Diversity of Thermogenic Capacity Predicts Divergent Obesity Susceptibility in a Wild Rodent
Bibliographic record
Abstract
OBJECTIVE: The objective of the present study was to examine whether wild rodents exhibit diverse obesity susceptibility and what factors predispose subjects to this divergence in response to a high-fat diet (HFD). METHODS: Sixty male and female Brandt's voles (Lasiopodomys brandtii) were fed an HFD for 8 weeks, and the upper (obesity prone [OP]) and lower (obesity resistant [OR]) one-third for mass gain were selected. Energy budgets and pathologic changes were measured. Another 30 males were fed a low-fat control diet (LFD) for 10 weeks and then fed an HFD for 12 weeks. The energetic parameters of the rodents on an LFD were analyzed for the correlation with body mass of the rodents on an HFD. RESULTS: OP voles had higher energy intakes, higher levels of noradrenaline-induced nonshivering thermogenesis, and a greater impairment of insulin tolerance than OR voles. Unlike laboratory rodents, there were no differences in physical activity or resting metabolic rate between these groups of voles. The thermogenic capacity during LFD feeding was the strongest predictor for mass gain during HFD feeding. CONCLUSIONS: This study suggests that a wild rodent species of Brandt's voles exhibits diverse obesity susceptibility in reaction to an HFD, providing a natural model to give insight into the mechanisms for divergent obesity susceptibility. This study also indicates that maximum thermogenic capacity has a predictive power for the development of obesity when an HFD was available.
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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 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".