Activation of A2b adenosine receptor regulates ovarian cancer cell growth: involvement of Bax/Bcl-2 and caspase-3
Bibliographic record
Abstract
A2b adenosine receptor (A2bAR) acts as a potent regulator of cell growth in various cell lines. The present study was designed to understand the controlling mechanism of A2bAR agonist (NECA)-induced apoptosis in ovarian cancer cells. Real-time PCR and western blotting assays were used to evaluate the gene and protein expression profiles of A2bAR, respectively. MTT assay was used to study the cell proliferation effect of A2bAR agonist (NECA). Detection of apoptosis was conducted using annexin V-FITC/PI staining, caspase-3 activation assay, and the expression of Bax and Bcl-2 proteins analysis. The mitochondrial membrane potential (ΔΨM) was analyzed by employing JC-1 prob. The mRNA and protein expression levels of A2bAR in ovarian cancer cells were detected. NECA significantly reduced cell viability in a dose-dependent manner in OVCAR-3 and Caov-4 cell lines. The growth inhibition effect of NECA was related to the induction of cell apoptosis, which was manifested by annexin V-FITC staining, activation of caspase-3, and loss of mitochondrial membrane potentials (ΔΨm). In addition, downregulation of the regulatory protein Bcl-2 and upregulation of Bax protein by NECA were also observed. These findings demonstrated that NECA induces apoptosis via the mitochondrial signaling pathway. Thus, A2bAR agonists may be a potential agent for induction of apoptosis in ovarian 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 | 0.000 |
| 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".