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Record W2150579874 · doi:10.2337/diabetes.54.4.1032

Reversal of Diabetes in Pancreatectomized Pigs After Transplantation of Neonatal Porcine Islets

2005· article· en· W2150579874 on OpenAlexaff
Tatsuya Kin, Gregory S. Korbutt, Tsunehiro Kobayashi, Jannette M. Dufour, Ray V. Rajotte

Bibliographic record

VenueDiabetes · 2005
Typearticle
Languageen
FieldMedicine
TopicPancreatic function and diabetes
Canadian institutionsUniversity of Alberta
FundersFondation pour la Recherche Médicale
KeywordsIsletMedicineInsulinTransplantationInternal medicineDiabetes mellitusEndocrinologyMiniature swinePortal vein

Abstract

fetched live from OpenAlex

Neonatal porcine islets (NPIs) are able to grow and to reverse hyperglycemia after transplantation in immunoincompetent mice. The aim of this study was to demonstrate the feasibility of allogeneic NPI grafts to achieve normoglycemia in a pancreatectomized diabetic pig. NPIs were isolated from pancreases of 1- to 3-day-old pigs, cultured, and then transplanted via the portal vein into the liver of totally pancreatectomized pigs (mean body weight, 20.8 kg). Each pig received NPIs consisting of 3.1 +/- 0.3 x 10(6) beta-cells/kg (12,476 +/- 1,146 islet equivalent/kg). The six pigs that were given cyclosporine and sirolimus achieved normoglycemia by day 14 without insulin therapy. Three pigs died of surgical complications shortly after transplantation, whereas the other three remained insulin independent up to day 69. Of seven nonimmunosuppressed recipients, four pigs became normoglycemic by day 14 without insulin treatment, with two of the animals remaining normoglycemic long term. Well-preserved insulin-positive cells were found in the graft at the end of follow-up with a significant increase in insulin content in long-term survivors of both groups. This study demonstrates for the first time that allogeneic NPIs can reverse hyperglycemia in totally pancreatectomized diabetic pigs.

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.367
Threshold uncertainty score0.738

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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.

Opus teacher head0.007
GPT teacher head0.223
Teacher spread0.216 · 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 teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
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

Citations65
Published2005
Admission routes1
Has abstractyes

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