Islet Graft Assessment in the Edmonton Protocol
Bibliographic record
Abstract
The success of the Edmonton Protocol for islet transplantation has provided new hope in the treatment of type 1 diabetes. This study reports on the assessment of 83 human islet grafts transplanted using the Edmonton Protocol since 1999. Cellular composition, as assessed by immunohistochemistry, showed a lower islet purity (approximately 40%) than has been reported in previous studies using dithizone staining to quantitate islet equivalents. Furthermore, grafts were found to contain substantial populations of exocrine and ductal tissue. Total cellular insulin transplanted was 8,097.6 +/- 3,164.4 microg/patient, and was significantly lower in bottom gradient layer grafts than top gradient layer or whole/combined grafts (P < 0.0005). A static incubation test for islet function gave a stimulation index of 3-4, although this measure did not correlate with posttransplant metabolic outcome. Furthermore, we confirmed a previously reported trend in which donor age affects islet yield and purity. It is important to note that a significant positive correlation was observed between the number of islet progenitor (ductal-epithelial) cells transplanted and long-term metabolic success as assessed an by intravenous glucose tolerance test at approximately 2 years posttransplant. In summary, careful assessment of islet graft composition is needed in a clinical transplantation program to accurately estimate islet purity and assess the contribution of other cell types present, such as islet progenitor 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 | 0.004 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.017 | 0.003 |
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".