Intestinal Microbial Composition of Children in a Randomized Controlled Trial of Probiotics to Treat Acute Gastroenteritis
Bibliographic record
Abstract
Compositional analysis of the intestinal microbiome in pre-schoolers is understudied. Effects of probiotics on the gut microbiota were evaluated in children under 4-years-old presenting to an emergency department with acute gastroenteritis. Included were 70 study participants (n=32 placebo, n=38 probiotics) with stool specimens at baseline (day 0), day 5, and after a washout period (day 28). Microbiota composition and deduced functions were profiled using 16S ribosomal RNA sequencing and predictive metagenomics, respectively. Probiotics were detected at day 5 of administration but otherwise had no discernable effects, whereas detection of bacterial infection (P<0.001) and participant age (P<0.001) had the largest effects on microbiota composition, microbial diversity, and deduced bacterial functions. Participants under 1 year had lower bacterial diversity than older aged pre-schoolers; compositional changes of individual bacterial taxa were associated with maturation of the gut microbiota. Advances in age were associated with differences in gut microbiota composition and deduced microbial functions, which have the potential to impact health later in life. Clinical Trial Registration: www.ClinicalTrials.gov, identifier: NCT01853124.
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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 | 0.003 | 0.005 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.005 | 0.003 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.005 | 0.001 |
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".