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Record W1964519450 · doi:10.1111/apha.12335

Muscle temperature and sweating during exercise: a new link?

2014· letter· en· W1964519450 on OpenAlexaff
Glen P. Kenny

Bibliographic record

VenueActa Physiologica · 2014
Typeletter
Languageen
FieldMedicine
TopicThermoregulation and physiological responses
Canadian institutionsUniversity of Ottawa
Fundersnot available
KeywordsThermoreceptorSWEATThermoregulationMetabolic rateChemistryInternal medicineMedicine

Abstract

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The study by Todd et al. (2014) advances the notion that intramuscular thermoreceptors may contribute to the regulation of eccrine sweating during exercise. While the evidence supporting the existence of such thermoreceptors remains to be established, it is not inconceivable that thermosensitive elements exist within muscle as the existence of thermoreceptors in various other regions of the body have been identified (Rawson & Quick 1972, El Ouazzani & Mei 1982). Moreover, some animal studies report that changes in muscle temperature can modulate the discharge frequency of groups I–IV muscle afferents (Hertel et al. 1976). The findings by Todd et al. of a strong temporal coupling of eccrine sweating to intramuscular temperature during a sinusoidal exercise bout certainly raise the possibility that such thermosensitive elements exist within skeletal muscle. The impact of their findings is particularly important given the critical role that thermal sweating plays in the regulation of internal body temperature in everyday activities. During exercise, a significant amount of energy is wasted and subsequently liberated as heat from the exercising muscles. To offset the perturbation in internal body temperature created by this increased rate of metabolic heat production, the thermoregulatory system must activate heat-dissipating mechanisms (Gagge & Gonzales 1996). The evaporation of sweat from the body surface represents the most important thermoregulatory mechanism for eliminating this excess heat especially when exercise is performed in the heat (Gagge & Gonzales 1996, Kenny & Jay 2013). While the rate of sweat secretion varies markedly depending on environmental temperature and the rate of metabolic heat production, sweat production increases rapidly at the onset of exercise, albeit regional variations in the time of onset have been reported (Kenny & Jay 2013, Taylor & Machado-Moreira 2013). Through conductive and convective heat exchange between tissues, the heat produced from the active musculature (e.g. such as the muscles from the lower limbs during running and cycling) is gradually transferred throughout the body resulting in a progressive storage of heat in the core (e.g. visceral organs) and peripheral tissues (e.g. inactive muscle, subcutaneous and skin tissue). As input from both core and skin temperatures are known to affect the sweating response (Nadel et al. 1971a,b), the control of sweating is commonly characterized using an integrated composite signal derived solely from thermoreceptor input from the core and skin (i.e. mean body temperature calculated using a weighted summation of core and mean skin temperatures; Gagge & Gonzales 1996). The rate at which the effector response changes as a function of the change in mean body temperature is known as the sensitivity, or gain, of the response (Gagge & Gonzales 1996). However, in view of the recent findings by Todd et al. (2014) of the possible role that intramuscular feedback may play in the regulation of sweating during exercise, incorporating the thermal influences of changes in muscle temperature of exercising muscle in an integrated composite signal may be warranted. The study by Todd et al. (2014) is not the first to raise the possibility of the existence of intramuscular thermal feedback in the regulation of sweating. However, it is the first to specifically examine their existence in the context of measuring how sweating response tracks changes in intramuscular muscle temperature of the exercising muscle using a well-controlled sinusoidal workload to modulate the rate of heat production and therefore the thermal load. Prior to performing a 24-min block of sinusoidal workload variations [three 8-min bouts; work rate varied between 60% of peak power (peak) and 30 W (trough)], participants cycled for 35 min (35% of peak power) to establish whole-body steady state in thermal and sudomotor responses. This experimental approach is particularly important given the impact that variations in thermal input from the core and skin regions can play in the modulation of the sweating response (Nadel et al. 1971a,b). By ensuring stable responses prior to starting the sinusoidal exercise bout, the authors were able to eloquently track the changes in local sweat rates (measured on the forehead, chest, forearm and left and right thigh) and assess the sudomotor waveforms as a function of controlled changes in thermal input of muscle (i.e. vastus lateralis) temperature as well as deep-body (as estimated by auditory canal, oesophageal and rectal measurement sites) and skin temperatures. Their study revealed that both the changes in intramuscular and oesophageal temperature preceded sweating. While there was a strong temporal coupling of the sweating response to both changes in oesophageal and active muscle temperatures, the sweating response was more tightly coupled with changes in temperature of the active muscle. The delay between the changes in oesophageal temperature and forehead sweat rate (46.9 ± 11.3 s), for example, was significantly greater than the corresponding delay between intramuscular temperature of the active vastus lateralis muscle and local sweat rate (25.6 ± 12.6 s). Taken together, their study findings support the possible existence of thermosensitive elements within active skeletal muscle which may contribute to the modulation of eccrine sweating. Earlier studies such as those by Robinson et al. (1965) and Saltin et al. (1970) examined the relationship between different body tissue temperatures and the regulation of sweating during thermal transients caused by exercise. However, in these studies, the assessment of the sweating response was judged by the rate of weight loss, and in one study, measurements were only performed in the recovery period. As such, it was not possible to accurately and precisely quantify the time-dependent changes in the activation of the sweating response. Moreover, in contrast to the experimental paradigm employed by Todd et al. (2014) wherein the 24-min sinusoidal workload variation was preceded by a 35-min low-intensity steady-state exercise to establish stable tissue temperature and sweating responses, both studies examined the sweating response