High Fructose Intake During Pregnancy in Rats Influences the Maternal Microbiome and Gut Development in the Offspring
Bibliographic record
Abstract
Studies in pregnant women indicate the maternal microbiome changes during pregnancy so as to benefit the mother and fetus. In contrast, disruption of the maternal microbiota around birth can compromise normal bacterial colonisation of the infant’s gastrointestinal tract. This may then inhibit development of the gut so as to increase susceptibility to inflammation and reduce barrier function. The impact of modulating fructose intake on the maternal microbiome through pregnancy is unknown, therefore we examined the effect of fructose supplementation on the microbiome together with the immediate and next generation effects in the offspring. Wistar rat dams were divided into control and fructose fed groups that received 10% fructose in their drinking water from 8 weeks of age and throughout pregnancy (10-13 weeks). Maternal fecal and blood samples were collected pre-mating (9 weeks) and during early (gestational day 4-7) and late pregnancy (gestational day 19-21).We show supplementation of the maternal diet with fructose modulated the maternal microbiome, increased diversity and abundance of Lactobacillus and Bacteroides species. In offspring maintained on this diet up to pregnancy and term there was a reduction in gene expression of markers of gut barrier function that could adversely affect its function. This was associated with an exacerbated insulin response to pregnancy, reduced birth weight, but increased fat mass. In conclusion dietary supplementation with fructose modulates the maternal microbiome in ways that could adversely affect fetal growth and later gut development.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| 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 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".