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Effects of arterial blood gas concentrations on regional cerebral blood flow and metabolism during exercise Smith, Kurt Jason 2015

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 Effects of arterial blood gas concentrations on regional cerebral blood flow and metabolism during exercise  By Kurt Jason Smith MSc, The University of Lethbridge, 2010   A THESIS SUBMITTED IN PARTIAL FULFILLMENT OF THE REQUIREMENTS FOR THE DEGREE OF   DOCTOR OF PHILOSOPHY   in   THE COLLEGE OF GRADUATE STUDIES  (Interdisciplinary Studies)     THE UNIVERSITY OF BRITISH COLUMBIA  (Okanagan)   August 2015     © Kurt Jason Smith, 2015  ii Abstract  The magnitude of the cerebral blood flow (CBF) response to exercise is primarily related to the sensitive balance between arterial blood gases (partial pressure of arterial oxygen [PaO2] and carbon dioxide [PaCO2]) and cerebral metabolism. However, it has remained unclear whether experimentally or environmentally manipulating the oxygen tensions alters the regulatory influence of arterial blood gases on the intracranial velocities (CBV) and regional CBF responses to incremental exercise. The goal of the experimental chapters of this thesis (Chapter 4, 5 and 6) was to quantify the independent and combined influence of PaO2 and PaCO2 on global and regional CBV and CBF during exercise.  Chapter 4 identified a heightened (nearly twice the expected response) posterior CBV response during hyperoxic (PO2 ∼713 mmHg) compared to normoxic (PO2 ∼160 mmHg) exercise. In contrast, both the anterior and posterior CBV responses were unaltered during mild hypoxic (PO2 ∼121 mmHg) exercise compared to normoxic exercise. Chapter 5 demonstrated that during exercise in severe hypoxia (PO2 ∼413 mmHg), following partial acclimatization to high altitude (5050 m), global CBF was elevated by ∼20% compared to sea-level exercise.  The elevated global CBF during exercise at high altitude served to compensate for the hypoxemia, and in turn maintained cerebral oxygen delivery equivalent to sea-level values. Chapter 6 revisited and extended the observations during hyperoxic exercise from Chapter 4, whereby measures of extra-cranial CBF were compared with the intracranial velocities during normoxic and hyperoxic (PO2 ∼300 mmHg) exercise, and also in a separate condition in which any exercise-induced rise in PaCO2 was prevented (i.e., isocapnia was maintained). The differences observed between   iii regional CBV and CBF during normoxic and hyperoxic incremental exercise trials were abolished when PaCO2 was held constant. This final chapter also demonstrated that the increased ventilation, per se, is unlikely to influence the cerebrovascular response to exercise. In conclusion, changes in arterial blood gases (hypoxia and hyperoxia) can exacerbate the cerebrovascular response to exercise; however, during incremental exercise in hyperoxia, the regional differences, as well as the differential intracranial and extra-cranial flow responses, are mediated primarily by PaCO2.         iv Preface The experimental chapters (i.e., chapters 4,5, and 6) were each performed with approval from the clinical ethical committee of the University of British Columbia (H10-02378, H11-03287, H13-02624), respectively.  A version of the study presented in Chapter 4, “Regional cerebral blood flow distribution during exercise: Influence of oxygen; authored / co authored by Kurt Smith, Lisa Wong, Neil  Eves, Graham Koelwyn, Jonathan Smirl, Christopher Willie, Philip  Ainslie” was accepted for publication (2012) in the journal of Respiratory, Physiology and Neurobiology. Lisa Wong, Neil Eves, Graham Koelwyn, Jonathan Smirl, Christopher Willie, Philip  Ainslie assisted with data collection and analysis and editing of final manuscript. I was responsible for majority of data collection, data analysis, writing and formatting of the manuscript.  The study presented in Chapter 5, “Influence of high altitude on cerebral blood flow and fuel utilization during exercise and recovery; authored/ co authored by Kurt Smith, David MacLeod, Christopher Willie, Nia Lewis, Ryan Hoiland, Keita Ikeda, Michael Tymko, Joseph Donnelly, Trevor Day, Nicholas MacLeod, Samuel Lucas and Philip Ainslie” was accepted for publication (2014) in the Journal of Physiology.  David MacLeod, Christopher Willie, Nia Lewis, Ryan Hoiland, Keita Ikeda, Michael Tymko, Joseph Donnelly, Trevor Day, Nicholas MacLeod, Samuel Lucas and Philip Ainslie were involved in the data collection, editing of final manuscript. I completed the bulk of the writing of the initial drafts and completion of the final manuscript, data collection, and data analysis. The findings were also presented at the 2012 American Physiological   v Society: Biology of exercise conference, the 2013 international Hypoxia symposium, as well as the 2014 Experimental Biology conference.  The final experimental study found in Chapter 6 “Role of CO2 in the cerebral hyperemic response to incremental normoxic and hyperoxic exercise; authored/co authored by Kurt Smith, Kevin Wildfong, Ryan Hoiland, Megan Harper, Nia Lewis, Andrew Pool, Sarah Smith, Thomas Kuca, Glen Foster, Philip Ainslie”.  The co authors contributed and assisted with data collection, analysis, and editing of the completed manuscript.  I was responsible for completing the major portions of data collection and analysis, formalizing initial drafts and completing the final formatted manuscript.  These findings have been submitted for publication to the Journal of Applied Physiology.               vi Table of Contents ABSTRACT    ................................................................................................................................... II PREFACE     .................................................................................................................................. IV TABLE OF CONTENTS .......................................................................................................................... VI LIST OF TABLES  VIII LIST OF FIGURES .................................................................................................................................. IX GLOSSARY     ................................................................................................................................. XV ACKNOWLEDGEMENTS .................................................................................................................. XVII CHAPTER 1.  INTRODUCTION AND PURPOSE ............................................................................... 1 CHAPTER 2.   LITERATURE REVIEW ................................................................................................ 4 2.1.  CEREBRAL ANATOMY ..................................................................................................... 4 2.2.  CEREBRAL BLOOD FLOW REGULATION ................................................................... 7 2.2.1. HISTORICAL REVIEW ........................................................................................... 7 2.2.2. INFLUENCE OF ARTERIAL BLOOD GASES ON CBF ................................... 10 2.2.3. CEREBRAL METABOLISM AND NEUROVASCULAR COUPLING ............ 20 2.2.4. BLOOD PRESSURE .............................................................................................. 26 2.2.5. DISTRIBUTION OF CARDIAC OUTPUT ......................................................... 28 2.2.6. NEUROGENIC INNERVATION .......................................................................... 29 2.3.  CEREBRAL BLOOD FLOW RESPONSE TO EXERCISE ........................................... 32 2.3.1. A HISTORICAL REVIEW OF THE CEREBRAL CIRCULATORY RESPONSE TO EXERCISE ................................................................................................................... 34 2.3.2. INFLUENCE OF ARTERIAL BLOOD GASES ON CEREBRAL BLOOD FLOW DURING EXERCISE ........................................................................................................ 45 2.3.3. BLOOD PRESSURE .............................................................................................. 52 2.3.4. REDISTRIBUTION OF CARDIAC OUTPUT ................................................... 53 2.3.5. NEURAL REGULATION OF CEREBRAL BLOOD FLOW DURING EXERCISE ......................................................................................................................... 54 2.3.6. CEREBRAL BLOOD FLOW AND METABOLISM DURING EXERCISE ..... 56 2.3.7. OVERALL AIMS AND HYPOTHESES .............................................................. 66 CHAPTER 3.  METHODOLOGY AND EXPERIMENTAL DESIGN ............................................... 70   3.1.  INSTRUMENTATION ..................................................................................................... 70 3.1.1. TRANSCRANIAL DOPPLER ULTRASOUND ................................................. 70 3.1.2. VASCULAR DUPLEX ULTRASOUND .............................................................. 78 3.1.3. CARDIO‐RESPIRATORY INSTRUMENTATION AND ASSESSMENT DURING EXERCISE ........................................................................................................ 92   vii CHAPTER 4.  REGIONAL CEREBRAL BLOOD FLOW DISTRIBUTION DURING EXERCISE: INFLUENCE OF OXYGEN ..................................................................................................................... 98 4.1.  PURPOSE AND BACKGROUND ................................................................................... 98 4.2.  METHODS ...................................................................................................................... 101 4.3.  RESULTS ......................................................................................................................... 103 4.4.  DISCUSSION ................................................................................................................... 115 4.5.  SUMMARY ...................................................................................................................... 123 CHAPTER 5.  INFLUENCE OF HIGH ALTITUDE ON CEREBRAL BLOOD FLOW AND FUEL UTILIZATION DURING EXERCISE AND RECOVERY ................................................................. 124 5.1.  PURPOSE AND BACKGROUND ................................................................................. 124 5.2.  METHODS ...................................................................................................................... 126 5.3.  RESULTS ......................................................................................................................... 135 5.4.  DISCUSSION ................................................................................................................... 162 5.5.  SUMMARY ...................................................................................................................... 172 CHAPTER 6.  VOLUMETRIC FLOW DURING INCREMENTAL EXERCISE: INFLUENCE OF CARBON DIOXIDE AND OXYGEN ................................................................................................... 173 6.1.  PURPOSE AND BACKGROUND ................................................................................. 173 6.2.  METHODS ...................................................................................................................... 176 6.2.  RESULTS ......................................................................................................................... 180 6.3.  DISCUSSION ................................................................................................................... 195 6.5.  SUMMARY ...................................................................................................................... 200 CHAPTER 7.  CONCLUSION ............................................................................................................. 201 7.1.  OVERALL SUMMARY AND SIGNIFICANCE ............................................................ 202 7.2.  STRENGTHS AND LIMITATIONS ............................................................................. 208       viii List of Tables Table 4.1. Cardiorespiratory  and  cerebrovascular  responses  during   ..................... 105 baseline and exercise in normoxic, hypoxic and hyperoxic  gas exposures.  Table 5.1. Cardiorespiratory  and  arterial - venous  variables  during   ..................... 139 exercise at sea-level and high-altitude (5050m).  Table 5.2. Cerebral blood flow and metabolism during exercise at sea   .................... 143 level and high-altitude.  Table 5.3. Cardiorespiratory  and   arterial-venous  variables   during   ..................... 154 recovery at sea-level and high-altitude (5050m).  Table 5.4 Cerebral blood flow and metabolism measurements during     .................... 159 recovery at sea-level and high-altitude.  Table 6.1. Cardio-respiratory  measurements   during   poikilocapnic   ..................... 185 and normocapnic exercise while breathing either  normoxia or hyperoxia.  Table 6.2. Cerebrovascular measurements during poicilocapnic and   ..................... 189 normocapnic exercise while breathing either normoxia  or hyperoxia.       ix List of Figures Figure 2.1 Anatomy of the cerebral vascular anatomy and distribution of anterior and posterior blood supply.   [A] Middle cerebral artery (MCA) and [C] Posterior cerebral vascular tree (PCA); [B] Intact circle of Willis; [D] Left and right internal carotid  and  [F]  vertebral  (VA)  and  basilar  (BA)  arteries;  [E]  Global  blood  flow contributions  from  the  right  (red) and  left  (green)  ICA  (73‐82%) and BA  (blue; ~18‐27%) through the anterior and posterior circulations.  Images adapted, with permission, from Nowinski et al. (2013). ..................................................................................... 6  Figure 2.2 Directional cerebral blood flow response to changes in the metabolism, blood pressure, sympathetic nervous activity (SNA), partial pressures of arterial carbon  dioxide  (PaCO2)  and  oxygen  (PaO2)  and  cardiac  output.  Adapted,  with permission from Ainslie & Duffin (2009) and Willie et al. (2014c).  ................................ 9  Figure  2.3  Global  cerebral  blood  flow  (CBF)  during  isocapnic  hypoxia  and hyperoxia  (black  squares),  hyperoxic  hypercapnia  (51 mmHg  PaCO2;  filled  red squares) and poikilocapnic hyperoxia (squares)). Black squares = [(ICA +VA) x 2; black  squares]  (Ainslie  et  al.,  2014);  red  squares  (Floyd  et  al.,  2003).  *  P <0.05 from baseline. ......................................................................................................................................... 12  Figure  2.4  A)  Extra‐cerebral  blood  flow  responses  (Q)  in  the  internal  carotid (ICA) and vertebral  (VA) arteries and B) cerebral blood flow velocity responses (CBV)  in  the  middle  and  posterior  cerebral  arteries  to  fluctuations  in  isoxic PaCO2;  C)  Relative  changes  in  vascular  PaCO2  reactivity  through  the hypercapnic,  hypocapnic  and  entire  PaCO2  (overall)  range.    *  p  <  0.05  from baseline, † p <0.05 (ICA vs VA; MCA vs PCA), Ø p<0.05 from ICA, ‡ p<0.05 from VA.  Adapted, with permission, from Willie et al. (2012). ................................................... 16  Figure  2.5  The  percent  change  in  cerebral  blood  flow  (∆%  CBF)  during acclimation  (>  4  days  above  3400m)  in  the  seven  studies  at  various  altitudes reviewed in (Ainslie & Subudhi, 2014), and one recent investigation following 5 days at 4350m (Rupp et al., 2014). ............................................................................................... 19  Figure  2.6  Generalized  relative  changes  in  cardio‐respiratory  (cardiac  output [CO],  partial  pressure  of  arterial  carbon  dioxide  [PaCO2]  and  arterial  oxygen content  [CaO2]),  cerebrovascular  (cerebral  perfusion  pressure  [CPP],  global cerebral  blood  flow  [gCBF],  cerebral  oxygen  delivery  [DO2]),  and  metabolic (oxygen extraction fraction [OEF], cerebral metabolic rate of oxygen [CMRO2]) responses  to  incremental exercise. The dotted  line signifies  the point at which ventilatory threshold is typically crossed during exercise. ................................................ 33  Figure  2.7  The  experimental  setup  for  early  cerebral  blood  flow  assessment (percent  change  in  cerebral  perfusion  [%  ∆])  using  the  [A]  Xe  clearance technique [C; flow compartment model (FCM) and initial slope index (ISI)] and [B] and transcranial Doppler [B, middle cerebral artery (MCAv)] during exercise   x with increasing workload.  Images adapted with permission, from Jorgensen et al. (1992b) and Thomas et al. (1989). .......................................................................................... 38  Figure 2.8 Percent changes in cerebral perfusion from rest, during incremental exercise  from mild  (20‐40% Wmax) moderate  (50‐70% Wmax)  and maximal (80‐100% Wmax) intensities.  Values are reported as a mean observed in the 13 studies  known  to  date  to  have  examined  changes  in  CBV  (using  transcranial Doppler)  during  exercise  to  exhaustion. Red numbers  indicate  average PaCO2 values. ........................................................................................................................................................ 41  Figure 2.9 The percent change of cerebral blood velocity (CBV) and flow (CBF) through  the middle  cerebral  (MCAv)  internal  carotid  (ICA) and vertebral  (VA) arteries, as well as the global CBF (gCBF = [ICAx2] + [VAx2]) during incremental exercise  to  80%  of  the  maximum  achieved  workload  (%WMax).    Findings adapted from (Sato et al., 2011). .................................................................................................... 44  Figure 2.10 Average relative cerebral blood flow (CBF) response during exercise at  mild  (20‐40%  Wmax),  moderate  (40‐70%  WMax)  and  Maximal  (100% Wmax) intensities from the 11 studies investigating CBF during normoxia ((Fan & Kayser, 2013; Huang et al., 1991; Imray et al., 2005; Rasmussen et al., 2010b; Subudhi et al., 2008; Subudhi et al., 2009; Subudhi et al., 2011)), acute hypoxia (Ainslie  et  al.,  2007; Fan & Kayser,  2013; Huang et  al.,  1991; Overgaard et  al., 2012;  Siebenmann  et  al.,  2013;  Subudhi  et  al.,  2008;  Subudhi  et  al.,  2009; Subudhi  et  al.,  2011)  and  chronic  hypoxia  ((Huang  et  al.,  1991;  Imray  et  al., 2005; Möller et al., 2002; Subudhi et al., 2009)).  Red lettering signifies the mean respective PaCO2 for the condition and exercise intensity. ............................................... 48  Figure 2.11 The percent change in CMRO2 (% ∆CMRO2) during light (20 – 40% WMax),  moderate  (40‐60%  Wmax)  and  maximal  (100%  Wmax)  exercise intensity.   The CMRO2 values are the average values calculated from the mean responses  in  the 12  studies  investigating  this  response  (Brassard  et  al.,  2010; Fisher et al., 2013; Kleinerman & Sokoloff, 1953; Kleinerman & Sancetta, 1955; Lambertsen et al., 1959; Madsen et al., 1993; Nybo et al., 2003; Rasmussen et al., 2010a; Rasmussen et al., 2010b; Scheinberg et al., 1953; Scheinberg et al., 1954; Trangmar et al., 2014). ....................................................................................................................... 58   Figure  2.12  A)  The  cumulative  oxidative  (CMRglu  +  ½  CMRlac)  and  non oxidative  (1/6 CMRO2 ‐  (CMRglu + ½ CMRlac) cerebral metabolic  ratio  (CMR: oxidative plus non‐oxidative in glucose equivalent units) and cerebral oxidative carbohydrate  ratio  during  rest,  light  (20‐40%  WMax),  moderate  (40‐60%Wmax)  and maximal  (100%WMax)  cycling  exercise.  An  increase  in  CMR indicates  an  increase  in  global  cerebral  metabolism while  a  reduction  in  OCI indicates  a  reduction  in  oxidative metabolism.  B)  The  percent  contribution  of oxygen, glucose and lactate trans‐cerebral uptake to the CMR.  Sizes of the circle are proportional to the percent difference in CMR from rest. All values are mean   xi and  standard  deviations  calculated  from  the  eight  studies  quantifying  CMR during incremental exercise (Brassard et al., 2010; Fisher et al., 2013; Ide et al., 2000b;  Larsen  et  al.,  2008;  Nybo  et  al.,  2003;  Rasmussen  et  al.,  2010a; Rasmussen et al., 2010b; Trangmar et al., 2014). ................................................................... 63  Figure 3.1 A) Magnetic resonance angiograph of Circle of Willis with right and left  internal  carotid  artery  (ICA),  basilar  artery  (BA)  and  B)  middle  cerebral (MCA) and C) posterior  cerebral  (PCA) arteries.  In  the  current  study,  cerebral blood velocities were  collected using  transcranial Doppler ultrasound  through the  anterior  and  posterior  temporal  acoustic  windows.  Adapted,  with permission, from Smith et al., (2012). ......................................................................................... 72  Figure 3.2 In the image: Red stripped lines = vessel walls, red arrow = direction of moving blood, blue dashed line = ultrasound beam, green bar = angle cursor, black  dashed  lines  indicate  the  percentage  of  the  reflected  ultrasound  signal that  is  received  by  the  receiver.  The  relationship  between  the  angle  of insonation  and  cosine  of  the  angle  (Cos  Ø).    The  image  demonstrates  the progressive and disproportional reduction in the percentage of the transmitted signal  reflected  back  to  the  ultrasound  probe  as  the  angle  of  insonation increases such that at 90 degrees no signal will be recorded. .......................................... 74  Figure  3.3  B‐mode  image  of  the  extra‐cranial  neck  vessels  (common  carotid [CCA],  internal  carotid  [ICA],  and  external  carotid  artery  [ECA])  that  deliver blood flow to the anterior cerebral circulation, collected using a vascular duplex ultrasound. ............................................................................................................................................... 79  Figure 3.4 Color‐coded Duplex imaging of internal carotid artery (orange color) illustrating the cross sectional area and velocity. The color‐coding refers to the direction  of  the  flow  (i.e.,  orange  towards  or  blue  away  from  the  ultrasound probe). ....................................................................................................................................................... 81  Figure 3.5 In all images: Red stripped lines = vessel walls, red arrow = direction of moving blood, blue dashed line = ultrasound beam, green bar = angle cursor. A. The ultrasound beam has been appropriately steered to reduce the angle to 60°.  B.  The  transducer  has  been  “heeled”  to  decrease  the  angle  of  the  beam relative  to  the  vessel  to  an  acceptable  60°.  C.  Appropriate  alignment  of  angle cursor parallel  to  the  vessel walls  at  60°. D.  Inappropriate placement of  angle cursor relative to the direction of blood flow. In this case the system will assume at  60°  angle  (between  ultrasound  beam  and  angle  cursor)  as  opposed  to  the actual angle of 45° (between the ultrasound beam and the blood flow) and will therefore underestimate the velocity calculated by ~30%. ............................................... 83  Figure  3.6  B‐Mode  image  of  the  vertebral  artery  viewed  between  the  cervical spinal chord sections (i.e., vertebral processes). .................................................................... 91    xii Figure 4.1 Middle cerebral arterial (MCAv) and posterior cerebral artery blood flow  velocity  (PCAv)  expressed  in  cm.s‐1,  during  baseline,  gas  exposure  and during  incremental  exercise  at  percentage  of  peak work  rate  intervals while breathing  a  normoxic  (●),  hypoxic  (■)  and  hyperoxic  (▲)  .‡  denotes significance  (P<0.001)  between  hyperoxia  and  normoxia.ϕ  denotes significance (P<0.001) between hyperoxia and hypoxia. ................................................ 109  Figure 4.2 Middle cerebral arterial (MCAv) and posterior cerebral artery blood flow  velocity  (PCAv)  expressed  in  cm.s‐1,  during  baseline,  gas  exposure  and during  incremental  exercise  at  percentage  of  peak work  rate  intervals while breathing  a  normoxic  (●),  hypoxic  (■)  and  hyperoxic  (▲).  ‡  denotes significance  (P<0.001)  between  hyperoxia  and  normoxia.ϕ  denotes significance (P<0.001) between hyperoxia and hypoxia. ................................................ 111  Figure 4.3 The relationship between the absolute changes  in    the middle and posterior  cerebral  artery  velocity  (MCAv  and PCAv,  respectively  (cm.s‐1))  to changes  in  the  end‐tidal  partial  pressure  of  CO2  (PetCO2  (mmHg))  from exposure  to  40%  workload  maximum  in  A)  Normoxia,  B)  Hypoxia,  and  C) Hyperoxia. ............................................................................................................................................. 114  Figure 4.4 Relationship between the absolute changes from rest to 40% Wmax between  the  middle  cerebral  artery  (MCAv,  cm.s‐1)  with  posterior  cerebral artery (PCAv, cm.s‐1) in A) normoxia, B) hypoxia C) hyperoxia. .................................. 115  Figure 5.1 Absolute (A) and relative (B) contributions of internal carotid (ICA) and  vertebral    (VA)  artery  blood  flow  to  resting  global  cerebral  blood  flow (gCBF; C) as well as the resting cerebral metabolic rate of oxygen (CMRO2) at sea‐level  (SL)  and  high  altitude  (HA).  The  red  line  indicates  subject  #5’s CMRO2  response  to  HA  and  illustrates  the  outlier  response  (see  results  for statistical details).  † Denotes difference between SL and HA (p<0.05). ................... 138  Figure  5.2  Arterial  partial  pressure  of  oxygen  (PaO2;  A)  and  carbon  dioxide (PaCO2;  B)  as  well  as  arterial  oxygen  content  (CaO2;  C)  and  pH  (D)  during baseline  (BL)  incremental  exercise  (20  ‐100  %  of  the  maximum  achieved workload  [%Wmax])  and  30 min  of  recovery  at  sea  level  (SL; )  and  high altitude (HA; ). * Denotes differences from BL, † Signifies difference between SL and HA (p<0.05). .......................................................................................................................... 146  Figure 5.3 Cerebral blood flow velocity in the middle (MCAv; A) and posterior (PCAv;  B)  cerebral  arteries,  and  global  cerebral  blood  flow  as  measured  by ultrasound (gCBF; C) and the Fick principle (gCBFFick; D) during baseline (BL) incremental  exercise  (20  ‐100  %  of  the  maximum  achieved  workload [%Wmax]) and 30 min of recovery at sea level (SL; ) and high altitude (HA; ).  * Signifies differences  from BL, † Denotes difference between SL and HA (p<0.05). ................................................................................................................................................ 148  xiii  Figure  5.4  Cerebral  oxygen  delivery  (CDO2;  A),  cerebral  metabolic  rate  of oxygen  (CMRO2;B),  cumulative metabolic  ratio  uptake  (CMRU  [mmol.l‐1];  C) and  cumulative  metabolic  rate  factored  for  cerebral  blood  flow  differences (CMRUgCBF  [mmol.100g‐1.min‐1],  D)  during  baseline  (BL)  incremental exercise  (20  ‐100 % of  the maximum achieved workload  [%Wmax])  and  30 min  of  recovery  at  sea  level  (SL; )  and  high  altitude  (HA; ).  *  Signifies differences from BL, † Signifies difference between SL and HA (p<0.05). ............... 150  Figure  5.5  Cerebral  delivery  of  glucose  (CDGlu;  A)  and  lactate  (CDLac:C), cerebral  metabolic  rate  of  glucose  (CMRGlu;  B)    and  lactate  (CMRLac;  D) during  baseline  (BL)  incremental  exercise  (20  ‐100  %  of  the  maximum achieved workload [%Wmax]) and 30 min of recovery at sea level (SL; ) and high  altitude  (HA; ).  *  Signifies  differences  from  BL,  †  Denotes  difference between SL and HA (p<0.05). ....................................................................................................... 152  Figure 5.6 The ratio of oxygen and glucose uptake (OGI= O2/ Glucose; C) and ratio oxygen to carbohydrate uptake (OCI = O2/ Glucose + ½ Lactate; E) as an indexes  of  oxidative  versus  non  oxidative  metabolism  during  baseline  (BL) incremental  exercise  (20  ‐100  %  of  the  maximum  achieved  workload [%Wmax]) and 30 min of recovery at sea level (SL; ) and high altitude (HA; ).  * Denotes differences  from BL, † Signifies difference between SL and HA (p<0.05). ................................................................................................................................................ 163  Figure 5.7 Arterial  lactate concentration (A),  ratio of oxygen  to carbohydrate uptake (OCI = O2/ Glucose + ½ Lactate; B), cerebral oxygen delivery (CDO2; C), and cerebral metabolic rate of oxygen (CMRO2; D) during incremental exercise at  the  same absolute workload  (60, 120 and 150 watts)  at  sea‐level  (SL; ) and high altitude (HA; ). † Signifies difference between SL and HA (p<0.05). ... 165  Figure  6.1  The  percent  change  in  the  middle  (∆  %MCAv)  and  (∆  %PCAv) posterior  cerebral  artery  blood  flow  velocities,  internal  (∆  %QICA)  and vertebral  (∆ %QVA)  artery  blood  flows  and  global  cerebral  blood  flow  (∆ % gCBF)  during  hyperoxia  compared  with  normoxia  with  (normocapnic)  or without  (poikilocapnic)  PETCO2  controlled  at  basal  values.  †  signifies differences between normoxia and hyperoxia (p < 0.05). ............................................... 187  Figure  6.2  Comparing  the  percent  change  in  the middle  (∆ %MCAv)  and  (∆ %PCAv)  posterior  cerebral  artery  blood  flow  velocities,  internal  (∆ %QICA) and vertebral (∆ %QVA) artery blood flows and global cerebral blood flow (∆ %  gCBF)  during  normocapnic  or  poikilocapnic  in  both  normoxia  and hyperoxia. ‡ signifies differences between normocapnic or poikilocapnic (p < 0.05). ........................................................................................................................................................ 192   xiv Figure  6.3  Comparisons  of  the  regional  intracranial  cerebral  blood  flow velocities  (MCAv  versus  PCAv)  and  extracranial  blood  flows  (QICA  versus QVA),  as  well  as  relative  velocity  and  blood  flow  changes  in  the  proximal intracranial versus extracranial (MCAv versus QICA; PCAv versus QVA) during normocapnic normoxia and hyperoxia. ϕ Signifies significance between vessels (p <0.05). ............................................................................................................................................... 194  Figure  6.4  Comparisons  of  the  regional  intracranial  cerebral  blood  flow velocities  (MCAv  versus  PCAv)  and  extracranial  blood  flows  (QICA  versus QVA),  as  well  as  relative  velocity  and  blood  flow  changes  in  the  proximal intracranial versus extracranial (MCAv versus QICA; PCAv versus QVA) during poikilocapnic  normoxia  and  hyperoxia.  ϕ  Signifies  significance  between vessels (p <0.05). ............................................................................................................................... 195  Figure  6.5  The  relationship  between  the  percent  change  in  intracranial velocities  (%  ∆MCAv  and  %  ∆PCAv)  and  extracranial  flow  (%  ∆QICA  and %∆QVA)  with  the  unit  change  in  the  partial  pressure  of  end‐tidal  carbon dioxide (∆PETCO2) during poikilocapnic normoxic and hyperoxic exercise. ......... 197  Figure 6.6 Comparison between the absolute  intracranial cerebral blood flow velocities  (MCAv;  PCAv)  and  extra‐cranial  blood  flows  (QICA;  QVA)  during poikilocapnic  exercise  and  isocapnic  hyperpnea.  λ  signifies  differences between poikilocapnic exercise and isocapnic hyperpnea (p < 0.05). ....................... 198      xv Glossary   Ca-vO2: arterial venous oxygen content differences CaO2: arterial oxygen content CDGlu: Cerebral glucose delivery CDLac: Cerebral lactate delivery CDO2: Cerebral oxygen delivery CMRGlu: Cerebral metabolic rate of glucose CMRLac; Cerebral metabolic rate of lactate CMRO2: Cerebral metabolic rate of oxygen CvO2: venous oxygen content Fb: breathing frequency gCBF: Global cerebral blood flow Glua-v: cerebral arterial venous glucose differences  HR: heart rate  ICA: Internal carotid artery Laca-v: arterial venous lactate differences MAP: mean arterial pressure CBV: intracranial cerebral velocity MCA(v): Middle Cerebral Artery (velocity) O2Ext: relative fraction of oxygen content  OCI: oxygen carbohydrate differences OGI: oxygen glucose index PCA(v): Posterior Cerebral Artery (velocity)  xvi PCO2: partial pressure of carbon dioxide  PETCO2: partial pressure of end-tidal carbon dioxide PETO2 : partial pressure of end-tidal oxygen  PO2: partial pressure of oxygen CBF: Extra-cranial cerebral flow QICA: Internal carotid artery blood flow QVA: Vertebral artery blood flow  SO2: oxygen saturation  VA: Vertebral artery VE: minute ventilation WMax:  maximum achieved workload     xvii Acknowledgements This thesis would not be possible without the remarkable, albeit unconventional, mentorship, guidance and support received from my supervisor Dr. Philip Ainslie.  My academic, scientific and personal growth throughout my PhD is the result of endless and selfless leadership and friendship from Dr. Ainslie. He has challenged me, and provided me with the opportunities needed to succeed throughout my time at UBC. Throughout this process I have learned the importance of balancing and maintaining a healthy work ethic and lifestyle.  I will continue to call upon the knowledge and experiences gained from the research endeavours, both in the laboratory and in the field, as well as the invaluable life lessons gained from my time working with Phil.   A great deal of effort has been spent in the completion of this thesis, and would not be possible without the contributions and feedback from my committee members: Dr. Neil Eves, Dr. Jonathan Little, Dr. Andis Klegaris, and Dr. James Fisher.  I would also like to thank my colleagues and the faculty within the Centre for Heart Lung and Vascular Health and the School of Health and Exercise Sciences at the University of British Columbia Okanagan.  The contributions, scientific and philosophical discussions with these individuals have been crucial to the successful completion of my dissertation and development as a lifelong integrative and exercise physiologist.   I would also like to deliver a special thanks to these national and international collaborators: Dr. Trevor Day, Dr. Samuel Lucas, Dr. Damien Bailey, Dr. David McLeod and Dr. Peter Rasmussen.  I have learned a great deal from these individuals, and have a  xviii great deal of respect for the time taken in order to teach and discuss physiology, philosophy, and even basic arithmetic, as it relates to science and life.  It has been a fantastic journey, thank you.  Finally, I would like to acknowledge the National Sciences and Engineering Research Council for the Alexander Graham Bell Canadian Graduate Scholarship; as well as the Heart and Stroke Foundation for the Doctoral research award which provided me with the funding required to pursue and complete my doctoral graduate studies.  xix Dedication To my intelligent and beautiful wife Brianne, it has been eleven years together, and you are still smarter than me. My success is only a small part of our family’s achievements, however none of it is possible without your love, support and brilliance. I look forward to being a part of your future successes. Thank you for all that we do, all that we have done and all we have yet to do.  To Sloane, Jordana and Aspen, my three little blonde monsters.  I would still be floundering around wasting time if you hadn’t come around. My life didn’t begin until you three came into my life and taught me how to play again, smile again and sometimes cry again.  Your inspiration has provided me with the motivation to live with passion, purpose and determination. Thank you for teaching me the meaning and beauty of living for someone other than myself.    To my Mom and Dad, thank you for teaching me the importance of aiming high, running fast, and speaking slow… sometimes.  Although the road at times may have been rocky, with a few sharp corners and a couple of unforeseen or extra hills I would not have it any other way. Thank you.  To Clare and Byron, your love and support, as well as practical and unending optimism continues to inspire.   I am proud to be part of it.       1 Chapter 1. Introduction and Purpose  The conservation of an adequate cerebral blood flow (CBF) is required to ensure normal brain function and sustain life.  The human brain, despite being only 2-3% of the total body mass while requiring ~15% of the total cardiac output, consumes ~20% of the total oxygen consumption at rest. Given the brain’s high-energy consumption and lack of meaningful intra-cellular energy stores, precise control of maintenance of CBF is essential.  During exercise, the cardiovascular system is challenged with the task of increasing the blood supply to the active musculature, while maintaining an adequate blood supply to vital organs such as the heart, lungs and most importantly the brain. The physiological mechanisms involved in the regulation of CBF at rest are relatively well established. During dynamic exercise, heart rate, venous return and contractility increase to augment cardiac output, which is the systemic source of blood flow distribution to all the organs in the body. For efficient substrate delivery, blood flow is diverted to the working muscles via an integrative mechanism of nervous, hormonal, and humoral systems. Consequently, dynamic exercise performed at moderate-to-high intensity can increase cardiac output and skeletal muscle blood flow by 8- and 100-fold respectively above the resting values, while CBF likely increases only slightly. Unfortunately, how these mechanisms serve to maintain CBF during exercise remain less clear.   Despite a plethora of data over the last 60 years describing the general relationship between arterial blood gases, metabolism, blood pressure, cardiac output, and neural innervation with CBF during exercise only a few studies have attempted to quantify these individual contributions.  One major issue associated with partitioning these individual   2 contributions is the redundancy with which the cardiovascular system achieves this complex regulation. For example, a consistent and almost unavoidable confound is experimental manipulation of one of the key mechanisms (e.g., cardiac output) will typically be reflected in another compensatory response (e.g., augmented blood pressure, neural innervation or arterial blood gases). A common theme throughout this thesis is the influential role that arterial blood gases – in particular the partial pressure of arterial CO2 (PaCO2) and O2 (PaO2)  - play in regulating CBF, both at rest and during exercise.  Therefore, with particular focus on arterial blood gases, the following Chapters will attempt to highlight what is currently known about CBF regulation at rest and during exercise. The overall goal of this thesis was to quantify the independent and combined influence of PaO2 and PaCO2 on global and regional CBV and CBF during exercise.  Prior to presenting the findings from the experimental chapters (Chapter 4, 5 and 6), an extensive literature review (Chapter 2) will establish the relevant background material in the context of the thesis. Key focus will be placed upon: the anatomy of the cerebrovasculature; mechanisms involved in the regulation of CBF at rest and during exercise; and finally concluding with the specific aims and hypothesis of the thesis. The subsequent chapter (Chapter 3) will highlight the specific instruments and methodological approaches utilized in the three experimental chapters. These experimental sections aim to identify the regional distribution of intracranial (Chapter 4) versus extra-cranial CBF (Chapters 5  & 6) during normoxic (Chapters 4, 5 and 6), hypoxic (Chapter  4 & 5) and hyperoxic (Chapter   4 &  6) exercise.  Specifically, Chapter  4 will attempt to establish the combined influence PaO2 and PaCO2 have on the   3 regional intracranial cerebral blood velocity (CBV) response to incremental poikilocapnic hypoxic and hyperoxia exercise.  To extend the findings from Chapter  4 into a state of chronic and severe hypoxemia, Chapter 5 will quantify the influence early acclimatization (4-6 days) to high altitude (5050 m) has on CBF and cerebral metabolism (CMR) during and following exercise.  To follow up from these studies, Chapter  6 will provide insight into the individual role that PaCO2 and ventilation plays in contributing to the regional and global CBF response to incremental normoxic and hyperoxic exercise. The collective findings and conclusions gained from these three experimental investigations will be presented in the final chapter of this thesis (Chapter 7). In this Chapter, appropriate methodological limitations, and future directions are provided to help further our understanding of CBF regulation during exercise.   4 Chapter 2. Literature Review  This literature review is organized to provide a brief anatomical and historical review of the regulation of CBF at rest and during exercise at sea level and high altitude. The following sections will outline the primary mechanisms, methodology, and significance, associated with investigating the regulation of CBF during exercise. Based on this overview, key gaps in the literature related to CBF regulation during exercise are identified and form the premise for the generation of the aims and hypothesis surrounding this thesis. The overall goal of this thesis is to examine the magnitude of combined and independent influence arterial blood gases (PaO2 and PaCO2) have on the regulation of regional and global CBF during exercise.  2.1. Cerebral anatomy The brain receives blood via two sources: The internal carotid arteries and the vertebral arteries.  