A Positive Regulatory Role for Suppressor of Cytokine Signaling 1 in IFN-γ-Induced MHC Class II Expression in Fibroblasts
Bibliographic record
Abstract
Suppressor of cytokine signaling 1 (SOCS1) is rapidly induced following stimulation by several cytokines. SOCS1 negatively regulates cytokine receptor signal transduction by inhibiting Janus family tyrosine kinases. Lack of such feedback regulation underlies the premature death of SOCS1(-/-) mice due to unbridled IFN-gamma signaling. We used mouse embryo fibroblasts derived from SOCS1(-/-) mice to investigate the role of SOCS1 in IFN-gamma signaling pathways. SOCS1(-/-) fibroblasts were exquisitely sensitive to the IFN-gamma-mediated growth arrest and showed sustained STAT1 phosphorylation. However, SOCS1(-/-) fibroblasts were inefficient in MHC class II surface expression following IFN-gamma stimulation, despite a marked induction of the MHC class II transactivator and MHC class II gene expression. Retroviral transduction of wild-type SOCS1 relieved the growth-inhibitory effects of IFN-gamma in SOCS1(-/-) fibroblasts by inhibiting STAT1 activation. SOCS1R105K, carrying a mutation within the phosphotyrosine-binding pocket of the Src homology 2 domain, did not inhibit STAT1 phosphorylation, yet considerably inhibited IFN-gamma-mediated growth arrest. Strikingly, expression of SOCS1R105K restored the IFN-gamma-induced MHC class II expression in SOCS1(-/-) cells, indicating that expression of SOCS1 facilitates MHC class II expression in fibroblasts. Our results show that SOCS1, in addition to its negative regulatory role of inhibiting Janus kinases, has an unanticipated positive regulatory function in retarding the degradation of IFN-gamma-induced MHC class II proteins in fibroblasts.
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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".