Prior caloric restriction increases survival of prepubertal obese- and PCOS-prone rats exposed to a challenge of time-limited feeding and physical activity
Bibliographic record
Abstract
We hypothesized that a polycystic ovary syndrome (PCOS) background associated with obese-prone genotype, coupled with preconditioning by caloric restriction, would confer a survival benefit in genetically prepubertal obese/PCOS (O/PCOS)-prone rats faced with an unpredictable challenge of food shortage. Female, juvenile JCR:LA-cp rats, O/PCOS- and lean-prone, were exposed to 1.5 h of daily meals and 22.5 h of voluntary wheel-running, a procedure that leads to activity anorexia (AA). One week before the AA challenge (AAC), O/PCOS-prone rats were freely fed (O/PCOS-FF) or pair fed (O/PCOS-FR) to lean-prone, free-feeding animals (Lean-FF). O/PCOS-FR and lean-prone, food-restricted (Lean-FR) groups were matched on relative average caloric intake. Animals were removed from protocol at 75% of initial body weight (starvation criterion) or after 14 days (survival criterion). The AAC induced weight loss in all rats, but there were significant effects of both genotype and feeding history on weight loss (lean-prone rats exhibited a higher rate of weight loss than O/PCOS-prone; P < 0.001), and rats with prior caloric restriction retained more weight than those free fed previously (90.68 ± 0.59% vs. 85.47 ± 0.46%; P < 0.001). The daily rate of running was higher in lean-prone rats compared with O/PCOS-prone. This difference in running rate correlated with differences in mean days of survival. All O/PCOS-FR rats survived at day 14. O/PCOS-FF rats survived longer (10.00 ± 0.97 days) than Lean-FR (6.17 ± 1.58 days) and Lean-FF (4.33 ± 0.42 days) rats (P < 0.05). Thus preconditioning by caloric restriction induces a substantial survival advantage, beyond genotype alone, in prepubertal O/PCOS-prone rats.
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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 | 0.000 | 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 | 0.001 |
| 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".