Curcumin Induces Apoptosis in EJ Bladder Cancer Cells via Modulating C-Myc and PI3K/Akt Signaling Pathway
Bibliographic record
Abstract
BACKGROUND: Cancer chemopreventive agent curcumin has been shown to possess cell growth inhibition and apoptosis induction properties in several types of cancer. However, the detailed molecular mechanisms of the compound remain far from clear in EJ bladder cancer cells. METHODS: The effect of curcumin on EJ cell growth and apoptosis was detected by MTT assays and flow cytometry. The phosphorylation levels of PTEN, PDK1, Akt, GSK-3β, c-Raf, and Bad and the expression levels of c-myc, Bax, Bcl-2, caspase-9, caspase-7, caspase-3, and PARP following curcumin administration were examined by immunoblots. RESULTS: Curcumin suppressed the growth of EJ cells in a time and concentration dependent manner. Immunoblot showed that curcumin increased expression levels of c-myc and inhibited the activation of PI3K/Akt pathway in a time-dependent manner in EJ cells. Activation of PTEN, GSK-3β, c-Raf, caspase-9, caspase-7, and caspase-3, cleavage of PARP, upregulation of Bad and Bax, and downregulation of Akt and Bcl-2 were also found in curcumin-treated EJ cells. CONCLUSIONS: These findings establish a mechanistic linkup or interaction between c-myc, Bax, Bad, Bcl-2, caspase cascades, PI3K/Akt pathway and curcumin- induced apoptosis of EJ cells, suggesting that c-myc and PI3K/Akt signaling pathway play important roles in curcumin-induced apoptosis of EJ bladder cancer cells.
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 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".