The role of GITR in the anti‐influenza CD8 memory T cell response
Bibliographic record
Abstract
Tumor necrosis receptor associated factor 1 (TRAF1) is an adaptor protein recruited to several costimulatory tumor necrosis factor receptor (TNFR) superfamily members, including 4‐1BB, CD30 and glucocorticoid‐induced TNF receptor family‐related gene (GITR). Work from our lab has shown that in the absence of TRAF1, a 7–8 fold defect in antigen‐independent memory CD8 T cell survival resulted 3 weeks following transfer into naïve mice. Under similar conditions, the lack of 4‐1BBL results in a 2–3 fold defect, suggesting that other than 4‐1BB at least 1 other TRAF1‐linked TNFR family member may contribute to CD8 T cell survival. Here we show that IL‐15, a cytokine involved in memory T cell survival, induces the co‐expression of GITR and 4‐1BB on CD8 memory T cells, suggesting a possible synergy between these receptors. In order to test the role of GITR on CD8 memory T cells in vivo we infected wildtype and GITR −/− mice intranasally with influenza A/X31. Whereas similar numbers of influenza specific CD8 T cells were observed in the lungs and draining lymph nodes of WT and GITR −/− mice at the peak of the primary response, reduced numbers were seen in the spleen of GITR −/− mice at this timepoint. When mice were challenged with influenza A/PR8 30 days after priming, GITR −/− mice showed decreased numbers of influenza specific CD8 T cells in the lung with a similar trend observed in draining LN. This defect is being investigated further using a transgenic model where GITR is absent only on CD8 T cells. This study was supported by a grant from the Canadian Institute of Health Research to T.H.W. L.M.S. is the recipient of a doctorate research award from the Fonds de la recherche en santé du Québec.
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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 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".