Conserved and Differential Features of TNF Superfamily Ligand Expression on APC Subsets over the Course of a Chronic Viral Infection in Mice
Bibliographic record
Abstract
There is currently much interest in how different APC subsets shape the immune response. We recently described a division of labor between classical dendritic cells (cDC) and inflammatory monocyte-derived APC in provision of costimulatory ligands to T cells early during chronic lymphocytic choriomeningitis clone 13 (LCMV 13) infection in mice. At day 2 of LCMV 13 infection, cDC preferentially express CD80 and CD86, whereas TNF superfamily ligands GITRL, 4-1BBL, CD70, and OX40L are preferentially induced by type I IFN on inflammatory monocyte-derived APC, with minimal expression on cDC. In this study, we further investigate the expression of TNF and B7 family ligands on APC over the course of LCMV 13 infection. OX40L and 4-1BBL remain above baseline through the chronic stage of infection, with predominant expression on inflammatory APC compared with cDC in the spleen, partially blocked by anti-IFN-γR Ab pretreatment. Conversely, CD70, like GITRL, returns to baseline on the APC within a few days postinfection. In the lung, TNF family ligands were also preferentially expressed on inflammatory monocyte-derived APC. CD86 was generally higher on cDC than inflammatory APC in the spleen, but in the lung CD86 was highest on inflammatory APC. Moreover, in the spleen, CD80 levels on different APC subsets fluctuated over the course of the infection. We also show that LPS induction of TNF superfamily ligands is largely mediated through type I IFN. This study highlights the importance of IFNs and monocyte-derived APC in TNF superfamily ligand expression in both secondary lymphoid organs and tissues during chronic viral 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 | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 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".