Arsenic trioxide induces <i>de novo</i> protein synthesis of annexin‐1 in neutrophils: association with a heat shock‐like response and not apoptosis
Bibliographic record
Abstract
We recently demonstrated that arsenic trioxide (ATO) induced apoptosis in human neutrophils and increased de novo protein synthesis. Here, we identified one of these newly synthesized proteins as annexin-1 (AnxA1), a protein recently found to be proapoptotic in neutrophils when added exogenously. AnxA1 was detected at the cell membrane of ATO-induced neutrophils as well as in the supernatants. Using neutrophils harvested from AnxA1 knockout mice, we found that the proapoptotic activity of ATO was similar in neutrophils, regardless of AnxA1 levels. A second protein was identified as heat shock protein (Hsp) 89alpha. Because ATO is known to induce a HS-like response in a variety of cells, we investigated its ability to induce gene expression of Hsp in neutrophils and found that ATO increases HSP90AA1, HSPA1 and HSPB1 mRNA in these cells. We conclude that ATO-induced neutrophil apoptosis by an AnxA1-independent mechanism. Our data provide the first evidence that ATO induces a stress response in human neutrophils and that de novo synthesis of AnxA1 is related to this event rather than to the proapoptotic activity of ATO.
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) | 0.000 | 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".