Chemerin, a Novel Adipokine That Regulates Adipogenesis and Adipocyte Metabolism
Bibliographic record
Abstract
Obesity is an alarming primary health problem and is an independent risk factor for type II diabetes, cardiovascular diseases, and hypertension. Although the pathologic mechanisms linking obesity with these co-morbidities are most likely multifactorial, increasing evidence indicates that altered secretion of adipose-derived signaling molecules (adipokines; e.g. adiponectin, leptin, and tumor necrosis factor alpha) and local inflammatory responses are contributing factors. Chemerin (RARRES2 or TIG2) is a recently discovered chemoattractant protein that serves as a ligand for the G protein-coupled receptor CMKLR1 (ChemR23 or DEZ) and has a role in adaptive and innate immunity. Here we show an unexpected, high level expression of chemerin and its cognate receptor CMKLR1 in mouse and human adipocytes. Cultured 3T3-L1 adipocytes secrete chemerin protein, which triggers CMKLR1 signaling in adipocytes and other cell types and stimulates chemotaxis of CMKLR1-expressing cells. Adenoviral small hairpin RNA targeted knockdown of chemerin or CMKLR1 expression impairs differentiation of 3T3-L1 cells into adipocytes, reduces the expression of adipocyte genes involved in glucose and lipid homeostasis, and alters metabolic functions in mature adipocytes. We conclude that chemerin is a novel adipose-derived signaling molecule that regulates adipogenesis and adipocyte metabolism.
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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 | 0.000 |
| 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".