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Medicine & Science in Sports & Exercise:
doi: 10.1249/MSS.0000000000000178
Basic Sciences

Dynamic Heterogeneity of Exercising Muscle Blood Flow and O2 Utilization


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1Applied Physiology Laboratory, Kobe Design University, JAPAN; 2Division of Respiratory and Critical Care Physiology and Medicine, Los Angeles Biomedical Research Institute at Harbor–UCLA Medical Center, and School of Biomedical Sciences, University of Leeds, Leeds, UNITED KINGDOM; 3Turku PET Centre and Research Centre of Applied and Preventive Cardiovascular Medicine, University of Turku and Turku University Hospital, Turku, FINLAND; Division of Experimental Cardiology, Thoraxcenter, Erasmus MC, University Medical Center Rotterdam, Rotterdam, THE NETHERLANDS; and 4Departments of Kinesiology and Anatomy and Physiology, Kansas State University, Manhattan, KS

Address for correspondence: Shunsaku Koga, Ph.D., Applied Physiology Laboratory, Kobe Design University, 8-1-1 Gakuennishi-machi, Nishi-ku, Kobe, 651-2196, Japan; E-mail:

Submitted for publication December 2012.

Accepted for publication September 2013.

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ABSTRACT: Resolving the bases for different physiological functioning or exercise performance within a population is dependent on our understanding of control mechanisms. For example, when most young healthy individuals run or cycle at moderate intensities, oxygen uptake (V˙O2) kinetics are rapid and the amplitude of the V˙O2 response is not constrained by O2 delivery. For this to occur, muscle O2 delivery (i.e., blood flow × arterial O2 concentration) must be coordinated superbly with muscle O2 requirements (V˙O2), the efficacy of which may differ among muscles and distinct fiber types. When the O2 transport system succumbs to the predations of aging or disease (emphysema, heart failure, and type 2 diabetes), muscle O2 delivery and O2 delivery–V˙O2 matching and, therefore, muscle contractile function become impaired. This forces greater influence of the upstream O2 transport pathway on muscle aerobic energy production, and the O2 delivery–V˙O2 relationship(s) assumes increased importance. This review is the first of its kind to bring a broad range of available techniques, mostly state of the art, including computer modeling, radiolabeled microspheres, positron emission tomography, magnetic resonance imaging, near-infrared spectroscopy, and phosphorescence quenching to resolve the O2 delivery–V˙O2 relationships and inherent heterogeneities at the whole body, interorgan, muscular, intramuscular, and microvascular/myocyte levels. Emphasis is placed on the following: 1) intact humans and animals as these provide the platform essential for framing and interpreting subsequent investigations, 2) contemporary findings using novel technological approaches to elucidate O2 delivery–V˙O2 heterogeneities in humans, and 3) future directions for investigating how normal physiological responses can be explained by O2 delivery–V˙O2 heterogeneities and the impact of aging/disease on these processes.

Historically, the interpretation of whole-body physiological responses such as cardiac output, pulmonary gas exchange, or fractional O2 extraction (arterial-mixed venous O2 concentration difference) tacitly presumed homogeneity across body compartments (e.g., [80,98–100]). Progress in the physiological understanding of control processes and their spatial dynamics, driven, in part, through empirical findings and technological advances, reveals that the whole-body response conceals a remarkable heterogeneity. Specifically, the human body’s physiology (and pathophysiology) is governed by ∼1028 atoms reacting and interacting as dictated by their own particular chemistry and surrounding milieu. Within this complexity, the level(s) at which determination of heterogeneity becomes scientifically meaningful and provides information about systems control is dependent on the physiological questions posed as tempered by the technology available (see Table 1).

Table 1
Table 1
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This review investigates heterogeneity within the O2 transport system from mouth to muscle mitochondria and addresses the global question as to how body O2 delivery (cardiac output × arterial O2 concentration) is distributed and matched to the requirement for O2 utilization (V˙O2) at the level of individual tissues during exercise. Effective matching distributes O2 among and within muscles (muscle O2 delivery) according to their needs and facilitates high rates of mitochondrial adenosine triphosphate production, making sustained exercise possible. Ineffective matching may slow V˙O2 kinetics and force reliance on substrate-level phosphorylation, rapid expense of finite intramuscular glycogen stores, and accelerate exhaustion. In a relatively fit, healthy young adult from rest to exercise (e.g., cycling or running), cardiac output may increase from ∼5 to more than 25 L·min−1 raising body O2 delivery proportionally from 1 to >5 L·min−1 (80). When that O2 is directed effectively among and within the exercising skeletal muscles, 80%–90% of the arterial O2 concentration is extracted, V˙O2 achieves its maximal value (i.e., V˙O2max) of >4 L·min−1, and effluent venous blood returning to the lungs has an O2 concentration of only 2–4 mL O2 per 100 mL. Determining how muscle O2 delivery and V˙O2 are matched and the heterogeneity associated with those processes yields crucial information germane to O2 transport systems control in health and dysfunction in diseases such as heart failure and diabetes. The balance between muscle O2 delivery and V˙O2 is crucial because this sets the microvascular or capillary PO2 and thus the upstream driving pressure for blood–myocyte O2 flux as well as influencing metabolic control via the impact on intramyocyte PO2 and V˙O2 kinetics. Elegant experimental designs and technological advances have afforded unprecedented capabilities to temporally and spatially resolve muscle O2 delivery and V˙O2 and their matching and dynamics at rest and during exercise. However, without further insights, the interpretation of muscle O2 delivery and V˙O2 (and microvascular PO2) is challenging. Specifically, it is straightforward that a low O2 delivery–V˙O2 ratio will result in a high fractional O2 extraction and, consequently, a microvascular PO2 so low that blood–myocyte O2 flux (and both muscle and pulmonary V˙O2 kinetics) will be impaired compromising mitochondrial control. However, to what degree a higher O2 delivery–V˙O2 ratio (and microvascular PO2) is beneficial in terms of optimizing V˙O2 kinetics and metabolic control in a specific region has not been determined. Moreover, that advantage must be considered with respect to potentially impoverishing (i.e., reducing the O2 delivery–V˙O2 ratio) in another spatially distinct muscle region. The resolution of these problems will come from determining the spatial and temporal heterogeneity existent in healthy muscle and the impact of conditions such as priming exercise, exercise training, and aging as well as chronic disease(s).

