Direct demonstration of CD4 T cell cooperation in the primary <i>in vivo</i> generation of CD4 effector T cells
Bibliographic record
Abstract
Many observations bear upon the cellular and molecular requirements for CD4 T cell activation. The interaction of CD4 T cells with dendritic cells (DC), central to the induction of most immune responses, is the most studied. However, leukocytes other than DC can dramatically affect the induction and differentiation of CD4 T cells into effector cells. We recently provided indirect evidence that in vivo CD4 T cooperation facilitates the activation of CD4 T cells. Here, we demonstrate that the activation of CD4 T cells, specific for the hen egg lysozyme (HEL)(105) (-120) peptide, is optimally achieved when BALB/c mice are immunized with additional MHC class II-binding HEL peptides in incomplete Freund's adjuvant. This cooperation cannot be mimicked by the coadministration of LPS or of an agonistic antibody to CD40, at the time of immunization. In contrast, OX40-OX40L interactions are necessary for CD4 T cell cooperation in that an OX40 agonistic antibody can replace, and an OX40L-blocking antibody can abrogate, CD4 T cell cooperation in situations where such cooperation would otherwise enhance the activation of CD4 T cells.
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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) | 0.004 | 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".