Select human milk oligosaccharide supplementation in post‐weanling rats affects metabolism and gut microbiota into adulthood
Bibliographic record
Abstract
OBJECTIVE: Feeding infants with human milk versus formula can produce long-lasting benefits, including reduced risk of inflammatory diseases. Most infant formulas do not contain human milk oligosaccharides (HMOs), which are important carbohydrates in human breast milk displaying prebiotic properties. The study's aim was to examine the effect of select HMOs in the post-weaning period. METHODS: Metabolic and microbial outcomes were measured in female and male rats whose post-weaning diet was supplemented with 3'sialyllactose and 2'-O-fucosyllactose (low dose, 0.75% of each, or high dose, 2% of each). It was determined whether exposure to the HMOs would attenuate metabolic dysfunction associated with a high fat/sucrose (HFS) diet. RESULTS: HMO supplementation resulted in dose-dependent and sex-dependent effects, with the high HMO female group displaying reduced food intake and percentage body fat and an increase in Blautia abundance. Early life HMO supplementation did not prevent the effects of an HFS diet on metabolic outcomes; however, rats that received high dose HMOs followed by the HFS diet were the only HFS group that maintained a measurable abundance of Blautia. CONCLUSIONS: This study highlights the potential for HMOs in follow-up infant formulas. Further investigation should include variable HMO mixtures and doses to optimize infant nutrition at this critical stage.
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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) | 0.001 | 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".