Immunoregulatory Effects of Interferon-β in Suppression of Th17 cells
Bibliographic record
Abstract
To investigate the immunoregulatory effects of interferon (IFN)-β on CD4+ T cells, we examined the response of CD4+ T cells from IFN-β(+/+) and IFN-β(-/-) mice to CD3/CD28 activation and to differentiation to Th17 lineage, analyzing the expression of signaling effectors, cell surface receptors, production of IL-17, and gene expression profiles. We provide evidence of increased phosphorylation of the membrane proximal kinase associated with TCR activation, ZAP-70, in IFN-β(-/-) T cells compared with IFN-β(+/+) T cells. Anti-CD3/anti-CD28 antibody stimulation of whole splenocytes or CD4+ T cells from IFN-β(-/-) mice results in secretion of IL-17A, in contrast to identical stimulation of cells from IFN-β(+/+) mice, which fails to increase IL-17A production. After CD3/CD28 activation, IFN-β(-/-) CD4+ T cells express higher levels of IRF-4, required for Th17 differentiation, and increased expression of CCR6, IL-23R, IL-6R, and CXCR4, compared with activated IFN-β(+/+) T cells. Notably, cell surface expression of IL-6R and IL-23R is significantly higher in the IFN-β(-/-) CD4+ T cells, with an increased number of double-positive CCR6+IL-23R+ and IL-6R+IL-23R+ CD4+ T cells. On polarization to Th17 lineage, CD4+ T cells from IFN-β(-/-) mice exhibit a more Th17-primed transcriptome compared with CD4+ T cells from IFN-β(+/+) mice. Indeed, when CD4+ T cells from IFN-β(+/+) mice are polarized to Th17 lineage in the presence of IFN-β, many Th17-associated genes are down-regulated. Employing a MOG-peptide-induced experimental autoimmune encephalomyelitis model of multiple sclerosis, we identify a greater proportion of Th17 cells in the lymph nodes of IFN-β(-/-) mice compared with IFN-β(+/+) mice, and increased numbers of CD4+ T cells in the central nervous system of IFN-β(-/-) mice, regardless of the stage of disease. Taken together, our data indicate an immunoregulatory role for IFN-β in the suppression of Th17 cells.
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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 | 0.002 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.002 |
| 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 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".