Type I interferon regulates GITRL on infiltrating monocyte-derived inflammatory APC to establish early viral control during chronic LCMV infection
Bibliographic record
Abstract
Abstract Disease outcome in chronic viral infections correlates with early viral set-point established by the initial T cell response. Previous studies showed that GITR, an NFκB-activating TNFR family member, sustains CD4 T cell accumulation and help for CD8 T cells at the onset of chronic LCMV infection. While the endogenous effect of GITR on CD8 T cells is largely attributed to enhanced early CD4 T cell help, CD8 T cells are directly responsive to exogenous GITR agonist. How endogenous GITR co-stimulation selectively impacts CD4 T cells early post-LCMV infection (p.i.), however, remains elusive. We hypothesize that CD4 and CD8 T cells interact with distinct antigen presenting cells (APC) and that the availability of GITRL underscores the regulation of GITR co-stimulation. Herein, we identify inflammatory monocyte-derived DC and macrophages (infMΦ) as the dominant GITRL-expressing APC with approximately 5 times higher levels compared to classical DC during LCMV infection. A preliminary experiment showed that deleting exon 2 of GITRL using MΦ-specific Lys-M-Cre recapitulates the marked reduction in Th1 response against LCMV observed in the whole-body GITR knockout. GITRL exhibits similar expression kinetics to type I interferon (IFN-I) with an early but transient peak at 24–48 hours p.i. IFN-I is a potent inducer of GITRL on thioglycollate-elicited peritoneal macrophages (TG-MΦ) ex vivo. Moreover, blockade of IFN-I receptor abrogates up-regulation of GITRL during LCMV infection of TG-MΦ in vitro, as well as on infMΦ in vivo. Together, the current study suggests a critical role for infMΦ in GITR-dependent immunity to LCMV and identifies IFN-I as a key regulator of GITRL on infMΦ in vivo.
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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 | 0.001 |
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".