Metabolic development in the liver and the implications of the n-3 fatty acid supply
Bibliographic record
Abstract
The n-3 fatty acids contribute to regulation of hepatic fatty acid oxidation and synthesis in adults and accumulate in fetal and infant liver in variable amounts depending on the maternal diet fat composition. Using 2D gel proteomics and matrix-assisted laser desorption/ionization time of flight mass spectrometry, we recently identified altered abundance of proteins associated with glucose and amino acid metabolism in neonatal rat liver with increased n-3 fatty acids. Here, we extend studies on n-3 fatty acids in hepatic metabolic development to targeted gene and metabolite analyses and map the results into metabolic pathways to consider the role of n-3 fatty acids in glucose, fatty acid, and amino metabolism. Feeding rats 1.5% compared with <0.1% energy 18:3n-3 during gestation led to higher 20:5n-3 and 22:6n-3 in 3-day-old offspring liver, higher serine hydroxymethyltransferase, carnitine palmitoyl transferase, and acyl CoA oxidase and lower pyruvate kinase and stearoyl CoA desaturase gene expression, with higher cholesterol, NADPH and glutathione, and lower glycine (P < 0.05). Integration of the results suggests that the n-3 fatty acids may be important in facilitating hepatic metabolic adaptation from in utero nutrition to the postnatal high-fat milk diet, by increasing fatty acid oxidation and directing glucose and amino acids to anabolic pathways.
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 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) | 0.000 | 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 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".