Gut microbiome modified by bariatric surgery improves insulin sensitivity and correlates with increased brown fat activity and energy expenditure
Bibliographic record
Abstract
Alterations in the microbiome correlate with improved metabolism in patients following bariatric surgery. While fecal microbiota transplantation (FMT) from obese patients into germ-free (GF) mice has suggested a significant role of the gut microbiome in metabolic improvements following bariatric surgery, causality remains to be confirmed. Here, we perform paired FMT from the same obese patients (BMI > 40; four patients), pre- and 1 or 6 months post-Roux-en-Y gastric bypass (RYGB) surgery, into Western diet-fed GF mice. Mice colonized by FMT from patients' post-surgery stool exhibit significant changes in microbiota composition and metabolomic profiles and, most importantly, improved insulin sensitivity compared with pre-RYGB FMT mice. Mechanistically, mice harboring the post-RYGB microbiome show increased brown fat mass and activity and exhibit increased energy expenditure. Moreover, improvements in immune homeostasis within the white adipose tissue are also observed. Altogether, these findings point to a direct role for the gut microbiome in mediating improved metabolic health post-RYGB surgery.
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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) | 0.000 | 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 | 0.001 |
| 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".