Factors controlling the tolerogenic phenotype of lymphatic endothelial cells.
Bibliographic record
Abstract
Abstract The prevailing model of peripheral tolerance necessitates tissue-resident dendritic cells migrating to lymph nodes and cross presenting self-antigen to T cells, resulting in their deletion or anergy. Our lab has identified a novel mechanism of peripheral tolerance involving a subset of lymph node stromal cells called lymphatic endothelial cells (LEC). LEC in the lymph node induce peripheral tolerance by presenting epitopes derived from peripheral tissue antigens (PTAs) in conjunction with expression of PD-L1, leading to CD8 T cell deletion. However, PTAs and PD-L1 are not expressed on LEC in the colon or diaphragm. We performed RNAseq analysis on LEC from lymph node and diaphragm to identify differences in expression of transcription factors that might control expression of PD-L1 and PTA. We found that Spi-B is the most differentially expressed transcription factor in the lymph node compared to the diaphragm, with a fold change of over 500. Spi-B has been implicated in the development and function of medullary thymic epithelial cells, a key cell type in central tolerance. Lymph node LEC harvested from Spi-B deficient mice have a significant shift in markers associated with LEC tolerogenicity. Expression levels of PD-L1, ICAM-1, MAdCAM-1, and LTbR delineate different lymph node LEC subpopulations that vary in their ability to express PTAs and tolerize CD8 T cells. LEC from Spi-B deficient mice have decreased MAdCAM-1 expression and increased LTbR and ICAM-1 expression suggesting a population shift of non-tolerogenic lymph node LEC to tolerogenic lymph node LEC. This data suggests Spi-B may be involved in a negative feedback mechanism to limit the number of tolerogenic LEC during development.
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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 | 0.000 |
| 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".