Protective Effects of Proanthocyanidin on Cerulein-induced Acute Pancreatic Inflammation in Rats
Bibliographic record
Abstract
Background: The aim of this study was to assess the possible protective effect of proanthocyanidin against cerulein-induced acute pancreatic inflammation (AP) and oxidative injury. Methods: Sprague-Dawley rats were pretreated with proanthocyanidine (100 mg/kg, orally) or saline 15 min before cerulein was given by 20 µg/kg subcutaneously at 1-h intervals within 4 hours. Six hours after cerulein or saline injections, the animals were killed by decapitation. Blood samples were collected to analyze amylase, lipase, and proinflammatory cytokines (TNF-alpha and IL-1b). Pancreas tissues were taken for the determination of tissue glutathione (GSH) and malondialdehyde (MDA) levels, Na + , K + -ATPas e and myeloperoxidase (MPO) activities. Formation of reactive oxygen species in pancreatic tissue samples was monitored by using chemiluminescence (CL) technique with luminol and lucigenin probes, while the extent of tissue injury was analyzed microscopically. Results: Acute pancreatitis caused a significant decrease in tissue GSH level and Na + , K + -ATPase activity, which was accompanied with significant increases in the pancreatic MDA, luminol and lucigenin chemiluminescences (CL) levels and MPO activity. Similarly TNF-alpha and IL-1beta levels were elevated in the pancreatic group as compared to control group. On the other hand, proanthocyanidin treatment reversed all these biochemical indices, as well as histopathological alterations that were induced by cerulein. Conclusions: Proanthocyanidine can ameliorate pancreatic injury induced by cerulein in rats, this result suggests that proanthocyanidin may have utility in treating acute pancreatititis. Gastroenterol Res. 2009;2(1):20-28 doi: https://doi.org/10.4021/gr2009.02.1276
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 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) | 0.000 | 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 teacher head, 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".