Dual Effects of N,N-dimethylformamide on Cell Proliferation and Apoptosis in Breast Cancer
Bibliographic record
Abstract
N,N-dimethylformamide (DMF) has been widely used as an organic solvent in industries. DMF is a potential medication. However, the antitumorigenic role of DMF in breast cancer remains unclear. Here, we examined dose-dependent effects of DMF on proliferation and apoptosis in breast cancer MCF-7 and nontumorous MCF-12A cells. We found that DMF had a growth inhibitory effect in MCF-12A cells in a dose-dependent manner. By contrast, however, DMF had dual effects on cell proliferation and apoptosis in MCF-7 cells. DMF at a high dose (100 mM) significantly inhibited MCF-7 cell growth while at a low dose (1 mM) significantly stimulated MCF-7 cell growth (both P < .05). The inhibitory effect of DMF on cell proliferation was accompanied by the decrease of cyclin D1 and cyclin E1 protein expression, leading to the cell cycle arrest at the G0/G1 phase. Furthermore, a high-dose DMF significantly increased the number of early apoptotic cells by increasing cleaved caspase-9 and proapoptotic protein Bax expression and decreased the ratio of Bcl-xL/Bax ( P < .01). Thus, our data demonstrated for the first time that DMF has dual effects on breast cancer cell behaviors depending upon its dose. Caution must be warranted in determining its effective dose for targeting breast cancer.
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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".