrial pressure [272] impacting right ventricular stroke volume and subsequently LV stroke volume via the Frank Starling relationship. While shown to influence orthostatic tolerance [171] these drastic reductions in stroke volume will require sufficient vasoconstrictor capacity to maintain arterial blood pressure. Thus, as discussed above, the endurance-trained males appeared to rely on greater sympathetic outflow to defend blood pressure in the postexercise condition. As total peripheral resistance was not affected by sex or training status in our study, we can safely assume that the mechanisms of vasoconstriction 84  employed by the endurance trained males, was adequate. In a recent investigation, vasoconstriction was not found to be impacted by training status at rest, nor was it limb specific [273]. However, when the participants in that study exercised, sympathetic vasoconstriction was blunted in both arms and legs but less so in the arms of the cyclists versus controls. These researchers infer this to reflect an increase in α-adrenergic sensitivity in the arms as part of the adaptations to chronic exercise demands, which is necessary to ensure optimal blood flow to the exercising legs and to avoid over-perfusion of the arm. Other recent work has illustrated the impact of endurance training on reducing sympathetic outflow to the renal vasculature and diminished renal vasoconstriction during head-up tilt [274]. This further supports the notion that regional alterations in vasoconstriction may be a compensatory mechanism under heavy demand. It has been said that humans have limited, individual and restricted vasoconstrictor reserve to which fitness may be one important factor [275]. While our data is unable to validate these mechanisms as active in our endurance-trained cohort, our indirect evidence suggests vasoconstrictor activity may play a role. 5.5.3 Other Considerations In the present investigation we intentionally measured exercise-related changes in baroreflex control in conjunction with lower body negative pressure to assess the effects of sex and training status on the ability to influence potential indicators of cardiovascular risk [276]. However, other factors may impact the observed responses: peripheral arterial structure and function [277]; leg venous compliance and function [278]; and morphological adaptions of the LV [279]. It must also be considered that factors more 85  commonly found in women versus men, or endurance-trained individuals have influenced our findings and may not be limited to the groups to which they have been identified. For example, baroreflex sensitivity declines with age [280]. Compelling evidence suggests that exercise-related maintenance of arterial compliance is associated with the attenuated decline in baroreflex sensitivity with healthy aging [46, 281]. The impact of a healthy diet on arterial compliance [282] cannot be ignored and is not limited to athletes or a particular sex. 5.5.4 Cardiovascular Risk We have shown that endurance-trained individuals displayed remarkable recovery in autonomic function following our strenuous intervention. In clinical work, heart rate recovery after exercise has been shown to be a powerful independent predictor of mortality in healthy subjects and those recovering from myocardial infarction [104, 283]. While the immediate post-exercise period harbours higher risk than without strenuous exercise even in healthy individuals [22] the clinical relevance of these transient large shifts in sympathovagal balance are unclear, particularly in light of an improved autonomic profile as a chronic training adaptation. 5.6 LIMITATIONS Participants were asked to refrain from exhaustive exercise for 24 hours prior to testing. In endurance trained individuals, particularly cyclists, being in an over-reaching or over-trained state cannot be ruled out. After very intensive training, cardiovagal baroreflex sensitivity has been shown to shift from parasympathetic toward sympathetic dominance [284]. In a study by Middleton and De Vito [285] endurance-trained females 86  were found to have significantly lower baroreflex sensitivity than untrained females (7.95 vs. 13 ms mmHg, respectively), a finding the authors concede may be due to the intense training schedule the women were engaged in at the time of testing. Our resting values were similar to the normative data presented by Iellamo and colleagues [284] during the rested phase of their training cycle. This along with subjective observations in the participants tested, we do not feel overtraining was likely in our group. Another consideration is that we compared active men and women as opposed to a sedentary cohort. This was by design as we wanted to assess the impact of training on cardiovascular function without the confounding factors that are associated with a sedentary lifestyle. Both groups had individuals who engaged in strength training. Strength training has been shown to affect the blood pressure response to head-up tilt differently than endurance training [279]. Although none of the participants were involved in high volume strength training and likely did not do enough to appreciable affect blood pressure regulation, this remains a factor that could be considered in future work. Finally the sample size was too small to assess confidently the sex and training interactions (i.e., condition x LBNP x sex x group). However, we identified that sex and training status independently have an impact on the haemodynamic and baroreflex responses to exercise and lower body negative pressure. Thus, future work should aim to assess this intervention with larger numbers in order to explore the interaction of these factors more effectively.  87  5.7 CONCLUSIONS This investigation showed that female sex was particularly resilient under a severe orthostatic stress. In particular, normally active women demonstrated the most tolerance based on cardiovascular and autonomic indicators. Endurance-trained males were presented with the greatest haemodynamic challenges and demonstrated greater sympathetic activity as evidenced by spectral measures of blood pressure variability. Endurance-trained individuals displayed a significantly more rapid baroreflex recovery than untrained. These findings highlight the impact of sex and training status on the recovery from strenuous exercise; yet the interplay between the paradoxical training and sex-related cardioprotection seen at rest and the acute exercise-induced cardiac impairments require further exploration.  88  Chapter 6: Post-exercise Hypotension in Men and Women Following High-Intensity Interval Exercise  6.1 INTRODUCTION An acute reduction in blood pressure can be observed after a single bout of exercise, termed post-exercise hypotension [286]. Post-exercise hypotension is thought to occur as a result of a mismatch between the drop in systemic vascular resistance and increase in cardiac output [287, 288]. There may be an intensity dependent relationship between exercise and acute reductions in blood pressure [289-291]. Typically thought to occur following moderate intensity aerobic exercise [292, 293], post-exercise hypotension has also been shown after prolonged endurance [232], brief maximal exercise [243, 294], and high intensity interval exercise [254, 295]. As the metabolic and cardiovascular benefits of high-intensity interval exercise have become more apparent recently [10, 296], the use of this type of exercise as an effective blood pressure–lowering strategy for at-risk populations is appealing and warrants further investigation. The limited research to date measuring changes in blood pressure resulting from highintensity exercise, would suggest that the magnitude of the blood pressure reduction is similar when compared to steady-state exercise [254, 295, 297] or between sexes [228, 295]. While the magnitude may be similar, the mechanisms behind the post-exercise hypotension response are unclear [228, 254, 295]. Autonomic, vascular, and cardiac mechanisms have been implicated in post-exercise hypotension [288, 298]. It has been suggested that differences in baroreflex function may be involved [299] but this has yet to be determined. As baroreflex, autonomic, and cardiac function are highly influenced by 89  sex and training status, their impact on the post-exercise hypotension response to strenuous interval exercise would benefit our understanding of this important physiological response. The purpose of this investigation was to explore the mechanisms of the post-exercise hypotension response following a strenuous bout of interval exercise in normotensive, endurance-trained and untrained men and women. It was hypothesized that the magnitude of post-exercise hypotension (i.e., blood pressure change) would be similar for all individuals but the mechanism of this response would differ by training status. 6.2 METHODS 6.2.1 Participants and Ethical Approval Participants in this investigation were healthy, young, normotensive individuals. A total of 40 individuals (18 F) volunteered to partake in this research. Individuals were classified as endurance-trained if they participated in a minimum of ten hours of endurance training per week, in addition to a VO2max greater than 55mL.kg.min-1. All were screened using the new Physical Activity Readiness Questionnaire for Everyone (PAR-Q+) to determine eligibility to participate: free from chronic disease and no contraindications to exercise. Participants were non-smokers and were not taking any medications other than oral contraceptives. Volunteers provided written informed consent, and this research was approved by the Clinical Research Ethics Board at the University of British Columbia.  90  6.2.2 Experimental Protocol All individuals participated in three separate testing sessions with a minimum of 48 hours between sessions. The first session involved a maximal aerobic power assessment (VO2max), followed by a second session where volunteers were assessed for body composition via a Dual-energy X-ray absorptiometry (DXA) scan. The third session involved the high-intensity interval session and was completed at least one week after the VO2max test. Cardiovascular variables were measured before exercise (pre) and 30minutes following the cessation of exercise (post). 6.2.3 Procedures and Analysis Anthropometrics and DXA. Body mass and stature were measured to the nearest 0.1 cm and 0.1 kg, respectively. Body surface area was calculated as BSA (m2) = SQR RT ([Height(cm) x Weight(kg)]/ 3600 ) [170]. Whole body and sub-regional composition analysis was performed using dual energy x-ray absorptiometry on a 2006 Hologic Discovery Wi running the Apex 3.0 software suite. Participants were scanned in metal free clothing in standard anatomical position, with the toes restrained using a small section of paper tape. Sub-regional and whole body values for lean, fat and bone mineral content were produced. VO2max Assessment. Baseline automated blood pressure and heart rate was obtained at the start of this session (BMP-100 VSM Medtech, Coquitlam, Canada). Participants then completed a structured warm up, which included a five-minute rest period prior to starting an incremental bike test to exhaustion (Velotron Dynafit Pro, RacerMate Inc, Seattle, USA). The protocol began at a workload of 80-100 watts and increased 25 watts 91  every two minutes until 1) the respiratory exchange ratio reached 1.0, and 2) the participant rated themselves a 6 or greater on the Ratings of Perceived Exertion scale. At this point, the test continued with workload increments every minute until volitional fatigue. Participants donned a face mask (Oro-nasal 7400 Vmask with Headgear, Hans Rudolph, Kansas, USA) for the collection of expired gases analyzed by metabolic cart (Medisoft Ergocard, Sorinnes, Belgium). In addition, HR and arterial hemoglobin saturation were measured continuously using a pulse oximeter (Masimo Radical, Irvine, CA, USA) attached to the participant’s left ear lobe. Cardiovascular Variables. Baseline cardiovascular measures were measured following ten minutes of supine rest. Participants were instrumented with an ECG and finger plethysmography secured to the middle finger, using a beat-by-beat blood pressure device (Model-1 Pro: Finapres Medical Systems BV, The Netherlands). Continuous recordings were sent to a data acquisition system (PowerLab/16SP ML 795, ADInstruments, Colorado Springs, CO) and displayed using Chart (version 7.0, ADInstruments, Colorado Springs, CO). Automated blood pressure measurements obtained by brachial occlusion (BMP-100 VSM Medtech, Coquitlam, Canada) in the seated position were also collected in duplicate. Pulse pressure was calculated from systolic blood pressure (SBP) – diastolic blood pressure (DBP), and mean arterial pressure (MAP) was calculated as DBP + 1/3 pulse pressure. Echocardiographic assessments were performed by a trained clinical sonographer using a portable ultrasound unit (Vivid i, GE Medical Systems, Israel) with simultaneous ECG and a 2.5-MHz transducer. Participants were positioned in the semi-left lateral decubitus position for imaging. Ventricular volumes and diameters were analyzed off92  line using EchoPAC software (GE Healthcare, v. 110.1.1) in accordance with the recommendations of the American Society of Echocardiography [175]. Left ventricular mass was determined using the formula: LV Mass (g) = 0.8 (1.04 ([LVIDD + PWTD + IVSTD]3- [LVIDD]3))+ 0.6 [177]. Apical four-chamber views were acquired for the assessment of end-diastolic volume (EDV) and end-systolic volume (ESV) using Simpson’s bi-plane method for which three consecutive beats were measured and analyzed. Stroke volume (SV) was calculated by EDV-ESV. Cardiac output (CO) was calculated as SV x heart rate. Ejection fraction (EF) was calculated as a percentage of EDV. Fractional shortening (FS) was calculated from left ventricular diameters, using the parasternal long axis window, and expressed as a percent. Total peripheral resistance (TPR) was derived from MAP/CO. All cardiac dimensions, volumes and flow parameters, as well as total peripheral resistance were expressed relative to body size by indexing to body surface area (BSA) and presented as EDVI, ESVI, SVI, CI, and TPRI. Hydration Assessment. A urine sample was collected prior to the interval session. A drop of urine was analyzed for urine specific gravity (Atago Pocket Refractometer, PAL10S, Japan) which has been shown to be a valid means of assessing hydration status [215]. A result <1.02 served as the threshold of hydration status acceptable to commence testing [216, 217]. Once adequate hydration was verified, a measure of body mass was recorded to the nearest 0.1 kg using a digital scale (Seca, Birmingham, UK) and measured again post-exercise. High Intensity Interval Exercise. For the high-intensity interval session, participants performed 15 one-minute maximal workbouts interspersed with two-minute recovery periods on a stationary cycle ergometer (Velotron Dynafit Pro, RacerMate Inc, Seattle, 93  USA). The workload was assigned in watts equivalent to the final power output obtained during the VO2max test. The recovery periods were active rest at 50 W. The test began after five minutes of warm up followed by two minutes of inactive rest while seated on the bike. Participants were allowed to drink water ad libitum. The test ended with one minute of active recovery totalling 44 minutes of exercise. Seated blood pressure and body mass was measured before and immediately after the high-intensity interval session. Baroreceptor Sensitivity Analysis. Baroreceptor sensitivity was analyzed by selecting a five minute segment of the Chart file via specialized software (Nevrokard NKFP 8.7.0 and BRS 5.7.0, Nevrokard, Izola, Slovenia). The sequence method was derived from the calculation of the slope between changes in R-R interval (RRI) and changes in systolic blood pressure, and the alpha coefficient in the low frequency (LF) or high frequency (HF) bands represented the cross-spectral method of BRS analysis [38]. For the sequence method, inclusion criteria was set as: a RR interval variation of greater than 5 ms, blood pressure changes greater than 0.5 mmHg, minimum sequence duration of four beats, sequence correlation coefficient greater than 0.85, and a one beat delay between SBP and RR interval. For the spectral method, the fast Fourier transformation was used to power spectral density of blood pressure and RR interval. The spectral gain of oscillations was set to fixed signal bandwidths of low frequency (0.04 – 0.15 Hz, LF) and high frequency (0.15 – 0.45 Hz, HF) as per current recommendations [38]. In the data analysis the sequence method values were labeled baroreceptor sensitivity, and the spectral components αLF and αHF. The ratio of LF to HF of the RRI as a measure of heart rate variability was labeled RRI LF/HF. Finally, the LF of blood pressure variability was labeled SBP LF. 94  6.3 STATISTICAL ANALYSIS A mixed-model ANOVA was used to assess differences in haemodynamic and autonomic variables between pre- and post-exercise (time) by the factors sex (male, female) and training (NA, ET). Haemodynamic variables were related to VO2max, muscle mass, percent body fat, baseline blood pressure and baroreceptor sensitivity, and magnitude of change in baroreceptor sensitivity using Pearson’s correlation analysis. Linear regression analysis was used to determine the factors responsible for the change in cardiac function. Significance for all tests was set a priori at p<0.05. All analyses were performed using SPSS software (version 20.0; SPSS IBM, Chicago, IL). Results are reported as mean ± SD. 6.4 RESULTS The participant characteristics are shown in Table 6.1. Sex differences at baseline were present as expected with men displaying greater height, body mass, lean body mass, aerobic capacity, peak power, and lower body fat (p<0.01). Endurance-trained individuals had greater aerobic capacity, peak power, and lower body fat than normally active individuals (p<0.05). Prior to the interval session, urine specific gravity was within the range considered to  represent adequate hydration [215] averaging 1.01 ± 0.01. Unaffected by sex or training status, body mass decreased 0.27 ± 0.47 kg following exercise. The peak heart rate response to the interval exercise bout was 94.7 ± 3.1 and 92.2 ± 3.8 % of maximum heart rate for NA and ET, respectively (p=0.037). There was no sex difference in this exercise heart rate response. All cardiovascular and autonomic variables displayed a main time 95  effect, or interaction of time and group (p<0.05), except ESVI, EF and SBP LF (Table 6.2; Table 6.3). Systolic blood pressure, DBP and MAP decreased from pre-exercise values by 6.2, 5.1, and 5.5%, respectively. Total peripheral resistance index decreased an average of 6% and was highly variable, while stroke volume index decreased 15% (9 – 22%) with an interaction of training status (p=0.026; Figure 6.2). Fractional shortening was significantly different from baseline and a trend was revealed by group (p=0.076; Figure 6.3). Among the autonomic variables, a time by training interaction was found for αLF (p=0.037) and αHF (p=0.002; Figure 6.4). Between subject effects (sex, training status) are also shown in Table 6.2 and 6.3. Men displayed greater SBP, EDVI, SVI, and CI than women, whereas women displayed higher BRS, αLF and αHF values than men. Endurance-trained individuals had greater EDVI, SVI, αLF and αHF and lower TPRI, RRI LF/HF and SBP LF than the normal active participants. Select correlations are listed in Table 6.4. Relationships of absolute stroke volume and VO2max and LV mass are shown in Figures 6.5 and 6.6, respectively. Lastly, the change in SVI as it relates to baseline SVI is shown in Figure 6.7.  