Contribution of a Single Islet Transplant Program to Basic Researchers in North America, Europe, and Asia through Distributing Human Islets
Bibliographic record
Abstract
There has been a steady expansion in islet isolation and transplantation activity worldwide. In addition to preparing human islets for transplantation, we have been providing human islets to basic researchers. The aim of this study was to review the activity of distribution of human islets to basic researchers in North America, Europe, and Asia, and to investigate if there are any differences in utilization rate of islets among three continents. We reviewed our islet isolation batch files, donor records, and documents related to shipping from 2007 to 2023. We have distributed islets to a total of 49 researchers (11 at the University of Alberta campus, 21 in North America, 7 in Europe, 10 in Asia). The yearly average [±SD] of islets distributed was 6,607,443 [±1,782,547] islet equivalents obtained from 28 [±5] pancreases, resulting in 230 [±88] shipments. Standard delivery to Europe or Asia takes at least 2 days whereas researchers in North America receive islets the next day. On top of this fact, we found that delayed delivery occurred more often in Asia (31.9%, 201/631 shipments) and Europe (30.8%, 134/435) than in North America (6.8%, 114/1682). Interestingly, the utilization rate of islets within delayed deliveries was highest in Asia (91.5%, 184/201) followed by Europe (83.6%, 112/134) and North America (77.2%, 88/114). There were disparities in the frequency of delayed deliveries and in the utilization rate among three continents. Our program with a 17-year track record has been actively distributing human islets to researchers in three continents.
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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 | 0.020 | 0.024 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.003 | 0.005 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 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".