On the effects of constant and variable work of equivalent average intensity on whole‐body heat exchange
Notice bibliographique
Résumé
Currently recommended heat exposure guidelines prescribe work‐rest allocations based on the level of heat stress originating from the environment and estimated work intensity with the primary goal of maintaining body core temperature within safe limits. Due to the nature of most occupations, these parameters are rarely, if ever, constant. For this reason, ambient conditions (e.g., temperature and humidity) and metabolic rate (endogenous heat production) are quantified as a time‐weighted average over a given work period. What is unknown, however, is whether time‐dependent alterations in work intensity influence whole‐body heat exchange and cardiovascular strain during work eliciting an equivalent time‐weighted average heat production. On four occasions, six young (27 years [SD 4]) males performed 90‐min of semi‐recumbent cycling at a time‐weighted average rate of heat production (~200 W·m −2 ) in dry heat (40°C, ~20% relative humidity) elicited via cycling at a constant external work rate of 40 W·m −2 (CON) or variable intensity cycling performed in 10‐min cycles: 1) 5 min at an external work rate of 15 W·m −2 followed by 5‐min at 60 W·m −2 (VAR‐LOW); 2) 6 min at 15 W·m −2 followed by 4 min at 70 W·m −2 (VAR‐MOD); and 3) 7 min at 15 W·m −2 followed by 3 min at 80 W·m −2 (VAR‐HIGH). Heat production was measured via indirect calorimetry while whole‐body evaporative heat loss and dry heat gain were evaluated with direct calorimetry. Body heat storage was calculated as the temporal‐summation of heat production and net heat exchange (evaporative heat loss minus dry heat gain). Calorimetric data were expressed as a time‐weighted average (W·m −2 ) except for heat storage, which was presented as a cumulative value (kJ). Rectal temperature and heart rate were monitored continuously and reported as an average of the final 10‐min of exercise (i.e., final cycle) as well as a peak 30‐s average during this period. Across conditions, there were no differences in evaporative heat loss (241 [20] W·m −2 , P=0.20 ), dry heat gain (59 [13] W·m −2 , P=0.52 ), net heat exchange (281 [10] W·m −2 , P=0.54 ) or body heat storage (224 [55] kJ, P=0.87) . Likewise, rectal temperature was not influenced by varying work intensity (average: 37.79 [0.23]°C; peak: 37.84 [0.22]°C; both P≥0.65 ). However, compared to CON (115 [8] beats·min −1 ), average heart rate over the final 10 min of exercise was elevated in VAR‐LOW (124 [12] beats·min −1 ; P=0.01 ), VAR‐MOD (122 [10] beats·min −1 ; P=0.04 ) and VAR‐HIGH (124 [11] beats·min −1 ; P=0.01 ), but similar between the variable work conditions (all P≥0.17 ). Similarly, peak heart rate was elevated in each of the variable work conditions compared to CON (120 [10] beats·min −1 ; all P<0.01 ) and in VAR‐HIGH (154 [11] beats·min −1 ) compared to both VAR‐LOW (140 [12] beats·min −1 ; P<0.01 ) and VAR‐MOD (143 [12] beats·min −1 ; P=0.01 ). These preliminary data suggest that time‐dependent alterations in work intensity eliciting equivalent time‐weighted rates of metabolic heat production do not influence whole‐body heat exchange or thermal strain, but exacerbate cardiovascular strain compared to constant‐intensity work. Support or Funding Information This project was funded by the Government of Ontario and the Natural Sciences and Engineering Research Council of Canada. This abstract is from the Experimental Biology 2019 Meeting. There is no full text article associated with this abstract published in The FASEB Journal .
Récupéré en direct depuis OpenAlex et désinversé. Les résumés ne sont pas conservés dans cette base de données : les index inversés représentent 8,6 Go des 9,3 Go de texte de la base, et le serveur dispose de 13 Go libres.
Comment cette classification a été obtenuedéplier
Prédiction machine sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Le volet Gemma est une étiquette directe du modèle pour chaque travail de la base, lue sur la notice réduite au titre. Le volet Codex est un classifieur appris des 10 348 étiquettes directes de Codex et calibré sur les taux pondérés de l'échantillon; les champs sans appui suffisant ne portent aucun appel Codex. Le mode candidate est l'union des deux volets; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont pas des étiquettes humaines.
Scores du classifieur distillé par catégorie (deux têtes)
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,001 | 0,002 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,000 |
| Bibliométrie | 0,000 | 0,000 |
| Études des sciences et des technologies | 0,000 | 0,001 |
| Communication savante | 0,000 | 0,000 |
| Science ouverte | 0,000 | 0,000 |
| Intégrité de la recherche | 0,000 | 0,000 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,002 | 0,000 |
Scores machine (provisoires)
Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.
Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.
score_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découleClassification
machine, non validéePrédiction automatique; un appel candidat d’une seule source (Gemma direct ou Codex distillé), pas un consensus.
Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».