Approximately 73-82% of the cerebral blood supply occurs through the internal carotid (ICA) arteries and the remaining 18-27% of the global CBF arrives via the basilar artery fed by the two vertebral (VA) arteries (Figure 2.1) (Nowinski et al. (2013).  The anterior circulation, which begins distal to the carotid sinus at the ICA’s, supplies both the forebrain (frontal and parietal lobes) and the midbrain (temporal lobe) regions in both the right and left hemispheres.  The ICA continues from the neck into the brain where it has a branch that feeds the ophthalmic artery prior to trifurcating into the middle cerebral artery (MCA) the anterior cerebral artery (ACA), and the posterior communicating artery. The anterior circulation delivers blood from both the right and left hemispheres via the anterior communication artery, which joins the two bilateral anterior cerebral arteries.    5 The middle cerebral and the anterior arterial branches deliver blood throughout the brain via the smaller stem and cortical branches which feed into the smaller cerebral arterioles and eventually into the anterior cerebral capillary beds. The posterior circulation starts from two bilateral vertebral arteries that join at the vertebro-basilar junction to form the basilar artery and supplies the hindbrain regions (brain stem and cerebellum) and the occipital cortices.  Several divergent branches lie along the vertebral and basilar arteries. These branches include spinal arteries, cerebellar, pontine and labyrinthine arteries truncations of the vertebro-basilar pathway, which delivers blood flow to the brainstem organs, the cerebellum and other corticospinal locations.  The remaining blood is delivered from the basilar artery into the posterior cerebral arteries (PCA) which branches into the parieto-occiptal and the calcarine arteries, as well as many other perforating branches such as the thalamoperforating, thalamogeniculate, and circumflex arteries which feed smaller stem and cortical branching arteries which eventually feed into the posterior arterioles and capillary beds.  The cerebral circulation is joined at several locations, which forms the vascular structure referred to as the Circle of Willis.  The Circle of Willis connects the anterior and posterior circulations through the posterior communicating arteries, which joins the ICA with the PCA.  Blood flow through the Circle of Willis is delivered from the ICA to the posterior circulation (van Kooij et al., 2010); however, a recent study has demonstrated that this may be reversed in some individuals (van Ooij et al., 2012). Furthermore, the right and left hemispheres are connected by right and left ACA’s via the anterior communicating artery. Blood flow through the anterior communicating artery appears to be dependent on the hemisphere with anterior artery hypoplasticity (typically the right hemisphere, with left to right blood   6 flow), which is believed to be the product of the usual dominance of the left hemisphere in humans.   Figure 2.1. Anatomy of the cerebral vasculature and distribution of anterior and posterior blood supply.  [A] Middle cerebral artery (MCA) and [C] Posterior cerebral vascular tree (PCA); [B] Intact circle of Willis; [D] Left and right internal carotid and [F] vertebral (VA) and basilar (BA) arteries; [E] Global blood flow contributions from the right (red) and left (green) ICA (73-82%) and BA (blue; ~18-27%) through the anterior and posterior circulations.  Images adapted, with permission, from Nowinski et al. (2013).     7 2.2. Cerebral blood flow regulation  The following sections will aim to describe the historical contributions and evolution of the measurement of CBF. These findings are provided in context to the continually evolving body of literature describing the relationship between CBF regulation and arterial blood gases, metabolism, blood pressure, cardiac output, and neural innervation at rest. The related alterations during exercise is considered in section 2.3.  2.2.1. Historical Review  When Roy & Sherrington (1890) first described the discrepancies and variability regarding repeated measurements of blood supply to the brain to be the result of internal sources of subject error, they inherently provided the first description of the local and peripheral mechanisms governing CBF regulation. As direct access to the human cerebral vasculature is limited and technology dependent, many of the key integrative investigations into brain blood supply were originally performed in animals. However, some 50 years after the seminal work of Roy & Sherrington (1890) the first quantitative measurement of global CBF (gCBF) in humans was achieved (Kety & Schmidt, 1945). With this approach, a combined in a series of studies, great insight was made into the integrative roles that metabolism, perfusion pressure, neurogenic activity and selected pathologies play in CBF regulation in humans [Figure 2.2; (Harmel et al., 1949; Kety & Schmidt, 1945; Kety & Schmidt, 1946; Kety & Schmidt, 1948a; Kety & Schmidt, 1948b)].     8 At rest, the brain receives approximately 12-15% of the total cardiac output (~750 ml.min-1). This is remarkable considering that the brain accounts for on average only 2% of the total body mass. Moreover, the brain contributes to nearly 20% of the bodies total energy consumption at rest.  Thus, it should not be surprising that maintaining this relatively high energy demand, adequate blood flow delivery is achieved through a myriad of regulatory mechanisms (Kety & Schmidt, 1945; Lassen, 1978; Lassen, 1985; Rowell, 1993).  As the brain has a high resting metabolic rate, but very small glycogen stores [e.g., 3-5 µmol.g-1; (Oz et al., 2007)], maintaining an adequate CBF is essential to providing a constant supply of metabolites and removal of byproducts to maintain cerebral tissue homeostasis (Hom et al., 2001).  Appreciable interruptions in CBF can lead to unconsciousness (Van Lieshout et al., 2003), brain damage, and death if left untreated (Kabat & Anderson, 1943). The focus of the following sections will aim to breakdown the individual influences of arterial blood gases, metabolism, blood pressure, cardiac output, and neural input have on CBF regulation.    Figure 2.2. Directional cerebral blood flow response to changes in the metabolism, blood pressure, sympathetic nervous activity (SNA), partial pressures of arterial carbon dioxide (PaCO2) and oxygen (PaO2) and cardiac output. Adapted, with permission from Ainslie & Duffin (2009) and Willie et al. (2014c).  Nerve%Cell%Ac*vity% Perfusion%Pressure% Cerebral%SNA% Arterial%PCO2%Arterial%PO2%Cardiac%Output%Metabolism% Blood%Pressure% Neurogenic% Chemical% Cardiac%Output%50% 150%Cerebral'blood'flow'(Coma)% (Seizure)%  10 2.2.2.  Influence of arterial blood gases on CBF   Initial investigations into the regulation of CBF have demonstrated that the cerebral circulation is sensitive to perturbations in arterial oxygen (PaO2) and carbon dioxide (PaCO2).  For example, depending on the prevailing PaCO2, reductions in PaO2 (e.g., < 50 mmHg) induced by breathing a hypoxic gas or at high altitude (> 4000 m) leads to cerebral vasodilation which increases CBF and in most cases acts to maintain cerebral oxygen delivery (Lewis et al., 2014a; Willie et al., 2012; Willie et al., 2014a; Wilson et al., 2011). In contrast, elevations in PaO2  [e.g. > 500 mmHg;  (Bulte et al., 2007; Floyd et al., 2003; Kety & Schmidt, 1948a; Lambertsen et al., 1953)] result in cerebral vasoconstriction contributing to a reduction in CBF.  Elevations or reductions in PaCO2 result in cerebral vasodilation and vasoconstriction, respectively. The degree to which CBF fluctuates in the face of dynamic or steady state changes in PaO2 or PaCO2 is different based on the background of the opposing blood gas (Gibbs et al., 1947). The following sections will highlight these interactions in regulating CBF.   Partial pressure of arterial oxygen  Hypoxia: The cerebral vasculature is impervious against mild to moderate drops in PaO2 (hypoxemia) such that little to no change in CBF is observed during mild (e.g., PaO2 > 60 mmHg) hypoxia; however, when PaO2 is reduced below ∼50 mmHg (severe hypoxemia), there is a robust elevation in CBF (Willie et al., 2012). It has been known for some time that changes in the caliber of the small pial vessels during normobaric hypoxia is contingent on the milieu of arterial blood gases, including hypoxia (Wolff et al., 1930).   11 Hypoxemia stimulates the peripheral chemoreceptors, triggering hyperventilation and hence reduces PaCO2 (hypocapnia); an effect that consequently generates an opposing vasoconstrictive effect on the cerebrovascular. Additionally, there is strong evidence, suggesting that CaO2 rather than PaO2 per se, is the hypoxic cerebrovascular stimulus (Brown et al., 1985; Todd et al., 1994; Tomiyama et al., 1999). Although it seems that PaO2 activates ATP sensitive potassium channels but CaO2 does not (Tomiyama et al., 1999), the mechanisms how CaO2 might alter CBF are unknown. Notwithstanding a lack of consensus over whether PaO2 versus CaO2 is the hypoxic stimulus, the increase in CBF during severe hypoxia serves to maintain cerebral oxygen delivery in the face of falling CaO2 {(Ainslie & Subudhi, 2014; Brown et al., 1985; Todd et al., 1994; Willie et al., 2012)). Presently, no single prevailing mechanism has been identified as the primary component involved in hypoxic cerebral vasodilation. However, increased cerebral activation and the release of local vasodilator molecules  [ie; adenosine (Bowton et al., 1988), and endothelium derived nitric oxide (Van Mil et al., 2002)] are known to partially modulate CBF during hypoxia.  It should be acknowledged, however, that the independent influence of these vasoactive factors play in adjusting the caliber of cerebral vessels in the presence of fluctuating arterial blood gases is largely unknown [see Willie et al. (2014c) for review].    12    Figure 2.3. Global cerebral blood flow (CBF) during isocapnic hypoxia and hyperoxia (black squares), hyperoxic hypercapnia (51 mmHg PaCO2; filled red squares) and poikilocapnic hyperoxia (squares)). Black squares = [(ICA +VA) x 2; black squares] (Ainslie et al., 2014); red squares (Floyd et al., 2003). * P <0.05 from baseline   25# 50# 75# 100# 300# 600#20#60#80#100#40#CBF#(ml.min41)#*#*#*#PaO2#(mmHg)#  13 Hyperoxia: Conflicting reports exist regarding cerebral vasoconstriction in the presence of elevated PaO2 (Ainslie et al., 2014; Floyd et al., 2003; Kety & Schmidt, 1948a; Lambertsen et al., 1953; Willie et al., 2012). At rest, breathing a hyperoxic gas mixture (FiO2>0.21) moderately increases ventilation resulting in mild hypocapnia [e.g., ~2 - 4 mmHg reduction in PaCO2 (Marczak & Pokorski, 2004)]. Kety & Schmidt (1948a) first observed a 13% reduction in global CBF (gCBF) when subjects breathed a gas mixture containing an FiO2 of 0.85 – 1.0 for 30 minutes compared to breathing room air (FiO2: 0.21) – this finding was later corroborated by Lambertsen et al. (1953) using the Kety Schmidt technique during hypobaric hyperoxia.  In addition to an observed 14% reduction in CBF during hyperoxia at normal ambient atmospheric pressure (1 atm), there are further reductions (~ 24%) when the ambient pressures were increased to 3-4 atm [PaO2 = 2100 mmHg; (Lambertsen et al., 1953)].  Floyd et al. (2003), using continuous arterial spin labeling MRI, observed a reduced CBF (~ 33%) while breathing a hyperoxic gas mixture (FiO2=1.0; poikilocapnic) during a 10-minute period. Additionally, increasing PaCO2 by 11 mmHg (i.e., to 51 mmHg) resulted in CBF returning to normoxic normocapnic levels. In contrast, using vascular ultrasound, Willie et al. (2012) only observed a small non-significant reduction in blood flow in the ICA and VA during progressive isocapnic hyperoxia (PaO2 = 320 and 430 mmHg; PaCO2 = 40 mmHg).  Ainslie et al. (2014) also observed no change in gCBF during isocapnic hyperoxia (PaO2 = 320 and 430 mmHg; PaCO2 = 40 mmHg).  However, when Floyd et al. (2003) elevated PaCO2 during hyperoxia, CBF was lower compared to CBF during a similar hypercapnic stimulus when compared with a similar isoxic hypercapnic stimulus (PaCO2 = + 4 - 11 mmHg).  In view of the discrepant findings regarding hyperoxic-induced cerebral   14 vasoconstriction, and the scarce consistency the manipulation of PaCO2, it appears as though hyperoxic vasoconstriction only clearly occurs at a threshold above a PaO2 of 430 mmHg (Figure 2.3). The punitive mechanisms behind the hyperoxic-induced cerebral vasoconstriction are four-fold: 1) the “Haldane effect” where CO2 transport is reduced because of oxyhemoglobin’s lower affinity for CO2 reducing the bloods buffering capacity ultimately eliminating up to 30% of CO2 removal from the blood (Marczak & Pokorski, 2004); 2) Because of the “Haldane effect” the resultant drop in CBF (~14-24%) may lead to elevated levels of CO2 in the brainstem which stimulates the central chemoreflex  (Hoiland et al., 2014); 3) inhibition of endothelium nitric oxide via hyperoxic release of free-radicals (Pohl, 1990; Rubanyi & Vanhoutte, 1986); and 4) the  potential for an inverse relationship between CaO2 and CBF (Brown et al., 1985) may cumulatively or independently result in cerebral vasoconstriction whilst in a hyperoxic environment.   Partial pressure of arterial carbon dioxide  The cerebrovascular response to altered PaCO2 is significantly more sensitive than the CBF response to PaO2 (Kety & Schmidt, 1948a; Severinghaus et al., 1966; Shapiro et al., 1970; Willie et al., 2012). The entire cerebrovasculature, from the pial vessels (Rebel et al., 2003; Wolff et al., 1930) to the intra-cranial (Coverdale et al., 2014; Ogawa et al., 1988; Verbree et al., 2014; Willie et al., 2012) and extra-cerebral (Figure 4 (Sato et al., 2012; Willie et al., 2012)) conduit arteries, are sensitive to changes in PaCO2 (Willie et al., 2014c). Typically, the slope of the cerebrovascular response to CO2 is approximately 3-5% increase per mmHg rise in PaCO2 above rest and 1-3% reduction per mmHg fall   15 below resting PaCO2 [reviewed in Willie et al. (2012)].   Interestingly, although similar responses to hypercapnia are observed in the anterior and posterior circulations, during hypocapnia the posterior circulation response (i.e., VA reactivity) is greater compared with the anterior circulation (i.e., ICA; Fig 2.4; (Willie et al., 2012)). However, no differences were observed between VA and ICA reactivity over the entire hypocapnic and hypercapnic PaCO2 range (i.e., 16 – 62 mmHg) (Willie et al., 2012). In contrast, Sato et al. observed a reduced CO2 reactivity in the VA compared to the ICA over the entire hypocapnic and hypercapnic PaCO2 ranges (i.e., 21 – 53 mmHg). It is unclear if the differences between these studies is related to the larger range of PaCO2 used in (Willie et al., 2012).  Regardless, the observed regional differences in PaCO2 reactivity are not a universal finding.     16   Figure 2.4. A) Extra-cerebral blood flow responses (Q) in the internal carotid (ICA) and vertebral  (VA) arteries and B) cerebral blood flow velocity responses (CBV) in the middle and posterior cerebral arteries to fluctuations in isoxic PaCO2; C) Relative changes in vascular PaCO2 reactivity through the hypercapnic, hypocapnic and entire PaCO2 (overall) range.  * p < 0.05 from baseline, † p <0.05 (ICA vs VA; MCA vs PCA), Ø p<0.05 from ICA, ‡ p<0.05 from VA.  Adapted, with permission, from Willie et al. (2012).   Q (ml.min-1) CBV  (cm.s-1) PaCO2 (mmHg) PaCO2 (mmHg) %.mmHg-1 PaCO2 Overall Hypercapnia Hypocapnia ø"ø" ‡" ‡""ø"A B C   17 The magnitude of cerebral vasoconstriction and vasodilation during hypocapnia and hypercapnia, respectively, are also largely dependent on the regulation of extracellular pH.  Hydrogen ions (H+) induce relaxation on cerebral vascular smooth muscles, resulting in vasodilation during acidosis and vasoconstriction during alkalosis (Kontos et al., 1977). The primary molecule responsible for CO2 transport and pH homeostasis is the bicarbonate (HCO3-) ion; this molecule forms the conjugate base used to buffer H+ forming carbonic acid when catalyzed by carbonic anhydrase yielding CO2 and water (CO2 + H2O !H2CO3! H+ + HCO3-) or vice versa. Because PaCO2 rapidly diffuses across most physiological membranes but H+ and HCO3- do not readily diffuse across the blood brain barrier into the vasculature, it influences cerebral smooth muscle tone by determining the extracellular and potentially intracellular pH (Lassen, 1968). When Kontos et al. (1977) manipulated feline cerebral spinal fluid CO2 while maintaining pH, and vice versa, vessel caliber was only altered during fluctuations in pH.  In contrast, when CBF is increased during hypercapnia, and sodium bicarbonate supplementation was used to reverse the PaCO2 induced acidemia, no change in CBF was observed (Lambertsen et al., 1961).  Combined, these studies indicate that the control of CBF from extracellular pH and PaCO2 is an integrative system influencing smooth muscle tone, and highlights just one of the myriad of redundancies involved in regulating cerebral metabolic homeostasis.  Cerebral blood flow regulation at high altitude The influence of PaO2 on CBF, as discussed above (section 2.2.2.1. Partial pressure of arterial oxygen) is contingent on the balance between the degree and duration of   18 hypoxemia and hypocapnia. Therefore, the extent to which cerebrovasculature responds to high altitude is dependent on four key integrated reflexes: 1) hypoxic cerebral vasodilation; 2) hypocapnic cerebral vasconstriction; 3) hypoxic ventilatory response; 4) hypercapnic ventilatory response (reviewed in detail by Ainslie & Subudhi (2014)). Moreover, because of the respective importance of pH and CaO2 on the hypercapnic ventilatory and cerebral vasodilatory responses, coupled with the acclimatatory changes in pH and CaO2 over time, the outcome of the CBF response to high altitude can be grouped into two time domains: 1) acute hypoxia (seconds to hours); and 2) short- to long term hypoxia [days to years (Ainslie & Ogoh 2010)].  Eight studies have measured CBF during acclimatization to HA (> 3400 m; Figure 2.5) using a variety of techniques (e.g., Kety Schmidt, Xe133, vascular ultrasound, TCD, and TCCD) to identify consistent increases in CBF following exposure to HA; however, the degree of hypoxia and duration of time at altitude is inconsistent and variable (Baumgartner et al., 1994; Huang et al., 1987; Jensen et al., 1990; Lucas et al., 2011; Rupp et al., 2014; Severinghaus et al., 1966; Subudhi et al., 2014; Willie et al., 2014b). Within the first few days exposure to HA, CBF was significantly elevated in each of these studies (~ 16 - 60 %) offsetting the hypoxemic-induced reductions in CaO2 in order to maintain CDO2.  Although the mechanisms are unclear, the temporal changes in CBF at HA appear to be directly related to the maintenance of CDO2 (Ainslie & Subudhi, 2014; Subudhi et al., 2014).  Figure 2.5. The percent change in cerebral blood flow (∆% CBF) during acclimation (> 4 days above 3400m) in the seven studies at various altitudes reviewed in (Ainslie & Subudhi, 2014), and one recent investigation following 5 days at 4350m (Rupp et al., 2014).Days at given altitude ∆ %CBF *"*"*"Rupp 2014 (4350 m) Severinghaus 1966 (3810m) Huang 1987 (4300m) Jensen 1990 (3475m) Baumgartner 1994 (4559m) Lucas 2011 (5050m) Willie 2013 (gCBF; 5050m) Willie 2013 (TCD; 5050m) Subudhi (2013 (5260m)   20  Considering the importance of PaCO2 in augmenting the cerebrovascular response to normobaric hypoxia (Cohen et al., 1967; Ogoh et al., 2013; Willie et al., 2012), the elevated CBF during initial exposure to high altitude, at first glance, appears paradoxical and variable (Severinghaus et al., 1966).  However, it is well established that individual variability in hypoxic and hypercapnic ventilatory sensitivities influence the onset of ventilatory acclimatization (i.e., degree of increased PaO2 and decreased PaCO2) (Dempsey & Forster, 1982).  A recent study shows that the onset of ventilatory acclimatization and combined metabolic compensation of the respiratory alkalosis over time result in a ‘resetting’ of CBF to hypocapnia (Willie et al., 2015).   2.2.3. Cerebral metabolism and neurovascular coupling  Research for over 100 years has been attempted to understanding how cerebral tissue metabolism and the cerebrovasculature cohesively interact to maintain an adequate supply of metabolic nutrients required for cerebral vascular functioning (Roy & Sherrington, 1890).  Over this time scientists have identified the primary macromolecules contributing to cerebral energy metabolism (i.e., oxygen, glucose and lactate), as well as their respective metabolic rates.  Despite this knowledge of the link between cerebral perfusion and cortical activity, identifying all of the complex components and pathways involved has proven problematic.  A great deal of progress has been made regarding in vitro imaging techniques, yet controversy still exists regarding the specific metabolic responses to physiological changes in the PaO2 and PaCO2, as well as the degree to which cerebral metabolism and CBF co-relate (Gordon et al., 2008). With particular focus on humans, the following sections will attempt to highlight the relative contribution of   21 oxygen, glucose and lactate to cerebral metabolism and how these substrates are utilized to maintain cerebral functioning during changes in PaO2 and PaCO2. Additionally, discussion of the key molecules and mechanisms that are known to either corroborate or refute the hypothesis that CBF and metabolism are linked will also be highlighted.   Cerebral metabolic rate  The cerebral metabolic rate is derived from the theory that the product of the CBF and the arterial venous differences indicate the volumetric metabolic rate of the primary substrates (e.g., oxygen, glucose and lactate) (Kety & Schmidt, 1946). Although the importance of blood flow to matching nutrient delivery to sustain organ metabolism has been well known for over a century (Barcroft, 1914), demonstrating this in the brain, and the role each nutrient plays in triggering the neurovascular or neuro-metabolic response, remains controversial (Attwell et al., 2010; Gordon et al., 2008; Howarth, 2014).   Cerebral ATP production is dependent on a continuous supply of oxygen, glucose and lactate. However, each substrate is delivered and consumed by the brain heterogeneously, with little consensus on the specific responses of cerebral metabolic substrate response to changes in arterial blood gases in humans and animals. The following sections discuss the respective cerebral metabolic rates of oxygen, glucose and lactate and the evidence for and against the involvement of CBF in maintaining normal cerebral metabolic functioning.       22 Cerebral metabolic rate of oxygen  The volume of whole body consumption of oxygen (VO2) at rest is typically 200-300 ml.min or in relation to whole body, assuming a mass ranging from 60 -100 kg, resting whole body 2.0 – 3.0 ml.kg-1.min-1.  The average resting cerebral blood flow is 54 ml.100g-1.min-1 and cerebral metabolic rate for oxygen (CMRO2) is ~3.3 ml.100 g-1.min-1 (or ~1.5 mmol.100g-1.min-1); therefore, assuming an average brain mass of 1.4 kg, the brain utilizes nearly 15-20 % of the total oxygen consumed by the body (Kety & Schmidt, 1948a). Despite the substantial energy demand and known increase in CBF with hypoxia, CMRO2 remains fairly stable during a brief exposure to isocapnic hypoxia [e.g., PaO2 = 36 mmHg; (Ainslie et al., 2014)] or following 6-12 hours at moderate (3700m) altitude (Severinghaus et al., 1966).   Although no change in CMRO2 has been reported during modest hypocapnia (PETCO2 = 20 mmHg), it was reduced during profound (PETCO2 = 10 mmHg) hypocapnia (Alexander et al., 1968).  However, controversy exists regarding the CMRO2 response to hypercapnia.  Early data from animal models indicate that CMRO2 was elevated [+25%; (Berntman et al., 1979)], unchanged (Eklöf et al., 1973) or reduced [10 – 40%(Artru & Michenfelder, 1980; Kliefoth et al., 1979) during hypercapnia. Unfortunately nearly thirty years later, despite substantial progress using in vivo techniques to measure the cerebral haemodynamic and metabolic responses in humans, the same controversy remains. A featured editorial by Yablonskiy et al. (2011) summarizes the findings that indicate a reduction (Xu et al. 2011) or no change (Chen & Pike, 2010; Jain et al., 2011) in CMRO2 during hypercapnia in humans. It should be noted, however, that when   23 compared over a range of PaCO2 (+10 versus -10 mmHg) CMRO2 is significantly reduced during hypercapnia (~20%) (Chen & Pike, 2010).  The lack of proportional increases in CMRO2 following the fluctuations in CBF observed during hypoxia and hypercapnia demonstrates the stability of CMRO2 during moderate changes in CBF at rest.  Cerebral metabolic rate of glucose  Glucose is the main substrate for cerebral energy metabolism, and the only substrate capable of maintaining whole brain functioning during rest and activation (Clarke & Sokoloff, 1999). Similar to the demands of cerebral oxygen, the brain is also dependent on a constant supply of glucose such that the cerebral glucose delivery (CDGlu) is in excess of its respective metabolic rate. Assuming a cerebral glucose extraction of 10% from the arterial blood (Rowe et al., 1959), and a global CBF of 57 ml.100g.min, the first estimates of cerebral glucose metabolism (CMRGlu) were 31 µmol.100g-1.min-1 (Kety & Schmidt, 1948b).  These calculated values were eventually confirmed to be within range of the CMRGlu values when first reported by Reivich et al. (1979) and Heiss et al. (1984) using positron emission tomography (PET). Interestingly, during rest, alterations in PaO2 (eg; hypoxia and hyperoxia) do not alter CMRGlu, despite changes in CBF (Ainslie et al., 2014). In contrast, during hypercapnia (+10 mmHg PaCO2) CMRGlu is reduced and is inversely related to elevations in CBF (Willie et al., 2015). Additionally, only one study has reported CMRGlu following acclimatization to HA (5260m); here, CMRGlu was unchanged compared with SL values (Möller et al., 2002). Exploration of the punitive   24 mechanisms and confirmation via more advanced imaging techniques in humans are needed.   Cerebral metabolic rate of lactate  The cerebral metabolic rate of lactate (CMRLac) is negligible at rest to an extent that the brain is reported to have a net release versus a net uptake of lactate (CMRLac= -2.4 to -0.4 µmol.100g.min, (Ainslie et al., 2014; Madsen et al., 1995b; Rasmussen, 2008).  This is primarily due to the low concentrations of lactate in the blood, and relatively limited transport across the blood-brain barrier compared with glucose (Knudsen et al., 1991). This, coupled with the significantly less efficient ATP-production elicited from lactate versus glucose metabolism, indicates that lactate may not be a required systemically derived fuel source to maintain normal brain functioning (Knudsen et al., 1991). Therefore, systemic utilization of lactate as a fuel is primarily only regarded as a cerebral fuel source during elevated cortical activation, and when arterial lactate concentration is sufficiently high. For example, large increases in lactate are primarily only observed during exercise, and thus at rest are not expected to alter global cerebral metabolism. The influence of exercise on CMRLac is reviewed in Section 2.3.6.3.   Substrate utilization at sea-level and high altitude  Changes in global cerebral metabolism as discussed above are important for identifying the relationship between substrate delivery and demand; however, given the wide array of metabolic substrates, it is also important to express the proportional contribution of each of these substrates to cerebral metabolism. Therefore, the ratio of oxygen to glucose   25 (OGI) and oxygen to carbohydrate (OCI, lactate and glucose) utilization at rest – assuming a perfect 1:1 ratio (complete substrate oxidization) - would result in a value of 6 (see chapter 5 for further detail).  Although fluctuations near this average are frequently observed, an average resting value of 5.7 has been expressed (Cohen et al., 1967; Dalsgaard et al., 2004b; Larsen et al., 2008; Seifert et al., 2009b).  Typically, this value is relatively stable during resting conditions, and is unchanged during mild hypoxia (Volianitis et al., 2008).   Neurovascular coupling  Neurovascular coupling (NVC) is a form of functional hyperemia involving the cerebral tissue and vasculature, where increased neuronal activity elicits an increase in cerebral blood flow (Fox & Raichle, 1986). The traditional theory describing NVC at first glance portrays a delicate balance between oxygen delivery and CMRO2. For example, CMRO2 and CBF respond proportionally to changes in one or the other through a local negative feedback system.  The metabolic system would respond to reductions in ATP used to restore ion gradients following synaptic activation, which in turn released a metabolic signal (i.e., insufficient O2, glucose or increasing CO2), which would elevate CBF to match demand. The delicate nature of this relationship is attributed primarily from the finding that ATP production ceases almost immediately following the cessation of CBF (Leithner & Royl, 2013). However, when Fox & Raichle (1986) demonstrated an uncoupling between CBF and CMRO2 (i.e., 29% increase in CBF versus 5% increase in CMRO2) during focal cortical activation four alternative postulates needed to be considered regarding the involvement of O2 in NVC.  These postulates are as follows: 1)   26 small increases in CMRO2 are dependent on large increases in CBF because of physical limitations of cerebral oxygen delivery (Buxton & Frank, 1997; Mintun et al., 2001); 2) the lack of homogenous oxygen diffusion along cerebral capillaries requires a greater increase in CBF to maintain oxygen delivery to the distant areas of cerebral vascular beds (Jespersen & Østergaard, 2012); 3) the excessive CDO2 compared with CMRO2 has evolved as a safety reserve mechanism to consistently supply the brain with supra-sufficient oxygen supply for emergency situations (Attwell et al., 2010; Howarth, 2014); and 4) the evolutionary adaption of the large increase serves to do more than maintain adequate oxygen delivery (i.e., removal metabolic bi-products and/or delivery of other metabolic nutrients) and works in conjunction with a feed forward system that regulates CBF upon initiation of neural activation (Howarth, 2014). A feed forward system would require that neuronal activity release a cascade of vasoactive metabolites, either from neural synapses or transmitted through nearby astrocytes onto the cerebral blood vessels resulting in an increased CBF.  The PaO2 and the availability of lactate, NO, ATP and adenosine have all been shown to have an influential role in the polarity of the neuronal astrocytic control of vascular smooth muscle. These topics have been reviewed in detail elsewhere [see: (Gordon et al., 2008; Howarth, 2014)] and are beyond the scope of this thesis.  2.2.4. Blood pressure   Although the mechanisms remain obscure, cerebral pressure-flow relationships or autoregulation refers to the physiological mechanisms that act to keep cerebral blood flow (CBF) constant during changes in blood pressure. On a continuum, static CA is efficient at buffering lower frequency fluctuations and higher frequency fluctuations are   27 counteracted via dynamic mechanisms that exhibit a greater gain. In other words, slow changes in mean arterial blood pressure (MAP) are counteracted effectively; whereas larger, faster changes in MAP results in a similar directional change in CBF.  The maintenance of CBF over a wide range of pressure fluctuations (CA) was first described by Lassen et al. (1959); stating that a stable maintenance of CBF over a large range of MAP (ie., 50 - 150 mmHg) was achieved from opposing fluctuations in CVR, where as passive fluctuations in CBF occur outside of the regulatory thresholds.  However, this figure has in the last 30 years been criticized for its conceptualization using a limited number of data points from different studies (rather than within-subject comparisons), flawed methodology and incorrect interpretation (Heistad & Kontos, 1983). Recent experiments (Lucas et al., 2010), along with re-interpretation of Lassen’s original curve (Heistad & Kontos, 1983) indicates that the CBF is more pressure passive than originally thought (0.82 % ∆CBF. mmHg ∆MAP-1; Figure 2.2).  Consequently, is has been suggested that a plateau region does not exist, or it exists within a much smaller range [i.e., ± 5-10 mmHg from baseline; (Tan, 2012)]. Furthermore, Numan et al. (2014) identified that cerebral vascular resistance is more effective at maintaining CBF during increases in MAP compared with decreases (Figure 2.2), however this difference is largely accounted for when studies corrected for changes in PaCO2. The mechanisms proposed for the pressure flow relationship are multifactorial and likely include myogenic, neurogenic, metabolic, and endothelial factors potentially influencing cerebrovascular resistance either independently or in combination [reviewed in; Tzeng & Ainslie (2014)]. Identifying the “normal” auto-regulatory range, given the multitude of factors listed previously, is difficult to establish.  For instance, since the arterial   28 baroreflex effectively functions within the autoregulatory range (Lucas et al., 2010), many of the studies utilizing vasoactive drugs or inducing of central hyper or hypovolemia may contaminate the CBF response via a baroreflex mechanism. Moreover, it is likely that autoregulation differs greater between and within subjects and environmental conditions.  2.2.5. Distribution of cardiac output  At rest, while supine, the brain receives approximately 12-15% of total cardiac output. However, assuming an upright position (i.e., standing) presents an initial orthostatic challenge that requires a myriad of homeostatic cardiovascular adjustments to avoid cerebrovascular insult and ultimately syncope.  The baroreflex mediated increase in heart rate upon standing serves to transiently increase cardiac output, but is insufficient to maintain cerebral perfusion in spite of the large reduction in cardiovascular resistance (MAP/Q) (Thomas et al., 2009).   Moreover, upright posture may also increase minute ventilation (VE) consequently reducing PaCO2 and further exacerbating the reductions in CBF. However, in most healthy individuals, CBF remains stable when assuming the upright position after the initial hypotension phase is over; the onset of syncopal symptoms are more of an issue of falling MAP and reduced vascular resistance than a redistribution of cardiac output (Madsen et al., 1995a). Nevertheless, the exact role that cardiac output, or rather redistribution of cardiac output has on CBF independent of MAP, has been attempted by only a select few lower body negative pressure in order to induce central hypovolemia and manipulate CO (Brown et al., 2003; Guo et al., 2006; Ogoh et al., 2005a; van Lieshout et al., 2001; Van Lieshout et al., 2003).  However,   29 experimentally this is problematic since each of these responses results in augmentation of other regulatory factors.  Despite a maintained MAP near resting levels during mild-moderate negative pressures it is difficult to ascertain if the drop in CBF is a result of the drop in cardiac output or PaCO2 in these studies.  Recently, it has been demonstrated that when hypocapnia was prevented during LBNP, the fall in CBF was attenuated in contrast to the reduction in cardiac output (Lewis et al., 2014b). Together, at least at rest, the importance cardiac output plays in CBF regulation is at best an indirect factor and cannot be separated from other reflex factors (MAP, PaCO2) that are know to effectively influence CBF.  2.2.6. Neurogenic innervation    Neural innervation of the major cerebral arteries was first introduced by Sir Thomas Willis as early as 1664; however, a clear role of neural regulation of CBF is still controversial  [reviewed in Hamner & Tan (2014)and (Willie et al., 2014c)]. Both small and larger cerebral vessels have abundant sympathetic alpha (Bevan et al., 1987) and beta (Tsukahara et al., 1986)) and parasympathetic (cholinergic) receptors (Forbes, 1928), which may result in disparate vascular responses based on the density, location and type of receptor being stimulated (Bevan et al., 1987; Fitch et al., 1975; Nielsen & Owman, 1967; Tsukahara et al., 1986). More specifically, sympathetic stimulation of alpha receptors can result in vasoconstriction of large cerebral arteries (Bevan et al., 1987) and a consequent reduction in CBF (Figure 2.2). In contrast, vasodilation is reported to occur following sympathetic simulation of beta receptors of the smaller vessels pial vessels;   30 (Bevan et al., 1987; Fitch et al., 1975). The functional significance of these segmental changes in resistance has on global and regional CBF in humans is unclear.  The putative influence of sympathetic regulation on the cerebrovasculature, at least in humans, assessed by either utilizing the removal of the sympathetic ganglion or following pharmacological blockade of the ganglia or systemic sympathetic receptors.  A total of nine studies observed an increase in CBF during ganglionectomy or blockade (reviewed in (Willie et al., 2014c)).  Three studies indicated no change (Harmel et al., 1949; Ohta et al., 1990; Scheinberg, 1950) and one study (Kang et al., 2010) indicated a decrease in CBF. The discrepancies may be the result of only a partial block of sympathetic innervation from the use of local anesthesia in the three studies showing a reduction in CBF.  On the basis of these studies, there appears to be evidence for cerebral sympathetic-induced vasoconstriction; however, due to obvious difficulties in accessing sympathetic nerves that innervate the cerebrovasculture in healthy humans identifying the exact role sympathetic innervation plays in regulating and maintaining CBF at rest remains elusive.  Animal models (Cassaglia et al., 2009) implicate the role of sympathetic innervation of the cerebrovasculature to serve as a protective mechanism to maintain CBF during abrupt changes in perfusion pressure. However, limitations in the human model stem from the inability to discern the effects of sympathetic antagonists on the cerebral versus the peripheral vasculature during pharmacological blockade. The latter has the potential to influence CBF regulation via afferent nervous inputs (Braz et al., 2014), baroreflex mediation (Chien, 1967) and or secondary peripheral   31 cardiorespiratory interactions [i.e., augmented arterial blood pressure and/or PaCO2 (Hartwich et al., 2010)].   The impact of cholinergic regulation in human CBF is also unclear. One study reported that, although clinical i.v. doses of glycopyrolate (cholinergic blockade) did not alter resting MCAv, there were subtle changes in transfer function metrics (elevations in coherence) (Hamner et al., 2012).  However, the utility of transfer function analysis merely suggests that MCAv may be influenced by either adrenergic constriction (Hamner et al., 2010) or cholinergic dilation (Hamner et al., 2012), doing little to identify the individual influences these neural innervations may have on CBF regulation at rest. Moreover, reporting of a sole transfer function metric (e.g., coherence) does not provide an accurate description of the pressure-flow relationships (Tzeng et al., 2012; Tzeng and Ainslie, 2014).    32 2.3. Cerebral blood flow response to exercise  Similar to rest, the primary functioning of the human circulation during exercise is to: 1) ensure an adequate delivery of oxygen and metabolic nutrients to fulfill the increased demand of tissue metabolism and the consequent removal of metabolic end-products; and 2) regulate systemic arterial blood pressure such that adequate organ specific perfusion pressure is met.  Therefore, it is not surprising that the cardiovascular and respiratory response to exercise perturbs almost all of the regulatory factors involved in regulating CBF.  Whole body oxygen consumption, MAP, heart rate, cardiac output, and metabolism all increase, albeit each with different magnitudes, during exercise (Figure  2.6). In contrast, PaCO2 increases and decreases based on the level of alveolar ventilation. Additionally, the balance between sympathetic and parasympathetic neural control of the entire cardiovascular system is altered during exercise [extensively reviewed in  (Fisher et al., 2015) and (White & Raven, 2014)].  Exposure to high altitude, as discussed in sections 2.2.2.3, can perturb each of these regulatory factors during exercise, where the blunting of one factor may be the result of an exacerbation of an factor (i.e., hypocapnic vasoconstriction versus hypoxic vasodilation) or vice versa.  The following sections will attempt to describe in detail the historical evolution of quantifying the cerebrovascular response to incremental exercise. Focus will also be made to describe the individual and interactive factors involved in regulating CBF during exercise, both at sea level and high altitude.    33  Figure 2.6. Generalized relative changes in cardio-respiratory (cardiac output [CO], partial pressure of arterial carbon dioxide [PaCO2] and arterial oxygen content [CaO2]), cerebrovascular (cerebral perfusion pressure [CPP], global cerebral blood flow [gCBF], cerebral oxygen delivery [DO2]), and metabolic (oxygen extraction fraction [OEF], cerebral metabolic rate of oxygen [CMRO2]) responses to incremental exercise. The dotted line signifies the point at which ventilatory threshold is typically crossed during exercise. Exercise intensity  Max Rest CMRO2 OEF -100 100 0 0 100 -100 gCBF CPP CO PaCO2 CaO2 0 100 -100 0 100 -100 0 100 -100 Percent ∆  D02 0 100 -100   34 2.3.1. A historical review of the cerebral circulatory response to exercise  Cerebral blood flow measurements were first achieved during supine exercise shortly after the first measurement of CBF was achieved by Kety-Schmdit using the nitrous oxide technique (Scheinberg et al., 1953; Kleinerman & Sokoloff, 1953; Lambertsen et al., 1953; Scheinberg et al., 1954; Kleinerman & Sancetta, 1955).  