Novel Curcumin Analogue L6H4 in Treating Liver Fibrosis and Type 2 Diabetes

Purpose

The objective of this study was to evaluate the therapeutic efficacy of the curcumin analogue L6H4 in attenuating liver fibrosis and alleviating insulin resistance in streptozotocin-induced diabetic rats.

Methods

Male Sprague-Dawley rats were fed a high-fat diet to induce insulin resistance, followed by streptozotocin injection to induce diabetes. The rats were then treated with L6H4 for eight weeks. Body weight, metabolic parameters, liver function, and liver histopathology were evaluated. Immunohistochemistry was performed to assess the expression of TGF-β1, TIMP-2, and MMP-2 in liver tissues. Statistical analysis was conducted using one-way ANOVA and Spearman rank correlation test.

Results

L6H4 treatment effectively reversed the weight gain associated with a high-fat diet and improved metabolic parameters in diabetic rats. Liver function markers, such as ALT and AST, were reduced after L6H4 treatment. Histological analysis showed improved liver morphology and reduced fibrosis in L6H4-treated rats. Electron microscopy revealed improved ultrastructural features of hepatocytes. Immunohistochemistry demonstrated downregulation of TGF-β1 and TIMP-2 expression and restoration of MMP-2 expression in the liver tissue of L6H4-treated rats. Correlation analysis showed a significant positive correlation between TGF-β1 and TIMP-2 expression.

Conclusion

The findings suggest that L6H4 has therapeutic potential in attenuating liver fibrosis and alleviating insulin resistance in streptozotocin-induced diabetic rats. The hepatoprotective effect of L6H4 may be attributed to its anti-inflammatory properties and its ability to target molecules involved in fibrosis. Further research is warranted to explore the potential of L6H4 as a treatment option for nonalcoholic fatty liver disease and type 2 diabetes.

Application of artificial neural networks in detection and diagnosis of gastrointestinal and liver tumors

As a form of artificial intelligence, artificial neural networks (ANNs) have the advantages of adaptability, parallel processing capabilities, and non-linear processing. They have been widely used in the early detection and diagnosis of tumors. In this article, we introduce the development, working principle, and characteristics of ANNs and review the research progress on the application of ANNs in the detection and diagnosis of gastrointestinal and liver tumors.