Expression of lymphotoxin‐αβ on antigen‐specific T cells is required for dendritic cell function
Bibliographic record
Abstract
The lymphotoxin (LT) pathway has been shown to be important in T cell responses and DC homeostasis/activation. LTαβ is a TNF family member upregulated on activated T cells and its receptor, LTβR, is constitutively expressed on DC. Elucidating the role of LTβR signaling in DC function is complicated by the expression of LTβR on both lymphoid stromal cells and DC. Here we have used two methods for inhibiting LTβR signaling. In the first we use an in vivo adoptive transfer system where the expression of the LTβR ligands is manipulated only on the Ag‐specific T cells that interact with and condition Ag‐bearing DC. Using this approach we demonstrate a novel requirement for the LTαβ for optimal DC conditioning during an immune response against protein antigen. In the second system, we have manipulated the expression of LTβR on DC using a mixed bone marrow chimera approach. Here we report a requirement for DC‐intrinsic LTβR signaling for the optimal upregulation of CD86. In addition, DC‐intrinsic LTβR signaling influences DC accumulation in the inflamed LN. Together these data identify a fundamental role for DC‐intrinsic LTβR signaling during T cell immune responses. Funding from CIHR (JLG and LSD) and MS Society of Canada (LSD) supported this research.
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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 | 0.001 | 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".