Only one of these studies reported that CBF was significantly elevated during exercise.  Here, Kleinerman & Sokoloff (1953) observed an 18% increase in gCBF during moderate intensity supine exercise (ie; ~15-20% of  VO2 max).  Where as, Scheinberg et al.  in (1953) and  (1954) both reported non-significant CBF increases of 10% and 5%, respectively, during light intensity supine exercise. Unfortunately, the later study by Scheinberg et al. (1954) measured basal CBF in the supine position before comparing the exercise response in the upright position, potentially underestimating the CBF response by 10-15%. Similarly, Lambertsen et al. (1959) observed no change in the mean CBF during supine exercise; however, the variable reductions in PaCO2 (ranges from -0.9  to -11 mmHg) during exercise indicates that subjects were exercising over a wide range of relative exercise intensities potentially confounding the results. The only study investigating continuous light intensity supine exercise (20 min at 10% maximum achieved workload) reported a reduction in both PaCO2 (~ 2mmHg) and CBF [-13%; (Kleinerman & Sancetta, 1955)].  The potential factors responsible for these contrasting reports from these early studies are three-fold: 1) The CBF response appears to be intensity related, requiring a minimum of an 15% increase in workload to elevate CBF; 2) methodological issues associated with measuring baseline flows in the supine position while some exercise measures were   35 performed in the upright position; and 3) variability in the respective relative individual exercise capacities and fluctuations in PaCO2 could be confounding the findings resulting in either an unchanged (Lambertsen et al., 1959) or reduced (Kleinerman & Sancetta, 1955)) CBF response to exercise. Lastly, one of the limitations of using the Kety-Schmidt technique to observe CBF during exercise is the requirement for a 10-minute steady state period. This latter influence limits the maximal range of exercise intensities to observe CBF without introducing a myriad of factors including thermal stress, fatigue and metabolic changes not related to those that occur during an acute bout of exercise to exhaustion.  The utilization of radioactive tracers (e.g., Xe clearance and radio labeled erythrocytes) and gamma detection (see Figure 2.7) improved the resolution of CBF imaging over the next 30 years, thus allowing CBF measures during incremental exercise. Three studies were published during this time using the Xe clearance technique.  One study reported an unchanged CBF (Globus et al., 1983) and two observed an increase in CBF ranging from 13% (Herholz et al., 1987) to 26% (Thomas et al., 1989) above basal values during light intensity semi-recumbent cycling exercise (20% Wmax). The increases in CBF were similar to those observed by researchers utilizing the nitrous oxide washout technique [~ +15 ± 10 % ; Zobl et al. (1965)] as well as those utilizing radio labeled erythrocytes, injected directly into the ICA, during light intensity exercise [~18% >(Hedlund et al., 1962)].  Further increases in exercise intensity (i.e., light to moderate) potentiated the elevated CBF (~ +33%; Herholz et al. (1987; 1989), whilst maximal intensity exercise (> 70% Wmax) failed to induce further elevations in CBF from basal values (Thomas et al.,   36 1989).  The potential variance in the magnitude of the CBF response to exercise using the radioactive tracer contrasts (i.e., Xe and erythrocytes) is two-fold:  1) in order for the gamma camera to detect the radioactive tracers and quantify CBF requires that the subjects head to remain motionless making it difficult to measure CBF at maximal intensity without introducing motion artefacts that may elevate or reduce CBF measures; and 2) because the entire body is subjected to venous injections of a radiolabelled isotope, quantification of CBF using gamma detection can be influenced by skin blood flow through the scalp.  However, given that skin blood flow increases with the thermal stress of exercise, Thomas et al. (1989) utilized a special cooling cap (-20 C) to maintain scalp temperature during exercise to demonstrate that skin blood flow did not alter the relative increase in gCBF during maximal exercise intensities (~ 86% Wmax). In summary, the collective consensus using a myriad of techniques indicates that CBF is elevated from baseline values during mild to moderate intensity exercise, and does not increase further at maximal exercise intensities.  The last 25 years, with the advancement of transcranial Doppler (TCD) and vascular ultrasound, has given rise to a new era of CBF measurements during exercise.  Continuous beat-to-beat measurement of CBV during exercise - as well as interventions to additionally alter blood gases (e.g., hypoxia and hypercapnia), neural innervation (e.g., pharmacological inhibition and stimulation), and blood pressure (e.g., LBNP and fluid loading)- have investigated the regulatory contributions to CBF and cerebral metabolism during exercise. Huang et al. (1991) measured ICA velocity (ICAv) and observed a similar directional, albeit a lesser relative increase (+ 16%), to incremental exercise   37 compared with the gCBF response (+ 26%) reported by Thomas et al. (1989) using the Xe approach.   A similar variation of the CBF response was observed by Jorgensen et al. (1992a) who compared the intracranial velocity (i.e., MCAv) response using transcranial Doppler, versus with the gCBF response measured with Xe clearance technique during light (30 W), moderate (60 W) and submaximal (149 W) exercise intensities. When compared with CBF, the authors found that the increase in MCAv from basal values was either lower (if indexed using the flow compartment model) or equivalent  (if using initial slope index) (Figure 2.7).  Regardless of the measurement used, Jorgensen et al. (1992b) observed a similar plateau in both CBF and MCAv at or above moderate workloads (i.e., > 60% maximum achieved workload [%WMax]). These findings, coupled with a similar submaximal exercise response, provided the first evidence that TCD was a viable non-invasive technique useful in quantifying the CBF response to exercise.     38     Figure 2.7:  The experimental setup for early cerebral blood flow assessment (percent change in cerebral perfusion [% ∆]) using the [A] Xe clearance technique [C; flow compartment model (FCM) and initial slope index (ISI)] and [B] and transcranial Doppler [B, middle cerebral artery (MCAv)] during exercise with increasing workload.  Images adapted with permission, from Jorgensen et al. (1992b) and Thomas et al. (1989).     A B C   39 The last piece of the puzzle, with regards to quantifying the cerebrovascular response to exercise, was observing the entire CBF progression (Figure 2.8) during exercise; i.e., beginning from rest to incremental exhaustion.  The following two studies used two distinctly different protocols to achieve exhaustion: 1) Hellström & Wahlgren (1993) measured MCAv while increasing the cycling exercise intensity (+50 W) every two minutes until 225 W was achieved; following this subjects were asked to continue cycling at this workload until exhaustion (total duration: 10-15 min); 2) Moraine et al. (1993) measured CBF during a continuous incremental maximal exercise protocol, during which subjects exercised with increasing intensity every 4 minutes until exhaustion (total duration: 16-26 min). Figure 2.8 illustrates the mean response taken from the 14 studies that have investigated CBV (MCAv, ICAv) during incremental exercise since Hellström & Wahlgren (1993) and Moraine et al. (1993). This summary graph highlights the CBF response to incremental exhaustive exercise, which can be described as resembling an inverse parabola.  Out of the other 12 studies, eleven (Brugniaux et al., 2014; Fisher et al., 2013; Hellstrom et al., 1996; Huang et al., 1991; Imray et al., 2005; Marsden et al., 2012; Olin et al., 2011; Smirl et al., 2012; Subudhi et al., 2008; Subudhi et al., 2011) observed significantly elevated MCAv values from rest during the two submaximal exercise intensities (20-80% VO2max) followed by a drop in CBF from the respective peaks during the progression towards maximal exercise intensities. Brugniaux et al. (2014) describes the CBFv response to exercise as a bi-phasic response where: 1) increases in exercise intensity until approximately 60% VO2max results in progressive elevations in CBFv; and 2) with further increases in exercise intensity produce a progressive reduction in MCAv from the previous intensities.   40 Contrary to this, in a study where eight participants performed an incremental bout of recumbent cycling to exhaustion (239 W ± 42 W), Larsen et al. (2008) observed that mean relative change in MCAv was 27 ± 17% elevated above basal values following 5 minutes at 100% WMax, despite a variable but significant hypocapnia (-8 ± 4.2 mmHg of PaCO2 from baseline). It is difficult to distinguish whether or not the recumbent position altered the cerebrovascular reactivity to hypocapnia at 100% Wmax leading to a maintained CBF, or if using the MCAv as an index of CBF is adequate during a 5 min bout of recumbent hypocapnic cycling at 100% Wmax given the potential for changes in vessel caliber during hypocapnia (see section 2.2.2.2). Nevertheless, the consensus response observed in figure 2.8 (10 out of 13 findings) provides convincing evidence for the distinct inverted parabolic pattern of CBV during progressive incremental exhaustive exercise.  41  Figure 2.8. Percent changes in cerebral perfusion from rest, during incremental exercise from mild (20-40% Wmax) moderate (50-80% Wmax) and maximal (90-100% Wmax) intensities.  Values are reported as a mean observed in the 13 studies known to date to have examined changes in CBV (using transcranial Doppler) during exercise to exhaustion. Red numbers indicate average PaCO2 values.-20% -10% 0% 10% 20% 30% 40% 50% Mean Brugniaux et al. (2014) Fisher et al. (2013) Smirl et al. (2012) Subudhi et al. (2011) Marsden et al. (2012) Subudhi et al. (2008) Olin et al. (2011) Imray et al. (2005) Hellstrom et al. (1996) Hellstrom et al. (1993) Moraine et al. (1993) Larsen et al. (2008) Fan et al. (2013) Trangmar et al. (2014) Mild Moderate Maximal Exercise Intensity % ∆ Cerebral Perfusion 37#42#31#  42 In addition to identifying the accurate CBF response to exercise over the past 60 plus years research investigations have also attempted to identify the regional distribution of CBF during exercise. At this point, it should not be surprising that early exploration into the regional CBF response using the myriad of techniques to quantify CBF (i.e., Xe clearance versus TCD versus vascular ultrasound) have resulted in discrepant findings. Herholz et al. (1987) observed similar increases in CBF, from basal values, throughout the various regions of the anterior and posterior circulation (i.e., frontal, parietal, temporal, central and occipital cortices) at 25 and 100 W (10-20 and 15-30 %) of cycling exercise.  Whereas Jorgensen et al. (1992a) compared anterior cerebral blood flow velocity (ACAv) and MCAv during incremental cycling exercise – here, the authors observed that increases in MCAv were greater than ACAv. The authors suggested that the elevated MCAv response to exercise, compared with the ACAv, indicated that MCAv contributes a greater portion of blood flow to the specific cortices (i.e., frontal, central, parietal and temporal) involved in controlling muscular effort during cycling where as the ACA supplies cortical areas involved in activities that differ in motor control.  In a different study, Sato et al. (2011) utilizing vascular ultrasound convincingly demonstrated that flow through the ICA (QICA) mimics the inverted parabolic velocity profile of the MCA during incremental recumbent cycling (80% WMax). In contrast, the relative increase in VA flow (QVA) was significantly greater than QICA and MCAv at 40, 60 and 80% Wmax (Figure 2.9).   Willie et al. (2011b) also observed a greater relative increase in PCAv compared with MCAv during constant load exercise (i.e., 40 min at 60% Wmax). Considering the regional differences observed at rest with altered arterial   43 blood gases (reviewed in sections 2.2.2.1 and 2.2.2.2), it appears that little is known regarding the influence arterial blood gases may play in the regional response to exercise.     44     Figure 2.9. The percent change of cerebral blood velocity (CBV) and flow (CBF) through the middle cerebral (MCAv) internal carotid (ICA) and vertebral (VA) arteries, as well as the global CBF (gCBF = [ICA x 2] + [VA x2]) during incremental exercise to 80% of the maximum achieved workload (%WMax).  Findings are adapted from (Sato et al., 2011).    0% 10% 20% 30% 40% 50% 60% 70% MCAv ICA VA gCBF 40 60 80 Workload (%Wmax) Relative cerebral perfusion (%)   45 The following section will attempt to explain the three primary factors that may influence the CBF response to incremental exercise: 1) The importance of arterial blood gases; 2) inconsistent influence of blood pressure, cardiac output and neural control; and 3) uncoupling of CBF and metabolism during incremental exercise to exhaustion.  These topics will be discussed in the context of CBF regulation both at sea-level and - where data are available - at high altitude.  2.3.2. Influence of arterial blood gases on cerebral blood flow during exercise  Despite the multitude of individual factors involved in regulating CBF at rest, the primary factor involved in regulating CBF during exercise appears to be changes in PaCO2.  Most of the investigations into the relationship between PaCO2 and CBF during exercise have been explored via increasing the inspired CO2 concentration to elevate CBF accordingly, and will be discussed in detail in the following sections.  To a lesser extent, depending on the severity and duration, PaO2 during exercise may also modify the CBF response during exercise. The following sections summarize the evidence identifying the integrative and individual roles that PaO2 and PaCO2 have on CBF during exercise.    Partial Pressure of arterial carbon dioxide  The relative hypventilation (i.e., reduced VE/VCO2), during light intensity exercise results in an increased PaCO2 prior to 60-70% Wmax or before the ventilatory threshold. In contrast, once the ventilatory threshold has been reached, typically occurring with increases in exercise intensity above 60-70% WMax, ensuing hyperventilation (i.e.   46 elevated VE/VCO2) consequently reduces PaCO2 (Figure 2.6). Because of the sensitivity of the cerebrovasculature to PaCO2 at rest, it was hypothesized early in the scientific literature that the magnitude and directionality of the CBF response to exercise was in part due to changes in PaCO2 ((Hedlund et al., 1962)).  The relationship between PaCO2 and CBV during exercise, first described by Moraine et al. (1993), indicated that the MCAv response to exercise paralleled the relative hyper- and hypocapnic responses of the ventilator system.   The importance of PaCO2 was so readily recognized that early studies investigating the CBF response to exercise corrected for the changes in PaCO2 using a generic correction factor i.e., 4.1%.mmHg-1 ∆ in PaCO2 (Madsen et al., 1993). The correction factor indicated that the reduction in CBF from rest (~ 7% reduced), measured using Xe clearance, during continuous exercise (i.e., 40 min at 50 %WMax) was primarily due to a falling PaCO2. Furthermore, because the correction factor heightened the MCAv response to exercise, the authors suggested that the hypocapnia serves to regulate the magnitude of the increase in intracranial velocity, possibly by augmenting vessel diameter. Additionally, Linkis et al. (1995) utilizing a subject specific correction factor (e.g., 3.1 %.mmHg-1∆ in PaCO2) that fell within the limits of the change in PaCO2 expected during exercise to demonstrate that the fall in MCAv during prolonged cycling ( 15 min at ~ 60% WMax) was strongly related to the fall in PaCO2 – when these changes were corrected for, a plateau in CBF above resting values was observed.  This phenomenon has since been confirmed by three studies that elevated the CBF response during exercise by either elevating the baseline PaCO2 (Siebenmann et al., 2013), or mitigating the drop in PaCO2 following the ventilatory threshold by increasing the inspired CO2 concentration (Olin et al., 2011; Subudhi et al., 2011).  The importance   47 of PaCO2 in influencing the magnitude of the CBF decrease during maximal intensity exercise has therefore is well known; however, little is known how mitigating the rise in PaCO2 during submaximal exercise will influence the cerebral hyperemic response to exercise. Moreover, since there may be a differential cerebral CO2 reactivity during exercise (Ogoh et al., 2008; Rasmussen et al., 2006) and likely dilation of the MCA (Coverdale et al., 2014), elevating PaCO2 may lead to confounding results.   Partial pressure of arterial oxygen  Hypoxia: As discussed in section 2.1.3.1  the magnitude of the hypoxic cerebral vasodilation is dependent on the balance between hypoxia-induced vasodilation, and the hypoxia-induced hyperventilation and resultant hypocapnia and the time course of the hypoxic exposure.  However, during exercise, because PaCO2 is dependent on the exercise intensity the enhanced CBF response to acute hypoxic exercise was originally thought to be paradoxical finding given the lack of any hypocapnic vasoconstriction. Figure 2.10 summarizes the studies comparing the CBF response to normoxic, acute hypoxic, and chronic hypoxic exercise, with similar relative exercise intensities.  The average changes in CBF indicate that acute hypoxic exercise causes a greater increase than normoxic exercise during mild and maximal exercise intensities. However, during exercise in chronic hypoxia, there is a reduced CBF response compared with both acute hypoxic and normoxic exercise.   48   Figure 2.10. Average relative cerebral blood flow (CBF) response during exercise at mild (20-40% Wmax), moderate (40-70% WMax) and Maximal (100% Wmax) intensities from the 11 studies investigating CBF during normoxia ((Fan & Kayser, 2013; Huang et al., 1991; Imray et al., 2005; Rasmussen et al., 2010b; Subudhi et al., 2008; Subudhi et al., 2009; Subudhi et al., 2011)), acute hypoxia (Ainslie et al., 2007; Fan & Kayser, 2013; Huang et al., 1991; Overgaard et al., 2012; Siebenmann et al., 2013; Subudhi et al., 2008; Subudhi et al., 2009; Subudhi et al., 2011) and chronic hypoxia ((Huang et al., 1991; Imray et al., 2005; Möller et al., 2002; Subudhi et al., 2009)).  Red lettering signifies the mean respective PaCO2 for the condition and exercise intensity.    -20% -10% 0% 10% 20% 30% 40% 50% Normoxia Acute Hypoxia Chronic Hypoxia Mild Moderate Maximal Exercise Intensity % ∆CBF 33"40"26"32"41"25"21"27"32"  49 Six out of the eight studies comparing CBF during acute hypoxic versus normoxic exercise, observed an elevated CBF response during hypoxia at mild (Fan & Kayser, 2013; Huang et al., 1991; Subudhi et al., 2009), moderate (Fan & Kayser, 2013; Rasmussen et al., 2010a) or maximal (Fan & Kayser, 2013; Imray et al., 2005; Rasmussen et al., 2010b; Subudhi et al., 2009) exercise. The greatest relative increase was observed by Fan & Kayser (2013) when MCAv increased from basal values by approximately 41, 44 and 48% at 40, 60 and 100% Wmax, respectively, during acute hypoxic exercise. These latter results were more than twice the increase in MCAv (15, 19 and 11%, respectively) observed during normoxic exercise at the same workloads.  However, the elevated CBF response during hypoxic exercise has not been consistently reported throughout all exercise intensities (Huang et al., 1991; Imray et al., 2005; Subudhi et al., 2009).  For instance, Huang et al. (1991) observed a greater rise in ICAv from basal velocities during submaximal (~25% Wmax) upright cycling in acute hypobaric (55 mmhg) hypoxia (~ +31% ) compared with normoxia (~ +13%) despite a reduced PaCO2 (- 3 mmHg ) with acute hypoxia.   However, this was only observed at 25%Wmax, since subsequent increases in exercise intensity reduced PaCO2 (-2 mmHg) resulting in only a 19% elevation in CBF from baseline during hypoxia compared to a 28% increase in normoxia with a unchanged PaCO2. Following acclimatization to altitude (18 days at 4300 m) with a similar PaO2 achieved during acute hypoxia but a more pronounced hypocapnia, ICAv was did not significantly change during incremental exercise. Considering the differential CBF responses above to exercise in normoxia, it is plausible that, similar to rest, the CBF response to acute and chronic hypoxic exercise is   50 dependent on the magnitude of hypocapnia which is dependent on the time course and magnitude of hypoxia (i.e., see section 2.2.2.3).  Regardless of the findings discussed thus far, only one study has actually quantified the global CBF response during exercise following chronic hypoxia at high altitude [i.e., Kety-Schmidt technique; (Möller et al., 2002)]. The authors reported no change in CBF during exercise at similar absolute workloads (100 watts); however, because of this absolute comparison, the  relative workloads at HA (~80% WMax) were higher compared with SL (40% WMax).  With the exception of Möller et al. (2002) the studies to date have compared the MCAv response to exercise in hypoxia and normoxia using similar relative exercise intensities.  The importance of this discrepancy is that given the importance of the integrative roles PaO2 and PaCO2 have on the CBF response at HA (see section 2.2.2.3), and the influence exercise intensity has on PaCO2 response, comparisons of CBF without normalizing for relative exercise intensity may potentially confound the CBF response to exercise in chronic hypoxia at HA. Therefore, it remains unknown if the CBF response to hypoxic exercise is different compared to the normoxic exercise response when similar relative exercise intensities are considered at HA. Moreover, no study to date has attempted to investigate the regional distribution of CBF during hypoxic exercise.    Hyperoxia: Little is known about the cerebrovascular response to exercise in hyperoxic conditions.  As discussed in sections (2.2.2.1), hyperoxia at rest leads to a reduction in CBF, a response mediated in part by hyperventilation-induced hypocapnia and resultant  cerebral vasoconstriction. The resultant hyperoxic hypocapnia at rest, coupled with a   51 reduced alveolar ventilation during hyperoxic exercise results in a larger increase in PaCO2 from basal levels during submaximal exercise compared with normoxic conditions (Asmussen & Nielsen, 1946; Bannister & Cunningham, 1954; Miyamoto, 1995; Welch et al., 1977).  It is unknown if the larger change in PaCO2 from rest during hyperoxic exercise results in an increased CBF/CBV.  Only one study has partly addressed this question. Lambertsen et al. (1959) measured changes in CBF in subjects performing a constant load (60-70% Wmax) exercise at 1.0 atmospheres (PO2 = 95 mmHg) and at 2.0 atm (PO2 = 1190 mmHg) while breathing hyperoxia (i.e., FiO2 = 1.0).  The end result indicated that although breathing at hyperoxia at 2 atm elicited a reduced PaCO2 (+3.5 mmHg), similar CBF values were observed during exercise. Unfortunately, between group comparisons were only assessed during exercise, and no resting data was reported in the two individuals who performed both normoxic and hyperoxic exercise.   Cerebral oxygen delivery during exercise  As discussed in section 1.1.2.1, the divergent cerebrovascular response to hypoxia and hypocapnia play important roles in shaping the CBF response to exercise.  However, given the sparse and often conflicting findings regarding the influence hypoxia and hypocapnia have on the cerebrovasculature during exercise, it should be no surprise that even less is known regarding the regulation of CDO2 in similar conditions. It is well accepted that the maintenance of CDO2 is important for ensuring an appropriate cerebral O2 reserve is present (i.e., capillary O2 volume sufficient to match CMRO2 demand) throughout the entirety of cerebral microvasculature (Jespersen & Østergaard, 2012). Subudhi et al. (2011) hypothesized that the reduction in CBF at maximal normoxic   52 exercise from the peak CBF response observed at 60% could implicate an inadequate CDO2 to maintain the cerebral O2 reserve required to maintain exercise performance resulting in the cessation of exercise. Therefore, the authors attempted to mitigate the reduction in CBF at maximal exercise intensity using hypercapnia (e.g., 50 mmHg PaCO2) to elevate CBF and help offset the reductions in CDO2 at maximal exercise. The hypothesis was that maintaining CDO2 could potentially improve exercise performance. Ultimately, their findings were negative with regards to performance during both hypercapnic normoxic and hypoxic exercise to exhaustion. Unfortunately, the authors did not report CDO2 in either the unclamped or clamped CO2 exercise.  Therefore, given that CDO2 is the product of CBF and CaO2, it remains unknown if CDO2 is reduced at maximal exercise, or if increases [+ 20% (Ekblom et al., 1975)] in CaO2 during exercise offset the reduction in CBF leading to a stable CDO2 throughout exercise. In support of this, Rasmussen et al. (2010a) observed that CMRO2 and performance was reduced when estimated CDO2 was not maintained during hypoxic exercise, despite a significantly elevated MCAv compared with normoxic exercise. Thus, given the above, the mechanisms involved in the integrative regulation of CBF and CDO2 and CMRO2 during exercise remain relatively unknown considering no study to date has accurately quantified if CDO2 using volumetric indexes of CBF is reduced during exercise.   2.3.3. Blood pressure   To ensure adequate oxygen delivery is distributed proportionally to the active musculature, lungs, heart and brain during exercise, MAP and CO progressively increases with incremental exercise intensity.  Without the reflex mediated control of the arterial pressure, appropriate distribution of the CO throughout the cardiovascular system would   53 not occur (Rowell, 1993).  However, the influence that arterial pressure plays in regulating CBF during exercise is difficult to discern.  For instance, incremental exercise is reflected by progressive increases in MAP by 20-30% up to maximal intensities (Figure 2.6); yet, CBF typical only increases (15-25% above rest) up to 70% of maximal intensity before returning towards baseline levels. Whilst elevations in MAP may influence CBF at rest (Newman et al., 2014; Willie et al., 2014), the lack of any observable linearity between MAP and CBF responses during exercise indicates that the CBF response is more likely the result of other regulatory factors (i.e., cerebral metabolism and PaCO2). Because the individual cardio-respiratory responses (i.e., MAP, PaCO2, and cardiac output) occur concurrently, albeit independently of one another during incremental exercise, there are obvious difficulties associated in differentiating the independent influences that PaCO2 and MAP have on CBF regulation during exercise. No study to date has been successful at manipulating each of these factors individually during exercise.   2.3.4. Redistribution of cardiac output   Similar to arterial blood pressure, although with different magnitude, both Q and CBF increase from basal values during progressive increases in exercise intensity to 60-70% Wmax increase.  While the nearly four-fold increase in cardiac output, achieved by increased heart rate and contractility is responsible for the distribution of blood to all systemic organs, the increase in cardiac output contributes negligibly to the CBF (~ 20% increase) response during exercise {Rowell, 1993, #99291}. For example, when the rise   54 in CO is blunted during submaximal exercise after administration of a β1 antagonist (metropolol) the rise in CBV is inhibited (Ide et al., 1999; Ide et al., 2000a).  Furthermore, in healthy humans, Ogoh et al. (2005b) quantified the linear relationship between CO and the MCAv during steady state sub-maximal exercise (40% Wmax), using lower body negative pressure (to reduce CO) and albumin infusion (to elevate CO). Interestingly, the slope between experimentally manipulated changes in CO and CBF during exercise was >50% lesser than those observed during rest. Unfortunately, in each condition (rest and exercise) the significant changes in MCAv observed per unit change in CO (R2 = 0.98 and 0.81, respectively) were statistically derived by plotting a linear regression line through the mean responses, instead of averaging the individual responses; the former method that is statistically incorrect and leads to inflation of R values.   Nevertheless, the slope of the averaged CO verses CBF response was small indicating a modest effect of CO on CBF during these controlled conditions (Ogoh et al., 2005b). Moreover, given that the 20% increase in CBF falls short of the four-fold increase in CO during submaximal exercise, and that the return of CBF to baseline values at maximal exercise occurs despite an almost 8-fold increase in CO (Figure 2.6),  suggests there can be little influence of CO on CBF during whole body exercise.  2.3.5.  Neural regulation of cerebral blood flow during exercise  The importance of neurogenic control of CBF during exercise has been described to facilitate adequate CBF during low-intensity exercise either through sympathetic (Brassard et al., 2010; Purkayastha et al., 2013) or parasympathetic (Seifert et al., 2010) innervations. Ide et al. (2000a) observed a coordinated reduction of CO and CBF during   55 submaximal exercise using b1 antagonists. Although it was speculated that there was a potential influence of sympathetic control of the cerebral vasculature during exercise, it would seem more likely that the attenuated CBF response was the result of indirect effects of SNA on the cardiac distribution of blood flow to the brain.  In a recent study Brassard et al. (2010) infused a bolus dose of the alpha-adrenergic agonist phenylephrine (0.25 mg) at rest which elevated vascular resistance, MAP (~ 19 %) and MCAv  (~ 10%). However, during light (heart rate = 110 bpm) and moderate (heart rate =150 bpm) steady state exercise, bolus infusion of phenylephrine (0.30 mg) compared with placebo (i.e., saline), failed to elicit any elevation in MCAv. The lack of influence on MCAv might potentially have been due to the somewhat lesser MAP elevations (~ 9% – 13%) during exercise compared to those observed at rest (~17 - 23%). These findings highlight a differential effect of alpha-adrenergic induced changes in MAP during exercise.  Unfortunately, the mechanisms explaining the differential responses from rest and exercise remain unclear, and subtle alterations in MCA diameter may also be a confounding factor (Brassard et al., 2010).   In contrast to Brassard and coworkers (Brassard et al., 2010)., Purkayastha et al. (2013) was able to abolish the rise in MCAv and MAP during submaximal exercise (i.e., 20 and 40% Wmax) using an alpha-1 antagonist (Prasozin).  The authors implicated the reduction in MCAv and increase in cerebrovascular conductance  (CVCi) as evidence for MCA dilation and a stable CBF – an interpretation in support of a sympathetic influence on the cerebral vasculature during exercise at these intensities.  Another interpretation,   56 however, is that the systemic reduction in sympathetic activity and the related attenuation of perfusion pressure, compared with placebo, could explain the lack of MCAv response to exercise. It should be noted that Purkayastha et al. (2013) tested the patency of the sympathetic block using phenylephrine pre and post exercise. The effective block at rest  (i.e, ~ 74%) was stable throughout exercise. In summary, the difficulties to date in identifying the role of neurogenic control on the cerebrovascular response to exercise are two-fold: 1) because of the potential for changes in MCA diameter, interpretation of neurogenic control quantified using only MCAv may underestimate the CBF response, (see chapter 3 section 3.1) for further details); and 2) the lack of a cerebral specific sympathetic antagonist or agonist makes it difficult to separate the systemic (i.e., perfusion pressure) factors from the local neural influences.  This latter confounding issue might be improved by using a more centrally acting SNA block [e.g., clonindine (alpha 2); (Bonhomme et al., 2008)].  2.3.6. Cerebral blood flow and metabolism during exercise  The majority of the investigations involved in quantifying cerebral metabolism and the various metabolic substrate contributions to cerebral metabolism have been performed during rest. Only 12 studies have examined CBF and the metabolic rates of oxygen, glucose and lactate during incremental exercise (Brassard et al., 2010; Fisher et al., 2013; Kleinerman & Sokoloff, 1953; Kleinerman & Sancetta, 1955; Lambertsen et al., 1959; Madsen et al., 1993; Nybo et al., 2003; Rasmussen et al., 2010a; Rasmussen et al., 2010b; Scheinberg et al., 1953; Scheinberg et al., 1954; Trangmar et al., 2014). Given the temporal response of global CBF during incremental exercise to exhaustion (Figure 2.8) and the multiple systemic factors involved in the regulation of the CBF versus the   57 myriad of local factors involved in the CBF:CMRO2 coupling, the following sections aim to briefly discuss the coupling of global CBF with global CMRO2 during exercise. Finally, a short overview outlines how changes to the relative contribution of oxygen, glucose and lactate during exercise impacts on cerebral energy metabolism.   Cerebral metabolic rate of oxygen during exercise  Only 12 out of the 61 studies investigating CBF during exercise in healthy individuals have also investigated CMRO2 (Figure 2.11). During light intensity cycling (100 Watts), there are general reports of CMRO2 to vary only slightly (~ 10% > rest) despite an 18% increase in CBF (Fisher et al., 2013; Kleinerman & Sokoloff, 1953; Lambertsen et al., 1959; Madsen et al., 1993; Möller et al., 2002; Nybo et al., 2003; Rasmussen et al., 2010a; Rasmussen et al., 2010b; Scheinberg et al., 1954; Trangmar et al., 2014). In contrast, Scheinberg et al. (1954) reported a significant increase in CMRO2 (~23% > from rest) during upright treadmill jogging at a moderate intensity (4.5 miles per hour with 4% grade) with a non-significant 5% rise in CBF.    58  Figure 2.11.  The percent change in CMRO2 (% ∆CMRO2) during light (20 – 40% WMax), moderate (40-60% Wmax) and maximal (100% Wmax) exercise intensity.  The CMRO2 values are the average values calculated from the mean responses in the 12 studies investigating this response (Brassard et al., 2010; Fisher et al., 2013; Kleinerman & Sokoloff, 1953; Kleinerman & Sancetta, 1955; Lambertsen et al., 1959; Madsen et al., 1993; Nybo et al., 2003; Rasmussen et al., 2010a; Rasmussen et al., 2010b; Scheinberg et al., 1953; Scheinberg et al., 1954; Trangmar et al., 2014).   -10% 0% 10% 20% 30% 40% 50% 60% % ∆ CMRO2 Light Moderate Maximal Exercise Intensity   59 Forty years later, Madsen et al. (1993) using the Xe clearance technique, observed an unchanged CMRO2 from basal values during recumbent moderate intensity cycling (50% Wmax) despite a ~ 7% reduction in CBF.  Likewise, Möller et al. (2002) using the Kety-Schmidt method, observed a similar absence of any alteration in CBF or CMRO2 during supine cycling (100 W) following 16 days at high altitude (5260m) and upon return to sea level. In another study, during the last 10 minutes of a 3 hour cycling protocol (60% WMax), CMRO2 was reduced by 13 ± 4% compared to resting values despite a slight 3% reduction in CBF (Nybo et al., 2003).  The disparate responses between studies are likely a reflection of the differing exercise intensities, duration and methodological approaches used to assess CMRO2 and CBF.   Recent assessments of CMRO2 during exercise, using intracranial (i.e., MCAv) or extra-cranial (i.e., ICA flow) assessments of CBF, have also produced contrasting findings regarding CMRO2 during exercise. For instance, Fisher et al. (2013), using the percent change in MCAv to indicate flow changes from an assumed resting gCBF of 46 ml.100g.min-1, observed a progressive increase in CMRO2, with peak values achieved during 100% Wmax (~ 25 µmol.100g-1.min-1 > basal values). In contrast, Trangmar et al. (2014) using volumetric flow through the ICA (multiplied by 2) as a surrogate for CBF, observed that CMRO2 was maintained throughout incremental exercise to exhaustion. Nevertheless, these authors provided evidence that during maximal exercise when CBF had fallen from its peak at 60% Wmax, CMRO2 was maintained via compensatory elevations in O2 extraction. Specifically, the early increases in CBF during submaximal exercise were met with proportional reductions in O2 extraction, whereas the return of   60 CBF to basal values near maximal intensities was met with proportional increases in O2 extraction.  Both Fisher et al. (2013) and Trangmar et al. (2014) utilized similar exercise protocols, but different approaches to estimate gCBF. Nevertheless, the differences in CMRO2 appear to be related to the change in transcerebral O2 extraction compared with differences in CBF; however, the disproportional increase in CBF compared with CMRO2 in both instances, supports the theory of CMRO2 and CBF uncoupling.  Rasmussen et al. (2010a) quantified the CMRO2 (i.e., using the arterial - jugular venous CaO2 differences and MCAv) response to upright cycling during incremental exercise in normoxia and during 10 minutes of steady state cycling in hypoxia (FIO2 =0.1).  During normoxia, CMRO2 increased by ~20% from baseline up to 80% WMax and was stable from then until exhaustion.  During hypoxic exercise, CMRO2 was reduced compared with the normoxic baseline, despite a 51% increase in CBF from the basal values.  Furthermore, CMRO2 during hypoxia remained lower compared with normoxia during cycling exercise with a similar absolute intensity (i.e., 124 W) and relative intensity (i.e., 224 W). Interestingly, during maximal exercise in normoxia, the elevated CMRO2 was maintained by an elevated oxygen extraction [Rasmussen et al. (2010a)]. In a different study, Rasmussen et al. (2010b) investigated CMRO2 during normoxic, hypoxic (FiO2 = 0.17), and hyperoxic (FiO2 = 0.30) breathing at the end of a maximal 2000 m rowing time trial. The findings indicated an increased exercising CMRO2 in each condition compared with the normoxic basal values.  The authors quantified an increased CMRO2 during exercise of 13 - 30% dependent on the respective O2 background (ie; hyperoxia < normoxia < hypoxia). In contrast to the hypoxic condition, during hyperoxic rowing exercise, the elevation in CMRO2 was driven more so by the increased gCBF, as oxygen   61 extraction was actually lower compared with hypoxic and normoxic exercise (Rasmussen et al., 2010b). The latter observation (in hyperoxia) is in support of a potential coupling of CBF and metabolism, whereas the former findings (in normoxia) support an uncoupling of the relationship between CBF and metabolism. Unfortunately, the differential findings observed during two distinctly different hypoxic (FiO2= 0.17 vs 0.1) exercise (i.e., rowing versus cycling) protocols provide little clarity to enhance the understanding of the coupling of CBF to CMRO2 during exercise. Regardless of the lack of consensus involving the matching of CBF to CMRO2 during exercise, as outlined, the matching of global CBF to global CMRO2 per se, is not required because of compensatory alterations in O2 extraction.  Further investigations are needed in order to identify the appropriate response of global CMRO2 to exercise and the impact of severe chronic hypoxia (i.e, high altitude) cerebral metabolism.  Cerebral metabolic rate of glucose during exercise  The first quantifiable cerebral metabolic rate for glucose obtained during exercise was performed by Scheinberg et al. (1954).  The authors observed no change in CMRGlu from resting values during exercise; therefore, little discussion was provided in relation to this finding.  In fact little attention was given to CMRGlu during exercise for almost 50 years following this.  Ide et al. (1999) measured the cerebral metabolic response to submaximal exercise; however, no inferences could be made regarding the metabolic rates since the authors only measured MCAv and did not attempt to assume a resting CBF.  Nevertheless, during submaximal exercise, MCAv and the arterial-venous glucose differences increased from resting values indicating the potential for an increased   62 metabolic rate of glucose at 60% Wmax. Figure 2.12, summarizes the cumulative findings to date that calculated the CMRGlu using either a calculated gCBF (vascular ultrasound) and/or the relative change in MCAv [e.g, Ide et al. (1999)] with an assumed resting CBF of 46 ml.100g-1.min-1 (Madsen et al., 1993) during incremental exercise. These data were combined with transcerebral arterial venous glucose values that were extracted from eight other studies (Brassard et al., 2010; Fisher et al., 2013; Ide et al., 2000b; Larsen et al., 2008; Nybo et al., 2003; Rasmussen et al., 2010a; Rasmussen et al., 2010b; Trangmar et al., 2014), and used to infer the respective change in the cerebral metabolic rate of glucose compared with oxygen and lactate during exercise by standardizing the units into glucose equivalent units (i.e., 1/6 CMRO2 and ½ Lac) given the stoichiometric metabolic differences between glucose and O2 (i.e., 1:6) and glucose to lactate (i.e., 1:2) (Dalsgaard et al., 2004a).   The cumulative findings point to a marked increase in CMRGlu when transitioning from rest to maximal exercise and are similar compared to the increases observed in CMRO2.  