A molecular map of lymph node blood vascular endothelium at single cell resolution
Bibliographic record
Abstract
Abstract Blood vascular endothelial cells (BECs) control the immune response by regulating immune cell recruitment, metabolite exchange and blood flow in lymphoid tissues. However, the diversity of BEC and their origins during immune angiogenesis remain poorly understood. Here we profile transcriptomes of BEC from mouse peripheral lymph nodes and map key phenotypes to the vasculature. Our analysis identifies multiple novel subsets including a venous population whose gene signature predicts an unexpectedly selective role in myeloid cell (vs lymphocyte) recruitment to the medulla, confirmed by 2 photon videomicroscopy. We define five phenotypes of capillary lining BEC including a capillary resident regenerative population (CRP) that displays stem cell and migratory gene signatures and contributes to homeostatic BEC turnover and to vascular neogenesis after immunization. Trajectory analyses reveal retention of developmental programs along a progression of cellular phenotypes from CRP to mature venous and arterial BEC subsets. Overall, our single cell atlas provides a molecular blueprint of the lymph node blood vasculature and defines subset specialization for immune cell recruitment and vascular homeostasis.
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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".