Retinol Saturase Knock-Out Mice are Characterized by Impaired Clearance of Apoptotic Cells and Develop Mild Autoimmunity
Bibliographic record
Abstract
Apoptosis and the proper clearance of apoptotic cells play a central role in maintaining tissue homeostasis. Previous work in our laboratory has shown that when a high number of cells enters apoptosis in a tissue, the macrophages that engulf them produce retinoids to enhance their own phagocytic capacity by upregulating several phagocytic genes. Our data indicated that these retinoids might be dihydroretinoids, which are products of the retinol saturase (RetSat) pathway. In the present study, the efferocytosis of RetSat-null mice was investigated. We show that among the retinoid-sensitive phagocytic genes, only transglutaminase 2 responded in macrophages and in differentiating monocytes to dihydroretinol. Administration of dihydroretinol did not affect the expression of the tested genes differently between differentiating wild type and RetSat-null monocytes, despite the fact that the expression of RetSat was induced. However, in the absence of RetSat, the expression of numerous differentiation-related genes was altered. Among these, impaired production of MFG-E8, a protein that bridges apoptotic cells to the αvβ3/β5 integrin receptors of macrophages, resulted in impaired efferocytosis, very likely causing the development of mild autoimmunity in aged female mice. Our data indicate that RetSat affects monocyte/macrophage differentiation independently of its capability to produce dihydroretinol at this stage.
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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) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.005 | 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".