Serum Chemerin Levels Vary with Time of Day and Are Modified by Obesity and Tumor Necrosis Factor-α
Bibliographic record
Abstract
Chemerin is an adipokine with important regulatory roles in adipogenesis. In humans, serum total chemerin (i.e. prochemerin plus chemerin) levels are positively associated with body mass index and metabolic syndrome. However, the mechanisms that increase serum chemerin concentration are unknown. We hypothesized that chronic low-grade inflammation that occurs in obesity promotes chemerin production by adipocytes. Consistent with this, TNFalpha treatment of 3T3-L1 adipocytes increased bioactive chemerin levels in the cell media as detected using a CMKLR1 cell-based bioassay. This effect was blocked by the protein synthesis inhibitor cycloheximide and protein secretion inhibitor brefeldin A, indicating that TNFalpha may enhance prochemerin synthesis and secretion from adipocytes. In vivo, TNFalpha produced a time-dependent increase in serum total chemerin and bioactive chemerin. Bioactive chemerin was produced by primary mouse adipocytes and hepatocytes. Only primary adipocyte-derived chemerin was responsive to TNFalpha regulation implicating adipocytes as a potential source of elevated serum chemerin after TNFalpha exposure in vivo. In lean mice, serum total chemerin levels oscillated with peak levels occurring during daytime and trough levels at night. Comparatively, leptin- and leptin receptor-deficient obese mice, which have elevated adipose tissue expression of TNFalpha, displayed elevated serum total chemerin levels with an enhanced oscillatory pattern. In summary, our novel results identified TNFalpha as a positive regulator of adipocyte-derived chemerin. We corroborate the finding of elevated chemerin in obese humans by identifying elevated serum levels of total chemerin in two obese mouse models with a corresponding alteration in the rhythmic pattern of serum chemerin levels.
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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".