The walking dead: macrophage inflammation and death in atherosclerosis
Bibliographic record
Abstract
PURPOSE OF REVIEW: To highlight recent studies that describe novel inflammatory and signaling mechanisms that regulate macrophage death in atherosclerosis. RECENT FINDINGS: Macrophages contribute to all stages of atherosclerosis. The traditional dogma states that in homeostatic conditions, macrophages undergo apoptosis and are efficiently phagocytosed to be cleared by a process called efferocytosis. In advanced atherosclerosis, however, defective efferocytosis results in secondary necrosis of these uncleared apoptotic cells, which ultimately contributes to the formation of the characteristic necrotic core and the vulnerable plaque. Here, we outline the different types of lesional macrophage death: apoptosis, autophagic and the newly defined necroptosis (i.e. a type of programmed necrosis). Recent discoveries demonstrate that macrophage necroptosis directly contributes to necrotic core formation and plaque instability. Further, promoting the resolution of inflammation using preresolving mediators has been shown to enhance efferocytosis and decrease plaque vulnerability. Finally, the canonical 'don't eat me' signal CD47 has recently been described as playing an important role in atherosclerotic lesion progression by impairing efficient efferocytosis. Although we have made significant strides in improving our understanding of cell death and clearance mechanisms in atherosclerosis, there still remains unanswered questions as to how these pathways can be harnessed using therapeutics to promote lesion regression and disease stability. SUMMARY: Improving our understanding of the mechanisms that regulate macrophage death in atherosclerosis, in particular apoptosis, necroptosis and efferocytosis, will provide novel therapeutic opportunities to resolve atherosclerosis and promote plaque stability.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 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".