Phagocytosis of Necrotic Debris at Sites of Injury and Inflammation
Bibliographic record
Abstract
Clearance of cellular debris is required to maintain the homeostasis of multicellular organisms. It is intrinsic to processes such as tissue growth and remodeling, regeneration and resolution of injury and inflammation. Most of the removal of effete and damaged cells is performed by macrophages and neutrophils through phagocytosis, a complex phenomenon involving ingestion and degradation of the disposable particles. The study of the clearance of cellular debris has been strongly biased towards the removal of apoptotic bodies; as a result, the mechanisms underlying the removal of necrotic cells have remained relatively unexplored. Here, we will review the incipient but growing knowledge of the phagocytosis of necrotic debris, from their recognition and engagement to their internalization and disposal. Critical insights into these events were gained recently through the development of new in vitro and in vivo models, along with advances in live-cell and intravital microscopy. This review addresses the classes of “find-me” and “eat-me” signals presented by necrotic cells and their cognate receptors in phagocytes, which in most cases differ from the extensively characterized counterparts in apoptotic cell engulfment. The roles of damage-associated molecular patterns, chemokines, lipid mediators, and complement components in recruiting and activating phagocytes are reviewed. Lastly, the physiological importance of necrotic cell removal is emphasized, highlighting the key role of impaired debris clearance in autoimmunity.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.003 |
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".