Synergistic activation of mitochondrial metabolism and the glutathione redox couple protects HepG2 hepatocarcinoma cells from palmitoylcarnitine-induced stress
Bibliographic record
Abstract
Fatty acid stress can have divergent effects in various cancers. We explored how metabolic and redox flexibility in HepG2 hepatocarcinoma cells mediates protection from palmitoylcarnitine. HepG2 cells, along with HCT 116 and HT29 colorectal cancer cells were incubated with 100 μM palmitoylcarnitine for up to 48 h. Mitochondrial H2O2 emission, glutathione, and cell survival were assessed in HT29 and HepG2 cells. 100 μM palmitoylcarnitine promoted early growth in HepG2 cells by ~8% after 48 h versus decreased cell survival observed in HT29 and HCT 116 cells. Palmitoylcarnitine increased mitochondrial respiration at physiological and maximal concentrations of ADP, while lowering cellular lactate content in HepG2 cells, suggesting a switch to mitochondrial metabolism. HepG2 cell growth was associated with an early increase in H2O2 emission by 10 min, followed by a decrease in H2O2 at 24 h that corresponded with increased glutathione content, suggesting a redox-based compensatory mechanism. In contrast, abrogation of HT29 cell proliferation was related to decreased mitochondrial respiration (likely due to cell death) and decreased glutathione. Concurrent glutathione depletion with BSO prevented palmitoylcarnitine-induced growth in HepG2 cells, indicating that glutathione was critical for promoting growth following palmitoylcarnitine. Inhibiting UCP2 with genipin sensitized HepG2 cells to palmitoylcarnitine, suggesting that activation of UCP2 may be a 2nd redox-based mechanism conferring protection. These findings suggest that HepG2 cells possess inherent metabolic and redox flexibility relative to HT29 cells that confers protection from palmitoylcarnitine-induced stress via adaptive increases in mitochondrial respiratory control, glutathione buffering, and induction of UCP2.
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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".