Investigating the role of CX3CR1 in a GITRL- dependent signal 4 checkpoint during LCMV clone 13 infection
Bibliographic record
Abstract
Abstract T cell-APC interactions early during chronic viral infection are critical for determining viral set point and disease outcome. Our recent work (Chang et al. Immunity. 2017) revealed a division of labour whereby monocyte-derived APCs (infAPCs), with low MHC II and CD80/86 expression compared to classical DCs (cDCs), preferentially up-regulate TNF receptor superfamily ligands, GITRL, 4-1BBL, OX40L and CD70, in response to type I interferon (signal 3) to provide a post-priming checkpoint (signal 4) for CD4 T cell responses. While cDCs contribute to signal 1 & 2 during priming in response to LCMV clone 13, GITRL on infAPCs binding to GITR on CD4 T cells results in increased surface expression of pro-survival receptors, including CD25, CD127 and OX40 to sustain Th1 helper cell accumulation, help for virus-specific CD8 T cell responses and viral control. Interestingly, CX3CR1, the receptor for fractalkine, was also upregulated on CD4 T cells by GITR signalling during clone 13 infection. CX3CR1 was recently shown to contribute to tumor-infiltration of CD4-helped CD8 CTLs (Ahrends et al. Immunity. 2017). In the chronic LCMV model, we observed that CX3CR1high virus-specific CD4 T cells in the spleen exhibit a markedly increased effector profile when compared to their CX3CR1int-low counterparts, with both higher frequency and per cell expression of Tbet and IFNg production. To investigate how CX3CR1 on CD4 T cells contributes to CD4 T cell help for the CD8 T cell response, we have crossed CX3CR1 deficient mice with TCR transgenic SMARTA mice, expressing an MHC II-restricted TCR specific for LCMV gp61–80. Overall, our data so far indicate that upregulation of CX3CR1 marks the most activated splenic CD4 Th1 effectors during chronic LCMV 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 | 0.001 |
| 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".