Intra‐Ductal Glutamine Administration Reduces Oxidative Injury During Human Pancreatic Islet Isolation
Bibliographic record
Abstract
Oxidative stress during islet isolation induces a cascade of events injuring islets and hampering islet engraftment. This study evaluated islet isolation and transplantation outcomes after intra-ductal glutamine administration. Human pancreata deemed unsuitable for pancreas or islet transplantation were treated with either a 5 mM solution of l-glutamine (n = 6) or collagenase enzyme alone (n = 6) through the main pancreatic duct. Islet yield, viability, in vitro function; markers of oxidative stress [malondialdehyde (MDA) and Glutathione (GSH)] and apoptosis were assessed. Islet yields were significantly increased in the glutamine group compared to controls (318, 559 +/- 25, 800 vs. 165, 582 +/- 39, 944 mean +/- SEM, p < 0.01). The amount of apoptotic cells per islet was smaller in the glutamine group than the control. The percentage of nude mice rendered normoglycemic with glutamine-treated islets was higher than the controls (83% n = 10/12 vs. 26% n = 6/23; p < 0.01), and the time to reach normoglycemia was decreased in the glutamine group (1.83 +/- 0.4 vs. 7.3 +/- 3 days; p < 0.01). Glutamine administration increased GSH levels (7.6 +/- 1.7 nmol/mg protein vs. 4.03 +/- 0.5 in control, p < 0.05) and reduced lipid-peroxidation (MDA 2.45 +/- 0.7 nmol/mg of protein vs. 6.54 +/- 1.7 in control; p < 0.05). We conclude that intra-ductal administration of glutamine reduces oxidative injury and apoptosis and improves islet yield and islet graft function after 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 | 0.000 |
| 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) | 0.001 | 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".