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Menstrual Cycle Phase does not Influence Whole Body Heat Loss Responses During Exercise in the Heat

2016· article· en· W4389024345 on OpenAlexafffundabout
Sheila Dervis, Martin P. Poirier, Gabrielle Paull, Sarah Y. Zhang, Glen P. Kenny

Bibliographic record

VenueThe FASEB Journal · 2016
Typearticle
Languageen
FieldMedicine
TopicThermoregulation and physiological responses
Canadian institutionsUniversity of Ottawa
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsMenstrual cycleFollicular phaseEndocrinologyLuteal phaseInternal medicineEstrogenCalorimetryChemistryThermoregulationHormoneMedicineThermodynamics

Abstract

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Traditionally, female reproductive hormones (i.e., estrogen and progesterone) have been shown to independently influence local thermal responses during exercise in the heat. Consequently, studies examining thermal responses during exercise usually only test females during the early follicular phase of the menstrual cycle (i.e., first five days) when estrogen and progesterone are at their lowest levels. However, it remains unclear whether local thermal responses translate into comparable changes in whole‐body heat loss throughout the menstrual cycle. Therefore, we examined changes in whole‐body evaporative heat loss as determined using direct calorimetry in the early follicular (i.e., when both estrogen and progesterone levels are low), late follicular (i.e., when estrogen levels are high) and mid‐luteal (i.e., when both progesterone and estrogen levels are high) phases in young females (n=5, 21±2 years). Participants performed three 30‐min bouts of semi‐recumbent cycling at a fixed rate of metabolic heat production equal to 250 (Ex1), 325 (Ex2) and 415 W (Ex3) in the heat (40°C and 15% relative humidity), each bout followed by 15‐min of recovery. Whole‐body heat loss (evaporative and dry) and metabolic heat production were measured by direct and indirect calorimetry, respectively. Whole‐body heat content was calculated as the temporal summation of heat production and heat loss. Our preliminary results demonstrate that the combined rate of metabolic heat production and dry heat gain (i.e., net heat load) was similar between hormonal phases throughout the incremental intermittent exercise protocol (P>0.05). The rate of whole‐body evaporative heat loss measured during the early follicular (Ex1: 259±10 W, Ex2: 328±17 W, Ex3: 353±20 W), late follicular (Ex1: 248±27 W, Ex2: 306±36 W, Ex3: 337±31 W) and mid‐luteal phases (Ex1: 246±21 W, Ex2: 304±52 W, Ex3: 346±46 W) of the menstrual cycle were similar between phases for each exercise bout (P≥0.05). Accordingly, whole‐body heat content was also similar (early follicular: Ex1: 124±80 kJ, Ex2: 147±80 kJ, Ex3: 247±78 kJ; late follicular: Ex1: 125±27 kJ, Ex2: 139±17 kJ, Ex3: 180±59 kJ; mid‐luteal: Ex1: 121±28 kJ, Ex2: 147±39 kJ, Ex3: 213±49 kJ) (P>0.05). Our preliminary findings suggest that ovarian hormone fluctuations (i.e., estrogen and progesterone) during the menstrual cycle in young females do not influence whole‐body heat dissipation and therefore the amount of heat stored during exercise in the heat. Support or Funding Information Funding support: This study was supported by grants from the Natural Sciences and Engineering Research Council of Canada (Discover grant, RGPIN‐06313‐2014; Discovery Grants Program ‐ Accelerator Supplement, RGPAS‐462252‐2014; funds held by Dr. Glen P. Kenny).

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 score0.003
Threshold uncertainty score0.008

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)0.0030.000

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 head0.020
GPT teacher head0.311
Teacher spread0.291 · 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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Citations2
Published2016
Admission routes3
Has abstractyes

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