Hyperosmolarity Triggers the Warburg Effect in Chinese Hamster Ovary Cells and Reveals a Reduced Mitochondria Horsepower
Bibliographic record
Abstract
Tumor cells are known to favor a glycolytic metabolism over oxidative phosphorylation (OxPhos), which takes place in mitochondria, to produce the energy and building blocks essential for cell maintenance and cell growth. This phenotypic property of tumor cells gives them several advantages over normal cells and is known as the Warburg effect. Tumors can be treated as a metabolic disease by targeting their bioenergetics capacity. Alpha-lipoic acid (ALA) and calcium hydroxycitrate (HCA) are two drugs known to target the Warburg effect in tumor cells and hence induce the mitochondria for ATP production. However, tumor cells, known to have an increased flux through glycolysis, are not able to handle the activation of their mitochondria by drugs or any other condition, leading to decoupling of gene regulation. In this study, these drug effects were studied by mimicking an inflammatory condition through the imposition of a hyperosmotic condition in Chinese hamster ovary (CHO) cells, which behave similarly to tumor cells. Indeed, CHO cells grown in high osmolarity conditions, using 200 mM mannitol, showed a pronounced Warburg effect phenotype. Our results show that hyperosmolar conditions triggered high-throughput glycolysis and enhanced glutaminolysis in CHO cells, such as during cancer cell proliferation in inflammatory tissue. Finally, we found that the hyperosmolar condition was correlated with increased mitochondrial membrane potential (ΔΨm) but mitochondrial horsepower seemed to vanish (h = Δp/ΔΨm), which may be explained by mitochondrial hyperfusion.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 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) | 0.000 | 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 teacher head, 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".