DHA and 19,20-EDP induce lysosomal-proteolytic-dependent cytotoxicity through de novo ceramide production in H9c2 cells with a glycolytic profile
Bibliographic record
Abstract
Docosahexaenoic acid (DHA) and their CYP-derived metabolites, epoxydocosapentaenoic acids (EDPs), are important fatty acids obtained from dietary sources. While it is known that they have significant biological effects, which can differ between cell type and disease state, our understanding of how they work remains limited. Previously, we demonstrated that DHA and 19,20-EDP triggered pronounced cytotoxicity in H9c2 cells correlating with increased ceramide production. In this study, we examine whether DHA- and 19,20-EDP-induced cell death depends on the type of metabolism (glycolysis or OXPHOS). We cultivated H9c2 cells in distinct conditions that result in either glycolytic or oxidative metabolism. Our major findings suggest that DHA and its epoxy metabolite, 19,20-EDP, trigger cytotoxic effects toward H9c2 cells with a glycolytic metabolic profile. Cell death occurred through a mechanism involving activation of a lysosomal-proteolytic degradation pathway. Importantly, accumulation of ceramide played a critical role in the susceptibility of glycolytic H9c2 cells to cytotoxicity. Furthermore, our data suggest that an alteration in the cellular metabolic profile is a major factor determining the type and magnitude of cellular toxic response. Together, the novelty of this study demonstrates that DHA and 19,20-EDP induce cell death in H9c2 cells with a glycolytic metabolicwct 2 profile through a lysosomal-proteolytic mechanism.
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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 | 0.001 |
| 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".