GITR potentiates anti-viral T cell immunity by limiting regulatory T cells (P1015)
Bibliographic record
Abstract
Abstract The immune system must be tightly balanced to control infection while avoiding immune pathology. We investigated the role of the glucocorticoid-induced tumour necrosis factor receptor (GITR) during infection of mice with persistent lymphocytic choriomeningitis virus (LCMV) clone 13 infection. Infection of wild-type (WT) and GITR-/- mice with LCMV revealed that GITR plays a critical role in T cell responses and viral control. At 8 days post-infection (dpi), GITR-/- mice showed 3-fold fewer LCMV-specific CD8+ T cells, and these cells expressed significantly higher levels of inhibitory receptors Tim-3 and PD-1. These defects became more striking at 45 dpi, when there was also a substantial deficit in multifunctional (IFNγ+CD107a+TNFα+) CD8+ T cells in GITR-/- relative to WT mice. GITR-/- mice had 35-fold higher viral load in the kidney 8 dpi and 10-fold higher at day 45. Depletion of CD4+ T cells ameliorated the immune defects observed in GITR-/- mice, suggesting that a CD4+ population largely contributed to the GITR-/- phenotype. Strikingly, there were 4- to 5-fold more CD4+Foxp3+ regulatory T cells (Tregs) in the spleen and lymph nodes of GITR-/- mice 8 dpi, and only slightly more at 45 dpi. The dramatic increase in Treg numbers in GITR-/- mice 8 dpi is accompanied by a more suppressive phenotype. These studies demonstrate that GITR plays an indirect, yet critical role in CD8+ T cell responses and viral control by limiting the accumulation and function of Foxp3+ Tregs.
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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) | 0.001 | 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 | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 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".