Choline and Folic Acid Balance in Diets During Pregnancy Programs Food Intake Regulation in Wistar Rat Offspring (FS08-05-19)
Bibliographic record
Abstract
High gestational folic acid (FA) induces an obesogenic phenotype in male Wistar rat offspring. Imbalances between FA and other methyl-nutrients (i.e., choline) leading to perturbations in the 1-carbon cycle may account for the effects of high FA diets. Canadian women consume high (2–7-fold) intakes of FA, but most are not meeting recommended adequate intakes for choline. Choline is also absent from Canadian prenatal supplements. The objective of this study is to evaluate the effects of the interaction between choline and FA in maternal diets of rats on the 1-carbon cycle, and the programming of food intake, body weight gain and biomarkers of obesity in the offspring later in life. Pregnant Wistar rat dams were fed the AIN-93 G diet with recommended (1X) choline and FA (RCRF, control), or a 5X FA diet with either 0.5X choline (LCHF), 1X choline (RCHF), or 2.5X choline (HCHF). Brain and blood were collected at birth. At weaning one male pup/dam from all groups was maintained on the control diet for 20 weeks then terminated. Dependent measures include weekly body weight-gain and food intake, plasma glucoregulatory hormones and 1-carbon metabolites at birth and post-weaning. Increasing choline content to 2.5-fold in a high (5-fold) gestational FA diet (HCHF) led to lower plasma insulin and leptin levels at birth compared to the LCHF and RCHF diets, respectively (P < 0.05). It also led to lower (25%, P = 0.03) plasma 5-methyltetrahydrofolate concentrations at birth compared to the RCHF diet, suggesting more efficient utilization of FA. Offspring born to dams maintained on a high folic acid diet with either low or recommended choline had higher weekly food intake (6%, P < 0.05) and body weight-gain (9%, P < 0.01). In contrast, offspring from dams fed the HCHF gestational diet were not different from those born to dams fed the RCRF (control) diet, highlighting the mitigating effects of a balanced choline and FA gestational diet. Increased intakes of choline mitigate the effects of high FA diets. Maternal dietary choline interacts with FA on the long-term programming of food intake regulation in the offspring; emphasizing a need for more attention to improving choline intakes by women of child-bearing age. This research was funded by the Canadian Institute of Health Research, Institute of Nutrition, Metabolism and Diabetes (CIHR-INMD).
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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 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".