Plasma Adipokines and Body Composition in Response to Modest Dietary Manipulations in the Mouse
Bibliographic record
Abstract
OBJECTIVE: The relationship between adipokine levels and body composition has not been carefully examined. Most studies in humans are cross-sectional, and the few studies in mice have been restricted to a comparison of control animals with markedly obese, insulin-resistant mice. Our objective was to study changes in adipokine levels and body composition in response to modest dietary intervention. RESEARCH METHODS AND PROCEDURES: Plasma resistin, adiponectin, and leptin levels were examined in mice fed ad libitum, a 75% restricted diet, or a diet supplemented with 10% sucrose. Body composition was determined by whole-body DXA. RESULTS: The percentage body fat was reduced in mice subjected to the restricted diet and increased in mice supplemented with 10% dextrose. Adipokine levels were not different in either of these groups compared with the control mice. A significant inverse correlation was observed between resistin levels and total body fat, whereas there was no significant correlation between body fat and adiponectin levels. Positive correlations were observed between leptin levels and percentage body fat, total body fat, and abdominal fat. Leptin levels correlated with plasma glucose, but multivariate analysis revealed that this correlation was the result of a strong positive correlation between leptin and insulin levels. There were no correlations between glycemia and resistin or glycemia and adiponectin levels, and no correlation was observed between any of the adipokine levels and bone mineral content or density. DISCUSSION: These data suggest that in the mouse, modest dietary perturbations have little effect on resistin and adiponectin levels despite significant effects on glycemia, insulin levels, and bone parameters.
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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 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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".