Neutrophil apoptosis: A target for enhancing the resolution of inflammation
Bibliographic record
Abstract
Neutrophils are essential for host defense and their programmed cell death and removal are critical for the optimal expression as well as for efficient resolution of inflammation. Delayed neutrophil apoptosis or impaired clearance of apoptotic neutrophils by macrophages contributes to the progression of chronic inflammation. Under most conditions, neutrophils are exposed to multiple factors and their fate would ultimately depend on the balance between pro-survival and pro-apoptotic signals. Life or death decisions are tightly controlled by a complex network of intracellular signaling pathways. Accumulating data indicate that receptors, such as the formyl peptide receptor 2/lipoxin receptor or beta(2)-integrins can generate contrasting cues in neutrophils in a ligand-specific manner and suggest a hierarchy among these signals. In this article, we review recent advances on how pro-apoptosis and pro-survival signals interact to determine the fate of neutrophils and the inflammatory response, and highlight novel pharmacological strategies that could be used to enhance the resolution of inflammation by redirecting neutrophils to apoptosis.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.002 |
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".