Research-Focused Isolation of Human Islets From Donors With and Without Diabetes at the Alberta Diabetes Institute IsletCore
Bibliographic record
Abstract
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.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.005 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 0.001 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".