as a function of intermittent exercise/recovery cycles of similar or varying work intensities which commenced following only a brief baseline resting period. Specifically, Robinson et al. (1965) examined temporal changes in muscle (gastrocnemius), blood (femoral and long saphenous veins), skin rectal and tympanic tissue temperatures in four subjects during light to moderate intensity intermittent exercise (two 5-min exercise bouts followed by three 10-min exercise bouts each interspersed with a 2-min rest period; ambient temperature of 20 °C). For one subject, trials were repeated in a range of ambient conditions (17–40 °C). In the study by Saltin et al. (1970), participants performed three successive bouts of exercise of increasing intensity (25, 50 and 75% of VO2max), each separated by a 30-min recovery period. On separate occasions, trials were performed at 10, 20 and 30 °C ambient conditions (not all subjects completed each condition). Despite the variations in exercise protocol, a consistent finding made by both groups was the observation that the rise in temperature of the exercising muscle preceded the increases in sweating, occurring earlier and more rapidly. While the design of these studies did not permit a comprehensive assessment of the influence that muscle temperature could theoretically contribute to the control of sweating, their findings provided cursory evidence that changes in muscle temperature of exercise muscles may be involved in the modulation of sweating in exercise. Of note, however, variations in the pattern of response with the different work intensity and ambient temperature conditions were observed suggesting that the regulation of sweating may involve the integration of other factors (Robinson et al. 1965, Saltin et al. 1970). This variation may have been in part due to the marked differences in tissue heat distribution associated with the different exercise and ambient conditions tested (Kenny & Jay 2013). Alternatively, it is plausible that factors of non-thermal origin may have influenced the pattern of response (Kenny & Journeay 2010, Shibasaki & Crandall 2010, Kenny & Jay 2013). Current research demonstrates that the sweating response during exercise is controlled not only by core and skin temperatures (thermal factors) but also by exercise-related (non-thermal) factors such as afferent inputs from exercising muscles (Kenny & Journeay 2010, Shibasaki & Crandall 2010, Kenny & Jay 2013). It is well known that group III muscle afferents are stimulated predominantly by mechanically sensitive muscle mechanoreceptors, whereas group IV muscle afferents are stimulated mainly by chemically sensitive muscle metaboreceptors and may therefore impinge upon the control of sweating (Kenny & Journeay 2010, Shibasaki & Crandall 2010). The relative contribution of thermal and non-thermal inputs in the modulation of sweating can vary as function of the intensity of exercise and type of exercise performed (i.e. isometric, continuous vs. intermittent exercise; Kenny & Journeay 2010, Kenny & Jay 2013). Moreover, the relative influence of non-thermal factors in the regulation of sweating differs between successive exercise/recovery cycles, with non-thermal factors predominating in control of sweating in the post-exercise recovery period (Kenny & Journeay 2010, Kenny & Jay 2013). This may in part explain the disparate findings reported in the early studies by both Robinson et al. (1965) and Saltin et al. (1970) in the relationship between body temperatures and sweating during exercise performed at different exercise intensities and/or ambient conditions. In this context, the experimental protocol employed by Todd et al. (2014) facilitates the assessment of intramuscular feedback for thermal sweating by minimizing the confounding contributions from non-thermal feedback. While these influences were not directly measured, the use of a controlled continuous rhythmical exercise (with a low work intensity of <120 W for 50% of the time) ensured that the contribution of non-thermal factors could be controlled thereby minimizing their influence on the sweating response. For example, their observation that the sweating response occurred more than 2 min after the corresponding change in heart rate between cycles revealed that the influence of central command was likely not a factor involved in the regulation of sweating. Can we conclude from the study by Todd et al. (2014) that thermal input from the active muscle plays an important role in the modulation of sweating? Their study advances new and compelling evidence to support this possibility. Whether through feedback from hypothetical intramuscular thermoreceptors or non-specific feedback from the groups I–V muscle afferents, their observation of a consistent tightly matched time-dependent coupling of sweating with changes in intramuscular temperature of the exercising muscle raises important new questions related to the mechanisms and controllers of eccrine sweating. Moreover, the findings by Todd et al. (2014) will certainly spark renewed interest in how we assess the control of sweating based solely on the influence of internal and skin temperatures (Kenny & Jay 2013). Total body mass is composed of approximately 40% muscle mass, and active muscle tissue represents the primary source of heat during exercise. When considered in the context of the findings by Todd et al. (2014), it seems logical to consider the influence of muscle heat content, and therefore muscle temperature when estimating changes in mean body temperature for the purposes of evaluating the control of sweating. Finally, beyond the new mechanistic insights that their study provides, the study raises important new directions for future research studies. These studies should consider examining the underlying influence of intramuscular thermal feedback as a function of changes in thermal input of core and skin brought about by the use of different forcing functions (e.g. thermal clamping/controlled hyperthermia, passive vs. exercise-induced heat stress, thermal transients caused by intermittent exercise of varying durations and/or heat loads, etc.) and in the context of different levels of non-thermal input. None.

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How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.563
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0010.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.024
GPT teacher head0.264
Teacher spread0.240 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

Study designNot applicable
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

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Citations3
Published2014
Admission routes1
Has abstractyes

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