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Record W2132669196 · doi:10.1002/micr.20454

Establishment of duodenojejunal bypass surgery in mice: A model designed for diabetic research

2008· article· en· W2132669196 on OpenAlexaff
Wei Liu, Roman Zassoko, Tina Mele, Patrick Luke, Hongtao Sun, Weihua Liu, Bertha García, Jifu Jiang, Hao Wang

Bibliographic record

VenueMicrosurgery · 2008
Typearticle
Languageen
FieldMedicine
TopicBariatric Surgery and Outcomes
Canadian institutionsWestern UniversityLawson Health Research InstituteLondon Health Sciences Centre
Fundersnot available
KeywordsMedicineJejunumDuodenumAnastomosisBiliopancreatic DiversionSurgeryDiabetes mellitusMicrosurgeryRoux-en-Y anastomosisGeneral surgeryInternal medicineGastric bypassWeight lossEndocrinologyObesity

Abstract

fetched live from OpenAlex

We have developed a mouse duodenojejunal bypass (DJB) surgical model that is for studying the effects of bariatric surgery on glucose homeostasis and has potential to impact clinical therapy of diabetes. The operation consists of using the majority of the duodenum and proximal part of the jejunum for biliopancreatic diversion. The distal end of the jejunum is anastomosed in an end-to-end fashion to the remaining proximal end of the duodenum just distal to the pylorus. The biliopancreatic secretions are diverted into the distal jejunum through an end-to-side anastomosis. We performed 10 DJB operations in C57BL/6 mice, with a 100% survival rate. The surgery had no effect on the growth or feeding patterns of the animals. The intestinal mucosa showed normal histology and function. This study confirms that it is technically possible to perform DJB surgery in mice. This mouse model can be used in the study of surgical treatment for type II diabetes.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.002
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.004
Threshold uncertainty score0.013

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.001
Meta-epidemiology (narrow)0.0020.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0030.001
Science and technology studies0.0010.001
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0010.004
Insufficient payload (model declined to judge)0.0040.002

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.

Opus teacher head0.112
GPT teacher head0.338
Teacher spread0.227 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designBench or experimental
Domainnot available
GenreEmpirical

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".

Quick stats

Citations25
Published2008
Admission routes1
Has abstractyes

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