β2 Integrin Regulation of Neutrophil Functional Plasticity and Fate in the Resolution of Inflammation
Bibliographic record
Abstract
Neutrophils act as the first line of cellular defense against invading pathogens or tissue injury. Their rapid recruitment into inflamed tissues is critical for the elimination of invading microorganisms and tissue repair, but is also capable of inflicting damage to neighboring tissues. The β2 integrins and Mac-1 (CD11b/CD18, αMβ2 or complement receptor 3) in particular, are best known for mediating neutrophil adhesion and transmigration across the endothelium and phagocytosis of microbes. However, Mac-1 has a broad ligand recognition property that contributes to the functional versatility of the neutrophil population far beyond their antimicrobial function. Accumulating evidence over the past decade has demonstrated roles for Mac-1 ligands in regulating reverse neutrophil transmigration, lifespan, phagocytosis-induced cell death, release of neutrophil extracellular traps and efferocytosis, hence extending the traditional β2 integrin repertoire in shaping innate and adaptive immune responses. Understanding the functions of β2 integrins may partly explain neutrophil heterogeneity and may be instrumental to develop novel therapies specifically targeting Mac-1-mediated pro-resolution actions without compromising immunity. Thus, this review details novel insights on outside-in signaling through β2 integrins and neutrophil functional heterogeneity pertinent to the resolution of inflammation.
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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 | 0.001 | 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 | 0.001 |
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".