High maternal folate intake by Sprague Dawley rats results in higher weight gain and lower plasma folate in male offspring
Bibliographic record
Abstract
High multivitamin intake during pregnancy leads to increased weight gain, food intake, and hyperinsulinemia in rat offspring (Szeto et al. Am J Physiol 2008; 295: R575‐82). The objective of this study was to investigate the role of maternal folate intake on offspring body weight (BW) and hypothalamic gene expression. Pregnant Sprague Dawley rats (n=10/group) were randomized to the AIN‐93G diet containing either the recommended (RF) or 2.5‐fold the folate content (HF) during pregnancy and lactation. All offspring were weaned to the RF diet. BW was measured from 1 wk post‐weaning (pw) to 25 wk pw. Plasma and liver folate levels were measured and hypothalamic gene expression of leptin receptor (LR) and POMC were determined by real‐time RT‐PCR. Males from HF dams were 6% heavier compared with those from RF dams (p<0.0001). Males from HF dams had 27% lower plasma folate compared to males from RF dams (p=0.01), while there were no differences in liver folate levels. Males from HF dams had 39% lower POMC mRNA compared to males from RF dams (p<0.05). No differences in LR mRNA levels were detected. In conclusion, a moderate increase in maternal folate intake resulted in higher BW, which may be related to lower hypothalamic POMC expression, and lower plasma folate concentrations in the male offspring. Grant Funding Source CIHR‐INMD (OOP‐77980), Ontario Graduate Scholarship
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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 | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| 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".