Role of Wnt/β-catenin pathway agonist SKL2001 in Caerulein-induced acute pancreatitis
Bibliographic record
Abstract
The goal of this study was to clarify the protective role of the Wnt/β-catenin pathway agonist SKL2001 in a rat model of Caerulein-induced acute pancreatitis. AR42J cells and rats were divided into 4 groups: control, Caerulein, SKL2001 + Caerulein, and SKL2001 + control. Cell apoptosis was examined using flow cytometry. Hematoxylin-eosin staining was performed to observe pathological changes in pancreatic and small intestinal tissues. Inflammatory cytokines were detected by enzyme-linked immunosorbent assay (ELISA), while genes related to the Wnt/β-catenin pathway were quantified using quantitative real-time PCR. In vitro results showed that Caerulein promoted cell necrosis, inhibited the Wnt/β-catenin pathway, and increased the level of inflammatory cytokines. However, SKL2001 reduced cell necrosis and inflammatory cytokines and activated the Wnt/β-catenin pathway. Additionally, in vivo results demonstrated the accumulation of fluid (i.e., edema), hemorrhage, inflammation and necrosis of the pancreatic acini occurred 6 h after the final Caerulein induction, with the damage reaching a maximal level 12 h after the final Caerulein induction; meanwhile, the Wnt/β-catenin pathway was evidently inhibited with an enhanced level of inflammatory cytokines. The aforementioned damage was further aggravated 12 h later. Nevertheless, the pancreatic and small intestinal tissue damages were alleviated in Caerulein-induced rats treated with SKL2001. In conclusion, activation of the Wnt/β-catenin pathway could inhibit Caerulein-induced cell apoptosis and inflammatory cytokine release, thus improving pancreatic and intestinal damage in rats with acute pancreatitis.
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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 | 0.000 | 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) | 0.001 | 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".