High multivitamin intake during pregnancy leads to dopamine dysregulation in the nucleus accumbens of Wistar rat dams post‐weaning (47.6)
Bibliographic record
Abstract
Diet‐induced obesity is known to alter dopamine neurochemistry within central reward circuitry essential for coding the rewarding properties of palatable foods. Our objective was to investigate whether high multivitamin (10‐fold, HV) intake during pregnancy alone, which increases post‐weaning (PW) weight gain in Wistar rat dams, affects their dopamine (DA) metabolism and related gene expression in the nucleus accumbens (NAc) when exposed to an obesogenic environment. Pregnant Wistar rats were fed an AIN‐93G diet with either the recommended vitamin (1‐fold, RV) or HV mix (n=15/group). During lactation, dams were fed a RV diet until weaning and then a high fat (RV with 60% fat) diet for 16 weeks. Dams fed the HV diet gained 30% (p<0.05) more weight after weaning than RV dams. Although differences in food intake were not detected, HV dams had a 10% (p<0.05) reduced preference for sucrose when exposed to a two‐bottle preference test (4% sucrose vs. water) at 12 weeks PW suggesting a state of reward hypofunction. Total DA, DA receptor 1a/2, catechol‐O‐methyl transferase and monoamine‐oxidase A mRNA expression in the NAc was unaffected by diets. However, turnover rate of homovanillic acid, but not di‐hydroxypheneylactic acid, was significantly lower in HV dams (p<0.05). In conclusion, HV diet during pregnancy in Wistar rat dams induces DA dysregulation in the NAc later in life and is consistent with PW weight gain. Grant Funding Source : Supported by Canadian Institutes of Health Research, Institue of Nutrition, Metabolism and Diabetes
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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) | 0.002 | 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".