Introduction: Nonalcoholic fatty liver disease (NAFLD) is a chronic liver disease ranging from liver steatosis to nonalcoholic steatohepatitis (NASH). Besides lifestyle modifications, Vitamin E (800 IU/day) is generally recommended for NASH. Vitamin E monotherapy is not sufficient for the multifaceted disease like NALFD. The combination of Vitamin E 400IU and Fraxinus excelsior 500 mg twice daily was found to be better than vitamin E 400 IU twice daily in improving the lipid profile and liver function parameters in patients with NAFLD. We conducted a study to assess safety and effectiveness of Vitamin E plus Fraxinus excelsior in Indian patients with NAFLD in real-world settings.How to cite this paper:Grade III and Grade I liver steatosis, respectively. After 12 weeks of treatment with vitamin E and Fraxinus excelsior combination, 21% patients had no steatosis, 58.79% patients were in Grade 1 steatosis, 19.57% in grade II steatosis and only 0.63% patients in Grade III steatosis. The mean percentage reduction in aspartate aminotransferase (AST) level at week 6 and week 12 from baseline was 24.92% and 43.79%, respectively. Similarly, the mean percentage reduction in alanine aminotransferase (ALT) level at week 6 and week 12 from baseline was 24.37% and 44.05% respectively. The mean reductions in AST and ALT were significant at week 6 and week 12. More than 50% of the investigators rated treatment as excellent for the safety and effectiveness. Conclusion: Evidence from this Indian real-life study suggests that Vitamin E (400 IU) and Fraxinus excelsior (500 mg) is safe and effective for the treatment of NAFLD in routine clinical practice. Its consumption is associated with improvement in hepatic steatosis and liver function parameters (AST and ALT). Given the limited therapeutic options in NAFLD, this combination has the potential to bridge the therapeutic gap in management of NAFLD.

Anomaly detection attempts to recognize abnormal behavior to detect intrusions. We have concentrated to design a prototype UNIX Anomaly Detection System. Neural Networks are tolerant of imprecise data and uncertain information. A tool has been devised for detecting such intrusions into the network. The tool uses the machine learning approaches ad clustering techniques like Self Organizing Map and compares it with the K-means approach. Our system is described for applying hierarchical unsupervised neural network to intrusion detection system.