The impact of EPA and DHA on ceramide lipotoxicity in the metabolic syndrome
Bibliographic record
Abstract
The metabolic syndrome (MetS) is a cluster of cardiovascular risk factors including obesity, insulin resistance (IR) and dyslipidaemia. Consumption of a high-fat diet (HFD) enriched in SFA leads to the accumulation of ceramide (Cer), the central molecule in sphingolipid metabolism. Elevations in plasma and tissue Cer are found in obese individuals, and there is evidence to suggest that Cer lipotoxicity contributes to the MetS. EPA and DHA have shown to improve MetS parameters including IR, inflammation and hypertriacylglycerolaemia; however, whether these improvements are related to Cer is currently unknown. This review examines the potential of EPA and DHA to improve Cer lipotoxicity and MetS parameters including IR, inflammation and dyslipidaemia in vitro and in vivo. Current evidence from cell culture and animal studies indicates that EPA and DHA attenuate palmitate- or HFD-induced Cer lipotoxicity and IR, whereas evidence in humans is greatly lacking. Overall, there is intriguing potential for EPA and DHA to improve Cer lipotoxicity and related MetS parameters, but more research is warranted.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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) | 0.001 | 0.001 |
| 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".