Adenosine and deoxyadenosine induces apoptosis in oestrogen receptor‐positive and ‐negative human breast cancer cells via the intrinsic pathway
Bibliographic record
Abstract
In this study we have examined the cytotoxic effects of different concentrations of adenosine (Ado) and deoxyadenosine (dAdo) on human breast cancer cell lines. Ado and dAdo alone had little effect on cell cytotoxicity. However, in the presence of adenosine deaminase (ADA) inhibitor, EHNA, adenosine and deoxyadenosine led to significant growth inhibition of cells of the lines tested. Ado/EHNA and dAdo/EHNA-induced cell death was significantly inhibited by NBTI, an inhibitor of nucleoside transport, and 5'-amino-5'-deoxyadenosine, an inhibitor of adenosine kinase, but the effects were not affected by 8-phenyltheophylline, a broad inhibitor of adenosine receptors. The Ado/EHNA combination brought about morphological changes consistent with apoptosis. Caspase-9 activation was observed in MCF-7 and MDA-MB468 human breast cancer cell lines on treatment with Ado/EHNA or dAdo/EHNA, but, as expected, caspase-3 activation was only observed in MDA-MB468 cells. The results of the study, thus, suggest that extracellular adenosine and deoxyadenosine induce apoptosis in both oestrogen receptor-positive (MCF-7) and also oestrogen receptor-negative (MDA-MB468) human breast cancer cells by its uptake into the cells and conversion to AMP (dAMP) followed by activation of nucleoside kinase, and finally by the activation of the mitochondrial/intrinsic apoptotic pathway.
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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".