Gammaherpesvirus Persistence Alters Key CD8 T-Cell Memory Characteristics and Enhances Antiviral Protection
Bibliographic record
Abstract
In herpesvirus infections, the virus persists for life but is contained through T-cell-mediated immune surveillance. How this immune surveillance operates is poorly understood. Recent studies of other persistent infections have indicated that virus persistence is associated with functional deficits in the CD8(+) T-cell response. To test whether this is the case in a herpesvirus infection, we used a mutant murine gammaherpesvirus that is defective in its ability to persist in the host. By comparing the immune response to this virus with a revertant virus that can persist, we were able to dissect the changes in the antiviral CD8(+) T-cell response that are induced by virus persistence. Surprisingly, persistently infected mice controlled a secondary challenge infection more rapidly than nonpersistently infected mice, indicating enhanced rather than diminished effector functions. Consistent with this, virus-specific CD8 T cells from these mice exhibited faster upregulation of the cytotoxic mediator granzyme B. Another unexpected finding was that CD8(+) T cells from neither infection responded efficiently to homeostatic cytokines. The unresponsiveness of the memory cells from the nonpersistently infected mice appears to be linked to the prolonged replication of virus within the lungs. Other changes seen in different chronic infection models were also observed, such as changes in Bcl-2 levels, interleukin-2 production, and the immunodominance hierarchy. These data show persistence of gammaherpesvirus type 68 alters the properties of CD8(+) T cells and illustrates that immune surveillance does not require CD8 T cells with the same attributes as "classical" memory CD8(+) 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) | 0.000 | 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) | 0.001 | 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".