Mechanisms of H4/ICOS costimulation: effects on proximal TCR signals and MAP kinase pathways
Bibliographic record
Abstract
H4/ICOS is a costimulatory molecule related to CD28. Its effects on early TCR signals have been analyzed in mouse CD4(+) Th2 cells, expressing H4/ICOS at higher levels than Th1 clones. Anti-H4/ICOS antibodies strongly enhanced CD3-mediated tyrosine phosphorylation of ZAP-70, zeta, or Vav, as well as extracellular signal-regulated kinase (ERK), Jun N-terminal kinase (JNK) and p38 MAP kinase activation in these cells. The association of phosphoinositide 3-kinase (PI-3K) to H4/ICOS was enhanced by H4/ICOS cross-linking, and PI-3K inhibitors inhibited ERK and JNK activation and IL-4/IL-10 secretion, but not p38 MAP kinase or ZAP-70 activation. H4/ICOS-mediated activation of JNK, but not ERK or p38, is partially dependent on the expression of CD4 by the cells, whereas H4/ICOS costimulation is partially independent on CD28 expression. Cytochalasin D, an inhibitor of actin polymerization, inhibited ZAP-70, MAP kinase activation, or IL-4/IL-10 secretion. Neither cyclosporin A nor inhibitors of PKC produced detectable inhibition of ZAP-70 phosphorylation or MAP kinase activation in these Th2 cells. Cyclosporin A strongly inhibited IL-4, but not IL-10 secretion. ERK or JNKinhibitors partially inhibited IL-4 and IL-10 secretion, while PKC or p38 inhibitors had no significant effects on IL-4 or IL-10 secretion. Taken together, our data show clear similarities of costimulation mechanisms between H4/ICOS and CD28 during the early steps of TCR activation.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| 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 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".