This review argues strongly for opening the “black box,” which historically has been used—with some predictive success—through either necessity or convenience, to explain pulmonary and muscle V˙O2 (cf. [7] and [34]). Herein, recent advances in technology and approaches to understanding heterogeneity and O2 flux control are sequenced according to the levels(s) at which muscle O2 delivery and V˙O2 heterogeneity are addressed. In the Dynamic Heterogeneity of Exercising Muscle V˙O2 section, a top-down approach is followed (see Fig. 1) where heterogeneity is considered with respect to O2 delivery and V˙O2 among active (i.e., recruited skeletal muscles) and inactive (rest-of-body) compartments and how such behavior is reflected in the pulmonary V˙O2 dynamics. Whereas distinct heterogeneities across limbs (i.e., arms vs legs) are not addressed specifically the impact of such is implicit within the Dynamic Heterogeneity of Exercising Muscle V˙O2 section and the reader is referred to the work of Wray and Richardson (102), which details important cross-limb vascular heterogeneities in young and older subjects across training states. In the Heterogeneity of Muscle Blood Flow and Microvascular V˙O2 in Animals section, animal investigations using techniques not possible in humans (i.e., radiolabeled microspheres, phosphorescence quenching) unveil how cardiac output can be distributed among and within muscles in the running rat as a function of muscle recruitment, oxidative capacity, and fiber type. Oxygen delivery–V˙O2 matching during electrically stimulated contractions of distinct rat muscles comprised of predominantly slow- or fast-twitch fibers assess the capacity for flexibility of the O2 delivery–V˙O2 relationship. An important cautionary note here is that fiber type and oxidative stratification within and among rodent muscles is generally far more distinct than that within or among human populations (cf. 4, 5 with 22, 50), and this undoubtedly leads to differences in energetic control (e.g., [31]). It is, however, pertinent that there exists a substantial heterogeneity of fiber types across human locomotor muscles (e.g., soleus 88% Type I vs rectus femoris [RF] 36%), as a function of depth within individual muscles (deeper muscle regions >Type I) (50) and across elite athletic populations (i.e., Type I%, sprinters <30%, distance runners >70%). Thus, although findings in animals cannot tell us what happens in humans, they demonstrate what is physiologically possible and, as such, help frame human experiments and their interpretation. This is the case for investigations of human muscle using positron emission tomography (PET), near-infrared spectroscopy (NIRS), and magnetic resonance imaging (MRI) technology, which are addressed in the final two major sections (i.e., the Muscle Blood Flow Heterogeneity as Assessed by PET section and the Spatial Heterogeneity of Quadriceps Muscle Deoxygenation Kinetics section) of this review. Focus is maintained on the physiological data obtained from each technique placing onus on the reader to refer to the original papers for technical details.

Figure 1
Figure 1
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As schematized in Figure 1, overall heterogeneities of O2 delivery–V˙O2 matching will be assessed spatially within the whole body (∼102 kg) down several orders of magnitude to the muscle microvascular level (10−5 kg). Although a greater resolution of O2 delivery–V˙O2 matching at the level of the individual RBC within a given capillary would doubtless be of great interest, this is currently infeasible in contracting skeletal muscle. Moreover, it is probable that the dominant control mechanisms for such (at least in health) are located upstream of the capillary, and the investigation of these processes is facilitated best by studying O2 delivery–V˙O2 matching within multiple capillary and fiber units, the greatest resolution investigated herein. Throughout this review, the reader is asked to keep in mind that heterogeneities, with respect to O2 delivery, V˙O2, and their matching, at all levels may result from differences in motor unit or muscle recruitment as well as inherent heterogeneities in vascular and/or metabolic control. Techniques for assessing muscle recruitment in vivo are generally crude (e.g., surface EMG) and/or may entail multiple assumptions (e.g., glycogen depletion, blood flow, and V˙O2). The dangers of not accounting for muscle recruitment patterns, for instance, across the human quadriceps muscles, when interpreting O2 delivery–V˙O2 relationships, have been emphasized by the work of Chin et al. (16) and are discussed in the Spatial Heterogeneity of Quadriceps Muscle Deoxygenation Kinetics section. Moreover, it should be appreciated that anatomically, microvascular units (i.e., terminal arteriole and dependent capillaries) are not spatially synchronized with distinct motor units and their fibers (23). One consequence of this arrangement is that an individual capillary may abut two or more fibers, each with a very different V˙O2, creating broad extremities of micro-mismatch of O2 delivery and V˙O2 within contracting muscle that are hidden from the resolution of present technology.

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Blood flow distribution among vascular beds

During the steady state of muscular exercise, pulmonary V˙O2 reflects muscle V˙O2 because the variable bodily O2 capacitances remain stable (principally, the O2 content of the lung and the venous blood). This external manifestation of internal cellular respiration provides a noninvasive window on cellular energy exchange from pulmonary measurements (98). During the exercise transient, however, the dynamics and distribution of changes in cardiac output in relation to muscular energy demands contribute to maintaining O2 pressures for diffusion across the capillary-to-myocyte interfaces. In addition, the dynamics and distribution of cardiac output also play an important role in determining the relationship between muscle and pulmonary V˙O2 during the exercise transient (7,12,25,89).

In healthy humans, arterial O2 concentration (CaO2) is relatively constant across the exercise transient (6,34,80,81), and therefore, the key determinant of the kinetics of venous O2 concentration (CvO2) is the ratio of muscle blood flow to V˙O2 (29,99):

Equation (Uncited)
Equation (Uncited)
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An exercise-induced rise (or transient rise) in muscle V˙O2/blood flow can reduce muscle capillary PO2 (reflected in CvO2) and peripheral O2 exchange. As such, the transient dynamics and distribution of blood flow–V˙O2 are key determinants of the ability to maintain muscular oxidative energy provision and external power production during exercise.

This principle holds for all levels of physiological organization, and on transition to exercise, there are substantial changes in blood flow–V˙O2 ratios distributed between bodily tissues, among active or quiescent muscles, and within individual muscles engaged in exercise (5,57,62,67,77). As a consequence, changes in regional O2 delivery are rarely, if ever, “matched” to changes in local V˙O2 at the onset of exercise because in many vascular beds, there is a change in CvO2 draining the tissues (27). The aim of blood flow control during exercise can, therefore, be considered to minimize the disturbance and distribution of CvO2 in the various vascular beds of the body.

The first level of organization to consider in influencing the dynamic heterogeneity of exercising muscle blood flow and O2 utilization is the dynamics and distribution of cardiac output among vascular beds. This can be usefully simplified for exercise by considering the distribution of flows between two compartments represented by active skeletal muscle (muscle blood flow) and the rest of the body (here termed body blood flow) (7,12). Oxygen is extracted from blood flowing into both of these compartments, and the venous effluent flows down a venous capacitance to where it is mixed in the central circulation. In this system, the key determinants of the temporal profile of CvO2 for a given work rate are: the ratio of the preexercise muscle blood flow to body blood flow, the venous volume of the two compartments, the “O2 cost” of the exercise (Δ V˙O2/Δ work rate) in each compartment (noting that overall O2 cost is relatively immutable among subjects but reflects the combination of an increase in muscle V˙O2 and the potential for a reduction in rest-of-body V˙O2 [12]), the magnitude of the increase in muscle blood flow during exercise relative to muscle V˙O2 (Δ blood flow/Δ V˙O2), and the ratio of muscle blood flow to V˙O2 kinetics [τ blood flow/τ V˙O2; where τ is the time constant of the response] (7,12,89).

For example, in considering the adjustments of these variables at the onset of moderate-intensity exercise in health, muscle blood flow tends to increase more rapidly than muscle V˙O2 (34,51). This might suggest that O2 delivery is in excess of requirement during the transient and, therefore, not limiting to local muscle V˙O2 or overall pulmonary V˙O2 kinetics (80). However, and despite the apparently favorable τ for muscle blood flow (τ muscle blood flow < τV˙O2), the absolute blood flow/V˙O2 ratio falls to a new steady state during the transient, meaning that CvO2 and muscle capillary/microvascular PO2 also fall. The reason for this is revealed in the analysis of the shape of the muscle blood flow versus the V˙O2 relationship during the exercise transition: a positive blood flow intercept necessitating a CvO2 fall (e.g., [27,99]). This provides the potential for regional O2 diffusion limitation during the exercise transient, even where muscle blood flow kinetics respond faster than V˙O2 kinetics (28,29,99,100).

