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SIMULTANEOUS ISLET LIVER ALLOTRANSPLANTATION IN RATS

2002· letter· en· W1982458679 on OpenAlexaff
James R. Wright, Weiming Yu

Bibliographic record

VenueTransplantation · 2002
Typeletter
Languageen
FieldMedicine
TopicOrgan Transplantation Techniques and Outcomes
Canadian institutionsDalhousie UniversityIzaak Walton Killam Health Centre
Fundersnot available
KeywordsAllotransplantationIsletMedicineLiver transplantationTransplantationPortal veinSplenectomySurgical oncologyHistocompatibilityDiabetes mellitusSpleenInternal medicinePathologySurgeryImmunologyEndocrinologyAntigenHuman leukocyte antigen

Abstract

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In a recent article, Wang et al. (1) report the results of a study in which they “examine the effect of liver transplantation on islet allografts in a rat model by comparing the survival times of islet allografts with or without liver allografting” using a strain combination in which liver allografts are spontaneously accepted across a full MHC barrier. This study provides independent confirmation of a very similar set of experiments and results previously published by Wan et al. (2,3). Our brief but definitive study, performed as a offshoot while we were using combined liver islet isotransplantation as a model to study hepatotropic factors (4), differed only slightly from that of Wang et al. (1) as we utilized different rat strains and islet allotransplantation was via the portal vein rather than the renal subcapsular space. A closely related clinical study has also been performed (5). Surprisingly, none of this work was cited or discussed. In the early 1990s, Tzakis and Riccordi (5) working in Starzl’s laboratory reported the results of a series of combined islet and liver allografts performed in cancer patients having undergone an upper abdominal exenteration because of extensive abdominal spread. The success achieved with this series of clinical islet transplants far exceeded any results before that time and remained unparalleled for another 10 years. Their outstanding results could be logically explained in two ways. First, because the recipients were diabetic secondary to pancreatectomies, there was no autoimmune component to promote graft loss as might be expected in type 1 diabetic patients; this was the explanation invoked by most of the islet transplant community. A second possibility was that liver allografts promoted the survival of simultaneous same donor islet allografts; however, no analogous animal study had been done. Therefore, we performed a study in rats using a strain combination, Wistar-Furth (RT1u) to Lewis (RT1l), in which islet allografts were rapidly rejected [mean graft survival time was 5 days (n=6)] when embolized into the portal veins of streptozotocin-diabetic recipients and in which arterialized orthotopic liver transplants were spontaneously accepted without immunosuppression [mean graft survival time uniformly >90 days (n=10)]. When simultaneous islet/liver transplantations were performed (n=6), two rats remained normoglycemic with adequate liver function for >90 days, two normoglycemic rats died of liver allograft rejection at 13 or 30 days, and two rats became jaundiced/mildly diabetic and were killed at 41 or 63 days. In all six rats, viable islet grafts were identified histologically after death or sacrifice, indicating that in no instance had the islets rejected (2,3). These results, now confirmed by Wang et al. (1), demonstrated that simultaneous orthotopic liver transplantation protects same donor islets from allograft rejection, but that islet allografts are very immunogenic and can precipitate liver allograft rejection. The mechanistic studies by Wang et al. (1) pertaining to up-regulation of Fas ligand and T cell apoptosis are an interesting extension of this work. James R. Wright Jr.1 Weiming Yu

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)0.000
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 score0.006
Threshold uncertainty score0.020

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0030.001
Meta-epidemiology (broad)0.0010.002
Bibliometrics0.0060.001
Science and technology studies0.0010.001
Scholarly communication0.0010.002
Open science0.0020.001
Research integrity0.0010.003
Insufficient payload (model declined to judge)0.0060.003

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 head0.019
GPT teacher head0.258
Teacher spread0.239 · 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

Citations0
Published2002
Admission routes1
Has abstractyes

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