96  Table 6.1 Participant Characteristics  Men NA n Age, y Height, cm Mass, kg BMI, kg/m2 .  VO2max, L min  -1  VO2max, ml.kg.min-1 LVM, g LVM/BSA, g/m2 LBM, kg LBM/BSA, kg/m2 Fat, % Peak Power, W  #  p value ∞ 0.045 0.467 0.528 0.269  0.046 0.339 0.694 0.369  Women ET  NA  ET  ^  10 28.0 ± 5.9 179.8 ± 6.5 77.0 ± 7.4  12 34.5 ± 5.6 179.5 ± 6.9 76.2 ± 7.0  9 29.4 ± 4.6 164.1 ± 8.6 62.3 ± 13.3  9 29.1 ± 5.9 167.9 ± 4.2 59.3 ± 5.8  23.8 ± 1.4  23.7 ± 1.7  22.9 ± 2.2  21.7 ± 2.0  0.209 0.000 0.000 0.019  3.61 ± 0.54  4.54 ± 0.53  2.81 ± 0.83  3.35 ± 0.49  0.000  0.001  0.328  46.9 ± 5.3 197.9 ± 29.4 179.8 ± 6.5 58.9 ± 6.0 30.0 ± 1.4 20.6 ± 3.9 225 ± 45.6  59.7 ± 4.0 242.0 ± 49.5 179.5 ± 6.9 58.6 ± 7.0 27.6 ± 8.9 18.8 ± 4.9 300.0 ± 41.3  44.0 ± 4.0 131.1 ± 19.2 164.1 ± 8.6 41.5 ± 6.5 24.6 ± 1.1 28.6 ± 3.6 182.2 ± 44.5  56.4 ± 3.9 176.2 ± 25.0 167.9 ± 4.2 42.9 ± 5.3 23.0 ± 8.8 22.5 ± 3.9 235.0 ± 24.5  0.069  0.000  0.659  <0.001 <0.001 0.000 0.021 0.000 0.000  <0.001 <0.001 0.785 0.329 0.004 0.000  0.963 0.614 0.670 0.853 0.106 0.542  Abbreviations: LVM=left ventricular mass; LBM=lean body mass; BSA=body surface area The effects of sex and training status on participant characteristics were analyzed by unadjusted general linear models. BOLD p values denotes statistically significant; # between sex, ∞between group, ^ between sex by group.  97  Table 6.2 Baseline and Post-Exercise Haemodynamics Men  Women ET 111.6 ± 10.3 99.3 ± 11.8  NA 101.0 ± 6.9 95.4 ± 8.2  ET 104.0 ± 8.8 98.7 ± 12.8  Pre Post  NA 113.4 ± 6.1 110.1 ± 12.2 64.7 ± 3.7 60.8 ± 8.6  66.6 ± 3.9 63.2 ± 7.4  63.7 ± 6.2 61.4 ± 8.4  67.0 ± 7.1 62.8 ± 13.3  MAP, mm Hg *  Pre Post  80.9 ± 3.7 77.2 ± 9.2  81.6 ± 5.0 75.2 ± 7.4  76.1 ± 5.7 72.8 ± 8.0  79.1 ± 6.8 74.7 ± 12.8  HR, bpm *  Pre Post  57.9 ± 5.2 78.3 ± 8.2  52.3 ± 7.6 72.8 ± 12.3  56.3 ± 10.1 74.9 ± 8.8  59.0 ± 8.5 74.1 ± 9.6  EDVI, mL/ m 2 ¥#  Pre Post  72.8 ± 14.7 60.9 ± 9.5  85.9 ± 15.7 71.9 ± 14.9  59.7 ± 10.4 50.8 ± 10.2  77.0 ± 17.9 67.9 ± 5.2  ESVI, mL/ m 2  Pre Post  29.4± 6.0 27.5± 5.3  31.1 ± 10.9 28.4 ± 7.8  22.4 ± 6.4 18.5 ± 3.9  30.7 ± 11.9 27.1 ± 5.8  SVI, mL/ m 2 ¥# ∞  Pre Post  26.4±8.2 20.3±3.6  33.2 ± 7.4 26.3 ± 5.5  23.3 ± 5.9 20.2 ± 4.7  27.4 ± 5.5 24.1 ± 2.5  EF, % ^  Pre Post  59.1±7.6 55.0±4.3  64.0 ± 9.3 60.8 ± 5.9  62.5 ± 9.1 63.4 ± 4.1  61.2 ± 7.5 60.3 ± 6.5  FS, % *  Pre Post  39.1±6.1 36.2±7.4  38.6 ± 7.3 33.3 ± 9.8  34.9 ± 5.7 36.5 ± 5.0  36.4 ± 4.7 30.9 ± 6.3  CI, L.min-1/ m 2* #  Pre Post  2.5 ± 0.6 2.7 ± 0.5  2.8 ± 0.6 3.1 ± 0.5  2.1 ± 0.6 2.5 ± 0.6  2.8 ± 0.7 3.2 ± 0.7  TPRI, mm Hg/ L.min-1/m 2 * # ∞  Pre Post  9.0 ± 2.5 7.8 ± 2.2  8.0 ± 2.3 6.6 ± 1.4  14.7 ± 6.5 11.5 ± 4.0  11.1 ± 3.1 8.8 ± 2.4  SBP, mm Hg * #  Pre Post  DBP, mm Hg *  ∞  Abbreviations: SBP=systolic blood pressure; DBP=diastolic blood pressure; MAP=mean arterial pressure; HR=heart rate; EDV=end-diastolic volume; ESV=end-systolic volume; SV=stroke volume; EF=ejection fraction; FS=fractional shortening; CO=cardiac output; TPR=total peripheral resistance * p<0.05 time, ¥ p<0.05 time by group # p<0.05 between sex, ∞ p<0.05 between group, ^ p<0.05 between sex by group.  98  Table 6.3 Baseline and Post-Exercise Autonomic Parameters Men  Women  NA  ET  NA  ET  BRS, ms.mm Hg * #  Pre Post  23.3±10.3 7.4±2.8  28.3±8.7 11.4±6.1  38.8±14.2 17.3±13.5  30.0±18.0 13.3±7.3  αLF, mm Hg ¥ #  Pre Post  13.5±6.6 7.0±3.2  20.3±8.7 10.1±6.0  22.0±14.0 14.1±9.6  28.5±8.2 9.3±4.3  αHF, mm Hg ¥ #  Pre Post  21.1±9.6 7.2±4.5  34.9±18. 3 10.7±5.6  37.0±27.0 25.1±16.3  56.9±16.9 15.0±7.8  RRI LFHF * ∞  Pre Post  2.1±1.2 8.4±5.9  1.2±0.6 8.4±7.4  1.5±0.8 3.4±3.1  1.1±0.7 5.0±5.0  SBP LF, mm Hg ∞  Pre Post  12.2±8.0 19.1±15.1  4.4±4.3 9.2±9.4  13.0±17.6 4.9±2.4  2.5±0.8 10.0±8.5  Abbreviations: BRS=baroreceptor sensitivity; αLF=alpha coefficient of low frequency spectral power; αHF=alpha coefficient of high frequency spectral power; RRI LFHF=low frequency to high frequency ratio of RR interval; SBP LF=low frequency power of systolic blood pressure variability  The effects of exercise on cardiovascular haemodynamics were analyzed by general linear models adjusted for sex and training status. * p<0.05 time effect, ¥ p<0.05 time by group, # p<0.05 between sex, ∞ p<0.05 between group  99  SBP (mm Hg)  130  *  NA m  125  ET m  120  NA f  115  ET f  110 105 100 95 90 80 75  DBP (mm Hg)  70 65 60 55 50 45 40  *  95 90 MAP (mm Hg)  85 80 75 70 65 60 Baseline  Post-exercise  Figure 6.1 Effect of Exercise on Blood Pressure * p<0.05 from baseline  100  NA  70 ¥  SVI (mL/m2)  60  ET  50 40 30 20  18  *  16 TPRI  14 12 10 8 6 4  *  CI (L.min-1/m2)  4 3.5 3 2.5 2 1.5 1 Baseline  Post-exercise  Figure 6.2 Exercise Haemodynamics * p<0.01 from baseline; ¥ p=0.026 time by group  101  50  *  * NA  45  ET  Fractional Shortening (%)  40 35 30 25 20 15 10 5 0 Baseline  Post-exercise  Figure 6.3 Effects of Exercise on Fractional Shortening * p=0.026 from baseline  102  NA m  40  ET m  αLF ms / mm Hg  35  ¥ #  30  NA f ET f  25 20 15 10 5 0  70  αHF ms / mm Hg  60  ¥ #  50 40 30 20  10 0 Pre-exercise  Post-exercise  Figure 6.4 Effect of High-Intensity Interval Exercise on Indices of Baroreceptor Sensitivity ¥ p<0.05 time by group; # between sex  103  Table 6.4 Select Correlations Δ SBP  Δ EDVI  Δ SVI  Δ aLF  Δ aHF  r = -0.314  r = 0.205  r = -0.214  r = 0.044  r = -0.027  P = 0.048  P = 0.204  P = 0.186  P = 0.787  P = 0.868  r = -0.365  r = 0.653  r = -0.623  r = 0.244  r = 0.157  P = 0.021  P = 0.000  P = 0.000  P = 0.129  P = 0.332  r = -0.290  r = 0.388  r = -0.755  r = 0.102  r = 0.209  P = 0.069  P = 0.013  P = 0.000  P = 0.529  P = 0.196  r = 0.082  r = -0.288  r = 0.547  r = -0.193  r = -0.208  P = 0.615  P = 0.071  P = 0.000  P = 0.232  P = 0.198  r = 0.227  r = -0.104  r = -0.003  r = 0.389  r = 0.433  P = 0.158  P = 0.523  P = 0.988  P = 0.013  P = 0.005  r = -0.041  r = 0.053  r = 0.081  r = -0.137  r = -0.344  P = 0.807  P = 0.754  P = 0.629  P = 0.413  P = 0.035  VO2max  r = -0.285  r = 0.107  r = -0.373  r = 0.045  r = 0.097  L.min-1  P = 0.075  P = 0.510  P = 0.018  P = 0.782  P = 0.550  r = -0.365  r = 0.097  r = -0.215  r = 0.198  r = 0.275  P = 0.021  P = 0.550  P = 0.183  P = 0.221  P = 0.086  r = 0.038  r = -0.106  r = -0.024  r = -0.097  r = -0.068  P = 0.817  P = 0.515  P = 0.885  P = 0.554  P = 0.677  r = -0.056  r = 0.129  r = -0.369  r = -0.050  r = -0.050  P = 0.739  P = 0.439  P = 0.023  P = 0.764  P = 0.764  r = -0.191  r = 0.093  r = -0.364  r = -0.032  r = 0.019  P = 0.254  P = 0.577  P = 0.025  P = 0.850  P = 0.910  r = -0.189  r = 0.065  r = -0.264  r = -0.042  r = 0.061  P = 0.255  P = 0.699  P = 0.109  P = 0.801  P = 0.718  Pre SBP  Pre EDVI  Pre SVI  Pre TPRI  Pre BRS  RRI LF/HF  VO2max .  .  mL kg min  -1  LBM  LBM/BSA  LVM  LVM /BSA  Abbreviations: SBP=systolic blood pressure; EDVI=end-diastolic volume index; SVI=stroke volume index; TPRI=total peripheral resistance index; BRS=baroreceptor sensitivity; αLF=alpha coefficient of low frequency spectral power; αHF=alpha coefficient of high frequency spectral power; RRI LFHF=low frequency to high frequency ratio of RR interval; LBM=lean body mass; BSA=body surface area; LVM=left ventricular mass BOLD p values denotes statistical significance (p<0.05)  104  10  Change in SV (%)  0 -10 -20 -30 -40 -50 -60 -70 0  1  2  3  4  5  6  7  VO2max (L.min-1)  Figure 6.5 Relationship of Aerobic Capacity to Percent Change in Stroke Volume Pearson r=-0.49, p=0.007; Linear Regression: r2=0.24, Std. Beta=-0.548 (adjusted for group), p=0.002  10  Change in SV (%)  0 -10 -20 -30 -40 -50 -60 -70 90  140  190  240  290  340  LVM (g)  Figure 6.6 Association of Left Ventricular Mass to Change in Stroke Volume Pearson r=-0.47, p = 0.011; Linear Regression: r2=0.22, Std. Beta=-0.515 (adjusted for group), p=0.004 105  0  10  20  30  40  50  60  70  80  10 5 Change in SVI (%)  0 -5 -10 -15 -20 -25  -30 -35 -40  Baseline SVI (mL/m2)  Figure 6.7 Association of Change in Stroke Volume to Baseline Stroke Volume Pearson r=-0.750, p<0.001; Linear Regression: r2=-0.63, Std. Beta=-0.851 (adjusted for group), p<0.001  106  6.5 DISCUSSION The aim of this investigation was to assess post-exercise hypotension following a strenuous bout of interval exercise in normotensive, endurance-trained and untrained men and women. The primary findings of this investigation are that 1) the magnitude of postexercise hypotension following high intensity interval exercise was similar regardless of sex or training status, and 2) endurance-trained individuals displayed more marked reductions in stroke volume than normally active individuals, and 3) greater reductions in baroreceptor sensitivity occurred in the trained group. To our knowledge this the first study to investigate post-exercise hypotension following high-intensity interval exercise incorporating both sex and training status into the design. Our study suggests that high intensity interval exercise elicits a similar acute blood pressure response in healthy individuals but that training status differentiates the mechanism of this response. Earlier work investigating post-exercise hypotension in healthy men and women found a sex and training interaction where endurance trained men presented a different mechanism of post-exercise hypotension compared with endurance-trained women, however in untrained individuals this sex difference did not exist [228]. These authors reported that untrained men experienced a fall in cardiac output with no change in total peripheral resistance whereas the other groups maintained cardiac output with significant reductions in peripheral resistance, an indication of more active vasodilation. Furthermore, these authors propose that a greater fall in central venous pressure and thus cardiac preload was responsible. Our work supports these findings, and extends this mechanism to include endurance-trained women, however differs from the work of Senitko and colleagues in a few ways. First they utilized a submaximal protocol at an 107  intensity of 60% VO2max. While exercise intensity appears to have little effect on the magnitude of post-exercise hypotension, higher intensity exercise alters hemodynamics to a greater extent than submaximal exercise [254, 295]. Second, the reported VO2max values of the endurance-trained individuals in the former study were similar to that of our normally active participants, subsequently making it difficult to compare with our competitive cyclists. By contrast, Rossow and colleagues [295] found endurance-trained males and females to have a similar mechanism of post-exercise hypotension following high intensity interval exercise, in agreement with our results: a decrease in SVI, an increase in CI, and a decrease in TPRI for both men and women. Contrary to our hypothesis, we did not find sex differences in the post-exercise hypotension response. We speculated that the larger cardiac size of males due to sexrelated differences coupled with the chronic training adaptations would create an acute exercise response unique to the four groups [300]. Further it has been shown that women experience higher peripheral resistance during endurance exercise [301] thus we expected normally active women to represent the other end of the spectrum. Indeed it has been suggested that men may experience post-exercise hypotension without vasodilation [302], however, a number of studies are in disagreement. Scott et al. [254] reported total peripheral resistance significantly reduced in endurance-trained males following both high-intensity interval exercise, and steady-state exercise. Moreover, vasodilation was found to occur in normally active males [228] and endurance-trained males following steady-state exercise [295]. There is a general consensus that post-exercise hypotension typically occurs as a result of a mismatch between the drop in systemic vascular resistance and increase in cardiac 108  output [288]. While this was reflected in our sample as a whole, the endurance-trained individuals exhibited greater reductions in stroke volume. Possible factors affecting stroke volume are preload, afterload, and myocardial contractility. Using systolic blood pressure as a surrogate of afterload, and cardiac indicators of contractility (end-systolic volume and fractional shortening), we did not find any differences in these responses among groups. Granted, a slight trend was observed for a greater reduction in fractional shortening for endurance trained subjects however this was not statistically significant. Thus, we cannot support the notion of differences in contractility between the groups, however we acknowledge this is a possibility. We did not measure central venous pressure in this investigation however, we found a prominent interaction of group by time for EDVI which would indicate differences in preload in endurance-trained versus normally active individuals. Possible explanations include alterations in baroreflex function, or the redistribution of cardiac output from less compliant to more compliant vascular beds, and are discussed below. Differences in baroreflex function may play a role. Following exercise, the baroreflex sets to a lower pressure [252] and sympathetic vasoconstrictor influence is reduced [292]. In the presence of reduced afterload, reduced vasoconstrictive capacity could alter cardiac filling. Earlier research showed that blocking the cardiac afferents and efferent fibers with intrapericardial procainamide prevented post-exercise hypotension, while blocking the cardiac efferent alone elicited no effect [303]. Chandler et al demonstrated in rats that by removal of the arterial baroreflex afferents via sinoaortic denervation, post-exercise hypotension was prevented [304]. Hence, these investigations showed the importance of a functioning baroreflex for the expression of post-exercise hypotension. In our study 109  using non-invasive cardiovagal measurements of baroreflex function, we found evidence of greater reductions in αLF and αHF components in the endurance-trained individuals. However, we did not find any association of these changes to the magnitude of postexercise hypotension or haemodynamic alterations. Lacombe et al. [297] compared the haemodynamic and BRS responses following high intensity interval exercise to that of steady state exercise in pre-hypertensive older (50 – 65y) men. They found similar postexercise hypotension responses between the two protocols but reductions in baroreceptor sensitivity for the high intensity exercise only. As in our study, the change in baroreceptor sensitivity did not evoke any differences in the post-exercise hypotension response. It has been suggested that a combination of central and peripheral mechanisms regulating blood pressure are likely responsible for post-exercise hypotension [286] and may explain why a direct link is not shown. The reduced venous return after exercise may be a result of the redistribution of cardiac output from less compliant to more compliant vascular beds such as the splanchnic organs and the skin [305]. Recently shown to be unrelated to post-exercise hypotension, new evidence suggests that vasoconstriction in other areas, perhaps the splanchnic or renal vascular beds, may offset the vasodilation in skeletal muscle in endurance-trained individuals [306] and would explain why they typically do not exhibit the post-exercise augmentation of systemic vascular conductance [302]. Recent work using pharmacological blockade has highlighted histaminergic mechanisms responsible for the post-exercise hyperemia in endurance-trained men and women [302]. Further, ventricular compliance is known to be greater in endurance-trained athletes and may potentially result in larger reductions in stroke volume for a given cardiac filling pressure 110  [263]. While a more compliant ventricle allows for greater cardiac efficiency during exercise, in concert with hyperemia in the lower limbs after exercise, may exaggerate the reduction in stroke volume for a given reduction in LV filling pressure [245]. 