It is worth noting that the elevated CMRGlu from baseline at maximal exercise was primarily attributable to an elevated trans-cerebral exchange of glucose  – changes that were unrelated (R2 = 0.02) to the cerebral glucose delivery (Dalsgaard et al., 2004b; Rasmussen et al., 2011). Nevertheless, a similar summary of the cumulative CMRGlu performed by Rasmussen et al. (2011) identified the mean glucose delivery at rest and during various exercise intensities (submax to exhaustion) to be consistently in excess of cerebral glucose demand. Such findings are generally consistent with the most recent findings in the studies performed by Fisher et al. (2013) and Trangmar et al. (2014).     63  Figure 3.7. A) The cumulative oxidative (CMRglu + ½ CMRlac) and non oxidative (1/6 CMRO2 - (CMRglu + ½ CMRlac) cerebral metabolic ratio (CMR: oxidative plus non-oxidative in glucose equivalent units) and cerebral oxidative carbohydrate ratio during rest, light (20-40% WMax), moderate (40-60%Wmax) and maximal (100%WMax) cycling exercise. An increase in CMR indicates an increase in global cerebral metabolism while a reduction in OCI indicates a reduction in oxidative metabolism. B) The percent contribution of oxygen, glucose and lactate trans-cerebral uptake to the CMR.  Sizes of the circle are proportional to the percent difference in CMR from rest. All values are mean and standard deviations calculated from the eight studies quantifying CMR during incremental exercise (Brassard et al., 2010; Fisher et al., 2013; Ide et al., 2000b; Larsen et al., 2008; Nybo et al., 2003; Rasmussen et al., 2010a; Rasmussen et al., 2010b; Trangmar et al., 2014).     Exercise IntensityCMR(mmol.100g1.min-1)OCIRest Light Moderate Maximal0204060801000246OCICMRRest53.757151.7% 48.3%Light57.235651.2%46.9%2%Moderate71.512846.6%42.8%10.6%Maximal95.480738.6%33.6%27.8%O2GluLacExercise Intensity Rest Light Moderate Maximal A B   64 Only a few studies (Möller et al., 2002; Overgaard et al., 2012; Rasmussen et al., 2010a) have investigated the influence that PaO2 exerts on CMRGlu. Möller et al. (2002) observed no change in CMRGlu during exercise at 5260m compared with SL; however, it is pertinent to remember that no comparisons of relative exercise intensity were performed. Similarly, Overgaard et al. (2012) revealed that 20–minutes of steady state cycling in hypoxia (FIO2 = 0.1) at 35% of the normoxic WMax did not alter CMRGlu from normoxic values.  However, unlike Moller et al. (2002), if consideration is given to the similar glucose extractions during normoxic and hypoxic exercise at similar relative intensities coupled with the elevated gCBF during hypoxia, the CMRGlu response to hypoxic exercise is heightened [Overgaard et al. (2012)].  In a different study, Rasmussen et al. (2010a) did not observe a significant elevation in CMRGlu during normoxic and hypoxic exercise at similar relative workloads, despite an increase in the estimated gCBF.  To date no studies have examined the influence of hyperoxia on CMRGlu during exercise.   Cerebral metabolic rate of lactate during exercise  Despite negligible involvement in cerebral metabolism at rest, over the course of a 10-minute bout of exercise, cerebral lactate uptake can increase almost 10-fold (Dalsgaard et al., 2004a).  However, during such incremental exercise, the exponential rise in lactate uptake is directly related to the arterial concentration (Fisher et al., 2013; Larsen et al., 2008). In certain instances, the arterial to venous differences of lactate has been observed to go from a small net ‘release’ at rest to a 10% and 17% uptake during exercise and recovery, respectively. Moreover, using lactate infusion, van Hall et al. (2009) highlighted the highly significant relationship (R2 = 0.98) between lactate availability and   65 lactate extraction at rest during 10 minutes of cycling at 75% Wmax. Therefore, despite its negligible metabolism at rest when lactate is in short supply, is an essential part of cerebral metabolism during exercise.   There has also been one investigation into the influence pH has on cerebral lactate uptake during rowing exercise. Here, Volianitis et al. (2011) demonstrated during a 2000 m rowing time trial that when both pH and arterial lactate concentration (~ 10 mM > placebo) were elevated (via bicarbonate infusion) the absolute uptake of cerebral lactate was not altered compared to a placebo condition.   Although potentially influenced by the prolonged high intensity exercise, this finding therefore demonstrates that lactate metabolism is not only provoked by elevations in lactate concentrations alone. In a different study, Volianitis et al. (2008) explored the influence PaO2 has on lactate metabolism. When compared to normoxic exercise, significantly reductions in lactate extraction were observed during hypoxic (FiO2 = 0.17) and hyperoxic (FiO2 = 0.30) exercise. These findings were most likely explained by the reduced arterial lactate concentrations observed in each condition. Similar to CMRO2 and CMRGlu Möller et al. (2002) is the only study to quantify the effects of exercise at HA may have on CMRLac; similar to the findings about CMRO2 and CMRGlu, the response was unremarkable.  Cerebral substrate utilization during exercise  During exercise, the cerebral metabolic ratios (i.e., OGI and OCI) are progressively reduced from their stable resting values of ~5.7 during incremental exercise by greater than one third.  The reduction in both OGI and OCI indicate an increase in anaerobic   66 non-oxidative cerebral metabolism i.e., a disproportional increase in the respective glucose and carbohydrate (glucose + ½ lactate) uptakes compared with oxygen (Dalsgaard et al., 2004a).   This reduction seems to be unaffected by changes in lactate availability (Volianitis et al., 2011) and mild hypoxia (FiO2 = 0.17) and hyperoxia [FiO2 =0.30; (Volianitis et al., 2008)].  It remains uncertain if this remains true in severe hypoxia at high altitude (5050m).    2.3.7. Overall Aims and Hypotheses  In the context of the literature review, and in relation to the current thesis, the following three primary questions remain unknown: 1) What are the effects of mild hypoxia and hyperoxia on regional CBFv during incremental maximal exercise; 2) What is the influence of severe hypoxia, following partial acclimatization to high altitude, on regional CBFv, volumetric CBF and metabolism during exercise; 3) What are the independent affects of altered ventilation, PaO2 and PaCO2 on regional and global CBF during exercise. Accordingly, in three experimental investigations, the following aims and hypotheses are examined:  Experimental study 1 (Chapter 4 )  Aim: To investigate concurrent blood flow velocity in the anterior and posterior cerebral circulation during exercise while breathing normoxia, normobaric hypoxia and hyperoxia.      67 Hypotheses:  1. Increases in the regional distribution of CBV during normoxic incremental exercise, would be greater in the posterior circulation than the anterior circulation. 2. Changes in PaCO2 and PaO2 (as indicated by changes in PETCO2 and PETO2) during hypoxic and hyperoxic exercise will result in increased anterior and posterior cerebral blood flow velocity compared to normoxic exercise  Experimental study 2 (Chapter 5) Based on the findings from the first experimental chapter (Chapter 4), and the discrepancies between previous exercise studies at sea level (e.g., Fisher et al., 2013; Sato et al., 2011; Smith et al., 2012; Trangmar et al. (2014)) and high altitude (Moller et al. 2014) the aims and hypotheses were:   Aim: To investigate the effects early acclimatization to high altitude and the consequent influence hypoxemia has on the cerebral haemodynamics, cerebral metabolism and substrate delivery at rest, during incremental exercise and recovery.   Hypotheses:  1. During incremental exercise and recovery following 4-6 days at 5050 m increases in gCBF will preserve delivery of oxygen (CDO2) in excess of an increasing CMRO2;  2. Because of the expected elevations in gCBF and maintained CDO2 the trans-cerebral exchange of oxygen vs. carbohydrates (OCI) would be similar during exercise and recovery at HA and sea-level.   68  Experimental study 3 (Chapter 6) The results from the final experimental chapter (Chapter 6) will revisit the findings from Chapter 4, with the goal of utilization volumetric regional and global CBF while clamping PETCO2 during normoxia and normobaric hyperoxic during incremental exercise.  Moreover, this study will attempt to investigate how breathing at similar volumes and flow rates achieved during incremental exercise independent of the exercise activity impacts on CBF.  Aims:  1. To investigate if the rise in PaCO2 is influential in driving the magnitude of the CBV and CBF response during incremental exercise. 2. To identify the role that PaCO2 plays in generating the regional differences observed during hyperoxic incremental exercise; 3.  To observe the role that increased ventilation during exercise plays in independently regulating CBF during hyperoxic and normoxic exercise.  Hypotheses:  1. Maintaining normocapnia during submaximal exercise will reduce gCBF and regional CBF differences in both normoxia and hyperoxia compared to poikilocapnia;   69 2. No differences will be observed between volumetric CBF and CBV in either the anterior or posterior cerebral circulation during exercise despite the manipulation of PaCO2 and PaO2;  3. Isocapnic hyperpnea will increase posterior CBF but to a lesser extent than that observed during exercise.     70Chapter 3. Methodology and Experimental Design  The following chapter will provide a methodological review on: 1) the instruments used to collect and quantify the cerebrovascular response during exercise in the three experimental chapters in this thesis; and 2) the methods and techniques used to assess and quantify the cardio-respiratory response to exercise.  The instrumentation and assessment methodologies will be specifically referenced within the context of the individual research chapters (Chapters 4 - 6). 3.1. Instrumentation The equipment and techniques utilized to collect the data presented in the experimental chapters of this thesis were transcranial Doppler and vascular duplex ultrasound.  These instruments are described in detail below. 3.1.1. Transcranial Doppler ultrasound  Principles of transcranial Doppler ultrasound [reviewed by Willie et al. (2011a)] Transcranial Doppler ultrasound (TCD) functions, in principle, through a transmitter (i.e., Piezoelectric crystal) housed in a hand held Doppler probe that emits a pulsed ultrasound wave at 1.5-2 Mhz. The ultrasound frequency is transmitted externally, capable of penetrating the skin and thin acoustic boney region, located in the temporal region of the cranium (i.e., acoustic window) insonating the MCA and PCA (approximately 5- 8 cm deep). This is possible because the relatively low 1.5-2 MHz wavelength emitted from the piezoelectric crystal, compared with the 3-12 MHz frequencies used in vascular      71Doppler ultrasound, provides an optimal resolution-to-penetration depth ratio necessary to penetrate the skull and image the deep intracranial vessels. The target of the ultrasound beam is the red blood cells of the specific intracranial vessel, which reflect the ultrasound beams back to the transducer where it is collected. The difference between the frequency of the transmitted and received signals is known as the Doppler shift and is calculated by the following calculation: Eq 1. Doppler Shift = 2 × Ft × V × Cos∅C Where Ft is the transmitted frequency (i.e., 2 MHz); V is the velocity of the reflector (red blood cells; Cos is the correction factor based on the angle of insonation; and C is the speed of sound in the blood (1540 m.s-1).  The Doppler shift is further processed through a fast Fourier transformation (i.e., converted from the frequency domain into the time domain) which alters the ultrasound waves into a velocity trace (i.e, pulse-wave velocity).  The velocity received can then be utilized to index the velocity of the red blood cells within the specific intracranial vessel from the waveform and the subsequent envelope derived from the waveform can be used for future analysis (Figure 3.1). Consideration is needed concerning constancy of the transmitted transducer signal and the speed that sound travels through the blood stream; thus, the main modifiable variables in the calculation of the Doppler shift are the insonation angle of the probe in relation to the specific intracranial vessel and the velocity.      72 Figure 3.1. A) Magnetic resonance angiograph of Circle of Willis with right and left internal carotid artery (ICA), basilar artery (BA) and B) middle cerebral (MCA) and C) posterior cerebral (PCA) arteries. In the current study, cerebral blood velocities were collected using transcranial Doppler ultrasound through the anterior and posterior temporal acoustic windows. Adapted from Smith et al., (2012).  The importance of the insonation angle, therefore, is vital to the accuracy of the  intracranial velocity measure, as the magnitude of the error associated with the Doppler shift is dependent on the cosine of the insonation angle (Figure 3.2).  An insonation angle between 0 and 30 degrees is the desirable and optimal angle for accurate calculation of red blood cell velocity; however, technical ultrasound guidelines state that CBV is accurate within 60 degrees [reviewed in: Wintermark et al. (2005)].  The techniques used to insonate the middle cerebral artery typically achieve an insonation angle no greater      73than 15 degree, nearly inline with the probe helping to create an optimal and stable signal.  Whereas the angle of insonation for the PCA is more difficult to assess, since in many circumstances the angle of insonation is slightly higher but low enough (i.e., < 30 degrees) to achieve an optimal signal yet in some individuals the only available insonation window provides only a blunt (i.e., > than 90 degrees) insonation angle [Aaslid et al. (1982)].  Thus assessment of the PCAv is not attainable in 10-20% of the population.         74  Figure 3.2 In the image: Red stripped lines = vessel walls, red arrow = direction of moving blood, blue dashed line = ultrasound beam, green bar = angle cursor, black dashed lines indicate the percentage of the reflected ultrasound signal that is received by the receiver. The relationship between the angle of insonation and cosine of the angle (Cos Ø).  The image demonstrates the progressive and disproportional reduction in the percentage of the transmitted signal reflected back to the ultrasound probe as the angle of insonation increases such that at 90 degrees no signal will be recorded.    60o 45o 30o 15o 0.97 0.87 0.71 0.50 0.25 Cos Ø 70o 90o 0.0      75Utilizing the pulse-wave velocities collected from TCD, in young healthy individuals, Aaslid et al. (1982) typical values of red blood cell velocity in the MCA were 62 ± 12 cm.s-1 and in the PCA were 44 ±11 cm.s-1.  Greater than 6000 studies have utilized this technique since the original experiments performed by Dr. Aaslid and colleagues, with 13 studies (Figure 2.3) indexing the intracranial velocity response during incremental exercise (Brugniaux et al., 2014; Fan & Kayser, 2013; Fisher et al., 2013; Hellstrom et al., 1996; Hellström & Wahlgren, 1993; Imray et al., 2005; Larsen et al., 2008; Marsden et al., 2012; Moraine et al., 1993; Olin et al., 2011; Smirl et al., 2012; Subudhi et al., 2008; Subudhi et al., 2011; Trangmar et al., 2014). Although  only one study has reported the regional (i.e., MCAv versus PCAv) response to a continuous exercise (Willie et al., 2011b), 10 studies (discussed in section 2.3.2) have investigated the MCAv response to a variety of exercise intensities with experimentally or environmentally augmented arterial blood gases (Fan & Kayser, 2013; Huang et al., 1991; Imray et al., 2005; Rasmussen et al., 2010b; Subudhi et al., 2008; Subudhi et al., 2009; Subudhi et al., 2011)).  The greatest benefit of TCD is that it is non-invasive, with a high reproducibility and temporal resolution needed for CBV indexing during exercise.  The limitation of TCD methodology is that it only provides an index of flow, and despite similar gCBF responses quantified using the Kety-Schmidt method (Jorgensen et al., 1992a) is not a true volumetric assessment; as such, dynamic changes in the diameter of the insonated vessels would impact the index of flow as per Poiseuille’s law (see below). Eq 2. � =(!!!!!)!!!!"! Where F equal flow, P1 is the inflow and P2 is the outflow pressure; r is the vessel radius;      76µ is the fluid viscosity (4-5 relative units); and L is the length of the vessel. Assessment of intracranial velocity using transcranial Doppler ultrasound The methodology for insonation of a cerebral vessel is summarized in the following steps: 1) application of a generous amount of acoustic gel to the temporal window of the subject and the Doppler probe in order to allow for the passage of the ultrasonic frequencies from probe to the subject.  This step is crucial as ultrasonic frequencies dissipate without acoustic gel; 2) The Doppler probe is positioned over the temporal window and secured to the headband once the desirable position is found. Initial placement is typically in the general window location that provides the best angle to insonate the specific intracranial vessel of interest.  The TCD headband ensures a stable probe position and ensures a quality signal is maintained throughout the entire assessment during protocol requiring dynamic movements; 3) In order to ensure an optimal signal is achieved and will remain throughout the entire experimental protocol an experienced sonographer will aim to adjust the angle of insonation to identify the vessel of interest based on their technical skill and anatomical awareness of the intracranial vessels in the circle of Willis [reviewed in (Willie et al., 2011a)]. The common insonation depths  for the intracranial vessels used in this thesis are 30-65 mm for the MCA, 45-55 mm for the M1 segment of the MCA, and 55-75 for the P1 segment of the posterior cerebral artery  (Nuttall et al., 1996); 5) Confirmation approaches to decisively identify the vessel of interest are performed.  A carotid compression technique is used to diminish the ipsilateral MCA, while either elevating the ipsilateral PCAv or not having any effect.  Additionally, occipital cortical activation typically achieved using a 10 second eye closed period followed by a 10 second eye open period will elevate PCAv by up to 20% with      77only a marginal response in the MCA (i.e., 5% increase). Validity of transcranial Doppler ultrasound Transcranial Doppler indices have been compared with gCBF (assessed via Xe clearance, Figure 2.7) during exercise (Jorgensen et al., 1992a). Dependent on the method used to assess gCBF, the change in CBV was equivelent (i.e., initial slope index) or progressively underestimated CBF by 10 - 40% (i.e., flow compartment model) with increasing exercise intensity.  To date no studies have investigated the TCD validity during exercise with MRI. However, in early studies investigating the influence of manipulation PaCO2  (23-60 mmHg) on the caliber of the MCA using MRI (1.5 tesla) demonstrated that the MCA diameter was unchanged (Serrador et al., 2000; Valdueza et al., 1997).  Unfortunately, the resolution (i.e., voxel size) of these early MRI studies was not high enough to detect the changes in MCA diameter recently observed by studies utilizing 3 Tesla (Coverdale et al., 2014) and 7 Tesla (Verbree et al., 2014) MRI.  These studies demonstrated that MCA diameter is altered when PETCO2 manipulation generates changes greater than 8 mmHg [reviewed in Ainslie & Hoiland (2014)].  Accordingly, if eucapnia (i.e., PETCO2 near baseline values) is maintained, CBV is a robust index of CBF (Ainslie & Hoiland, 2014).  However, a change in PETCO2 is greater than 8 mmHg, the caliber of the MCA can change by 6-8% in a hypercapnic direction (Coverdale et al., 2014; Verbree et al., 2014) and 4% in a hypocapnic direction (Coverdale et al., 2014). The impact of these changes in MCA diameter potentially result in a overestimation of the CBF response to hypercapnic by ~25%  or a 10% underestimation of the CBF response to hypocapnia (Ainslie & Hoiland, 2014). Therefore, sufficient increases in PETCO2 have a greater effect on intracranial CBV indices of CBF than reductions in      78PETCO2. Such findings are consistent with the notion that the entire cerebrovascular tree is sensitive to changes in PaCO2. To date, no study has attempted to rectify if this is also true during exercise with arterial blood gas manipulations.  Nevertheless, the collective findings reinforce the vital need of any study reporting CBV values from a TCD ultrasound to monitor PETCO2 closely throughout the experiment.  3.1.2. Vascular Duplex ultrasound   Vascular duplex ultrasound was used in the experimental Chapters 5 and 6; therefore, the following sections discuss the principles and methodological considerations as well as assessment techniques.  Vascular Duplex ultrasound principles and methodological considerations The vascular duplex ultrasound principles are similar to those discussed in the previous section with a few important distinctions.  First, unlike TCD, duplex ultrasound, as the name implies, utilizes two concurrent types of imaging resolution (i.e., temporal and spatial resolution) to quantify the velocity of blood vessels, as well as the cross-sectional area of the insonated vessels to calculate extra-cranial blood flow (ICA and/or VA). The spatial resolution of duplex ultrasound provides information of the returning ultrasound wavelength regarding the longitudinal and lateral, position of echogenic tissues, and is computed into a graphical representation of the underlying structures.  This graphical representation is commonly referred to as B-mode (brightness mode) is most easily described as a 2-dimensional grey scale image (Figure 3.3). Second, the ultrasound frequencies used in vascular Duplex ultrasound are significantly higher, ranging from 3-      7912 MHz; these higher Hz subsequently increase the axial resolution (i.e., longitudinal) necessary for the vessel wall identification.   Figure 3.3 B-mode image of the extra-cranial neck vessels (common carotid [CCA], internal carotid [ICA], and external carotid artery [ECA]) that deliver blood flow to the anterior cerebral circulation, collected using a vascular duplex ultrasound.        80Because duplex sonography provides a clear image of the desired vessel, duplex ultrasound removes the assumptions concerning the insonation angle during pulse-wave measurements, unlike TCD.  Similar to TCD, however, are the principles associated with maintaining a steering angle no greater than 60 degrees. Experience in B-Mode imaging results in appropriate steering the ultrasound beam to ensure that an adequate ultrasound angle is achieved.  Given the importance of the insonation angle in pulse wave velocity, the ability to steer the insonation angle is an important aspect of accurately assessing extra-cranial blood flow.  Figure 3.4 below illustrates how the insonation angle is both observable, and steered in order to maintain the sample volume parallel to the direction flow in the ICA during color coded-duplex scanning (i.e, simultaneous scanning of cross sectional area and velocity).        81   Figure 3.4. Color-coded Duplex imaging of internal carotid artery (orange color) illustrating the cross sectional area and velocity. The color-coding refers to the direction of the flow (i.e., orange towards or blue away from the ultrasound probe).         82Additionally, duplex sonography provides one additional measure useful in accurately assessing pulse wave velocity that TCD does not; angle correction.  An angle correction cursor is commonly located within the sample volume area of the ultrasound beam.  This angle correction, if done correctly, allows quantification of pulse-wave velocity in vessels that prove difficult to insonate (vascular plaque present or particularly tortuous vessel).  However, angle correction must be aligned parallel with the blood flow through the vessel (Figure 3.5).  Incorrect angle correction will result in an incorrect calculation of pulse-wave velocity.        83 Figure 3.5: In all images: Red stripped lines = vessel walls, red arrow = direction of moving blood, blue dashed line = ultrasound beam, green bar = angle cursor. A. The ultrasound beam has been appropriately steered to reduce the angle to 60°. B. The transducer has been “heeled” to decrease the angle of the beam relative to the vessel to an acceptable 60°. C. Appropriate alignment of angle cursor parallel to the vessel walls at 60°. D. Inappropriate placement of angle cursor relative to the direction of blood flow. In this case the system will assume at 60° angle (between ultrasound beam and angle cursor) as opposed to the actual angle of 45° (between the ultrasound beam and the blood flow) and will therefore underestimate the velocity calculated by ~30%.   60o 60o 60o 60o 60o 60o 60o 45 A B C D      84Duplex ultrasound assessment techniques In order to accurately perform a reliable and valid assessment of extra-cranial blood flow during dynamic protocols (i.e., exercise) requires a systematic and structured methodological approach.  The following sections highlight this systematic approach. Brightness Mode B-Mode imaging is the initial adjustment made during extra-cranial assessment. In order to optimize the B-Mode image and produce an accurate and stable representation of the underlying structures the order of B-Mode optimization is depth, focus, and 2D gain.  Below are detailed instructions for each of these B-Mode optimization points. Depth: Optimization of the depth of the live B-mode screen requires that the vessel of interest is set at a depth of about 2/3 of the display. This approach ensures that movement will not result in the vessel shifting off-screen but also means there is no wasted Doppler progpogation beyond the area of interest; thus allowing for higher frame rates (Gent., 1997), and interfaces such as the vessel wall occurs when the incident ultrasound beam is at 90° to the interface. To achieve a perpendicular alignment, the operator can “heel-toe” the transducer (tilt from end to end) or assess the vessel from a different acoustic window. A non-perpendicular approach is not recommended. Focus: Proper, optimization of the focus point, requires that the focus cursor is set approximate to the point of interest which ensures the focal zone encompasses the vessel and therefore provides the best lateral resolution at this level (Gent., 1997). Gain: Optimization of the gain on the b-mode image should be used to clearly identify      85the contrasting differences between the vessel walls (white) from the lumen (black), particularly if using edge-detection software. This optimization can be achieved in as follows. First, increase the overall gain in order to improve the echogenic contrast of tissue structures while attenuating any possible echogenic artifacts in the lumen.  Second, selectively (at the level of the region of interest) adjust the time gain compensation (TGC’s) sliders to increase the contrast locally to the corresponding tissue surrounding the vessel and the vessel walls, while reducing the TGC’s in order to further remove any echogenic artifact in the vessel lumen. Finally, subtracting the dynamic range (compression) will increase the contrast of the entire B-mode image (reduces the gray scales used resulting in a greater black and white contrasting image), and increase the noise rejection (mitigates acoustic noise from poor echogenic structures). Pulse-Wave Doppler Pulse-wave Doppler adjustments are the next step in optimization the extra-cranial vascular assessment.  Thus, the following adjustments are aimed at improving the quantification of the velocity profile and are based on the received Doppler frequency shift (discussed in section 3.1.1).  Angle of Approach: The ultrasound beam should be steered such that an appropriate Doppler angle is achieved (between 30 - 60 degrees; Figure 3.5) in order to reduce the measurement error and detect an adequate Doppler shift signal.   Similar to TCD, angles greater than 60 degrees should never be used as small errors in angle cursor alignment will result in unacceptably large errors in velocity.    Sample volume placement: The sample volume cursor indicates the depth along the beam      86axis from which Doppler information is being obtained. This should be placed in the fastest flowing stream. The width is adjusted to the sample volume to encompass the desired portion of the vessel; this is dependent on the equation being used to calculate flow and should be confirmed with the analysis software engineers. In most cases, the calculation of flow uses the time-averaged maximum velocity derived from the peak velocity envelope, so a sample volume that encompasses ~80% of the vessel lumen allows the peak velocity to be captured even if the vessel moves slightly; thus,  significant wall / tissue movement will likely be excluded. Angle correction: An angle correction cursor is usually located within the sample volume; this must be aligned with the direction of flow (see Figure 3.5D; note: the flow direction may be off-axis to the vessel walls if there is eccentric plaque present, or if the vessel is particularly tortuous). The angle created between the angle correction cursor and the central axis of the beam is displayed on the screen and this is the angle used in the calculation of velocity (Figure 3.5B).   Doppler baseline: The Doppler baselines in the spectral display which represent 0 cm.s.1, are adjusted in order to display the spectral waveform above the baseline (representing flow towards the transducer). If the baseline is too high, the spectral trace will appear to wrap around the display with the systolic peaks seen at the bottom of the display. There is not usually a retrograde velocity component in carotid vessels, especially in the ICA; however,  if the baseline is too low, the retrograde portion of the trace (if any) may be displayed at the top of the display in error.  Doppler scale: The velocity scale (pulse repetition frequency [PRF]) is displayed as the      87y-axis, which is set to accommodate the spectral display ensuring that the velocity of the blood being measured has sufficient range to allow for any expected increases in velocity. A spectral velocity wave form trace that occupied approximately 60 percent of the display was used at baseline in anticipation of the potential increases in velocity during the experimental protocols.   Doppler gain: In order to optimize the gain of the spectral Doppler velocity trace, the gain was increased to a point where a sufficient clear and crisp trace was observed.  Careful attention was paid to ensure that the gain was not increased as to present noise in the spectral window (e.g., random white spectral dots) or cause a mirrored spectral trace beneath the baseline to be present during scanning. Optimization of the dynamic range of the spectral trace was also reduced to improve the contrast of the trace (i.e., improve black and white background contrasts); this is important for the utilization of automatic edge-detection software.  As with B-mode, in certain individuals, noise rejection was increased to remove weak spectral noise in the background of the spectral trace.  Trade-off between B-mode and PWD: The unique utilization of B-mode and Pulse-wave Duplex, in this thesis, allowed for the simultaneous acquisition of vessel diameter and blood velocity, respectively. Thus, these collective measurements enable the calculation of beat-to-beat blood flow in the vessels that deliver blood to the brain. However, an important trade-off exists: For optimal B-mode resolution of the vessel walls (i.e., clear and crisp white echogenic walls) the vessel of interest needs to be orientated horizontally within the field of view which requires the ultrasound transducer to be parallel to the vessel perpendicular to the beam.  This increases the maximum reflection of the ultrasound beam and provides a clearer crisper image. However, for PWD, the rule of  0-     8860°, discussed above regarding the incident beam and direction of blood flow needs to be strictly followed in order accurately assess blood velocity. Angles of insonation greater than 60 degrees will lead to Doppler shifts that are to low, and poorly represent the correct velocity waveform. Therefore, given the importance of both modalities in acquiring volumetric blood flow, a compromise is needed in order to validly satisfy the principles of each imaging technique. Adjusting the steering of the beam from the transducer allows sonographers to achieve this compromise by reducing the angle of insonation in order to improve spectral Doppler analysis (see Figure 3.5). Similarly, manually adjusting the steering angle of the transducer (e.g., heel/ toe maneuverers) can ensure an appropriate angle of insonation (≤ 60°) is achieved (see Panel B Figure 3.5).  Identification of carotid and vertebral vessels To satisfactorily and standardize blood flow measurements of the carotid and vertebral vessels, all scans began in B-mode, with a generous application of gel to the transducer.  Each scan began with the identification of the common carotid artery (CCA) at the base of the neck. In many instances, the internal jugular vein is observable lateral to the CCA and the thyroid is observed medial to the CCA.  To distinguish between the CCA and the internal jugular vein, a pressure maneuver was performed which resulted in the jugular vein, which has a lower internal pressure, to be compressed where as the CCA remains taught given the higher internal pressures.  Once a adequate identification of the CCA was achieved, the technician would  track the transducer (~ 1-  3cm below the jaw) cranially towards the CCA bulb and bifurcation (Figure 3.3). The technician then      89optimized the Doppler signal in order to identify the ICA and ECA (Figure 3.3), identifying the orientation that the ICA and ECA originated from the bulb. These vessels are only visible in one plane provided they lie within the uni-scan plane of the transducer.  With regards to the experimental chapters in this thesis, the diameter and flow in the ICA and vertebral arteries are of interest; therefore it is essential to confidently differentiate between the ICA and ECA.  The ICA and ECA can be differentiated using the following five steps:  1) The ICA tends (~ 95% of individuals)  to lie more posterior-lateral compared to the anterior medial position of the ECA when scanning in the sagittal plane.  A 1 to 40 degree transducer pivot (i.e., anterior-medial to posterior lateral and vice versa) is used to alternate between ECA and ICA when they do not lie on the same scanning plane.  2) The ICA diameter (~6 mm) is typically larger than the ECA (~3-4 mm) at the CCA bifurcation, but similar as the vessels progress. 3) There are eight exracranial branches in the ECA, and are visible in some individuals in the proximal sections.  These branches supply the thyroid, as well as scalp and facial tissues.  The ICA has no extracranial branches. 4) The wave form of the ECA is a high resistance spectral Doppler trace.  This is defined as a spectral trace with a sharp upstroke that leads to systolic peak that is narrow at its apex, followed by a rapid decline during diastole towards baseline, with an almost zeroing of the trace at the lowest end of the diastole.   5) The waveform of ICA is defined as a low resistance spectral Doppler trace.  This pattern begins with a more gradual upstroke than the ECA, leading to a broader      90systolic peak that tapers forward flow throughout the cardiac cycle leaving a higher end-diastolic velocity (Figure 3.4). The steps above were followed in sequence to ensure standardization of the vessel insonation prior to beginning each experimental protocol.  Vertebral artery In all subjects, the vertebral artery (VA) was insonated between its origin from the subclavian artery and approximately the transverse process of the 4th cervical vetebrae. Identification was achieved using a lateral pivot (i.e., ipsilateral to the ear) of the transducer while the distal CCA was visible in the sagittal plane. The vertebral artery located deeper and lateral to the CCA and internal jugular vein in all subjects, with only sections of it visible between the vertebral processes (Figure 3.6). In some individuals, insonation of B-mode and PWV was only achievable distal to the 4th cervical section of the vertebrae but sufficiently proximal from the subclavian artery.       91 Figure 3.6. B-Mode image of the vertebral artery viewed between the cervical spinal chord sections (i.e., vertebral processes).        92 Computerized assessment of diameter: edge detection Collection of the extra-cranial diameter was achieved using a computerized edge-detection system that automatically tracks the artery wall. The use of a offline edge-detection software allows for the simultaneous acquisition of B-mode and Doppler which reduces inter-rater bias while improving blood flow resolution, thus facilitating more objective and accurate diameter measurements. 3.1.3. Cardio-respiratory instrumentation and assessment during exercise  In order to assess the how the cardiovascular and respiratory systems interact with the cerebrovascular system during exercise.  The following section will provide a brief explanation regarding the principles and methodology required to accurately assess the cardio-respiratory (i.e., respiration, blood pressure and heart rate) response to exercise. The specific details that are exclusive to the individual studies are contained within the Chapters of interest.  Data acquisition In order obtain the continuous cardiovascular (heart rate and arterial blood pressure) and respiratory (ventilation and partial pressure of end-tidal carbon dioxide) parameters reported in this thesis the signal specific signal transducers were connected to a continuous data acquisition device (Powerlab/16SP ML 880; ADInstruments, Colorado, US).  The data acquisition device was used to collect the converted and amplified physical signals from the various instruments in order for the data acquisition device to      93transmit the signal to the computer software program (LabChart7; ADInstruments, Colorado, US). These data are then displayed as digital computerized signals.  Assessment of heart rate In order to collect heart rate, each participant was instrumented to a 3-lead electrocardiography (ECG) transducer connected to the data acquisition device.  The 3-lead electrodes are placed in a triangular pattern around the heart utilizing Einthoven’s triangle to detect the direction and magnitude of the hearts electrical rhythms.  The electrical rhythms of the heart are a product of neuro-muscular electrical signals resulting in contraction (depolarization) and relaxation (repolarization) of the cardiac tissue via neural synapses intrinsic to the cardiac tissue.  The electrical signal detected by the ECG transducer is the result of the electro-chemical exchange caused by the exchanged of the ions involved in neural cardiac contraction and relaxation.  The direction and magnitude of the electrical signals detected during ECG tracing form a specialized pattern with 5 distinct shapes and waveforms indicative of the cardiac cycle stages: 1) Atrial depolarization, a small but positive increase in ECG is referred to as the P wave; 2 - 4) ventricular depolarization and almost concomitant repolarization of the atria is referred to as the QRS complex; described as a small brief negative reduction in the ECG trace (Q-wave), followed by a sharp and significant increase in ECG (R-wave) and a equal sharp and slightly more negative ECG increase than the Q wave (S-wave); 5) repolarization of the ventricles leads to a longer gradual rise in the ECG trace (T wave).  The largest increase in the ECG signal in healthy individuals using correct electrode placement is      94typically the R-wave, making it a easily used ECG landmark to calculate the continuous beat-to-beat heart rate by calculating the time between consecutive R-waves. Thus, heart rate was recorded and obtained via R to R wave detection on the electrocardiogram (lead II, Dual Bio Amp, ADInstruments) connected to the data acquisition device.  Blood pressure assessment via photoplethysmography Continuous assessment of blood pressure was performed using photoplethysmography (Finometer Pro, Finapres Medical Systems, Amsterdam, Neth). This approach provides a non-invasive means to estimates the beat-to-beat systolic and diastolic pressure fluctuations at the finger and is corrected to the brachial blood pressure. The photoplethysmograph utilizes infrared light to illuminate the red blood cells moving through the small non compliant arteries in the finger, and quantifies the amount of infrared light absorbed by the vessels (Nijboer et al., 1981).  This allows for continuous monitoring of the diameter and volume of red blood cells moving through these vessels via a fast pressure servo controller, and because the smaller arteries do not change in diameter changes in volume are used to index of the blood pressure in the finger.   The blood pressure in the finger is than filtered digitally, and corrected for the pressure difference between the finger and the brachial artery pressure in order to recreate a continuous intra-arterial waveform (Guelen et al., 2003). In a few instances in each experiment, during maximal exercise, non-invasive continuous assessment of blood pressure was unobtainable due to excess movement and/or hand compression.  In those instances automated manual blood pressure measurements (SunTech Tango, SunTech Medicals, Morrisville, NC, USA) were used to assess systolic and diastolic blood pressure.  The blood pressure recordings in Chapters 5 and 6 were also confirmed using a      95invasive pressure transducer catheter in the radial artery, and which was corrected to the positioning of the right atrium located in the midaxillary line.  