Early hyperlipidemia triggers metabolomic reprogramming with increased SAH, increased acetyl-CoA-cholesterol synthesis, and decreased glycolysis
Bibliographic record
Abstract
To identify metabolomic reprogramming in early hyperlipidemia, unbiased metabolome was screened in four tissues from ApoE−/− mice fed with high fat diet (HFD) for 3 weeks. 30, 122, 67, and 97 metabolites in the aorta, heart, liver, and plasma, respectively, were upregulated. 9 upregulated metabolites were uremic toxins, and 13 metabolites, including palmitate, promoted a trained immunity with increased syntheses of acetyl-CoA and cholesterol, increased S-adenosylhomocysteine (SAH) and hypomethylation and decreased glycolysis. The cross-omics analysis found upregulation of 11 metabolite synthetases in ApoE‾/‾ aorta, which promote ROS, cholesterol biosynthesis, and inflammation. Statistical correlation of 12 upregulated metabolites with 37 gene upregulations in ApoE‾/‾ aorta indicated 9 upregulated new metabolites to be proatherogenic. Antioxidant transcription factor NRF2−/− transcriptome analysis indicated that NRF2 suppresses trained immunity-metabolomic reprogramming. Our results have provided novel insights on metabolomic reprogramming in multiple tissues in early hyperlipidemia oriented toward three co-existed new types of trained immunity.
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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".