Viability Profiles of Normal and Cancer Bladder Cells With Metformin, Nitrate and Adenosine Monophosphate-Activated Protein Kinase Inhibitor
Bibliographic record
Abstract
Background: There is no literature report on how metformin and adenosine monophosphate-activated protein kinase (AMPK) inhibitor affect normal and cancer bladder cells under the presence of nitrate. Methods: Various treatment concentrations and methods were used to study the effects of nitrate, metformin, and/or AMPK inhibitor on normal and/or cancer bladder cells. Normal bladder cells were exposed to nitrate or metformin alone or in combination. The effects of AMPK on normal bladder cells were investigated with nitrate and metformin pretreatment. The effects of varying metformin concentrations on cancer bladder cells were examined as well. Results: Metformin has produced almost no changes in cell viability of normal cells with various concentrations. Addition of both nitrate and metformin at the same time resulted in less than 17% cell viability as compared to the controlled values; however, this value is about 10% better than nitrate alone for 24 h and approximate 27% better for 48 h. Pre-treatment of normal cells with AMPK inhibitor for 6 h prior to addition of metformin and nitrate reduced the cell viability greatly. The treatment of cancer bladder cells with metformin indicated an inverse relationship between metformin concentration and cancer bladder cell viability. Conclusion: Metformin assisted normal bladder cells in surviving in the presence of nitrate, but its total survival was greatly reduced by AMPK inhibitors. Metformin inhibited the growth of bladder cancer cells.
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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".