Inducible T‐cell co‐stimulator: Signaling mechanisms in T follicular helper cells and beyond
Bibliographic record
Abstract
Human patients with homozygous null mutations in the ICOS gene suffer from recurrent infections due to humoral immune defects. Studies on human patients and mouse models have shown that inducible T-cell co-stimulator (ICOS)-deficient individuals cannot form T follicular helper (Tfh) cells, a group of CD4 T cells that migrate into B cell follicles and facilitate germinal center (GC) reactions. ICOS-induced phosphoinositide 3-kinase signaling pathways have been shown to play critical roles in Tfh programming, migration of Tfh cells into the GC, and delivery of T cell help during Tfh-GC B cell conjugation. These processes are also assisted by ICOS-mediated intracellular calcium mobilization and TANK-binding kinase 1 signaling. However, ICOS signaling also has stimulatory roles in T regulatory cells and innate lymphoid cells (ILCs), providing another layer of complexity. In this review, we discuss cell-type-specific signaling mechanisms utilized by ICOS in Tfh cells, T regulatory cells, and ILCs. Whenever relevant, we compare the roles and signaling pathways of ICOS and CD28. Understanding ICOS signal transduction mechanisms used by distinct immune subsets at different stages of immune responses or disease progression may help improve vaccination protocols, treat autoimmune diseases, and enhance cancer immunotherapy.
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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) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 0.003 |
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".