6.6 LIMITATIONS The potential decreased in plasma volume due to sweat loss in the endurance-trained subjects must be considered as possible factor affecting preload in our study. While we did not measure plasma volume, we did assess weight loss following the exercise; the small decrease was not different between groups. Also, participants were encouraged to drink throughout, thus we do not anticipate decreases in plasma volume were responsible for our results. Finally, while our sample size was determined to be adequately powered to detect the expected physiological changes a priori, the division of four groups lowered the observed power significantly for certain variables. This needs to be considered when interpreting the interaction of sex and training status on post-exercise hypotension. 6.7 CONCLUSIONS We determined that high intensity interval exercise induced post-exercise hypotension in normotensive men and women of different training status. We also demonstrated that following high intensity interval exercise training status, but not sex, differentiated the mechanisms of post-exercise hypotension where endurance-trained individuals presented post-exercise hypotension via a decrease in stroke volume whereas normally active did not. This work has implications for the use of interval exercise as an effective means of acute blood pressure modifications, and may be an alternate form of exercise that could be used in interventions aimed at prevention of hypertension. 111  Chapter 7: The Effects of High Intensity Exercise on Cognitive Function in Healthy Young Adults  7.1 INTRODUCTION Cognition broadly defined pertains to knowledge processing (i.e., attention, memory, learning, reasoning, problem solving, and decision making) mediated by a centralised nervous system [307]. Physical activity and exercise positively influence cognition. Regular physical activity has been associated with a reduction in the decline in cognitive function that is typically associated with aging [308-313], and this cognitive decline may be due to age-related brain atrophy [314]. There have also been reports that aerobic exercise in childhood may increase cerebral resilience to age-related decline, whereby improved cognition is shown in those who exercised more [315]. This suggests that there are lasting effects of exercise on cognitive function. Furthermore, a recent study has shown cognitive function was higher in physically active compared with inactive individuals, with cognition correlated to VO2max [316]. Fit individuals were also shown to have greater cerebrovascular conductance and increased cerebrovascular reserve. Both acute and chronic effects of exercise such as alterations in neurotransmitters, neurotrophins, and vasculature changes, and their association with cognitive function have been of recent mechanistic interest [317]. Hence a large gap remains in how exercise mediates cognitive benefits. Dopamine, a key neurotransmitter in the brain, has been shown to be involved in learning [318-321] and may mediate improvements in memory [322]. However investigations exploring the plasma dopamine response to physical exercise have 112  produced conflicting results as not all investigations report an increase in dopamine with exercise [323]. Intensity of exercise may be a key factor in stimulating dopamine release whereby a certain degree of acidosis is required [324]. In this regard, high-intensity exercise may be an effective means of stimulating dopamine and accentuating circulation, resulting in a substantial impact on cognition. Currently the research involving high intensity exercise and cognition is limited. It has been suggested that cognitive performance decrements would occur with strenuous exercise due to substantial physiological fatigue [325] or diminished attention [326]. Reaction time, the time taken to complete a task, may also be affected when under a fatigued state as increased reaction times (decreased cognitive performance) were reported after high-intensity exercise [327, 328]. However, improved cognitive function (i.e., working memory, reaction time, vocabulary learning) may occur during the recovery period [328-330]. Collectively, the findings of these investigations suggest that enhanced cognitive performance may occur during recovery from exercise, when attentional resources become available while an increase in systemic circulation persists. High-intensity interval exercise is increasing in popularity, in part due to the greater physiological and metabolic gains that have been reported over traditional aerobic exercise in various populations [17]. Therefore, the assessment of cognition following high-intensity interval exercise may reveal further health benefits for this type of exercise. The small body of work investigating cognition in relation to high-intensity exercise has predominately involved very brief exercise bouts, such as the 30-second Wingate. The repeated nature of high-intensity interval exercise produces a substantial physiological stimulus and would be expected to impact cognition differently to that of a 113  30-second sprint. Accordingly we investigated the impact of maximal high-intensity interval exercise on cognitive function (reaction time and working memory) following one and four hours of recovery. As haemodynamic indicators of recovery have been shown to return towards baseline very rapidly following high-intensity exercise in healthy young adults [331], it was hypothesized that increased reaction time and working memory would be enhanced from baseline values following one hour of recovery but return to baseline at four hours. 7.2 METHODS 7.2.1 Participants and Ethical Approval Twelve healthy, physically active individuals (2 F) with a mean age 28 ± 3.7 y volunteered for this study. All participants answered pre-screening questionnaires indicating they were free of chronic disease, with no history of concussion. All individuals were non-smokers and not taking any medications other than oral contraceptives. Volunteers provided informed consent and this research was approved by, and executed in exact accordance with the guidelines set out by the Clinical Research Ethics Board at the University of British Columbia. 7.2.2 Experimental Protocol Participants were engaged in two days of testing. On day 1, participants were assessed for basic anthropometrics, baseline cardiovascular and cognitive function, as well as maximal aerobic capacity (VO2max). After one to two weeks, individuals returned to the laboratory and completed two more baseline assessments of cognition (Pre), the last of which was considered true baseline. Following 44 minutes of exercise, basic 114  haemodynamic variables were assessed at three time points: immediately post-exercise (Post), one hour post-exercise (Rec 1), and four hours post-exercise (Rec 2). Cognitive assessments after exercise were conducted at one hour post-exercise (Rec 1), and four hours post-exercise (Rec 2). Blood samples were taken before exercise and immediately post-exercise. A schematic of the protocol can be found in Appendix C. 7.2.3 Procedures Basic Anthropometrics. Anthropometrics and Cardiovascular Variables. Height and body mass were measured to the nearest 0.1 cm and 0.1 kg, respectively. Baseline cardiovascular measures of heart rate, blood pressure, arterial compliance and pulse wave velocity were assessed on day 1 following 10 minutes of supine rest. Participants were instrumented with an ECG and finger plethysmography secured to the middle finger, using a beat-by-beat blood pressure device (Model-1 Pro: Finapres Medical Systems BV, The Netherlands). Automated blood pressure measurements obtained by brachial occlusion (BMP-100 VSM Medtech, Coquitlam, Canada) were used to verify and correct readings obtained from the Finometer. At the femoral and carotid arteries, infared photoelectric sensors (MLT1020PPG Plethysmograph, AD Instruments) recorded changes in pulsatile blood flow by recording changes in blood volume as the arterial pulse expands and contracts the microvasculature. These instruments plug directly into a bridge amp to the PowerLab (Bridge Amp/ML221; Powerlab/16SP ML 795: ADInstruments, Colorado Springs, CO). Pulse wave velocity was determined via postcollection analysis as previously described [212]. Briefly, a minimum of 30 consecutive cardiac cycles were averaged to calculate the foot-to-foot pulse transit time between the 115  carotid artery and femoral artery. The shortest distances between the sites of pulse contour collection were measured to the nearest 0.5 cm using a standard measuring tape and this distance was divided by the corresponding pulse transit time in order to calculate pulse wave velocity. Baseline arterial compliance was obtained as a measure of vascular health, and was assessed non-invasively using an applanation tonometer (CR-3000, HDI Hypertension Diagnostics). This technique, based on a modified Windkessel model that allows for the calculation of large (capacitive) artery and small (oscillatory) artery compliance, has been validated with invasive testing [173]. The radial arterial waveform acquisition of the right arm was obtained in conjunction with automated blood pressure on the left arm inflated to 20-30 mmHg below radial pulsatory pressure. For the exercise sessions, blood pressure was measured before and after exercise, with heart rate measured every minute throughout. VO2max. Following the acquisition of seated automated blood pressure and heart rate (HR; BMP-100 VSM Medtech, Coquitlam, Canada), participants completed a structured warm up, which included a 5 minute rest period prior to starting the incremental bike test to exhaustion (Velotron Dynafit Pro, RacerMate Inc, Seattle, USA). The protocol began at a workload of 80-100 watts and increased 25 watts every 2 minutes until 1) the respiratory exchange ratio reached 1.0, and 2) the participant rated themselves a 6 or greater on the Ratings of Perceived Exertion scale. At this point, the test continued with 25 watt increments every minute until volitional fatigue, and the criteria for maximal testing were met. Participants donned a face mask (Oro-nasal 7400 Vmask with Headgear, Hans Rudolph, Kansas, USA) for the collection of expired gases analyzed by 116  metabolic cart (Medisoft Ergocard, Sorinnes, Belgium). In addition, heart rate and arterial hemoglobin saturation were measured continuously using a pulse oximeter (Masimo Radical, Irvine, CA, USA) attached to the participant’s left ear lobe. High-Intensity Interval Exercise. For the high intensity interval session participants performed fifteen 1-minute maximal work intervals interspersed with two-minute recovery periods on a stationary cycle ergometer (Velotron Dynafit Pro, RacerMate Inc, Seattle, USA). The workload was 100% of the power output obtained during the VO2max test, and the recovery periods were active rest (50-100 watts). Participants completed a warm up at a self-selected intensity followed by two minutes of inactive rest while seated on the bike with the final set ending after one minute of active rest for total session duration of 44 minutes. Participants were allowed to drink water ad libitum. Blood Sampling and Dopamine Analysis. Pre- and post-exercise blood samples (6 ml each) were drawn from a medial cubital vein using a needle and vacutainer system. The blood was centrifuged and frozen at -80°C until analysis. Dopamine was analyzed by immunoassay using ELISA kit RE59395 (IBL International, Hamburg, Germany) with an analytical sensitivity of 4 pg.mL-1 and cross-reactivity <0.5%. The intra-assay and interassay coefficient of variation were <10.9% and 16%, respectively. Cognitive Test Battery. Cognitive testing was performed using computerized assessment to measure simple reaction time, choice reaction time, working memory task time, and working memory task accuracy (CogState Ltd, Carlton, VIC, Australia). This computerized assessment is easy to administer and shown to be sensitive to mild cognitive impairment from various causes [332-337]. Each testing situation started with  117  three to five warm-up stimuli (specific practice for each task). The chosen tests are briefly described below: Detection Task (Simple Reaction Time): In front of a monitor displaying a green background and a deck of cards (face down), the participant was instructed to hit the space bar as rapidly as possible after the card displayed on the monitor turned face up. The next card was then displayed, and the participant repeated the task until 35 stimuli were presented. Reaction time was recorded in milliseconds (ms). Identification Task (Choice Reaction Time): Similar to the Detection Task, the participant answered the question “Is the card red?” by clicking the yes or no assigned keys as rapidly as possible after the card displayed on the monitor turned face up. The next card was then displayed, and the participant repeated the task until 30 stimuli were presented. Choice reaction time was measured in ms. CPAL Task (Visual Learning and Memory): This task was divided into two stages. In Stage 1, one ball was presented in the middle of the computer monitor, around which seven other balls were displayed. The participant was required to click on the peripheral balls to reveal a hidden picture. The participant was asked to memorize the pictures hidden under each of the balls, and their respective locations. In Stage 2, the participant was asked to answer the question “In what locations do these pictures belong?”. The ball in the middle displays a picture, and the participant clicked on the peripheral ball hiding the same picture. Seven rounds of eight stimuli were presented to the participant, for a total of 56 stimuli. Time to complete the total task in milliseconds, and total number of errors were assessed.  118  7.3 STATISTICS Cognitive and corresponding cardiovascular variables were assessed using repeatedmeasures ANOVA with Bonferroni adjustment for multiple comparisons. Simple and choice reaction time and working memory were correlated with baseline vascular measures, VO2max, change in heart rate and blood pressure, and change in dopamine, using Pearson’s r. Linear regression analysis was used to determine the factors responsible for the change in cardiac function. Significance for all tests was set a priori at p<0.05. All analyses were performed using SPSS software (version 20.0; SPSS IBM, Chicago, IL). Results are reported as mean ± SD. 7.4 RESULTS All 12 recruited individuals completed the testing protocol and were included for analysis. Participant characteristics, baseline cardiovascular measures, and maximal aerobic capacity are found in Table 7.1. Mean group heart rate during exercise increased from 147.2 ± 12.1 bpm after the first interval to a mean heart rate of 174.5 ± 7.4 bpm following the last work bout. Figure 7.1 presents pre-exercise and recovery heart rates. At the first recovery measurement (Post), mean heart rate decreased to 100.5 ± 10.9 bpm compared to the last exercise bout. Participants post body mass was 74.6 ±10.1 from 74.9 ± 10.1 kg (p<0.001), all significantly different from baseline and each other. Resting heart rate was negatively correlated with VO2max (r=-0.81, p=0.001).  119  Table 7.1 Participant Characteristics Variable  n = 12 (2F)  Age, y Height, cm Body Mass, kg BMI, kg.m2 SBP, mm Hg DBP, mm Hg LAC, ml.mmHg.10 SAC, ml.mmHg.100 PWVc, cm/s PWVu, cm/s VO2max, mL.kg.min-1  28.0 ± 3.7 176.7 ± 8.5 74.5 ± 10.0 23.7 ± 1.5 115.5 ± 10.8 61.1 ± 6.7 19.6 ± 3.8 10.5 ± 1.8 624.2 ± 211.2 547.3 ± 348.4 48.9 ± 8.1  Heart Rate (bpm)  Abbreviations: BMI=body mass index; SBP=systolic blood pressure; DBP=diastolic blood pressure; LAC=large artery compliance; SAC=small artery compliance; PWVc=central pulse wave velocity; PWVu=upper segment of pulse wave velocity  *  *  Post  Rec 1  *  120 110 100 90 80 70 60 50 40 ⁄ 30 0 ⁄ Pre  Rec 2  Condition Figure 7.1 Individual Results for Change in Heart Rate Baseline (Pre), immediately post-exercise (Post), 1 hour post-exercise (Rec 1) and 4 hours post-exercise (Rec 2). The mean is represented by the dashed (- - -) line. * different from baseline p<0.001. 