The contextual role of <scp>TNFR</scp> family members in <scp>CD</scp>8<sup>+</sup> T‐cell control of viral infections
Bibliographic record
Abstract
Immunity to viruses must be tightly controlled to avoid pathology. Receptors and ligands of the tumor necrosis factor (TNF) family play important roles in controlling lymphocyte activation and survival during an immune response. The role of specific TNF receptor (TNFR) family members in antiviral immunity depends on the stage of the immune response and can vary with the virus type and its virulence. Here, we focus on five members of the TNFR family that are prominently expressed on CD8(+) T cells during viral infections, namely, 4-1BB (CD137), CD27, OX40 (CD134), GITR, and TNFR2. 4-1BB, CD27, OX40, and GITR have primarily prosurvival roles for CD8(+) T cells during viral infection, although under some circumstances 4-1BB, GITR, or CD27 signals can limit immunity. Although TNFR2 can be costimulatory under some circumstances, its main role in CD8(+) T-cell responses during viral infection appears to be in contraction of the response. Several TNF family ligands are being explored as adjuvants for viral vaccines, and agonistic antibodies to TNFR family members are being investigated for immunotherapy of chronic viral infection alone and in combination with checkpoint blockade. Such therapies will require thorough and specific optimization to avoid pathology induced by hyperstimulation of these pathways.
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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 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".