Maternal fructose consumption during gestation increases body weight and fat mass in young adult offspring
Bibliographic record
Abstract
Increased fructose (FR) consumption is a potential cause of adult obesity and the metabolic syndrome but the extent to which enhanced exposure to FR through pregnancy influences later body mass and composition of offspring has received little attention. Our study examined the effect of FR consumption during gestation body mass and composition in young adulthood. Female rats received 10% FR solution (n=8) or tap water (C) (n=8) throughout gestation and lactation in addition to standard chow. Offspring were weaned at 21 days; 1 male and 1 female/litter were fed standard chow plus tap water to 90 days of age. Retroperitoneal and epididymal (males) and uterine (females) fat was dissected and weighed. Body weight was offspring born and reared to FR dams compared to C (Females ‐ C: 251.9±6.7; FR: 278.6±5.67 g (p<0.01); Males – C: 469.3±7.44; FR: 506.7±13.49 g (p= 0.05). Fat mass was greater in all depots (absolute and relative) regardless of gender (e.g. retroperitoneal depot: Females – C: 2.1±0.11; FR: 3.2±0.27g (p<0.01); Males – C: 6.4±0.74; FR: 10.9±1.57 g (p<0.05)). Exposure to FR through pregnancy and lactation promotes postnatal growth and fat deposition in the offspring irrespective of gender. FR consumption during pregnancy deserves further attention given its potential contribution to obesity in offspring. Funding: NSERC (Canada); British Heart Foundation.
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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 | 0.000 | 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".