120  Simple reaction time decreased from baseline (Figure 7.2, p=0.001) with both Rec 1 and Rec 2 different from baseline (p=0.008 and p=0.028, respectively) and not different from each other (p=0.546). Choice reaction time decreased over time (Figure 7.3, p=0.001), also with both Rec 1 and Rec 2 different from baseline (p=0.024 and p=0.016, respectively) and not different from each other (p=0.863). The participants performed better on the CPAL test from baseline (Figure 7.4, p<0.001) for Rec 1 (p<0.001) and Rec 2 (p=0.003), with no difference between the recovery measurements (p=0.212). Errors on the other hand were not significantly impacted differently over time (p=0.325). Dopamine was significantly elevated post-exercise (Figure 7.5). Moderate correlations were found for post-exercise dopamine and the change in CPAL scores from pre-exercise to Rec 1 (r=0.572, p=0.08) and baseline dopamine and large artery compliance (r=0.601, p=0.07) but these did not reach the statistical significance threshold established for this research (Figures 7.6 and 7.7, respectively). A significant correlation was found for baseline blood pressure and CPAL duration indicating those with higher baseline blood pressure took longer to complete the CPAL test (Figure 7.8).  121  360  Reaction Time (ms)  340  *  *  Rec 1  Rec 2  320 300 280 260 240 220 200 0  ⁄⁄ Pre  Condition Figure 7.2 Individual Results for the Comparison of Simple Reaction Time Baseline (Pre), 1 hour post-exercise (Rec 1) and 4 hours post-exercise (Rec 2). The mean is represented by the dashed (- - -) line. * different from baseline p<0.05.  725  *  *  Reaction Time (ms)  675 625 575 525 475 425 375 325 0 275  ⁄⁄ Pre  Rec 1  Rec 2  Condition Figure 7.3 Individual Results for the Comparison of Choice Reaction Time Baseline (Pre), 1 hour post-exercise (Rec 1) and 4 hours post-exercise (Rec 2). The mean is represented by the dashed (- - -) line. * Significant from baseline p<0.05. 122  350000 330000  *  310000  *  Duration (ms)  290000 270000 250000 230000 210000 190000 170000 0 150000  ⁄⁄ Pre  Rec 1  Rec 2  Condition Figure 7.4 Individual Results for Working Memory Duration Baseline (Pre), 1 hour post-exercise (Rec 1) and 4 hours post-exercise (Rec 2). The mean is represented by the dashed (- - -) line. * Significant from baseline p<0.05. *  Dopamine (pg/mL)  140 120 100 80 60 40 20 0 Pre  Post  Figure 7.5 Change in Dopamine with Exercise Values at baseline (Pre), and immediately post-exercise (Post). * Significant from baseline p=0.001  123  40  Reduction of CPAL Task Duration (%)  35 30 25 20 15 10 5 0 0  20  40  60  80  100  120  140  Increase in Dopamine (pg/mL)  Figure 7.6 Relationship of the Change in Dopamine to the Change in Working Memory Duration Pearson r =0.56, p=0.09  Large Artery Compliance (mL.mm Hg.10))  30 25 20 15 10 5  ⁄⁄  0 20 0  25  30  35  40  45  Dopamine (pg/mL)  Figure 7.7 Relationship of Baseline Dopamine Values to Large Artery Compliance Pearson r = 0.60, p=0.07 124  400000  CPAL Duration  350000 300000 250000 200000 150000 100000 50000 0  90  100  110  120  130  140  Systolic Blood Pressure (mm Hg)  Figure 7.8 Relationship of Baseline Working Memory Duration to Systolic Blood Pressure Pearson r =0.65, p=0.022  7.5 DISCUSSION The main findings of this investigation are that vigorous exercise in the form of intervals has a positive effect on cognitive performance early in the recovery period and that these effects were still prominent four hours after the cessation of exercise. Participants displayed improved reaction time and choice reaction time, as well as completed the working memory task more quickly. Our work supports other findings shwoing improvements in cognition following intense exercise [328, 330] and adds to the literature by showing lasting effects in cognitive performance. An earlier meta-analysis from the literature revealed moderate intensity exercise has positive effects on acute cognitive performance including selective attention, planning, 125  organizing, multitasking, inhibition, and working memory [338]. These positive effects may be affected by the intensity and duration of exercise [338]. Maximal exercise has been studied minimally in comparison to lower intensity exercise (i.e., aerobic exercise). In a narrative review by Tomporowski [339] it was proposed that minor decrements in cognitive performance may occur with maximal exercise, although there were very few studies to draw conclusions from. The author further speculated that submaximal aerobic exercise leading to dehydration may be the most detrimental, as shown in tests examining information processing and memory. As shown in the heart rate response, the exercise protocol elicited near maximal heart rates and the protocol involved 30 minutes of strenuous work. However, participants were allowed to drink water ad libitum and experienced very little weight loss as a result of the exercise. Thus, it is possible that through the maintenance of hydration status, we mitigated this supposed negative influence on cognition. However, this only explains why our protocol may have avoided large decrements in performance. The more important question is how did this strenuous interval exercise and the other recent studies showing the benefits of intense exercise [330] [328] elicit improvements in cognitive function? One aspect to consider is fitness. Fitness level has been identified as a factor in the cognitive response to exercise, where higher cognitive function was found in those who exercised versus inactive individuals [316]. It has been speculated that the relative stress of the exercise will be different depending on how accustomed one is to such stress. Our participants were recreational exercisers with three individuals engaging in regular aerobic training for cycling and cross-country skiing. The range in VO2max verified that 126  this was a diverse group yet fitness was not correlated to any of our cognitive measures. This may suggest that cognitive benefits of physical activity are not limited to aerobic exercise [309]. Indeed in a cohort of elderly individuals, any history of physical activity was associated with better episodic memory and decreased likelihood of developing dementia [340]. Furthermore, the effects of a healthy lifestyle in already cognitively high functioning subjects cannot be overlooked as an additional factor [308]. Importantly we showed that working memory was improved following high-intensity interval exercise. We also showed a significant improvement in simple reaction time and choice reaction time. Our findings are in agreement with prior work involving intense exercise. In one investigation, two three-minute bouts of intense running improved retention in a verbal fluency task at one week post-exercise and this improved memory was associated with immediate post-exercise dopamine levels [330]. Another investigation reported improved working memory at 30 minutes post-aerobic exercise to exhaustion [328]. By contrast, Lemmink et al. found that following an eight-minute bout of interval exercise (40:20 second work:rest ratio) choice reaction time was no different from that of the control group who rested (seated) [341]. To our knowledge we are the first to investigate the time course of acute exercise on cognitive function so far into the controlled recovery period following intense exercise. Other work involving lower intensity exercise shows similar trends. Cognition in the form of speed and accuracy of mathematical problem solving was shown to remain heightened 15 minutes following sub-maximal exercise [342] and choice reaction time peaked at eight minutes postexercise after which the performance began to return to baseline [343]. Recently, an 127  investigation analyzing the lasting effects of sub-maximal exercise on response execution and response inhibition using a stop-signal task observed improved performances up to 52 minutes post-exercise [344]. Our findings of improved working memory evident four hours post-exercise is intriguing, particularly considering the CPAL duration was not yet close to returning to baseline. The investigation by Winter et al. [330] which reported enhanced retention at one week post-exercise, is limited by the potential effects of other influences on their participants during the week between assessments. Our work brings us closer to understanding if cognition may truly be enhanced when assessed at such lengths post-exercise. Taken together, our work and that of others, suggests that cognitive benefits of exercise could extend further than the day of exercise. Regular aerobic exercise increases endothelial function, reduces arterial stiffness, and increases arterial compliance [345-348]. These vascular adaptations benefit cerebral circulation as individuals with higher cardiorespiratory fitness exhibit higher brain blood flow [349], greater cerebral vascular conductance at rest, and greater cerebrovascular reserve [350]. Furthermore, vascular adaptations as the result of exercise may be involved in neurogenesis [351]. Dopamine is a modulator of sympatho-adrenal activity and serves as an important hormone involved in altering the inotrophic and chronotrophic response of the myocardium and vascular system to exercise [352]. It may also indirectly regulate blood pressure by increasing angiotensin II [353]. Given enhanced cognition is associated with lower blood pressure [354], dopamine is an important regulator of blood pressure [355] and recent findings linking higher dopamine levels with better retention of verbal fluency [330], dopamine was an appropriate target catecholamine for our research. Our 128  findings are in agreement with this prior work. First, we found a significant correlation between SBP and CPAL duration demonstrating that higher SBP was associated with longer time to complete the working memory task. Second, we found a trend of greater resting dopamine and higher large artery compliance, a measure of vascular health. With respect to the change in dopamine, we also found a trend for faster working memory in the presence of a greater increase in dopamine. Our investigation was adequately and highly powered to detect the cognitive, cardiovascular and catecholamine changes (average statistical power 0.976) however, future investigations involving more participants will help determine the nature of this relationship. 7.6 LIMITATIONS In this investigation we did not collect plasma samples during the recovery period. In this way our investigation is limited to associating post-exercise dopamine to cognition measured at different time points. However, catecholamines have a very short half-life (~ 2 minutes) and thus we expected detectable elevations to disappear by these later time periods. This is shown in other investigations involving a much shorter interval (i.e., 10 x 6s sprints or one 2-min sprint) where post-exercise plasma dopamine concentrations were not statistically different from baseline [323, 356]. Another consideration with respect to dopamine is that peripheral dopamine levels are not necessarily reflective of brain dopamine levels [357], thus conclusions should be drawn with caution. Finally, our investigation did not include serial assessments of cognition in the recovery phase. This was by design to avoid any confounding learning effects, although the CogState test battery has not displayed any learning effects after the second assessment in studies of 129  serial assessment [358, 359]. Our participants completed 3 baseline assessments of which we considered trial 3 to be our true baseline. Future investigations should include an immediate post-exercise time point to see if detriments in cogntition occurred which would strenthen the interpretation of cognition in recovery. In addition, a comparison of high-intensity interval exercise in comparison to other forms of exercise, and the inclusion of more women, would provide greater insight into the effects of strenuous exercise on cognitive function. 7.7 CONCLUSIONS In this investigation we showed that substantial improvements in reaction time and learning were evident following an intense bout of interval exercise. Additionally, we showed that the enhanced cognition persisted for a period of four hours. These results provide further support of the benefits of exercise. Future work should involve a more systematic exploration of the recovery period over multiple days to gain further insight into how the acute and chronic adaptations of exercise may impact cognition.  130  Chapter 8: General Summary and Conclusions 8.1 INTEGRATION AND INTERPRETATION OF MAJOR FINDINGS Research has demonstrated that strenuous forms of acute exercise have the ability to reduce ventricular function [123], particularly high volume exercise [161, 184]. Recent evidence suggests that cardiac fatigue is not limited to extreme duration but rather can be provoked with brief, but maximal exercise [21]. Our understanding of the implications of acute bouts of strenuous exercise on short term cardiovascular risk remains limited, particularly in athletes [189] and women [26]. In this dissertation, Chapter 2 provides a narrative review of the literature pertaining to effects of endurance training and sex on cardiovascular responses at rest and with exercise. The literature suggests that women demonstrate enhanced autonomic [62-66] and cardiac function [82] at rest, however with strenuous exercise, women may show greater vulnerabilities than men [66]. Similarly, athletes typically display an improved autonomic profile over untrained individuals [62, 89-93], structural adaptations (eccentric hypertrophy), and enhanced systolic and diastolic function [109, 110]. These adaptations increase the efficiency of the cardiovascular system to do more work under less stress [115-118]. However, while eccentric hypertrophy is seen as a normal adaptation to chronic endurance training, the similarity to hypertrophic cardiomyopathy or arrhythmogenic right ventricular dysplasia (linked to increased risk of sudden death in athletes) [111] questions the actual risks associated with strenuous exercise. Consequently, the series of studies contained in this dissertation examined the  131  cardiovascular consequences of strenuous exercise in healthy men and women, representing diverse physical training backgrounds. In Chapter 3, our investigation of ultra-marathoners provided unique findings pertaining to exercise-induced cardiac fatigue in women. Results show similar responses to an ultra-marathon between the sexes. Females have been rarely studied in previous work and we provide unique insight in to how women respond to strenuous exercise. From this work, an interesting novel finding was that more experienced ultra-marathoners presented less evidence of cardiac fatigue. The association with race pace and ventricular strain also demonstrates that the faster runners (and presumably the fittest) may experience less relative physiological strain. We provide for the first time an association of lifetime involvement in ultra-endurance training and cardiac fatigue which recently has come into question [165]. It is also unknown what impact cardiac fatigue has on performance. This work is limited in the echocardiographic measures collected and could have been strengthened by more advanced techniques of strain imaging [30]. The work presented in Chapter 4 addresses the effects of brief, strenuous exercise on cardiac function. Gaps in the cardiac fatigue literature have included insufficient exercise intensity, variability in protocols, and the need for more research using high-level female athletes [145]. Our work addressed these concerns by assessing both sexes, trained and untrained. In addition, we employed the same protocol as Scott et al. [21] so that our findings could be compared to this ground-breaking work. In support of this work, our findings revealed significant cardiac fatigue following high-intensity interval work. By contrast, endurance athletes did not experience greater cardiac fatigue than normally active individuals. Some novel aspects of this work include the assessment arterial132  ventricular coupling following high-intensity interval exercise. We found men displayed greater cardiac efficiency in the recovery from strenuous exercise, driven by higher arterial elastance. These findings would indicate a greater sensitivity to volume change [58]. Limitations of this study are the lack of exercise or follow up cardiac assessments. Currently, the use of echocardiography during exercise is limited and would not have been possible at the high intensities in our protocol. However, future work should include additional assessments in the recovery period, which may provide more insight into the manifestation of chronic adaptations [232]. To build upon our understanding of the response to very high intensity exercise, the investigation presented in Chapter 5 focused on autonomic responses to