Thus, throughout this thesis, mean arterial pressure was then either calculated (1/3 systolic blood pressure + 2/3 diastolic blood pressure) with the values obtained using the automatic blood pressure cuff or continuously derived from the mean envelope obtained from the continuous invasive or non-invasive intra-arterial blood pressure recordings.  Cerebrovascular resistance (CVR) and conductance (CVC) (CVRMCA and CVRPCA; CVCMCA and CVCPCA) for MCAv (CVRMCA, CVCMCA), PCAv (CVRPCA, CVCPCA), ICA (CVRICA, CVCICA), and VA (CVRVA, CVCVA) was calculated using the MAP or the respective CBV or CBF values (i.e., CVR = MAP/CBF; CVC = CBF/MAP). Assessment of ventilation and gas exchange Ventilatory parameters (i.e., breathing frequency, tidal volume and ventilation) were quantified using the flow signal from a two-way pneumotach (Series 3813, Hans Rudolph, Shawnee, KS) connected to the data acquisition device. The total deadspace of the breathing set-up was less than 250 ml. The pneumotach was calibrated against a 3L syringe in order to define the oscillatory pressure changes received by the spirometer pod (i.e., pressure amplifier connected with pnuemotach) during breathing.  The spirometer pod was attached to the data acquisition device and used to calculate continuous tidal volume, breathing frequency and VE.    Both PETO2 and PETCO2 were sampled from an ADInstruments gas analyzer (model ML 206, ADInstruments, Colorado, US) connected to the data acquisition device.  The signals derived from the gas analyzer (i.e., PETO2 and PETCO2) were sampled at the mouth using a thin plastic sample tube connected to a small pump that draws the gas      96sample into the transducer for measurement.  The signal obtained is the respective percentages of O2 and CO2 values in each breath.  The percent fluctuations of O2 during inspiration and expiration are then measured using an absorption spectroscopy transducer. A laser diode in the transducer emits a narrow band of light (760 nm) through the incoming gas sample and a detector quantifies the amount of light that absorbed by the O2 spectrum.  The greater the percentage of O2 in the gas sample the greater the absorption of light within the O2 spectrum subsequently resulting in reduced light signal is received by the detector in the transducer.  In contrast, lower percentages of O2 will absorb less of the emitted light, resulting in a greater quantity light detected by the transducer.  Quantification of the percent fluctuations of CO2 occurs following O2 assessment in the gas analyser. This is because CO2 assessment is achieved using non- dispersive infrared analysis; and although similar to absorption spectroscopy, the infrared analysis requires filtration of all of the infrared wavelengths except CO2.  This is achieved using an infrared lamp that is projected through the gas sample with infrared wave-length being absorbed by the gas molecules with similar spectral properties as the infrared light (i.e., CO2).  The absorbed infrared light is then filtered using an optical filter in the sampling tube that absorbs all of the wavelengths of light that are not CO2 derived before comparing the difference of light filtered and light absorbed at the end of the sampling tube.  This difference is proportional to the percentage of CO2 molecules in each breath-by-breath sample. The percentages of the end-tidal signals were further processed in the computer software,      97estimated using a simplified alveolar gas equation, which takes into account the atmospheric pressure (Pb = ~760 mmHg at sea-level and ~400 mmHg at high altitude) minus the vapour pressure (47 mmHg) as well as the fraction of end-tidal of O2 and CO2 (FETO2 and FETCO2, respectively).  Thus, the following calculation was used to estimate arterial blood gas tensions using the partial pressure of end-tidal O2 and CO2 (i.e., PETO2 and PETCO2):  Eq 3. �ET�2 ��� �ET��2 (����) =   (�!"�2 �� �!"��2) ×(�� –  47 ����) Where PETO2 and PETCO2 are the partial pressures of end-tidal oxygen and carbon dioxide values, and the % O2 or CO2 are the percent concentrations of collected form the gas samples, Pb is the atmospheric pressure sampled at the beginning of each test, and 47 vapour pressure loss from atmosphere to alveoli.  All reported end-tidal values were extracted from the expired end-tidal signal during end-expiration during rest and exercise.        98Chapter 4. Regional cerebral blood flow distribution during exercise: influence of oxygen  The following section has been published: Smith KJ, Wong LE, Eves ND, Koelwyn GJ, Smirl JD, Willie CK & Ainslie PN  (2012). Regional cerebral blood flow distribution during exercise: influence of oxygen. Respiratory Physiology & Neurobiology 184: 97–105.  I was responsible for drafting the manuscript, and creating all of the figures presented throughout the chapter. All of the co-authors edited the initial version once before submission to Respiratory Physiology and Neurobiology. I completed all revisions following the reviewers’ comments, and completed the final manuscript with the help of Prof. Ainslie for publication. Copyright approval for reproduction of figures and text was obtained from Elsevier B.V via their “Retention of Rights for Scholarly Purposes” policy. 4.1. Purpose and background Increases in exercise intensity up to ~70% of peak oxygen uptake (VO2peak) are reflected in elevations in cerebral blood flow (CBF) (Madsen et al., 1993; Marsden et al., 2011; Moraine et al., 1993; Olin et al., 2011; Subudhi et al., 2008). These changes in CBF are largely mediated via elevations in cerebral neuronal activity and the partial pressure of arterial carbon dioxide (PaCO2) (Olin et al., 2011; Sato et al., 2009b). At higher exercise intensities, CBF and the middle cerebral artery blood velocity (MCAv) decrease toward baseline values in parallel with hyperventilation-induced hypocapnia and consequent cerebral vasoconstriction (Moraine et al., 1993) The cerebral circulation is composed of the anterior and posterior circulations. The anterior/middle cerebral arteries received their blood supply from the left and right      99internal carotid arteries, where as the posterior cerebral arteries receive their blood supply from the basilar artery, via the two vertebral arteries (Figure 3.1). With the exception of two studies (Sato et al., 2011; Willie et al., 2011b), research in humans has only explored the relationship of CBF (or cerebral velocity) control in the anterior portion of the cerebral circulation. Sato et al., (2011) reported that blood flow in the internal carotid artery (ICA) returned to resting levels after 50% workload maximum (Wmax), whereas blood flow in the external carotid artery, common carotid artery and vertebral artery (VA) progressively increased up to 80% of the VO2peak (Sato et al., 2011). Willie et al., (2008) reported greater relative increases in PCAv (26±23%) compared to MCAv (15±14%) during exercise at 60% of maximal workload (Wmax).  Together, these findings indicate a difference in the control of blood flow through the anterior and posterior cerebral circulations during exercise.  It is currently not known if similar regional disparities are observed at increasing intensities of exercise or whether the anterior and posterior cerebral circulations respond differently to changes in partial pressure of arterial oxygen (PaO2).  Breathing a hypoxic gas causes cerebral dilation, thus reducing cerebral vascular resistance and increasing CBF in humans (Cohen et al., 1967; Kety & Schmidt, 1948a). Hypoxic cerebral vasodilation can be identified by a rise in CBF (Wilson et al., 2011) in proportion to the severity of isocapnic hypoxia (Gupta et al., 1997; Wilson et al., 2011); however, in normal resting conditions the hypoxic-induced activation of peripheral chemoreceptor activity leads to hyperventilatory-induced lowering of PaCO2 and subsequent cerebral vasoconstriction that can negate the dilatory effects of hypoxia on the      100cerebral vasculature. This response is seen during exercise in hypoxia (Ainslie et al., 2007; Subudhi et al., 2008); as such, the exercise-induced change in MCAv during acute hypoxia is similar to breathing air. It remains to be determined if the same effect occurs in the posterior cerebral arteries and whether blood flow is regulated differently in the MCA and PCA during hypoxic exercise.  Little is known about the cerebrovascular response to exercise in hyperoxic conditions.  Under resting conditions, hyperoxia (i.e. FIO2 > 0.21) is a respiratory stimulant in adults (Becker et al., 1996), which leads to the hyperventilation induced reduction in PaCO2 and accompanying vasoconstriction of the cerebral vascular beds (Floyd et al., 2003).   It has been repeatedly demonstrated that while breathing hyperoxia during exercise, respiration is reduced, resulting in elevations in PaCO2 compared with normoxic exercise (Asmussen & Nielsen, 1946; Bannister & Cunningham, 1954; Miyamoto, 1995; Wilson and Welch, 1975). At rest, MCAv increases ~3.8% for every 1 mmHg increase in PaCO2 (Ainslie and Duffin, 2009). Consequently, any increase in PaCO2 during exercise with hyperoxia, should result in an increase in MCAv.  It is unknown if this relationship is changed during hyperoxic exercise and whether anterior and posterior CBF differences exist.  The aim of this study was to investigate concurrent blood flow velocity in the anterior and posterior cerebral circulation during exercise, while breathing normoxia, hypoxia or hyperoxia.  We examined the hypothesis that increases in the regional distribution of CBF during normoxic incremental exercise would be greater in the posterior circulation than the anterior circulation.  A secondary objective was to investigate the effect of breathing a hypoxic or hyperoxic oxygen concentration on the regional distribution of blood flow to the anterior and posterior cerebral circulation during exercise.         1014.2. Methods Subjects Ten healthy male volunteers (age: 22±3 years, weight: 76±9kg, height: 178±9cm) participated in three graded exercise tests under different oxygen manipulations. The study had approval from the University of British Columbia research ethics board (H10-02378). All subjects provided voluntary written and informed consent. No subjects had any respiratory or circulatory disease or any contraindications to exercise. All were non-smokers and were not taking any medications. Each subject underwent a familiarization session involving comfortable placement of instruments and bike adjustments, and resting baseline measurements.  Prior to testing subjects were asked to abstain from caffeine, alcohol, and heavy exercise 24 hours prior to participation in each condition.  Subjects were also instructed to avoid eating 4-hours prior to testing, and arrive hydrated (i.e. consume one litre of water the evening prior, and 0.5 litre on the morning of testing).    Study Design In a single-blind randomized cross-over trial, each subject performed three graded exercise tests while breathing different inspired oxygen fractions: hypoxia (FIO2= 0.16); normoxia (FIO2= 0.21); and oxygen (FIO2= 1.0).  Each test was separated by > 48 hours, and at the same time each day.   Medical grade gases were delivered from K-sized cylinders (Praxair inc, Kelowna, BC, Canada) via a Douglas Bag (Hans Rudolph, Kansas City, MO, USA) and low-resistance tubing to a two-way breathing valve (2700 Series, Hans Rudolph, Shawnee, KS, USA).  Upon arrival to the laboratory, subjects were seated on the cycle ergometer (Velotron, RacerMate, Seattle, USA) and instrumented with TCD and cardiorespiratory equipment      102as outlined in chapter 3.0. Following baseline measurements breathing room air, the test gas was washed in for 10-min before resting measures were repeated.   After a 5 minute warm-up at 100W the graded exercise test began at 150W and was increased 30 W every 2 min until a clear decline in end tidal carbon dioxide (PETCO2)(5% reduction in PETCO2) was observed signifying hyperventilation (Beaver et al., 1986). After this point workload was increased at 30W/min until volitional failure. Subjects were instructed to keep eyes open throughout the protocol in order to avoid confounding posterior cerebral blood flow velocity from the effects of neurovascular coupling (Willie et al., 2011).     Cerebral blood flow velocity, heart rate and arterial blood pressure:  Regional CBV (MCAv and PCAv), heart and non-invasive blood pressure were measured and recorded as outlined in chapter 3.0.  Analyses:  Five minutes of baseline (BL) recordings were used to examine the resting values associated with rest and during exposure to the different FIO2. Steady state 30-second segments ending 10-seconds prior to the end of each stage were analyzed for heart rate, MCAv, PCAv, PETO2, PETCO2. MAP and thus CVC/CVR measurements were taken as a snap shot within the 30-second segments as the automatic blood pressure cuff was unable to make a continuous blood pressure sample. Nevertheless, we have previous confirmed the validity of this automated blood pressure approach against intra-arterial BP recording (Marsden et al., 2011). At rest, both MCAv and PCAv are presented in absolute values. During exercise, changes in MCAv and PCAv was calculated both in absolute (cm.s-1) and relative terms (%) from rest. In brief, as absolute change signifies the magnitude of      103the stimulus response regardless of baseline, which permits the investigation of individual vessel response.  The use of relative changes control for the disparate baseline velocities and permit more meaningful within artery comparisons (i.e., PCA vs. MCA). Each incremental test was separated and analyzed using the percentage of the workload maximum (ie; 40, 50, 60, 70, 80, 90 and 100% Wmax) and all variables are presented as a % of Wmax.  Statistics:  A paired samples t-test was performed on all dependent variables to ascertain differences at rest with each gas administration.  The alpha-level was set at 0.017 to correct for multiple comparisons. A one-way repeated measures analysis of variance (ANOVA) was used to compare the effects of incremental exercise and FIO2 on all dependent variables for each intervention.  A two-way repeated measures ANOVA was performed to compare the absolute and relative effects of FIO2 at rest and during exercise on the MCA and PCA. For all ANOVA analysis the alpha level was set at 0.05. When the ANOVA found significant differences, paired samples t-tests with a Bonferroni correction factor were applied to all significant interaction effects.  Pearson r correlations were performed to determine linear relationships between the absolute change from rest to 60% Wmax in MCAv and PCAv, and from rest to 40 to 60 % Wmax with PETCO2 for each condition. The R2 value provides an indication of the shared variance between the two variables.  4.3. Results The effect of hypoxia and hyperoxia at rest:       104There was no significant difference in any dependent variable between the three baselines on room air (Table 4.1). The between day coefficient of variation for MCAv and PCAv were 2.6% and 2.4%, respectively. Compared to breathing room air, hyperoxia elevated PETO2 from 105 ± 12 to 578 ± 79 mmHg and reduced PETCO2 from 38 ± 3 to 33 ± 2 mmHg; P<0.016). Hyperoxia at rest also reduced CVRPCA (P<0.016), but had no effect on MCAv and PCAv. Hypoxia reduced PETO2 by 27 ± 8 mmHg (P<0.016) with no significant changes in PETCO2 or MCAv. In contrast, PCAv was reduced (-7 ± 3 %) during hypoxic rest (P<0.016). As expected, PCAv exhibited a lower baseline velocity in all conditions compared to MCAv (P<0.003). There was no observed interference from the crossing of the bilateral TCD beams in any of the subjects.   Table 4.1. Cardiorespiratory and cerebrovascular responses during baseline and exercise in normoxic, hypoxic and hyperoxic gas exposures.   Baseline Exposure 40% 50% 60% 70% 80% 90% 100% Normoxia           PETO2 (mmHg) 104 ± 2 109  ± 3 99 ± 7 102 ± 11 104 ± 10 107 ± 10 111 ± 10* 117 ± 7* 121 ± 6*  PETCO2 (mmHg) 36 ± 3 37 ± 3 44 ± 2* 43 ± 3* 43 ± 2* 42 ± 4* 39 ± 4 36 ± 6 34 ± 6  HR (BPM) 69 ± 5 71 ± 3 146 ± 10 148 ± 18 159 ± 16 169 ± 14 179 ± 13 183 ± 12 187 ± 8  MAP (mmHg) 91.3 ± 6.0 98.1 ± 5.9 101 ± 8* 105 ± 8* 107 ± 9* 106 ± 10* 106 ± 12 109 ± 8* 113 ± 13*  MCAv (cm.s-1) 64 ± 10 63 ± 13 80 ± 12* 79 ± 15* 79 ± 16* 79 ± 17* 76 ± 16 74 ± 16 69 ± 15  PCAv (cm.s-1) 44 ± 5 43 ± 3 52 ± 8* 53 ± 9* 52 ± 8* 51 ± 8 49 ± 8 47 ± 6 45 ± 7  CVRMCA 1.5 ± 0.3 1.6 ± 0.2 1.3 ± 0.3 1.4 ± 0.3 1.4 ± 0.3 1.5 ± 0.4 1.5 ± 0.4 1.4 ± 0.1 1.3 ± 0.2  CVRPCA 2.1 ± 0.2 1.8 ± 0.3 1.9 ± 0.4 2.0 ± 0.4 2.2 ± 0.5 2.2 ± 0.2 2.3 ± 0.2 2.4 ± 0.4   CVCMCA 0.70 ± 0.12 0.69 ± 0.12 0.79 ± 0.15 0.75 ± 0.19 0.74 ± 0.19 0.75 ± 0.18 0.72 ± 0.17 0.68 ± 0.16 0.62 ± 0.16  CVCPCA 0.48 ± 0.05 0.44 ± 0.03 0.51 ± 0.09 0.50 ± 0.09 0.48 ± 0.09 0.48 ± 0.08 0.48 ± 0.06 0.43 0.05  Hypoxia           PETO2 (mmHg) 105 ± 7 78 ± 1* 70 ± 8* 71 ± 5* 74 ± 4* 77 ± 4* 82 ± 4* 90 ± 12* 93 ± 8*  PETCO2 (mmHg) 38 ± 4 38  ± 4 43 ± 3* 42 ± 4* 41 ± 3 39 ± 4 36 ± 47 34 ± 4.2* 31 ± 4*  HR (BPM) 75 ± 6 77 ± 6 147 ± 14 150 ± 19 162 ± 17 170 ± 14 179 ± 10 182 ± 10 188 ± 10  MAP (mmHg) 92 ± 6 91 ± 6 102 ± 6 99 ± 10* 105 ± 11* 107 ± 10* 113 ± 11* 115 ± 17* 119 ± 20  MCAv (cm.s-1) 64 ± 9 63 ± 13 77 ± 8* 79 ± 11* 78 ± 10* 77 ± 11 73 ± 12 73 ± 11 70 ± 10  PCAv (cm.s-1) 45 ± 7 42 ± 5* 56 ± 8* 52 ±11* 52 ± 11* 53 ± 9* 51 ± 10* 51 ± 9 50 ± 9  CVRMCA 1.4 ± 0.3 1.4 ± 0.3 1.4 ± 0.3 1.3 ± 0.2 1.4 ± 0.3 1.5 ± 0.3 1.5 ± 0.3 1.6 ± 0.3 1.8 ± 0.4  CVRPCA 2.1 ± 0.3 1.6 ± 0.2 1.9 ± 0.5 2.0 ± 0.4 2.0 ± 0.3 2.1 ± 0.5 2.2 ± 0.5 2.6 ± 0.4*   CVCMCA 0.72 ± 0.13 0.71 ± 0.13 0.77 ± 0.11 0.80 ± 0.14 0.75 ± 0.12 0.72 ± 0.13 0.63 ± 0.10 0.66 ±  0.14 0.59 ± 0.08  CVCPCA 0.48 ± 0.09 0.49 ± 0.06 0.55 ± 0.09 0.53 ± 0.13 0.49 ± 0.09 0.49 ± 0.10 0.44 ± 0.10 0.46 ± 0.12   Table 4.1. Cardiorespiratory and cerebrovascular responses during baseline and exercise in normoxic, hypoxic and hyperoxic gas exposures. Hyperoxia           PETO2 (mmHg) 105 ± 11 578 ± 79* 597 ± 64* 603 ± 54* 612 ± 47* 607 ± 61* 611 ± 53* 610 ± 62* 601 ± 83*  PETCO2 (mmHg) 38 ± 4 33 ± 2* 43 ± 3* 42 ± 5* 44 ± 3* 43 ± 4* 41 ± 5 37 ± 5 33 ± 3  HR (BPM) 74 ± 5 70 ± 6 142 ± 16 142 ± 28 161 ± 16 171 ± 18 181 ± 14 187 ± 12 190 ± 11  MAP (mmHg) 92 ± 8.7 94 ± 8.5 111 ± 1.1* 112 ± 8.2* 114 ± 7.7* 116 ± 10.9* 118 ± 8.8* 125 ± 8.7* 130 ± 5.6*  MCAv (cm.s-1) 63± 11 63 ± 9 78 ± 10* 79 ±13* 84 ± 14* 81 ± 15* 78 ± 17 72 ± 19 70 ± 19  PCAv (cm.s-1) 46 ± 7 44 ± 3 63 ± 6* 61 ± 9* 63 ± 7* 62 ± 8* 60 ± 9* 57 ± 8* 51 ± 9*  CVRMCA 1.5 ± 0.2 1.5 ± 0.3 1.3 ± 0.2 1.3 ± 0.2 1.4 ± 0.2 1.4 ± 0.3 1.4 ± 0.3 1.7 ± 0.3 1.9 ± 0.4  CVRPCA 2.0 ± 0.1 1.6 ± 0.3 1.6 ± 0.2 1.7 ± 02 1.7 ± 0.1 1.7 ± 0.1 1.9 ± 0.3 1.9 ± .1   CVCMCA 0.68 ± 0.13 0.67 ± 0.12 0.70 ± 0.09 0.71 ± 0.12 0.73 ± 0.13 0.69 ± 0.13 0.65 ± 0.15 0.58 ± 0.16 0.54 ± 0.15  CVCPCA 0.50 ± 0.09 0.48 ± 0.05 0.57 ± 0.06 0.54 ± 0.09 0.55 ± 0.07 0.52 ± 0.08 0.50 ± 0.08 0.46 ± 0.07   * signifies difference from baseline values, p<0.05. Mean Maximum workload and time spent exercising at during each stage are as follows; Normoxia Wmax = 376 Watts, mean time = 15 min; Hypoxia Wmax = 338 Watts, mean time = 12 min; Hyperoxia Wmax = 395 Watts, mean time = 16 min.      107The effect of incremental exercise on cerebral blood flow velocity:  There was no significant difference in the maximum achieved wattage with any gas condition (p = 0.25). With normoxia, MCAv was increased from resting values between 40-90% Wmax (P<0.001) but returned to baseline values at 100% Wmax (Figure 4.1).  The peak increase in MCAv occurred at 40% Wmax (~27 % increase).  PCAv was also elevated above baseline values during incremental exercise at 40% Wmax (+9 ± 5 cm.s-1) and 50% Wmax (+10 ± 5 cm.s-1)  before returning to baseline velocities, P<0.001 (Figure 4.2).  The peak increase in PCAv occurred at 50% Wmax (~ 23 % increase).      108 Figure 4.1. Middle cerebral arterial (MCAv) and posterior cerebral artery blood flow velocity (PCAv) expressed in cm.s-1, during baseline, gas exposure and during incremental exercise at percentage of peak work rate intervals while breathing a normoxic (●), hypoxic (■) and hyperoxic (▲) .‡ denotes significance (P<0.001) between hyperoxia and normoxia. denotes significance (P<0.001) between hyperoxia and hypoxia.      109The effects of exercise on MCAv versus PCAv breathing normoxia:  The absolute MCAv and PCAv velocities were different at intensities between 40-90% Wmax ( P<0.0001; Table 4.1 & Figure 4.1) while breathing room air. Differences in the absolute change in MCAv compared to PCAv was only observed at 40% Wmax (Figure 4.2); the absolute change between each artery was not different between 50-100% Wmax. No difference in the relative change between MCAv and PCAv was observed at any point throughout normoxic exercise (Figure 2B). Whilst breathing normoxia, PETCO2 was increased at both 40% Wmax (44 ± 3 mmHg) and 60% Wmax (43 ± 2 mmHg) compared to baseline (37 ± 3mmHg), before returning to baseline values at 100% Wmax.        110 Figure 4.2. Middle cerebral arterial (MCAv) and posterior cerebral artery blood flow velocity (PCAv) expressed in cm.s-1, during baseline, gas exposure and during incremental exercise at percentage of peak work rate intervals while breathing a normoxic (●), hypoxic (■) and hyperoxic (▲). ‡ denotes significance (P<0.001) between hyperoxia and normoxia. denotes significance (P<0.001) between hyperoxia and hypoxia.      111The effect of hypoxia and hyperoxia on MCAv and PCAv during incremental exercise  Breathing hypoxia or hyperoxia resulted in MCAv being elevated above baseline at 40% Wmax; this elevation remained until 60% Wmax in hypoxia and at 70% Wmax during hyperoxia (P<0.001; Table 4.1).  No differences were observed between the absolute and relative changes in MCAv between the conditions. During hypoxia, PCAv was greater from baseline at intensities up to 80% Wmax, P<0.001 (Table 4.1); however, these changes  did not differ significantly from normoxia. In contrast, during exercise in hyperoxia, PCAv remained significantly above baseline from 40 % Wmax (+19 ± 4 cm.s-1) to 100% Wmax  (+7 ± 5 cm.s-1).  Furthermore, throughout exercise, hyperoxia resulted in significant absolute and relative increases in PCAv compared to both normoxia (40%-100% Wmax) and hypoxia (40%-90% Wmax).  Effects of incremental exercise on MCAv versus PCAv during hypoxia or hyperoxia: In hypoxia, absolute MCAv was significantly greater than PCAv at all intensities (Table 4.1). At 60% Wmax, the absolute change in PCAv, with hypoxia was lower compared to the absolute change in MCAv (mean difference = 5.5 cm.s-1, P<0.0001, Figure 4.2A). During hyperoxic exercise, absolute values for MCAv and PCAv were only different between 40-60% Wmax. Similarly, there was a significant difference in absolute change in MCAv and PCAv at 60% Wmax (~21 ± 13cm.s-1, P<0.0003). No significant relative differences were observed between the changes in PCAv and MCAv from baseline during exercise while breathing any gas.   Effects of hyperoxia and hypoxia on MAP and CVC/CVR:      112MAP was significantly higher during exercise with hyperoxia compared to normoxia and hypoxia at all intensities. CVC/CVRMCA and CVC/CVRPCA were not different between any gas at any exercise intensity.  Correlations between MCAv and PCAv with PETCO2: Absolute changes in PETCO2 from hyperoxic rest to 40% Wmax were greater (+10mmHg) compared to both normoxic (+7 mmHg) and hypoxic (+5 mmHg) rest, P<0.016. While the change in PETCO2 from rest to 40% Wmax was related to change in MCAv (Figure 4.3) for both normoxia (R2 = 0.24, P<0.05) and hyperoxia (R2 = 0.80, P<0.05), there were no significant correlations during hypoxia.  Moreover, there were no observable relationships between the changes in PETCO2 and PCAv during any oxygen condition from rest to 40% Wmax (Figure 4.3). Nevertheless, correlations were found between MCAv and PCAv during each condition (normoxia R2 = 0.64; hypoxia R2 = 0.15; hyperoxia R2 = 0.69, P< 0.05; Figure 4.4).   Figure 4.3. The relationship between the absolute changes in  the middle and posterior cerebral artery velocity (MCAv and PCAv, respectively (cm.s-1)) to changes in the end-tidal partial pressure of CO2 (PETCO2 (mmHg)) from exposure to 40% workload maximum in A) Normoxia, B) Hypoxia, and C) Hyperoxia.       114 Figure 4.4. Relationship between the absolute changes from rest to 40% Wmax between the middle cerebral artery (MCAv, cm.s-1) with posterior cerebral artery (PCAv, cm.s-1) in A) normoxia, B) hypoxia C) hyperoxia.  ! ! !1154.4. Discussion There are three novel findings from the current study. First, during the first two minutes of incremental exercise in normoxia, the absolute changes from resting values were lower in  PCAv compared to MCAv.  This finding is contrary to the original hypothesis that incremental exercise would result in a larger response in the posterior circulation compared to the anterior circulation.  Second, supporting the initial aim to investigate regional distribution of CBF while breathing hypoxia or hyperoxia during exercise, the results indicate that the posterior circulations response was greater than the response in MCAv during hypoxic and hyperoxic incremental exercise. Third, and unexpectedly, the findings demonstrated that hyperoxic exercise resulted in larger absolute and relative increases in PCAv compared with normoxia.   Changes in CBFv during normoxic exercise: The majority of exercise studies to date have examined CBF only in the anterior circulation. Although the anterior pathway contributes approximately 70% of the total cerebral circulation, only a few studies have attempted to examine other regional changes (e.g., in the posterior circulation). The relevance of adequate blood flow to the posterior region has implications for blood supply to the medulla oblongata, an area that contains cardiac, vasomotor and respiratory control centers of intrinsic importance for the maintenance of consciousness. The pattern of CBF during incremental exercise in the current study is similar to previous studies measuring MCAv during exercise (Marsden et al., 2011; Moraine et al., 1993; Olin et al., 2011). At the onset of normoxic exercise, MCAv, PETCO2, and MAP increase above baseline values and remains stable until an intensity of 70% Wmax is reached. After this 70% Wmax, hyperventilation results in ! ! !116reductions in PaCO2  followed by a subsequent vasocontrictive reduction in CBF towards baseline values. Interestingly, PCAv during normoxic exercise followed a similar pattern as MCAv. However, in contrast to the relationship between MCAv, MAP and PETCO2, a relationship with these parameters and PCAv remained absent.   Sato et al., (2009a) demonstrated that exercise increases central command, more specifically the increases in cardiorespiratory systems (eg; blood flow, heart rate, ventilation, etc.) and motor activation are in part produced via descending neural pathways in a feed forward mechanism.  Alterations in the regional blood flow distribution to autonomic regions such as the insular cortex (Williamson et al., 1997), an area fed by the anterior cerebral arteries (Sato et al., 2009a; Williamson et al., 2003) suggests that neuro-metabolic activation in this region is partly responsible for increases in anterior cerebral blood flow. Increases in local and global cerebral activation, may result in an increased absolute blood flow demand to the larger anterior regions compared to the smaller but relatively similar activated posterior regions. However, because of the similar relative increases in both anterior and posterior cerebral blood flow velocities it may be that anterior and posterior cerebral metabolic and neural activation is relatively similar, resulting in similar relative increases to cortical regions of varying size.  This is further supported by the lack of any relationship  between PCAv, MAP and PETCO2 and the strong relationship between PCAv and MCAv during normoxic exercise. Regional differences during low intensity steady state exercise (i.e. < 50% WMax) have been reported previously  (Willie et al., 2011b), demonstrating a larger relative change in the blood flow distribution to the posterior region compared to the anterior region during steady state normoxic exercise.  This finding is in contrast to the current results that have ! ! !117revealed no relative differences in regional blood flow distribution. Although the steady state exercise in the previous study was similar in intensity to our 40% Wmax, it may be that during a more prolonged exposure (~9 min vs. 2 min) at steady state exercise (Willie et al., 2011b) resulted in differential changes in MCAv and PCAv.  The observed changes in MCAv are comparable with the pattern of ICA blood flow changes previously reported during exercise (Sato et al., 2011); however, PCAv does not follow the linear increases as reported in the vertebral arteries during incremental exercise (ie; +10% VA flow between 60% and 80% VO2 max (Sato & Sadamoto, 2010; Sato et al., 2011). In our study PCAv decreased between 5-10% at intensities above 60%Wmax.  There are a number of potential mechanisms for these contrasting findings between the current study and those observed by Sato et al., (2011).  First, the PCA, distal to the VA, may vasodilate to maintain flow (thus leading to a reduction in PCAv) while compensating for the large increase in perfusion pressure stemming from the larger flow of the proximal VA’s during exercise. Second, the difference between PCAv and VA response during exercise may be the result of divergent flows between the VA and the basilar artery which is located distal to the PCA. The spinal arteries, cerebellar, pontine and labyrinthine arteries are all truncations of the VA and basilar arteries which may divert VA flow prior to reaching the PCA (Nowinski et al., 2011).  Furthermore, in our study (Table 1), both MCAv and PCAv temporally tracked the increases in PETCO2, yet only the MCAv during normoxic exercise was correlated with PETCO2. Contrasting results are found within the literature, with some studies indicating a reduced sensitivity to CO2 in the posterior circulation compared to the anterior (Sato et al., 2012; Sorond et al., 2005), an increased sensitivity to CO2 in the posterior circulation ! ! !118(Willie et al., 2012,), and others indicating no difference between the regions (Park, 2002; Rozet et al., 2006). Additionally, comparisons between the intracranial arteries measured by both Sato et al. (2012) (MCA and BA) and Willie et al. (2012) (MCA and PCA) demonstrated no differences in reactivity in the respective anterior and posterior intracranial arteries when only changes in velocity parameters and not flow were used.  The differences associated between the reactivity of the posterior and anterior circulations in may either be due to physiological differences in anatomy or technical differences in analysis and measurement. Willie et al. (2012) compared both absolute (ml.min-1.mmHg-1, cm.s-1.mmHg-1) and relative (%.mmHg-1) regional reactivity in three different ranges, eg; hypocapnia, hypercapnia and overall in accordance with the differences in reactivity due to the nature of the sigmoidal reactivity curve discussed in (Battisti-Charbonney et al., 2011). Whereas in Sato et al. (2012), the authors solely used the relative changes within the overall reactivity range between the different regional vessels, ICA vs VA, and MCA vs BA. It should be further noted that Sato et al. (2012) measured blood flow in the ICA and VA, as well as MCAv in a semi-recumbent position and BAv in an upright position.  Willie et al., (2012) measured each subject while supine.  Despite these differences in the reactivity ranges used in each study, it is apparent, that CO2 reactivity in the anterior and posterior regions is partially related to both location, method of the measures, ie; major conduit arteries (ml.min-1. mmHg-1) vs intracranial vessels (cm.s-1.mmHg-1), and possibly body position.  However, all of these studies were conducted at rest. Thus, at rest and during exercise, further research investigating cerebral vascular reactivity with both cerebral blood flow and velocity is needed to explore the ! ! !119influencing factors involved in the regulation of posterior CBF throughout the entire cerebral circulation during exercise.   Influence of FIO2 on CBFv during exercise: Exercise in acute hypoxia did not alter MCAv compared to normoxic exercise. This finding is consistent with previous studies investigating the influence of acute hypoxia on MCAv during exercise (Ainslie et al., 2007; Subudhi et al., 2008). However, in these previous studies the authors attributed the lack of response in MCAv during hypoxic exercise due to a balancing influence of vasodilatory and vasoconstrictive properties associated with a reduction in both PaO2 and PaCO2 observed during exposure during severe hypoxia. The maintenance of normoxic velocities in the current study suggest that the mild hypoxic stimulus used in the current study was either insufficient to alter the balance of PaO2 and PaCO2 to an extent to alter CBF (i.e., comparable influences of cerebral dilation and constriction).  The effects of hyperoxia on regional CBFv has not previously been measured in humans during exercise. We found that MCAv was not elevated during hyperoxia compared to normoxic exercise whereas PCAv was significantly elevated (Figure 2). These results support our hypothesis that there are regional differences in how CBF is regulated, at least during mild intensity hyperoxic exercise (i.e., 40% Wmax),.  The importance of PaCO2 on the cerebral vasculature has been previously highlighted at rest, such that for a ∼ 1mmHg change in PaCO2, MCAv would exhibit a paralleled change of 3.8% (Ainslie and Duffin, 2009, #2179).  If a similar relationship exists between PaCO2 and the PCAv, then the 10 mmHg increase in PETCO2 from resting values ! ! !120(ie; throughout 40 – 70% Wmax) could explain the ∼40% increase in PCAv during exercise with oxygen. However, unlike in the MCA, where there was a significant relationship between the change in PETCO2 (rest to 40%Wmax) and MCAv (R2=0.8, P<0.05), we found no association between the change in PETCO2 and the elevations in PCAv. Although we acknowledge that correlation does not establish causation, this finding may indicate that the increase in PCAv during hyperoxia was likely related to mechanisms other than an increased PaCO2. Mechanisms explaining our findings may include factors such as differences in cerebral autoregulation, sympathetic innervation or region specific physiological and/or anatomical differences. Potential mechanisms of regional differences in CBF velocity: It is apparent from the current findings that breathing mild hypoxic stimuli at rest selectively perturbs the posterior circulation.  The observable decrease in PCAv, compared to MCAv during hypoxic rest in absence of any change in PETCO2 or MAP indicates the posterior circulation may be responding to the reduction in PaO2.  The mild reduction in PETO2 may result in a vasodilatation of the PCA and subsequently decreasing PCAv. Previous studies have shown that in the presence of severe hypoxia the MCAv remains stable as the vasodilatory effects of a reduced PaO2 are countered by the vasoconstrictive properties of a reduced PaCO2 as a result of an increased alveolar ventilation (Ainslie et al., 2007). Further studies are required to determine if the posterior cerebral arteries are more sensitive to fluctuations in PaO2 compared to the anterior cerebral circulation and how these differences effects regional cerebral autoregulation and sympathetic control of the cerebral vasculature.  ! ! !121To date only four studies have attempted to assess regional CBF during normoxic exercise (Delp et al., 2001; Sato & Sadamoto, 2010; Sato et al., 2011; Willie et al., 2011b). Each of these studies identified a disparate regional distribution of CBF between the anterior and posterior brain regions during exercise in mammals, which is further supported by our data. Speculation regarding these regional differences include temperature regulation, sympathetic innervations, cerebral autoregulation, PaCO2 and or a region specific neuro-metabolic demands in the brain during exercise. Regional differences in any of the aforementioned physiological systems may result in the exercise stimulus on the anterior region of the brain demanding a larger absolute contribution of CBF during normoxic exercise than the demand of the autonomic and respiratory control centres located in the brainstem. In contrast, during hypoxic exercise, the modest hypoxic stimulus may selectively increase the relative demand of the posterior circulation to a similar level as the anterior circulation.  The large increase in PCAv during hyperoxic exercise, coupled with the lack of change in MCAv during any of the exercise conditions, is a unexpected finding. The increase in CBF to a specific region could lend support to a possible increase in metabolic demand within that region.  However, studies indicating changes to autonomic responses such as reduced ventilation and heart rate during exercise or a reduced stress on skeletal muscle during hyperoxic exercise suggest a reduced metabolic demand within the body (Asmussen & Nielsen, 1946; Bannister & Cunningham, 1954; Miyamoto, 1995).  Whilst speculative, during hyperoxic exercise, the large increase in PCAv may be related to a concomitant increase in the posterior communicating arteries, distributed from the anterior circulation from an intact Circle of Willis.  If so, the large increase in PCAv ! ! !122during hyperoxia may be a product of a shared increase in the anterior and posterior blood supply. Figure 4 highlights the strong relationship between PCAv and MCAv during both normoxia and hyperoxia whereas changes in MCAv and PCAv were unrelated during hypoxia. The limitations of correlational analysis to provide insight into cause and effect are acknowledged; however, whether the large increase in PCAv is reflective of a lack of shared blood passing through the anterior posterior communicating arteries through the Circle of Willis remains to be established. Methodological considerations:   The use of CBF velocity as an index of absolute change in CBF should be used cautiously. Nevertheless the usefulness of TCD in measuring changes associated with stimulus response protocols, as well as regional differences by analyzing both absolute and relative changes from baseline makes it a powerful cerebral imaging tool with high temporal and spatial resolution (Ainslie and Duffin, 2009; Willie et al., 2012).   It should also be noted, that the use of TCD to measure the sensitivity to changes in PaCO2 has been associated with dissimilar findings compared to other more localized techniques such as arterial spin labelling MRI (Mandell et al., 2008). For example,  grey matter has a higher PaCO2 sensitivity than white matter, resulting in a divergent increased in blood flow (i.e. blood flow steal) from cortical areas high in white matter, to areas high in gray matter (Mandell et al., 2008). Both the MCAv and PCAv when measured using the TCD, are measuring arteries that feed regions of the brain with large volumes of both gray and white matter, which limits the ability to infer on regional cortical sensitivity to changes in PaCO2. At rest, Park (2002) investigated the differences in PaCO2 sensitivities between MCAv and basilar.  The findings indicated that the basilar artery and MCA had ! ! !123similar sensitivities to PaCO2 within a physiological range; however, comparison is hindered with the current study since this study did not examine the role of exercise.  Moreover, Park (2002) monitored basilar artery velocity using a handheld TCD probe on subjects in a supine position, making this technique difficult to use during upright exercise. Further research, utilizing higher resolution imaging techniques such as MRI, which can measure specific brain regions, distal to the major cerebral arteries, to identify specific regional tissue is required.  4.5. Summary Administration of hyperoxia during exercise lead to a selective increase in PCAv compared to both normoxic and hypoxic exercise. The observed difference between MCAv and PCAv during normoxic exercise compared against one and another supports previous findings that demonstrated regional differences in CBF distribution during exercise. Further study is now needed to investigate the mechanisms and teleological relevance of such regional brain blood flow changes during exercise.   ! ! !124Chapter 5. Influence of high altitude on cerebral blood flow and fuel utilization during exercise and recovery !The following section has been published: Smith KJ, MacLeod D, Willie CK, Lewis NCS, Hoiland RL, Ikeda K, Tymko MM, Donnelly J, Day TA, MacLeod N, Lucas SJE & Ainslie PN. (2014) Influence of high altitude on cerebral blood flow and fuel utilization during exercise and recovery. J Physiol 592: 5507–5527.!I was responsible for drafting the manuscript, and creating all of the figures presented throughout the chapter. All of the co-authors edited the initial version once before submission to the Journal of Physiology. I completed all revisions following the reviewers’ comments, and completed the final manuscript with the help of Prof. Ainslie for publication. Copyright approval for reproduction of figures and text was obtained from Jon Wiley and Sons.!5.1. Purpose and Background  Exposure to high altitude results in a reduced partial pressure of arterial oxygen (PaO2) that stimulates hyperventilation and reduces the partial pressure of arterial carbon dioxide (PaCO2). The blood vessels of the brain dilate in response to hypoxia and constrict during hypocapnia; thus, high altitude exposes the brain to competing vasoactive stimuli, the balance of which is a primary determinant for resting global cerebral blood flow (gCBF). Upon arrival to HA (>3500 m) there is an initial increase in gCBF of 20-60% - depending on the severity of hypoxia - that acts to offset the impact of the reductions in arterial oxygen content (CaO2) to maintain cerebral oxygen delivery (CDO2) [(Ainslie & Subudhi, 2014)]. As acclimatization proceeds, increased ventilation increases PaO2 and decreases in PaCO2 act to return gCBF towards SL values (Ainslie & Subudhi, 2014; ! ! !125Severinghaus et al., 1966; Willie et al., 2014b). Exercise too is a potent stimulus to the cerebrovasculature, producing gCBF changes that are a function of both blood gases and neuronal metabolism. However, mechanisms of CBF regulation during exercise at HA have been subject to limited study.  