Interferon beta-1b increases interleukin-10 in a model of T cell–microglia interaction
Bibliographic record
Abstract
BACKGROUND: The modes of action of interferon beta (IFN-beta) in MS remain unclear, but enhanced levels of the anti-inflammatory cytokine interleukin-10 (IL-10) in the CSF of patients with MS may be a marker of its prognostic efficacy. OBJECTIVE: To examine potential mechanisms by which IL-10 may be increased by IFN-ss in the milieu of the CNS. METHODS: A model of T cell interaction with microglia in vitro was used. Production of cytokines was monitored by measuring the levels of various cytokine proteins, using ELISA. RESULTS: Pretreatment of T cells with IFN-beta potentiates the production of IL-10 when they interact with adult human microglia, human fetal microglia, or U937 cells treated with phorbol-12-myristate-13-acetate (PMA) and IFN-gamma. The enhancing effect of IFN-beta on IL-10 requires cell-cell contact, but does not seem to depend on pathways implicated in microglia-T cell interactions, involving CD40, CD23, and B7. In contrast to IL-10, IFN-beta inhibits the production of other cytokines, including tumor necrosis factor-alpha (TNF-alpha), IL-1beta, IL-4, IL-12, and IL-13. CONCLUSIONS: The increase of IL-10 in microglia-T cell interaction by IFN-beta together with a decrease of other cytokines may lead to a noninflammatory milieu in the CNS. This mechanism could contribute to the efficacy of IFN-beta in MS.
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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) | 0.000 | 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) | 0.002 | 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".