Synergistic cytotoxic effects of tamoxifen and black cohosh on MCF-7 and MDA-MB-231 human breast cancer cells: an in vitro studyThis article is one of a selection of papers published in this special issue (part 2 of 2) on the Safety and Efficacy of Natural Health Products.
Bibliographic record
Abstract
Breast cancer cell cultures were exposed to different concentrations of black cohosh, estradiol (E2), and tamoxifen to examine the effect on cell proliferation; cytotoxicity was assessed by using sulforhodamine B (SRB) dye solution. E2 (10(-10) - 10(-8) mol/L) markedly stimulated the proliferation of MCF-7 cells (p < 0.01). Tamoxifen stimulated MCF-7 cell proliferation at 10(-6) mol/L and 10(-5) mol/L (p < 0.005) but inhibited in a dose-dependent fashion the proliferative effect of E2 (p < 0.001). Black cohosh alone did not show any stimulatory effect, but exhibited a cytotoxic effect, which was significant at 10(3) microg/mL (p < 0.001). Adding black cohosh at 10(0)-10(3) microg/mL to E2 at 10(-9) mol/L also resulted in a dose-dependent inhibition of E2 proliferative effect. Interestingly, the combination of black cohosh (10(0)-10(3) microg/mL) with increasing tamoxifen concentrations further inhibited MCF-7 cell growth. On MDA-MB-231 cells, neither E2 nor tamoxifen displayed any detectable effect. However, black cohosh inhibited MDA-MB-231 cell proliferation at 10(3) microg/mL (p < 0.05), and this inhibitory effect was enhanced by increasing tamoxifen concentrations. This study reveals a cytotoxic effect of black cohosh on both estrogen-sensitive and estrogen-insensitive breast cancer cells and a synergism with tamoxifen for inhibition of cancerous cell growth.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 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) | 0.002 | 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".