In Vitro Probiotic Modulation of the Intestinal Microbiota and 2′Fucosyllactose Consumption in Fecal Cultures from Infants at Two Months of Age
Bibliographic record
Abstract
2′-fucosyllactose (2′FL) is one of the most abundant oligosaccharides in human milk, with benefits on neonatal health. Previous results point to the inability of the fecal microbiota from some infants to ferment 2′FL. We evaluated a probiotic formulation, including the strains Lactobacillus helveticus Rosell®-52 (R0052), Bifidobacterium longum subsp. infantis Rosell®-33 (R0033), and Bifidobacterium bifidum Rosell®-71 (R0071), individually or in an 80:10:10 combination on the microbiota and 2′FL degradation. Independent batch fermentations were performed with feces from six full-term infant donors of two months of age (three breastfed and three formula-fed) with added probiotic formulation or the constituent strains in the presence of 2′FL. Microbiota composition was analyzed by 16S rRNA gene sequencing. Gas accumulation, pH decrease and 2′FL consumption, and levels of different metabolites were determined by chromatography. B. bifidum R0071 was the sole microorganism promoting a partial increase of 2′FL degradation during fermentation in fecal cultures of 2′FL slow-degrading donors. However, major changes in microbiota composition and metabolic activity occurred with L. helveticus R0052 or the probiotic formulation in cultures of slow degraders. Further studies are needed to decipher the role of the host intestinal microbiota in the efficacy of these strains.
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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 | 0.000 | 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) | 0.001 | 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".