High Choline Intake during Pregnancy Reduces Characteristics of the Metabolic Syndrome in Male Wistar Rat Offspring Fed a High Fat But Not a Normal Fat Post-Weaning Diet
Bibliographic record
Abstract
Maternal choline intakes are below recommendations, potentially impairing the child’s later-life metabolic health. This study aims to elucidate the interaction between the choline content of the gestational diet (GD) and fat content of the post-weaning diet (PWD) on metabolic phenotype of male Wistar rats. Pregnant Wistar rats were fed a standard rodent diet (AIN-93G) with either recommended choline (RC, 1 g/kg diet choline bitartrate) or high choline (HC, 2.5-fold). Male pups were weaned to either a normal (16%) fat (NF) or a high (45%) fat (HF) diet for 17 weeks. Body weight, visceral adiposity, food intake, energy expenditure, plasma hormones, triglycerides, and hepatic fatty acids were measured. HC-HF offspring had 7% lower body weight but not food intake, and lower adiposity, plasma triglycerides, and insulin resistance compared to RC-HF. They also had increased hepatic n-3 fatty acids and a reduced n-6/n-3 and C 18:1 n-9/C18:0 ratios. In contrast, HC-NF offspring had 6–8% higher cumulative food intake and body weight, as well as increased leptin and elevated hepatic C16:1 n-7/C16:0 ratio compared to RC-NF. Therefore, gestational choline supplementation associated with improved long-term regulation of several biomarkers of the metabolic syndrome in male Wistar rat offspring fed a HF, but not a NF, PWD.
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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 | 0.001 | 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 | 0.001 |
| 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".