Maternal diet rich in saturated fats has deleterious effects on plasma lipids of mice.
Bibliographic record
Abstract
BACKGROUND AND OBJECTIVES: High dietary fat intake has been reported to cause an alteration in lipid metabolism that is associated with an increased risk of cardiovascular disease. In the present study, an animal model was used to evaluate the effects of feeding diets rich in different fatty acids to mothers during pregnancy and lactation, and the effects of the maternal diet on parameters of lipid metabolism in adult offspring. The interaction between the offspring's own diet and the programming due to the maternal diet was also evaluated. METHODS: Female C57BL/6 mice were fed a high-fat diet (20% fat [weight to weight]) rich in either saturated fatty acids (SFA) or polyunsaturated fatty acids (PUFA) for two weeks before mating, during pregnancy and until weaning. The offspring were divided into two groups; each group was fed a high-fat diet enriched in either SFA or PUFA for eight weeks after weaning. The groups were designated as SFA/SFA (diet of the mother/diet of the offspring), SFA/PUFA, PUFA/PUFA and PUFA/SFA. Blood and tissues were collected at the end of the eight-week feeding period after an overnight fast. RESULTS: The plasma total cholesterol and low density lipoprotein cholesterol concentrations were significantly higher in the SFA/SFA group than in all other groups, whereas the PUFA/PUFA group had the lowest total cholesterol and low density lipoprotein cholesterol concentrations. Plasma high density lipoprotein cholesterol concentrations were significantly higher in the PUFA/SFA group than in the PUFA/PUFA and SFA/PUFA groups, whereas plasma triglyceride concentrations were not different among the groups. CONCLUSIONS: The data suggest that high maternal dietary fat intake during pregnancy affects lipid metabolism in the adult offspring. However, it appears that the offspring's own diet is also important in maintaining the regulation of lipid metabolism.
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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) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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".