Rab17 mediates differential antigen sorting following efferocytosis and phagocytosis
Bibliographic record
Abstract
Macrophages engulf and destroy pathogens (phagocytosis) and apoptotic cells (efferocytosis), and can subsequently initiate adaptive immune responses by presenting antigens derived from engulfed materials. Both phagocytosis and efferocytosis share a common degradative pathway in which the target is engulfed into a membrane-bound vesicle, respectively, termed the phagosome and efferosome, where they are degraded by sequential fusion with endosomes and lysosomes. Despite this shared maturation pathway, macrophages are immunogenic following phagocytosis but not efferocytosis, indicating that differential processing or trafficking of antigens must occur. Mass spectrometry and immunofluorescence microscopy of efferosomes and phagosomes in macrophages demonstrated that efferosomes lacked the proteins required for antigen presentation and instead recruited the recycling regulator Rab17. As a result, degraded materials from efferosomes bypassed the MHC class II loading compartment via the recycling endosome - a process not observed in phagosomes. Combined, these results indicate that macrophages prevent presentation of apoptotic cell-derived antigens by preferentially trafficking efferocytosed, but not phagocytosed, materials away from the MHC class II loading compartment via the recycling endosome pathway.
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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 | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| 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".