Regulation of eotaxin‐3/CCL26 expression in human monocytic cells
Bibliographic record
Abstract
Eotaxin-3/CCL26 is an agonist for chemokine receptor 3 (CCR3) and a natural antagonist for CCR1, CCR2 and CCR5. CCL26 expression by non-haematopoietic cells has been well documented; however, no studies to date have demonstrated CCL26 expression by leucocytes. In this study, we investigated the ability of human monocytic cells to produce CCL26 in response to cytokines. We found that interleukin-4 (IL-4) increased the expression of CCL26 messenger RNA (mRNA) and protein in U937 cells, in human monocytes and in human monocyte-derived macrophages. Tumour necrosis factor-alpha (TNF-alpha) and interleukin-1beta (IL-1beta) alone did not induce CCL26 expression, yet these pro-inflammatory cytokines synergized with IL-4 to increase CCL26 protein expression. Signal transducer and activator of transcription 6 (STAT6) was not affected by costimulation with TNF-alpha, suggesting that the synergy between IL-4 and TNF-alpha occurs at a step downstream of STAT6 activation. Co-incubation of interferon-gamma (IFN-gamma) with IL-4 had no effect on CCL26 protein release. By contrast, pretreatment with IFN-gamma decreased total STAT6 protein, blocked IL-4-mediated STAT6 phosphorylation and decreased IL-4-mediated CCL26 mRNA expression and protein release. These data show that IL-4 and pro-inflammatory cytokines such as TNF-alpha, IL-1beta and IFN-gamma regulate CCL26 synthesis in human monocytic cells, which may be important in regulating monocyte inflammatory responses.
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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 | 0.001 |
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".