The Number of Responding CD4 T Cells and the Dose of Antigen Conjointly Determine the Th1/Th2 Phenotype by Modulating B7/CD28 Interactions
Bibliographic record
Abstract
Our previous in vivo studies show that both the amount of Ag and the number of available naive CD4 T cells affect the Th1/Th2 phenotype of the effector CD4 T cells generated. We examined how the number of OVA-specific CD4 TCR transgenic T cells affects the Th1/Th2 phenotype of anti-SRBC CD4 T cells generated in vivo upon immunization with different amounts of OVA-SRBC. Our observations show that a greater number of Ag-dependent CD4 T cell interactions are required to generate Th2 than Th1 cells. We established an in vitro system that recapitulates our main in vivo findings to more readily analyze the underlying mechanism. The in vitro generation of Th2 cells depends, as in vivo, upon both the number of responding CD4 T cells and the amount of Ag. We demonstrate, using agonostic/antagonistic Abs to various costimulatory molecules or their receptors, that the greater number of CD4 T cell interactions, required to generate Th2 over Th1 cells, does not involve CD40, OX40, or ICOS costimulation, but does involve B7/CD28 interactions. A comparison of the level of expression of B7 molecules by APC and CD4 T cells, under different conditions resulting in the substantial generation of Th1 and Th2 cells, leads us to propose that the critical CD28/B7 interactions, required to generate Th2 cells, may directly occur between CD4 T cells engaged with the same B cell acting as an APC.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.002 |
| 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".