LBNP and highintensity interval exercise. We expected this protocol could highlight group differences not identified following exercise alone, as we have previously shown exercise and LBNP to represent a substantial stressor [272]. Indeed our findings did feature sex differences in autonomic and ventricular function. Under cumulative physiological stress, we discovered females experienced less disruption from baseline values compared with men. We also found evidence of greater reductions in baroreflex function in endurance-trained individuals. Insight into the post-exercise response is of particular interest as reduced cardiovagal baroreflex function is associated with impaired regulation of arterial blood pressure and in the presence of myocardial ischemia, with increased risk of ventricular tachyarrhythmias and sudden cardiac death [45]. While our work is not able to ascertain the full meaning of the post-exercise autonomic responses on cardiovascular risk, we can infer from the faster recovery in endurance trained individuals that this potential susceptibility occurs within a shorter timeframe than untrained individuals undergoing 133  strenuous exercise. A major limitation surrounding this work is the sample size is too small to assess the three-way interactions involving training and sex over lower body negative pressure and within condition (rest vs. exercise). Hence, improvements to this investigation would involve recruiting more participants for each group. Chapter 6 investigated the impact of training status and sex on post-exercise hypotension. The literature shows clearly the benefits of acute exercise on lowering blood pressure in hypertensives [288] but in healthy individuals, alterations to blood pressure are less clear. We used our 4 group model (training x sex) to assess post-exercise hypotension, which has yet to be explored with high-intensity interval exercise. Clinically, there is a lot of interest in understanding the risks versus benefits of highintensity interval exercise as it is being used increasingly in various rehabilitation programs [4, 17]. We found that healthy individuals experience significant blood pressure reductions following high intensity exercise, especially endurance trained athletes. Our work and others [295] demonstrates that post-exercise hypotension is apparent when utilizing very strenuous aerobic work, and perhaps intensity is responsible for the lack of hypotension in earlier work. We also found an association of baseline systolic blood pressure and the drop in post-exercise systolic blood pressure that has previously been shown in pre-hypertensives [297]. These researchers also showed greater autonomic alterations following high-intensity interval exercise compared with steady state exercise. Taken together with our findings, we have further evidence to support that high-intensity exercise has a significant acute effect on blood pressure. In endurance trained athletes however, it would appear that a more substantial stress need be applied in order to  134  recognize this acute response. This study was limited in not measuring plasma volume to show the degree of loss which occurred with this strenuous exercise. In Chapter 7 we present the findings of our final investigation. Here our aim was to explore cognitive performance following high intensity interval exercise. Known as an effective means to improve aerobic capacity [7, 9] we hypothesized that this form of exercise could improve cognitive performance as well. As in Chapter 6, we were attempting to establish a link between acute cardiovascular responses and enhanced cognitive function. Habitual exercisers have demonstrated improved cognition [338] into old age compared to those who do not exercise. Considering high-intensity interval exercise has been shown to improve metabolic parameters which lead to better health outcomes [15, 16], and compromised glucoregulation and cardiovascular health has been associated with an increased risk of developing cognitive impairment and Alzheimer disease [360], our work suggests that high-intensity interval exercise is an appropriate stimulus for affecting cardiovascular and cognitive improvements. Our association of systolic blood pressure to working memory duration, and our trends independently linking dopamine to vascular function and cognitive performance, are promising indications that the acute exercise response leading to fitness adaptations are also capable of influencing positively, cognitive function. This work could be improved by incorporating more physiological measures in the recovery period, such as measures of blood pressure regulation, arterial stiffness, brain blood flow and other blood markers (i.e., brain-derived neurotrophic factor). This would allow for better insight into the mechanisms of this adaptation. Further, the addition of other cognitive assessments  135  would be useful in confirming the impact of exercise on this aspect of human performance. 8.2 FUTURE STUDIES Interval Exercise: Collectively, this body of work comprehensively illustrates the effects of strenuous exercise in healthy humans. The exercise protocols used in this body of work consists of very high intensity exercise that is typical in training programs of elite athletes. However, interval exercise typically performed in recreational settings (i.e., spin classes), and in rehabilitation programs for those with chronic disease, offer very different forms of physical stress. While to the healthy person they represent a gradation of exercise intensity, to an individual with heart failure, assessing the degree of relative intensity becomes more complex. As such, future work should assess the cardiovascular impact of various forms of interval exercise performed by appropriate populations. In this way, we will gain a better understanding of the true efficacy of this type of exercise. Cognitive Performance: The integration of the cardiovascular responses to strenuous exercise and effects on cognition are an emerging area of research. In addition to addressing the limitations listed above, future work should investigate the progression of cardiovascular adaptations in conjunction with cognitive assessment, and over longer serial time points. Chronic Endurance Training: The structural adaptations present in endurance athletes remains of clinical concern [361, 362]. Longitudinal studies are needed in which cardiovascular adaptations to endurance training can be tracked. From this work,  136  researchers and clinicians may better understand the risks versus benefits from life-long endurance participation. Prolonged strenuous exercise: The impact of strenuous long duration exercise and its role in the development of cardiac fatigue has been a popular area of study in the last thirty years [19, 123]. However we remain limited in our understanding of training and sex effects. With greater numbers of older athletes participating each year, as well as more women [3, 18], further study in these populations are required. In summary, strenuous exercise has significant reductions in acute measures of cardiovascular function. Despite the benefits of chronic exercise, the risks of long-term participation, remains uncertain. As strenuous exercise increases in popularity, further work is warranted to ascertain the true costs versus benefits specific to various populations, so that individualized exercise recommendations may be specific and relevant.  137  References 1. 2. 3.  4. 5. 6.  7.  8. 9.  10.  11.  12.  13.  14.  15. 16.  Warburton, D.E., C.W. Nicol, and S.S. Bredin, Health benefits of physical activity: the evidence. CMAJ, 2006. 174(6): p. 801-9. Warburton, D.E., et al., A systematic review of the evidence for Canada's Physical Activity Guidelines for Adults. Int J Behav Nutr Phys Act, 2010. 7: p. 39. Knechtle, B., P. Knechtle, and R. Lepers, Participation and performance trends in ultra-triathlons from 1985 to 2009. Scand J Med Sci Sports, 2011. 21(6): p. e8290. Boutcher, S.H., High-intensity intermittent exercise and fat loss. J Obes, 2011. 2011: p. 868305. Tremblay, A., J.A. Simoneau, and C. Bouchard, Impact of exercise intensity on body fatness and skeletal muscle metabolism. Metabolism, 1994. 43(7): p. 814-8. Mourier, A., et al., Mobilization of visceral adipose tissue related to the improvement in insulin sensitivity in response to physical training in NIDDM. Effects of branched-chain amino acid supplements. Diabetes Care, 1997. 20(3): p. 385-91. Warburton, D.E., et al., Effectiveness of high-intensity interval training for the rehabilitation of patients with coronary artery disease. Am J Cardiol, 2005. 95(9): p. 1080-4. Helgerud, J., et al., Aerobic high-intensity intervals improve VO2max more than moderate training. Med Sci Sports Exerc, 2007. 39(4): p. 665-71. Talanian, J.L., et al., Two weeks of high-intensity aerobic interval training increases the capacity for fat oxidation during exercise in women. J Appl Physiol, 2007. 102(4): p. 1439-47. Burgomaster, K.A., et al., Similar metabolic adaptations during exercise after low volume sprint interval and traditional endurance training in humans. J Physiol, 2008. 586(1): p. 151-60. Perry, C.G., et al., High-intensity aerobic interval training increases fat and carbohydrate metabolic capacities in human skeletal muscle. Appl Physiol Nutr Metab, 2008. 33(6): p. 1112-23. Trapp, E.G., et al., The effects of high-intensity intermittent exercise training on fat loss and fasting insulin levels of young women. Int J Obes (Lond), 2008. 32(4): p. 684-91. Tjonna, A.E., et al., Aerobic interval training reduces cardiovascular risk factors more than a multitreatment approach in overweight adolescents. Clin Sci (Lond), 2009. 116(4): p. 317-26. Whyte, L.J., J.M. Gill, and A.J. Cathcart, Effect of 2 weeks of sprint interval training on health-related outcomes in sedentary overweight/obese men. Metabolism, 2010. 59(10): p. 1421-8. Gibala, M., Molecular responses to high-intensity interval exercise. Appl Physiol Nutr Metab, 2009. 34(3): p. 428-32. Gibala, M.J. and S.L. McGee, Metabolic adaptations to short-term high-intensity interval training: a little pain for a lot of gain? Exerc Sport Sci Rev, 2008. 36(2): p. 58-63. 138  17. 18. 19. 20.  21.  22. 23. 24.  25. 26.  27.  28. 29. 30.  31. 32.  33.  Kemi, O.J. and U. Wisloff, High-intensity aerobic exercise training improves the heart in health and disease. J Cardiopulm Rehabil Prev, 2010. 30(1): p. 2-11. Hoffman, M.D., Performance trends in 161-km ultramarathons. Int J Sports Med, 2010. 31(1): p. 31-7. Dawson, E., et al., Does the human heart fatigue subsequent to prolonged exercise? Sports Med, 2003. 33(5): p. 365-80. Middleton, N., et al., Novel application of flow propagation velocity and ischaemia-modified albumin in analysis of postexercise cardiac function in man. Exp Physiol, 2006. 91(3): p. 511-9. Scott, J.M., et al., Effects of high intensity exercise on biventricular function assessed by cardiac magnetic resonance imaging in endurance trained and normally active individuals. Am J Cardiol, 2010. 106(2): p. 278-83. Albert, C.M., et al., Triggering of sudden death from cardiac causes by vigorous exertion. N Engl J Med, 2000. 343(19): p. 1355-61. Virmani, R., et al., Causes of sudden death in young and middle-aged competitive athletes. Cardiol Clin, 1997. 15(3): p. 439-66. Goodman, J.M., S.G. Thomas, and J. Burr, Evidence-based risk assessment and recommendations for exercise testing and physical activity clearance in apparently healthy individuals (1) (1) This paper is one of a selection of papers published in this Special Issue, entitled Evidence-based risk assessment and recommendations for physical activity clearance, and has undergone the Journal's usual peer review process. Appl Physiol Nutr Metab, 2011. 36 Suppl 1: p. S14-32. Fagard, R., Athlete's heart. Heart, 2003. 89(12): p. 1455-61. Mosca, L., E. Barrett-Connor, and N.K. Wenger, Sex/gender differences in cardiovascular disease prevention: what a difference a decade makes. Circulation, 2011. 124(19): p. 2145-54. Nagueh, S.F., et al., Recommendations for the evaluation of left ventricular diastolic function by echocardiography. J Am Soc Echocardiogr, 2009. 22(2): p. 107-33. Starling, M.R., Left ventricular-arterial coupling relations in the normal human heart. Am Heart J, 1993. 125(6): p. 1659-66. Klabunde, R., Cardiovascular Physiological Concepts2011, Philadelphia, PA: Lippincott Williams & Wilkins. 241. George, K.P., et al., Diastolic function in healthy humans: non-invasive assessment and the impact of acute and chronic exercise. Eur J Appl Physiol, 2010. 108(1): p. 1-14. Hainsworth, R., Exercise training in orthostatic intolerance. QJM, 1998. 91(11): p. 715-7. Pumprla, J., et al., Functional assessment of heart rate variability: physiological basis and practical applications. International Journal of Cardiology, 2002. 84(1): p. 1-14. Aubert, A.E., B. Seps, and F. Beckers, Heart rate variability in athletes. Sports Med, 2003. 33(12): p. 889-919. 139  34. 35. 36.  37.  38.  39. 40. 41.  42.  43. 44.  45. 46.  47.  48. 49. 50.  Camm, A.J. and L. Fei, Chronotropic incompetence--Part I: Normal regulation of the heart rate. Clin Cardiol, 1996. 19(5): p. 424-8. Tsuji, H., et al., Determinants of heart rate variability. J Am Coll Cardiol, 1996. 28(6): p. 1539-46. Electrophysiology, T.F.o.t.E.S.o.C.a.t.N.A.S.o.P.a., Heart Rate Variability: Standards of Measurement, Physiological Interpretation, and Clinical Use. Circulation, 1996. 93(5): p. 1043-1065. Malliani, A. and M. Pagani, Spectral analysis of cardiovascular variabilities in the assessment of sympathetic cardiac regulation in heart failure. Pharmacol Res, 1991. 24 Suppl 1: p. 43-53. La Rovere, M.T., G.D. Pinna, and G. Raczak, Baroreflex sensitivity: measurement and clinical implications. Ann Noninvasive Electrocardiol, 2008. 13(2): p. 191207. Eckberg, D.L., et al., Reproducibility of human vagal carotid baroreceptorcardiac reflex responses. Am J Physiol, 1992. 263(1 Pt 2): p. R215-20. Kirchheim, H.R., Systemic arterial baroreceptor reflexes. Physiol Rev, 1976. 56(1): p. 100-77. Abboud, S., et al., Non-invasive recording of late ventricular activity using an advanced method in patients with a damaged mass of ventricular tissue. J Electrocardiol, 1983. 16(3): p. 245-51. Lanfranchi, P.A. and V.K. Somers, Arterial baroreflex function and cardiovascular variability: interactions and implications. Am J Physiol Regul Integr Comp Physiol, 2002. 283(4): p. R815-26. Monahan, K.D., Effect of aging on baroreflex function in humans. Am J Physiol Regul Integr Comp Physiol, 2007. 293(1): p. R3-R12. Billman, G.E. and M. Kukielka, Effects of endurance exercise training on heart rate variability and susceptibility to sudden cardiac death: protection is not due to enhanced cardiac vagal regulation. J Appl Physiol, 2006. 100(3): p. 896-906. Billman, G.E., P.J. Schwartz, and H.L. Stone, Baroreceptor reflex control of heart rate: a predictor of sudden cardiac death. Circulation, 1982. 66(4): p. 874-80. Monahan, K.D., et al., Age-associated changes in cardiovagal baroreflex sensitivity are related to central arterial compliance. Am J Physiol Heart Circ Physiol, 2001. 281(1): p. H284-9. Longo, M.R., A.W. Guzman, and J.H. Triebwasser, Normal values and commonly used echocardiographic formulae for adults. Aviat Space Environ Med, 1975. 46(8): p. 1062-4. Khouri, S.J., et al., A practical approach to the echocardiographic evaluation of diastolic function. J Am Soc Echocardiogr, 2004. 17(3): p. 290-7. Lim, M.J. and A.J. Buda, Doppler echocardiography in the evaluation of left ventricular diastolic function. Curr Opin Cardiol, 1991. 6(6): p. 937-45. Ommen, S.R. and R.A. Nishimura, A clinical approach to the assessment of left ventricular diastolic function by Doppler echocardiography: update 2003. Heart, 2003. 89 Suppl 3: p. iii18-23.  140  51.  52.  53.  54. 55.  56. 57. 58.  59. 60. 61.  62. 63. 64. 65.  66.  67.  Border, W.L., et al., Color M-mode and Doppler tissue evaluation of diastolic function in children: simultaneous correlation with invasive indices. J Am Soc Echocardiogr, 2003. 16(9): p. 988-94. Burgess, M.I., et al., Diastolic stress echocardiography: hemodynamic validation and clinical significance of estimation of ventricular filling pressure with exercise. J Am Coll Cardiol, 2006. 47(9): p. 1891-900. Stoylen, A., U. Wisloff, and S. Slordahl, Left ventricular mechanics during exercise: a Doppler and tissue Doppler study. Eur J Echocardiogr, 2003. 4(4): p. 286-91. Marwick, T.H., Measurement of strain and strain rate by echocardiography: ready for prime time? J Am Coll Cardiol, 2006. 47(7): p. 1313-27. Helle-Valle, T., et al., New noninvasive method for assessment of left ventricular rotation: speckle tracking echocardiography. Circulation, 2005. 112(20): p. 314956. Burns, A.T., et al., Doin' the twist: new tools for an old concept of myocardial function. Heart, 2008. 94(8): p. 978-83. Phillips, A.A., et al., Heart Disease and Left Ventricular Rotation - A Systematic Review and Quantitative Summary. BMC Cardiovasc Disord, 2012. 12(1): p. 46. Chantler, P.D., E.G. Lakatta, and S.S. Najjar, Arterial-ventricular coupling: mechanistic insights into cardiovascular performance at rest and during exercise. J Appl Physiol, 2008. 