Improved Islet Yields From Macaca Nemestrina and Marginal Human Pancreata After Two-Layer Method Preservation and Endogenous Trypsin Inhibition
Bibliographic record
Abstract
We tested whether two-layer method (TLM) pancreas preservation and trypsin inhibition (Pefabloc) during processing allows longer preservation while retaining or improving viable islet recovery. Non-marginal primate (Macaca nemestrina) and marginal human (ischemic or preservation-injured) pancreata were processed with a research-oriented pan technique (Seattle method). Organs were processed upon arrival (± Pefabloc), or after TLM or University of Wisconsin solution (UW) preservation (+ Pefabloc). Islet yield, viability, and function were assessed.\nPefabloc increased M. nemestrina islet yields from 9696 ± 1749 IE/g to 15 822 ± 1332 IE/g (p < 0.01). Two-layer method preservation (< 6 h) further increased yields, to 23 769 ± 2773 IE/g (vs. + Pefabloc; p < 0.01). Similarly, Pefabloc increased marginal human islet yields from 2473 ± 472 IE/g to 4723 ± 1006 IE/g (p < 0.04). This increase was maintained after lengthy TLM preservation (> 30 h; 4801 ± 1066 IE/g).\nWe also tested the applicability of TLM preservation (23.5 ± 3.2 h) to the processing of marginal human pancreata by the Edmonton/Immune Tolerance Network clinical protocol. Islet yield and function approached published results of pancreata processed 4.8 ± 0.8 h after organ recovery (p = 0.06).\nPefabloc, and TLM vs. UW preservation, prolonged the tolerable interval between organ recovery and islet isolation. Islet yield, viability, and functionality improved from both marginal and nonmarginal pancreata.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| 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 | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
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.
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 teacher head, 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".