High‐resolution magic angle spinning nuclear magnetic resonance of donor pancreatic tissue may predict islet viability prior to isolation
Bibliographic record
Abstract
For patients with type 1 diabetes mellitus complicated by severe hypoglycemia, clinical islet transplantation is an efficacious alternative to whole pancreas transplantation. While islet transplantation has improved over the last few years, there remain questions regarding its cost-effectiveness and donor allosensitization, which is exacerbated when islets from more than one donor are required. Understanding the features of a pancreas that would provide viable islets prior to isolation may lead to development of an accurate assay that could identify suitable pancreases and provide significant cost savings to a clinical islet transplantation program. In this pilot study, solid-state high-resolution magic angle spinning (HRMAS) nuclear magnetic resonance (NMR) spectroscopy was used to assess samples of convenience of human pancreatic tissue taken prior to islet isolation both before and after incubation using the two-layer perfluorocarbon (PFC)/University of Wisconsin (UW) solution cold-storage method. We observed that, prior to incubation, human pancreatic tissue exhibited evidence of hypoxia with decreased peak integrals associated with glucose and increased peak integrals corresponding to lactate and free fatty acids. After incubation, we observed a reversal of the hypoxia-induced damage, as integrals corresponding to glucose increased, and those corresponding to lactate and free fatty acid resonances decreased. Interestingly, a significant correlation between the ratio of the glucose integral (at 3.0-4.5 ppm) to the sum of the fatty acid (at 0.9 ppm) and lactate + fatty acid (at 1.3 ppm) integrals and glucose responsiveness, a measure of islet viability, of the isolated islets, was observed after incubation in PFC/UW solution for pancreases that responded to PFC/UW solution incubation (p = 0.02). Notably, pancreases with little or no change in the integral ratio after PFC/UW solution incubation had poor recovery. These results suggest that tissue recovery is a key feature for determining islet cell viability, and further that HRMAS NMR may be a practical method to quickly assess human donor pancreatic tissue prior to islet isolation for clinical transplantation.
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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 | 0.001 |
| 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 | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".