Evidence map›Paper›PMID 41457285›Full record

ReviewLipids in health and disease2025

Burning fast & slow: a review of the differential metabolic routes of brown adipose tissue activity during cold exposure and their implications for populational variation.

Cara Ocobock, Alexandra Niclou, Ville Stenbäck, Daniel McElreavy

Abstract readReview
In one paragraph

Review in Lipids in health and disease, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

4 authors.

Cara OcobockDepartment of Anthropology, University of Notre Dame, 296 Corbett Family Hall, Notre Dame, IN, 46556, USA. cocobock@nd.edu.
Alexandra NiclouPennington Biomedical Research Center, Baton Rouge, LA, USA.
Ville StenbäckDepartment of Anthropology, University of Notre Dame, 296 Corbett Family Hall, Notre Dame, IN, 46556, USA.
Daniel McElreavyDepartment of Anthropology, University of Notre Dame, 296 Corbett Family Hall, Notre Dame, IN, 46556, USA.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Brown adipose tissue (BAT) has received renewed attention for its ability to increase metabolic rate and heat production, via non-shivering thermogenesis, in response to mild cold exposure. When activated, BAT also appears to improve circulating glucose and fatty acid levels, highlighting the potential for this mitochondria-dense tissue to be used as an antiobesogenic tool. A great deal of populational and individual variation is seen in BAT metabolic responses as well as substrate metabolism even between populations from similar climates, though we do not yet understand the underlying reasons for this variation. Here, using an anthropological and biological lens, we review what is currently known about BAT physiology and its variation across human populations. We then review evidence that suggests BAT may use aerobic and anaerobic metabolism in a way that mirrors skeletal muscle. We then argue that the many and often redundant pathways leading to BAT thermogenesis may be what explains the observed population variation. We end the review by briefly suggesting a potential way to test whether aerobic and anaerobic metabolism are occurring within human BAT in hopes of more fully understanding and explaining BAT physiological variation.

Indexed as

Adipose Tissue, BrownCold TemperatureThermogenesisAnimalsEnergy MetabolismHumansAerobic metabolismAnaerobic metabolismBrown adipose tissueCold adaptationNon-shivering thermogenesis

Identifiers

PMID41457285
PMCPMC12860087

What OpenQuestion holds

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LicenceCC BY-NC-ND
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Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.