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The kinetic association of muscle and lung V˙O2

Muscle blood flow kinetics also contribute to dissociating phase II pulmonary τV˙O2 from muscle τV˙O2, complicating the interpretation of intramuscular events from pulmonary V˙O2 kinetics. An example of this influence of blood flow-to-V˙O2 heterogeneity during exercise is the evidence from Grassi et al. (34) showing that the V˙O2 from the nonactive muscle tissues reduces slightly on transition from unloaded to moderate-intensity cycling. In this case, a reduction in blood flow in the rest of the body and its associated increase in CvO2 each contribute to distorting muscle τV˙O2 as it transitions to pulmonary τV˙O2. Dynamic adjustments in the flow-weighted mixing of venous blood draining the two vascular compartments may, therefore, speed or slow muscle V˙O2 kinetic expression at the lung.

The computational model of Barstow et al. (7) (also see [12,25,89]) is useful in this regard. This demonstrates that the kinetics of O2 exchange at the muscle and lung can be similar under the particular conditions of cardiac output kinetics and distributions expected for healthy young humans. Equally, it is demonstrated using this modeling approach that muscle τV˙O2 and pulmonary τV˙O2 can be different under conditions of heterogeneous muscle blood flow and/or rest-of-body blood flow dynamics and distribution.

There are limited available measurements that directly compare muscle V˙O2 and phase II pulmonary V˙O2 kinetics. The only data for large muscle-mass exercise in humans are derived from six healthy participants during cycle ergometry presented in Grassi et al. (34). These data suggest that the mean value for pulmonary τV˙O2 (32 s) is within approximately ±10% of muscle τV˙O2 (36 s), as originally predicted by Barstow et al. (7). Review and reanalysis of the original data from Grassi et al. (34) show that although on average pulmonary V˙O2 kinetics are slightly faster than that for muscle V˙O2, within-participant pulmonary phase II V˙O2 kinetics are (with the exclusion of one outlying value) between 2% and 35% faster than muscle V˙O2 (12). This suggests that kinetic dissociations between muscle and lung are possible in healthy subjects during moderate-intensity cycling exercise.

This notion is in contrast to the common perception that pulmonary phase II τV˙O2 provides a good reflection of τV˙O2 to within approximately ±10%. Figure 2 shows all the available data from human volunteers comparing on-transient pulmonary phase II τV˙O2 (by breath-by-breath gas exchange) and muscle τV˙O2 (by direct Fick across the exercising limb) during cycling exercise (34) and two-legged (59) or single-legged (61) knee-extension exercise. Although the ±10% estimate was achieved in the group as a whole (mean difference is −2.5 s, or −6% of muscle τV˙O2; Figures 2A and 2B), the range of coherence among the 25 individual measurements was extremely wide (−34 to +18 s, or −65% to +72% of τ for muscle V˙O2). In 15 of the 25 measurements, the modeled pulmonary τV˙O2 lay outside ±10% of muscle τV˙O2. It is interesting to note that during constant power exercise, the combined effects of the heterogeneity and kinetics of muscle and body blood flow in the transient can result in either positive or negative kinetic distortions in pulmonary relative to muscle τV˙O2 (7,12,89). In other words, the exercise-induced fall in CvO2 need not necessarily slow pulmonary versus muscle V˙O2 kinetics (15) but may also speed them (Figs. 2A and 2B).

Figure 2
Figure 2
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The magnitude and the direction of kinetic distortions between muscle and pulmonary V˙O2 are predicted to be dependent on a wide range of variables but importantly include exercise-independent variables such as the venous volume (7,25) and the preexercise fraction of cardiac output directed to the active limbs (i.e., muscle blood flow/cardiac output [12,13]). Naturally, exercise-related variables also contribute to these distortions, such as the exercise-induced increase in O2 delivery relative to O2 uptake (Δ muscle blood flow/Δ muscle V˙O2 [90]), the kinetic ratio (τ muscle blood flow/τ muscle O2 [89]), and any exercise-induced reduction in blood flow to the remainder of the body (Δ body blood flow [12]). This means that the relationships between pulmonary and muscle τV˙O2 may be different between exercise onset and cessation (61), in conditions where preexercise muscle blood flow is affected such as after prior exercise (13) or heart failure (90) or during small muscle-mass exercise modalities where relative perfusion (Δ muscle blood flow/Δ muscle V˙O2) is high (51). Therefore, although the most sensitive contributor to pulmonary phase II τV˙O2 in health appears to be muscle phosphate metabolism (31,35,91), the heterogeneity and dynamics of cardiac output among and within tissues are key the determinants of both muscle and lung V˙O2 dynamics on transition to exercise.

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Despite the longstanding recognition that human and animal skeletal muscles are heterogeneous with respect to function, fiber types (4,5,22,50) and recruitment profiles, oxidative and glycolytic enzymes, myoglobin content (color), vascularity, and vascular control, the detection of blood flow differences within and among human and animal muscles was largely intractable. Thus, techniques developed in the late 19th and throughout the 20th centuries including the Fick principle (equation 1), the indocyanine green technique for cardiac output and plethysmography, 133Xe washout, thermodilution, and ultrasound for limb and/or muscle blood flow, each required assumptions regarding the distribution of that blood flow. Furthermore, limitations imposed by the specific technique often detract from performance of unencumbered voluntary exercise. To circumvent these issues, Laughlin and Armstrong used radioactive microspheres of a size (i.e., 15 μm) designed to lodge within the microcirculation at a level approaching the smallest arterioles (i.e., A4s) (4,5,63). The quantitation of muscle blood flow in the selected sample is determined by the comparison of radioactivity in that sample versus that in a reference sample collected at a known flow rate (i.e., 0.25 mL·min−1) typically by sampling arterial blood from the caudal (tail) artery while microspheres are infused (∼500,000–600,000) in proximity to the aortic arch. This technique, although restricted to research animals and requiring a terminal preparation, has the following advantages: 1) muscle blood flow can be measured during voluntary exercise such as treadmill running; 2) blood flow can be measured in muscles and muscle portions down to ∼50 mg; 3) depending on the isotopes available, multiple (three or more) measurements may be made in a single animal without impairing physiological function; 4) agreement of blood flow between bilateral structures (i.e., left and right kidneys and/or muscles) to within ±10%–15% provides confidence that neither microsphere clumping nor streaming occurred allowing a high signal-to-noise ratio; 5) judicious selection of animal model and muscles permits powerful insights into the control of muscle blood flow and vascular function and the impact of fiber type and oxidative/glycolytic capacity on that control (Table 2); and 6) it is applicable to multiple species (e.g., rats, hamsters, dogs, pigs, and horses). Disadvantages include the following: 1) not being suitable for humans or animal survival studies; 2) tissues become radioactive, and although this is in minimal amounts, it requires careful treatment and tissue disposal; colorimetric microspheres avoid this problem but may lack sufficient resolution for small samples; 3) the requirement for two arterial catheters may complicate implementation in small animals (e.g., mice); and 4) measurements require approximation of blood flow steady state, and therefore, this technique is unsuitable for dynamic/non-steady-state conditions.

Table 2
Table 2
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Heterogeneity of muscle blood flow as a function of muscle fiber type

Traditionally, the presumption was that the homogeneity of muscle blood flow within and among different muscles was the ideal situation and that the heterogeneity of flow therefore represented a mismatch between muscle O2 delivery and V˙O2. Today, it is recognized that different muscle fibers and fiber types may have a wide range of metabolic (oxidative) potentials and different O2 demands based, in part, on their recruitment and contractile performance under any given situation. Thus, having the flexibility to distribute O2 spatially and temporally according to O2 requirements represents a degree of freedom that may improve muscle O2 delivery and V˙O2 matching and metabolic regulation.

