Effect of faecal microbial transplant via colonoscopy in patients with severe obesity and insulin resistance: A randomized double‐blind, placebo‐controlled Phase 2 trial
Bibliographic record
Abstract
AIM: To assess the effects of faecal microbial transplant (FMT) from lean people to subjects with obesity via colonoscopy. MATERIAL AND METHODS: and insulin resistance were randomized, in a 1:1 ratio in blocks of four, to either allogenic (from healthy lean donor; n = 15) or autologous FMT (their own stool; n = 13) delivered in the caecum and were followed for 3 months. The main outcome was homeostatic model assessment of insulin resistance (HOMA-IR) and secondary outcomes were glycated haemoglobin levels, lipid profile, weight, gut hormones, endotoxin, appetite measures, intestinal microbiome (IM), metagenome, serum/faecal metabolites, quality of life, anxiety and depression scores. RESULTS: In the allogenic versus autologous groups, HOMA-IR and clinical variables did not change significantly, but IM and metabolites changed favourably (P < 0.05): at 1 month, Coprococcus, Bifidobacterium, Bacteroides and Roseburia increased, and Streptococcus decreased; at 3 months, Bacteroides and Blautia increased. Several species also changed significantly. For metabolites, at 1 month, serum kynurenine decreased and faecal indole acetic acid and butenylcarnitine increased, while at 3 months, serum isoleucine, leucine, decenoylcarnitine and faecal phenylacetic acid decreased. Metagenomic pathway representations and network analyses assessing relationships with clinical variables, metabolites and IM were significantly enhanced in the allogenic versus autologous groups. LDL and appetite measures improved in the allogenic (P < 0.05) but not in the autologous group. CONCLUSIONS: Overall, in those with obeisty, allogenic FMT via colonoscopy induced favourable changes in IM, metabolites, pathway representations and networks even though other metabolic variables did not change. LDL and appetite variables may also benefit.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.004 | 0.002 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.007 | 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".