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Compaction of Islets Is Detrimental to Transplant Outcome in Mice

2006· article· en· W2071659185 on OpenAlexaff
Shaheed Merani, Colleen D. Schur, Wayne Truong, Victor K. Knutzen, Jonathan R. T. Lakey, Colin C. Anderson, Camillo Ricordi, A. M. James Shapiro

Bibliographic record

VenueTransplantation · 2006
Typearticle
Languageen
FieldMedicine
TopicPancreatic function and diabetes
Canadian institutionsUniversity of Alberta
Fundersnot available
KeywordsIsletTransplantationMedicineAndrologyIn vivoDiabetes mellitusEndocrinologyInternal medicineImmunologyBiologyBiotechnology

Abstract

fetched live from OpenAlex

BACKGROUND: Despite recent progress in clinical islet transplantation, the cumulative world experience remains small. Optimizing protection of islets throughout the isolation, purification, and peritransplant period remains critical to outcome. We herein investigate the potential detrimental impact of maintaining islets in a pelleted state for periods preceding implantation. We hypothesize that periods of islet compaction lead to impairment if islet function in vivo. METHODS: In this study, 250-islet marginal mass transplants were conducted in the BALB/c syngeneic mouse model using islets either preincubated as an islet pellet or suspended in culture during the 30 min immediately preceding transplant. Nonfasting blood glucose, intraperitoneal glucose tolerance test, graft histology, and graft insulin content were all used to monitor graft function up to four weeks posttransplant. RESULTS: Maintaining islets in a compact pellet for 30 min prior to transplantation significantly reduces the proportion of transplant recipients that achieve normoglycemia (from 100% to 38%, P=0.026) and increases the proportion of apoptotic beta-cells. CONCLUSION: Our findings confirm that damage induced by sustained islet compaction results in poor graft outcome in mice. These findings raise concerns relating to potential damage to human islets prior to clinical transplantation, and this will be explored in further studies.

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 score0.148
Threshold uncertainty score0.303

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 head0.020
GPT teacher head0.286
Teacher spread0.266 · 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

Citations14
Published2006
Admission routes1
Has abstractyes

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