Loss of STAT3 in CD4+ T Cells Prevents Development of Experimental Autoimmune Diseases
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Bibliographic record
Abstract
Th17 cells are implicated in CNS autoimmune diseases. We show that mice with targeted-deletion of Stat3 in CD4(+) T cells (CD4(Stat3)(-/-)) do not develop experimental autoimmune uveoretinitis (EAU) or experimental autoimmune encephalomyelitis. Defective Th17 differentiation noted in CD4(Stat3)(-/-) mice is compensated by exaggerated increases in Foxp3-, IL-10-, IL-4-, and IFN-gamma-expressing T cells, suggesting critical roles of STAT3 in shaping Ag-specific CD4(+) T cell repertoire. In mice with EAU, a high percentage of IL-17-expressing T cells in their peripheral lymphoid organs also secrete IFN-gamma while these double-expressors are absent in CD4(Stat3)(-/-) and wild-type mice without EAU, raising the intriguing possibility that uveitis maybe mediated by Th17 and IL-17-expressing Th1 cells. Resistance of Stat3-deficient mice to EAU derives in part from an inability of uveitogenic Th17 and Th1 cells to enter eyes or brain of the CD4(Stat3)(-/-) mouse because of the reduction in the expression of activated alpha4/beta1 integrins on CD4(Stat3)(-/-) T cells. Adoptive transfer of activated interphotoreceptor retinoid-binding protein-specific uveitogenic T cells induced in CD4(Stat3)(-/-) mice a severe EAU characterized by development of retinal folds, infiltration of inflammatory cells into the retina, and destruction of retinal architecture, underscoring our contention that the loss of STAT3 in CD4(+) T cells results in an intrinsic developmental defect that renders CD4(Stat3)(-/-) resistant to CNS inflammatory diseases. STAT3 requirement for IL-17 production by Th17, generation of double positive T cells expressing IL-17 and IFN-gamma, and for T cell trafficking into CNS tissues suggests that STAT3 may be a therapeutic target for modulating uveitis, sceritis, or multiple sclerosis.
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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 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 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 it