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Influence Of Passive Heating On Physiological Responses To Different Body Hydration Levels In Healthy Men

2005· article· en· W4236961563 on OpenAlexaff
J Zachwieja, Brian W. Timmons, Elizabeth A. Stover

Bibliographic record

VenueMedicine & Science in Sports & Exercise · 2005
Typearticle
Languageen
FieldMedicine
TopicThermoregulation and physiological responses
Canadian institutionsMcMaster University
Fundersnot available
KeywordsDehydrationHeart rateRectal temperatureCore temperatureAnimal scienceCore (optical fiber)Skin temperatureThermoregulationMedicineHeat stressChemistryInternal medicineBlood pressureMaterials scienceBiologyBiomedical engineeringBiochemistry

Abstract

fetched live from OpenAlex

At times humans are required to withstand high environmental heat stress in a passive manner. Depending on access to fluids, the physiological responses to this passive heat stress (PHS) may differ. PURPOSE To determine the effects of PHS on physiological responses of healthy men at three levels of body hydration. A secondary purpose was to compare ingestible temperature sensor (ITS) and rectal thermistor methods for measurement of core body temperature during PHS. METHODS Ten healthy men participated (mean ± SD, age: 28 ± 3 yrs; wgt: 80.7 ± 12.4 kg; % body fat: 17.2 ± 4.8 %; body surface area: 1.96 ± 0.13 m2). Each subject underwent 80 min of PHS (35 °C, 70 % RH, WBGT=30) with lower legs submersed in re-circulated water (∼43 °C) on 3 occasions. A dehydration trial (DT; no fluid intake) was always performed first followed by trials of forced (FT; 120% of dehydration in DT) and voluntary drinking (VT; ad libitum) of tap water. FT and VT were counterbalanced. During each session, heart rate (HR) and skin temperatures were recorded. Core body temperature was determined with a rectal thermistor and ITS. RESULTS Body hydration in each session was significantly (p<0.05) different than each other session and averaged −1.5 ± 0.5 % (DT), 0.7 ± 0.6 % (FT), and −0.6 ± 0.7 % (VT). HR increased by 40 ± 26 beats/min (DT), 21 ± 11 beats/min (FT), and 29 ± 12 beats/min (VT), with the smaller increases in FT and VT significantly (p<0.05) different than DT. The increase in forearm (∼4.5 °C) and anterior thigh (∼5.0 °C) temperature did not differ between trials. However, the increase in forehead temperature (3.0 ± 0.9 °C) during VT was greater than during FT (2.5 ± 0.8 °C). In each trial, rectal temperature (RT) increased from ∼37.1 °C at rest to 37.94 ± 0.47 °C (DT), 37.46 ± 0.25 °C (FT) and 37.88 ± 0.39 °C (VT) by the end of heat exposure. Although small, the absolute change in RT was significantly (p<0.05) attenuated during FT. RT correlated significantly with ITS (r=0.67, p<0.05). However, there was poor agreement between the two measures with ITS overestimating RT by 0.14 °C (±1SD=0.36°C). There were no differences between sessions in sweating rate, which averaged 0.84 ± 0.30 L/hour. CONCLUSION The results indicate that passive heating is associated with significant physiological alterations that can be minimized with either voluntary or forced fluid intake. Thus, humans exposed to high heat stress under passive conditions (e.g., fighter pilots, race car drivers) will benefit from access to fluids. Furthermore, ITS tracks changes in body temperature under conditions of PHS, but may not be an accurate surrogate for rectal temperature.

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)0.000
metaresearch head score (Gemma)0.001
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: Empirical
Teacher disagreement score0.001
Threshold uncertainty score0.003

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
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 head0.040
GPT teacher head0.354
Teacher spread0.314 · 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".

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Citations0
Published2005
Admission routes1
Has abstractyes

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