Myeloperoxidase suppresses apoptosis of human neutrophils
Bibliographic record
Abstract
Myeloperoxidase (MPO), a heme protein abundantly expressed in the azurophilic granules in neutrophils mediates killing of bacteria and oxidative tissue injury. Since elevated plasma MPO levels and prolonged survival of neutrophils are characteristic features of inflammatory diseases, we studied the impact of MPO on neutrophil apoptosis. Culture of neutrophils with MPO at clinically relevant concentrations (10–160 nM) markedly enhanced neutrophil viability by suppressing apoptosis. These actions were prevented by an anti‐CD11b antibody, but not by 4‐aminobenzoic acid hydrazide, an inhibitor of the enzymatic activity of MPO. MPO evoked concurrent activation of the ERK and phosphatidylinositol 3‐kinase/Akt signaling pathways, leading to phosphorylation of Bad at Ser112 and Ser136, respectively. These led to prevention of collapse of mitochondrial transmembrane potential and cytochrome c release, resulting in decreased caspase‐3 activity. Consistently, pharmacological inhibition of either ERK or phosphatidylinositol 3‐kinase almost completely blocked the responses to MPO. MPO and the pan‐caspase inhibitor z‐VAD‐fmk (20 μM) did not produce additive suppression of neutrophil apoptosis. Our results identify MPO as a survival signal for neutrophils by delaying intrinsic neutrophil apoptosis and thus may contribute to amplification of the inflammatory response. (Supported by CIHR MOP‐64283).
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
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".