Type I interferon induced by lymphotoxin-beta receptor signaling on dendritic cell is crucial for CD8 T cell infiltration into effector site by modulating the expression of tissue specific adhesion molecule VLA4 (P5045)
Bibliographic record
Abstract
Abstract In non-infectious settings with minimal inflammatory stimulus, CD4 T cell help is needed for dendritic cells (DC) to cross-prime antigen in order to elicit a CD8 T cell response. Activated CD4 T cells express CD40-ligand (CD40L) and lymphotoxin-α1β2 (LTαβ), which interacts with their respective TNF receptors, CD40 and lymphotoxin-β receptor (LTβR) on DC, thereby significantly increases the DC immunogenic potential. Our early work showed that LTβR signaling induces Type I IFN expression in DC which facilitates CD8 T cell expansion against soluble protein antigen. In this study, we identified that LTβR signals through TNF receptor-associated factor (TRAF)-3 for interferon regulatory factor (IRF)-3 phosphorylation and Type I IFN production. Furthermore, using an inducible diabetes model through the transfer of activated DC, we found that LTβR signaling on DC is absolutely required for the proper priming of CD8 T cells and diabetes induction. We further showed that LTβR-induced Type I IFN affect the expression of the adhesion molecule VLA-4 on antigen specific CD8 T cells and it affects their ability to infiltrate into the pancreas. LTβR deficient DC fail to induce diabetes, and the provision of exogenous IFN-α was sufficient to rescue the diabetes status. Together, these results describe a novel role for LTβR in the induction of Type I IFN by DC, and demonstrate its relevance in an autoimmune setting.
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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) | 0.002 | 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".