Bibliographic record
Abstract
Abstract Description Immune cell cytotoxicity is associated with CD8 cytotoxic T lymphocytes (CTL) and NK cells; however, CD4 T cells can also exhibit cytotoxic properties. In response to viral infections and cancers, cells downregulate MHC-I but maintain MHC-II, thereby preventing CD8-CTL killing and enabling CD4-CTL targeting. Further, CD8-CTL are functionally exhausted during chronic infections, limiting their ability to kill and providing a potential role of CD4-CTL in controlling chronic infection. In fact, we recently identified CD4-CTL activity as a main CD4 T cell function restored by anti-PD-L1 during chronic LCMV infection. Conversely, although CD4-CTL are generated in acute infections, their role is unclear. In acute murine infections, we demonstrate that CD4-CTL are restricted to the Th1 subset, although not all Th1 are cytotoxic, and are associated with the highest level of metabolic and functional activation. In vivo, we show that these cells target B cells via MHC-II in a perforin-dependent manner, and we are uncovering a potential evolutionary role of CD4-CTL to tune B cell immunity and enable a focused immune response. Interestingly, during chronic LCMV infection, CD4 killing fails to form, despite the presence of Th1 cells, which indicates a molecular mechanism restricting the induction of cytolytic activity. Ultimately, we propose that CD4-CTL have important roles at multiple stages of the acute and chronic immune response to tune the quality of antiviral immunity. Topic Categories Viral Immunology (VIR)
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 | 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 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 0.000 |
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".