Defense of increased body weight against caloric restriction in diet-induced obesity: The role of relaxin-3
Bibliographic record
Abstract
O is a multi-factorial disorder that generally develops on the polygenetic basis in an obesogenic environment. An animal model related to human obesity is diet-induced obesity in rats. The rats placed on a high-energy diet show wide distribution in body weight with a subset of animals developing diet-induced obesity (DIO) and the remaining animals showing a diet-resistant (DR) phenotype. Once obesity is established, DIO rats strongly defend their increased body weight against caloric restriction. The neuronal mechanisms involved in the defence of increased body weight in the DIO rats are not yet completely understood. Our results suggest that an orexigenic neuropeptide relaxin-3 may be involved in the mechanisms of defence of elevated body weight against caloric restriction in DIO rats. Expression of relaxin-3 and its specific receptor RXFP3 mRNAs were assessed by in situ hybridization in ad libitum, food-deprived and refed DIO and DR rats. The brain levels of expression of relaxin-3 were higher in the DIO rats compared to the DR rats in the ad libitum-fed state. The stronger expression of relaxin-3 in the ad libitum-fed state in the DIO rats was accompanied by low expression of the RXFP3 receptor. However, refeeding significantly increased expression of RXFP3 in the DIO rats. These results provide evidence that DIO rats show a constitutive increase in relaxin-3 brain expression and that refeeding after food deprivation may enhance the orexigenic effects of relaxin-3 in DIO rats by rapid upregulation of the expression of RXFP3 in the brain regions involved in food intake regulation.
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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".