Imray et al. (2005) reported that after acute HA (5050m) exposure (<1-2 days), middle cerebral artery velocity (MCAv) during maximal exercise was decreased compared to at rest. In contrast, Huang et al. (1991) reported that following 18 days at 4000m, there is no change in blood flow velocity in the internal carotid artery (ICA) during incremental exercise compared to rest. Different severities of hypoxia, different acclimatisation periods, and different exercise protocols (%max work rate compared with a constant work rate at SL and HA) may contribute to these conflicting findings. In addition, the absence of concomitant robust measures of cerebral substrate delivery, metabolism and regional blood flow distribution at each exercise intensity hinders mechanistic interpretation. Only one study has assessed the roles of arterial blood gases and cerebral metabolic rates on gCBF regulation during exercise following partial acclimatization to HA.  Moller et al. (2002) used the Kety-Schmidt technique to measure gCBF, cerebral metabolic rates (CMRO2,Glucose,Lactate), and oxidation index of glucose and carbohydrates (OGI & OCI) during exercise (100 W), following 5 weeks at HA (5260m), and again following return to SL.  The authors observed no influence of altitude or exercise on any of these variables. Two major caveats of this study hinder interpretation:  1) Because gCBF returns to SL values as the acclimatization period is extended, may explain the lack of a cerebral metabolic response during exercise and to HA; 2) Most likely because of the ! ! !126need for a prolonged steady state period (~10 min; (Kety, 1945) when using the Kety-Schmidt technique, only one exercise workload (100 W) was used to assess the cerebral metabolic response to exercise at HA. A problem with this approach is that the absolute workload of 100 W at high altitudes (>5000m) would be near maximal intensity in contrast to a submaximal intensity at SL (Green et al., 1989). Maximal intensity exercise at HA is expected to elicit either a return to baseline CBF values (Imray et al., 2005)) or plateau (Siebenmann et al., 2013). In contrast, at SL a (submaximal) workload of 100 W would elicit a ~15 – 25 % increase in CBF (Imray et al., 2005; Moraine et al., 1993; Smith et al., 2012; Subudhi et al., 2011); Therefore, the differential MCAv responses during incremental exercise of differing intensities at SL and HA, highlights the need to make comparisons over a range of workloads. Therefore, we wished to examine how early acclimatisation to HA affects regional and global cerebral haemodynamics, cerebral metabolism and substrate delivery during incremental exercise. We hypothesised that 1) during incremental exercise and recovery following 4-6 days at 5050m, increases in gCBF will preserve delivery of oxygen (CDO2) in excess of that required by an increasing cerebral metabolic rate of oxygen (CMRO2) and 2) because of the expected elevations in gCBF, early acclimatization to HA results in the trans-cerebral exchange of oxygen versus carbohydrates (glucose + ½ lactate, [OCI]) would be similar during exercise and recovery at HA and sea-level (SL).. 5.2. Methods Participants A total of 11 subjects volunteered for the study providing informed written consent, two ! ! !127subjects were unable to complete the HA trial due to medical emergency evacuation prior to any of the HA testing (unrelated to any experiments). We were unable to obtain adequate blood flow measures in another subject at both SL and HA; therefore, 8 subjects were used throughout our analysis unless otherwise noted. None of the subjects were smokers, and all subjects underwent pulmonary function screening, maximal exercise stress testing and a polysomnography examination to ensure that they were free from any cardiovascular, cerebrovascular and respiratory disorders.   Subjects avoided exercise, caffeine and alcoholic beverages for 12 hours and fasted for 4 hours prior to each session. This study was part of a research expedition conducted in April-June in 2012. As such, participants took part in a number of studies conducted during the three weeks at the Ev-K2-CNR Pyramid Laboratory. The experimental question addressed in this paper was a priori driven and the data included herein will not be duplicated in future reports. Ethical approval by the Clinical Research Ethical Review Board of the University of British Columbia  (H11-03287) and the Nepal Health Medical Research Council was received prior to testing.   Study Design All variables and measurements were obtained at SL (SL: 350m, Barometric pressure [Pb] 715 ± 15mmHg) and following 4-6 days at the Ev-K2-CNR Pyramid Laboratory, Khumbu Valley, Nepal (HA: 5050m, Pb =413 ± 4 mmHg). Subjects spent 7 days in Kathmandu (1338"m) acclimatizing before flying to Lukla (2,840"m) and trekking over 9-days (rest days: Namche Bazaar, 3,440"m; Pengbouche, 3,995"m; Pheriche, 4,240"m). During ascent participants were given low-dose acetazolamide (125 mg, oral) twice a day ! ! !128to help prevent acute mountain sickness (Basnyat et al., 2006; Richalet et al., 2005). Acetazolamide was discontinued on day 8 of the trek at Pheriche; Approximately 24 hours prior to subjects HA maximal exercise test to account for acetazolamide washout (Richalet et al., 2005). Subjects were familiarized with all measurements prior to beginning the study.  Each subject performed an incremental maximal exercise test while pedaling on a light-weight portable supine cycle ergometer prior to both the SL and HA sessions.  The maximum achieved workload (Wmax) was recorded in order to calculate the relative workloads for each altitude.  Data collection was performed within a minimum of 24 hours following each maximal exercise test.    Protocol Following instrumentation of cardio-respiratory devices, internal jugular and radial artery catheterization, and trans-cranial Doppler subjects rested for 30 min. Baseline data (BL) were recorded and sampled during the last 5 min of this resting period prior to beginning the incremental exercise test with relative workloads of 20, 40, 60, 80, 100% Wmax. The duration of each workload was 3 min.  Steady-state blood samples were drawn during exercise at each workload (at the 2.8 min mark for each workload).  Upon completion of the maximal exercise test, subjects remained supine for a 30-minute recovery period.  Recovery measurements and blood samples were taken at 1, 2, 4, 6, 8, 10, 15, 25, 30 min following exercise.  Instrumentation and measurement technique Detailed discussion for cardiorespiratory, and blood flow measures are found in chapter 3.0. ! ! !129 Arterial and Jugular Venous Catheterization Local anesthetic (1% lidocaine) was injected to the surrounding tissue of the radial artery and internal jugular vein under the guidance of a portable 8-MHz ultrasound unit (Nanomaxx, Sonosite, Washington, USA). A 20-gauge catheter (Arrow, Markham, Ontario, Canada) was placed into the radial artery and attached to a pressure transducer that was positioned at the level of the right atrium in the midaxillary line for the measurement of beat-to-beat arterial blood pressure and gas sampling.  A jugular bulb catheter (Edwards PediaSat Oximetry Catheter, Edwards, Irvine, CA, USA) was placed in the right internal jugular vein and directed cephalad under sterile conditions while guided via ultrasound.   Arterial and jugular venous blood gas analysis Blood gas samples were drawn into a preheparinized syringe, and analyzed immediately (within 2 min).  Following standardized calibration, all blood samples were analyzed using an arterial blood-gas analysis system (ABL-90 CO-Ox, Radiometer, Copenhagen, Denmark) for arterial (a) and internal jugular venous (v) pH, PO2, PCO2, SaO2, Hb, glucose, and lactate.  Calculations The average values for mean arterial pressure (MAP), MCAv, PCAv, heart rate (HR), PETO2, PETCO2, FB, VE were calculated offline using LabChart v7.0 (ADInstruments) during the entire 5 min of BL, 30 seconds prior to the blood gas samples at each workload (i.e., at steady state) and during the recovery time points. ! ! !130!Global Cerebral Blood Flow (gCBF):  !"#$(!".!"#!!) = !"#$ ∙ 2 + (!"# ∙ 2)  Where QICA is the blood flow from the left ICA, and QVA is the blood flow in the right VA. The total of QICA and QVA therefore is the estimated gCBF assuming a symmetrical blood flow between contralateral ICA and VA arteries. The QICA and QVA were calculated offline:  ! = !!!!!  Where Q is the flow, r is the radius, and v is the velocity of the blood moving through the respective vessels.  Global cerebral blood flow per unit of tissue: !"#$(!". 100!.!"!!!) =!"#$14  Assuming an average brain mass of 1.4 kg.  Global cerebral blood flow during exercise at each workload was also calculated using the % change in MCAv and PCAv and baseline QICA and QVA:  ! ! !131!"#$!" = !"#$!" ∙ 2 + !"#$!" ∙%∆!"#$ + !"#!" ∙ 2 + !"#!" ∙%∆!"#$   Where gCBFEx equals the gCBF for the given workload (20, 40, 60, 80, 100% Wmax), QICA and QVA are the resting baseline values, and the %∆MCAv and %∆PCAv are the changes at the given Wmax from resting baseline MCAv and PCAv values (Fisher et al., 2013; Gonzalez-Alonso, 2004). In addition, gCBF was also estimated via the Fick principle assuming a maintained cerebral metabolic rate of oxygen (see below).   Arterial (CaO2) and venous (CvO2) content of oxygen: !"#! !". !"!!= ([!"] ∙ 1.36 ∙!"#! %100+ 0.003 ∙ !"#! !"#! !". !"!!= ([!"] ∙ 1.36 ∙!"#! %100+ 0.003 ∙ !"#!  Where [Hb] is the concentration of haemoglobin in venous blood, 1.36 is the affinity for O2 to hemoglobin independent of saturation, and 0.003 is the percent of O2 dissolved in the blood.  Cerebral delivery of oxygen (CDO2): !"#! !". 100!.!"#!!= !"#$ ∙ !"#! Where gCBF is the blood flow per unit of brain tissue.  Cerebral metabolic rate for oxygen (CMRO2): !"#$! !!"#. 100!.!"#!!= [ !"#$ ∙ !"#! − !"#! ] ∙ 0.446 ! ! !132Where CMRO2 is the gCBF multiplied by the arterial jugular venous O2 content differences, and 0.446 equals the ratio of 1 mmol of O2 in a volume equal to 1ml (ie;1/22.4 mmol). CMRO2 indicates the uptake rate of oxygen by the brain.  Direct Fick measurement of Cerebral Blood Flow (CBF): Assuming a maintained cerebral metabolic rate of oxygen from rest during exercise: !"#!(!". 100!!!.!"#!!) =!"#$2!"!!!! − !!!! Where CMRO2BL is the CMRO2 at rest for SL and HA, and CaO2 – CvO2 is the absolute arterial venous oxygen extraction at each exercise intensity and minute of recovery.  Cerebrovascular conductance  (CVC): !"! !!"#.!". 100!.!"#!! = !"# ∙ !"#$  Oxygen extraction fraction (O2EF): !!!" % =!"!! − !!"!!!"!!∙ 100% Where the CaO2 and CvO2 represent the arterial and jugular venous O2 content, respectively.  The O2EF is interpreted as being the percent O2 extraction across the brain.  Cerebral delivery of Glucose: !"!"# !!"#. 100!.!"#!!= !"#$ ∙ !"#!  Cerebral delivery of Lactate: ! ! !133!"!"# !!"#. 100!.!"#!!= !"#$ ∙ !"#! Where gCBF is the blood flow per unit of tissue, and Glua and Laca are the arterial concentrations of glucose and lactate, respectively.  Cerebral metabolic rate for glucose (CMRglu): !"#!"# !!"#. 100!.!"#!!= !"#$ ∙ (!"#! − !"#!)  Cerebral metabolic rate for lactate (CMRlac): !"#!"# !!"#. 100!.!"#!!= !"#$ ∙ (!"#! − !"#!) Where the gCBF is the blood flow per unit of brain tissue, and the Glua, Laca and Gluv, Lacv are the arterial and venous differences of glucose and lactate in the arterial and jugular venous blood, respectively.  Oxygen Glucose Index (OGI): !"# = (!"!! − !!"!!)/!(!"#! − !"#!) The OGI indicates the ratio of oxygen to glucose taken up by the brain.  OGI values at a 1:1 ratio would equal 6, as the stoichiometry for the oxidization of glucose by oxygen requires 1 oxygen molecule per each of the 6 carbon atoms found in glucose. A reduction from this value would indicate that some of the glucose was not fully oxidized, and could indicate a non-oxidative energy production.  Oxygen Carbohydrate Index (OCI) was calculated by: !"# = (!"!! − !!"!!)/!(!"#! − !"#!)+12(Lac! − Lac!) ! ! !134The OCI indicates the ratio of oxygen to carbohydrate (Glu and Lac) taken up by the brain.  The carboxylation of lactate to pyruvate into the citric acid cycle results in only one molecule of pyruvate, compared to the two derived from the breakdown of glucose to pyruvate during glycolysis.  Cumulative Molar Ratio of Carbohydrate Uptake to Oxygen Uptake was calculated by: !"#$!(!!"#. !!!) = (!"#!!!)+12(Lac!!!)− !16(!"!! − !!"!!)  Where CMRU is reported in glucose equivalent units such that a score of zero indicates complete oxidation of extracted glucose and lactate.  Any deviation from a score of 0 indicates either an extraction of carbohydrates in excess of oxygen (increase) or a surplus extraction of oxygen versus carbohydrate (decrease).  Furthermore, CMRU is cumulatively added for each subsequent measure from rest in order to demonstrate the cumulative mismatch between carbohydrate and oxygen metabolism during and following exercise.   Cumulative metabolic ratio of carbohydrate uptake to oxygen uptake was calculated by: !"#!!"#$ !(!!"#. 100!!!.!"!!!) = (!"#!!!)+12(Lac!!!)− !16(!"!! − !!"!!)  Where CMRU, as calculated above, and gCBF are considered in parallel (CMRUgCBF).  This calculation is used to identify how changes in gCBF may impact HA and SL CMRU.   ! ! !135Statistical analysis Normal distribution of variables was confirmed with the Shapiro-Wilk normality test. A two way (time x condition) repeated measures analysis of variance (ANOVA) was employed to compare all the variables measured and calculated at SL and HA during BL, exercise and recovery.  A P value of <0.05 was considered statistically significant. The false discovery rate was used post hoc to adjust for multiple comparisons (P<0.003).  Values are presented as mean ±SD.  5.3. Results Subjects Eight males completed the entire protocol (Age: 30 ± 6 years; Height: 167 ± 40 cm, body mass: 55-102 kg; SL VO2peaksupine: 43.1 ± 5.0 ml.kg-1.min-1). The Wmax was reduced by 50% at HA compared with SL (150 ± 25 vs. 300 ± 50 W, respectively). As such, the average relative workloads equated to: 30, 60, 90, 120, 150 W at HA, and 60, 120, 180, 240, 300 W at SL for 20, 40, 60, 80 and 100% Wmax, respectively.  Rest (Tables 5.1 and 5.3; Fig 5.1-5.5) Following partial acclimatization at 5050m, PETO2, PETCO2, PaO2, PaCO2, SaO2, CaO2, PvO2, PvCO2, SvO2, CvO2, OGI and OCI were reduced compared to SL values (p < 0.05, Table 1). Resting arterial pH, arterial lactate, venous pH, and O2Ext were all elevated at HA compared with SL (p < 0.05). No significant differences were observed for MAP, CVRi or CVCi at either altitude. Figure 5.1 highlights the contribution of ICA and VA to the resting gCBF at SL and HA. At rest at HA, QICA was elevated (~ +22 %) from SL (p ! ! !136<0.05), however, gCBF (p = 0.056) and QVA (P = 0.898) were not raised at HA compared with SL. No differences were observed in the diameter of the ICA and VA at SL and HA, nor were there differences observed for MCAv and PCAv between SL and HA at rest (Table 3; P = 0.335 & 0.237 respectively). Although cerebral oxygen and glucose delivery were not different at SL and HA, the cerebral lactate delivery was elevated at HA compared with SL (Fig. 5.5C; p<0.05). The CMRO2 and CMRglu were also elevated (~ +23 % vs SL; p < 0.05) at HA whereas CMRlac was unaltered (Fig. 5.5B; p = 0.515). Finally, in Figure 5.1 the red lines indicate the one subject who was deemed a statistical univariate outlier (CMRO2 z score > 3.29 and > 2 SD from the mean). Consequently, this subject was removed from the CMRO2 calculations. In addition, when this subject was removed from the gCBF data set, the increase in gCBF at HA was significant (up 25 %; p = 0.02 vs. SL).     ! ! !137  Figure 5.1:  Absolute (A) and relative (B) contributions of internal carotid (ICA) and vertebral  (VA) artery blood flow to resting global cerebral blood flow (gCBF; C) as well as the resting cerebral metabolic rate of oxygen (CMRO2) at sea-level (SL) and high altitude (HA). The red line indicates subject #5’s CMRO2 response to HA and illustrates the outlier response (see results for statistical details).  † Signifies difference between SL and HA (p<0.05).    gCBF (ml.min)SLHA02004006008001000CMRO2 (µmol.100g- .min- )SLHA0.00.51.01.52.0†SL HA0100200300400500600700800Q gCBF (ml.min-1)SL HA0.000.250.500.751.00VAICA% of Q gCBFA BC D! ! !138Table 5.1. Cardiorespiratory and arterial-venous variables during exercise at sea-level and high-altitude (5050m)    Rest Exercise (%Wmax) Var Cond BL 20 40 60 80 100  Cardio-respiratory variables  HR (BPM) SL 68 ±10 101 ±12* 125 ±12* 143 ± 10* 164   ±8* 176   ±6* HA 68 ±12 95  ±9* 111 ±10* 121 ±9*† 135 ±9*† 142 ±11*† MAP (mmHg) SL 116 ±7 124 ±9 137 ±9 147 ±9* 149 ±11* 154 ±11* HA 124 ±9 132 ±8 137 ±5 142 ±7 147 ±8 151 ±9* PETO2 (mmHg) SL 92 ±5 92 ±6 97 ±7 103 ±5* 106 ±3* 110 ±4* HA 46 ±2† 48 ±3† 51 ±2*† 54 ±2*† 57 ±3*† 58 ±3*† PETCO2 (mmHg) SL 40 ±1 40 ±1 40 ±2 40 ±3 38 ±3 36 ±3 HA 28 ±2† 27 ±2† 26 ±2† 25 ±2† 24 ±2*† 23 ±2*† Fb (bpm) SL 16 ± 3 21 ± 3* 24 ± 3* 29 ± 5* 39 ± 4* 47 ± 6* HA 18 ± 3 24 ± 5* 29 ± 5*† 37 ± 7*† 43 ± 8 * 51 ± 9* VE (l.min-1) SL 15 ± 5 29 ± 8* 46 ± 9* 67 ± 14* 102 ± 15* 127 ± 25* HA 18 ± 3 38 ± 10* 52 ± 14* 73 ± 19* 95 ± 23* 114 ± 19* Arterial  PO2 (mmHg) SL 92 ±8 75 ±8* 75 ±12* 81 ±13 85 ±12 82 ±12 HA 42 ±3† 38 ±2*† 38 ±3*† 37 ±3*† 37 ±3*† 38 ±3† PCO2 (mmHg) SL 38 ±3 39 ±2 38 ±2 37 ±2 34 ±2* 34 ±3* HA 23 ±4† 23 ±3† 23 ±2† 22 ±3† 22 ±2† 20 ±2*† SO2 (%) SL 98±1 96 ±1 95 ±4 96 ±2 96 ±2 95 ±3* HA 81 ±4† 77 ±3† 75 ±4†* 75 ±4†* 73 ±5†* 71 ±5†* pH SL 7.41 ±0.01 7.40 ±0.01* 7.40 ±0.01* 7.37 ±0.02* 7.33 ±0.03* 7.27 ±0.05* HA 7.48±0.05† 7.48±0.03† 7.47±0.02† 7.45±0.03*† 7.42±0.04*† 7.38±0.05*† ! ! !139Table 5.1. Cardiorespiratory and arterial-venous variables during exercise at sea-level and high-altitude (5050m)  CaO2 (ml.dl-1) SL 21±1 21±1 21±1 21±1 22±1* 22±1* HA 18±2† 17±1† 17±1† 17±2† 17±1† 17±1† Glucose (mmol.l-1) SL 5.4±0.3 5.4±0.3 5.4±0.2 5.5±0.3 5.5±0.3 5.4±0.2 HA 5.2±0.2 5.3±0.2 5.3±0.2 5.3±0.3 5.4±0.2 5.4±0.4 Lactate (mmol.1-1) SL 0.7±0.1 0.9±0.3* 2.0±0.5* 4.5±1.2* 8.8±1.7* 13.5±2.3* HA 0.9±0.2† 1.2±0.2*† 2.0±0.5* 3.6±1.3* 5.7±2.0*† 8.3±2.1*† Venous PO2 (mmHg) SL 33 ± 3 32 ± 4 33 ±3 34 ± 2 34 ± 3 35 ± 3 HA 27 ±2† 25 ± 1† 25 ± 1† 30 ± 5† 26 ± 2† 26 ± 2† PCO2 (mmHg) SL 48 ± 4 49 ± 2 49 ± 2 48 ± 2 45 ± 5 46 ± 1 HA 30 ± 3† 29 ± 2† 28 ± 2† 28 ± 2† 28 ± 2† 27 ± 2† SO2 (%) SL 64 ± 2 64 ± 3 65 ± 3 65 ± 3 63 ± 5 61 ± 5 HA 52 ± 4† 49 ± 2*† 49 ± 3*† 49 ± 3*† 47 ± 3*† 46 ± 2*† pH SL 7.37±0.01 7.36±0.01 7.35±0.01 7.32±0.02 7.28±0.03 7.23±0.04 HA 7.43±0.04† 7.44±0.04† 7.42±0.03*† 7.42±0.03*† 7.39±0.04*† 7.35±0.05*† CvO2 (ml.dl-1) SL 14 ± 1 14 ± 1 14 ± 1 14 ± 1 14 ± 1 14 ± 1 HA 12 ± 1† 10 ± 1*† 11 ± 1† 11 ± 1† 11 ± 1† 11 ± 1† Glucose (mmol.l-1) SL 5.0 ± 0.2 5.0 ± 0.4 5 .0 ± 0.3 5.0 ± 0.3 4.8 ± 0.5 5.0 ± 0.4 HA 4.6 ± 0.5 4.7 ± 0.4 4.7 ± 0.4 4.8 ±  4.8 ± 0.5 4.8 ± 0.5 Lactate (mmol.1-1) SL 0.6 ± 0.1 0.9 ± 0.2 1.7 ± 0.5* 4.0 ± 1.0* 6.7 ± 1.6* 10.1 ± 1.3*  HA 0.9 ± 0.2 1.2 ± 0.2 1.9 ± 0.3* 3.1 ± 0.7 4.8 ± 1.4*† 7.0 ± 1.7*† ! ! !140   Table 5.1. Cardiorespiratory and arterial-venous variables during exercise at sea-level and high-altitude (5050m)  Arterial-venous differences and metabolism Ca-vO2   (ml.dl-1) SL 7.1 ± 0.7 6.8 ± 0.6 6.8 ± 0.7 6.9 ± 1.1 7.6 ± 1.3 7.9 ± 1.6 HA 6.6 ± 1.8 6.8 ± 1.2 6.2 ± 1.2 6.2 ± 1.7 6.1 ± 1.2† 6.1 ± 1.0† O2Ext (%) SL 34 ± 2 33 ± 3 33 ± 3 32 ± 4 34 ± 5 36 ± 6 HA 38 ± 5† 38 ± 3† 36 ± 3† 35 ± 6 36 ± 5 36 ± 4 Glua-v (mmol.l-1) SL 0.4 ± 0.1 0.6 ± 0.3 0.4 ± 0.2 0.5 ± 0.3 0.7 ± 0.5 0.4 ± 0.3 HA 0.7 ± 0.4 0.4 ± 0.2† 0.6 ± 0.3 0.8 ± 0.2 0.6 ± 0.3 0.6 ± 0.2  Laca-v (mmol.l-1) SL 0.04 ± 0.1 0.06 ± 0.05 0.3 ± 0.2* 0.6 ± 0.3* 2.1 ± 0.9* 3.5 ± 1.3* HA -0.02 ± 0.2 0.2 ± 0.3* 0.4 ± 0.6* 0.9 ± 0.9* 1.3 ± 1.1* 1.4 ± 0.9* Ratios OGI SL 7.1 ± 1.2 7.7 ± 4.1 7.5 ± 2.7 7.5 ± 2.7 5.2 ± 2.2 8.3 ± 4.1 HA 4.0 ± 0.5† 4.3 ± 0.8 4.3 ± 1.2† 3.9 ± 1.4† 4.6 ± 1.6 5.3 ± 2.3 OCI SL 6.7 ± 1.0 7.4 ± 4.3 6.1 ± 2.4 4.4 ± 2.5* 1.9 ± 0.6* 1.6 ± 0.7* HA 4.0 ± 0.5† 3.8 ± 0.9† 3.3 ± 0.8*† 2.4 ± 1.0*† 2.1 ± 0.5* 2.1 ±0.4* Cond: Condition; HR: heart rate (beats per minute); MAP: mean arterial pressure; PETO2 partial pressure of end-tidal oxygen; PETCO2: partial pressure of end-tidal carbon dioxide: Fb: breathing frequency (breaths per minute); VE: minute ventilation; PO2: partial pressure of oxygen; PCO2: partial pressure of carbon dioxide; SO2: oxygen saturation; CaO2: arterial oxygen content; CvO2: venous oxygen content; Ca-vO2: arterial venous oxygen content differences; O2Ext: relative fraction of oxygen content; Glua-v: cerebral arterial venous glucose differences; Laca-v: arterial venous lactate differences; OGI: oxygen glucose index; OCI: oxygen carbohydrate differences. * Signifies differences from baseline (p <0.003), † signifies differences between SL and HA (p <0.05). ! ! !141 Table 5.2. Cerebral blood flow and metabolism during exercise at sea-level and high-altitude    Variable Cond BL 20 40 60 80 100 MCAv (cm.s-1) SL 71 ±9 75 ±9 80 ±10* 83 ±12* 77 ±12* 76 ±14 HA 75 ±9 82 ±11* 87 ±11* 90 ±12* 90 ± 10*† 92 ±11*† PCAv (cm.s-1) SL 49 ±8 52 ±9* 56 ±9* 56 ±9* 52 ±9 52 ±10 HA 54 ±10 57 ±8* 61 ±8* 65 ±9* 64 ±9*† 64 ±11*† QICA (l.min-1) SL 245 ±34 259 ±44 261 ±49 254 ±60 - - HA 301 ±58† 313 ±59† 336 ±49† 355 ±72† - - ICAdiam (cm) SL 0.53 ±0.03 0.53 ±0.04 0.52 ±0.04 0.51 ±0.03* - - HA 0.53 ±0.06 0.52 ±0.06 0.52 ±0.05 0.52 ±0.05 - - ICAvel (cm.s-1)  SL 37 ±4 40 ±2 40 ±5 41 ±5* - - HA 44 ±3† 49 ±6 *† 53 ±5*† 56 ±9*† - - QVA (l.min-1) SL 78 ±31 79±32 86 ± 35 - - - HA 76 ±26 74 ±12 - - - - VAdiam (cm) SL 0.37 ±0.07 0.37 ±0.08 0.38 ± 0.08 - - - HA 0.38 ±0.03 0.38 ±0.04 - - - - VAvel (cm.s-1) SL 23 ±6 24 ±6 23 ± 8 - - - HA 20 ±2 22 ±2 - - - - gCBF (ml.100g.min-1) SL 46 ±9 48 ±9* 52 ±9* 53 ±12* 50 ±11* 47 ±12 HA 53 ±6 58 ±6† 62 ±8*† 64 ±7*† 64 ±10*† 62 ±8*† CVRigCBF SL 2.2 ±0.6 2.2±0.6 2.3 ±0.7 2.5 ±0.7 2.7 ±0.8 2.7 ±0.9 HA 1.9 ±0.2 1.9 ±0.2 1.8 ±0.3† 1.9 ±0.3† 2.2 ±0.4† 2.0 ±0.3† CVCigCBF SL 0.47 ± 0.09 0.46 ± 0.09 0.45 ± 0.09 0.43 ± 0.10 0.40 ± 0.10 0.39 ± 0.10 HA 0.52 ± 0.04 0.52 ± 0.06 0.54 ± 0.06† 0.53 ± 0.06 † 0.52 ± 0.09† 0.51 ± 0.09† CDO2 (ml.dl-1.min-1) SL 134 ± 23 139 ± 22 150 ± 22* 159 ± 29* 153 ± 29* 156 ± 29* HA 137 ± 20 141 ± 20 149 ± 18 155 ± 21* 151 ± 24* 156 ± 28* CDglu  (µmol.100g. min-1) SL 248 ± 40 258 ± 39 276 ± 39* 289 ± 55* 274 ± 56 272 ± 55 HA 283 ± 37 307 ± 33*† 324 ± 39*† 345 ± 49*† 346 ± 69*† 351 ± 84*† ! ! !142Table 5.2. Cerebral blood flow and metabolism during exercise at sea-level and high-altitude CDlac (µmol.100g.min-1) SL 30 ± 5 45 ± 11* 104 ± 18* 236 ± 43* 430 ± 84* 682 ± 188* HA 48 ± 7† 78 ± 23*† 141 ± 51* 259 ± 106* 393 ± 157* 551 ± 154* CMRO2 (µmol.g-1.min-1) SL 1.3 ± 0.2 1.4 ± 0.3 1.5 ± 0.3 1.6 ± 0.2* 1.6 ± 0.2* 1.7 ± 0.3* HA 1.7 ± 0.2† 1.8 ± 0.2† 1.9 ± 0.2*† 1.9 ± 0.4* 1.9 ± 0.3*  2.0 ± 0.2* CMRglu (mmol.100g-1.min-1) SL 20 ± 3.0 21 ± 7† 23 ± 9 25 ± 9 28 ± 8 23 ± 7 HA 44 ± 7† 42 ± 9† 44 ± 10† 52 ± 16† 45 ± 15† 39 ± 15† CMRlac (mmol.100g-1.min-1) SL 1.7 ± 4 3.0 ± 2.0 10 ± 3* 32 ± 10* 110 ± 36* 188 ± 85* HA -0.9 ± 10 14 ± 20* 30 ± 40* 67 ± 62* 81 ± 77* 103 ± 61*  Cond: condition; MCAv; middle cerebral artery velocity; PCAv: posterior cerebral artery velocity; QICA: internal carotid blood flow; ICAdiam: internal carotid artery diameter; ICAvel: internal carotid artery velocity; QVA: Vertebral blood flow; VAdiam: Vertebral artery diameter; VAvel: Vertebral artery velocity; gCFB: global cerebral blood flow; CVRigCBF: cerebrovascular resistance; CVCigCBF: cerebrovascular conductance; CDO2: cerebral oxygen delivery; CDglu: cerebral glucose delivery; CDLac: cerebral lactate delivery; CMRO2: cerebral metabolic rate of oxygen; CMRglu: cerebral metabolic rate of glucose; CMRlac: cerebral metabolic rate of lactate. * Signifies differences from baseline (p <0.003), † signifies differences between SL and HA (p <0.05).   ! ! !143Exercise (Tables 5.1 and 5.3; Fig. 5.2 – 5.6) Supine submaximal exercise at SL (i.e., 20 and 40 % Wmax) resulted in a reduced PaO2 followed by a return to resting values at higher intensities (Fig. 5.2A).  At HA PaO2 was reduced from rest and SL at all intensities (p < 0.003 vs. rest; p < 0.05 vs. SL). Figure 5.2B illustrates a lack of any marked changes in PaCO2 during sub-maximal exercise at both altitudes, while similar reductions in PaCO2 from rest were observed during the highest exercise intensities (80 and 100% Wmax) at SL and HA (down 3-4 mmHg). Moreover, the change in pH at 100% Wmax at HA (∆0.10; 7.38) was less than that at SL (∆0.13; 7.27; Table 5.1; Fig 5.2D). Arterial venous differences of oxygen content (Ca-vO2) across the brain at SL and HA did not change during low-to-moderate intensity exercise (20-60% Wmax); however, Ca-vO2 at HA during 80 and 100% Wmax was lower (~20 %; p<0.05) than at SL. During the lowest exercise intensities (20 and 40 % Wmax), O2Ext was elevated at HA (~8 - 12 %) compared with SL, whereas at moderate and high intensities (60, 80, 100 % Wmax) O2Ext was comparable (Table 5.1). Absolute a-v lactate differences across the brain increased progressively from rest during exercise at both SL and HA (p < 0.003, Table 5.1), and more so at SL (p < 0.05). Specifically, the maximal achieved arterial lactate concentration and extraction during 100 % Wmax at HA was ~half of that achieved at SL (8.2 and 1.4 vs. 13.5 and 3.5 mmol·l-1, respectively). The OGI did not change during exercise at HA or SL, but there were differences between SL and HA at 20 and 40 % Wmax (Fig. 5.6A). In contrast, the OCI was generally reduced from rest during exercise (Table 5.1, Fig. 5.6B). Similar to the OGI, OCI was lower at HA during 20 and 40 % Wmax compared with SL, but there were no differences observed at higher intensities.   ! ! !144   Figure 5.2: Arterial partial pressure of oxygen (PaO2; A) and carbon dioxide (PaCO2; B) as well as arterial oxygen content (CaO2; C) and pH (D) during baseline (BL) incremental exercise (20 -100 % of the maximum achieved workload [%Wmax]) and 30 min of recovery at sea level (SL; ) and high altitude (HA; ). * Signifies differences from BL, † Signifies difference between SL and HA (p<0.05).   BL 20 40 60 80 100 1 2 4 6 8 10 15 20 25 300151617181920212223242526*†* * *** * *CaO2 (ml.dl O2)Exercise (%Wmax) Recovery (Min)BL 20 40 60 80 100 1 2 4 6 8 10 15 20 25 300102030405060708090100110120* ** * * * ** * * * *†PaO2 (mmhg)Exercise (%Wmax) Recovery (Min)BL 20 40 60 80 100 1 2 4 6 8 10 15 20 25 300203040**†**** * * * ** * ** * * * * * * *PaCO2 (mmhg)Exercise (%Wmax) Recovery (Min)A BC DBL 20 40 60 80 100 1 2 4 6 8 10 15 20 25 30067.07.58.0Exercise (%Wmax) Recovery (Min)†* ***pH! SL " HA! ! !145Incremental exercise up to 60 % Wmax at both SL and HA raised gCBF, MCAv, and PCAv from resting baseline values (Fig. 5.3A,B,C; p < 0.003).  At 100 % Wmax gCBF, MCAv and PCAv returned to baseline levels at SL, whereas at HA they remained elevated (p < 0.003, Table 5.3; Fig. 5.3). Similar temporal changes in gCBF were also apparent when estimated via the Fick equation at HA and SL (Fig 5.3D).  The CDO2 progressively increased (p < 0.003 vs. rest, Table 5.3; Fig. 5.4A) during exercise at SL (~ +16 %) and HA (~ +14 %). Although the magnitude of the MAP response was similar at both altitudes during exercise, MAP was elevated above rest at 60-100% Wmax at SL and only at 100%Wmax at HA.  Because the exercise response in MAP was similar at SL and HA, and CBF was elevated during maximal exercise intensities (> 60% Wmax) at    ! ! !146  Figure 5.3: Cerebral blood flow velocity in the middle (MCAv; A) and posterior (PCAv; B) cerebral arteries, and global cerebral blood flow as measured by ultrasound (gCBF; C) and the Fick principle (gCBFFick; D) during baseline (BL) incremental exercise (20 -100 % of the maximum achieved workload [%Wmax]) and 30 min of recovery at sea level (SL; ) and high altitude (HA; ). * Signifies differences from BL, † Signifies difference between SL and HA (p<0.05).   BL 20 40 60 80 100 1 2 4 6 8 10 15 20 25 30-15-10-505101520253035*** **********†∆MCAv (%)Exercise (%Wmax) Recovery (Min)BL 20 40 60 80 100 1 2 4 6 8 10 15 20 25 30-15-10-505101520253035** ****** *†**** ∆PCAv (%)Exercise (%Wmax) Recovery (Min)BL 20 40 60 80 100 1 2 4 6 8 10 15 20 25 30020406080* * * ** * ***†gCBF (µmol.100g- .min- )Exercise (%Wmax) Recovery (Min)BL 20 40 60 80 100 1 2 4 6 8 10 15 20 25 3030354045505560657075Exercise (%Wmax) Recovery (Min)† †† † †*gCBFFIck (µmol.100g- .min- )A BC D! SL " HA! ! !147HA, CVCi was higher at HA. However the temporal change from rest at SL and HA was comparable.  An elevated CDgluc was observed at HA during all exercise intensities compared with SL (~16 - 30 %; p < 0.05, Fig. 5.5A). Despite the greater increase in arterial lactate production during higher exercise intensities (80 and 100 % Wmax) at SL compared with HA (p < 0.05, Fig. 5.5C), the elevated gCBF resulted in similar increases in CDLac from rest at both altitudes. During exercise, although absolute CMRO2 was higher at HA than SL at 20 and 40% Wmax (+28 % and 26 %, respectively; p < 0.05), at the higher exercise intensities (i.e., 60 -100 % Wmax) there no statistical difference was evident (Fig. 5.4). Conversely, relative changes in CMRO2 at HA and SL were similar from 20-80% Wmax; however, during 100 % Wmax at HA the relative increase in    ! ! !148  Figure 5.4: Cerebral oxygen delivery (CDO2; A), cerebral metabolic rate of oxygen (CMRO2;B), cumulative metabolic ratio uptake (CMRU [mmol.l-1]; C) and cumulative metabolic rate factored for cerebral blood flow differences (CMRUgCBF [mmol.100g-1.min-1], D) during baseline (BL) incremental exercise (20 -100 % of the maximum achieved workload [%Wmax]) and 30 min of recovery at sea level (SL; ) and high altitude (HA; ). * Signifies differences from BL, † Signifies difference between SL and HA (p<0.05).    BL 20 40 60 80 100 1 2 4 6 8 10 15 20 25 300100110120130140150160170180190CDO2 (ml.min- )***Exercise (%Wmax) Recovery (Min)BL 20 40 60 80 100 1 2 4 6 8 10 15 20 25 30-50510152025††CMRU (mmol.l-1)Exercise (%Wmax) Recovery (Min)*BL 20 40 60 80 100 1 2 4 6 8 10 15 20 25 300.00.51.01.52.0 †*††* * * * * * * ******* * * * * * * **CMRO2 (µmol.100g- .min- )Exercise (%Wmax) Recovery (Min)BL 20 40 60 80 100 1 2 4 6 8 10 15 20 25 30-50050100150200250300350400450†CMRUgCBF (µmol.100g-1.min-1)Exercise (%Wmax) Recovery (Min)A BC D! SL " HA! ! !149CMRO2 from rest was almost halved (i.e., 17 vs. 27 %; p < 0.05 vs. SL; Table 5.1). Incremental exercise did not elevate CMRglu from resting values at either altitude (p > 0.003); however, CMRglu at HA was greater (~50%) than SL across all workloads (Table 5.3; Fig 5.5B). Similar progressive increases in CMRlac were observed throughout exercise at HA and SL (Fig 5.5D).   Recovery (Tables 5.2 & 5.4; Figs 5.2-5.6) During recovery at SL, PaO2 was elevated from rest and returned to baseline after the 10th minute of recovery (Table 2; Fig 2A). At HA, compared with rest, PaO2 was elevated from minute 2 of recovery (+ ~10 mmHg) until the 15th minute (+ ~6 mmHg). Arterial pH was higher at HA compared with SL throughout recovery (Table 2; Fig 2D). At SL, O2EF was elevated from rest (34 ± 2 %, Table 1) throughout the 2nd to 25th minute of recovery (39 – 43 %; p < 0.05), however it was unchanged from rest (38 ± 5 %) at HA (Table 5.2). Glucose extraction and OGI (Fig. 5.6A) were not reliably different at HA and SL during recovery (p > 0.003). Lactate extraction remained elevated from rest until the 15th minute at HA (increase ~0.7 mmol.l-1 vs. rest) and the 25th minute at SL (increased ~0.6 mmol.l-1 vs. rest). At HA, the OCI remained reduced compared with rest at the 1st minute of recovery, and was elevated compared with SL OCI at 1st, 2nd, 4th and 6th min of recovery (P<0.003, Table 2: Fig 5.6B).    ! ! !150 Figure 5.5: Cerebral delivery of glucose (CDGlu; A) and lactate (CDLac:C), cerebral metabolic rate of glucose (CMRGlu; B)  and lactate (CMRLac; D) during baseline (BL) incremental exercise (20 -100 % of the maximum achieved workload [%Wmax]) and 30 min of recovery at sea level (SL; ) and high altitude (HA; ). * Signifies differences from BL, † Signifies difference between SL and HA (p<0.05).   BL 20 40 60 80 100 1 2 4 6 8 10 15 20 25 300100200300400500600700800900 *† ††† † † †† †CDLac (µmol.100g- .min- )Exercise (%Wmax) Recovery (Min)BL 20 40 60 80 100 1 2 4 6 8 10 15 20 25 3005101520253035404550556065Exercise (%Wmax) Recovery (Min)†††CMRGlu (µmol.100g- .min- )BL 20 40 60 80 100 1 2 4 6 8 10 15 20 25 30-50050100150200250Exercise (%Wmax) Recovery (Min)**† † †CMRLac (µmol.100g- .min- )BL 20 40 60 80 100 1 2 4 6 8 10 15 20 25 300100200300400†† †* *** **CDGlu (µmol.100g- .min- )Exercise (%Wmax) Recovery (Min)A BC D! SL " HA! ! !151At HA, gCBF was greater throughout all of recovery compared to SL, but was only elevated from rest at 1st minute of recovery (p<0.05; Table 4; Fig 3C). At HA, MAP was greater than SL throughout recovery; however CVRi and CVCi were not generally different between SL and HA. At SL and HA CDO2 were not different throughout recovery (Table 4; Fig 4). The CDGlu was only different between SL and HA during the last 5 min of recovery (p<0.05, Table 4), while being similar to resting values throughout recovery at both altitudes (p>0.003; Fig 5A). Both arterial lactate concentration and CDLac remained elevated during recovery for the entire 30 min at both SL and HA (p < 0.003).  The elevated gCBF at HA did not sufficiently compensate for the reduced arterial lactate concentration, resulting in a lower CDLac for most of recovery at HA compared with SL (p < 0.05, Fig 5C). When compared with SL, there was a greater absolute CMRO2 at HA during the entire 30 min of recovery (p <0.05, Table 5.4, Fig 5.4B), despite an unaltered CMRglu and CMRlac compared to rest at either altitude (Table 5.4, Fig. 5.5B).  However, CMRglu was higher at HA compared with SL values during the 1st, 2nd, 4th , 25th and 30th min of recovery, whereas CMRlac was lower at HA during 1st, 2nd, 4th min of recovery compared with SL (p < 0.05).         152 Table 5.3. Cardiorespiratory and arterial-venous variables during recovery at sea-level and high-altitude (5050m) Recovery time following exercise (min)  Cond 1 2 4 6 8 10 15 20 25 30 HR (BPM) SL 134 ±14* 113 ±17* 98   ±10* 97 ±11* 97 ±13 93 ±12 86   ±14 90 ±11 86  ±11 84  ±12 HA 110   ±12* 91  ± 14* 88 ±14* 85 ±14 86 ±10 85 ±11 80 ±13 77  ±9 80  ±12 79  ±11 MAP (mmHg) SL 116 ±10 113 ±9 99 ±7 96 ±7 87 ±24 96 ±4 99 ±7 101 ±5 103 ±5 104 ±3 HA 134 ±6† 122 ±8† 118 ±9† 116 ±17† 114 ±19† 113 ±8† 117 ±10† 115 ±10† 119±8† 120 ±6† PETO2 (mmHg) SL 120 ±6* 120 ±6* 116 ±5* 114 ±6 113 ±6 109 ±7 106 ±7 102 ±8 99 ±9 96 ±8 HA 59 ±4*† 57 ±5*† 57 ±3*† 56 ±4*† 55 ±4*† 53 ±4† 51 ±4† 49 ±3† 48 ±3† 47 ±3† PETCO2 (mmHg) SL 32 ±6 31 ± 31 ±5 30 ±5 30 ±5 30 ±5 30 ±5 32 ±5 32 ±5 33 ±5 HA 23 ±3† 24 ±3† 24 ±3† 24 ±3† 23 ±3† 24 ±3† 24 ±3† 25 ±3† 25 ±3† 26 ±2† Fb (bpm) SL 29 ± 12 26 ± 11 21 ± 10 18 ± 9 20 ± 9 19 ± 8 18 ± 8 18 ± 8 16 ± 7 18 ± 7 HA 34 ± 17* 27 ± 14 22 ± 10 21 ± 9 21 ± 9 21 ± 10 18 ± 8 18 ± 8 19 ± 9 18 ± 8 VE  (l.min-1) SL 69 ± 17* 46 ± 9* 34 ± 10* 26 ± 4* 24 ± 4* 22 ± 5* 18 ± 2* 18 ± 2* 15 ± 2 15 ± 2 HA 72 ± 18* 46 ± 17* 36 ± 10* 32 ± 10* 28 ± 8* 28 ± 7* 23 ± 6 25 ± 8 21 ± 4 21 ± 4 Arterial PO2 (mmHg) SL 103 ±13 112 ±2* 109 ±5* 109 ±6* 103 ±5* 101 ±5* 98 ±6 91 ±7 91 ±9 87 ±6 HA 46 ±4† 52 ±4*† 52 ±4*† 52 ±4*† 50 ±4*† 50 ±5*† 48 ±5*† 43±4† 43 ±4† 43±4†        153             Table 5.3. Cardiorespiratory and arterial-venous variables during recovery at sea-level and high-altitude (5050m) PCO2 (mmHg) SL 33 ±2* 31 ±2* 31 ±2* 30 ±2* 30 ±2* 30 ±2* 31 ±2* 32 ±2* 33 ±2* 34±2* HA 20 ±2*† 20 ±3*† 21 ±3*† 20 ±3*† 20 ±3*† 20 ±3*† 20 ±2*† 21±2*† 22 ±2† 22±2† SO2 (%) SL 97 ±1 97 ±1 97 ±1 97 ±1 97 ±1 97 ±1 97 ±1 97 ±1 97 ±1 97 ±1 HA 78 ±5† 83 ±3† 83 ±2† 85 ±2† 83 ±2† 84 ±3† 84 ±4† 83 ±3† 81 ±3† 82±4† pH SL 7.20±0.05* 7.20±0.05* 7.18±0.06* 7.19±0.05* 7.20±0.05* 7.21±0.05* 7.26±0.04* 7.30±0.04* 7.33±0.03* 7.35±0.03* HA 7.32±0.06*† 7.32±0.05*† 7.31±0.05*† 7.33±0.07*† 7.34±0.07*† 7.34±0.07*† 7.41±0.06*† 7.43±0.04*† 7.45±0.03*† 7.46±0.03† CaO2 (ml.dl-1) SL 23±1* 22±1* 22±1* 21±1 22±1* 21±1 21±2 21±2 20±1 21±2 HA 19±2† 20±1*† 19±2† 19±1† 19±1† 19±1† 19±1† 18±1† 18±1† 18±1† Glucose SL 5.5±0.3 5.7±0.5 5.8±0.6 5.8±0.6 5.7±0.6 5.7±0.6 5.7±0.7 5.8±0.7 5.7±0.6 5.7±0.8 HA 5.5±0.6 5.5±0.6 5.5±0.8 5.4±0.8 5.4±0.8 5.4±0.8 5.5±0.7 5.4±0.5 5.3±0.5 5.3±0.4 Lactate SL 16.1±2.7* 15.8±2.6* 15.8±2.9* 14.7±2.6* 13.9±2.6* 12.9±2.2* 10.2±2.1* 8.2±1.9* 6.7±1.8* 5.5±1.4* HA 9.7±2.7*† 9.4±2.7*† 8.7±2.1*† 7.5±3.0*† 7.5±3.0*† 6.9±2.9*† 5.4±2.5*† 4.3±2.0*† 3.5±1.7*† 2.9±1.3*† Venous PO2 (mmHg) SL 38 ± 4* 37 ±3* 37 ±3* 37 ±3* 36 ± 3* 36 ± 3* 32 ±1 32 ± 2 32 ± 2 32 ± 2 HA 30 ± 2* 32 ± 2* 31 ± 1* 30 ± 2* 30 ± 2* 29 ± 2* 27 ± 3 26 ± 2 26 ± 1 27 ± 2                    154 Table 5.3. Cardiorespiratory and arterial-venous variables during recovery at sea-level and high-altitude (5050m) PCO2 (mmHg) SL 48 ± 1 47 ± 2 44 ±5 45 ±5 44 ± 2 44 ± 4* 44 ± 3* 45 ±3* 45 ± 3 44 ± 6 HA 26 ± 2*† 27 ± 2*† 28 ±3*† 28 ± 2*† 28 ± 2† 45 ± 5† 28 ± 2† 29 ±2† 29 ± 2† 29 ± 2† SO2 (%) SL 62 ± 6 61 ± 5 59 ± 4* 59 ± 5* 57 ± 4* 59 ± 4* 55 ± 4* 58 ±5* 58 ± 6* 61 ± 6 HA 50 ± 3† 55 ± 3† 53 ± 3† 51 ± 3† 50± 4† 50 ± 4† 48 ± 4*† 49 ± 4*† 48 ± 2*† 51 ± 3 pH SL 7.17±0.04 7.16±0.05 7.15±0.05 7.15±0.05 7.16±0.05 7.18±0.04 7.22±0.04 7.26±0.03 7.28±0.03 7.30±0.03 HA 7.30±0.06† 7.30±0.06† 7.29±0.06† 7.30±0.07† 7.30±0.07† 7.33±0.06† 7.37±0.05† 7.39±0.04† 7.41±0.03† 7.42±0.03† CvO2 (ml.dl-1) SL 14 ± 2 14 ± 1 13 ± 1* 13 ± 1* 13 ± 3* 13 ± 1* 12 ± 1* 12 ± 1* 12 ± 1* 13 ± 1* HA 12 ± 1† 13 ± 1* 12 ± 1† 12 ± 1† 11 ± 1† 11 ± 1† 11 ± 1† 10 ± 1*† 10 ± 1*† 11 ± 1*† Glucose SL 5.0 ± 0.4 5.1 ± 0.6 5.1 ± 0.4 5.3 ± 0.7 5.3 ± 0.8 5.2 ± 0.7 5.2 ± 0.7 5.3 ± 0.7 5.3 ± 0.7 5.1 ± 0.8 HA 4.9 ± 0.6 4.9 ± 0.6 5.0 ± 0.7 5.0 ± 0.7 5.0 ± 0.8 4.9 ± 0.7 4.9 ± 0.6 4.9 ± 0.5 4.8 ± 0.5 4.8 ± 0.8 Lactate SL 12.0 ± 1.6 12.0 ± 2.0 11.4 ± 2.2 12.2 ± 3.0 12.0 ± 2.6 10.8 ± 2.4 8.6 ± 2.0 7.2 ± 1.5 5.8 ± 1.1 4.7 ± 0.9 HA 8.2 ± 1.9 8.0 ± 2.2 7.6 ± 2.3 7.1 ± 2.4 6.5 ± 2.4 6.0 ± 2.6 4.7 ± 2.1 3.8 ± 1.6 3.2 ± 1.4 2.7 ± 1.1 Arterial–venous differences and metabolism Ca-vO2   (ml.dl-1) SL 8.2 ± 2.0 8.6 ± 1.1* 8.7 ±1.0* 8.4 ± 0.8* 8.8 ± 1.1* 8.5 ± 0.8* 9.0 ± 0.9* 8.4 ± 1.3 8.0 ± 1.4 8.3 ± 2.3 HA 6.9 ± 1.5 6.9 ± 1.2 7.1 ± 1.3 7.8 ± 1.2* 7.6 ± 1.4* 7.8 ± 1.5* 8.0 ± 1.5* 7.7 ± 1.2* 7.5 ± 1.1 7.0 ± 1.3          155    Table 5.3. Cardiorespiratory and arterial-venous variables during recovery at sea-level and high-altitude (5050m) O2Ext (%) SL 36 ± 9 39 ± 5* 40 ± 4* 39 ± 4* 40 ± 5* 40 ± 4* 43 ± 4* 40 ± 5* 40 ± 5* 40 ± 7 HA 38 ± 5 36 ± 4 38 ± 4 41 ± 4 41 ± 4 43 ± 5 44 ± 4 43 ± 5 43 ± 3 40 ± 5 Gluca-v (mmol.l-1) SL 0.6 ± 0.2 0.6 ± 0.3 0.6 ± 0.3 0.5 ± 0.3 0.5 ± 0.3 0.5 ± 0.2 0.6 ± 0.2 0.4 ± 0.2 0.4 ± 0.2 0.6 ± 0.6 HA 0.7 ± 0.2 0.7 ± 0.2 0.6 ± 0.2 0.6 ± 0.2 0.6 ± 0.2 0.6 ± 0.4 0.6 ± 0.4 0.6 ± 0.3 0.6 ± 0.2 0.6 ± 0.2 Laca-v (mmol.l-1) SL 4.1 ± 1.5* 3.8 ± 1.6* 4.1 ± 1.8* 2.5 ± 2.4* 1.9 ± 2.2* 2.0 ± 2.0* 1.6 ± 1.7* 1.0 ± 1.2* 1.0 ± 0.7* 1.0 ± 1.2 HA 1.6 ± 0.8*† 1.4 ± 0.8*† 1.2 ± 0.9*† 1.1 ± 0.7* 1.0 ± 0.8* 0.8 ± 0.8* 0.6 ± 0.6* 0.4 ± 0.5 0.3 ± 0.4 0.3 ± 0.3* Ratios OGI  SL 7.9 ± 2.7 6.4 ± 3.2 7.7 ± 5.6 12 ± 13 14± 11 11 ± 11 8.1 ± 5.2 9.2 ± 3.8 6.9 ± 4.0 7.6 ± 4.4 HA 4.6 ± 1.5† 4.7 ± 1.4 4.9 ± 0.8 6.9 ± 3.5 10 ± 14 10 ± 14 8.4 ± 6.4 8.4 ± 6.5 7.2 ± 5.6 7.0 ± 5.3 OCI SL 1.4 ± 0.4* 1.5 ± 0.4* 1.5 ± 0.6* 1.8 ± 0.8* 2.3 ± 0.7* 2.1 ± 0.4* 2.4 ± 0.5* 3.0 ± 2.0 4.9 ± 3.8 6.3 ± 7.6 HA 2.1 ± 0.6† 2.4 ± 0.6† 2.6 ± 0.6† 3.2 ± 0.9† 3.2 ± 1.0 4.8 ± 3.9 5.9 ± 4.3 5.6 ± 2.8 5.0 ± 2.2 4.8 ± 2.2 Cond: Condition; HR: heart rate (beats per minute) ; MAP: mean arterial pressure; PETO2 partial pressure of end-tidal oxygen; PETCO2: partial pressure of end-tidal carbon dioxide: Fb: breathing frequency (breaths per minute); VE: minute ventilation; PO2: partial pressure of oxygen; PCO2: partial pressure of carbon dioxide; SO2: oxygen saturation; CaO2: arterial oxygen content; CvO2: venous oxygen content; Ca-vO2: arterial venous oxygen content differences; O2Ext: relative fraction of oxygen content; Glua-v: cerebral arterial venous glucose differences; Laca-v: arterial venous lactate differences; OGI: oxygen glucose index; OCI: oxygen carbohydrate differences. * Signifies differences from baseline (p <0.003), † signifies differences between SL and HA (p <0.05).        156 Table 5.4.  Cerebral blood flow and metabolism measurements during recovery at sea‐level and high‐altitude   Recovery (min) Var Cond 1 2 4 6 8 10 15 20 25 30 MCAv (cm.s-1) SL 73 ±15 70 ±12 68 ±12 66 ±11* 65 ±10* 66 ±10 67 ±11 66 ±10 66 ±12 67 ±12 HA 88 ±10*† 85 ±9*† 81 ±10*† 75 ±8 74 ±7 74 ±7 75 ±8 77 ±10 78 ±10 79 ±11 PCAv (cm.s-1) SL 51 ±12 49 ±10 48 ±11 45 ±8* 46 ±8* 48 ±10 47 ±9* 47 ±8* 46 ±8* 47 ±9 HA 61 ±9*† 60 ±9*† 58 ±10*† 53 ±9 53 ±9 52 ±7 53 ±4 54 ±8 56 ±8† 57 ±9† QICA (l.min-1) SL  283 ±99 267 ±84 269 ±85 260 ±91 259 ±89 259 ±89 258 ±80 264 ±76 263 ±91 HA 350 ±48 349 ±71 340 ±89 328 ±89 323 ±94 324 ±94 327 ±66 322 ±61 330 ±68 321 ±66 ICAdiam (cm) SL - - 0.53 ±0.04 0.53 ±0.04 0.58 ±0.04 0.55 ±0.06 0.52 ±0.05 0.54 ±0.05 0.54 ±0.05 0.52 ±0.07 HA - - 0.55 ±0.8 0.54 ±0.08 0.55 ±0.08 0.54 ±0.54 0.55 ±0.07 0.55 ±0.07 0.56 ±0.08 0.55 ±0.08 ICAvel (cm.s-1) SL - - 38 ±7 39 ±9 36 ±8 36 ±6 40 ±4 37 ±6 38 ±6 41 ±5* HA - - 48 ±5† 47 ±5† 45 ±5† 46 ±2† 46 ±10 45 ±8 45 ±9 46 ±9 QVA (l.min-1) SL - -  81 ±35 80 ±35 85 ±38 76 ±33 70 ±31 77 ±37 81 ±33 HA - - - - - - - - - -        157 Table 5.4.  