Regulation of hepatic cardiolipin metabolism by TNFα: Implication in cancer cachexia
Bibliographic record
Abstract
Cardiolipin (CL) content accumulation leads to an increase in energy wasting in liver mitochondria in a rat model of cancer cachexia in which tumor necrosis factor alpha (TNFα) is highly expressed. In this study we investigated the mechanisms involved in liver mitochondria CL accumulation in cancer cachexia and examined if TNFα was involved in this process leading to mitochondrial bioenergetics alterations. We studied gene, protein expression and activity of the main enzymes involved in CL metabolism in liver mitochondria from a rat model of cancer cachexia and in HepaRG hepatocyte-like cells exposed to 20 ng/ml of TNFα for 12 h. Phosphatidylglycerolphosphate synthase (PGPS) gene expression was increased 2.3-fold (p<0.02) and cardiolipin synthase (CLS) activity decreased 44% (p<0.03) in cachectic rat livers compared to controls. CL remodeling enzymes monolysocardiolipin acyltransferase (MLCL AT-1) activity and tafazzin (TAZ) gene expression were increased 30% (p<0.01) and 50% (p<0.02), respectively, in cachectic rat livers compared to controls. Incubation of hepatocytes with TNFα increased CL content 15% (p<0.05), mitochondrial oxygen consumption 33% (p<0.05), PGPS gene expression 44% (p<0.05) and MLCL AT-1 activity 20% (p<0.05) compared to controls. These above findings strongly suggest that in cancer cachexia, TNFα induces a higher energy wasting in liver mitochondria by increasing CL content via upregulation of PGPS expression.
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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".