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Record W2194040129 · doi:10.1210/en.2015-1562

Research-Focused Isolation of Human Islets From Donors With and Without Diabetes at the Alberta Diabetes Institute IsletCore

2015· article· en· W2194040129 on OpenAlexafffundabout
James Lyon, Jocelyn E. Manning Fox, Aliya F Spigelman, Ryekjang Kim, Nancy Smith, Doug O’Gorman, Tatsuya Kin, A. M. James Shapiro, R. V. Rajotte, Patrick E. MacDonald

Bibliographic record

VenueEndocrinology · 2015
Typearticle
Languageen
FieldMedicine
TopicPancreatic function and diabetes
Canadian institutionsUniversity of Alberta
FundersAlberta Diabetes FoundationUniversity of Alberta
KeywordsIsletGlycated hemoglobinDiabetes mellitusType 2 diabetesIsolation (microbiology)MedicineEndocrinologyInternal medicineType 1 diabetesBiologyImmunologyPhysiologyBioinformatics

Abstract

fetched live from OpenAlex

Recent years have seen an increased focus on human islet biology, and exciting findings in the stem cell and genomic arenas highlight the need to define the key features of mature human islets and β-cells. Donor and organ procurement parameters impact human islet yield, although for research purposes islet yield may be secondary in importance to islet function. We examined the feasibility of a research-only human islet isolation, distribution, and biobanking program and whether key criteria such as cold ischemia time (CIT) and metabolic status may be relaxed and still allow successful research-focused isolations, including from donors with type 1 diabetes and type 2 diabetes. Through 142 isolations over approximately 5 years, we confirm that CIT and glycated hemoglobin each have a weak negative impacts on isolation purity and yield, and extending CIT beyond the typical clinical isolation cutoff of 12 hours (to ≥ 18 h) had only a modest impact on islet function. Age and glycated hemoglobin/type 2 diabetes status negatively impacted secretory function; however, these and other biological (sex, body mass index) and procurement/isolation variables (CIT, time in culture) appear to make only a small contribution to the heterogeneity of human islet function. This work demonstrates the feasibility of extending acceptable CIT for research-focused human islet isolation and highlights the biological variation in function of human islets from donors with and without diabetes.

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: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.301
Threshold uncertainty score0.405

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 studies0.0000.001
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 head0.058
GPT teacher head0.316
Teacher spread0.258 · 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

Citations147
Published2015
Admission routes3
Has abstractyes

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