Single-Cell Analysis Reveals Heterogeneity of High Endothelial Venules and Different Regulation of Genes Controlling Lymphocyte Entry to Lymph Nodes
Bibliographic record
Abstract
High-endothelial venules (HEVs) are specialized blood vessels allowing recirculation of naive lymphocytes through lymphoid organs. Here, using full-length, single-cell RNA sequencing, RNA fluorescence in situ hybridization (FISH), flow cytometry, and immunohistofluorescence, we reveal the heterogeneity of HEVs in adult mouse peripheral lymph nodes (PLNs) under conditions of homeostasis, antigenic stimulation, and after inhibition of lymphotoxin-β receptor (LTβR) signaling. We demonstrate that HEV endothelial cells are in an activated state during homeostasis, and we identify the genes characteristic of the differentiated HEV phenotype. We show that LTβR signaling regulates many HEV genes and pathways in resting PLNs and that immune stimulation induces a global and temporary inflammatory phenotype in HEVs without compromising their ability to recruit naive lymphocytes. Most importantly, we uncover differences in the regulation of genes controlling lymphocyte trafficking, Glycam1, Fut7, Gcnt1, Chst4, B3gnt3, and Ccl21a, that have implications for HEV function and regulation in health and disease.
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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) | 0.000 | 0.000 |
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".