Aurintricarboxylic Acid Inhibits Protein Synthesis Independent, Sanguinarine-Induced Apoptosis and Oncosis
Bibliographic record
Abstract
Sanguinarine, a benzophenanthridine alkaloid, has anticancer potential through induction of cell death. We previously demonstrated that sanguinarine treatment at a low concentration (1.5 microg/ml) induced apoptosis in K562 human erythroleukemia cells, and a high concentration (12.5 microg/ml) induced the morphology of blister formation or oncosis-blister cell death (BCD). Treatment of cells at an intermediate sanguinarine concentration (6.25 microg/ml) induced diffuse swelling or oncosis-diffuse cell swelling (DCS). To assess the underlying mechanism of sanguinarine-induced apoptosis and oncosis-BCD in K562 cells, we studied their response to pre-treatment with two chemical compounds: aurintricarboxylic acid (ATA) and cycloheximide (CHX). The pretreatment effects of both chemical compounds on apoptosis and oncosis-BCD were evaluated by measuring multiple parameters using quantitative morphology, electron microscopy, terminal deoxynucleotidyl transferase (TdT) end-labeling and annexin-V-binding. ATA, a DNA endonuclease inhibitor, efficiently prevented DNA nicking and inhibited apoptosis almost completely and oncosis-BCD by about 40%, while CHX, a protein synthesis inhibitor, failed to inhibit both apoptosis and oncosis-BCD. These results demonstrate, first, the importance of endonuclease in sanguinarine-induced apoptosis and to some extent in oncosis-BCD and, second, that this inhibition does not require de novo protein synthesis.
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".