Nan Li,Zhenzhen Han,Lin Li,Bing Zhang,Zhidong Liu,Jiawei Li
Purpose The objective of this study was to investigate the effects of the solid lipid nanoparticles of baicalin (BA-SLNs) on an experimental cataract model and explore the molecular mechanism combined with bioinformatics analysis.Materials and methods The transparency of lens was observed daily by slit-lamp and photography. Lenticular opacity was graded. Two-dimensional gel electrophoresis (2-DE) was employed to analyze the differential protein expression modes in each group. Proteins of interest were subjected to protein identification by nano-liquid chromatography tandem mass spectrometry (LC–MS/MS). Bioinformatics analysis was performed using the Ingenuity Pathway Analysis (IPA) online software to comprehend the biological implications of the proteins identified by proteomics.Results At the end of the sodium selenite-induced cataract progression, almost all lenses from the model group developed partial nuclear opacity; however, all lenses were clear and normal in the blank group. There was no significant difference between the BA-SLNs group and the blank group. Many protein spots were differently expressed in 2-DE patterns of total proteins of lenses from each group, and 65 highly different protein spots were selected to be identified between the BA-SLNs group and the model group. A total of 23 proteins were identified, and 12 of which were crystalline proteins.Conclusion We considered crystalline proteins to play important roles in preserving the normal expression levels of proteins and the transparency of lenses. The general trend in the BA-SLN-treated lenses’ data showed that BA-SLNs regulated the protein expression mode of cataract lenses to normal lenses. Our findings suggest that BA-SLNs may be a potential therapeutic agent in treating cataract by regulating protein expression and may also be a strong candidate for future clinical research.
Rheumatoid arthritis (RA) is a common autoimmune and inflammatory disease worldwide, but understanding its pathogenesis is still limited. In this study, plasma untargeted metabolomics of a discovery cohort and targeted analysis of a verification cohort were performed by gas chromatograph mass spectrometry (GC/MS). Univariate and multivariate statistical analysis were utilized to reveal differential metabolites, followed by the construction of biomarker panel through random forest (RF) algorithm. The pathways involved in RA were enriched by differential metabolites using Ingenuity Pathway Analysis (IPA) suite. Untargeted metabolomics revealed eighteen significantly altered metabolites in RA. Among these metabolites, a three-metabolite marker panel consisting of L-cysteine, citric acid and L-glutamine was constructed, using random forest algorithm that could predict RA with high accuracy, sensitivity and specificity based on a multivariate exploratory receiver operator characteristic (ROC) curve analysis. The panel was further validated by support vector machine (SVM) and partial least squares discriminant analysis (PLS-DA) algorithms, and also verified with targeted metabolomics using a verification cohort. Additionally, the dysregulated taurine biosynthesis pathway in RA was revealed by an integrated analysis of metabolomics and transcriptomics. Our findings in this study not only provided a mechanism underlying RA pathogenesis, but also offered alternative therapeutic targets for RA.
Qixuan Mu,Yaping Zhang,Ying Cui,Xin Chai,Junlian Liu,Yongzhi Li,Huijuan Yu,Yuefei Wang
As the representatives of closely related Chinese medicinal materials (CMMs) originated from Rutaceae family, Aurantii fructus immaturus (AFI), Aurantii fructus (AF), Citri reticulatae pericarpium viride (CRPV), and Citri reticulatae pericarpium (CRP) have better functions in regulating qi and promoting gastrointestinal motility. However, differences in the quality of closely related Citrus CMMs have not yet been revealed until now. Herein, this study focused on the systematic differentiation and in-depth understanding of closely related Citrus CMMs by a strategy integrating chemometrics and network pharmacology. Determined by ultra performance liquid chromatography, the content of nine flavonoids showed obvious fluctuations in the decoction pieces from different species (Citrus aurantium Linnaeus and Citrus reticulate Blanco) with decreasing levels in the samples of ripe fruits. Decoction pieces from the different species and ripening stages were well distinguished by orthogonal projection to latent structure-discriminate analysis (OPLS-DA) and cluster analysis. As a result, four active components including narirutin, naringenin, hesperidin, and 3,5,6,7,8,3′,4′-heptemthoxyflavone were filtered out by variable importance for the projection (VIP) value (VIP > 1.0), which were regarded as chemotaxonomic markers. Furthermore, a components-targets-diseases network was constructed via ingenuity pathway analysis (IPA), and the correlations were predicted between four chemotaxonomic markers, 223 targets, and three diseases including colitis, breast cancer, and colorectal cancer. The obtained results will be of great significance for identifying closely related Citrus CMMs and conduce to improving the resource utilization of CMMs.
危险品化学品经营许可证（带存储）