IL-2 and IL-15 on CD8 T cells during chronic viral infection: The exhaustion program awakens
Bibliographic record
Abstract
Abstract CD8 T cell exhaustion is an immunosuppressive mechanism by which chronic viruses escape adaptive immune response. Yet, the direct implication of cytokines as well as the precise candidates involved in this process have remained elusive. Here we demonstrate the direct contribution of IL-2 and IL-15 on several aspects of CD8 T cell exhaustion. Using a mouse model of chronic viral infection (LCMV clone-13), we show that IL2Rβ (CD122; the receptor chain common to IL-2 and IL-15) is maintained on CD8 T cells during chronicity. Its expression correlates with deeper exhaustion and selectively marks terminally exhausted CD8 T cells in mice and humans. Adoptive transfer of IL2Rβ−/− P14 CD8 T cells (unresponsive to combined IL-2 and IL-15-dependent signals) revealed that IL-2 and IL-15 directly control the expression of a specific pattern of inhibitory receptors and are mandatory for the development of PD-1hi effectors. Further, IL-2 and IL-15 instigate the arrested development of central memory cells seen during antigen persistence and preclude responsiveness to IL-7-dependent signals. Together, we ascribe a novel role to IL-2 and IL-15 as instigators of CD8 T cell exhaustion during chronic viral infection.
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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 | 0.000 |
| 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".