Towards an integrative approach to understanding the role of chemerin in human health and disease
Bibliographic record
Abstract
Chemerin is an adipocyte-secreted protein with autocrine/paracrine roles on adipose development and function as well as endocrine roles in metabolism and immunity. Following prochemerin secretion, protease-mediated generation of chemerin isoforms with a range of biological activities is a key regulatory mechanism controlling local, context-specific chemerin bioactivity. Together, experimental and clinical data indicate that localized and/or circulating chemerin expression and activation are elevated in numerous metabolic and inflammatory diseases including psoriasis, obesity, type 2 diabetes, metabolic syndrome and cardiovascular disease. These elevations are positively correlated with deleterious changes in glucose, lipid, and cytokine homeostasis, and may serve as a link between obesity, inflammation and other metabolic disorders. This review highlights the current state of knowledge regarding chemerin expression, processing, biological function and relevance to human disease, particularly with respect to adipose tissue development, inflammation, glucose homeostasis and cardiovascular disease. Furthermore, it discusses study variability, deficiencies in current measurement, and questions concerning chemerin function in disease, with a special emphasis on techniques and tools used to properly assess chemerin biology. An integration of basic and clinical research is key to understanding how chemerin influences disease pathobiology, and whether modulation of chemerin levels and/or activity may serve as a potential method to prevent and treat metabolic diseases.
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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 | 0.002 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.002 | 0.004 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.002 | 0.004 |
| Insufficient payload (model declined to judge) | 0.004 | 0.003 |
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".