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Enregistrement W4297007956 · doi:10.1242/jeb.244975

Some mice are better than others at recycling warmth to conserve energy

2022· article· en· W4297007956 sur OpenAlexaboutno aff
Kathryn Knight

Notice bibliographique

RevueJournal of Experimental Biology · 2022
Typearticle
Langueen
DomaineMedicine
ThématiqueAdipose Tissue and Metabolism
Établissements canadiensnon disponible
Organismes subventionnairesnon disponible
Mots-clésWonderPeromyscusWarming upPsychologyBiologyEcologySocial psychologyPhysiology

Résumé

récupéré en direct d'OpenAlex

Generating your own internal warmth to keep going regardless of the conditions is all well and good when it's temperate and balmy, but as soon as the mercury begins to fall, your energetic costs can become exorbitant as you struggle to keep the furnace fuelled. ‘Many endotherms [warm-blooded animals] spend a considerable amount of energy on simply keeping warm’, says Vincent Careau from the University of Ottawa, Canada. However, some warm-blooded animals may be able to capitalise on heat generated by tissues as a side-effect of activity to supplement body warmth when chilly. ‘Substitution cannot reduce the energy used to thermoregulate, but can use that energy efficiently if the activity that generates heat can be potentially invested in physiological processes’, Careau explains. Effectively, animals can get two bangs for their metabolic buck. However, populations are made up of unique individuals, some of which may be more talented at specific tasks than others, which made Careau and Caroline Maloney (University of Ottawa), wonder whether some individuals are better placed to benefit from supplementary warming than others and, if so, which tissues and organs may give them a warm head start.The duo investigated how much individual white-footed mice (Peromyscus leucopus), widespread from Mexico to chilly Canada, might profit from the warmth generated by their muscles as they scampered on a wheel. Selecting 48 rodents, the researchers isolated each mouse in individual cages where they could run and rest to their heart's content for 4 days, 2 of which they spent at a comfortable 22°C, while the remaining 2 days were at a cool 10°C. In addition, the pair recorded the animals’ oxygen consumption, to keep track of their metabolic rates, to find out how much each one utilised the warmth generated by their exertions, repeating the entire procedure another 2 times, to determine out how hardwired their ability was to supplement their warmth with exertion.Calculating how much each rodent was able to take advantage of the warmth generated by their muscles, Maloney and Careau confirmed that some individuals benefited more from the heat produced by their muscles than others, conserving energy which they could then reinvest in other aspects of life. But how are some white-footed mice able to take more advantage of the warmth generated by their exertions than others?The duo took a close look at the animals’ vital organs, as well as their calf muscles – which power running – and their insulating fur mass and skin area, to find out whether they might influence an individual's ability to retain supplementary warmth. Although, the skin and insulation barely had an impact, the animals with a smaller surface area seemed better at retaining their muscle warmth. However, the longest mice conserved more of their muscle heat than shorter animals, probably because they have larger heads – which lose less heat to their surroundings – to retain more of their muscle warmth. Having a larger heart also seemed to allow the mice to conserve more heat, likely because larger hearts cope better with the higher blood pressure that chilly animals experience when they close off blood vessels close to the skin and direct blood to the core to retain heat.So, some white-footed mice are better than others at making the most from the warmth generated by their muscles as they exercise to supplement their body temperature, and Maloney and Careau are curious to find out how much of an advantage recycling body warmth may give the lucky beasts that benefit most.

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 enseignants

Ni 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.

score de la tête « metaresearch » (Codex)0,002
score de la tête « metaresearch » (Gemma)0,003
Version: metacan-v3-hybrid-931329e0061cStatut de validation: machine_predicted_unvalidated
Catégories candidatesaucune
Catégories consensuellesaucune
DomaineSignal candidat: aucune · Signal consensuel: aucune
Devis d'étudeSignal candidat: Expérimental (laboratoire) · Signal consensuel: Expérimental (laboratoire)
GenreSignal candidat: Empirique · Signal consensuel: Empirique
Score de désaccord entre enseignants0,016
Score d'incertitude au seuil0,055

Scores du classifieur distillé par catégorie (deux têtes)

CatégorieCodexGemma
Métarecherche0,0020,003
Méta-épidémiologie (sens strict)0,0010,000
Méta-épidémiologie (sens large)0,0010,001
Bibliométrie0,0010,000
Études des sciences et des technologies0,0010,002
Communication savante0,0020,003
Science ouverte0,0010,001
Intégrité de la recherche0,0020,004
Charge utile insuffisante (le modèle a refusé de juger)0,0160,005

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.

Tête enseignante Opus0,026
Tête enseignante GPT0,312
Écart entre enseignants0,286 · la distance entre les deux têtes enseignantes sur ce seul travail
Statut de validationscore_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 découle

Classification

machine, non validée

Prédiction automatique; un appel candidat d’une seule source (Gemma direct ou Codex distillé), pas un consensus.

Les modèles n’ont appliqué aucune catégorie : rien dans la taxonomie ne correspondait à ce travail.
Devis d'étudeExpérimental (laboratoire)
Domainenon disponible
GenreEmpirique

Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».

En bref

Citations0
Publié2022
Routes d'admission1
Résumé présentoui

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