Highland deer mice support increased thermogenesis in response to chronic cold hypoxia by shifting uptake of circulating fatty acids from muscles to brown adipose tissue
Bibliographic record
Abstract
During maximal cold challenge (cold-induced V̇O2,max) in hypoxia, highland deer mice (Peromyscus maniculatus) show higher rates of circulatory fatty acid delivery compared with lowland deer mice. Fatty acid delivery also increases with acclimation to cold hypoxia (CH) and probably plays a major role in supporting the high rates of thermogenesis observed in highland deer mice. However, it is unknown which tissues take up these fatty acids and their relative contribution to thermogenesis. The goal of this study was to determine the uptake of circulating fatty acids into 24 different tissues during hypoxic cold-induced V̇O2,max, by using [1-14C]2-bromopalmitic acid. To uncover evolved and environment-induced changes in fatty acid uptake, we compared lab-born and -raised highland and lowland deer mice, acclimated to either thermoneutral (30°C, 21 kPa O2) or CH (5°C, 12 kPa O2) conditions. During hypoxic cold-induced V̇O2,max, CH-acclimated highlanders decreased muscle fatty acid uptake and increased uptake into brown adipose tissue (BAT) relative to thermoneutral highlanders, a response that was absent in lowlanders. CH acclimation was also associated with increased activities of enzymes citrate synthase and β-hydroxyacyl-CoA dehydrogenase in the BAT of highlanders, and higher levels of fatty acid translocase CD36 (FAT/CD36) in both populations. This is the first study to show that cold-induced fatty acid uptake is distributed across a wide range of tissues. Highland deer mice show plasticity in this fatty acid distribution in response to chronic cold hypoxia, and combined with higher rates of tissue delivery, this contributes to their survival in the cold high alpine environment.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".