Serum leptin is not correlated with body fat in severe food restriction
Bibliographic record
Abstract
Leptin is an adipose-derived hormone with established roles in energy balance that can impact the response to refeeding after malnutrition. Although the amount of circulating leptin has traditionally been associated with the amount of adipose tissue, controversy exists as to whether this relationship is constant in both humans and animals and over a wide range of body composition. Our objective was to evaluate whether the leptin - body fat ratio is constant in the range of healthy to low body mass in female Wistar rats. Eight ad libitum fed (C) and eight food-restricted (FR) rats were compared over a period of four weeks. FR rats attained the target 75% of baseline body mass after the first two weeks, which was maintained for the remaining two weeks. Serum leptin and IGF-1 (ELISA) and body composition (DXA) were measured at baseline (t(0)) and once weekly for the remainder of the study (t(1)-t(4)). The leptin - body fat ratio was reduced during the two-week period of weight loss (t(0) = 0.036 ± 0.016 (ng·mL(-1))·g(-1) vs. t(1) = 0.010 ± 0.004 (ng·mL(-1))·g(-1) and t(2) = 0.015 ± 0.007 (ng·mL(-1))·g(-1), p < 0.05). Leptin concentration plateaued at its nadir (~0.24 (ng·mL(-1))·g(-1)) at fat mass < 22 g. IGF-1 was correlated with lean mass (r = 0.45, p < 0.05) and fat mass (r = 0.58, p < 0.05), regardless of body mass. We concluded that the leptin - body fat ratio was reduced early in food restriction and the correlation between these two variables was absent at low body fat.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 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) | 0.001 | 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".