5-Aza-2′-deoxycytidine stress response and apoptosis in prostate cancer
Bibliographic record
Abstract
While studying on epigenetic regulatory mechanisms (DNA methylation at C-5 of -CpG- cytosine and demethylation of methylated DNA) of certain genes (FAS, CLU, E-cadh, CD44, and Cav-1) associated with prostate cancer development and its better management, we noticed that the used in vivo dose of 5-aza-2'-deoxycytidine (5.0 to 10.0 nM, sufficient to inhibit DNA methyltransferase activity in vitro) helped in the transcription of various genes with known (steroid receptors, AR and ER; ER variants, CD44, CDH1, BRCA1, TGFβR1, MMP3, MMP9, and UPA) and unknown (DAZ and Y-chromosome specific) proteins and the respective cells remained healthy in culture. At a moderate dose (20 to 200 nM) of the inhibitor, cells remain growth arrested. Upon subsequent challenge with increased dose (0.5 to 5.0 μM) of the inhibitor, we observed that the cellular morphology was changing and led to death of the cells with progress of time. Analyses of DNA and anti-, pro-, and apoptotic factors of the affected cells revealed that the molecular events that went on are characteristics of programmed cell death (apoptosis).
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".