Authenticity and species identification of Fritillariae cirrhosae: a data fusion method combining electronic nose, electronic tongue, electronic eye and near infrared spectroscopy.

This paper focuses on determining the authenticity and identifying the species of Fritillariae cirrhosae using electronic nose, electronic tongue, and electronic eye sensors, near infrared and mid-level data fusion. 80 batches of Fritillariae cirrhosae and its counterfeits (including several batches of Fritillaria unibracteata Hsiao et K.C. Hsia, Fritillaria przewalskii Maxim, Fritillaria delavayi Franch and Fritillaria ussuriensis Maxim) were initially identified by Chinese medicine specialists and by criteria in the 2020 edition of Chinese Pharmacopoeia. After obtaining the information from several sensors we constructed single-source PLS-DA models for authenticity identification and single-source PCA-DA models for species identification. We selected variables of interest by VIP value and Wilk's lambda value, and we subsequently constructed the three-source fusion model of intelligent senses and the four-source fusion model of intelligent senses and near-infrared spectroscopy. We then explained and analyzed the four-source fusion models based on the sensitive substances detected by key sensors. The accuracies of single-source authenticity PLS-DA identification models based on electronic nose, electronic eye, electronic tongue sensors and near-infrared were respectively 96.25%, 91.25%, 97.50% and 97.50%. The accuracies of single-source PCA-DA species identification models were respectively 85%, 71.25%, 97.50% and 97.50%. After three-source data fusion, the accuracy of the authenticity identification of the PLS-DA identification model was 97.50% and the accuracy of the species identification of the PCA-DA model was 95%. After four-source data fusion, the accuracy of the authenticity of the PLS-DA identification model was 98.75% and the accuracy of the species identification of the PCA-DA model was 97.50%. In terms of authenticity identification, four-source data fusion can improve the performance of the model, while for the identification of the species the four-source data fusion failed to optimize the performance of the model. We conclude that electronic nose, electronic tongue, electronic eye data and near-infrared spectroscopy combined with data fusion and chemometrics methods can identify the authenticity and determine the species of Fritillariae cirrhosae. Our model explanation and analysis can help other researchers identify key quality factors for sample identification. This study aims to provide a reference method for the quality evaluation of Chinese herbs.

Two Key Amino Acids Variant of α-l-arabinofuranosidase from Bacillus subtilis Str. 168 with Altered Activity for Selective Conversion Ginsenoside Rc to Rd.

α-l-arabinofuranosidase is a subfamily of glycosidases involved in the hydrolysis of l-arabinofuranosidic bonds, especially in those of the terminal non-reducing arabinofuranosyl residues of glycosides, from which efficient glycoside hydrolases can be screened for the transformation of ginsenosides. In this study, the ginsenoside Rc-hydrolyzing α-l-arabinofuranosidase gene, BsAbfA, was cloned from Bacilus subtilis, and its codons were optimized for efficient expression in E. coli BL21 (DE3). The recombinant protein BsAbfA fused with an N-terminal His-tag was overexpressed and purified, and then subjected to enzymatic characterization. Site-directed mutagenesis of BsAbfA was performed to verify the catalytic site, and the molecular mechanism of BsAbfA catalyzing ginsenoside Rc was analyzed by molecular docking, using the homology model of sequence alignment with other ß-glycosidases. The results show that the purified BsAbfA had a specific activity of 32.6 U/mg. Under optimal conditions (pH 5, 40 °C), the kinetic parameters Km of BsAbfA for pNP-α-Araf and ginsenoside Rc were 0.6 mM and 0.4 mM, while the Kcat/Km were 181.5 s-1 mM-1 and 197.8 s-1 mM-1, respectively. More than 90% of ginsenoside Rc could be transformed by 12 U/mL purified BsAbfA at 40 °C and pH 5 in 24 h. The results of molecular docking and site-directed mutagenesis suggested that the E173 and E292 variants for BsAbfA are important in recognizing ginsenoside Rc effectively, and to make it enter the active pocket to hydrolyze the outer arabinofuranosyl moieties at C20 position. These remarkable properties and the catalytic mechanism of BsAbfA provide a good alternative for the effective biotransformation of the major ginsenoside Rc into Rd.

[A rapid identification of authenticity and specifications of Chinese medicine Fritillariae Cirrhosae Bulbus based on E-eye technology].

The quality of traditional Chinese medicine tablets is correlated with clinical efficacy and drug safety, and plays a great role in promoting the development of traditional Chinese medicine. However, the existing traditional artificial identification and modern instrument detection in terms of accuracy and timeliness have both advantages and disadvantages. Therefore, how to quickly and accurately identify the quality of traditional Chinese medicine tablets has become a high-profile issue. The purpose of this paper is to explore the feasibility of the application of electronic eye technology in the study of rapid identification of traditional Chinese medicine quality. A total of 80 batches of samples were collected and tested by Fritillariae Cirrhosae Bulbus for traditional empirical identification(M_1) and modern pharmacopeia(M_2). The optical data was collected from electronic eyes, and the chemical metrology was used to establish suitable discrimination models(M_3). Four authenticity and commodity specification models, namely identification analysis(DA), minimum bidirectional support vector machine(LS-SVM), partial minimum two-multiplier analysis(PLS-DA), main component analysis identification analysis(PCA-DA), were established, respectively. The accuracies of the authenticity identification models were 82.5%, 90.0%, 96.2% and 93.8%, while the accuracies of the commodity specification identification models were 89.3%, 96.0%, 90.7% and 97.3%, respectively. The models were well judged, the authenticity identification was based on the final identification model of PLS-DA, and the commodity specification was based on the final identification model of PCA-DA. There was no significant difference between its accuracy and M_1, and the time of determination was much shorter than M_2(P<0.01). Therefore, electronic-eye technology could be used for the rapid identification of the quality of Fritillariae Cirrhosae Bulbus.