Laughlin and Armstrong (4,5,63) used radiolabeled microspheres to resolve blood flow differences within and among muscles of different fiber types at rest and progressively up to 105 m·min−1 (i.e., ≫V˙O2max) in running rats. These investigations revealed, for the first time, that 1) blood flow could exceed 300–400 mL per 100 g·min−1 (not determined in humans until Richardson et al., in 1993 [87]). 2) There existed ∼10-fold differences in blood flow between discrete regions (highly oxidative deep red vs superficial white) in the gastrocnemius muscle that persisted even at maximal running speeds when, presumably, both regions were highly recruited. 3) On the basis of blood flow, it was possible to document muscle recruitment as a function of running speed and demonstrate that, as one might suspect, fast twitch, less oxidative (Type IIb/d/x) muscles/muscle portions were recruited at faster running speeds. Piiper et al. (77) addressed blood flow heterogeneity within the electrically stimulated dog gastrocnemius-plantaris preparation using radiolabeled microspheres and discovered that, even within a muscle with a fairly spatially homogeneous fiber-type distribution (more akin to human muscles), there existed considerable spatial and temporal blood flow heterogeneities that were present during overall steady-state conditions (64,77). These authors cautioned that the lack of consideration of these heterogeneities would invalidate then current O2 supply analyses and O2 transport models. Indeed, the estimation of whole body or muscle O2 diffusing capacity presumes the homogeneity of blood flow (and muscle O2 delivery–V˙O2) (88,94).

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Heterogeneity of vascular control

The control of blood flow and vascular smooth muscle is a complex and multifaceted process that may be impacted by exercise mode, intensity, and duration as well as by the animal/human under observation (age, health, fitness, exercise history, environment, etc.) (17). Notwithstanding these considerations, the knowledge of substantial differences in blood flow among fiber types has revealed discrete fiber-type differences in vascular control mechanisms that help explain the disparate vascular responses documented earlier. Specifically, nitric oxide (NO)–mediated vasodilation is more important in muscles or muscle regions comprised of highly oxidative fibers (i.e., I, IIa, e.g., soleus, red gastrocnemius) (Fig. 3, top) (49,65), whereas those comprised of low oxidative fibers (IIb/d/x, e.g., white gastrocnemius) evince greater α1-mediated vasoconstrictor responsiveness (Fig. 3, bottom, ref. 8).

Figure 3
Figure 3
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Although the above-mentioned evidence argues strongly for a fiber-type-oriented control of vascular function, there are obvious examples where oxidative capacity per se or specialized function may assume an overriding importance. Specifically, as seen in Table 2, the diaphragm has a very similar fiber-type composition to the spinotrapezius muscle, and yet the diaphragm is three times more oxidative (21). During exercise designed specifically to recruit the spinotrapezius muscle (i.e., downhill running [55]), this muscle only achieves a modest fraction (i.e., 1/7th) of that blood flow possible in the diaphragm (cf. 55 and 82). With respect to the particular case of the diaphragm, Aacker and Laughlin (2) reported that the diaphragm 2A arterioles vasodilated in response to approximately physiological concentrations of acetyl choline (as did 2As from the white and red gastrocnemius portions), whereas the white gastrocnemius and diaphragm also responded to adenosine but the red gastrocnemius did not. The diaphragm 2A arterioles are considerably less sensitive to α1-mediated vasoconstriction than their counterparts from the white or red gastrocnemius (1). Interestingly, the costal diaphragm during chemically induced hyperpnea and the red gastrocnemius during high-speed running (96 m·min−1, ≫V˙O2max) sustain similar and extraordinarily high blood flows approaching 600 mL per 100 g·min−1 (82). Collectively, these data support that vasomotor control can be modulated as a function of fiber type and/or oxidative capacity but, as the special case of the diaphragm shows, for muscles that are critical to life and to sustaining the O2 transport pathway, extraordinary emphasis may be placed on maximizing vasodilatory sensitivity and minimizing vasoconstriction. Indeed, these responses are likely fundamental to raising diaphragm microvascular PO2 to promoting blood–myocyte O2 flux and permitting a tight metabolic regulation that reduces substrate-level phosphorylation and permits conservation of glycogen reserves (33,83).

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Misconceptions and missed-perceptions arising from whole hindlimb blood flow measurements

Where technical limitations preclude the assessment of the distribution of, for example, limb blood flow among and within different muscles, the ability to discriminate the impact of experimental or pathological effects may be compromised. This problem erodes the capacity to derive mechanistic insights from the measurements and, in the extreme, may lead to incorrect conclusions. Two examples of such are the effects of exercise training and aging on blood flow. Specifically, Armstrong and Laughlin (4) trained by exercise a cohort of rats on a motor-driven treadmill and reported that when running at 30 m·min−1, total hindlimb blood flow was not different from that in untrained rats (i.e., untrained, 89 ± 7; trained, 86 ± 5 mL per 100 g·min−1; P > 0.05). However, discrimination among muscles revealed a pronounced redistribution of that limb blood flow such that blood flow increased (∼25%) to muscles/muscle parts composed of SO (Type I) and FOG (Type IIa) was unchanged in FOG + FG (Type IIa/d/x) and decreased ∼50% in predominantly FG muscles/muscle parts. Similarly, Musch et al. (74) found no difference in total hindlimb blood flow in old rats (27–29 months, approximately equivalent to 70–80-yr-old humans) running up a 5% grade at 20 m·min−1 compared with their young adult counterparts (6–8 months) (i.e., young, 124 ± 7, old, 137 ± 12 mL per 100 g·min−1, P > 0.05). In marked contrast to the effects of training presented previously, aging significantly redistributed the available blood flow away from SO and FOG muscles toward FG muscles. Although the mechanistic bases for these effects are likely complex and involve multiple levels of vasomotor control as well as possible differences in muscle fiber recruitment profiles, it is evident that altered blood flow (and therefore O2 delivery), in-and-of itself, alters muscle contractile performance (18). Consequently, contractile function in the SO and FOG muscles would be expected to be improved by increased blood flow after exercise training (4) and impaired in aged muscles, thereby helping to explain the improved (exercise training) and compromised (aged) exercise tolerance in these populations.

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Matching O2 delivery to V˙O2 across fiber types

As mentioned earlier, it is not muscle blood flow and its distribution in separatum that is important so much as how that muscle blood flow is matched to the V˙O2 of different muscles and muscle parts. In considering the close-to-linear relationship between cardiac output and V˙O2 across the whole body or limb, the following equation is derived:

Equation (Uncited)
Equation (Uncited)
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where intercept I = 5–6 L·min−1 and slope S = 5–6, and V˙O2 is measured at the mouth or across the exercising limb(s); the assumption has been that this relationship holds for most muscles recruited (80). If this is indeed the case, it would be expected that microvascular PO2 would be similar across muscles and muscle fiber types. However, Behnke et al. (11) and McDonough et al. (66) demonstrated that the kinetic profile of microvascular PO2 and its absolute level during contractions was very different in the soleus (SO) compared with either the peroneal (FOG/FG) or gastrocnemius (white, FG, medial, and FOG/FG). As demonstrated in Figure 4 (top panel), microvascular PO2 fell much faster and to a far lower level in FG + FOG versus SO muscles. This behavior reflects that these FG + FOG muscles rely to a far greater extent on increased fractional O2 extraction as opposed to elevated O2 delivery per se to support the oxidative requirements of higher work rates. This contrasting behavior is depicted graphically in the “Wagner” diagrams (Fig. 4, bottom panels), where the soleus muscle increases V˙O2 by elevating perfusive O2 conductance (O2 delivery) and diffusive O2 conductance by 31% (Fig. 4, bottom left). In contrast, the white gastrocnemius elevated O2 delivery only 18% compared with a 60% increase of diffusing capacity (Fig. 4, bottom right). The mechanistic bases for this behavior emerge from a pronounced difference in the blood flow intercept (I in equation 2) rather than slope S (27). Intriguingly, this demonstrates that the control of blood flow as related to V˙O2, in so much as this relationship dictates microvascular PO2 (and thus O2 flux and intracellular PO2), may influence the metabolic response to contractions. Thus, the site of fiber(s) metabolic regulation may, to a certain extent, be located proximal to the myocyte.

