Apoptotic Cells, at All Stages of the Death Process, Trigger Characteristic Signaling Events That Are Divergent from and Dominant over Those Triggered by Necrotic Cells
Bibliographic record
Abstract
Current models of autoimmunity suggest that delayed clearance of apoptotic cells leads to the presentation of apoptotic antigens in the context of inflammatory signals, with resultant autoimmunity. These models implicitly assume that, in contrast to early apoptotic cells (that retain membrane integrity), late apoptotic cells (with compromised membranes) act like necrotic cells (which also lack intact membranes), possibly because of the release of proinflammatory intracellular contents. We showed previously that early apoptotic and necrotic cells induce distinct mitogen-activated protein kinase modules in macrophages with which they interact. Exposure to apoptotic cells led to nearly complete inhibition of both basal and macrophage colony-stimulating factor-induced ERK1/2 by macrophages. In contrast, necrotic cells induced ERK1/2. We show here that apoptotic cells also strongly induced both c-Jun N-terminal kinase and p38, whereas necrotic cells had no detectable effect on c-Jun N-terminal kinase and p38. We also compared the signaling events induced in macrophages by exposure to early apoptotic cells, late apoptotic cells, and necrotic cells. The signaling events induced by late apoptotic cells were identical to and just as potent as those induced by early apoptotic cells. Thus, apoptotic cells are functionally equivalent throughout the cell death process, irrespective of membrane integrity. Moreover, the effects of both early and late apoptotic cells on signaling were dominant over those of necrotic cells. These data show that apoptotic cells do not become proinflammatory upon the loss of membrane integrity and are inconsistent with the notion that delayed clearance alone can lead to 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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| 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".