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1.
Article in Chinese | WPRIM | ID: wpr-1015911

ABSTRACT

Gram-positive bacteria secrete virulence factors into host cells and cause suppurative inflammation, which leads to the emergence of diseases, therefore poses a great threat to human health. Identifying secreted proteins is beneficial to understand the secretion system and pathogenic mechanism of bacteria, and lays the foundation for further screening of pathogenic factors. Due to the lack of classical signal peptide sequence in non-classical secreted proteins, it is relatively difficult and time-consuming to identify such proteins in large-scale experiments. At present, some computational prediction methods have been proposed, but their performance in predicting non-classical secreted proteins of Gram-positive bacteria is not satisfactory. This paper proposed an ensemble learning model - SPNG+, which integrates six machine learning algorithms including naive bayes, random forest, support vector machine, two gradient promotion trees XGBoost and LightGBM, and K-nearest neighbor through stacking strategy. The results of 5-fold cross validation and independent dataset test show that the SPNG+ is superior to the single machine learning model, the simple integrated learning model and the existing prediction tools in predicting non-classical secreted proteins of Gram-positive bacteria. Compared with the predictors constructed by limited feature coding methods or single machine learning algorithms in the past, the proposed method is a useful supplement to the study of non-classical secreted proteins in Gram-positive bacteria. The source code of SPNG+ is available from https: / / github.com / weidai00 / SPNG.

2.
Article in Chinese | WPRIM | ID: wpr-872748

ABSTRACT

Sojae Semen Germinatum (SSG) was firstly recorded in Shennong Bencaojing. It is a dry processed product which is germinated using mature seeds of Glycine max. It is neutral in nature and sweet flavor, and its functions are to relieve heat, clear away heat and remove dampness. SSG has a long history of being used both as food and medicine, but it was not enrolled in the Chinese Pharmacopoeia until 2010. Doctors of different dynasties had different views of its processing procedures, and thus the quality of its decoction pieces is inconsistent. This article systematically straightened out the records of SSG in ancient books and modern literature, and summarized and analyzed the processing procedures, chemical constituents, quality analysis and pharmacological effects of SSG. It found that SSG contains proteins, isoflavones, saponins and other components, analytical methods for detecting these components include ultraviolet spectrophotometry (UV), thin-layer chromatography (TLC), high performance liquid chromatography (HPLC), etc. It has effect such as antioxidant, anti-inflammatory, anti-osteoporosis, improvement of menopausal syndrome, treatment of cardiovascular diseases, and processing will change the type and content of its chemical components. Therefore, it is necessary to dig out active constituents of SSG, explore those changes in chemical constituents and pharmacological effect during the period of its primary and subsequent processing, and explore its action mechanism. This paper can provide the theoretical basis for standardized processing procedure, modern quality control and clinical application of SSG.

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