Figure 4
Figure 4
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Research techniques using radiolabeled microspheres, phosphorescence quenching, and also muscle intravital microscopy necessitate the use of animal in place of human models. As such, these techniques permit a degree of resolution of muscle blood flow and O2 delivery–V˙O2 matching not currently possible in humans. Although findings in animals cannot tell us what happens in humans, in a given situation, they demonstrate what is physiologically possible. This is powerful because it helps frame human experiments and interpret the findings mechanistically. Here, it is crucial to appreciate that not only is there a substantial heterogeneity of fiber types across human locomotor muscles (e.g., soleus 88% Type I vs RF 36%) but also with respect to depth within individual muscles (deeper muscle regions >Type I) (50) and among individuals as exposed most clearly by the comparison of accomplished distance runners with sprint athletes (i.e., sprinters <30% vs distance runners >70% Type I). For instance, as seen earlier for the effects of training and also aging on muscle blood flow during submaximal exercise, the finding of a major fiber-type-specific redistribution belies the intransigence of bulk (whole hindlimb) blood flow and offers important insights into the mechanisms for increased exercise tolerance with training and compromise with aging. In addition to unveiling the dangers of trying to interpret muscle blood flow regulation in heterogeneous tissues from single values, the consideration of how disease processes impact muscle blood flow heterogeneity and especially muscle O2 delivery–V˙O2 matching in animal and human muscles may help to resolve important components of dysfunction and aid in the development of combative therapeutic countermeasures. For instance, there are defined shifts toward a greater Type I muscle fiber-type profile with endurance-type training (e.g., [95]) and the obverse with diseases such as chronic heart failure (79,97), peripheral arterial disease and diabetes (75), and possibly aging (e.g., [60]). In and of itself, this would be expected to lead to a faster and more substantial fall in microvascular PO2, thereby reducing the O2 pressure head driving blood–myocyte O2 flux (10,65–68,76,101), which may lead to slower muscle V˙O2 kinetics and a greater fall in [creatine phosphate] and elevated free [adenosine diphosphate] (ref. [67]). Moreover, there may be a within-fiber-type effect that is more pronounced within Type I muscles, for example, in chronic heart failure (9). As mentioned previously, this is also expected to lead to greater muscle O2 delivery–muscle V˙O2 mismatch, lower PO2intramyocyte, and exacerbation of fatigue-related intramyocyte perturbations, all contributing to the increased fatigability of these states.

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Studying muscle blood flow distribution and heterogeneity in humans has been challenging. Attempts to do so have used PET or MRI (3,86,92,103) during small muscle mass exercise such as one leg knee extension (3,40–46,48,52–54,62). When PET is being used, 15O-H2O radiowater tracer, the autoradiographic method, and a one-compartment model have been applied to calculate blood flow voxel-by-voxel and portrayed as parametric blood flow images (92) (Fig. 5). The method has been validated against the radiolabeled microsphere technique in dogs in vivo, which demonstrated high accuracy in measuring regional muscle blood flow (30).

Figure 5
Figure 5
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PET facilitates blood flow measurement in any organ or tissue (e.g., [40,41,47]). Common utilization of the one-leg knee extensor exercise model has focused attention on the four heads of the quadriceps femoris muscle (Fig. 5), specifically, the vastus intermedius muscle (nearest to the bone) and the three superficial muscles, RF, vastus medialis (VM), and vastus lateralis (VL) muscles. In addition, other parts of the leg, such as the calf, and tissues such as adipose tissue, bone, and skin have been evaluated (40,41). As an index of blood flow heterogeneity (relative dispersion) within the muscles, the coefficient of variation of the voxel values of the defined regions are calculated as CV = SD / mean × 100%. Blood flow heterogeneity can be resolved down to voxel sizes of 2.6 × 2.6 × 2.4 mm, and thus, blood flow is measured in sample volumes of 16 mm3 (44). Heterogeneity among the quadriceps femoris muscle is calculated as previously mentioned, but instead of voxel values, the coefficient of variation of the separate blood flow values of its four heads is used. Thus, PET can precisely evaluate spatial blood flow heterogeneity, but as the frame sampling frequency is usually always >5 s and conditions and results represent steady-state situations, addressing the temporal heterogeneities of blood flow with high resolution in humans requires other methods such as Doppler ultrasound (84).

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Human muscle blood flow heterogeneity at rest and during exercise

One of the most consistent findings regarding blood flow distribution in the thigh musculature, the most heavily assessed limb area in human studies, is that blood flow is often highest in the vastus intermedius muscle compared with the other three superficial muscles of the quadriceps femoris muscle (e.g., [43], Fig. 5). This muscle is located deep within a muscle group and is in an anatomical position to resist gravity and is thus “designed” and responsible for body posture maintenance. It is generally regarded to consist mostly of Type I muscle fibers being highly oxidative and rich in capillaries, making it ideal for repetitive low-intensity muscle work. Therefore, it is natural that the highest blood flow is generally observed in this muscle, at least during low- to moderate-intensity exercise. However, the fact that O2 delivery (and also muscle V˙O2) is the highest in this muscle even at rest (i.e., not standing/moving) when the muscle is quiescent suggests, intriguingly, that the inherent metabolism of highly oxidative muscle (fibers) is greater than that of less oxidative muscles, comprised predominantly of Type II glycolytic fibers. This phenomenon raises questions regarding whether the differing degree of muscle fiber-type recruitment, or these inherent characteristics, represent the driving force controlling blood flow distribution and its changes among and within muscles in response to exercise.

Blood flow heterogeneity in the whole knee-extensor muscle group decreases with increasing workload (44): an effect that can be explained primarily by the decreased variability in mean blood flow values of the individual quadriceps femoris muscle with the increasing exercise intensity resulting disproportionately from a larger blood flow increase in VL muscle than that in the other muscles (toward the values observed in the three other muscles). This could reflect that VL muscle is recruited proportionally more in this exercise model when intensity is increased. Interestingly, VL muscle is also the only individual quadriceps femoris muscle in which heterogeneity decreases from the lowest to the highest exercise intensity. It has previously been shown that when exercise intensity is increased, blood flow is directed to newly recruited muscle fibers rather than to fibers already engaged in exercise (85), and this is the most likely reason for the decreased blood flow heterogeneity observed solely in VL muscle as well as for the decreased variability among the quadriceps femoris muscles. Moreover, it is pertinent that the hyperemia and blood flow distribution induced by drug infusion may not be similar to that induced by exercise, although mean blood flow can be similar among muscles (43). The current evidence suggests that the often-observed exercise-induced changes in blood flow heterogeneity probably reflect true changes in blood flow linked to muscle fiber recruitment and increased blood flow within defined vascular units (16,43,44,78).