105(4): p. 1342-51. Najjar, S.S., et al., Age and gender affect ventricular-vascular coupling during aerobic exercise. J Am Coll Cardiol, 2004. 44(3): p. 611-7. Barron, H.V. and M.D. Lesh, Autonomic nervous system and sudden cardiac death. J Am Coll Cardiol, 1996. 27(5): p. 1053-60. Farrell, T.G., et al., Risk stratification for arrhythmic events in postinfarction patients based on heart rate variability, ambulatory electrocardiographic variables and the signal-averaged electrocardiogram. J Am Coll Cardiol, 1991. 18(3): p. 687-97. Gregoire, J., et al., Heart rate variability at rest and exercise: influence of age, gender, and physical training. Can J Appl Physiol, 1996. 21(6): p. 455-70. Yamasaki, Y., et al., Diurnal heart rate variability in healthy subjects: effects of aging and sex difference. Am J Physiol, 1996. 271(1 Pt 2): p. H303-10. Ryan, S.M., et al., Gender- and age-related differences in heart rate dynamics: are women more complex than men? J Am Coll Cardiol, 1994. 24(7): p. 1700-7. Ramaekers, D., et al., Heart rate variability and heart rate in healthy volunteers. Is the female autonomic nervous system cardioprotective? Eur Heart J, 1998. 19(9): p. 1334-41. Mendonca, G.V., et al., Sex differences in linear and nonlinear heart rate variability during early recovery from supramaximal exercise. Appl Physiol Nutr Metab, 2010. 35(4): p. 439-46. Kuo, T.B., et al., Effect of aging on gender differences in neural control of heart rate. Am J Physiol, 1999. 277(6 Pt 2): p. H2233-9.  141  68.  69. 70. 71. 72.  73. 74. 75. 76. 77. 78.  79.  80. 81.  82.  83. 84.  85.  Dart, A.M., X.J. Du, and B.A. Kingwell, Gender, sex hormones and autonomic nervous control of the cardiovascular system. Cardiovasc Res, 2002. 53(3): p. 678-87. Luzier, A.B., et al., The effects of gender on adrenergic receptor responsiveness. J Clin Pharmacol, 1998. 38(7): p. 618-24. Tank, J., et al., Reference values of indices of spontaneous baroreceptor reflex sensitivity. Am J Hypertens, 2000. 13(3): p. 268-75. Ylitalo, A., et al., Baroreflex sensitivity and variants of the renin angiotensin system genes. J Am Coll Cardiol, 2000. 35(1): p. 194-200. Abdel-Rahman, A.R., R.H. Merrill, and W.R. Wooles, Gender-related differences in the baroreceptor reflex control of heart rate in normotensive humans. J Appl Physiol, 1994. 77(2): p. 606-13. Convertino, V.A., Gender differences in autonomic functions associated with blood pressure regulation. Am J Physiol, 1998. 275(6 Pt 2): p. R1909-20. Huikuri, H.V., et al., Sex-related differences in autonomic modulation of heart rate in middle-aged subjects. Circulation, 1996. 94(2): p. 122-5. Laitinen, T., et al., Age and gender dependency of baroreflex sensitivity in healthy subjects. J Appl Physiol, 1998. 84(2): p. 576-83. Beske, S.D., et al., Gender difference in cardiovagal baroreflex gain in humans. J Appl Physiol, 2001. 91(5): p. 2088-92. Minson, C.T., et al., Sympathetic activity and baroreflex sensitivity in young women taking oral contraceptives. Circulation, 2000. 102(13): p. 1473-6. Minson, C.T., et al., Influence of the menstrual cycle on sympathetic activity, baroreflex sensitivity, and vascular transduction in young women. Circulation, 2000. 101(8): p. 862-8. Bonyhay, I., G. Jokkel, and M. Kollai, Relation between baroreflex sensitivity and carotid artery elasticity in healthy humans. Am J Physiol, 1996. 271(3 Pt 2): p. H1139-44. Schvartzman, P.R., et al., Normal values of echocardiographic measurements. A population-based study. Arq Bras Cardiol, 2000. 75(2): p. 107-14. Cain, P.A., et al., Age and gender specific normal values of left ventricular mass, volume and function for gradient echo magnetic resonance imaging: a cross sectional study. BMC Med Imaging, 2009. 9: p. 2. Chung, A.K., et al., Women have higher left ventricular ejection fractions than men independent of differences in left ventricular volume: the Dallas Heart Study. Circulation, 2006. 113(12): p. 1597-604. Foll, D., et al., Magnetic resonance tissue phase mapping of myocardial motion: new insight in age and gender. Circ Cardiovasc Imaging, 2010. 3(1): p. 54-64. Okura, H., et al., Age- and gender-specific changes in the left ventricular relaxation: a Doppler echocardiographic study in healthy individuals. Circ Cardiovasc Imaging, 2009. 2(1): p. 41-6. Sudhir, K., et al., Mechanisms of estrogen-induced vasodilation: in vivo studies in canine coronary conductance and resistance arteries. J Am Coll Cardiol, 1995. 26(3): p. 807-14. 142  86.  87. 88. 89. 90. 91. 92. 93.  94. 95. 96. 97.  98. 99. 100. 101. 102.  103.  104. 105.  Rossouw, J.E., et al., Postmenopausal hormone therapy and risk of cardiovascular disease by age and years since menopause. JAMA, 2007. 297(13): p. 1465-77. Farquhar, C.M., et al., Long term hormone therapy for perimenopausal and postmenopausal women. Cochrane Database Syst Rev, 2005(3): p. CD004143. Sun, J.P., et al., Effect of age and gender on left ventricular rotation and twist in a large group of normal adults - A multicenter study. Int J Cardiol, 2012. Goldsmith, R.L., D.M. Bloomfield, and E.T. Rosenwinkel, Exercise and autonomic function. Coron Artery Dis, 2000. 11(2): p. 129-35. Shi, X., et al., Autonomic nervous system control of the heart: endurance exercise training. Med Sci Sports Exerc, 1995. 27(10): p. 1406-13. Shin, K., et al., The power spectral analysis of heart rate variability in athletes during dynamic exercise--Part II. Clin Cardiol, 1995. 18(11): p. 664-8. Smith, M.L., et al., Exercise training bradycardia: the role of autonomic balance. Med Sci Sports Exerc, 1989. 21(1): p. 40-4. Carter, J.B., E.W. Banister, and A.P. Blaber, The effect of age and gender on heart rate variability after endurance training. Med Sci Sports Exerc, 2003. 35(8): p. 1333-40. Blomqvist, C.G. and B. Saltin, Cardiovascular adaptations to physical training. Annu Rev Physiol, 1983. 45: p. 169-89. Dixon, E.M., et al., Neural regulation of heart rate variability in endurance athletes and sedentary controls. Cardiovasc Res, 1992. 26(7): p. 713-9. Reardon, M. and M. Malik, Changes in heart rate variability with age. Pacing Clin Electrophysiol, 1996. 19(11 Pt 2): p. 1863-6. Tasaki, H., et al., A 15-year longitudinal follow-up study of heart rate and heart rate variability in healthy elderly persons. J Gerontol A Biol Sci Med Sci, 2000. 55(12): p. M744-9. Muster, A.J., et al., Cardiopulmonary and Cardiovascular Physiology in Elderly Competitive Endurance Athletes. Am J Geriatr Cardiol, 1999. 8(4): p. 162-168. Yataco, A.R., L.A. Fleisher, and L.I. Katzel, Heart rate variability and cardiovascular fitness in senior athletes. Am J Cardiol, 1997. 80(10): p. 1389-91. Eckberg, D.L. and J.M. Fritsch, Human autonomic responses to actual and simulated weightlessness. J Clin Pharmacol, 1991. 31(10): p. 951-5. Cooke, W.H., et al., Autonomic compensation to simulated hemorrhage monitored with heart period variability. Crit Care Med, 2008. 36(6): p. 1892-9. Kaikkonen, P., H. Rusko, and K. Martinmaki, Post-exercise heart rate variability of endurance athletes after different high-intensity exercise interventions. Scand J Med Sci Sports, 2008. 18(4): p. 511-9. Martinmaki, K. and H. Rusko, Time-frequency analysis of heart rate variability during immediate recovery from low and high intensity exercise. Eur J Appl Physiol, 2008. 102(3): p. 353-60. Cole, C.R., et al., Heart-rate recovery immediately after exercise as a predictor of mortality. N Engl J Med, 1999. 341(18): p. 1351-7. Kuipers, H. and H.A. Keizer, Overtraining in elite athletes. Review and directions for the future. Sports Med, 1988. 6(2): p. 79-92. 143  106.  107.  108.  109. 110.  111.  112. 113. 114. 115. 116.  117.  118.  119.  120.  121. 122.  Baumert, M., et al., Heart rate variability, blood pressure variability, and baroreflex sensitivity in overtrained athletes. Clin J Sport Med, 2006. 16(5): p. 412-7. Vesterinen, V., et al., Heart rate variability in prediction of individual adaptation to endurance training in recreational endurance runners. Scand J Med Sci Sports, 2011. Maron, B.J. and A. Pelliccia, The heart of trained athletes: cardiac remodeling and the risks of sports, including sudden death. Circulation, 2006. 114(15): p. 1633-44. D'Andrea, A., et al., Biventricular myocardial adaptation to different training protocols in competitive master athletes. Int J Cardiol, 2007. 115(3): p. 342-9. Spence, A.L., et al., A prospective randomised longitudinal MRI study of left ventricular adaptation to endurance and resistance exercise training in humans. J Physiol, 2011. 589(Pt 22): p. 5443-52. Caso, P., et al., The athlete's heart and hypertrophic cardiomyopathy: two conditions which may be misdiagnosed and coexistent. Which parameters should be analysed to distinguish one disease from the other? J Cardiovasc Med (Hagerstown), 2006. 7(4): p. 257-66. Pluim, B.M., et al., The athlete's heart. A meta-analysis of cardiac structure and function. Circulation, 2000. 101(3): p. 336-44. Barbier, J., et al., Sports-specific features of athlete's heart and their relation to echocardiographic parameters. Herz, 2006. 31(6): p. 531-43. Jones, A.M. and H. Carter, The effect of endurance training on parameters of aerobic fitness. Sports Med, 2000. 29(6): p. 373-86. Green, D.J., et al., Exercise and vascular adaptation in asymptomatic humans. Exp Physiol, 2011. 96(2): p. 57-70. Vendelin, M., et al., Optimizing ventricular fibers: uniform strain or stress, but not ATP consumption, leads to high efficiency. Am J Physiol Heart Circ Physiol, 2002. 283(3): p. H1072-81. Nottin, S., et al., Alteration in left ventricular normal and shear strains evaluated by 2D-strain echocardiography in the athlete's heart. J Physiol, 2008. 586(Pt 19): p. 4721-33. Zocalo, Y., et al., Assessment of training-dependent changes in the left ventricle torsion dynamics of professional soccer players using speckle-tracking echocardiography. Conf Proc IEEE Eng Med Biol Soc, 2007. 2007: p. 2709-12. Notomi, Y., et al., Enhanced ventricular untwisting during exercise: a mechanistic manifestation of elastic recoil described by Doppler tissue imaging. Circulation, 2006. 113(21): p. 2524-33. Esch, B.T. and D.E. Warburton, Left ventricular torsion and recoil: implications for exercise performance and cardiovascular disease. J Appl Physiol, 2009. 106(2): p. 362-9. Starnes, J.W. and D.K. Bowles, Role of exercise in the cause and prevention of cardiac dysfunction. Exerc Sport Sci Rev, 1995. 23: p. 349-73. Apstein, C.S. and F.R. Eberli, Diastolic function and dysfunction with exercise, hypertrophy, ischemia, and heart failure. Cardiologia, 1998. 43(12): p. 1269-79. 144  123. 124. 125. 126.  127. 128.  129.  130. 131. 132. 133. 134. 135. 136. 137. 138. 139.  140.  Middleton, N., et al., Left ventricular function immediately following prolonged exercise: A meta-analysis. Med Sci Sports Exerc, 2006. 38(4): p. 681-7. Collinson, P.O. and L. Chamberlain, Cardiac markers in the diagnosis of acute coronary syndromes. Curr Cardiol Rep, 2001. 3(4): p. 280-8. Bonetti, A., et al., Serum cardiac troponin T after repeated endurance exercise events. Int J Sports Med, 1996. 17(4): p. 259-62. Cummins, P., et al., Comparison of serum cardiac specific troponin-I with creatine kinase, creatine kinase-MB isoenzyme, tropomyosin, myoglobin and Creactive protein release in marathon runners: cardiac or skeletal muscle trauma? Eur J Clin Invest, 1987. 17(4): p. 317-24. Lucia, A., et al., Short-term effects of marathon running: no evidence of cardiac dysfunction. Med Sci Sports Exerc, 1999. 31(10): p. 1414-21. Davila-Roman, V.G., et al., Transient right but not left ventricular dysfunction after strenuous exercise at high altitude. J Am Coll Cardiol, 1997. 30(2): p. 46873. Rifai, N., et al., Cardiac troponin T and I, echocardiographic [correction of electrocardiographic] wall motion analyses, and ejection fractions in athletes participating in the Hawaii Ironman Triathlon. Am J Cardiol, 1999. 83(7): p. 1085-9. Denvir, M.A., et al., Changes in skeletal and cardiac muscle enzymes during the Scottish Coast to Coast Triathlon. Scott Med J, 1999. 44(2): p. 49-51. Siegel, A.J., et al., Changes in cardiac markers including B-natriuretic peptide in runners after the Boston marathon. Am J Cardiol, 2001. 88(8): p. 920-3. Neumayr, G., et al., Plasma levels of cardiac troponin I after prolonged strenuous endurance exercise. Am J Cardiol, 2001. 87(3): p. 369-71, A10. Neumayr, G., et al., Effect of the "Race Across The Alps" in elite cyclists on plasma cardiac troponins I and T. Am J Cardiol, 2002. 89(4): p. 484-6. Shave, R., et al., Cardiac troponin I is released following high-intensity shortduration exercise in healthy humans. Int J Cardiol, 2010. 145(2): p. 337-9. Shave, R., et al., Exercise-induced cardiac troponin T release: a meta-analysis. Med Sci Sports Exerc, 2007. 39(12): p. 2099-106. Shave, R., et al., Exercise-induced cardiac troponin elevation: evidence, mechanisms, and implications. J Am Coll Cardiol, 2010. 56(3): p. 169-76. Eysmann, S.B., et al., Prolonged exercise alters beta-adrenergic responsiveness in healthy sedentary humans. J Appl Physiol, 1996. 80(2): p. 616-22. Hart, E., et al., Beta-adrenergic receptor desensitization in man: insight into postexercise attenuation of cardiac function. J Physiol, 2006. 577(Pt 2): p. 717-25. Scott, J.M., et al., Sex differences in left ventricular function and beta-receptor responsiveness following prolonged strenuous exercise. J Appl Physiol, 2007. 102(2): p. 681-7. Welsh, R.C., et al., Prolonged strenuous exercise alters the cardiovascular response to dobutamine stimulation in male athletes. J Physiol, 2005. 569(Pt 1): p. 325-30.  145  141.  142.  143.  144. 145. 146.  147.  148. 149. 150.  151. 152. 153.  154. 155. 156.  157. 158.  Banks, L., et al., Impaired left and right ventricular function following prolonged exercise in young athletes: influence of exercise intensity and responses to dobutamine stress. J Appl Physiol, 2010. 108(1): p. 112-9. Euteneuer, F., et al., Association of in vivo beta-adrenergic receptor sensitivity with inflammatory markers in healthy subjects. Psychosom Med, 2012. 74(3): p. 271-7. Wachter, S.B. and E.M. Gilbert, Beta-Adrenergic Receptors, from Their Discovery and Characterization through Their Manipulation to Beneficial Clinical Application. Cardiology, 2012. 122(2): p. 104-12. Lefkowitz, R.J., H.A. Rockman, and W.J. Koch, Catecholamines, cardiac betaadrenergic receptors, and heart failure. Circulation, 2000. 101(14): p. 1634-7. Zouhal, H., et al., Catecholamines and the effects of exercise, training and gender. Sports Med, 2008. 38(5): p. 401-23. Werle, E.O., G. Strobel, and H. Weicker, Decrease in rat cardiac beta 1- and beta 2-adrenoceptors by training and endurance exercise. Life Sci, 1990. 46(1): p. 917. Vitiello, D., et al., beta-Adrenergic receptors desensitization is not involved in exercise-induced cardiac fatigue: NADPH oxidase-induced oxidative stress as a new trigger. J Appl Physiol, 2011. 111(5): p. 1242-8. Wood, M.J., NADPH oxidase: short-term foe, long-term friend. J Appl Physiol, 2011. 111(5): p. 1231-2. Kaneko, M., et al., Inhibition of heart sarcolemmal Ca(2+)-pump activity by oxygen free radicals. Bratisl Lek Listy, 1991. 92(1): p. 48-56. Miller, D.J. and N.G. MacFarlane, Intracellular effects of free radicals and reactive oxygen species in cardiac muscle. J Hum Hypertens, 1995. 9(6): p. 46573. Tsutsui, H., S. Kinugawa, and S. Matsushima, Mitochondrial oxidative stress and dysfunction in myocardial remodelling. Cardiovasc Res, 2009. 81(3): p. 449-56. Murdoch, C.E., et al., NADPH oxidase-dependent redox signalling in cardiac hypertrophy, remodelling and failure. Cardiovasc Res, 2006. 71(2): p. 208-15. Sanchez, G., et al., Exercise and tachycardia increase NADPH oxidase and ryanodine receptor-2 activity: possible role in cardioprotection. Cardiovasc Res, 2008. 77(2): p. 380-6. Seals, D.R., et al., Left ventricular dysfunction after prolonged strenuous exercise in healthy subjects. Am J Cardiol, 1988. 61(11): p. 875-9. McKechnie, J.K., et al., Acute pulmonary oedema in two athletes during a 90-km running race. S Afr Med J, 1979. 56(7): p. 261-5. Liedtke, A.J., S. Nellis, and J.R. Neely, Effects of excess free fatty acids on mechanical and metabolic function in normal and ischemic myocardium in swine. Circ Res, 1978. 43(4): p. 652-61. Niemela, K.O., et al., Evidence of impaired left ventricular performance after an uninterrupted competitive 24 hour run. Circulation, 1984. 70(3): p. 350-6. Nielsen, R., et al., Short term increase in free fatty acids and intracellular myocardial lipid content does not depress left ventricular performance in heart 146  159. 160.  161. 162.  163.  164. 165. 166.  167.  168.  169.  170. 171. 172.  173. 174.  failure patients with type 2 diabetes. Journal of the American College of Cardiology, 2012. 59(13): p. E1046. Douglas, P.S., et al., Cardiac fatigue after prolonged exercise. Circulation, 1987. 76(6): p. 1206-13. McGavock, J.M., et al., The effects of prolonged strenuous exercise on left ventricular function: a brief review. Heart Lung, 2002. 31(4): p. 279-92; quiz 293-4. Whyte, G.P., et al., Cardiac fatigue following prolonged endurance exercise of differing distances. Med Sci Sports Exerc, 2000. 