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Reassessment of the Vascularization of Renal Subcapsular Islet Grafts

2004· article· en· W1965644358 on OpenAlexaff
Tatsuya Kin, Ray V. Rajotte, Gregory S. Korbutt

Bibliographic record

VenuePancreas · 2004
Typearticle
Languageen
FieldMedicine
TopicPancreatic function and diabetes
Canadian institutionsAlberta Medical AssociationUniversity of Alberta
Fundersnot available
KeywordsRenal capsuleMedicineTransplantationIsletKidneyCapsuleRenal arteryLigationUrologyLeft renal veinKidney transplantationRenal veinInternal medicineSurgeryInsulinBiology

Abstract

fetched live from OpenAlex

OBJECTIVES: The purpose of this study was to evaluate the functional significance of the renal capsular vessels in renal subcapsular islet grafts. METHODS: Syngeneic islets were transplanted under the left renal capsule of diabetic Wistar-Furth rats. At 4 weeks post-transplantation, the left renal artery and vein were ligated (group A); in group B, the left renal capsule was dissected to remove capsular vessels; or both were performed in group C. Controls included ligation of the right renal vessels (group D). RESULTS: : All recipients achieved normoglycemia post-transplantation. Treatments for groups A, B, and D did not result in significant changes in glycemia and glucose tolerance. In contrast, all rats in group C returned to hyperglycemia immediately post-treatment. Insulin contents in grafts harvested at 10 days post-treatment in groups A and B were significantly lower than those in group D but higher than those in group C. Histologic examination revealed well-preserved insulin-positive cells under the capsule of necrotic kidney at 8 weeks post-treatment in group A. CONCLUSIONS: Renal subcapsular islet grafts do not acquire their blood supply solely from the renal artery but rather from the renal capsular arteries as well. Not only renal veins but also renal capsular veins play a role as effluent vessels from these grafts.

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: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.410
Threshold uncertainty score0.207

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
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)0.0000.000

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 head0.009
GPT teacher head0.236
Teacher spread0.226 · 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 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

Citations5
Published2004
Admission routes1
Has abstractyes

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