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Matching of muscle blood flow to V˙O2 at rest and during exercise in humans

To assess the coupling of muscle blood flow and V˙O2, these variables must be assessed independently. One powerful aspect of PET is that it permits direct measurement of blood flow, O2 extraction, and V˙O2 in separatum in skeletal muscle using inhaled [15O]-O2 tracer. The most suitable approach to measure muscle O2 extraction and V˙O2 at rest is the steady-state method (68) because, when inhaled as a bolus, tissue time activity curves remain stable (initial rise followed by steady state) even after 5–6 min of inhalation because of the relatively low V˙O2 (46). From a general physiological perspective, this finding supports that when O2 is extracted from the blood, it first binds to myoglobin rather than being consumed directly by the muscle. The steady-state method has revealed that when measured directly from thigh musculature, resting muscle O2 extraction approaches 60% (68). Thus, it is two to three times greater than is usually obtained from the determinations of femoral artery and mixed venous samples (20%–25%), meaning that O2 extraction is much lower in skin, adipose tissue, and bone than that in muscle itself. Moreover, although muscle V˙O2 is increased for a period after exhaustive exercise (the so-called excess postexercise O2 consumption), fractional O2 extraction is reduced, reflecting that blood flow decreases more slowly than V˙O2 (28,68). This raises the likelihood that sustained the elevation of blood flow (and O2 delivery) postexercise, while raising microvascular and intramyocyte PO2, also subserves key functions of heat (40) and metabolite removal.

Direct PET determinations confirm that fractional O2 extraction is enhanced in endurance-trained athletes compared with untrained subjects during exercise (54). Lower blood flow heterogeneity, potentially longer red blood cell (RBC) capillary transit times, overall improved vascular control, and increased muscle O2 diffusing capacity are thought to contribute to this finding (52,54). However, when blood flow and V˙O2 are examined at the individual muscle level, their relationship evinces substantial variability (53). Yet matching appears to be better in endurance athletes than that in untrained subjects (53). Indeed, in untrained subjects, muscle blood flow heterogeneity correlates positively with fractional O2 extraction (arterio-venous sampling over the limb) only at rest, but not during exercise (43). Moreover, blood flow heterogeneity does not correlate with the excess muscle V˙O2 (analogous to the V˙O2 slow component [80]) during high-intensity exercise (62). In addition, when Richardson et al. (86) investigated the coupling of muscle blood flow (with a resolution of 0.25–0.35 cm3, image acquisition every 5–6 s) and V˙O2 (1–1.5 cm3, 10 min) by MRI, they found that matching was far from ideal during submaximal exercise. These findings may be partially explained by the fact that, anatomically, microvascular units do not closely approximate muscle motor units (23). Consequently, to ensure blood flow to contracting muscle fibers during exercise, some vascular units (i.e., those abutting noncontracting nonrecruited muscle fibers) may be relatively overperfused. It also appears that this “luxurious” blood flow in relation to O2 demand may be especially prominent in untrained healthy subjects performing small muscle mass exercise (51). One potential benefit of this situation is that the high O2 delivery–V˙O2 ratio will elevate microvascular PO2 and, consequently, intramyocyte PO2, thereby enhancing metabolic control. Obviously, having the greatest microvascular PO2 possible in those capillaries in close proximity to the working muscle fibers would be expected to better facilitate this process.

In contrast to healthy individuals, patients with congestive heart failure have a low (and limiting) cardiac output, which is distributed according to pathophysiological constraints, such as preventing a catastrophic fall in blood pressure rather than regulating muscle blood flow and its distribution as in health. Patients with congestive heart failure may have high fractional O2 extractions, not because there is a superior matching of muscle O2 delivery–V˙O2 or a high O2 diffusing capacity but rather because muscle O2 delivery is very low relative to muscle V˙O2 requirements (24). In contrast to endurance training where blood flow distribution to highly oxidative fibers (muscles) may be improved (see previous section), aging redistributes available blood flow toward more fast glycolytic muscles at the expense of their more oxidative counterparts, at least in rats (74). It is worth noting that, as introduced in the Dynamic Heterogeneity of Exercising Muscle V˙O2 section, during maximal exercise, individuals with a higher V˙O2max demonstrate superior fractional O2 extractions according to the approximation (99):

Equation (Uncited)
Equation (Uncited)
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where Δ CaO2–CvO2 is arterial–mixed venous O2 extraction (mL per 100 mL) and V˙O2 is V˙O2max in liters per minute. Thus, Δ CaO2–CvO2 increases as a hyperbolic function of V˙O2max (i.e., 13.3, 15, 16, and 16.7 mL per 100 mL for V˙O2max values of 2, 3, 4, and 5 L·min−1, respectively). The degree to which this is facilitated by reduced heterogeneity of O2 delivery–V˙O2 in the exercising muscles rather than improved diffusing capacity, for example, is unknown.

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Regulatory aspects of blood flow and its heterogeneity in humans

There are many, especially regulatory, aspects of blood flow heterogeneity, in addition to those identified earlier, that require further investigation. For instance, the differing degrees of α-adrenergic regulation and NO synthase contribution across different muscle fiber types demonstrated in experimental animals (8,49) is not well explored in humans. Regarding α-adrenergic control, one indication for the possible differences in regulation among different human muscles stems from the finding that blood flow is consistently higher, and because perfusion pressure is similar in all muscles, resistance lower in the knee extensor muscles that are known to be more oxidative. This may be due to different α-adrenergic tone in different muscles as demonstrated in rats (8). However, a recent study with direct intra-arterial drug infusions of α-adrenergic agonist and antagonist drugs did not confirm this hypothesis in humans (48). Moreover, although it is evident from human and animal studies that NO plays a major role in regulating muscle blood flow at rest, human knee extensor studies suggest that NO is not as important during exercise in humans versus animals (32,46). In fact, the finding that NO synthesis inhibition reduces blood flow at rest, but not during exercise paradoxically, suggests that NO inhibition increases the absolute hyperemic response of exercise (32,46), making the comparison to animals about its relevance in fiber-type specific vasodilation challenging. However, this conclusion is tempered by the fact that a far more complete NO synthase blockade is possible in animals than humans. Finally, as previously mentioned, muscles in humans are not as defined with respect to solely oxidative or glycolytic fibers as clearly as seen in animals (Table 2), which suggests that human muscle-specific differences are not as pronounced and easily detectable as shown in animals. In addition to these regulatory aspects, it would also be crucial in the future to separate inherent vascular/metabolic regulatory differences from those resulting from contrasting patterns of muscle activation/recruitment.

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In summary, human studies indicate a marked heterogeneity among and within muscles with respect to blood flow, O2 delivery, and V˙O2. However, before parallels can be drawn to the animal data, heterogeneity due to varying recruitment patterns must be assessed carefully. Once this is done, it is likely that the less extreme stratification or “clumping” of fiber types in humans will mean that these differences are less pronounced than found in animals. Notwithstanding this, the regulatory aspects of muscle-specific blood flow and their applicability to animal findings remain largely uncharacterized in humans, presenting the opportunity for mechanistically valuable PET and MRI investigations in health and disease.

