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Record W2408881733 · doi:10.1249/mss.0000000000000638

On the Maintenance of Human Heat Balance during Cold and Warm Fluid Ingestion

2015· letter· en· W2408881733 on OpenAlexaffabout
Anthony R. Bain, Nathan B. Morris, Matthew N. Cramer, Ollie Jay

Bibliographic record

VenueMedicine & Science in Sports & Exercise · 2015
Typeletter
Languageen
FieldMedicine
TopicThermoregulation and physiological responses
Canadian institutionsUniversity of OttawaUniversity of British Columbia
Fundersnot available
KeywordsCalorimetryIngestionThermodynamicsChemistryThermal energy storagePhysicsBiochemistry

Abstract

fetched live from OpenAlex

Dear Editor-in-Chief, The influence of ingested fluid temperature on thermoregulatory responses during exercise has attracted considerable attention during the past decade. To date, however, it has remained unclear whether body heat storage is truly altered. A thermometric model is generally considered inaccurate for estimating heat storage during exercise (2). Therefore, we previously assessed the influence of ingested fluid temperature on this parameter using partitional calorimetry (1). In a follow-up study, we demonstrated that thermoreceptors in the abdomen—not mouth—might independently mediate fluid-temperature-dependent alterations in sweating (4). A recent study by Lamarche et al. (3), published in Medicine & Science in Sports & Exercise®, duplicated the design of our earlier study but importantly assessed heat storage using direct, rather than partitional, calorimetry—the former, ostensibly, being more accurate. Their précis suggested observations different from our two previous studies and questioned the validity of employing partitional calorimetry. However, upon closer examination, their study seemingly yielded similar findings, with one important exception that helps highlight the limitations of partitional calorimetry. Arguably, the most practically relevant finding from our previous study (1) was that ingestion of cold fluids (10°C or 1.5°C), compared to thermoneutral (37°C) fluids, during exercise does not lead to lower body heat storage due to a reduction in evaporation that is proportional to the heat energy exchanged internally with ingested fluids. Lamarche et al. (3) reproduced the same finding (for 1.5°C), thus demonstrating that partitional calorimetry provides an apparently reliable assessment of heat storage at least during cold fluid ingestion. No statistical difference in forehead sweat rate was observed between ingestion of 50°C water and ingestion of 1.5°C water, whereas upper back sweat rate was only statistically different after the third bolus ingestion (3). Together, these observations were reported to contradict our other previous study (4). However, a clear separation between conditions appears evident—particularly on the forehead (Fig. 3D in [3])—after ingestion, indicating that statistical significance may have been attained with a larger sample size. With direct calorimetry, our previous conclusion of a disproportionately greater increase in evaporation from the skin relative to the heat gained internally with ingestion of 50°C water (1) is now shown to be potentially incorrect (3). These conflicting reports can probably be explained by a better maintenance of sweating efficiency with circulating airflow in a direct calorimeter, as opposed to our forward-facing airflow. Although the accuracy of both calorimetric methods is limited to combinations of activity and climate that induce complete evaporation, the present study indicates that the upper limit of these conditions is likely cooler and drier for a given metabolic rate when employing partitional calorimetry. These limits can probably be expanded though with the addition of a sideways-facing fan. Collectively, these studies conclusively demonstrate that humans physiologically compensate for internal heat exchange with cold (and probably warm) fluid ingestion by altering sweating activity and thus evaporation from the skin. As such, when complete sweat evaporation is permitted, no differences in heat storage occur, irrespective of drink temperature. However, colder fluid is probably beneficial from a human heat balance perspective when sweat begins dripping. Anthony R. Bain Center for Heart, Lung and Vascular Health University of British Columbia Kelowna, BC, CANADA Nathan B. Morris Exercise and Sport Science Faculty of Health Sciences University of Sydney Lidcombe, AUSTRALIA Matthew N. Cramer School of Human Kinetics University of Ottawa Ottawa, ON, CANADA Ollie Jay Exercise and Sport Science Faculty of Health Sciences University of Sydney Lidcombe, AUSTRALIA School of Human Kinetics University of Ottawa Ottawa, ON, CANADA [email protected]

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.002
metaresearch head score (Gemma)0.011
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.010
Threshold uncertainty score0.033

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.011
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0020.000
Bibliometrics0.0010.001
Science and technology studies0.0010.001
Scholarly communication0.0020.001
Open science0.0020.001
Research integrity0.0040.005
Insufficient payload (model declined to judge)0.0100.005

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 head0.029
GPT teacher head0.294
Teacher spread0.265 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
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".

Quick stats

Citations2
Published2015
Admission routes2
Has abstractyes

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