Cerebral blood flow and metabolism measurements during recovery at sea‐level and high‐altitude gCBF (ml.100g.min-1) SL 47 ±12 46 ±10 44 ±11 43 ±10 42 ±10 43 ±9 43 ±9 43 ±9 43 ±10 44 ±9 HA 62 ±8*† 61 ±8† 57 ±9† 54 ±8† 53 ±7† 53 ±6† 54 ±5† 54 ±4† 56 ±6† 56 ±5† CVRigCBF SL 2.2 ±0.7 2.2 ±0.6 2.0 ±0.6 2.0 ±0.6 1.8 ±0.6 2.0 ±0.5 2.0 ±0.5 2.1 ±0.5 2.1 ±0.6 2.1 ±0.5 HA 1.8 ±0.2 1.7 ±0.2† 1.8 ±0.3 1.9 ±0.3 1.8 ±0.3 1.8 ±0.2 1.8 ±0.2 1.8 ±0.2 1.8 ±0.2 1.8 ±0.2 CVCigCBF SL 0.48 ± 0.13 0.48 ± 0.12 0.53 ± 0.15 0.53 ± 0.15 0.64 ± 0.29 0.53 ± 0.13 0.52 ± 0.10 0.50 ± 0.10 0.49 ± 0.11 0.50 ± 0.10 HA 0.55 ± 0.06 0.59 ± 0.09 0.58±0.11 0.55±0.10 0.55±0.09 0.55±0.09 0.54±0.08 0.56±0.08 0.55±0.07 0.56±0.07 CDO2 (ml.min-1) SL 148 ± 34 143 ± 30 136 ± 28 128 ± 28 128 ± 23 128 ± 24 126 ± 23 125 ± 20 122 ± 26 127 ± 21 HA 162 ± 25* 168 ± 24* 155 ± 23* 146 ± 21 140 ± 20 140 ± 21 141 ± 17 140 ± 13 140 ± 18 143 ± 16 CDglu(mmol.100g-1.min-1) SL 262 ± 70 260 ± 63 261 ± 76 251 ± 65 246 ± 60 247 ± 61 250 ± 55 248 ± 50 242 ± 6 246 ± 50 HA 330 ± 54 335 ± 73 319 ± 84 300 ± 79 291 ± 73 291 ± 74 292 ± 62 294 ± 49 299 ± 53† 299 ± 47† CDlac (mmol.100g-1.min-1) SL 741 ± 178* 710 ± 169* 698 ± 204* 623 ± 162* 583 ± 163* 549 ± 153* 441 ± 122* 350 ± 97* 287 ± 93* 240 ± 72*  HA 597 ± 148* 561 ± 167* 501 ± 171* 438 ± 156*† 400 ± 163*† 361 ± 150*† 282 ± 139*† 226 ± 111*† 190 ± 97*  167 ± 82*        158 Cond: condition; MCAv; middle cerebral artery velocity; PCAv: posterior cerebral artery velocity; QICA: internal carotid blood flow; ICAdiam: internal carotid artery diameter; ICAvel: internal carotid artery velocity; QVA: Vertebral blood flow; VAdiam: Vertebral artery diameter; VAvel: Vertebral artery velocity; gCFB: global cerebral blood flow; CVRigCBF: cerebrovascular resistance; CVCigCBF: cerebrovascular conductance; CDO2: cerebral oxygen delivery; CDglu: cerebral glucose delivery; CDLac: cerebral lactate delivery; CMRO2: cerebral metabolic rate of oxygen; CMRglu: cerebral metabolic rate of glucose; CMRlac: cerebral metabolic rate of lactate. * Signifies differences from baseline (p <0.003), † signifies differences between SL and HA (p <0.05).   Table 5.4.  Cerebral blood flow and metabolism measurements during recovery at sea‐level and high‐altitude CMRO2 (ml.g-1.min-1) SL 1.6 ± 0.2* 1.7 ± 0.3* 1.7 ± 0.3* 1.6 ± 0.3* 1.6 ± 0.3* 1.6 ± 0.3* 1.7 ± 0.3* 1.5 ± 0.3 1.5±0.3 1.5±0.3  HA 2.1 ± 0.4*† 2.1±0.4*† 2.0±0.2*† 2.0±0.2*† 2.0±0.2*† 2.0±0.3*† 2.1±0.2*† 2.0±0.3*† 2.0±0.3*† 1.9±0.2*† CMRglu (µmol.100g-1.min-1) SL 21 ± 6 30 ± 11 26 ± 10 22 ± 11 18 ± 10 20 ± 9 24 ± 7 19 ± 9 18 ± 5 20 ± 8 HA 44 ± 12† 44 ± 12† 40 ± 6† 34 ± 16 34 ± 17 35 ± 20 31 ± 14 32 ± 16 36 ± 16† 34 ± 12† CMRlac (µmol.100g-1.min-1) SL 199 ± 85 178 ± 79 194 ± 100 107 ± 114 89 ± 106 89 ± 95 74 ± 85 47 ± 58 47 ± 33 50 ± 61 HA 103 ± 61† 89 ± 51† 80 ± 46†  66 ± 42 63 ± 41 48 ± 48 32 ± 41 32 ± 41 19 ± 23 20 ± 15       159 Figure 5.6: The ratio of oxygen and glucose uptake (OGI= O2/ Glucose; C) and ratio oxygen to carbohydrate uptake (OCI = O2/ Glucose + ½ Lactate; E) as an indexes of oxidative versus non oxidative metabolism during baseline (BL) incremental exercise (20 -100 % of the maximum achieved workload [%Wmax]) and 30 min of recovery at sea level (SL; ) and high altitude (HA; ). * Signifies differences from BL, † Signifies difference between SL and HA (p<0.05).    BL 20 40 60 80 100 1 2 4 6 8 10 15 20 25 3005101520† † †OGIExercise (%Wmax) Recovery (Min)BL 20 40 60 80 100 1 2 4 6 8 10 15 20 25 300123456789Exercise (%Wmax) Recovery (Min)†** * * * * ** ** ****†OCI†! SL " HAAB! ! !160Cumulative metabolism (Fig. 5.4) The cumulative molar ratio of carbohydrate to oxygen (CMRU) progressively rose from baseline to the end of recovery (Fig. 5.4; p<0.003), with it being higher at rest and during submaximal exercise (20-60% Wmax) at HA compared to SL (p<0.05), but lower during recovery at HA compared to SL (interaction: p=0.001). There was a similar rise in the cumulative metabolic ratio of carbohydrate to oxygen (CMRUgCBF) from baseline to the end of recovery (P<0.003).   ! ! !161  Figure 5.7: Arterial lactate concentration (A), ratio of oxygen to carbohydrate uptake (OCI = O2/ Glucose + ½ Lactate; B), cerebral oxygen delivery (CDO2; C), and cerebral metabolic rate of oxygen (CMRO2; D) during incremental exercise at the same absolute workload (60, 120 and 150 watts) at sea-level (SL; ) and high altitude (HA; ). † Signifies difference between SL and HA (p<0.05).   60 120 15001234567891011Exercise (Watts)†††60 120 15001234567Exercise (Watts)60 120 15001234567891011Exercise (Watts)†††20% vs 40% 40% vs 80% 60% vs 100%60 120 1500.00.5† † †1.01.52.0Exercise (Watts)20% vs 40% 40% vs 80% 60% vs 100%20% vs 40% 40% vs 80% 60% vs 100%20% vs 40% 40% vs 80% 60% vs 100%A BC D! ! !1625.4. Discussion !Our main novel findings were: 1) following partial acclimatization to HA, elevations in gCBF during and following exercise facilitate the maintenance of CDO2.  Despite this maintained CDO2, CMRO2 was generally elevated during submaximal exercise and recovery compared with SL. At maximal exercise, however, the relative increase in CMRO2 at HA was ~half that of the SL response; 2) Despite a CDO2 in excess of CMRO2 at HA and SL (Fig 7), the brain appears to increase non-oxidative metabolism, as reflected by an OCI lower than six (complete oxidation of carbohydrates), during exercise and recovery. The reason for this latter finding is not obvious; however, the greater arterial lactate during exercise at HA compared with SL during similar workloads and the continued maintenance of the non-oxidative metabolism and greater arterial lactate during recovery at SL may implicate lactate availability as a key factor.   Global cerebral blood flow and delivery at high altitude: rest, exercise and recovery The temporal changes in gCBF rest upon initial arrival and over time at HA (>3500 m) that serve to maintain CDO2 have been well described in seven studies (Ainslie & Subudhi, 2014). Although isocapnic hypoxia at SL causes a greater increase in posterior blood flow comparable to anterior flow (Willie et al., 2012), the lack of regional changes in CBF is consistent with other studies over a comparable time frame at altitudes >5000m (Subudhi et al., 2014; Willie et al., 2014b).  In contrast, only four studies have monitored CBF (Möller et al., 2002) or velocity (Huang et al., 1991; Imray et al., 2005; Siebenmann et al., 2013) during exercise at HA; However, none of these studies measured regional CBF distribution, oxygen delivery, or metabolism during exercise despite previous ! ! !163findings showcasing regional differences to specific brain regions that control motor/ sensory, cerebellum and/or brainstem regions (Herholz et al. 1987). Nevertheless, at a global inflow level the regional distributions from the current study were not different during exercise and recovery at either altitude.  This is in contrast to the larger increase in VA flow compared with ICA changes during upright exercise at SL observed by Sato et al. (2011). Möller et al. (2002) observed gCBF to be unaltered from supine rest during both SL and HA upright exercise.  Furthermore, no differences in gCBF were observed between SL and HA during exercise with similar absolute workloads (i.e., 100 W) at SL and HA. This finding is supported by Huang et al. (1991) who reported no difference in absolute change in ICA velocity during exercise following a prolonged exposure to HA (~18 days).  However, the authors reported a larger relative increase in ICA velocity from rest during an incremental exercise bout to exhaustion following acute exposure to hypobaric hypoxia (barometric pressure and inspired PO2 similar to 4300 m; ~ +30%) versus SL (~ 17%). Only limited interpretations are possible regarding gCBF because the authors did not report VA measurements or ICA diameter (Huang et al., 1991). Imray et al. (2005) reported that despite an increased MCAv following acute exposure to HA (5260m; <1-2 days), the estimated CDO2 (i.e., MCAv * arterial oxygen saturation) was reduced at maximal exercise compared to the maintained CDO2 at sea level (150 m); as reflected in both a reduction in saturation and MCAv baseline measures at maximal exercise. During incremental exercise at moderate altitude (i.e., 3454m), Siebenmann et al. (2013) observed an unexpected elevation in MCAv during maximal intensities when compared to the reductions observed at SL (Fisher et al., 2013, #16983; Moraine et al., 1993; Sato ! ! !164et al., 2011; Smith et al., 2012). Our findings support those of Siebenmann et al. (2013) such that gCBF during exercise at HA is increased during maximal exercise intensities compared with SL. Moreover, our study extends these previous findings from a lower elevation by incorporating both anterior and posterior regional volumetric flow. The functional relevance of the ‘paradoxical’ elevation in gCBF at maximal exercise at HA is unknown but is likely beneficial for the maintenance of CDO2 in excess of CMRO2, as observed during SL exercise.  At HA, the elevated gCBF during maximal exercise remained elevated above SL throughout recovery. One possible explanation for this is that during recovery fluctuations in gCBF reflect the need to preserve CDO2 in excess of CMRO2.      Cerebral oxygen delivery, extraction, and metabolism during exercise:   Three novel findings related to CDO2, extraction and metabolism have been revealed:  1) Maintenance of oxygen delivery during exercise: Following partial acclimatization to HA with a reduced CaO2 (Tables 5.1 and 5.3), our findings highlight a compensatory increase in gCBF during exercise at HA in order to maintain CDO2 at HA in response to a reduced CaO2. Evidence indicates that the CBF response to hypoxia appears to be determined more so by oxygen content versus PaO2. For example, studies using carbon monoxide exposure (Todd et al. 1994; Paulson et al. 1973) acute or chronic anaemia (Brown et al. 1985; Brown et al. 1985) or haemodilution have all reported elevations in CBF independent of changes in PaO2 (Paulson et al. 1973; Todd et al. 1994; Tomiyama et al. (1947)); thus, CaO2 (or haemoglobin) seems to regulate CBF not necessarily just PaO2. In contrast, despite elevated limb blood flow during exercise at high altitude (5260 ! ! !165m) following haemodilution, O2 delivery is not maintained (Calbet et al. 2002). These findings highlight a differential capacity or mechanism involving the regulation of oxygen delivery between the muscle and the brain during exercise at high altitude.  The two previous studies that have attempted to investigate CDO2 during exercise at high altitude have reported that CDO2 delivery is unaltered during moderate intensity exercise (Moller al., 2002) and reduced (by ~18%) at maximal exercise (Imray et al. 2005). There are two distinct differences between the Imray et al. (2005) study and the current study. First, Imray et al. (2005) estimated CDO2 by multiplying arterial saturation (SaO2) and MCAv, whereas we measured CDO2 by measurement of arterial oxygen content and utilized a combination of volumetric flow measures (i.e., QICA + QVA) and velocity measures (i.e., ∆MCAv and ∆PCAv). Second, during maximal exercise at high altitude Imray et al. (2005) observed a drop in MCAv similar to SL. In contrast, and generally consistent with another report at 3454m (Siebenmann et al. (2013), we observed that gCBF, MCAv, and PCAv during maximal exercise continued to be elevated from resting values. Such changes subsequently maintaining CDO2 above rest at HA to comparable levels observed during exercise at SL. The mechanisms explaining the tight control of gCBF and CDO2 in excess of CMRO2 during exercise are unknown, but likely involve one of two possible standpoints: 1) that gCBF and CDO2 are not tightly coupled to CMRO2 as indicated by a lack of linearity between increases in gCBF/CDO2 and CMRO2 (Fox & Raichle, 1986; Fox et al., 1988); and 2) that the coupling between delivery and metabolism may be described by an exponential relationship (Buxton & Frank, 1997).  The latter is believed to be related to a limited capacity for cerebral capillary recruitment and a constant or fixed oxygen diffusion through from the capillaries to the cerebral ! ! !166tissues, ultimately requiring a large increase in gCBF and/or oxygen extraction to elevate CMRO2 (Buxton & Frank, 1997; Mintun et al., 2001). For example, unlike in the skeletal muscle or the lungs, it is generally accepted that the diffusive surface area for O2 remains constant in the brain – i.e. the brain does not increase capillary recruitment (Kuchinsky et al., 1992; William et al. 1993). Therefore, cerebral oxygen extraction can be described as being inversely proportional to CBF when metabolism is held constant, and directly proportional to metabolism when CBF is held constant.  Acclimatization to HA is a multifaceted process involving cardiorespiratory and renal compensatory changes that are most dynamic during the first few weeks of exposure (Ainslie & Subudhi 2014; Ogoh and Ainslie, 2010).  Hypoxic stimulation of the peripheral chemoreceptors leads to hyperventilation, resulting in hypocapnia and respiratory alkalosis for which renal bicarbonate excretion slowly compensates. The balance between neuronal substrate demand, blood pressure, arterial blood gases, and pH determine the volume of blood flow to the brain (Willie et al., 2014). Ascent to HA thus represents a complex stimulus to the cerebrovasculature, the nature of which is not well understood, particularly in light of sustained alterations and compensations in arterial blood gases and pH. The sensitivity of CBF to CO2 appears to rely on diffusion of molecular CO2 into the vascular wall where the resultant shift in extracellular pH drives changes in smooth muscle tone (Lassen et al., 1968). That CBF is a function of extravascular pH rather than arterial pH is further supported in earlier studies showing that CBF at HA was equivalent to SL despite chronic alkalosis, indicating CBF CO2 sensitivity is reset over time at HA (reviewed in: Ainslie & Subudhi 2014). The ! ! !167implications of such adjustments are that CBF is likely regulated differently by PaCO2 and pH at rest and during exercise at HA.  2) Differential changes in CMRO2 and extraction during exercise:  Cerebral perfusion and oxygen extraction elevations during incremental cycling exercise at SL result in a 25% increase in CMRO2 at maximal intensity when estimating gCBF using relative changes in MCAv (Fisher et al., 2013). A similar increase in CMRO2 is observed during a maximal rowing time trial (Rasmussen et al., 2010b). These findings are similar to our results, which indicate a progressive rise in CMRO2 from rest during incremental exercise, with the largest increase occurring at 100% Wmax (up ~30%). In contrast, Trangmar et al. (2014) did not observe an increase in CMRO2 at any point during incremental exercise to exhaustion when using ICA flow as an index for gCBF. However, Trangmar et al. (2014) likely underestimated CBF by only measuring the flow in the anterior circulation, as VA flow has been shown to progressively increase during incremental exercise up to at least 80% VO2 peak (~35-60% above baseline (Sato et al., 2011)). Based on our exercise data, and in agreement with others (Fisher et al., 2013; Möller et al., 2002; Overgaard et al., 2012). CMRO2 does not appear to be altered until maximal intensity exercise is achieved at both SL and HA. Our data show a differential response, with the increase in CMRO2 at HA achieved through increases in gCBF (Figures 5.3 and 5.4), whereas at SL the increase is achieved via an increased oxygen extraction (Table 5.3). In comparison, the HA CMRO2 value is greater than SL during exercise at the same workloads (20, 60, 150 watts; Figure 6). The differences between the relative increase in CMRO2 from rest to maximal exercise at HA (~17%) and SL (~27%) ! ! !168is most likely related to the lower absolute maximum workload achieved at HA (150 watts) versus SL (300 Watts). Collectively, these findings are consistent with the reported linear relationship between absolute intensity/frequency dependent increases in focal CMRO2 during graded motor activation (i.e., finger tapping) (Kastrup et al., 1999).   3) Non-oxidative metabolism during exercise and recovery  At HA there was a disproportionate increase in carbohydrate uptake versus oxygen uptake (i.e., reduced OCI) at rest and during low-to-moderate intensity (20 to 60% Wmax) exercise compared with SL.  The disproportionate increase is believed to indicate that the brain has altered a portion of its ATP production from oxidative to non-oxidative pathway (Wyss et al., 2011). Additionally, at HA both at rest and during all exercise intensities except 100% Wmax, CMRU and CMRUgCBF were higher than SL (Fig 5.4). However, with increasing exercise intensity (60, 80 and 100% Wmax) OCI was not noticeably different at HA compared with SL. During recovery, OCI at HA returned almost immediately following the cessation of exercise and was elevated above SL for much of recovery, whereas SL OCI remained below resting values for most of recovery. Furthermore, the increase in CMRU during HA recovery was ~half of SL values. However, no reliable statistically significant difference was observed for the CMRUgCBF during recovery for either altitude compared to rest, nor was there a difference between SL and HA values. The measurement of CMRU indicates the molar quantity of carbohydrate substrate that is in excess of the oxygen extraction, while CMRUgCBF incorporates the gCBF providing both a convective and diffusive component to cerebral carbohydrate metabolism. Collectively, these findings indicate that the surplus of cerebral ! ! !169carbohydrate uptake compared with oxygen uptake during exercise at SL was greater at HA, and independent of gCBF. During recovery the elevated gCBF results in a similar contribution of non-oxidative at HA and SL (Fig. 5.3).  Our findings are both consistent and inconsistent with Volianitis et al. (2008) who despite a reduction in OCI with exercise intensity during normoxic and moderate hypoxic steady-state 2000 m rowing time trial, observed no significant difference in OCI when oxygen intake was varied. The discrepancies between the Volianitis et al. (2008) study and our findings may be related to the difference in the intensity of the hypoxic exposure, with their study inducing a mild (FiO2 = 0.17) hypoxic exposure versus the more severe exposure of our HA (~ FiO2= 0.108 at 5050m).  Another possibility may be related to the exercise intensity, such that during the 2000 m rowing time trials, the intensity was above the submaximal intensities that elicited the differences observed in the current study. As illustrated in Figure 6, greater amounts of arterial lactate was produced that, in the context of the increased CMRU (Fig 5.4) and reduced OCI (Figure 5.5) at HA during exercise at the same workload (20 vs. 40%, 40 vs. 80%, and 60 vs. 100% Wmax at SL and HA, respectively), suggests the increase in non-oxidative metabolism may not be only intensity dependent but also lactate dependent.  However, Volianitis et al. (2011) observed no difference in OCI during SL rowing time trial with an elevated pH and greater arterial lactate production. Our sea-level response is similar to the response observed by (Dalsgaard et al., 2004a), who reported that the CMRU increased during a 15-minute exercise bout to exhaustion. Unfortunately, a hypoxic trial was not conducted. It seems likely that the combination of a greater workload and subsequent increase in the ! ! !170production of lactate in the current data set, may explain the difference in the changes to oxidative and non-oxidative metabolism during exercise and recovery at SL and HA.  5.4.1. Methodological considerations and limitations The current study was performed in a controlled laboratory setting at sea level, as well as in a high-altitude laboratory at 5050m following a 9-day ascent. Unfortunately,!because!of!sickness!and!time!constraints,!we!were!only!able!to!collect!data!in!9!out!of!the!12!subjects. Our data set and results only pertain to males, as no females were studied. Casey et al. (2013) demonstrated that, at sea level, women had an elevated hypoxic vasodilatory response in the forearm at rest and during exercise independent of baseline forearm blood volume.  However, it remains unknown if any sex differences exist in the gCBF response during exercise at HA; control of menstrual phase and extent of acclimatization during these conditions would be problematic. It is important to note, that all CBF measurements were made using either vascular ultrasound or a combination of vascular (Lewis et al., 2014a) and transcranial (TCD) ultrasound (Gonzalez-Alonso, 2004).  Each measurement of gCBF utilizes the blood flow measurements in the right ICA and left VA (Subudhi et al., 2014). Despite no reported differences in blood flow between contra-lateral ICAs, a regional disparity (~20%) between contra-lateral vertebral vessels has been observed (Schöning et al., 1994). However, should a disparity between contra-lateral VAs exist while in the current study at rest, one would anticipate that the stimulus-response would be similar during exercise. Moreover, the limitations of using TCD been documented, with the primary concerns being related to whether or not the intracranial vessels change in diameter.  Following ascent to HA the MCA diameter does increase (Willie et al., 2014b; Wilson et al., 2011).  ! ! !171Our finding at HA of an elevated QICA flow at rest in the face of an unchanged MCAv is consistent with MCA dilation. Although the changes in estimated gCBF were broadly consistent with the direct Fick measures, we cannot rule out dilation of MCA during exercise considering dilation is likely mediated via hypoxemia, which was greater during exercise. However, since the reductions in PaO2 during exercise at HA were countered by a similar drop in PaCO2 and maintained pH (Fig 5.2), this would seem unlikely; therefore, consistent with the direct Fick data, the stimulus-response changes in MCAv/PCAv seem valid during exercise at 5050m. Furthermore, at both SL and HA, the observation that CVRi was not reduced supports our findings that there was no further active vasodilation of the larger cerebral arteries (e.g., MCA and PCA) from rest during exercise. Previous investigations of CBF and cerebral metabolism responses to HA have been compared during either similar absolute intensity exercise (Moller et al. 2002), or during incremental exercise tests with different durations (Imray et al. 2005; Seibennman et al. 2013). Each of the exercise intensities in the current study established steady state allowing for comparison of both relative (Figures 5.2-5.6) and absolute exercise intensity (Figure 6). For a given absolute workload gCBF is elevated at HA compared with SL, such that it maintains CDO2 in excess of CMRO2, while OCI is reduced as expected given the greater availability of arterial lactate at HA (~50% more) versus SL.  In contrast, during exercise at HA, with similar workloads to SL, a reduced arterial lactate is reported despite reduced available oxygen [i.e., lactate paradox (Kayser, 2006; West, 1986)].  It should be noted that all subjects would have been exercising for 3 - 6 min longer at HA for a given workload at SL.  The increased time could allow greater ! ! !172accumulation of blood lactate and could explain part of the discrepancy between the current findings and previous investigations focusing on lactate production at HA during similar absolute workloads.  We did not measure circulating catecholamines as a index of adrenergic drive, which if elevated at high altitude, may have influenced the different arterial lactate productions during exercise (Kayser, 2006), and possibly the increased non-oxidative metabolism (lower OCI) at rest and during exercise with the same workloads at HA (Figure 5.7) (Seifert & Secher, 2011; Seifert et al., 2009a). 5.5. Summary In conclusion,! the elevations in gCBF during exercise and recovery at HA maintain an adequate CDO2 to CMRO2 ratio.  Despite preservation of this ratio, as reflected by paralleled increases in CDO2 and CMRO2, the brain appears to prefer non-oxidative metabolism during exercise and recovery at HA and SL, even if the contribution to total energy production is marginal. ! ! !173Chapter 6. Volumetric flow during incremental exercise: influence of carbon dioxide and oxygen !6.1. Purpose and Background  Steady-state increases in exercise up to ~60-80% of peak oxygen uptake (VO2 peak) are reflected in elevations of extra-cranial cerebral blood flow (CBF; e.g., Sato et al., 2011) and intra-cranial cerebral blood velocities (CBV) (Madsen et al. 1993; Marsden et al. 2012; Moraine et al. 1993; Sato et al. 2011; Subudhi et al. 2008, 2009). At intensities greater than ~80% of VO2 peak, blood flow in the internal carotid artery (QICA) and intra-cranial velocities through the middle and posterior cerebral arteries (MCAv and PCAv) decrease from their peak toward baseline values! (Fisher et al. 2013; Sato & Sadamoto 2010; Sato et al. 2011; Smith et al. 2012). In contrast to the reduced (Smith et al. 2012) or plateau in PCAv at 80% Wmax (Smith et al. 2014), blood flow in the vertebral artery (QVA) continues to increase at least until 80% VO2 peak (Sato et al., 2011).  It is unclear if the regional (i.e., anterior and posterior) and intra-cranial velocities versus extra-cranial blood flows (i.e., PCAv vs QVA) is related to differences in the specific vessel responses to the primary factors that regulate CBF during exercise.  Regulation of global CBF (gCBF) during exercise is likely influenced by four main factors: Metabolic demand, perfusion pressure, redistribution of cardiac output and the partial pressure of arterial carbon dioxide [(PaCO2); reviewed in Ogoh & Ainslie (2009)]. Of these factors, PaCO2 is the most important. For example, changes in CBF and CBV during incremental exercise parallel changes in PaCO2 and are explained by an enhanced ! ! !174CBF reactivity to PaCO2 [~5% per mmHg change in PaCO2 (Rasmussen et al. 2006)] compared to an ~4% per mmHg at rest (Willie et al. 2012). Therefore, the paralleled elevations (e.g., +15-25%) in CBF and PaCO2 (e.g., +3-5 mmHg PaCO2 at 70% VO2 peak), combined with the return to baseline values in both CBF and PaCO2 at maximal exercise intensities, largely implicate PaCO2 as the primary mediator of CBF during exercise. In support, (Olin et al. 2011) elevated end-tidal PCO2 (PETCO2) by 10 mmHg at maximal exercise intensities (80-100% VO2peak) and were able to increase MCAv by +15%. The lack of hypocapnic vasoconstriction and subsequent increases in MCAv at maximal exercise supports the concept that PaCO2 plays a primary role in regulating CBF during incremental exercise (Olin et al. 2011). While these findings are pertinent to CBF at maximal exercise, what remains to be established is if maintaining PaCO2 at isocapnic levels at the onset of exercise would inhibit the typical exercise induced increases in CBF. It is also unknown if preventing the changes in PaCO2 may influence the previously reported regional differences in QVA compared with QICA and MCAv (Sato!et!al.,!2011).!! Under resting conditions, normobaric poikilocapnic hyperoxia (FiO2 > 300 mmHg) is known as a respiratory stimulant in adults, resulting in a hyperventilatory drop in PaCO2 ranging from 1-4 mmHg (Becker et al. 1996). Exercise while breathing hyperoxia (i.e., end-tidal partial pressure of Oxygen > 95 mmHg; PETO2) leads to a reduced minute ventilation (V̇E) and elevated PETCO2 compared to V̇E during normoxic exercise with similar absolute workloads (Asmussen & Nielsen 1946; Bannister & Cunningham 1954; Mateika & Duffin 1994; Miyamoto 1995; Nakazono & Miyamoto 1987; Welch et al. 1977). Recently, we have demonstrated that during submaximal exercise (~40% Wmax) ! ! !175the increase in PCAv was significantly greater during hyperoxia (+43%) compared with normoxic exercise (+20%) at the same relative intensity (Smith et al. 2012). The resting PETCO2 was reduced by approximately 5 mmHg following 10 minutes of breathing hyperoxia (PETO2 = 600 mmHg). In the same study, the increase in PETCO2 from rest to exercise (+10 mmHg) was significantly greater than the increase observed during normoxia (+7 mmHg). The larger relative increase in PETCO2 in hyperoxia was speculated as the primary reason for the larger increase in PCAv when compared to the MCAv. It remains unknown if the larger change in PaCO2 from rest to exercise is responsible for the increased PCAv during submaximal exercise intensities or if hyperoxia has a direct influence on CBF during exercise.   In addition to the importance of PaCO2 during exercise for CBF regulation, the action of V̇E per se may influence CBF. For example, Neubauer et al. (1983) observed a 22% increase in ventral medullary blood flow (i.e., brainstem) in cats, following a specialized hind-limb electrical stimulation that increased V̇E by 2.5 fold while maintaining arterial blood gas tensions and pH (isocapnic hyperpnea).  This model effectively showed that, despite no difference in the gCBF during isocapnic hyperpnea, regional blood flow through the respiratory control centers (e.g; posterior circulation) was significantly increased. Although such changes in V̇E may explain, in part, previously reported regional changes in CBF during exercise [e.g., (Sato et al. 2011)], this possibility has yet to be explored in humans.  ! ! !176Considering this rationale, the aims of this study were to address the following questions: 1) Is the increase in CBF during incremental exercise primarily mediated by PaCO2; 2) Are the regional differences in CBF during hyperoxia also explained by changes in PaCO2; and 3) What are the independent effects of V̇E on regional and gCBF during hyperoxic and normoxic exercise. The following two hypotheses were examined: 1) maintaining isocapnia during submaximal exercise will reduce gCBF and regional CBF differences in both normoxia and hyperoxia compared to poikilocapnia; and 2) isocapnic hyperpnea will increase posterior CBF but to a lesser extent than that observed during exercise. 6.2. Methods Participants The fourteen healthy (11 male), non-smoking participants (18 - 26 years; BMI <30 kg/m2), were screened prior to participating in the current investigation to ensure they were free from cardiovascular, cerebrovascular and respiratory disorders. The three female participants were tested in the early follicular phase  (day 1–7) of their menstrual cycle. All subjects avoided exercise, caffeine and alcoholic beverages for 12 hours and fasted for 4 hours prior to each session. All testing was approved by the Clinical Research Ethical Review Board of the University of British Columbia (H13-02624), and conformed to the standards set forth by the Declaration of Helsinki.  Study Design Following baseline screening and familiarization, participants visited the laboratory on three separate occasions. At the beginning of the first two visits participants performed one incremental exercise protocol (+ 20 W every 3 min beginning at 40 W) on a ! ! !177recumbent cycle ergometer (Lode Ergometer, Lode, Groningen, Netherlands) until exhaustion was achieved (maximum achieved workload [WMax]). Participants were asked to maintain a cadence between 60-70 RPMs throughout the protocol. Each test was performed in either normoxia or hyperoxia (PETO2 = 95 mmHg) versus hyperoxia  (PETO2 = 300 mmHg), respectively). Visits one and two were randomly ordered (separated by a minimum of 48 hours), and all participants were blinded to the specific FiO2. During the final visit, participants completed the isocapnic hyperpnea trial (details below).   Visit 1 and 2 (normoxia or hyperoxia):  Following the maximal exercise test (~1 hour) when baseline heart rate (HR), blood pressure and CBF had returned to resting values, participants were asked to perform one submaximal exercise protocol with relative workloads corresponding to 20, 40 60 and 80% of the maximum achieved workload (%WMax) in the exhaustive trial while breathing room air without an PETCO2 clamp in that order. The duration of each workload was approximately 5 minutes with data sampling occurring within the final 3 minutes of the stage once steady state had been achieved. Once cardiorespiratory, and cerebrovascular values had returned to baseline (~20 minutes), participants performed a final submaximal exercise protocol at 20 40 and 60% of WMax with a similar duration and sampling period as previous submaximal test; however, during this test PETCO2 was maintained at basal values (isocapnic). The PETCO2 was maintained at baseline values by asking participants to increase V̇E by ~20 l/min > as noted during the poikilocapnia exercise during 20, 40 and 60% Wmax. As described in detailed elsewhere (Tymko et al. 2015; Willie et al. 2012), elevation of PETO2 and PETCO2 was clamped using a modification of the end-tidal forcing system designed to ! ! !178manipulate PETO2 and PETCO2 on a breath-by-breath basis. To achieve the necessary rate of gas delivery during exercise two gas delivery systems were connected in parallel to a gas humidification chamber and a 6L capacity inspiratory breathing reservoir. In this configuration, the end-tidal forcing system can supply the necessary gas mixtures to a ventilatory capacity in excess of 220 L/min. Visit two was identical to visit one; however, all exercise was performed while breathing the alternate inspirate (depending on the experimental randomization).  Visit 3 (isocapnic hyperpnea): Following the completion of visits one and two (>48 hours), 11 participants returned to the laboratory to perform both a normoxic and hyperoxic isocapnic hyperpnea intervention. During each test, subjects were asked to breathe at similar ventilations achieved during the respective submaximal poikilocapnic exercise tests at 20, 40, 60 and 80% WMax, while PETCO2 was maintained at basal values using the end-tidal forcing system. The duration of each hyperpnea stage was approximately 5 minutes with data sampling occurring within the final 3 minutes of each stage once steady state had been achieved. Normoxic and hyperoxic hypernea trials were separated by 20 minutes once cardiorespiratory, and cerebrovascular values had returned to baseline values.   Instrumentation The cardiorespiratory and blood flow instrumentation is discussed in detail in Chapter 3. Respiratory gas exchange: Ventilation, PETO2 and PETCO2 were measured continuously using a two-way pneumotach (Series 3813, Hans Rudolph, Shawnee, KS) and gas ! ! !179analyzer connected to our data acquisition device (Powerlab/16SP ML 880; ADInstruments, Colorado, US), respectively. Each device was connected to the online acquisition system (Labchart 7, AdInstruments, Colorado, US). Invasive arterial blood gases were sampled from two individuals during both normoxic and hyperoxic exercise in normo- and poikilocapnia in order to confirm effectiveness of the end-tidal forcing system. Blood gas samples were drawn into a preheparinized syringe, and analyzed immediately (ABL-90 CO-Ox, Radiometer, Copnehagen, Denmark).    Statistical Analysis  Two-way repeated measures analysis of variance (ANOVA) was performed to investigate changes in all variables from baseline during normoxic versus hyperoxic exercise in conditions of poikilocapnia versus isocapnia. Repeated measures ANOVA was also performed to investigate absolute and relative differences from baseline values between anterior and posterior arteries (MCA vs PCA; ICA vs VA), as well as proximal and distal cerebral arteries (ICA vs MCA; VA vs PCA) during both PaO2 and PETCO2 manipulations. A P-value of <0.05 was considered statistically significant. Sidaks correction for multiple comparisons was applied when ANOVA’s identified significant differences or interactions.  ! ! !1806.2. Results Tables 6.1 and 6.2 summarize the collective findings during normoxic and hyperoxic exercise in conditions of poikilocapnia and isocapnia. In three subjects volumetric blood flow metrics were unattainable; therefore, comparisons between ICA, VA and gCBF were based on an n=14. The mean maximum achievable wattage during recumbent cycling was significantly elevated during hyperoxic (240 ± 55 W) compared with normoxic (200 ± 50 W) exercise (p <0.05). During poikilocapnic exercise VE increased linearly with exercise intensity Table 1. Additionally, because of the nature of the isocapnic exercise protocol, VE was 20% elevated at each stage of exercise compared with poikilocapnic exercise (Table 6.1).    ! ! !181  Table 6.1. Cardio-respiratory measurements during poikilocapnic and normocapnic exercise while breathing either normoxia or hyperoxia   Stage Measurement Condition BL1 BL2 20 % 40% 60% 80%   poikilocapnic VE  (l.min-1) Normoxia 13.5 ± 1.7* 12.4 ± 2.4 22.0 ± 4.0* 30.3 ± 6.3* 41.0 ± 9.5* 57.0 ± 12.0* Hyperoxia 13.4 ± 2.2* 13.7 ± 3.4 21.3 ± 5.0* 30.4 ± 5.8* 42.0 ± 8.2* 55.0 ± 13.0* HR (BPM) Normoxia 75 ± 13 74 ± 12 100 ± 15* 113 ± 15* 131 ± 13* 150 ± 13* Hyperoxia 72 ± 16 68 ± 15 93 ± 17* 110 ± 18* 126 ± 19* 142 ± 22* MAP (mmHg) Normoxia 88 ± 8 89 ± 10 97 ± 6* 103 ± 7* 108 ± 9* 112 ± 11* Hyperoxia 89 ± 8 91 ± 6 97 ± 8* 99 ± 8* 106 ± 9* 110 9* PETO2  (mmHg) Normoxia 98 ± 13 99 ± 13 94 ± 14 93 ± 6 96 ± 5 100 ± 5 Hyperoxia 96 ± 3* 299 ± 8† 298 ± 5† 297 ± 6† 294 ± 7† 294 ± 6† PETCO2 (mmHg) Normoxia 40 ± 2 40 ± 2 41 ± 2 42 ± 3* 42 ± 3* 41 ± 3 Hyperoxia 40 ± 3* 36 ± 4 ѱ 39 ± 3* ѱ 42 ± 3* ѱ 42 ± 4* ѱ 42 ± 4* ѱ   normocapnia VE  (l.min-1) Normoxia 13.5 ± 1.8* 16.5 ± 3.7‡ 29.6 ± 4.7*‡ 39.7 ± 7.2*‡ 56.3 ± 13.4*‡ - Hyperoxia 13.9 ± 2.2* 18.8 ± 4.8‡ 30.0 ± 6.4*‡ 39.4 ± 7.4*‡ 53.8 ± 13.6*‡ - HR (BPM) Normoxia 73 ± 14 77 ± 13 101 ± 12* 116 ± 133* 133 ± 17* - Hyperoxia 71 ± 18 73 ± 20 97 ± 19* 113 ± 18* 128 ± 19* - MAP (mmHg) Normoxia 88 ± 6.7 89 ± 6.2 96 ± 6.0* 101 ± 8.0* 108 ± 11* - Hyperoxia 89 ± 7.5 91 ± 7.7 99 ± 7.8* 102 ± 9.1* 112 ± 13* - PETO2  (mmHg) Normoxia 95 ± 4.2 99 ± 1.9 97 ± 5.7 97 ± 4.8 94 ± 4.2 - Hyperoxia 96 ± 6.7 298 ± 5.3 298 ± 3.5 299 ± 5.2 310 ± 34 - PETCO2 (mmHg) Normoxia 40 ± 1.6 40 ± 1.7 40 ± 1.8 40 ±1.9‡ 41 ± 2.6‡ - Hyperoxia 39 ± 3.8 39 ± 3.7‡ 39 ± 3.5 39 ± 3.4‡ 40 ± 4.0‡ - VE: Ventilation; HR: heart rate; MAP: mean arterial pressure; PETO2 & PETCO2: partial pressure of arterial oxygen & carbon dioxide; * p < 0.05 from BL2, † p <0.05 from normoxia, ѱ p<0.05 interaction effect between normoxia and hyperoxia, ‡ p <0.05 from poikilocapnia.      ! ! !182Cardio-respiratory measurements: As outlined in Table 6.1, the main goal of controlling PETCO2 was effectively achieved. For example, the progressive elevations in PETCO2 during poikilocapnic normoxic and hyperoxic exercise were prevented during the isocapnic conditions. Likewise, the isocapnic interventions prevented the ~4 mmHg reductions in PETCO2 that were observed at rest during poikilocapnic hyperoxia. As expected, PETO2 was also effectively maintained at hyperoxic levels in the related interventions. During both the normoxic and hyperoxic isocapnic exercise, the changes in PaCO2 and PETCO2 were comparable (i.e., within 1-2 mmHg). Additionally, despite a slightly lower intra-arterial MAP at each intensity, the relative changes in the intra-arterial blood pressure measurements were similar (i.e., within 3-6 mmHg) to the non-invasive estimates of MAP during isocapnic exercise, regardless of inspired FiO2. Both HR and MAP were not influenced by the hyperoxic or isocapnic interventions. Likewise, the progressive elevations during exercise in HR and MAP were similar during exercise between the poikilocapnia and isocapnic interventions.     Figure 6.1.  The percent change in the middle (∆ %MCAv) and (∆ %PCAv) posterior cerebral artery blood flow velocities, internal (∆ %QICA) and vertebral (∆ %QVA) artery blood flows and global cerebral blood flow (∆ % gCBF) during hyperoxia compared with normoxia with (normocapnic) or without (poikilocapnic) PETCO2 controlled at basal values. † signifies differences between normoxia and hyperoxia (p < 0.05).         184Cerebrovascular measurements:  Normoxia and hyperoxic poikilocapnic exercise (Tables 6.1 and 6.2; Fig. 6.1):  All cerebrovascular variables were unchanged following 10 minutes of normal breathing; however, during poikilocapnic hyperoxia, MCAv and PCAv were significantly lower compared with initial baseline (-4.4 ± 1.3 cm.s-1 and -3.0 ± 1.3 cm.s-1, respectively). Incremental poikilocapnic normoxic exercise generated progressive increases in MCAv and PCAv at 20, 40, 60 and 80% WMax. Similarly, QICA was increased at 40, 60 and 80% Wmax, and QVA was increased at 60% WMax (Table 6.2; p<0.05). A similar time course of cerebrovascular changes occurred during the incremental poikilocapnic hyperoxic exercise (Table 6.1; p<0.05). Incremental poikilocapnic normoxic exercise resulted in progressive increases in gCBF from rest during 40-80% Wmax (~ 104 – 138 ml.min-1; p <0.05); poikilocapnic hyperoxic exercise also evoked progressive increases in gCBF from rest during 20-60% Wmax. When compared to normoxic exercise, during hyperoxic poikilocapnic exercise (Fig. 6.1) there were significantly greater relative (5-20%) changes in MCAv, PCAv and QVA at 40, 60 and 80% Wmax (Fig. 6.1), respectively, with no significant difference in the QICA response (p < 0.05). Likewise, the relative increase in gCBF was significantly greater at 60 (15.7 ± 3.9 %) and 80% WMax (12.7 ± 3.9 %) during hyperoxic versus normoxic poikilocapnic exercise (p< 0.05).             