Impact of Pancreatic Cold Preservation on Rat Islet Recovery and Function
Bibliographic record
Abstract
BACKGROUND: Islet transplantation success depends on the number and quality of islets transplanted. This study aimed at exploring the molecular mechanisms associated with cold pancreas preservation and their impact on islet cell survival and function. METHODS: Rat pancreata were stored in cold University of Wisconsin preservation solution for short (3 hr; control) or long (18 hr) cold ischemia times (CIT). RESULTS: Pancreata exposed to long CIT yielded lower islet numbers and showed reduced cellular viability; isolated islets displayed higher levels of phosphorylated stress-activated protein kinase (c-jun N-terminal Kinase and Mitogen-Activated Protein Kinase-p38), and chemokine (C-C) ligand-3, and lower levels of vascular endothelial growth factor, interleukins (IL)-9 and IL-10. Islets obtained from long-CIT pancreata were functionally impaired after transplantation. Differential proteomic expression in pancreatic tissue after CIT included increased eukaryotic translation elongation factor-1-alpha-1 (apoptosis related) and reduced Clade-B (serine protease inhibitor). CONCLUSIONS: Our study indicates that cold ischemia stimulates inflammatory pathways (chemokine (c-c)ligand-3, phosphorylation of c-jun N-terminal Kinase and mitogen-activated protein kinase-p38, and eukaryotic translation elongation factor-1-alpha-1) and decreases repair/cytoprotective pathways (IL-10, vascular endothelial growth factor, and Clade-B), all of which may negatively affect the quality and mass of islets obtained from a donor 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 | 0.000 | 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 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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 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".