Novel human neutrophil agonistic properties of arsenic trioxide: involvement of p38 mitogen-activated protein kinase and/or<i>c-jun</i>NH2-terminal MAPK but not extracellular signal-regulated kinases-1/2
Bibliographic record
Abstract
Arsenic trioxide (ATO) is known for treating acute promyelocytic leukemia and for inducing apoptosis and mitogen-activated protein kinases (MAPKs) in promyelocytes and cancer cells. We recently reported that ATO induces neutrophil apoptosis. The aim of this study was to establish whether or not ATO recruits MAPKs in neutrophils, as well as to further investigate its agonistic properties. We found that ATO activates p38 and that, unlike H2O2, this response was not inhibited by exogenous catalase. Also, we demonstrated that ATO-induced p38 activation occurs before H2O2 generation and without a calcium burst. We next established that ATO recruits c-jun NH2-terminal (JNK) but not extracellular signal-regulated kinase 1 and 2 (Erk-1/2). Using pharmacological inhibitors, we found that the proapoptotic activity of ATO occurs by a MAPK-independent mechanism. In contrast, the ability of ATO to enhance adhesion, migration, phagocytosis, release, and activity of gelatinase and degranulation of secretory, specific, and gelatinase, but not azurophilic granules, is dependent upon activation of p38 and/or JNK. This is the first study establishing that ATO possesses important agonistic properties in human neutrophils. Given the central role of neutrophils in various inflammatory disorders, we propose that ATO might have broader therapeutic implications in clinics, especially for regulating 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) | 0.000 | 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 | 0.000 |
| 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".