Normothermic <em>Ex Vivo</em> Pancreas Perfusion for the Preservation of Pancreas Allografts before Transplantation
Bibliographic record
Abstract
Pancreas transplantation (PTx) is a curative treatment for people who live with the burden of a diagnosis of diabetes mellitus (DM). However, due to organ shortages and increasing numbers of patients being listed for PTx, new strategies are needed to increase the number of available grafts for transplantation. Static cold storage (SCS) is considered the gold standard for standard criteria organs. However, standard criteria donors (SCD) are becoming scarce and new strategies that can increase the rate of organ acceptance from extended criteria donors (ECD) are urgently needed. Normothermic ex vivo perfusion (NEVP) is one of the strategies that has become increasingly popular over the past couple of decades. This preservation method has already been used successfully in other organs (liver, kidneys, and lungs) but has been minimally explored in pancreas transplantation. The few papers that describe the method for pancreas show little success, edema being one of the major issues. The following manuscript describes the successful NEVP method and setup developed by our group to perfuse swine pancreas.
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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 | 0.000 |
| 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 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.006 | 0.002 |
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".