Tetrahydrobiopterin Attenuates Microvascular Reperfusion Injury Following Murine Pancreas Transplantation
Bibliographic record
Abstract
In this study we investigated the effect of tetrahydrobiopterin (BH4), an essential cofactor for nitric oxide synthases, on ischemia-reperfusion injury (IRI) following murine pancreas transplantation. Pancreatic grafts were exposed to prolonged cold ischemia times (CIT) and different treatment regimens: normal saline (S), S + 16 h CIT, BH4 50 mg/kg + 16 h CIT. Nontransplanted animals served as controls. Graft microcirculation was analyzed by means of functional capillary density (FCD) and capillary diameters (CD) after 2 h reperfusion using intravital microscopy. Quantification of inflammatory responses (mononuclear infiltration) and endothelial disintegration (edema formation) was done by histology (hematoxylin and eosin), and peroxynitrite formation assessed by nitrotyrosine immunostaining. FCD was significantly reduced after prolonged CIT, paralleled by increased peroxynitrite formation as compared with controls (all p < 0.05). Microcirculatory changes correlated significantly with intragraft peroxynitrite generation (Spearman: r = -0.56; p < 0.01). Pancreatic grafts treated with BH4 displayed markedly higher FCD values (p < 0.01) and abrogated nitrotyrosine staining (p = 0.03). CD were not significantly different in any group. Histology showed increased inflammation, interstitial edema, hemorrhage, acinar vacuolization and focal areas of necrosis after 16 h CIT, which was diminished by BH4 administration (p < 0.01). BH4 treatment significantly reduces post-ischemic deterioration of microcirculation as well as histologic damage and might be a promising novel strategy in attenuating IRI following pancreas 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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.003 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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".