Quality of Air-Transported Human Islets for Single Islet Cell Preparations
Bibliographic record
Abstract
In new generation medical therapies for type 1 diabetes mellitus (DM), cell-based approaches using pancreatic islets have attracted significant attention worldwide. In particular, dispersed islet cells obtained from isolated pancreatic islets have been a valuable source in the cell biology and tissue engineering fields. Our experimental approach to the development of new islet-based DM therapies consisted of creating a monolithic islet cell sheet format using dispersed islet cells. In this experiment, we explored the potential of internationally transporting human islets from Alberta, Canada to Tokyo, Japan and obtaining viable dispersed islet cells. A total of 34 batches of isolated and purified human islets were transported using a commercial air courier service. Prior to shipping, the human islets had been in culture for 0-108 h at the University of Alberta. The transportation period from Alberta to Tokyo was 2-5 days. The transported human islet cells were enzymatically dispersed as single cells in Tokyo. The number of single islet cells decreased as the number of transportation days increased. In contrast, cell viability was maintained regardless of the number of transportation days. The preshipment culture time had no effect on the number or viability of single cells dispersed in Tokyo. When dispersed single islet cells were plated on laminin-5-coated temperature-responsive polymer-grafted culture dishes, the cells showed favorable attachment followed by extension as a monolithic format. The present study demonstrated that long-distance transported human islets are a viable cell source for experiments utilizing dispersed human islet cells.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".