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Dynamic matching of muscle microvascular O2 delivery to V˙O2 in exercising humans

It remains a matter of enduring controversy whether the speed of muscle V˙O2 kinetics reflects sluggishness in O2 delivery to the muscle or whether intramuscular limitations such as a microvascular O2 delivery–V˙O2 mismatch or oxidative enzyme inertia limit the adaptation of muscle oxidative energy production at exercise onset (reviewed and discussed in 34,37,72,80,89). Current thinking suggests that in healthy adult humans, the primary component of pulmonary V˙O2 kinetics (approximate analog of muscle V˙O2, see the Dynamic Heterogeneity of Exercising Muscle V˙O2 section) does not appear to be regulated by “bulk” O2 delivery at the onset of moderate-intensity large muscle mass (e.g., cycling) exercise in an upright position (80). However, the investigation of the relative matching of O2 delivery–V˙O2 within and among muscles is crucial for resolving the mechanistic bases for vascular and metabolic control at the onset of exercise. In this regard, NIRS-derived muscle deoxygenation (i.e., the increase in deoxygenated hemoglobin and myoglobin; [deoxy(Hb + Mb)]) reflects the O2 delivery–V˙O2 balance (56,57). The recent development of multichannel time-resolved NIRS enables continuous measurement of absolute and dynamic changes in muscle deoxygenation and therefore eliminates the potential influence of unknown optical path length, absorption, and scattering coefficients on muscle deoxygenation (58). The estimation of the tissue volume interrogated by NIRS is complex (particularly the dimensions of the coronal plane when optodes are placed along the sagittal axis). However, the NIRS method reflects changes in Hb and Mb chromophores ∼1.5–2.0 cm below the skin surface in a volume approximating 3–4 cm3 (the depth of the measured area is typically assumed to be approximately half of the distance between the emitter and the receiver optodes). The time resolutions of NIRS measurements are ∼0.5–2.0 s.

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Spatial heterogeneity of muscle deoxygenation kinetics during exercise

The primary component kinetics of muscle deoxy(Hb + Mb) reflecting increased O2 extraction is spatially heterogeneous. We found that the degree of dynamic heterogeneity in muscle deoxygenation (O2 delivery/V˙O2) is not associated with any systematic variation of the pulmonary phase II V˙O2 (thus muscle V˙O2, but also see the Dynamic Heterogeneity of Exercising Muscle V˙O2 section on this issue) profile at the onset of cycling exercise (57,58,93). However, caution is required to interpret the following findings (57). 1) With only a few studies conducted, the number of measurements is limited, which may cause a greater chance of statistical error. 2) The multichannel NIRS allows the investigation of a limited volume of the superficial muscle. Thus, it may be difficult to find the precise relation for the overall kinetics of the muscle V˙O2 and the metabolic and microvascular heterogeneities associated with skeletal muscle fiber type and fiber-type recruitment. Therefore, the definitive impact of different profiles of deoxygenation on the whole limb and individual muscle V˙O2 kinetics must await development of more powerful and comprehensive technologies.

Whereas blood flow dynamics in the active skeletal muscle microcirculation differs from that in larger conduit arteries (39), it remains unclear exactly how microvascular blood flow is distributed after the onset of exercise. Because the muscle pump increases blood flow (phase I) within a muscle without regard for the metabolic requirements of the individual fibers or motor units, a microvascular mismatching of O2 delivery with respect to V˙O2 will occur in some intramuscular regions, that is, hyperperfusion in areas of the muscle that are inactive, which is reflected as the deoxy(Hb + Mb) time delay (57,93). This behavior is significantly reduced by priming exercise (19,20,36,38). As exercise continues, a negative feedback control of local vascular responses progresses toward a better matching of muscle O2 delivery/V˙O2 (17,80). However, mismatching of exercising muscle O2 delivery/V˙O2 is still greater than at rest, reflecting the admixture of a greater proportion of microvascular units adjacent to very active (high V˙O2) muscle fibers with very low microvascular PO2 and other units that perfuse nonrecruited muscle fibers (lower fractional O2 extraction and higher microvascular PO2).

In the locomotor muscles of rats, there exists a considerable heterogeneity of blood flow among muscles at a given whole-body metabolic rate during running (8,27,63,74). These effects may well be present in human studies, although one might expect this effect to be less during cycling, where there is a reduced opportunity for different muscle recruitment strategies than during running (58). Further, with the mosaic of different fiber types found in most human muscles (vs clumping/stratification in certain animal muscles), there should be no such extreme dominance of one fiber type over another as seen in the rat. Irrespective of fiber type, however, the O2 delivery–V˙O2 matching is the important criterion as this sets the blood–myocyte O2 driving pressure (i.e., microvascular PO2) and, via its effects on intramyocyte O2 pressures, impacts directly on metabolic regulation, the contractile machinery, and the fatigue process (67).

Recent findings of a near-sigmoidal profile of increase in VL muscle deoxy(Hb + Mb) during a ramp or incremental cycle exercise suggest that the relationship between muscle O2 delivery and V˙O2 varies across the different exercise intensities (e.g., [26]). In different muscles of the quadriceps (RF, VL, and VM), the profiles of muscle deoxygenation during cycle ramp exercise are each well described by a near-sigmoid function (Fig. 6) (16). However, differences exist in muscle deoxygenation among muscle groups, where a rightward shift (i.e., delayed to higher work rates and pulmonary V˙O2) of deoxy(Hb + Mb) is observed in the RF muscle compared with VL and VM. Concurrent measurement of muscle activation by surface electromyography revealed that this deoxy(Hb + Mb) response of RF is related to a lower muscle activation/recruitment during incremental cycling exercise.

Figure 6
Figure 6
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The shallow slope of the near-sigmoidal deoxy(Hb + Mb) profile during light exercise (26) may be reflective of early recruitment of muscle fibers (presumably slow-twitch type I) that have better matching and maintenance of O2 delivery and V˙O2 than fibers recruited later in the exercise (presumably type II that exhibit a lower potential for blood flow increases and lower capillarity). As activation of RF was very low, at least in the moderate domain, the recruited fiber-type profile is likely to contain a greater proportion of highly vascularized slow twitch muscle fibers, which may constitute one mechanistic basis for the rightward shift of the deoxy(Hb + Mb) response relative to VL and VM. As work rate continues to increase during incremental exercise, the steeper slope of deoxy(Hb + Mb) during moderate exercise may represent greater O2 extraction and thus an increasingly lower O2 delivery–V˙O2 ratio as muscle fiber recruitment patterns shift from predominantly slow-twitch to fast-twitch muscle fibers (cf. 66). Therefore, the rightward shift of the deoxy(Hb + Mb) response in RF may demonstrate a delayed recruitment of fast-twitch muscle fibers. The plateau of deoxy(Hb + Mb) at the end of exhaustive exercise reflects a matching between the rate of increase in O2 delivery and V˙O2, where V˙O2 appears to be dependent on O2 delivery, as fractional O2 extraction reaches its apogee. The alternative interpretation is that O2 delivery becomes sufficient to maintain CvO2, which of course is expected at higher absolute rates of O2 delivery and V˙O2 (because of the intercept in the blood flow–V˙O2 relationship; see the Blood flow distribution among vascular beds section [27,99]). But even in this case, a linear blood flow–V˙O2 relationship would predict some (albeit small) decline in CvO2 and, therefore, deoxy(Hb + Mb) as V˙O2 nears V˙O2max.

This important observation exemplifies that O2 delivery–V˙O2 heterogeneity among different muscles at different work intensities does not necessarily represent a different O2 delivery at a given absolute V˙O2 because of differences in metabolic demand (V˙O2) and/or recruitment. In other words, the metabolic demand of different muscles must be accounted to discern between a fundamental alteration of the O2 delivery/V˙O2 relationship (such as is found between fast and slow twitch muscles in the rat, see the Heterogeneity of Muscle Blood Flow and Microvascular V˙O2 in Animals section) and different O2 delivery/V˙O2 ratios resulting from differences in recruitment/metabolic rate per se (regardless of whether it is in a different muscle or the same muscle).

