Roux-en-Y Gastric Bypass is Associated With Increased Intestinal Glucose Uptake in Humans
Bibliographic record
Abstract
Abstract Context In animal models, Roux-en-Y gastric bypass (RYGB) is associated with increased Roux limb intestinal glucose uptake that may contribute to early metabolic benefits, though prospective clinical studies are lacking. Objective The present study aimed to test the hypothesis that Roux limb glucose uptake would increase relative to baseline in a cohort of patients undergoing RYGB. Methods RYGB patients underwent preoperative baseline, and 3- and 6-month positron emission tomography/computed tomography postoperative imaging. Maximum and mean standardized uptake values (SUV) were measured from the following predefined regions of interest: cecum, hepatic flexure, splenic flexure, sigmoid colon, duodenal bulb, Roux limb, and common channel. SUV ratios were normalized to the spleen for assessment of longitudinal change. Results Despite significant weight loss in all patients, no changes in Roux limb glucose uptake were observed relative to baseline; however, marked increases in glucose uptake were detected in the colon (cecum, hepatic flexure, and sigmoid colon) by 3 months that were maintained at 6 months (P < .05). Conclusion RYGB is associated with increased intestinal glucose uptake in humans, but this increase appears limited to the colon in the early postoperative period up to 6 months. While the marked increases in Roux limb glucose uptake may contribute to weight loss in rodent models, this mechanism does not appear to translate to human physiology. Unexpected increases in colonic glucose uptake warrant dedicated mechanistic studies to determine the clinical significance of these changes.
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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 | 0.000 |
| 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".