Simulation of gastric bypass effects on glucose metabolism and non-alcoholic fatty liver disease with the Sleeveballoon device
Bibliographic record
Abstract
Background Gastric bypass surgery is a very effective treatment of obesity and type 2 diabetes. However, very few eligible patients are offered surgery. Some patients also prefer less invasive approaches. We aimed to study the effects of the Sleeveballoon – a new device combining an intragastric balloon with a connecting sleeve, which covers the duodenal and proximal jejunal mucosa – on insulin sensitivity, glycemic control, body weight and body fat distribution. Methods We compared the effects of Sleeveballoon, Roux-en-Y Gastric-Bypass (RYGB) and sham-operation in 30 high-fat diet (HFD) fed Wistar rats. Whole body and hepatic insulin sensitivity and insulin signaling were studied. Transthoracic echocardiography was performed using a Vevo 2100 system (FUJIFILM VisualSonics Inc., Canada). Gastric emptying was measured using gastrografin. Findings Hepatic ( P = .023) and whole-body ( P = .011) insulin sensitivity improved in the Sleeveballoon and RYGB groups compared with sham-operated rats. Body weight reduced in both Sleeveballoon and RYGB groups in comparison to the sham-operated group (503.1 ± 8.9 vs. 614.4 ± 20.6 g, P = .006 and 490.0 ± 17.7 vs. 614.4 ± 20.6 g, P = .006, respectively). Ectopic fat deposition was drastically reduced while glycogen content was increased in both liver and skeletal muscle. Gastric emptying (T 1/2 ) was longer (157.7 ± 29.2 min, P = .007) in the Sleeveballoon than in sham-operated rats (97.1 ± 26.3 min), but shorter in RYGB (3.5 ± 1.1 min, P < .0001). Cardiac function was better in Sleeveballoon and RYGB versus sham-operated rats. Interpretation The Sleeveballoon reduces peripheral and hepatic insulin resistance, glycaemia, body weight and ectopic fat deposition to a similar level as RYGB, although the contribution of gastric emptying to blood glucose reduction is different.
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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".