32(6): p. 1067-72. Thompson, P.D., et al., Exercise and acute cardiovascular events placing the risks into perspective: a scientific statement from the American Heart Association Council on Nutrition, Physical Activity, and Metabolism and the Council on Clinical Cardiology. Circulation, 2007. 115(17): p. 2358-68. Scott, J.M. and D.E. Warburton, Mechanisms underpinning exercise-induced changes in left ventricular function. Med Sci Sports Exerc, 2008. 40(8): p. 14007. Oxborough, D., et al., "Exercise-induced cardiac fatigue"--a review of the echocardiographic literature. Echocardiography, 2010. 27(9): p. 1130-40. George, K., et al., Cardiac adaptation to acute and chronic participation in endurance sports. Heart, 2011. 97(24): p. 1999-2004. Hoffman, M.D., J.C. Ong, and G. Wang, Historical analysis of participation in 161 km ultramarathons in North America. Int J Hist Sport, 2010. 27(11): p. 187791. Ohba, H., et al., Effects of prolonged strenuous exercise on plasma levels of atrial natriuretic peptide and brain natriuretic peptide in healthy men. Am Heart J, 2001. 141(5): p. 751-8. Schroeder, C., et al., Phenotypical evidence for a gender difference in cardiac norepinephrine transporter function. Am J Physiol Regul Integr Comp Physiol, 2004. 286(5): p. R851-6. Shave, R., et al., A comparison of Doppler, tissue Doppler imaging, and strain rate imaging in the assessment of postexercise left ventricular function. Appl Physiol Nutr Metab, 2009. 34(1): p. 33-9. Mosteller, R.D., Simplified calculation of body-surface area. N Engl J Med, 1987. 317(17): p. 1098. Cote, A.T., et al., Predictors of orthostatic intolerance in healthy young women. Clin Invest Med, 2012. 35(2): p. E65-74. McVeigh, G.E., et al., Age-related abnormalities in arterial compliance identified by pressure pulse contour analysis: aging and arterial compliance. Hypertension, 1999. 33(6): p. 1392-8. Cohn, J.N., et al., Noninvasive pulse wave analysis for the early detection of vascular disease. Hypertension, 1995. 26(3): p. 503-8. Resnick, L.M., et al., Pulse waveform analysis of arterial compliance: relation to other techniques, age, and metabolic variables. Am J Hypertens, 2000. 13(12): p. 1243-9. 147  175.  176. 177.  178.  179. 180. 181.  182.  183.  184.  185. 186. 187. 188. 189. 190. 191.  Lang, R.M., et al., Recommendations for chamber quantification: a report from the American Society of Echocardiography's Guidelines and Standards Committee and the Chamber Quantification Writing Group, developed in conjunction with the European Association of Echocardiography, a branch of the European Society of Cardiology. J Am Soc Echocardiogr, 2005. 18(12): p. 144063. Scott, J.M., et al., Cardiovascular consequences of completing a 160-km ultramarathon. Med Sci Sports Exerc, 2009. 41(1): p. 26-34. Devereux, R.B., et al., Echocardiographic assessment of left ventricular hypertrophy: comparison to necropsy findings. Am J Cardiol, 1986. 57(6): p. 4508. Reichek, N., et al., Noninvasive determination of left ventricular end-systolic stress: validation of the method and initial application. Circulation, 1982. 65(1): p. 99-108. Niemela, K., et al., Impaired left ventricular diastolic function in athletes after utterly strenuous prolonged exercise. Int J Sports Med, 1987. 8(2): p. 61-5. La Gerche, A., et al., Biochemical and functional abnormalities of left and right ventricular function after ultra-endurance exercise. Heart, 2008. 94(7): p. 860-6. Nottin, S., et al., Alteration in left ventricular strains and torsional mechanics after ultralong duration exercise in athletes. Circ Cardiovasc Imaging, 2009. 2(4): p. 323-30. George, K., et al., Mitral annular myocardial velocity assessment of segmental left ventricular diastolic function after prolonged exercise in humans. J Physiol, 2005. 569(Pt 1): p. 305-13. Nichols, W.W. and M.F. O'Rourke, McDonald's Blood Flow in Arteries: Theoretic, Experimental and Clincial Principles. 5th ed. ed2005, Philadelphia, PA.: Hodder Arnold. Shave, R.E., et al., Evidence of exercise-induced cardiac dysfunction and elevated cTnT in separate cohorts competing in an ultra-endurance mountain marathon race. Int J Sports Med, 2002. 23(7): p. 489-94. Crandall, C.G., et al., Effects of passive heating on central blood volume and ventricular dimensions in humans. J Physiol, 2008. 586(1): p. 293-301. Crandall, C.G. and J. Gonzalez-Alonso, Cardiovascular function in the heatstressed human. Acta Physiol (Oxf), 2010. 199(4): p. 407-23. Millet, G.Y., et al., Neuromuscular consequences of an extreme mountain ultramarathon. PLoS One, 2011. 6(2): p. e17059. Mattsson, C.M., et al., Late cardiovascular drift observable during ultraendurance exercise. Med Sci Sports Exerc, 2011. 43(7): p. 1162-8. Whyte, G.P., et al., Arrhythmias and the athlete: mechanisms and clinical significance. Eur Heart J, 2007. 28(11): p. 1399-401; author reply 1401. Heath, G.W., et al., A physiological comparison of young and older endurance athletes. J Appl Physiol, 1981. 51(3): p. 634-40. Sims, S.T., et al., Sodium loading aids fluid balance and reduces physiological strain of trained men exercising in the heat. Med Sci Sports Exerc, 2007. 39(1): p. 123-30. 148  192. 193.  194. 195.  196.  197.  198. 199. 200. 201. 202.  203. 204. 205. 206.  207.  208.  209.  Douglas, P.S., et al., Different effects of prolonged exercise on the right and left ventricles. J Am Coll Cardiol, 1990. 15(1): p. 64-9. Douglas, P.S., M.L. O'Toole, and J. Woolard, Regional wall motion abnormalities after prolonged exercise in the normal left ventricle. Circulation, 1990. 82(6): p. 2108-14. Neilan, T.G., et al., Myocardial adaptation to short-term high-intensity exercise in highly trained athletes. J Am Soc Echocardiogr, 2006. 19(10): p. 1280-5. Oxborough, D., et al., The impact of marathon running upon ventricular function as assessed by 2D, Doppler, and tissue-Doppler echocardiography. Echocardiography, 2006. 23(8): p. 635-41. Hassan, M.Y., et al., Preload maintenance protects against a depression in left ventricular systolic, but not diastolic, function immediately after ultraendurance exercise. Br J Sports Med, 2006. 40(6): p. 536-40; discussion 540. Tulloh, L., et al., Raised troponin T and echocardiographic abnormalities after prolonged strenuous exercise--the Australian Ironman Triathlon. Br J Sports Med, 2006. 40(7): p. 605-9. Vanoverschelde, J.L., et al., Prolonged exercise induces left ventricular dysfunction in healthy subjects. J Appl Physiol, 1991. 70(3): p. 1356-63. Gibala, M.J., et al., Physiological adaptations to low-volume, high-intensity interval training in health and disease. J Physiol, 2012. 590(Pt 5): p. 1077-84. Whyte, G.P., Clinical significance of cardiac damage and changes in function after exercise. Med Sci Sports Exerc, 2008. 40(8): p. 1416-23. Niewiadomski, W., et al., Suppression of heart rate variability after supramaximal exertion. Clin Physiol Funct Imaging, 2007. 27(5): p. 309-19. Mohlenkamp, S., et al., Running: the risk of coronary events : Prevalence and prognostic relevance of coronary atherosclerosis in marathon runners. Eur Heart J, 2008. 29(15): p. 1903-10. Trivax, J.E., et al., Acute cardiac effects of marathon running. J Appl Physiol, 2010. 108(5): p. 1148-53. Kjaer, M., et al., Increased epinephrine response and inaccurate glucoregulation in exercising athletes. J Appl Physiol, 1986. 61(5): p. 1693-700. Boone, J.B., Jr., et al., Plasma Met-enkephalin and catecholamine responses to intense exercise in humans. J Appl Physiol, 1992. 73(1): p. 388-92. Silverman, H.G. and R.S. Mazzeo, Hormonal responses to maximal and submaximal exercise in trained and untrained men of various ages. J Gerontol A Biol Sci Med Sci, 1996. 51(1): p. B30-7. Greiwe, J.S., et al., Norepinephrine response to exercise at the same relative intensity before and after endurance exercise training. J Appl Physiol, 1999. 86(2): p. 531-5. Friedmann, B. and W. Kindermann, Energy metabolism and regulatory hormones in women and men during endurance exercise. Eur J Appl Physiol Occup Physiol, 1989. 59(1-2): p. 1-9. Zouhal, H., et al., Adrenal medulla responsiveness to the sympathetic nervous activity in sprinters and untrained subjects during a supramaximal exercise. Int J Sports Med, 1998. 19(3): p. 172-6. 149  210. 211. 212. 213.  214.  215.  216. 217.  218. 219.  220. 221.  222. 223.  224.  225. 226.  Friedlander, A.L., et al., Effects of exercise intensity and training on lipid metabolism in young women. Am J Physiol, 1998. 275(5 Pt 1): p. E853-63. Jacob, C., et al., Training status (endurance or sprint) and catecholamine response to the Wingate-test in women. Int J Sports Med, 2002. 23(5): p. 342-7. Phillips, A.A., et al., Aortic Stiffness Increased in Spinal Cord Injury when Matched for Physical Activity. Med Sci Sports Exerc, 2012. Laurent, S., et al., Expert consensus document on arterial stiffness: methodological issues and clinical applications. Eur Heart J, 2006. 27(21): p. 2588-605. Notomi, Y., et al., Measurement of ventricular torsion by two-dimensional ultrasound speckle tracking imaging. J Am Coll Cardiol, 2005. 45(12): p. 203441. Oppliger, R.A., et al., Accuracy of urine specific gravity and osmolality as indicators of hydration status. Int J Sport Nutr Exerc Metab, 2005. 15(3): p. 23651. Armstrong, L.E., et al., Urinary indices of hydration status. Int J Sport Nutr, 1994. 4(3): p. 265-79. Shirreffs, S.M. and R.J. Maughan, Urine osmolality and conductivity as indices of hydration status in athletes in the heat. Med Sci Sports Exerc, 1998. 30(11): p. 1598-602. Sagiv, M., et al., Left ventricular contractility and function at peak aerobic and anaerobic exercises. Med Sci Sports Exerc, 2000. 32(7): p. 1197-201. duManoir, G.R., et al., The effect of high-intensity rowing and combined strength and endurance training on left ventricular systolic function and morphology. Int J Sports Med, 2007. 28(6): p. 488-94. Greenberg, N.L., et al., Doppler-derived myocardial systolic strain rate is a strong index of left ventricular contractility. Circulation, 2002. 105(1): p. 99-105. Urheim, S., et al., Myocardial strain by Doppler echocardiography. Validation of a new method to quantify regional myocardial function. Circulation, 2000. 102(10): p. 1158-64. Belz, G.G., Elastic properties and Windkessel function of the human aorta. Cardiovasc Drugs Ther, 1995. 9(1): p. 73-83. Hwang, J.W., et al., Impact of arterial stiffness on regional myocardial function assessed by speckle tracking echocardiography in patients with hypertension. J Cardiovasc Ultrasound, 2012. 20(2): p. 90-6. Stohr, E.J., et al., Left ventricular mechanics in humans with high aerobic fitness: adaptation independent of structural remodelling, arterial haemodynamics and heart rate. J Physiol, 2012. 590(Pt 9): p. 2107-19. Borlaug, B.A. and D.A. Kass, Ventricular-vascular interaction in heart failure. Heart Fail Clin, 2008. 4(1): p. 23-36. Otsuki, T., et al., Contribution of systemic arterial compliance and systemic vascular resistance to effective arterial elastance changes during exercise in humans. Acta Physiol (Oxf), 2006. 188(1): p. 15-20.  150  227.  228.  229.  230. 231.  232. 233.  234. 235. 236.  237. 238.  239.  240. 241.  242. 243.  Otsuki, T., et al., Systemic arterial compliance, systemic vascular resistance, and effective arterial elastance during exercise in endurance-trained men. Am J Physiol Regul Integr Comp Physiol, 2008. 295(1): p. R228-35. Senitko, A.N., N. Charkoudian, and J.R. Halliwill, Influence of endurance exercise training status and gender on postexercise hypotension. J Appl Physiol, 2002. 92(6): p. 2368-74. Frenneaux, M. and L. Williams, Ventricular-arterial and ventricular-ventricular interactions and their relevance to diastolic filling. Prog Cardiovasc Dis, 2007. 49(4): p. 252-62. Redfield, M.M., et al., Age- and gender-related ventricular-vascular stiffening: a community-based study. Circulation, 2005. 112(15): p. 2254-62. Mizuguchi, Y., et al., The functional role of longitudinal, circumferential, and radial myocardial deformation for regulating the early impairment of left ventricular contraction and relaxation in patients with cardiovascular risk factors: a study with two-dimensional strain imaging. J Am Soc Echocardiogr, 2008. 21(10): p. 1138-44. Goodman, J.M., et al., Left ventricular contractile function is preserved during prolonged exercise in middle-aged men. J Appl Physiol, 2009. 106(2): p. 494-9. Liao, D., et al., Cardiac autonomic function and incident coronary heart disease: a population-based case-cohort study. The ARIC Study. Atherosclerosis Risk in Communities Study. Am J Epidemiol, 1997. 145(8): p. 696-706. Tsuji, H., et al., Impact of reduced heart rate variability on risk for cardiac events. The Framingham Heart Study. Circulation, 1996. 94(11): p. 2850-5. Westerhof, B.E., et al., Time-domain cross-correlation baroreflex sensitivity: performance on the EUROBAVAR data set. J Hypertens, 2004. 22(7): p. 1371-80. Iellamo, F., et al., Effects of a residential exercise training on baroreflex sensitivity and heart rate variability in patients with coronary artery disease: A randomized, controlled study. Circulation, 2000. 102(21): p. 2588-92. Pardo, Y., et al., Exercise conditioning and heart rate variability: evidence of a threshold effect. Clin Cardiol, 2000. 23(8): p. 615-20. Hautala, A.J., et al., Physical activity and heart rate variability measured simultaneously during waking hours. Am J Physiol Heart Circ Physiol, 2010. 298(3): p. H874-80. Hautala, A.J., A.M. Kiviniemi, and M.P. Tulppo, Individual responses to aerobic exercise: the role of the autonomic nervous system. Neurosci Biobehav Rev, 2009. 33(2): p. 107-15. Niemela, T.H., et al., Recovery pattern of baroreflex sensitivity after exercise. Med Sci Sports Exerc, 2008. 40(5): p. 864-70. Smith, L.L., M. Kukielka, and G.E. Billman, Heart rate recovery after exercise: a predictor of ventricular fibrillation susceptibility after myocardial infarction. Am J Physiol Heart Circ Physiol, 2005. 288(4): p. H1763-9. Greiwe, J.S., et al., Effects of endurance exercise training on muscle glycogen accumulation in humans. J Appl Physiol, 1999. 87(1): p. 222-6. Piepoli, M., et al., Persistent peripheral vasodilation and sympathetic activity in hypotension after maximal exercise. J Appl Physiol, 1993. 75(4): p. 1807-14. 151  244.  245.  246.  247. 248.  249.  250. 251.  252. 253. 254.  255. 256. 257. 258. 259.  260.  261.  Carter, R., 3rd, D.E. Watenpaugh, and M.L. Smith, Gender differences in cardiovascular regulation during recovery from exercise. J Appl Physiol, 2001. 91(4): p. 1902-7. Esch, B.T., et al., Diastolic ventricular interactions in endurance-trained athletes during orthostatic stress. Am J Physiol Heart Circ Physiol, 2007. 293(1): p. H409-15. Fu, Q., et al., Effects of gender and hypovolemia on sympathetic neural responses to orthostatic stress. Am J Physiol Regul Integr Comp Physiol, 2005. 289(1): p. R109-16. Levine, B.D., et al., Physical fitness and cardiovascular regulation: mechanisms of orthostatic intolerance. J Appl Physiol, 1991. 70(1): p. 112-22. Fu, Q., et al., Evidence for unloading arterial baroreceptors during low levels of lower body negative pressure in humans. Am J Physiol Heart Circ Physiol, 2009. 296(2): p. H480-8. Cooke, W.H., et al., Muscle sympathetic nerve activity during intense lower body negative pressure to presyncope in humans. J Physiol, 2009. 587(Pt 20): p. 498799. Cooke, W.H., et al., Human responses to upright tilt: a window on central autonomic integration. J Physiol, 1999. 517 ( Pt 2): p. 617-28. Cooper, V.L. and R. Hainsworth, Effects of head-up tilting on baroreceptor control in subjects with different tolerances to orthostatic stress. Clin Sci (Lond), 2002. 103(3): p. 221-6. Raven, P.B., P.J. Fadel, and S. Ogoh, Arterial baroreflex resetting during exercise: a current perspective. Exp Physiol, 2006. 91(1): p. 37-49. Fadel, P.J., Arterial baroreflex control of the peripheral vasculature in humans: rest and exercise. Med Sci Sports Exerc, 2008. 40(12): p. 2055-62. Scott, J.M., et al., Post-exercise hypotension and cardiovascular responses to moderate orthostatic stress in endurance-trained males. Appl Physiol Nutr Metab, 2008. 33(2): p. 246-53. Williams, C.C. and D.T. Bernhardt, Syncope in athletes. Sports Med, 1995. 19(3): p. 223-34. Hagberg, J.M., et al., Faster adjustment to and recovery from submaximal exercise in the trained state. J Appl Physiol, 1980. 48(2): p. 218-24. Tulppo, M.P., et al., Effects of aerobic training on heart rate dynamics in sedentary subjects. J Appl Physiol, 2003. 95(1): p. 364-72. Yamamoto, K., et al., Effects of endurance training on resting and post-exercise cardiac autonomic control. Med Sci Sports Exerc, 2001. 33(9): p. 1496-502. Du, N., et al., Heart Rate Recovery After Exercise and Neural Regulation of Heart Rate Variability in 30-40 Year Old Female Marathon Runners. Journal of Sports Science and Medicine, 2005. 4: p. 9-17. Evans, J.M., et al., Gender differences in autonomic cardiovascular regulation: spectral, hormonal, and hemodynamic indexes. J Appl Physiol, 2001. 91(6): p. 2611-8. White, D.D., R.W. Gotshall, and A. Tucker, Women have lower tolerance to lower body negative pressure than men. J Appl Physiol, 1996. 