ICOS promotes T cell activation and function beyond phosphoinositide 3-kinase signaling (126.11)
Bibliographic record
Abstract
Abstract ICOS delivers an important costimulation to promote T-cell activation and function. Using a knock-in mouse strain, termed ICOS-YF, in which the cytoplasmic tail of ICOS cannot activate phosphoinositide 3-kinase (PI3K), we have shown that ICOS-PI3K signaling axis is critical for generation of follicular helper T cells. Although ICOS can potentiate TCR-mediated calcium flux in a PI3K-independent manner, its biological significance is unclear. To address this question, we studied the function of ICOS-YF T cells in comparison with ICOS wild-type (WT) and knock-out (KO) T cells in MHC-mismatched bone marrow transplantation (BMT) models. We found that CD4 T cells from ICOS-YF and KO mice were similarly impaired in their capacity to induce acute graft-versus-host disease (GVHD). In contrast, the pathogenic capacity of CD8 T cells from ICOS-YF mice was comparable to that of WT cells, whereas ICOS KO CD8 T cells were less pathogenic. In vitro, we observed that in both CD4 and CD8 T cells ICOS could potentiate TCR-mediated calcium flux in a PI3K-independent manner. These results suggest that although both CD4 and CD8 T cells depend on ICOS costimulation, the downstream signaling pathways they utilize are distinct: CD4 T cells depend on ICOS-PI3K signaling whereas CD8 T cells are more dependent on PI3K-independent pathways, probably calcium signaling. Taken together, our study reveals a complexity in ICOS signaling mechanisms in GVHD.
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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 | 0.000 |
| 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 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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".