This study aims to establish a rapid and non-destructive method for recognizing the origins and cultivation patterns of Astragali Radix. A hyperspectral imaging system(spectral ranges: 400-1 000 nm, 900-1 700 nm; detection time: 15 s) was used to examine the samples of Astragali Radix with different origins and cultivation patterns. The collected hyperspectral datasets were highly correlated and numerous, which required the establishment of stable and reliable dimension reduction and classification models. Firstly, the original spectra were preprocessed by normalization, Gaussian smoothing, and masking. Then, principal component analysis(PCA), partial least squares-discriminant analysis(PLS-DA), and competitive adaptive reweighted sampling(CARS) were performed to reduce the dimension of the hyperspectral data. Finally, support vector machine(SVM), feedforward neural network(FFNN), and convolutional neural network(CNN) were used for data training of the spectral images and spectral curves with dimension reduction. The results showed that applying CARS as a variable selection method before PLS-DA on the hyperspectral data of Astragali Radix achieved the accuracy, precision, and recall of 100% on the CNN test dataset. The F_1-score and area under the curve of ROC(AUC) reached 1. This method is convenient, quick, sample-saving, and non-destructive, providing technical support for rapid identification of the origins and cultivation patterns of Astragali Radix.
Drugs, Chinese Herbal/chemistry* ; Neural Networks, Computer ; Algorithms ; Support Vector Machine ; Principal Component Analysis ; Discriminant Analysis ; Hyperspectral Imaging/methods* ; Least-Squares Analysis ; Astragalus Plant/growth & development* ; Astragalus propinquus/growth & development*

OBJECTIVE: To investigate the mechanism of the effect of Astragalus membranaceus (A. membranaceus) on lung adenocarcinoma at the molecular level to elucidate the specific targets according to the network pharmacology approach. METHODS: The active components of A. membranaceus and their potential targets were collected from the Traditional Chinese Medicine Systems Pharmacology Database. Lung adenocarcinoma-associated genes were acquired based on GeneCards, Online Mendelian Inheritance in Man (OMIM), PharmGKB, and Therapeutic Targets databases. The PI3K/AKT signaling pathway-related genes were obtained using Reactome portal. Networks of "ingredient-target" and "ingredient-target-pathway-disease" were constructed using the Cytoscape3.6.0 software. The relationships among targets were analyzed according protein-protein interaction (PPI) network. Finally, molecular docking was applied to construct the binding conformation between active ingredients and core targets. Cell counting kit 8 (CCK8) and Western blot assays were performed to determine the mechanism of the key ingredient of A. membranaceus. RESULTS: A total of 20 active components and their 329 targets, and 7,501 lung adenocarcinoma-related genes and 130 PI3K/AKT signaling pathway-related genes were obtained. According to Venn diagram and PPI network analysis, 2 mainly active ingredients, including kaempferol and quercetin, and 6 core targets, including TP53, MAPK1, EGF, AKT1, ERBB2, and EGFR, were identified. The two important active ingredients of A. membranaceus, kaempferol and quercetin, exert the therapeutic effect in lung adenocarcinoma partly by acting on the 6 core targets (TP53, MAPK1, EGF, AKT1, ERBB2, and EGFR) of PI3K/AKT signaling pathway. Expressions of potential targets in lung adenocarcinoma and normal samples were analyzed by using UALCAN portal and found that ERBB2 was overexpressed in lung adenocarcinoma tissues and upregulation of it correlated with clinicopathological characteristics. Finally, quercetin repressed viabilities of lung adenocarcinoma cells by targeting ERBB2 on PI3K/AKT signaling confirmed by CCK8 and Western blot. CONCLUSION Our finding unraveled that an active ingredient of A. membranaceus, quercetin, significantly inhibited the lung adenocarcinoma cells proliferation by repressing ERBB2 level and inactivating the PI3K/AKT signaling pathway.
Humans ; Astragalus propinquus ; Kaempferols ; Network Pharmacology ; Phosphatidylinositol 3-Kinases ; Proto-Oncogene Proteins c-akt ; Epidermal Growth Factor ; Molecular Docking Simulation ; Quercetin ; Adenocarcinoma of Lung ; Lung Neoplasms ; Signal Transduction ; ErbB Receptors ; Drugs, Chinese Herbal

Astragali Radix (AR) is one of the most popular herbal medicines in traditional Chinese medicine (TCM). Wild AR is believed to be of high quality, and substitution with cultivated AR is frequently encountered in the market. In the present study, two types of ARs (wild and cultivated) from Astragalus membranaceus (Fisch.) Bge. and A. membranaceus var. mongholicus (Bge.) Hsiao, growing in different regions of China, were analyzed by NMR profiling coupled with multivariate analysis. Results showed that both could be differentiated successfully and cultivation patterns or growing years might have greater impact on the metabolite compositions than the variety; the metabolites responsible for the separation were identified. In addition, three extraction methods were compared and the method (M1) was used for further analysis. In M1, the extraction solvent composed of water, methanol, and chloroform in the ratio of 1 : 1 : 2 was used to obtain the aqueous methanol (upper layer) and chloroform (lower layer) fractions, respectively, showing the best separation. The differential metabolites among different methods were also revealed. Moreover, the sucrose/glucose ratio could be used as a simple index to differentiate wild and cultivated AR. Meanwhile, the changes of correlation pattern among the differential metabolites of the two varieties were found. The work demonstrated that NMR-based non-targeted profiling approach, combined with multivariate statistical analysis, can be used as a powerful tool for differentiating AR of different cultivation types or growing years.
Astragalus propinquus ; chemistry ; classification ; metabolism ; China ; Magnetic Resonance Spectroscopy ; methods ; Metabolomics ; Plant Extracts ; chemistry ; metabolism ; Plant Roots ; chemistry ; classification ; growth & development ; Plants, Medicinal ; chemistry ; growth & development ; metabolism