IFNγ-dependent SOCS3 expression inhibits IL-6-induced STAT3 phosphorylation and differentially affects IL-6 mediated transcriptional responses in endothelial cells
Bibliographic record
Abstract
IL-6 has pro- and anti-inflammatory effects and is involved in endothelial cell (EC) dysfunction. The anti-inflammatory effects of IL-6 are mediated by signal transducer and activator of transcription-3 (STAT3), which is importantly controlled by suppressor of cytokine signaling 3 (SOCS3). Therefore, cytokines that modulate SOCS3 expression might inhibit the anti-inflammatory effects of IL-6. We hypothesized that in EC, interferon-gamma (IFNgamma)-induced SOCS3 expression leads to inhibition of IL-6-induced STAT3 activation and IL-6-dependent expression of anti-, but not pro-inflammatory, target genes. IFNgamma activated STAT1 and STAT3 and increased SOCS3 expression in EC. IL-6 only activated STAT3 and induced SOCS3 expression. IFNgamma pretreatment of EC inhibited IL-6-induced STAT3 activation accompanied by increased SOCS3 protein. Inhibition of SOCS3 expression, using costimulation, Act-D, and small interfering RNA (siRNA), subsequently implicated the importance of IFNgamma-induced SOCS3 in this phenomenon. Pretreatment of EC with IFNgamma also affected the transcriptional program induced by IL-6. We identified 1) IL-6 anti-inflammatory target genes that were inhibited by IFNgamma, 2) IFNgamma-target genes of pro-inflammatory nature that were increased in response to IL-6 in the presence of IFNgamma, and 3) a set of target genes that were increased upon IL-6 or IFNgamma alone, or combined IFNgamma and IL-6. In summary, by increasing SOCS3 expression in EC, IFNgamma can selectively inhibit STAT3-dependent IL-6 signaling. This in turn leads to decreased expression of some EC protective genes. In contrast, other genes of pro-inflammatory nature are not inhibited or even increased. This IFNgamma-induced shift in IL-6 signaling to a pro-inflammatory phenotype could represent a novel mechanism involved in EC dysfunction.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 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) | 0.000 | 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 teacher head, 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".