Effect of lactose on gut microbiota and metabolome of infants with cow’s milk allergy
Bibliographic record
Abstract
To cite this article: Francavilla R, Calasso M, Calace L, Siragusa S, Ndagijimana M, Vernocchi P, Brunetti L, Mancino G, Tedeschi G, Guerzoni E, Indrio F, Laghi L, Miniello VL, Gobbetti M, De Angelis M. Effect of lactose on gut microbiota and metabolome of infants with cow’s milk allergy. Pediatric Allergy Immunology 2012: 23 : 420–427. Abstract Allergic infants have an unusual gastrointestinal microbiota with low numbers of Bifidobacterium /Lactobacilli and high levels of Clostridium , staphylococci and Escherichia coli. Hydrolyzed formula used to treat these infants is deprived of lactose that instead may influence the gut microbial composition. The aim of the present study is to investigate the influence of lactose on the composition of the gut microbiota and metabolome of infants with cow’s milk allergy. Infants prospectively enrolled received an extensively hydrolyzed formula with no lactose for 2 months followed by an identical lactose‐containing formula for an additional 2 months. Healthy, age‐gender‐matched infants were used as controls. The following determinations were performed before and after the introduction of lactose in the diet: enumeration of cells present in the feces using FISH, counts of viable bacterial cells and gas‐chromatography mass spectrometry/solid‐phase microextraction analysis. The addition of lactose to the diet significantly increases the counts of Bifidobacteria and lactic acid bacteria (p < 0.01), decreases that of Bacteroides/clostridia (p < 0.05) reaching counts found in healthy controls; lactose significantly increases the concentration of total short‐chain fatty acids (p < 0.05). The addition of lactose to an extensively hydrolyzed formula is able to positively modulate the composition of gut microbiota by increasing the total fecal counts of Lactobacillus/Bifidobacteria and decreasing that of Bacteroides/Clostridia. The positive effect is completed by the increase of median concentration of short chain fatty acids, especially for acetic and butyric acids demonstrated by the metabolomic analysis.
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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 | 0.001 |
| 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) | 0.001 | 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".