Phytochemical analysis and hepatotoxicity assessment of braised Polygoni Multiflori Radix (Wen-He-Shou-Wu).

Polygoni Multiflori Radix (PMR) is a medicinal herb commonly used in China and Eastern Asia. Recently, the discovery of hepatotoxicity in PMR has received considerable attention from scientists. Processing is a traditional Chinese medicine technique used for the effective reduction of toxicity. One uncommon technique is the braising method-also known as 'Wen-Fa' in Chinese-which is used to prepare tonics or poisonous medications. Braised PMR (BPMR)-also known as 'Wen-He-Shou-Wu'-is one of the processed products of the braising method. However, the non-volatile components of BPMR have not been identified and examined in detail, and therefore, the hepatotoxic advantage of BPMR remains unknown. In this study, we compared the microscopic characteristics of different samples in powder form using scanning electron microscopy (SEM), investigated the non-volatile components, assessed the effects of different processed PMR products on the liver, and compared the differences between BPMR and PMR Praeparata recorded in the Chinese Pharmacopoeia (2020 edition). We found that the hepatotoxicity of BPMR was dramatically decreased, which may be related to an increase in polysaccharide content and a decrease in toxic substances. The present study provides an important foundation for future investigations of the processing mechanisms of BPMR.

PSRna: Prediction of small RNA secondary structures based on reverse complementary folding method.

Prediction of RNA secondary structures is an important problem in computational biology and bioinformatics, since RNA secondary structures are fundamental for functional analysis of RNA molecules. However, small RNA secondary structures are scarce and few algorithms have been specifically designed for predicting the secondary structures of small RNAs. Here we propose an algorithm named "PSRna" for predicting small-RNA secondary structures using reverse complementary folding and characteristic hairpin loops of small RNAs. Unlike traditional algorithms that usually generate multi-branch loops and 5[Formula: see text] end self-folding, PSRna first estimated the maximum number of base pairs of RNA secondary structures based on the dynamic programming algorithm and a path matrix is constructed at the same time. Second, the backtracking paths are extracted from the path matrix based on backtracking algorithm, and each backtracking path represents a secondary structure. To improve accuracy, the predicted RNA secondary structures are filtered based on their free energy, where only the secondary structure with the minimum free energy was identified as the candidate secondary structure. Our experiments on real data show that the proposed algorithm is superior to two popular methods, RNAfold and RNAstructure, in terms of sensitivity, specificity and Matthews correlation coefficient (MCC).