An Improved Quantitative Approach for the Assessment of Mitochondrial Fragmentation in Chemoresistant Ovarian Cancer Cells
Bibliographic record
Abstract
Mitochondrial fission is a process that involves cleavage of mitochondria into smaller fragments and is regulated by the GTPase Dynamin-related protein 1 (Drp1). Higher levels of mitochondrial fission are associated with the induction of apoptosis in cancer cells. However, current methods to accurately quantify mitochondrial fission in order to compare therapeutics that target this process are often ambiguous or rely on subjective assessment. Mitochondria are also prone to aggregation, making accurate analysis difficult. Here we describe an improved approach for the quantification of mitochondrial fragmentation involving several differences from currently existing methods. Cells are first subjected to cytological centrifugation, which reduces cellular z-axis height and disperses individual mitochondria for easier observation. Three commercially available fluorescence analysis tools are then applied to disambiguate remaining mitochondrial clusters that require further inspection. Finally, cut-off scoring is applied, which can be tailored to individual cell type. The resultant approach allows for the efficient and objective assessment of mitochondrial fragmentation in response to treatment. We applied this technique to an experimental question involving chemosensitive and chemoresistant ovarian cancer (OVCA) cells. Cisplatin and the phytochemical piperlongumine were found to induce both mitochondrial fission and apoptosis in chemosensitive cells, while only piperlongumine was able to elicit these cellular responses in chemoresistant cells. Piperlongumine-induced apoptosis appeared to be mediated by Drp1-dependent mitochondrial fission since the apoptotic response was attenuated by the presence of the Drp1 inhibitor mDivi-1. Our study provides groundwork for a more objective approach to the quantification of mitochondrial fragmentation, and sheds further light on a potential mechanism of action for piperlongumine in the treatment of chemoresistant OVCA.
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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 | 0.002 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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".