Differential expression of hypothalamic, metabolic and inflammatory genes in response to short-term calorie restriction in juvenile obese- and lean-prone JCR rats
Bibliographic record
Abstract
BACKGROUND: Childhood obesity is an important early predictor of adult obesity and associated comorbidities. Common forms of obesity are underpinned by both environmental and genetic factors. However, the rising prevalence of obesity in genetically stable populations strongly suggests that contemporary lifestyle is a premier factor to the disease. In pediatric population, the current treatment/prevention options for obesity are lifestyle interventions such as caloric restriction (CR) and increase physical activity. In obese individuals, CR improves many metabolic parameters in peripheral tissues. Little is known about the effect of CR on the hypothalamus. This study aimed to assess the effect of CR on hypothalamic metabolic gene expression of young obese- and lean-prone animals. METHODS: Male juvenile JCR:LA-cp obese-prone rats were freely fed (Obese-FF) or pair fed (Obese-FR) to lean-prone, free-feeding animals (Lean-FF). A group of lean-prone rats (Lean-FR) were matched for relative average degree of CR to Obese-FR rats. RESULTS: In free-feeding conditions, obese-prone rats consumed more energy than lean-prone rats (P<0.001) and showed greater increases in body weight, fat mass, plasma glucose, insulin and lipids (P<0.01). These metabolic differences were associated with alterations of feeding-related neuropeptides expression in the hypothalamus, as well as pro-inflammatory cytokines and oxidative stress markers. When submitted to the same degree of CR, the two genotypes responded differently; hypothalamic inflammatory and oxidative stress gene expression was improved in Obese-FR, while it was worsened in Lean-FR rats. CONCLUSIONS: We demonstrate in JCR rats that the metabolic and inflammatory response of the brain to CR is genotype dependent.
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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 | 0.000 |
| 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".