A Transendocytosis Model of CTLA-4 Function Predicts Its Suppressive Behavior on Regulatory T Cells
Bibliographic record
Abstract
Manipulation of the CD28/CTLA-4 pathway is at the heart of a number of immunomodulatory approaches used in both autoimmunity and cancer. Although it is clear that CTLA-4 is a critical regulator of T cell responses, the immunological contexts in which CTLA-4 controls immune responses are not well defined. In this study, we show that whereas CD80/CD86-dependent activation of resting human T cells caused extensive T cell proliferation and robust CTLA-4 expression, in this context CTLA-4 blocking Abs had no impact on the response. In contrast, in settings where CTLA-4(+) cells were present as "regulators," inhibition of resting T cell responses was dependent on CTLA-4 expression and specifically related to the number of APC. At low numbers of APC or low levels of ligand, CTLA-4-dependent suppression was highly effective whereas at higher APC numbers or high levels of ligand, inhibition was lost. Accordingly, the degree of suppression correlated with the level of CD86 expression remaining on the APC. These data reveal clear rules for the inhibitory function of CTLA-4 on regulatory T cells, which are predicted by its ability to remove ligands from 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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 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 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".