Chemerin Exacerbates Glucose Intolerance in Mouse Models of Obesity and Diabetes
Bibliographic record
Abstract
Obesity, characterized by an excess of adipose tissue, is an established risk factor for cardiovascular disease and type 2 diabetes. Different mechanisms linking obesity with these comorbidities have been postulated but remain poorly understood. Adipose tissue secretes a number of hormone-like compounds, termed adipokines, that are important for the maintenance of normal glucose metabolism. Alterations in the secretion of adipokines with obesity are believed to contribute to the undesirable changes in glucose metabolism that ultimately result in the development of type 2 diabetes. In the present study, we have shown that serum levels of the novel adipokine chemerin are significantly elevated in mouse models of obesity/diabetes. The expression of chemerin and its receptors, chemokine-like receptor 1, chemokine (C-C motif) receptor-like 2, and G protein-coupled receptor 1 are altered in white adipose, skeletal muscle, and liver tissue of obese/diabetic mice. Administration of exogenous chemerin exacerbates glucose intolerance, lowers serum insulin levels, and decreases tissue glucose uptake in obese/diabetic but not normoglycemic mice. Collectively, these data indicate that chemerin influences glucose homeostasis and may contribute to the metabolic derangements characteristic of obesity and type 2 diabetes.
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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 | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.002 |
| 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".