Immune regulation by 4‐1BB and 4‐1BBL: complexities and challenges
Bibliographic record
Abstract
SUMMARY: The tumor necrosis factor receptor family member 4-1BB plays a key role in the survival of activated and memory CD8(+) T cells. Depending on the disease model, 4-1BB can participate at different stages and influence different aspects of the immune response, likely due to the differential expression of receptor and ligand relative to other costimulatory molecules. Studies comparing mild versus severe influenza infection of mice suggest that the immune system uses inducible receptors such as 4-1BB to prolong the immune response when pathogens take longer to clear. The expression of 4-1BB on diverse cell types, evidence for bidirectional as well as receptor-independent signaling by 4-1BBL, the unexpected hyperproliferation of 4-1BB-deficient T cells, and complex effects of agonistic anti-4-1BB therapy have revealed additional roles for the 4-1BB/4-1BBL receptor/ligand pair in the immune system. In this review, we discuss these diverse roles of 4-1BB and its ligand in the immune response, exploring possible mechanisms for the observed complexities and implications for therapeutic applications of 4-1BB/4-1BBL.
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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 | 0.000 |
| 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 | 0.001 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.002 | 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".