Bibliographic record
Abstract
Very little is known concerning the toxicity of antimony, despite its commercial use as a flame retardant and medical use as a treatment for parasitic infections. Our previous studies show that antimony trioxide (Sb2O3) induces growth inhibition in patient-derived acute promyelocytic leukemia (APL) cell lines, a disease in which a related metal, arsenic trioxide (As2O3), is used clinically. However, signaling pathways initiated by Sb2O3 treatment remain undefined. Here, we show that Sb2O3 treatment of APL cells is associated with increased apoptosis as well as differentiation markers. Sb2O3-induced reactive oxygen species (ROS) correlated with increased apoptosis. In addition, when we decreased the buffering capacity of the cell by depleting glutathione, ROS production and apoptosis was enhanced. Arsenic-resistant APL cells with increased glutathione levels exhibited increased cross-resistance to Sb2O3. Based on studies implicating c-jun kinase (JNK) in the mediation of the response to As2O3, we investigated the role for JNK in Sb2O3-induced apoptosis. Sb2O3 activates JNK and its downstream target, AP-1. In fibroblasts with a genetic deletion in SEK1, an upstream regulator of JNK, Sb2O3-induced growth inhibition as well as JNK activation was decreased. These data suggest roles for ROS and the SEK1/JNK pathway in the cytotoxicity associated with Sb2O3 exposure.
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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.003 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.005 | 0.002 |
| Open science | 0.002 | 0.004 |
| Research integrity | 0.003 | 0.002 |
| Insufficient payload (model declined to judge) | 0.368 | 0.478 |
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".