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Effects of altered O2 delivery conditions on spatial heterogeneity of muscle deoxygenation kinetics

Previous heavy exercise may alter muscle O2 delivery and help elucidate the mechanisms controlling muscle V˙O2 kinetics after the onset of subsequent heavy or moderate exercise (36,37,70; rev. 80). The mechanistic bases for the changes (where present) in pulmonary V˙O2 kinetics induced by prior heavy exercise on subsequent moderate or heavy exercise presumably involve increased muscle V˙O2 and/or increased O2 delivery mediated by an accentuated vasodilatation (as supported by either reduced or unchanged ratio between deoxy(Hb + Mb) and pulmonary V˙O2 in the face of faster pulmonary V˙O2 kinetics) and/or a right shift in the oxyhemoglobin dissociation curve (36–38,80). Whether these O2 delivery-related factors in preference to reduced mitochondrial oxidative enzyme inertia provide the motive force for those cases where faster pulmonary (and presumably muscle V˙O2) kinetics are found remains to be determined.

Although intracellular mechanisms remain the foremost putative factors controlling the adjustment of muscle V˙O2 kinetics during the exercise on transient, for pulmonary τV˙O2 values greater than ∼20 s, the rate of adjustment of the pulmonary phase II V˙O2 is also constrained by the matching of local muscle O2 delivery to V˙O2 in a young, healthy population (69,71,73,96). Further, it has been shown recently that a significant reduction in the pulmonary phase II τV˙O2, when moderate-intensity exercise is preceded by a bout of heavy-intensity (i.e., supra-lactate threshold) prior exercise, was related to improvements in the matching of muscle O2 delivery to V˙O2 as reflected by reductions in the deoxy(Hb + Mb)/V˙O2 ratio (71,96).

Prior heavy exercise reduces the spatial heterogeneity of muscle oxygenation kinetics during subsequent heavy exercise (93). Further, the significantly shorter time delay and slower time constant of [deoxy(Hb + Mb)] kinetics after priming suggest that the performance of prior heavy exercise improved the O2 delivery/V˙O2 matching at multiple sites within the muscles during the subsequent bout of exercise. However, the reduction of the spatial heterogeneity of muscle oxygenation kinetics did not translate into faster primary pulmonary V˙O2 kinetics during subsequent heavy exercise, suggesting that the heterogeneity of microvascular O2 delivery (in relation to muscle V˙O2) was not associated with any discernible O2 delivery limitation of the primary phase of muscle V˙O2 kinetics in healthy young subjects. Further, the decrease in the spatial heterogeneity of the muscle deoxygenation kinetics was not related to the reduction in the pulmonary V˙O2 slow component (93).

An examination of the relationship between pulmonary V˙O2 kinetics and absolute quadriceps [deoxy(Hb + Mb)] during exercise in normoxia and two levels of hypoxia (i.e., inspired O2 fractions of 0.21, 0.16, and 0.10) revealed no correlation between the slowing of pulmonary V˙O2 kinetics and the spatial heterogeneity of [deoxy(Hb + Mb)] across conditions (14). Similarly, in the steady state, thigh muscle blood flow heterogeneity remains unchanged during exercise in moderate hypoxia with the heterogeneity of muscle O2 delivery (relative to muscle V˙O2) being similar irrespective of inspired O2 fraction (45). Interestingly, however, it was demonstrated that increasing hypoxia causes a progressive reduction in the spatial variance of peak and end-exercise deoxy(Hb + Mb) (14). This resulted in an apparent inverse correlation between the spatial heterogeneity (CV) of peak [deoxy(Hb + Mb)] and the pulmonary V˙O2 kinetics; that is, the transient peak [deoxy(Hb + Mb)] across the quadriceps became more homogenous relative to the slowing of pulmonary V˙O2 kinetics observed in hypoxia. Collectively, therefore, these findings implicate (at least in healthy young humans) that the degree of spatial heterogeneity in O2 delivery/V˙O2 across the quadriceps may exert an influence on muscle V˙O2 kinetics during moderate-intensity exercise under conditions of decreased arterial O2 concentration.

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In summary, muscle deoxygenation measured by NIRS assesses the transient responses at the microvascular/myocyte level with high temporal fidelity. Such responses are not necessarily revealed by bulk measurements of O2 delivery and V˙O2 across the muscle.

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The balance between muscle O2 delivery and V˙O2 is crucial because this sets the microvascular PO2 and, thus, the upstream driving pressure for blood–myocyte O2 flux as well as influencing metabolic control via the impact on V˙O2 kinetics and intramyocyte PO2. Elegant experimental designs and technological advances now afford unprecedented capabilities to temporally and spatially resolve muscle O2 delivery and V˙O2 and their heterogeneity at rest and during exercise. This constitutes a novel and exciting window into metabolic control, and significant new data are currently being generated to determine physiological responses and to identify whether there are defined characteristics, especially in regard to the dynamics of the O2 delivery–V˙O2 relationship, within and across muscle regions. However, without further insights and possibly even better techniques to assess the degree of muscle fiber(s) recruitment in humans, the interpretation of O2 delivery–V˙O2 relationship (and microvascular PO2) remains challenging. Specifically, it is straightforward that a low O2 delivery–V˙O2 ratio will result in a high fractional O2 extraction and, consequently, a microvascular PO2 so low that blood–myocyte O2 flux (and both muscle and pulmonary V˙O2 kinetics) will be impaired via altered mitochondrial metabolic control. However, to what degree is a higher O2 delivery–V˙O2 ratio (and microvascular PO2) beneficial in terms of optimizing muscle V˙O2 kinetics and metabolic control in a specific region, and when might another spatially distinct muscle region derive more benefit from some of the “extra” O2 delivery? Additional pressing questions include the following: How do the slowed pulmonary V˙O2 kinetics emblematic of chronic heart failure, emphysema, and (often) diabetes relate to local O2 delivery–V˙O2 heterogeneity or mismatch? What mechanisms of vascular control are most important in regulating or fine-tuning O2 delivery–V˙O2 matching, and how are these perturbed in specific disease conditions? How can therapeutic measures, such as, exercise training, and enhanced NO bioavailability (via sildenafil or nitrate/beetroot juice or reduction of inflammatory/oxidant state), correct O2 delivery–V˙O2 mismatching, and will this translate into improved muscle contractile function and exercise capacity? Given the current capabilities to resolve O2 delivery–V˙O2 relationships in contracting skeletal muscles as enunciated herein, the potential scientific and therapeutic value of this field shines bright.

All authors are grateful to Professor John M. Kowalchuk for recognizing the need to better relate research findings in animals within the context of human physiology/pathophysiology and Professor Jerry A. Dempsey for scintillating discussion, especially regarding arteriolar vasomotor control within the diaphragm. S.K. thanks Professors Thomas J. Barstow, Yoshiyuki Fukuba, Yoshiyuki Fukuoka, Yoshimistu Inoue, and Narihiko Kondo for their encouraging and facilitating this review. H.B.R. thanks Dr. Alan Benson and Dr. Daniel Cannon for discussions in preparation of this manuscript.

S.K. was supported by the Japan Society for the Promotion of Science (grant nos. KAKENHI-18207019, 20650103, 21370111, 22370091, and 22650151). H.B.R. was supported by the Biotechnology and Biological Sciences Research Council, UK (grant nos. BB/I00162X/1 and BB/I024798/1). T.I.M. and D.C.P. were supported by the National Institutes of Health (grant nos. AG-19228, HL-50306, HL-67619, and HL-108328) and grants-in-aid from the American Heart Association (10GRNT4350011). Each author has no conflict of interest.

The results of the present study do not constitute endorsement by the American College of Sports Medicine.

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