Multivitamin supplementation during pregnancy alters body weight and macronutrient selection in Wistar rat offspring
Bibliographic record
Abstract
The hypothesis that vitamin content of the diet during gestation alters macronutrient choice, food intake and the expression of serotonin receptors and proopiomelanocortin (POMC) in the hypothalamus of the offspring was investigated. Pregnant Wistar rats (n = 10/group) were fed the AIN-93G diet containing a multivitamin mix at the recommended (RV) content or10-fold higher (high vitamin, HV) content. Male offspring were weaned to a choice of 10% and 60% casein diets. Intake regulation by the serotonergic system was determined by measuring food choice daily for 7 weeks, and following tryptophan (TRP) or mCPP (a serotonin receptor agonist) injections at 4 and 6 weeks post-weaning. mRNA expressions of hypothalamic serotonin receptor and POMC were measured at birth, weaning and sacrifice (7 weeks post-weaning). No differences were found in body weight at birth or weaning. HV offspring had lower food intake for the duration of the study (P < 0.001), and 11% lower body weight (P < 0.05) and 23% lower fat pad mass (P < 0.05) at 7 weeks post-weaning. They selected less protein following 12 h of food deprivation (P < 0.05) and were less responsive to TRP (P = 0.05) and mCPP (P < 0.05) injections at 6 weeks post-weaning. Expressions of mRNA for serotonin receptors 5-HT1A/2A/2C at weaning (P < 0.01) and of POMC at weaning and 7 weeks post-weaning (P < 0.05) were lower. In conclusion, intake of multivitamins above the requirements during pregnancy affected macronutrient choice, food intake and the expression of serotonin receptors and POMC in the hypothalamus.
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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 | 0.000 |
| 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".