Chronic viral infection: the perfidious role of IL-2 and IL-15 on CD8 T cell exhaustion (IRM4P.500)
Bibliographic record
Abstract
Abstract CD8 T cell exhaustion is a major immuno-regulatory mechanism by which chronic viruses escape the immune response. However, little is known on the factors regulating the unresponsiveness of CD8 T cells is this context. Here, we investigated the combined role of IL-2 and IL-15, two common gamma chain-dependent cytokines, on CD8 T cell differentiation and exhaustion during a chronic viral infection. We performed adoptive transfer of WT or IL-2RβKO P14 CD8 T cells (unresponsive to both IL-2 and IL-15 signals) in mice challenged with LCMV clone 13. Initially, IL-2Rβ-signals were critical for short-lived effector cell differentiation. IL-2 and IL-15 conditioned optimal proliferation of early effector CD8 T cells and promoted their cytotoxic functions. Interestingly, over the chronic phase, IL-2Rβ-signals dramatically worsened CD8 T cell exhaustion. IL-2 and IL-15 sustained the expression of several inhibitory receptors and fostered the development of the highly exhausted PD-1hi progeny population. Finally, IL-2Rβ-signals precluded central memory CD8 T cell differentiation capable of homeostatic proliferation and robust secondary expansion. Altogether, these data demonstrated for the first time an important deleterious effect of IL-2 and IL-15 on the CD8 T cell response to a chronic viral infection. Reconsidering their role in this context may provide new insights for therapeutic regimens against chronic viruses.
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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".