High-fat diet differentially regulates metabolic parameters in obesity-resistant S5B/Pl rats and obesity-prone Osborne-Mendel rats
Bibliographic record
Abstract
The current experiment tested the hypothesis that consumption of a high-fat diet (HFD) would differentially affect metabolic parameters in obesity-prone Osborne-Mendel (OM) and obesity-resistant S5B/Pl (S5B) rats. In OM rats consuming a HFD, an increase in HFD intake, body mass, and percent fat mass, and a HFD-induced decrease in metabolic rate and energy expenditure were demonstrated. In S5B rats consuming a HFD, no change in percent body fat or HFD intake was demonstrated and HFD increased metabolic rate and energy expenditure. To assess whether HFD differentially altered skeletal muscle markers of metabolism in OM and S5B rats, the expression of the transporters, CD36 and GLUT4, and the energy sensors, AMPK and PPARγ, in the gastrocnemius muscle was measured. Oxidation and lipid accumulation in the gastrocnemius muscle was histologically determined. Consumption of a HFD decreased phosphorylated AMPK and PPARγ expression in the skeletal muscle of obesity-prone OM rats. Lipid accumulation in skeletal muscle was significantly higher in OM rats fed a HFD. Overall, these data suggest that the differential response to HFD on metabolic rate, energy expenditure, and phosphorylated AMPK and PPARγ in OM and S5B rats, may partially account for differences in the susceptibility to develop obesity.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".