Arsenic trioxide (AT) is a novel human neutrophil pro‐apoptotic agent: effects of catalase on AT‐induced apoptosis, degradation of cytoskeletal proteins and <i>de novo</i> protein synthesis
Bibliographic record
Abstract
The anti-cancer drug arsenic trioxide (AT) induces apoptosis in a variety of transformed or proliferating cells. However, little is known regarding its ability to induce apoptosis in terminally differentiated cells, such as neutrophils. Because neutropenia has been reported in some cancer patients after AT treatment, we hypothesised that AT could induce neutrophil apoptosis, an issue that has never been investigated. Herein, we found that AT-induced neutrophil apoptosis and gelsolin degradation via caspases. AT did not increase neutrophil superoxide production and did not induce mitochondrial generation of reactive oxygen species. AT-induced apoptosis in PLB-985 and X-linked chronic granulomatous disease (CGD) cells (PLB-985 cells deficient in gp91(phox) mimicking CGD) at the same potency. Addition of catalase, an inhibitor of H2O2, reversed AT-induced apoptosis and degradation of the cytoskeletal proteins gelsolin, alpha-tubulin and lamin B1. Unexpectedly, AT-induced de novo protein synthesis, which was reversed by catalase. Cycloheximide partially reversed AT-induced apoptosis. We conclude that AT induces neutrophil apoptosis by a caspase-dependent mechanism and via de novo protein synthesis. H2O2 is of major importance in AT-induced neutrophil apoptosis but its production does not originate from nicotinamide adenine dinucleotide phosphate dehydrogenase activation and mitochondria. Cytoskeletal structures other than microtubules can now be considered as novel targets of AT.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 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) | 0.000 | 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 teacher head, 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".