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Record W4297007956 · doi:10.1242/jeb.244975

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

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

Bibliographic record

VenueJournal of Experimental Biology · 2022
Typearticle
Languageen
FieldMedicine
TopicAdipose Tissue and Metabolism
Canadian institutionsnot available
Fundersnot available
KeywordsWonderPeromyscusWarming upPsychologyBiologyEcologySocial psychologyPhysiology

Abstract

fetched live from 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.

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)0.003
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.016
Threshold uncertainty score0.055

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.003
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.000
Science and technology studies0.0010.002
Scholarly communication0.0020.003
Open science0.0010.001
Research integrity0.0020.004
Insufficient payload (model declined to judge)0.0160.005

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 head0.026
GPT teacher head0.312
Teacher spread0.286 · 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 designBench or experimental
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

Citations0
Published2022
Admission routes1
Has abstractyes

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