Singlet Oxygen-Induced Mitochondrial Reset in Cancer: A Novel Approach for Ovarian Cancer Therapy
Bibliographic record
Abstract
Background/Objectives: This study explores the generation of singlet oxygen (SO) through methylene blue (MB) activation as a metabolic intervention for ovarian cancer. We aimed to examine the role of SO in modulating mitochondrial function, cellular metabolism, and proliferation in ovarian cancer cell lines compared to control cells. Methods: The study utilized two ovarian cancer cell lines, OV1369-R2 and TOV1369, along with ARPE-19 control cells. Following MB treatment and light activation, mitochondrial function and ATP synthesis were assessed. Metabolomic analyses were performed to evaluate changes in central carbon metabolism, particularly focusing on markers of the Warburg effect. Results: TOV1369 cells exhibited a pronounced sensitivity to MB treatment, resulting in significant inhibition of ATP synthesis and reduced proliferation. Metabolomic analysis indicated that MB-induced SO production partially reversed the Warburg effect, suggesting a shift from glycolysis to oxidative phosphorylation. These effects were less pronounced in OV1369-R2 and ARPE-19 cells, correlating with their lower MB sensitivity. Conclusions: MB-generated SO selectively modulates mitochondrial energetics in ovarian cancer cells, driving a metabolic reorganization that curtails their proliferative capacity. This approach, leveraging the bacterial-like features of cancer metabolism, offers a promising therapeutic avenue to induce apoptosis and enhance treatment outcomes in ovarian 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 | 0.001 | 0.001 |
| 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".