Phosphatidylserine receptor cooperates with high-density lipoprotein receptor in recognition of apoptotic cells by thymic nurse cells
Bibliographic record
Abstract
The thymus contains many apoptotic cells that arise from the process of positive and negative selection. Both thymic macrophages and thymic nurse cells/nursing thymic epithelial cells (nursing TECs), non-professional phagocytes, recognize and ingest apoptotic cells without inflammation or tissue damage. Previously we reported that human scavenger receptor class B (SR-B1) is involved in recognition of apoptotic thymocytes by nursing TECs. In this study, we examined the expression and role of a phosphatidylserine receptor (PSR). This receptor is believed to participate in the clearance of apoptotic cells. PSR was strongly expressed in nursing TECs. Transforming growth factor-beta augmented the expression of PSR leading to enhanced binding of apoptotic cells to nursing TECs. In nursing TECs, suppressed expression of human SR-B1 with anti-PSR antibody decreased binding of apoptotic thymocytes to nursing TECs. Our results suggest that both PSR and SR-B1 are expressed in nursing TECs and these receptors appear to play a major role in the clearance of apoptotic cells from the thymus.
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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) | 0.001 | 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".