Maternal prebiotic supplementation reduces fatty liver development in offspring through altered microbial and metabolomic profiles in rats
Bibliographic record
Abstract
A maternal high-fat/sucrose diet, in the presence of maternal obesity, can program increased susceptibility to obesity and metabolic disease in offspring. In particular, nonalcoholic fatty liver disease risk is associated with poor maternal nutrition and obesity status, which may manifest via alterations in gut microbiota. Here, we report that in a preclinical model of diet-induced maternal obesity, maternal supplementation of a high-fat/sucrose diet with the prebiotic oligofructose improves glucose tolerance, insulin sensitivity, and hepatic steatosis in offspring following a long-term high-fat/sucrose dietary challenge compared with offspring of untreated dams. These improvements are associated with alterations in gut microbial composition and serum inflammatory profiles in early life and improvements in inflammatory and fatty-acid gene expression profiles in tissues. Serum metabolomics analysis highlights potential metabolic links between the gut microbiota and the degree of steatosis, including alterations in 1-carbon metabolism. Overall, our data suggest that maternal prebiotic intake protects offspring against hepatic steatosis and insulin resistance following 21 wk of high fat/sucrose diet, which is in part due to alterations in gut microbiota.-Paul, H. A., Collins, K. H., Nicolucci, A. C., Urbanski, S. J., Hart, D. A., Vogel, H. J., Reimer, R. A. Maternal prebiotic supplementation reduces fatty liver development in offspring through altered microbial and metabolomic profiles in rats.
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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".