CMKLR1 activation ex vivo does not increase proportionally to serum total chemerin in obese humans
Bibliographic record
Abstract
Prochemerin is the inactive precursor of the adipokine chemerin. Proteolytic processing is obligatory for the conversion of prochemerin into active chemerin and subsequent regulation of cellular processes via the chemokine-like receptor 1 (CMKLR1). Elevated plasma or serum chemerin concentrations and differential processing of prochemerin have been reported in obese humans. The impact of these changes on CMKLR1 signalling in humans is unknown. The objective of this pilot study was to develop a cellular bioassay to measure CMKLR1 activation by chemerin present in human serum and to characterise how obesity modifies serum activation of CMKLR1 under fasted and fed conditions. Blood samples were collected from control (N = 4, BMI 20-25) and obese (N = 4, BMI >30) female subjects after an overnight fast (n = 2) and at regular intervals (n = 7) following consumption of breakfast over a period of 6 h. A cellular CMKLR1-luminescent reporter assay and a pan-chemerin ELISA were used to determine CMKLR1 activation and total chemerin concentrations, respectively. Serum total chemerin concentration (averaged across all samples) was higher in obese vs control subjects (17.9 ± 1.8 vs 10.9 ± 0.5 nM, P < 0.05), but serum activation of CMKLR1 was similar in both groups. The CMKLR1 activation/total chemerin ratio was lower in obese vs control subjects (0.33 ± 0.04 vs 0.58 ± 0.05, P < 0.05). After breakfast, serum total chemerin or CMKLR1 activation did not differ from baseline values. In conclusion, the unexpected observation that obese serum activation of CMKLR1 did not match increased total chemerin concentrations suggests impaired processing to and/or enhanced degradation of active chemerin in serum of obese humans.
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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 | 0.001 |
| 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".