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Record W1980557101 · doi:10.1002/bjs.6391

Optimal implantation site for pancreatic islet transplantation

2008· review· en· W1980557101 on OpenAlexafffund
Shaheed Merani, Christian Toso, Juliet Emamaullee, A. M. James Shapiro

Bibliographic record

VenueBritish journal of surgery · 2008
Typereview
Languageen
FieldMedicine
TopicPancreatic function and diabetes
Canadian institutionsUniversity of Alberta
FundersCanadian Institutes of Health ResearchAlberta Heritage Foundation for Medical ResearchFondation pour la Recherche MédicaleSchweizerischer Nationalfonds zur Förderung der Wissenschaftlichen ForschungNational Science Foundation
KeywordsMedicineIsletTransplantationPancreasImmunosuppressionPouchPortal veinPancreatic isletsIslet cell transplantationSurgeryInsulinInternal medicine

Abstract

fetched live from OpenAlex

BACKGROUND: Since the first report of successful pancreatic islet transplantation to reverse hyperglycaemia in diabetic rodents, there has been great interest in determining the optimal site for implantation. Although the portal vein remains the most frequently used site clinically, it is not ideal. About half of the islets introduced into the liver die during or shortly after transplantation. Although many patients achieve insulin independence after portal vein infusion of islets, in the long term most resume insulin injections. METHODS: This review considers possible sites and techniques of islet transplantation in small and large animal models, and in humans. Metabolic, immunological and technical aspects are discussed. RESULTS AND CONCLUSION: Many groups have sought an alternative site that might offer improved engraftment and long-term survival, together with reduced procedure-related complications. The spleen, pancreas, kidney capsule, peritoneum and omental pouch have been explored. The advantages and disadvantages of various sites are discussed in order to define the most suitable for clinical use and to direct future research.

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)0.001
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: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.003
Threshold uncertainty score0.009

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.001
Science and technology studies0.0000.001
Scholarly communication0.0010.001
Open science0.0010.000
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0030.002

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 head0.059
GPT teacher head0.308
Teacher spread0.249 · 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 designNot applicable
Domainnot available
GenreReview

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

Citations256
Published2008
Admission routes2
Has abstractyes

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