GITR/GITRL interaction in the lung provides signal 4 for T cell expansion and TRM formation
Bibliographic record
Abstract
Abstract Influenza remains an important global threat and it is important to identify key mechanisms by which the immune system handles the virus. TNFR family members can play a crucial role in determining the magnitude of T cell response against viral infections. Previous studies using TCR transgenic models showed that GITR, an NF-κB activating TNFR family member, is required on CD8 T cells for maximal response against influenza virus. However, it remains unknown how GITR affects the endogenous T cell response during influenza infection. Using competitive mixed bone marrow chimeras, we found that GITR is intrinsically required for the accumulation of effector CD4 and CD8 T cells in the lung and secondary lymphoid organs during influenza infection as well as for optimal lung Trm formation. GITR affected PA224–233-specific CD8 T cells more dramatically than NP366–374-specific CD8 T cells, which exhibited a compensatory increase in TCR affinity in the absence of GITR. GITRL expression was higher on inflammatory APCs compared to classical DCs with peak expression day 3 to day 5 post-infection in the lung. We observed peak GITR expression on CD4 T cells day 7 post-infection in the lung but earlier for CD8 T cells. The finding that both the receptor and the ligand are expressed in the lung raises the possibility that GITR costimulation plays an important role in the lung. Consistently, within the same mouse, lung GITR+/+OT-II had a higher level of pS6 (downstream of GITR signaling) than GITR−/− OT-II, providing evidence of GITR costimulation (signal 4) in the lung. In sum, GITR on CD4 and CD8 T cells plays an important role in their accumulation in the lung, likely through interaction with GITRL on inflammatory rather than classical DCs. Funded by CIHR:MOP133443
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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 | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 0.002 |
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".