Development of techniques for gastrojejunal bypass surgery in obese mice
Bibliographic record
Abstract
We have previously described a duodenojejunal bypass (DJB) surgical model in healthy C57BL/6 mice. However, our pilot study showed that the same surgical technique caused a high mortality rate in obese mice. In this study, to significantly improve animal survival rate following bariatric surgery and thereby providing a stable surgical model for the study of glucose homeostasis in obese mice, we have used modified techniques and developed the end-to-side gastrojejunal bypass (GJB) surgery in obese C57BL/6 with impaired glucose tolerance. The modification consisted of using the distal part of the jejunum for biliopancreatic diversion including: 1) ligation of the distal stomach at the level of the pylorus; 2) connection the jejunum to the anterior wall of stomach in an end-to-side fashion; and 3) diverting the biliopancreatic secretions through the blind limb into the distal jejunum through an end-to-side anastomosis. We found that by modifying the proximal end-to-end duodenojejunal anastomosis, described in our original model, to an end-to-side gastrojejunal anastomosis in these obese mice, we were able to significantly improve the postoperative mortality in this study. We have also demonstrated that performing the GJB surgery in obese mice resulted in significant weight loss, normalized blood glucose levels, and prevented acute pancreatitis. This newly developed GJB surgery in the obese mice offers a unique advantage to study the mechanisms of gastrointestinal surgery as treatment for type 2 diabetes.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.004 |
| Insufficient payload (model declined to judge) | 0.004 | 0.002 |
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".