80(4): p. 1138-43. 152  262.  263.  264.  265. 266.  267.  268.  269. 270.  271.  272.  273.  274. 275. 276. 277.  Raven, P.B. and J.A. Pawelczyk, Chronic endurance exercise training: a condition of inadequate blood pressure regulation and reduced tolerance to LBNP. Med Sci Sports Exerc, 1993. 25(6): p. 713-21. Levine, B.D., et al., Left ventricular pressure-volume and Frank-Starling relations in endurance athletes. Implications for orthostatic tolerance and exercise performance. Circulation, 1991. 84(3): p. 1016-23. Watenpaugh, D.E., et al., Lower body negative pressure exercise plus brief postexercise lower body negative pressure improve post-bed rest orthostatic tolerance. J Appl Physiol, 2007. 103(6): p. 1964-72. Harrison, M.H., Effects on thermal stress and exercise on blood volume in humans. Physiol Rev, 1985. 65(1): p. 149-209. Hautala, A.J., et al., Short-term correlation properties of R-R interval dynamics at different exercise intensity levels. Clin Physiol Funct Imaging, 2003. 23(4): p. 215-23. Winsley, R.J., G.L. Battersby, and H.C. Cockle, Heart rate variability assessment of overreaching in active and sedentary females. Int J Sports Med, 2005. 26(9): p. 768-73. Uusitalo, A.L., A.J. Uusitalo, and H.K. Rusko, Exhaustive endurance training for 6-9 weeks did not induce changes in intrinsic heart rate and cardiac autonomic modulation in female athletes. Int J Sports Med, 1998. 19(8): p. 532-40. Pagani, M., et al., Extracting autonomic information from oscillations in MSNA. J Physiol, 2012. 590(Pt 3): p. 647-8; author reply 649. Phillips, A.A., et al., Aortic distensibility is reduced during intense lower body negative pressure and is related to low frequency power of systolic blood pressure. Eur J Appl Physiol, 2012. Kimmerly, D.S., et al., Forebrain regions associated with postexercise differences in autonomic and cardiovascular function during baroreceptor unloading. Am J Physiol Heart Circ Physiol, 2007. 293(1): p. H299-306. Esch, B.T., et al., Changes in ventricular twist and untwisting with orthostatic stress: endurance athletes versus normally active individuals. J Appl Physiol, 2010. 108(5): p. 1259-66. Wray, D.W., et al., Acute sympathetic vasoconstriction at rest and during dynamic exercise in cyclists and sedentary humans. J Appl Physiol, 2007. 102(2): p. 704-12. Conboy, E.E., et al., Endurance training reduces renal vasoconstriction to orthostatic stress. Am J Physiol Renal Physiol, 2010. 298(2): p. F279-84. Fu, Q., S. Witkowski, and B.D. Levine, Vasoconstrictor reserve and sympathetic neural control of orthostasis. Circulation, 2004. 110(18): p. 2931-7. Ogoh, S., et al., Carotid baroreflex responsiveness to head-up tilt-induced central hypovolaemia: effect of aerobic fitness. J Physiol, 2003. 551(Pt 2): p. 601-8. Levine, B.D., Regulation of central blood volume and cardiac filling in endurance athletes: the Frank-Starling mechanism as a determinant of orthostatic tolerance. Med Sci Sports Exerc, 1993. 25(6): p. 727-32.  153  278.  279. 280.  281.  282.  283.  284.  285.  286. 287. 288. 289.  290. 291. 292.  293. 294.  Monahan, K.D., Letter to the editor: "does baroreflex unloading decrease limb venous compliance in women?". Am J Physiol Heart Circ Physiol, 2009. 296(2): p. H534; author reply H535. Sugawara, J., et al., Impact of chronic exercise training on the blood pressure response to orthostatic stimulation. J Appl Physiol, 2012. 112(11): p. 1891-6. Monahan, K.D., et al., Regular aerobic exercise modulates age-associated declines in cardiovagal baroreflex sensitivity in healthy men. J Physiol, 2000. 529 Pt 1: p. 263-71. Monahan, K.D., et al., Central arterial compliance is associated with age- and habitual exercise-related differences in cardiovagal baroreflex sensitivity. Circulation, 2001. 104(14): p. 1627-32. Billaud, M., S.R. Johnstone, and B.E. Isakson, Loss of compliance in small arteries, but not in conduit arteries, after 6 weeks exposure to high fat diet. J Cardiovasc Transl Res, 2012. 5(3): p. 256-63. Nissinen, S.I., et al., Heart rate recovery after exercise as a predictor of mortality among survivors of acute myocardial infarction. Am J Cardiol, 2003. 91(6): p. 711-4. Iellamo, F., et al., Conversion from vagal to sympathetic predominance with strenuous training in high-performance world class athletes. Circulation, 2002. 105(23): p. 2719-24. Middleton, N. and G. De Vito, Cardiovascular autonomic control in endurancetrained and sedentary young women. Clin Physiol Funct Imaging, 2005. 25(2): p. 83-9. MacDonald, J.R., Potential causes, mechanisms, and implications of post exercise hypotension. J Hum Hypertens, 2002. 16(4): p. 225-36. Kenney, M.J. and D.R. Seals, Postexercise hypotension. Key features, mechanisms, and clinical significance. Hypertension, 1993. 22(5): p. 653-64. Halliwill, J.R., Mechanisms and clinical implications of post-exercise hypotension in humans. Exerc Sport Sci Rev, 2001. 29(2): p. 65-70. Quinn, T.J., Twenty-four hour, ambulatory blood pressure responses following acute exercise: impact of exercise intensity. J Hum Hypertens, 2000. 14(9): p. 547-53. Pescatello, L.S., et al., Exercise intensity alters postexercise hypotension. J Hypertens, 2004. 22(10): p. 1881-8. Eicher, J.D., et al., The additive blood pressure lowering effects of exercise intensity on post-exercise hypotension. Am Heart J, 2010. 160(3): p. 513-20. Halliwill, J.R., J.A. Taylor, and D.L. Eckberg, Impaired sympathetic vascular regulation in humans after acute dynamic exercise. J Physiol, 1996. 495 ( Pt 1): p. 279-88. Halliwill, J.R., et al., Augmented baroreflex heart rate gain after moderateintensity, dynamic exercise. Am J Physiol, 1996. 270(2 Pt 2): p. R420-6. Dujic, Z., et al., Postexercise hypotension in moderately trained athletes after maximal exercise. Med Sci Sports Exerc, 2006. 38(2): p. 318-22.  154  295.  296.  297.  298. 299. 300.  301. 302.  303. 304.  305.  306. 307. 308. 309. 310. 311. 312.  Rossow, L., et al., Postexercise hypotension in an endurance-trained population of men and women following high-intensity interval and steady-state cycling. Am J Hypertens, 2010. 23(4): p. 358-67. Rakobowchuk, M., et al., Sprint interval and traditional endurance training induce similar improvements in peripheral arterial stiffness and flow-mediated dilation in healthy humans. Am J Physiol Regul Integr Comp Physiol, 2008. 295(1): p. R236-42. Lacombe, S.P., et al., Interval and continuous exercise elicit equivalent postexercise hypotension in prehypertensive men, despite differences in regulation. Appl Physiol Nutr Metab, 2011. 36(6): p. 881-91. Chen, C.Y. and A.C. Bonham, Postexercise hypotension: central mechanisms. Exerc Sport Sci Rev, 2010. 38(3): p. 122-7. Tank, J., et al., Baroreflex regulation of heart rate and sympathetic vasomotor tone in women and men. Hypertension, 2005. 45(6): p. 1159-64. Lindqvist, P., S. Morner, and M.Y. Henein, Cardiac mechanisms underlying normal exercise tolerance: gender impact. Eur J Appl Physiol, 2012. 112(2): p. 451-9. Ogawa, T., et al., Effects of aging, sex, and physical training on cardiovascular responses to exercise. Circulation, 1992. 86(2): p. 494-503. McCord, J.L. and J.R. Halliwill, H1 and H2 receptors mediate postexercise hyperemia in sedentary and endurance exercise-trained men and women. J Appl Physiol, 2006. 101(6): p. 1693-701. Collins, H.L. and S.E. DiCarlo, Attenuation of postexertional hypotension by cardiac afferent blockade. Am J Physiol, 1993. 265(4 Pt 2): p. H1179-83. Chandler, M.P. and S.E. DiCarlo, Sinoaortic denervation prevents postexercise reductions in arterial pressure and cardiac sympathetic tonus. Am J Physiol, 1997. 273(6 Pt 2): p. H2738-45. Rowell, L., D. O'Leary, and D. Kellogg Jr, Integration of cardiovascular control systems in dynamic exercise, in Handbook of Physiology. Exercise: Regulation and Integration of Multiple Systems, L. Rowell and J. Shepard, Editors. 1996, Oxford University Press: New York. p. 770-830. Pricher, M.P., et al., Regional hemodynamics during postexercise hypotension. I. Splanchnic and renal circulations. J Appl Physiol, 2004. 97(6): p. 2065-70. Arhem, P. and H. Liljenstrom, On the coevolution of cognition and consciousness. J Theor Biol, 1997. 187(4): p. 601-12. Abbott, R.D., et al., Walking and dementia in physically capable elderly men. JAMA, 2004. 292(12): p. 1447-53. Colcombe, S.J., et al., Neurocognitive aging and cardiovascular fitness: recent findings and future directions. J Mol Neurosci, 2004. 24(1): p. 9-14. Larson, E.B., et al., Brief cognitive assessment and prediction of functional outcome in stroke. Top Stroke Rehabil, 2003. 9(4): p. 10-21. van Gelder, B.M., et al., Physical activity in relation to cognitive decline in elderly men: the FINE Study. Neurology, 2004. 63(12): p. 2316-21. Weuve, J., et al., Physical activity, including walking, and cognitive function in older women. JAMA, 2004. 292(12): p. 1454-61. 155  313. 314. 315. 316.  317.  318. 319. 320. 321. 322. 323.  324.  325.  326.  327.  328. 329. 330. 331.  Laurin, D., et al., Physical activity and risk of cognitive impairment and dementia in elderly persons. Arch Neurol, 2001. 58(3): p. 498-504. Hillman, C.H., K.I. Erickson, and A.F. Kramer, Be smart, exercise your heart: exercise effects on brain and cognition. Nat Rev Neurosci, 2008. 9(1): p. 58-65. Dik, M.G., et al., Insulin-like growth factor I (IGF-I) and cognitive decline in older persons. Neurobiol Aging, 2003. 24(4): p. 573-81. Brown, A.D., et al., Effects of cardiorespiratory fitness and cerebral blood flow on cognitive outcomes in older women. Neurobiol Aging, 2010. 31(12): p. 204757. Cotman, C.W., N.C. Berchtold, and L.A. Christie, Exercise builds brain health: key roles of growth factor cascades and inflammation. Trends Neurosci, 2007. 30(9): p. 464-72. Fiorillo, C.D., The uncertain nature of dopamine. Mol Psychiatry, 2004. 9(2): p. 122-3. Floel, A., et al., Dopaminergic influences on formation of a motor memory. Ann Neurol, 2005. 58(1): p. 121-30. Floel, A., et al., Dopaminergic effects on encoding of a motor memory in chronic stroke. Neurology, 2005. 65(3): p. 472-4. Knecht, S., et al., Levodopa: faster and better word learning in normal humans. Ann Neurol, 2004. 56(1): p. 20-6. Ruscheweyh, R., et al., Physical activity and memory functions: an interventional study. Neurobiol Aging, 2011. 32(7): p. 1304-19. Bracken, R.M., D.M. Linnane, and S. Brooks, Plasma catecholamine and nephrine responses to brief intermittent maximal intensity exercise. Amino Acids, 2009. 36(2): p. 209-17. Strobel, G., E. Werle, and H. Weicker, Isomer specific kinetics of dopamine betahydroxylase and arylsulfatase towards catecholamine sulfates. Biochem Int, 1990. 20(2): p. 343-51. Farrell, P.A., T.L. Garthwaite, and A.B. Gustafson, Plasma adrenocorticotropin and cortisol responses to submaximal and exhaustive exercise. J Appl Physiol, 1983. 55(5): p. 1441-4. Yagi, Y., et al., Effects of aerobic exercise and gender on visual and auditory P300, reaction time, and accuracy. Eur J Appl Physiol Occup Physiol, 1999. 80(5): p. 402-8. Chmura, J., K. Nazar, and H. Kaciuba-Uscilko, Choice reaction time during graded exercise in relation to blood lactate and plasma catecholamine thresholds. Int J Sports Med, 1994. 15(4): p. 172-6. Lo Bue-Estes, C., et al., Short-term exercise to exhaustion and its effects on cognitive function in young women. Percept Mot Skills, 2008. 107(3): p. 933-45. Hillman, C.H., E.M. Snook, and G.J. Jerome, Acute cardiovascular exercise and executive control function. Int J Psychophysiol, 2003. 48(3): p. 307-14. Winter, B., et al., High impact running improves learning. Neurobiol Learn Mem, 2007. 87(4): p. 597-609. Esco, M.R., et al., The relationship between resting heart rate variability and heart rate recovery. Clin Auton Res, 2010. 20(1): p. 33-8. 156  332. 333. 334.  335.  336.  337. 338. 339. 340. 341. 342.  343. 344. 345. 346.  347. 348. 349. 350.  Darby, D., et al., Mild cognitive impairment can be detected by multiple assessments in a single day. Neurology, 2002. 59(7): p. 1042-6. Maruff, P., et al., Cognitive deterioration associated with an expedition in an extreme desert environment. Br J Sports Med, 2006. 40(6): p. 556-60. Mollica, C.M., P. Maruff, and A. Vance, Development of a statistical approach to classifying treatment response in individual children with ADHD. Hum Psychopharmacol, 2004. 19(7): p. 445-56. Silbert, B.S., et al., Detection of cognitive decline after coronary surgery: a comparison of computerized and conventional tests. Br J Anaesth, 2004. 92(6): p. 814-20. Snyder, P.J., et al., A method for determining the magnitude of change across different cognitive functions in clinical trials: the effects of acute administration of two different doses alprazolam. Hum Psychopharmacol, 2005. 20(4): p. 26373. Maruff, P. and M. Falleti, Cognitive function in growth hormone deficiency and growth hormone replacement. Horm Res, 2005. 64 Suppl 3: p. 100-8. Colcombe, S. and A.F. Kramer, Fitness effects on the cognitive function of older adults: a meta-analytic study. Psychol Sci, 2003. 14(2): p. 125-30. Tomporowski, P.D., Effects of acute bouts of exercise on cognition. Acta Psychol (Amst), 2003. 112(3): p. 297-324. Floel, A., et al., Lifestyle and memory in the elderly. Neuroepidemiology, 2008. 31(1): p. 39-47. Lemmink, K.A. and C. Visscher, Effect of intermittent exercise on multiple-choice reaction times of soccer players. Percept Mot Skills, 2005. 100(1): p. 85-95. Heckler, B. and R. Croce, Effects of time of posttest after two durations of exercise on speed and accuracy of addition and subtraction by fit and less-fit women. Percept Mot Skills, 1992. 75(3 Pt 2): p. 1059-65. Kashihara, K. and Y. Nakahara, Short-term effect of physical exercise at lactate threshold on choice reaction time. Percept Mot Skills, 2005. 100(2): p. 275-91. Joyce, J., et al., The time course effect of moderate intensity exercise on response execution and response inhibition. Brain Cogn, 2009. 71(1): p. 14-9. Green, D.J., et al., Effect of exercise training on endothelium-derived nitric oxide function in humans. J Physiol, 2004. 561(Pt 1): p. 1-25. Green, D.J., et al., Comparison of resistance and conduit vessel nitric oxidemediated vascular function in vivo: effects of exercise training. J Appl Physiol, 2004. 97(2): p. 749-55; discussion 748. Tanaka, H., et al., Aging, habitual exercise, and dynamic arterial compliance. Circulation, 2000. 102(11): p. 1270-5. Kingwell, B.A., Large artery stiffness: implications for exercise capacity and cardiovascular risk. Clin Exp Pharmacol Physiol, 2002. 29(3): p. 214-7. Ainslie, P.N., et al., Elevation in cerebral blood flow velocity with aerobic fitness throughout healthy human ageing. J Physiol, 2008. 586(16): p. 4005-10. Davenport, M.H., et al., Cerebrovascular reserve: the link between fitness and cognitive function? Exerc Sport Sci Rev, 2012. 40(3): p. 153-8. 157  351.  352. 353.  354. 355. 356. 357. 358.  359.  360. 361.  362.  Baker, S.A., K.A. Baker, and T. Hagg, Dopaminergic nigrostriatal projections regulate neural precursor proliferation in the adult mouse subventricular zone. Eur J Neurosci, 2004. 20(2): p. 575-9. Esler, M., et al., Overflow of catecholamine neurotransmitters to the circulation: source, fate, and functions. Physiol Rev, 1990. 70(4): p. 963-85. Jose, P.A., G.M. Eisner, and R.A. Felder, Role of dopamine receptors in the kidney in the regulation of blood pressure. Curr Opin Nephrol Hypertens, 2002. 11(1): p. 87-92. Knecht, S., et al., High-normal blood pressure is associated with poor cognitive performance. Hypertension, 2008. 51(3): p. 663-8. Jose, P.A., G.M. Eisner, and R.A. Felder, Regulation of blood pressure by dopamine receptors. Nephron Physiol, 2003. 95(2): p. p19-27. Bracken, R.M. and S. Brooks, Plasma catecholamine and nephrine responses following 7 weeks of sprint cycle training. Amino Acids, 2010. 38(5): p. 1351-9. Sutoo, D. and K. Akiyama, Regulation of brain function by exercise. Neurobiol Dis, 2003. 13(1): p. 1-14. Collie, A., et al., The effects of practice on the cognitive test performance of neurologically normal individuals assessed at brief test-retest intervals. J Int Neuropsychol Soc, 2003. 9(3): p. 419-28. Falleti, M.G., et al., Practice effects associated with the repeated assessment of cognitive function using the CogState battery at 10-minute, one week and one month test-retest intervals. J Clin Exp Neuropsychol, 2006. 28(7): p. 1095-112. Helzner, E.P., et al., Contribution of vascular risk factors to the progression in Alzheimer disease. Arch Neurol, 2009. 66(3): p. 343-8. La Gerche, A., et al., Exercise strain rate imaging demonstrates normal right ventricular contractile reserve and clarifies ambiguous resting measures in endurance athletes. J Am Soc Echocardiogr, 2012. 25(3): p. 253-262 e1. La Gerche, A., et al., Exercise-induced right ventricular dysfunction and structural remodelling in endurance athletes. Eur Heart J, 2012. 33(8): p. 9981006.  158  Appendices  159  A: PHYSICAL ACTIVITY READINESS QUESTIONNAIRE FOR EVERYONE (PARQ+)  160  161  162  163  B: FAT DOG 100 ULTRA-MARATHON QUESTIONNAIRE  164  165  C: SCHEMATIC OF PROTOCOLS  Protocol Chapter 5  Protocol Chapter 7  166  

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