185  Table 6.2. Cerebrovascular measurements during poicilocapnic and normocapnic exercise while breathing either normoxia or hyperoxia   Stage Measurement Condition BL1 BL2 20 % 40% 60% 80%   poikilocapnia MCAv (cm.s-1) Normoxia 61 ± 8.4 60 ± 9.2 65 ± 11* 67 ± 12* 70 ± 12* 75 ± 16* Hyperoxia 60 ± 8.4* 55 ± 8.5 61 ± 8.7* 66 ± 14* 69 ± 12* 71 ± 14* CVCiMCA (cm.s-1.mmHg-1) Normoxia 0.71 ± 0.12 0.70 ± 0.11 0.67 ± 0.10 0.66 ± 0.1 0.66 ± 0.1 0.69 ± 0.1 Hyperoxia 0.67 ± 0.12* 0.58 ± 0.09 0.63 ± 0.08 0.67 ± 0.1* 0.65 ± 0.12* 0.64 ± 0.14* QICA (ml.min-1) Normoxia 234 ± 64 232 ± 66 249 ± 76 277 ± 79* 288 ± 80* 279 ± 97* Hyperoxia 226 ± 52 223 ± 53 257 ± 62 282 ± 79* 305 ± 106* 295 ± 81* ICAdiam (cm) Normoxia 0.50 ± 0.06 0.50 ± 0.06 0.50 ± 0.06 0.49 ± 0.06 0.49 ± 0.06 0.47 ± 0.06 Hyperoxia 0.49 ± 0.06 0.48 ± 0.04 0.48 ± 0.06 0.49 ± 0.06 0.49 ± 0.07 0.49 ± 0.06 ICAVel (cm.s-1) Normoxia 40 ± 9.3 39.8 ± 8.7 43.4 ± 9.2* 49.0 ± 10* 50.5 ± 10* 53.2 ± 11* Hyperoxia 39.4 ± 8.1 40.0 ± 7.0 47.8 ± 7.4* 50.2 ± 8.3* 53.2 ± 11* 53.8 ± 13* CVCiICA (ml.min-1.mmHg-1) Normoxia 2.6 ± 0.1 2.6 ± 0.7 2.5 ± 0.7 2.6 ± 0.7 2.6 ± 0.7 2.4 ± 0.8 Hyperoxia 2.5 ± 0.6 2.5 ± 0.6 2.5 ± 0.5 2.8 ± 0.6 2.7 ± 0.7 2.6 ± 0.7 PCAv (cm.s-1) Normoxia 43 ± 6.4 42 ± 6.8 45 ± 7.4* 47 ± 7.4* 48 ± 7.6* 49 ± 6.8* Hyperoxia 42 ± 10* 39 ± 9.7 43 ± 13* 45 ± 13* 48 ± 16* 50 ± 17* CVCiPCA (cm.s-1.mmHg-1) Normoxia 0.52 ± 0.12 0.51 ± 0.12 0.50 ± 0.14 0.49 ± 0.14 0.48 ± 0.13 0.48 ± 0.13 Hyperoxia 0.48 ± 0.14*† 0.42 ± 0.12† 0.45 ± 0.17† 0.47 0.17* 0.46 ± 0.18 0.46 ± 0.18 QVA (ml.min-1) Normoxia 86 ± 31 85 ± 34 87 ± 35 92 ± 38 96 ± 44* 94 ± 38 Hyperoxia 80 ± 28 75 ± 27 82 ± 28 93 ± 33* 102 ± 38* 101 ± 44* VAdiam (cm) Normoxia 0.36 ± 0.7 0.36 ± 0.07 0.36 ± 0.07  0.36 ± 0.07 0.36 ± 0.07 0.35 ± 0.07 Hyperoxia 0.35 ± 0.06 0.34 ± 0.06 0.34 ± 0.06 0.34 ± 0.06 0.35 ± 0.06 0.34 ± 0.06 VAVel (cm.s-1) Normoxia 29 ± 6.2 28 ± 5.6 29 ± 5.4 30 ± 7.0 31 ± 7.2* 33 ± 8.8* Hyperoxia 27 ± 5.2 27 ± 5.8 30 ± 5.7* 33 ± 6.9*† 35 ± 8.8*† 36 ± 11*† CVCiVA (ml.min-1.mmHg-1) Normoxia 1.0 ± 0.4 1.0 ± 0.4 0.9 ± 0.4 0.9 ± 0.4 0.9 ± 0.5 0.9 ± 0.4 Hyperoxia 0.9 ± 0.4*† 0.8 ± 0.3 0.9 ± 0.3 1.0 ± 0.4* 1.0 ± 0.4* 1.0 ± 0.5* gCBF (ml.min-1) Normoxia 640 ± 140 634 ± 146 673 ± 179 738 ± 188* 770 ± 204* 773 ± 256* Hyperoxia 611 ± 109 596 ± 108 677 ± 132 751 ± 190* 814 ± 238* 792 ± 184*   normocapnia MCAv (cm.s-1) Normoxia 59 ± 6.6 59 ± 7.8 61 ± 9.2 65 ± 12 71  ± 16* - Hyperoxia 56 ± 8.9 55 ± 7.9 57 ± 10.6‡ 57 ± 9.8‡        64 ± 15*‡ -                186 Table 6.2. Cerebrovascular measurements during poicilocapnic and normocapnic exercise while breathing either normoxia or hyperoxia CVCiMCA (cm.s-1.mmHg-1) Normoxia 0.67 ± 0.1 0.68 ± 0.1 0.65 ± 0.1* 0.65 ± 0.1* 0.65 ± 0.1* - Hyperoxia 0.64 ± 0.1 0.62 ± 0.1 0.60 ± 0.1 0.57 ± 0.1* 0.59 ± 0.1* - QICA (ml.min-1) Normoxia 241 ± 58 240 ± 58 255 ± 57 269 ± 76* 282 ± 78* - Hyperoxia 229 ± 57 237 ± 52 255 ± 64 262 ± 51*‡ 278 ± 74*‡ - ICAdiam (ml) Normoxia 0.49 ± 0.06 0.49 ± 0.06 0.49 ± 0.07 0.49 ± 0.07 0.48 ± 0.06 - Hyperoxia 0.50 ± 0.06 0.49 ± 0.05 0.48 ± 0.06 0.48 ± 0.06 0.48 ± 0.06 - ICAVel (cm.s-1) Normoxia 42 ± 9.9 42 ± 10 45 ± 10* 47 ± 10* 51 ± 9* - Hyperoxia 40 ± 9.4 42 ± 6.1 46 ± 7.0* 49 ± 7.8* 50 ± 8.3* - CVCiICA Normoxia 2.7 ± 0.7 2.7 ± 0.7 2.6 ± 0.6 2.6 ± 0.7 2.5 ± 2.7 - Hyperoxia 2.5 ± 0.6 2.6 ± 0.6 2.6  0.7 2.5 ± 0.7 2.5 ± 0.7 - PCAv (cm.s-1) Normoxia 42 ± 7.0 41 ± 6.5 43 ± 6.0 46 ± 7.0* 49 ± 6.8* - Hyperoxia 43 ± 11 43 ± 12‡ 44 ± 13 45 ± 13*‡ 50 ± 18*‡ - CVCiPCA (cm.s-1.mmHg-1) Normoxia 0.48 ± 0.07 0.46 ± 0.06 0.44 ± 0.07 0.45 ± 0.07 0.46 ± 0.07 - Hyperoxia 0.48 ± 0.1 0.46 ± 0.1 0.44 ± 0.1 0.43 ± 0.4 0.44 ± 0.1 - QVA (ml.min-1) Normoxia 81 ± 26 80 ± 28 86 ± 36 91 ± 40 95 ± 47* - Hyperoxia 76 ± 25 76 ± 25 82 ± 27 85 ± 34‡ 93 ± 38*‡ - VAdiam (cm) Normoxia 0.35 ± 0.06 0.36 ± 0.07 0.35 ± 0.07 0.35 ± 0.07 0.35 ± 0.07 - Hyperoxia 0.35 ± 0.06 0.35 ± 0.06 0.35 ± 0.06 0.34 ± 0.07 0.34 ± 0.06 - VAVel (cm.s-1) Normoxia 28 ± 5.0 27 ± 5.4 29 ± 7.1 31 ± 7.3* 33 ± 7.2* - Hyperoxia 26 ± 3.6 27 ± 4.1 29 ± 4.6 30 ± 5.0* 33 ± 7.8* - CVCiVA Normoxia 0.93 ± 0.3 0.90 ± 0.3 0.89 ± 0.4 0.90 ± 0.4 0.84 ± 0.4 - Hyperoxia 0.86 ± 0.3 0.84 ± 0.3  0.84 ± 0.3 0.83 ± 0.4 0.82 ± 0.3 - gCBF  (ml.min-1) Normoxia 644 ± 128 641 ± 123 682 ± 124 719 ± 181* 755 ± 214* - Hyperoxia 609 ± 120 626 ± 115‡ 675 ± 148 693 ± 132*‡ 741 ± 180*‡ - ; * p < 0.05 from BL2, † p <0.05 from normoxia, ‡ p <0.05 from poikilocapnia.       187Normoxia and hyperoxic isocapnic exercise (Table 6.2; Fig 6.2):  No differences in any cerebrovascular responses were observed between room air and hyperoxia during resting isocapnia (Fig 6.2). Furthermore, regardless of the FiO2, isocapnic exercise generated an elevated MCAv and QVA at 60% Wmax (10.2 ± 1.6 cm.s-1 and 16.1 ml.min-1 >; respectively) from basal values (p< 0.05) (Table 6.2).  Moreover, PCAv and QICA were elevated at 40 and 60% WMax, respectively (Table 6.2). The gCBF during incremental exercise was also elevated (p<0.05) at 40 (+13%) and 60 % WMax (+20%) similarly in isocapnic normoxia and hyperoxia (Table 6.2; Fig 6.2).  Figure 6.2 illustrates that maintaining isocapnia during normoxic exercise (20-60% Wmax) did not significantly alter the cerebrovascular response to incremental exercise compared with poikilocapnia, except for reducing PCAv at 60% Wmax (p<0.05). Additionally, all vessels and gCBF were significantly reduced during hyperoxic isocapnia compared with poikilocapnia (Fig 6.2; p<0.05)       188    Figure 6.2. Comparing the percent change in the middle (∆ %MCAv) and (∆ %PCAv) posterior cerebral artery blood flow velocities, internal (∆ %QICA) and vertebral (∆ %QVA) artery blood flows and global cerebral blood flow (∆ % gCBF) during normocapnic or poikilocapnic in both normoxia and hyperoxia. ‡ signifies differences between normocapnic or poikilocapnic (p < 0.05).      190 Figure 6.3. Comparisons of the regional intracranial cerebral blood flow velocities (MCAv versus PCAv) and extracranial blood flows (QICA versus QVA), as well as relative velocity and blood flow changes in the proximal intracranial versus extracranial (MCAv versus QICA; PCAv versus QVA) during normocapnic normoxia and hyperoxia. ϕ Signifies significance between vessels (p <0.05).      191 Figure 6.4. Comparisons of the regional intracranial cerebral blood flow velocities (MCAv versus PCAv) and extracranial blood flows (QICA versus QVA), as well as relative velocity and blood flow changes in the proximal intracranial versus extracranial (MCAv versus QICA; PCAv versus QVA) during poikilocapnic normoxia and hyperoxia. ϕ Signifies significance between vessels (p <0.05).       192  Influence of carbon dioxide (Fig 6.5): During normoxic poikilocapnic exercise the relative change in MCAv, QICA, and QVA were positively correlated with the absolute change in PETCO2 (R2 = 0.13, 0.10 and 0.20, respectively [Fig 6.5]).  During hyperoxic poikilocapnic exercise the relative change in MCAv, PCAv, QICA, and QVA were positively correlated with the absolute change in PETCO2 (R2 = 0.32, 0.11, 0.22, 0.22, respectively [Fig 6.5]).  Since PETCO2 was maintained during isocapnia no correlations were ran during these trials.  Isocapnic Hyperpnea (Fig 6.6):  There were no changes in intra-cranial velocities or extra-cranial blood flow during isocapnic hyperpnea.         189   Comparisons between vessels (Table 6.2; Fig 6.3 and Fig 6.4):  There were no relative intra- or extra-cranial differences observed while resting during poikilocapnia and isocapnia in normoxia and hyperoxia (Table 6.2).  However, during normoxic, but not hyperoxic, poikilocapnic exercise, the relative increase in MCAv at 80% WMax was greater (+6.8 ± 1.7 %) compared to the increases in PCAv (p < 0.05) (Fig 6.3). Similarly, during normoxic, but not hyperoxic, poikilocapnic exercise elevations in QVA were significantly lower by 10 - 14 % compared with QICA at 40 and 80 % WMax (Fig 6.3). Additionally, during both normoxic and hyperoxic poikilocapnic exercise the relative increases in QICA were ~10.0 % greater compared with MCAv increases during 40 and 60% WMax, (Table 6.2; Fig 6.3; p<0.05). Except for 60% Wmax during hyperoxia (%∆ QVA equals 21% > than %∆PCAv), no significant differences were observed between the relative QVA and PCAv changes during normoxic and hyperoxic poikilocapnic exercise (Fig 6.3).  There were no differences between any of the intra- or extra-cranial, or regional flows during normoxic or hyperoxic exercise when isocapnia was maintained (Fig 6.4).          193    Figure 6.5. The relationship between the percent change in intracranial velocities (% ∆MCAv and % ∆PCAv) and extracranial flow (% ∆QICA and %∆QVA) with the unit change in the partial pressure of end-tidal carbon dioxide (∆PETCO2) during poikilocapnic normoxic and hyperoxic exercise.      194   Figure 6.6. Comparison between the absolute intracranial cerebral blood flow velocities (MCAv; PCAv) and extra-cranial blood flows (QICA; QVA) during poikilocapnic exercise and isocapnic hyperpnea. λ signifies differences between poikilocapnic exercise and isocapnic hyperpnea (p < 0.05).! ! !1956.3. Discussion There are four novel findings from the current study: 1) The individual CBF responses to exercise are not altered by maintaining isocapnia during normoxic semi-recumbent exercise; 2) hyperoxia heightened the intra- and extra-cranial blood flow responses to exercise, and is primarily mediated via elevations in PETCO2; 3) Subtle differences in the regional (QICA vs QVA) and intracranial- versus extracranial responses to poikilocapnic normoxic (MCAv vs QICA) and hyperoxic (PCAv vs QVA) exercise are no longer present during isocapnia; and 4) isocapnic hyperpnea per se does not alter CBF.    6.3.1. Cerebral blood flow during exercise Normoxia: Traditionally, the CBF response to incremental exercise has been described as being driven primarily by the hypercapnic and hypocapnic consequences of hypo- and hyperventilation during submaximal and maximal exercise, respectively (Hellström & Wahlgren 1993; Linkis et al. 1995; Moraine et al. 1993; Olin et al. 2011; Subudhi et al. 2011). The current findings demonstrate that MCAv increases to the same extent (i.e., ~ 20%) during exercise up to 80%WMax with and without PETCO2 clamped at baseline values (Fig 6.1 and 6.2). Furthermore, the similar response throughout all exercise intensities, regardless of PETCO2, was also observed in both of the proximal neck vessels (QICA and QVA), as well as in the PCAv and gCBF. Thus, contrary to our hypothesis, these findings indicate that the magnitude of the cerebrovascular response to submaximal semi-recumbent normoxic exercise is not necessarily influenced by PETCO2. Since both MAP and cardiac output were similar between conditions, the mechanism(s) elevating ! ! !196CBF are therefore likely reflected to compensatory increases in cerebral metabolism and/or shear stress mediated vasodilation.   Hyperoxia: The effects of hyperoxia on the CBF response are not well known.  Lambertsen et al. (1959) first attempted to address this response in subjects performing constant load exercise during normoxia (FiO2= 0.21) and hyperbaric (2 atm) hyperoxia (FiO2 = 1.0).  Likely because of the small sample size (n=2), absolute workloads, and lack of baseline, hyperoxic exercise did not result in a different absolute gCBF compared with normoxic values despite a significantly elevated PETCO2 (+3.5 mmHg). We have previously observed a significant increase in PCAv, but not MCAv, during exercise in normobaric hyperoxia  (FiO2 = 1.0) compared with normoxic exercise at 40% Wmax (Smith et al. 2012).  In support of these findings, the current results indicated that when controlling for relative exercise intensity the relative increases in intra-cranial velocities and extra-cranial flows during hyperoxia were elevated by (~5 to 20%) compared with normoxia.     In our earlier study, we found a strong and significant relationship (R2=0.8) between the elevations in PETCO2 with PCAv during upright hyperoxic exercise. In the current study, however, despite all of the cerebrovascular variables being linearly related to the change in PETCO2 (Fig 6.5), the strength of the relationships were less (R2 = 0.11 to 0.32) compared with our previous findings. One possible explanation regarding the differences between PETCO2 relationships in these two studies is that upright hyperoxic exercise had a greater PETCO2 increase from basal values when compared to semi-recumbent exercise ! ! !197(e.g., 9 vs 6 mmHg, respectively). Therefore, the postural effect of upright versus recumbent cycling in hyperoxia have likely reduced the PETCO2 response to submaximal exercise; however, posture does not seem to have affected the overall cerebrovascular response to hyperoxic exercise. 6.4. Cerebrovascular response to isocapnic hyperoxic exercise Hyperoxia heightened the cerebrovascular response by ~15% to exercise compared to normoxia (Fig 6.1 and 6.3). When isocapnia was maintained during exercise, the hyperoxic cerebrovascular response was abolished, demonstrating the critical importance of PaCO2 in mediating this response (Fig 6.4). At rest, 1 mmHg elevation in PaCO2 results in a 3-5% increase in CBF (reviewed in Willie et al., 2014). During exercise, however, this reactivity is increased to 4-6% per mmHg elevation in PETCO2 (Rasmussen et al. 2006). Based on these latter findings, the 6-mmHg increase in PETCO2 from baseline values could explain the majority of the 20% greater increase in intra-cranial velocities and extra-cranial flows compared with normoxic exercise.  The abolishment of the observed differences during poikilocapnic hyperoxia further support this finding (Fig 6.4).   Regional, intracranial and extra-cranial vascular responses to exercise: To date only five studies have investigated the regional cerebrovascular response to exercise (Herholz et al. 1987; Sato & Sadamoto 2010; Sato et al. 2011; Smith et al. 2012; Willie et al. 2011b). The first study to investigate regional CBF during exercise, using a Xeno graph (i.e., gamma radiation detection following Xenon injections) reported no differences in the blood flow response between various cortical regions (frontal, precentral, post-! ! !198central, parietal, temporal and occipital) during recumbent cycling exercise at 25 or 100 W (Herholz et al. 1987). Three of the remaining four studies observed larger relative increases in posterior compared with anterior intra-cranial [PCAv vs. MCAv; (Willie et al. 2011b)] velocities and extra-cranial [QVA vs. QICA; (Sato & Sadamoto 2010; Sato et al. 2011)] flows during normoxic exercise. The final study, consistent with the current findings, observed a regional difference in the intra-cranial velocity response that was selective to hyperoxic exercise (i.e., hyperoxia only exacerbated the PCAv response not the MCAv; (Chapter 4; Smith et al. 2012)). Furthermore, we have identified a greater relative increase in extra-cranial flow (QICA) versus intracranial velocity (MCAv) in the anterior circulation during normoxia, and in both the anterior and posterior circulations during hyperoxia. Given that clamping PETCO2 at isocapnia during exercise in both normoxia and hyperoxia abolished any of the observed regional and intra- versus extracranial responses it appears that PaCO2 is primarily responsible for the variation (i.e., regional, intracranial vs extra-cranial and FiO2) in the cerebrovascular response to exercise.  Isocapnic Hyperpnea The observations by Neubauer et al. (1983) indicating an increase in ventral medullary blood flow (~22%) in anesthetized cats during isocapnic hyperpnea were suggested to indicate that increases in V̇E lead to local increases in brain metabolism sufficient to elevated the local blood flow response. Given that no changes were observed in any of the intra- or extra-cranial flows during the isocapnic hyperpnea trial our finding are not consistent to these well-controlled animal data. Further investigations with more ! ! !199localized resolution (i.e., magnetic resolution imaging) is needed to discover if local cortical blood flow in the medulla is altered during isocapnic hyperpnea. 6.4.1. Methodological considerations and limitations Although the current study was performed in a controlled laboratory setting, some limitations are apparent. For instance, because of the difficulty associated with measuring volumetric flow in the extra-cranial vessels during exercise we utilized a recumbent ergometer to minimize potential motion artefacts. Nevertheless, despite the 17 participants we attempted to collect extra-cranial flows in during exercise, we were unable to obtain adequate measures in three subjects. Additionally, because of the difficulties associated with measuring beat-to-beat volumetric flow during exercise, we chose to utilize a protocol that provided sufficient time (i.e., 5 minute stages) to achieve an adequate time window with which to collect the volumetric measures during steady state exercise. Thus our protocol limited our ability to measure volumetric flow during exercise intensities above 80% Wmax. Regardless, the maximal exercise tests performed at the beginning of each trial allowed for accurate determination of the absolute wattages required for controlling the relative intensity.  It has traditionally been thought that the changes in the transcranial Doppler measurements of MCAv were valid indexes of the CBF response to exercise, when compared with gCBF measured using the Kety-Schmidt technique (Hellström & Wahlgren 1993; Jorgensen et al. 1992).  However, only three studies have successfully quantified both the MCAv and QICA responses during exercise (Sato & Sadamoto 2010; Sato et al. 2011; Trangmar et al. 2014), and no studies have compared the PCAv and QVA responses during exercise. The previous studies investigating the MCAv and QICA ! ! !200responses to exercise showed almost identical responses, which are in contrast with the current findings, which observed greater extra-cranial versus intra-cranial responses to incremental exercise in both normoxia and hyperoxia (Fig 6.3). The discrepancies between studies may be a reflection of differences in exercise duration and the use of manual (Sato & Sadamoto 2010; Sato et al. 2011; Trangmar et al. 2014) measures of blood flow rather than our automated approach. Using edge-detection software not only provides a more robust and sensitive assessment of vessels diameter and velocity (Woodman et al. 2001), it limits subjectivity and bias during data analysis. Whether dilation of the MCA occurs during exercise is unknown, although this has been recently reported to occur during modest (>8mmhg) elevations in PETCO2, albeit at rest, using high resolution MRI (Coverdale et al. 2014).     6.5. Summary In conclusion, our findings demonstrate an absence of V̇E influence, per se, and a differential effect of PaCO2 on intra- and extra-cranial blood flow during semi-recumbent exercise that is dependent on the prevailing oxygen level.    !201!Chapter 7. Conclusion !The cerebrovascular response to exercise is regulated through a myriad of direct, indirect and reflexive mechanisms.  The magnitude of this response is primarily related to the specific balance between arterial blood gases (i.e., PaO2 and PaCO2) and metabolism, while the influences of factors such as MAP, CO and neurogenic innervation have on the cerebrovasculature during exercise seems to be less important.  Thus, given the significant capacity for energy consumption of the brain at rest, coupled with the increased metabolism during exercise, a constant supply of oxygen and metabolic nutrients is achieved through the precise regulation of CBF primarily through arterial blood gases and metabolism.  The work presented in the experimental chapters of this thesis (Chapter 4, 5 and 6) demonstrates how alterations in arterial blood gases, both separate and combined, impact on the regulation of CBF during exercise.  The research questions, experiments and primary findings, discussed within this thesis, were driven from the limited available data (as outlined in Chapter 2), and resulted in three comprehensive questions that were addressed: 1) What are the effects of mild hypoxia and hyperoxia on regional CBV during incremental maximal exercise (Chapter 4); 2) What is the influence of severe hypoxia, following partial acclimatization to high altitude, on regional CBV, volumetric CBF and metabolism during exercise (Chapter 5); 3) What are the independent affects of altered ventilation, PaO2 and PaCO2 on regional and global CBF during exercise (Chapter 6). !202!7.1. Overall summary and significance The combined influences of PaO2 and PaCO2 on the regional CBV response to incremental exercise were investigated in Chapter 4.  The intracranial velocities in the MCA and PCA were continuously measured during normoxic, mild hypoxic and hyperoxic incremental exercise to exhaustion.  This study was the first study to assess the anterior and posterior CBV response to incremental exercise using TCD, a technique that allowed for continuous CBV assessment throughout the entire exercise protocol.  The use of TCD provided the necessary temporal resolution to identify a greater absolute but not relative increase in MCAv, when compared with PCAv, during submaximal normoxic, hypoxic and hyperoxic exercise.  In contrast to the initial hypothesis the absolute, but not relative increases, in MCAv were greater than PCAv during normoxic exercise.  The lack of a greater increase in the PCAv, compared with MCAv, during incremental exercise is in contrast with regional extracranial flow differences [i.e., the relative increases in QVA were greater than those in the QICA; [60 vs 13% respectively] Sato et al. (2011)]. In Chapter 4, however, the relative increase in MCAv was similar during normoxic, hypoxic and hyperoxic exercise, whereas an exaggerated PCAv response was identified only during hyperoxic exercise. The heightened PCAv response during hyperoxic exercise was speculated to be the result of a greater rise in PaCO2 from rest compared to normoxia (i.e., 10 vs. 6 mmHg), where as the lack of a heightened MCAv was taken to be indicative of a differential regional sensitivity to PaCO2 during hyperoxic exercise (Smith et al., 2012). This speculation was not supported through correlational observations, however, as no significant relationships between the PCAv and PaCO2 were observed during normoxic, hypoxic or hyperoxic exercise.  However, there was a strong linear relationship (R2=0.80) between the change in MCAv and PaCO2 from rest to 40% WMax !203!in hyperoxia. Likely because of the competing mild hypoxic (FiO2 = 0.16) and consequent hypocapnia stimuli, no difference in the relationship between CBV (MCAv or PCAv) and PaCO2 was observed during hypoxic exercise.  The lack of observable differences between the hypoxic and normoxic CBV exercise response was consistent with our original hypothesis, and explained by the counterbalancing influence of hypoxia (which causes vasodilation) and hypoxic-induced hyperventilation (which results in hypocapnic vasoconstriction).  Contrasting findings have been reported since Siebenmann et al. (2013) first demonstrated that the hypoxic-hypocpanic balance is intact during exercise at high altitude.  Nevertheless, the findings of a heightened regional CBV response during hyperoxic but not hypoxic exercise provided important insight into the regional intracranial CBV sensitivity to PaCO2 during exercise.   These observations were thus crucial in directing the second (Chapter 5) and third (Chapter 6) experimental studies in this thesis.    Ascent to high altitude exposes individuals to environmentally-induced hypoxemia and results in a progressive hyperventilation consequently lowering of PaCO2.  The experimental ascent to 5050 m in Chapter 5 resulted in severe hypoxia (i.e., PaO2 < 50 mmHg) and hypocapnia (i.e., PaCO2 < 25 mmHg) with partial metabolic compensation of the respiratory alkalosis.  The greater vasodilatory and vasoconstrictive influences from the hypoxia and hypocapnia than that observed in Chapter 4, provided the experimental background with which to examine the hypoxic verses hypocapnic influence on regional CBV and CBF during exercise.  This study was the first in the literature to compare the regional cerebrovascular (CBV, CBF and CDO2) as well as the !204!cerebral metabolic response (i.e., oxidative and non-oxidative cerebral fuel utilization) to incremental exercise with similar relative intensities at both sea-level and high altitude.  Additionally, this study investigated the cerebrovascular and metabolic response immediately following the cessation of exercise up to 30 minutes of recovery.  The primary findings from this study were as follows: 1) following partial acclimatization to high altitude, there were no regional differences observed in the cerebrovascular response to exercise.  However, gCBF was elevated compared with the sea-level response during and following exercise, thus facilitating the maintenance of CDO2.  Despite a maintained CDO2 at altitude, the CMRO2 was elevated during submaximal exercise and recovery compared with sea-level. However, the relative increase in CMRO2 at altitude was attenuated compared with the increase observed at sea-level.  2) Given that the CDO2 remained in excess of the CMRO2 throughout exercise to the same extent at high altitude and sea-level, it was noteworthy that the brain had a greater contribution from non-oxidative metabolism (i.e., lower OCI) during rest and submaximal exercise.    The findings from Chapter 5 also indicated a greater reduction in OCI and a greater arterial lactate production during exercise with similar relative intensities at sea-level compared with high altitude. In contrast, observations made during exercise with similar absolute workloads indicate that OCI at high altitude was reduced compared with than sea-level despite a greater increase in arterial lactate at the same absolute workload (see figure 5.7). Together, these findings suggest that the increase in arterial lactate availability is a key factor behind the falling OCI during exercise under conditions of chronic hypoxemia.  The findings from this Chapter demonstrated that following partial !205!acclimatization (i.e., 4-6 days) to high altitude, CBF is elevated in order to maintain CDO2 despite profound hypocapnia.  It should be noted that Siebenmann et al. (2013), following 24 hours at a more modest altitude (3454 m), also observed a significantly heightened MCAv response during isocapnic hypoxic exercise compared with hypoxic hypocapnic exercise.  It is unknown however, if these findings indicate that during acute high altitude exposure, hypocapnia influences the CBV response to hypoxic exercise since no comparisons were made between altitude and sea-level exercise.   The final experimental chapter (Chapter 6) revisited and extend the experimental findings from Chapter 4. The goal was to clarify if regional intracranial velocities versus extra-cranial flow responses differed during normoxic and hyperoxic exercise. Additionally, the involvement of PaCO2 in establishing the magnitude of the global and regional cerebrovascular responses to normoxic and hyperoxic exercise was examined. Furthermore, based on early animal studies that showed that ventilation itself may elevated posterior CBF (Neubauer et al., 1983), this possibility was examined for first time in humans. There were four novel findings from Chapter 6: 1) The individual CBF responses to exercise were not altered by maintaining isocapnia during normoxic semi-recumbent exercise; 2) Hyperoxia heightened the intra- and extra-cranial blood flow responses to exercise, and is primarily mediated via elevations in CO2; 3) Subtle differences in the regional (QICA vs QVA) and intracranial- versus extracranial responses to poikilocapnic normoxic (MCAv vs QICA) and hyperoxic (PCAv vs QVA) exercise are no longer present during isocapnia; and 4) Isocapnic hyperpnea per se does not alter CBF. Previous studies have attempted to quantify the role that PaCO2 plays in the !206!regulating intracranial velocity (i.e., MCAv) response to normoxic and hypoxic exercise by elevating PaCO2 using end-tidal forcing (Olin et al., 2011; Siebenmann et al., 2013; Subudhi et al., 2011).  The collective findings from these three studies indicate that increasing PaCO2 during normoxic and hypoxic exercise elevates the MCAv response, similar to rest. However, the findings from Chapter 6 are the first to demonstrate that mitigating the rise in PaCO2 observed during poikilocapnic exercise does little to alter the global cerebrovascular response to normoxic semi-recumbent exercise. Nevertheless, maintaining isocapnia during normoxic and hyperoxic exercise abolishes the differential regional and intracranial velocity versus extra-cranial flow responses observed during poikilocapnic normoxic and hyperoxic exercise.  The fact that isocapnic hyperpnea did not alter intracranial velocity or extra-cranial blood flow is in contrast to the earlier study that reported elevations in ventral medullary blood flow in cats during isocapnic hyperpnea (Neubauer et al., 1983).  This finding was speculated to implicate that metabolic activity in in cortical tissue responsible for VE was driving the increased CBF.  Since no observable change in the intra- or extra-cranial flows during the isocapnic hyperpnea trial may be the result of insufficient resolution required to consistently observe the changes observed in these well-controlled animal studies. Alternatively, the divergent findings may reflect species differences in the cat verses the human.   Although it was previously known that the cerebrovascular response to exercise is sensitive to environmental and experimental manipulations of arterial blood gases [e.g., (Imray et al., 2005; Rasmussen et al., 2010a; Subudhi et al., 2011)], the cumulative findings from the three experimental chapters of this thesis demonstrate that the !207!magnitude and consistency of the global, intracranial and extra-cranial vascular responses to normoxic, hypoxic and hyperoxic exercise is dependent on the following:  1) The balance between PaO2 and PaCO2 (and likely pH, as has been established at rest e.g., Willie et al., 2015); 2) The specific sensitivity of the individual vessels to changes in PaO2 and PaCO2; and 3) The methodological assessment (i.e., transcranial versus vascular Doppler ultrasound) used to determine the cerebrovascular response during exercise with manipulated arterial blood gases.  The combined findings from Chapters 4 and 5 indicate that the cerebrovascular response to hypoxia, similar to the resting response, occurs only after a severe enough drop in PaO2 has occurred.  Unfortunately, the experimental findings do not allow for clear identification of this threshold during exercise.  At least during rest, hypoxic cerebral vasodilation occurs only after PaO2 is reduced below 50 mmHg under conditions of isocapnic (Willie et al., 2012).  Thus, the elevation in gCBF observed during severe hypoxia serves to offset the drop in PaO2  (an hence CaO2) and maintains CDO2 (Ainslie & Subudhi, 2014).  Similarly, following partial acclimatization to high altitude, the progressive reductions in PaO2 during incremental exercise potentially facilitate the elevated gCBF compared with sea-level exercise. More importantly, likely because of partial metabolic compensations for the respiratory alkalosis (Willie et al 2015), the increases in gCBF during exercise at high altitude occur despite an opposing effect of PaCO2. Unfortunately, although unlikely to be altered, no measures of CDO2 were obtained during the mild hypoxic exercise in Chapter 4; thus, during mild hypoxic exercise it is difficult to conclude if a hypocapnic vasoconstriction opposed any expected hypoxic vasodilation. In contrast, the findings from Chapter 4 and 6 demonstrated that the heightened cerebrovascular response to !208!exercise in hyperoxia compared with normoxia is directly related to the greater absolute increase in PaCO2.  Finally, 12 studies have investigated the intracranial velocity response to exercise [see; (Figure! 2.7)], while only three studies have investigated the extra-cranial flow response (Sato & Sadamoto, 2010; Sato et al., 2011; Trangmar et al., 2014).  When caliper based manual diameter analysis methods were used, these studies indicated that no observable differences between the intracranial and extra-cranial flows (Sato & Sadamoto, 2010; Sato et al., 2011; Trangmar et al., 2014), at least in the anterior circulation (i.e., MCAv versus QICA).  The larger relative increases in extra-cranial flows compared with intracranial velocity during normoxic and hyperoxic exercise observed in Chapter 6 is in contrast to these previous studies.  However, in Chapter 6, the use of edge-detection software not only provides a more robust and sensitive assessment of vessels diameter and velocity (Woodman et al., 2001), it also limits subjectivity and bias during data analysis further validating the contrasting results. Whether the differential response in extra-cranial flow versus intracranial velocity is a result of dilation of the MCA and PCA during exercise is unknown.  It is worth noting, however, that a dilation of the MCA has been recently reported to occur during modest elevations in PETCO2, albeit at rest, using high resolution MRI (Coverdale et al., 2014).  7.2. Strengths and limitations The greatest strengths of the research within this thesis were employing methods that allowed for the combined and individual assessment of PaO2 and PaCO2 on the regional intracranial and extra-cranial vascular response to exercise. Additionally, great care was taken to ensure that all comparisons were made during similar relative exercise intensities (e.g., via repeat maximal exercise testing under different PO2 conditions, etc.).  By !209!utilizing this approach, the experiments within this thesis systematically demonstrated the important regulatory balance involved in the cerebrovascular response to exercise with environmental and experimental manipulation of PaO2 and PaCO2. Moreover, the methodological approach - which utilized both TCD and vascular ultrasound – permitted the differential regional CBV versus CBF responses during exercise demonstrates the need in future studies for volumetric vascular assessment both the anterior and posterior CBF during exercise. Additionally, the addition of the cerebral metabolic observations in Chapter 5 were crucial in demonstrating that maintaining oxygen delivery does not mitigate the increase in non-oxidative cerebral metabolism during exercise. This finding, in contrast to the early theories that suggested cerebral metabolism was primarily oxidative in nature (Gjedde, 2001), indicates that the neural activation during exercise has a profound increase in anaerobic metabolism.  The use of the specialized end-tidal forcing system, utilized in Chapter 6, allowed for the manipulation of PaCO2 without confounding elevations in breathing resistance found in other end-tidal forcing systems used during exercise (Olin et al., 2011; Subudhi et al., 2011).    The greatest imitations associated with this thesis are four-fold: 1) the utilization of TCD in Chapter 4 as the only index of the regional cerebrovascular response to normoxic, hypoxic and hyperoxic exercise. Likewise, in Chapter 5, gCBF during exercise at sea-level and high altitude was estimated via the utilization of the relative intracranial velocity changes. Since there is potential for exercise or hypoxia, or both, to induce intracranial vessel diameter changes (Willie et al., 2015; Ainslie & Hoiland, 2014; Coverdale et al., 2014; Verbree et al., 2014), this approach potentially underestimated the !210!global and regional responses given the heightened extra-cranial flow versus intracranial velocity response; 2) the utilization of PETCO2 in Chapter 4 without any confirmation using direct assessment of arterial blood gases to confirm that the PaCO2 response was adequately represented by the PETCO2 response; 3) only using unilateral ICA and VA assessments in Chapter 5 and 6 may not have accounted for contralateral asymmetries, potentially introducing a 20% difference in baseline flows; and 4) in Chapters 4, 5 and 6  a different cycling body position was utilized in each study (i.e., upright, supine and semi recumbent cycling) which may have influenced not only the cerebrovascular response but also the cardiorespiratory (i.e., heart rate, cardiac output, MAP and arterial blood gases) responses to incremental exercise.   Chapter 6 addressed some of these mentioned limitations by utilizing both TCD and vascular ultrasound throughout the entire exercise protocol; however, the CBF response to hypoxic exercise may need to be re-visited while assessing both intracranial and extra-cranial vascular responses.  This is an important question considering the findings from recent studies demonstrating significant changes in resting MCA diameter during hypoxemia [reviewed in: (Willie et al., 2014a; Wilson et al., 2011)] and during changes in PaCO2 challenges (Willie et al., 2015; Ainslie & Hoiland, 2014; Coverdale et al., 2014; Verbree et al., 2014). No study to date has examined if the PCA diameter is similarly altered during physiological stress.  Whether a technique such as transcranial color-coded duplex ultrasound (Wilson et al., 2011) has the sensitivity to identify changes in MCA diameter during exercise, remains to be established.  !211!During Chapter 4, PETCO2 measures were solely used to estimate the PaCO2 response during normoxic, hypoxic and hyperoxic exercise. This is a limitation during exercise as it has been reported that the arterial and alveolar gradients widens (Jones et al., 1979), and hence the use of PETCO2 alone leads to an overestimation of the PaCO2.  Nevertheless, the limitation was overcome in Chapter 5 where an elevation in gCBF during exercise at sea-level and high altitude was found and was based on direct measurement of arterial blood gases. Moreover, the confirmation of a similar PaCO2 and PETCO2 as well as CBV responses during normoxic and hyperoxic exercise in Chapter 6 further supports the findings in Chapter 4.  The extracranial blood flow assessments were achieved using unilateral QICA and QVA measurements; therefore, an assumption was made regarding the symmetrical flow in the contralateral vessels.  Schöning et al. (1994) identified a 20% disparity between contralateral VA blood flows using vascular ultrasound. More recently, however, using 3-tesla phase contrast MRI no regional disparities between contralateral flows in the extra-cranial vasculature [left versus right ICA and VA’s, respectively (Zarrinkoob et al. (2015)].  There is also no evidence that the relative blood flow responsiveness to exercise, with or without arterial blood gas manipulation, would be different in contralateral vessels with resting asymmetrical flows.  The exercise protocol in each of the experimental chapters was heavily reliant on ensuring that similar relative exercise intensities were used to compare the cerebrovascular response to exercise in normoxia, hypoxia and hyperoxia.  However, !212!each Chapter utilized different body position to perform the cycling exercise protocol.  The lack of consistency of the cycling position in each study is related to the addition of vascular ultrasound in Chapters 5 and 6, which required the participants to remain stable to limit any head and neck motion; thus, cycling in the upright position was not possible.  The impact of posture on CBF during exercise has not been well investigated, however, no difference in the cerebrovascular response to exercise has been observed in the primary studies discussed [see section 2.3, (Figure 2.7)] investigating the cerebrovascular response to exercise in three distinctly different positions; upright (Brugniaux et al., 2014; Moraine et al., 1993; Subudhi et al., 2008), supine (Imray et al., 2005), and recumbent (Fisher et al., 2013; Hellström & Wahlgren, 1993; Jorgensen et al., 1992b; Trangmar et al., 2014). However, as discussed previously in this section, Sato et al. (2011) observed a heightened response in the posterior circulation during incremental recumbent exercise compared with our upright findings.  In Chapter 6, no differences were found in the anterior and posterior circulation during maximal incremental exercise. The reasons for the discrepancy in posterior cerebral blood response to incremental recumbent exercise in this thesis compared to Sato and coworkers [Sato et al. (2011)] remains to be established.   7.1  Future Considerations The immediate future considerations stemming from this research should attempt to address the limitations presented in the above sections of this Chapter.  Using transcranial color-coded duplex sonography and a specialized wall tracking software, experiments are needed to quantify the intracranial flow response in the MCA and comparing it to the !213!extra-cranial flow response in the ICA during normoxic incremental exercise.  This approach, combining volumetric intracranial and extracranial flow comparisons, may further improve our understanding of how the cerebrovascular response is regulated at various locations throughout the cerebrovascular tree.  As the transcranial color-coded duplex technique continues to improve, the ultimate goal will be to investigate the regional intracranial flow responses and compare those to the regional extra-cranial flow responses to exercise in a myriad of environmental (temperature-stress, altitude, breath-hold diving, etc), and clinical settings (i.e., Dementia, Parkinson’s disease, multiple sclerosis, heart failure, spinal cord injuries, traumatic brain injury, etc.).   The overall findings from this study have led to the formation of three distinct future cerebrovascular research questions: 1) Given the already underway volumetric intracranial and extracranial responses to exercise using transcranial color coded ultrasound, a comparison study utilizing a higher resolution technique (i.e., positron emission tomography or phase contrast MRI) would help to index the cerebrovascular response throughout the entire cerebrovascular tree; 2) Identification of how the cerebrovasulature has evolved in natives to high altitude environments would provide insight in the role of genetic adapation (Simonson et al., 2014; Jansen & Basnyat, 2011). For instance, no study to date has compared the cerebrovascular response to exercise in high altitude natives (i.e., Andean vs. Tibetan natives). Thus, it would be of interest to investigate if the cerebrovascular response to exercise differs in these populations, and if any regional disparities, or sensitivities to altered arterial blood gases are present. 3) Since the findings of Seibenmann and colleagues (Siebenmann et al., 2013) have !214!demonstrated that maintaining PaCO2 at sea-level values during exercise at high altitude (thereby mitigating the hypoxic hypocapnia) heightened the CBV response to incremental exercise, it would be of interest to observe the regional and volumetric comparisons during isocapnic high altitude exercise. Moreover, at both sea level and high altitude, comparisons of cerebrovascular sensitivities to changes in arterial blood gases and cerebral oxygen delivery during exercise would provide useful information regarding the role PaCO2 (and pH) plays in influencing the maintenance of CDO2 during exercise.    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