Urinary Phenotyping Indicates Weight Loss-Independent Metabolic Effects of Roux-en-Y Gastric Bypass in Mice
Bibliographic record
Abstract
Patients with a body mass index (BMI) above 35 kg/m(2) with metabolic diseases benefit from Roux-en-Y gastric bypass (RYGB) independently of their final BMI and the amount of body weight lost. However, the weight loss independent metabolic effects induced by RYGB remain less well understood. To elucidate metabolic changes after RYGB, (1)H NMR spectroscopy-based urine metabolic profiles from RYGB (n = 7), ad libitum-fed sham (AL, n = 5), and body-weight-matched sham (BWM, n = 5) operated mice were obtained. Gut morphometry and fecal energy content were analyzed. Food intake and body weight of RYGB mice were significantly reduced (p = 0.001) compared to sham-AL. There was a strong tendency that BWM-shams required less food to maintain the same body weight as RYGB mice (p = 0.05). No differences were found in fecal energy content between the groups, excluding malabsorption in RYGB animals. Unlike RYGB-operated rats, gut hypertrophy was not observed in RYGB-operated mice. Urinary tricarboxylic acid cycle intermediates were higher in the sham groups, suggesting altered mitochondrial metabolism after RYGB surgery. Higher urinary levels of trimethylamine, hippurate and trigonelline in RYGB mice indicate that the RYGB operation caused microbial disturbance. Taken together, we demonstrate for the first time that there are RYGB specific metabolic effects, which are independent of food intake and body weight loss. Increased utilization of TCA cycle intermediates and altered gut microbial-host co-metabolites might indicate increased energy expenditure and microbial changes in the gut, respectively.
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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) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 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".