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Record W2623455668 · doi:10.1053/j.gastro.2017.05.055

Prebiotics Reduce Body Fat and Alter Intestinal Microbiota in Children Who Are Overweight or With Obesity

2017· article· en· W2623455668 on OpenAlexaff
Alissa C. Nicolucci, Megan Hume, Inés Martínez, Shyamchand Mayengbam, Jens Walter, Raylene A. Reimer

Bibliographic record

VenueGastroenterology · 2017
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicGut microbiota and health
Canadian institutionsUniversity of AlbertaUniversity of Calgary
Fundersnot available
KeywordsOverweightObesityMedicinePhysiologyEndocrinologyInternal medicine

Abstract

fetched live from OpenAlex

BACKGROUND & AIMS: It might be possible to manipulate the intestinal microbiota with prebiotics or other agents to prevent or treat obesity. However, little is known about the ability of prebiotics to specifically modify gut microbiota in children with overweight/obesity or reduce body weight. We performed a randomized controlled trial to study the effects of prebiotics on body composition, markers of inflammation, bile acids in fecal samples, and composition of the intestinal microbiota in children with overweight or obesity. METHODS: We performed a single-center, double-blind, placebo-controlled trial of 2 separate cohorts (March 2014 and August 2014) at the University of Calgary in Canada. Participants included children, 7-12 years old, with overweight or obesity (>85th percentile of body mass index) but otherwise healthy. Participants were randomly assigned to groups given either oligofructose-enriched inulin (OI; 8 g/day; n=22) or maltodextrin placebo (isocaloric dose, controls; n=20) once daily for 16 weeks. Fat mass and lean mass were measured using dual-energy-x-ray absorptiometry. Height, weight, and waist circumference were measured at baseline and every 4 weeks thereafter. Blood samples were collected at baseline and 16 weeks, and analyzed for lipids, cytokines, lipopolysaccharide, and insulin. Fecal samples were collected at baseline and 16 weeks; bile acids were profiled using high-performance liquid chromatography and the composition of the microbiota was analyzed by 16S rRNA sequencing and quantitative polymerase chain reaction. The primary outcome was change in percent body fat from baseline to 16 weeks. RESULTS: After 16 weeks, children who consumed OI had significant decreases in body weight z-score (decrease of 3.1%), percent body fat (decrease of 2.4%), and percent trunk fat (decrease of 3.8%) compared with children given placebo (increase of 0.5%, increase of 0.05%, and decrease of 0.3%, respectively). Children who consumed OI also had a significant reduction in level of interleukin 6 from baseline (decrease of 15%) compared with the placebo group (increase of 25%). There was a significant decrease in serum triglycerides (decrease of 19%) in the OI group. Quantitative polymerase chain reaction showed a significant increase in Bifidobacterium spp. in the OI group compared with controls. 16S rRNA sequencing revealed significant increases in species of the genus Bifidobacterium and decreases in Bacteroides vulgatus within the group who consumed OI. In fecal samples, levels of primary bile acids increased in the placebo group but not in the OI group over the 16-week study period. CONCLUSIONS: In a placebo-controlled, randomized trial, we found a prebiotic (OI) to selectively alter the intestinal microbiota and significantly reduce body weight z-score, percent body fat, percent trunk fat, and serum level of interleukin 6 in children with overweight or obesity (Clinicaltrials.gov no: NCT02125955).

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.004
Threshold uncertainty score0.008

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0020.000

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.

Opus teacher head0.007
GPT teacher head0.247
Teacher spread0.239 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

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".

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Citations507
Published2017
Admission routes1
Has abstractno

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