CD4+ T cell-derived IL-10 is independent of IL-27 signaling in a recall response. (CCR3P.220)
Bibliographic record
Abstract
Abstract Surviving influenza infection requires a careful balance of pro-inflammatory signals that promote viral clearance and anti-inflammatory signals that prevent immunopathology. IL-10 is a potent immunosuppressive cytokine that is essential to this balance. Evidence suggests that in CD4+ T cells, IL-10 expression is critically dependent on IL-27 signaling. Here we show in vitro and in vivo that CD4+ cells downregulate gp130, the signal transduction component of the IL-27 receptor, upon activation. Gp130 expression remains low throughout CD4+ T cell contraction and memory, and renders the T cells non-responsive to IL-27 stimulation. Despite this, during secondary activation effector CD4+ T cells express IL-10 at a level equivalent to their primary effector counterparts. Cells genetically deficient for il27ra also fail to express IL-10 during primary activation but are equivalent to wildtype cells during a secondary response. Together our data highlight an IL-27 independent mechanism of IL-10 regulation that is unique to secondary CD4+ T cell activation, and plays a decisive role in the balance between effective immunity and immunopathology during influenza-induced respiratory disease.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.002 |
| Insufficient payload (model declined to judge) | 0.005 | 0.002 |
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".