Divergent Mechanisms Utilized by SOCS3 to Mediate Interleukin-10 Inhibition of Tumor Necrosis Factor α and Nitric Oxide Production by Macrophages
Bibliographic record
Abstract
The cytokine interleukin-10 (IL-10) potently inhibits macrophage function through activation of the transcription factor STAT3. The expression of SOCS3 (suppressor of cytokine signaling-3) has been shown to be induced by IL-10 in a STAT3-dependent manner. However, the relevance of SOCS3 expression to the anti-inflammatory effect of IL-10 on macrophages has been controversial. Through kinetic analysis of the requirement for SOCS3 in IL-10 inhibition of lipopolysaccharide (LPS)-stimulated tumor necrosis factor-alpha (TNFalpha) transcription and translation, SOCS3 was found to be necessary for TNFalpha expression during the early phase, but not the late phase of IL-10 action. SOCS3 was essential for IL-10 inhibition of LPS-stimulated production of iNOS (inducible nitric-oxide synthase) protein and nitric oxide (NO). To determine the domains of SOCS3 protein important in mediating these effects, SOCS3-/- macrophages were reconstituted with SOCS3 mutated for the SH2, KIR, SOCS box domains, and tyrosines 204 (Tyr204) and 221 (Tyr221). The SH2 domain, SOCS box, and both Tyr204 and Tyr221 were required for IL-10 inhibition of TNFalpha mRNA and protein expression, but interestingly the KIR domain was necessary only for IL-10 inhibition of TNFalpha protein expression. In contrast, Tyr204 and Tyr221 were the only structural features of SOCS3 that were necessary in mediating IL-10 inhibition of iNOS protein expression and NO production. These data define SOCS3 as an important mediator of IL-10 inhibition of macrophage activation and that SOCS3 interferes with distinct LPS-stimulated signal transduction events through differing mechanisms.
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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 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".