Origin identification of Polygonatum cyrtonema based on hyperspectral data / 中国中药杂志

In this study, visual-near infrared(VNIR), short-wave infrared(SWIR), and VNIR + SWIR fusion hyperspectral data of Polygonatum cyrtonema from different geographical origins were collected and preprocessed by first derivative(FD), second derivative(SD), Savitzky-Golay smoothing(S-G), standard normalized variate(SNV), multiplicative scatter correction(MSC), FD+S-G, and SD+S-G. Three algorithms, namely random forest(RF), linear support vector classification(LinearSVC), and partial least squares discriminant analysis(PLS-DA), were used to establish the identification models of P. cyrtonema origin from three spatial scales, i.e., province, county, and township, respectively. Successive projection algorithm(SPA) and competitive adaptive reweighted sampling(CARS) were used to screen the characteristic bands, and the P. cyrtonema origin identification models were established according to the selected characteristic bands. The results showed that(1)after FD preprocessing of VNIR+SWIR fusion hyperspectral data, the accuracy of recognition models established using LinearSVC was the highest, reaching 99.97% and 99.82% in the province origin identification model, 100.00% and 99.46% in the county origin identification model, and 99.62% and 98.39% in the township origin identification model. The accuracy of province, county, and township origin identification models reached more than 98.00%.(2)Among the 26 characteristic bands selected by CARS, after FD pretreatment, the accuracy of origin identification models of different spatial scales was the highest using LinearSVC, reaching 98.59% and 97.05% in the province origin identification model, 97.79% and 94.75% in the county origin identification model, and 90.13% and 87.95% in the township origin identification model. The accuracy of identification models of different spatial scales established by 26 characteristic bands reached more than 87.00%. The results show that hyperspectral imaging technology can realize accurate identification of P. cyrtonema origin from different spatial scales.

New Advances, Challenges and Opportunities in Forensic Applications of Microbiomics / 法医学杂志

The succession of microbiota is closely associated with several essential factors, including race, sex, health condition, lifestyle, postmortem interval, etc., and it has great potential application value in forensic medicine. This paper summarizes recent studies on the forensic applications of the microbiome, including individual identification, geographical feature identification, origin identification of the tissue or body fluid, and postmortem interval estimation, and introduces the current machine learning algorithms for microbiology research based on next-generation sequencing data. In addition, the current problems facing forensic microbiomics such as the extraction and preservation of samples, construction of standardization and database, ethical review and practical applicability are discussed. Future multi-omics studies are expected to explore micro ecosystems from a comprehensive and dynamic perspective, to promote the development of forensic microbiomics application.

Fusion of spectrum and image features to identify Glycyrrhizae Radix et Rhizoma from different origins based on hyperspectral imaging technology / 中国中药杂志

To identify Glycyrrhizae Radix et Rhizoma from different geographical origins, spectrum and image features were extracted from visible and near-infrared(VNIR, 435-1 042 nm) and short-wave infrared(SWIR, 898-1 751 nm) ranges based on hyperspectral imaging technology. The spectral features of Glycyrrhizae Radix et Rhizoma samples were extracted from hyperspectral data and denoised by a variety of pre-processing methods. The classification models were established by using Partial Least Squares Discriminate Analysis(PLS-DA), Support Vector Classification(SVC) and Random Forest(RF). Meanwhile, Gray-Level Co-occurrence matrix(GLCM) was employed to extract textural variables. The spectrum and image data were implemented from three dimensions, including VNIR and SWIR fusion, spectrum and image fusion, and comprehensive data fusion. The results indicated that the spectrum in SWIR range performed better classification accuracy than VNIR range. Compared with other four pre-processing methods, the second derivative method based on Savitzky-Golay(SG) smoothing exhibited the best performance, and the classification accuracy of PLS-DA and SVC models were 93.40% and 94.11%, separately. In addition, the PLS-DA model was superior to SVC and RF models in terms of classification accuracy and model generalization capability, which were evaluated by confusion matrix and receiver operating characteristic curve(ROC). Comprehensive data fusion on SPA bands achieved a classification accuracy of 94.82% with only 28 bands. As a result, this approach not only greatly improved the classification efficiency but also maintained its accuracy. The hyperspectral imaging system, a non-invasively, intuitively and quickly identify technology, could effectively distinguish Glycyrrhizae Radix et Rhizoma samples from different origins.

Classification and Identification of Cynomorii Herba from Different Producing Areas Based on Fourier Rransform Infrared Spectroscopy and Chemometrics / 中国实验方剂学杂志

Objective: To realize the classification and identification of Cynomorii Herba from different producing areas based on fourier transform infrared spectroscopy (FTIR) and chemometrics. Method: FTIR spectrum data of 106 batches of Cynomorii Herba from 12 cities in 5 provinces were collected by transmission method and preprocessed. The FTIR fingerprints of Cynomorii Herba were established, and spectrum analysis was performed. The FTIR similarities of Cynomorii Herba from different producing areas were calculated by correlation coefficient method. The first derivative (1D) spectrum of average FTIR of Cynomorii Herba from different producing areas were obtained. The soft independent modeling of class analog (SIMCA) model based on principal component analysis (PCA) was established by the preprocessed 1D spectrum data. The orthogonal partial least squares (OPLS) model was established by top 6 principal components. Result: The FTIR fingerprint trend and main absorption peaks of Cynomorii Herba from different producing areas were basically the same,and 16 common characteristic absorption peaks were recognized. Similarity and 1D spectrum of FTIR fingerprint of Cynomorii Herba from different producing areas showed significant and unique characteristics. The established SIMCA model can realize the classification and identification of Cynomorii Herba from different provinces,while OPLS model can realize accurate classification and identification of Cynomorii Herba in different cities. The classification and identification of Cynomorii Herba from 12 city producing areas showed obvious geographical clustering characteristics. Conclusion: The established method based on FTIR and chemometrics can realize the classification and identification of Cynomorii Herba from 12 cities.

Specific Polymerase Chain Reaction Molecular Identification of Pheretima aspergillum (E. Perrier) / 广州中医药大学学报

Objective To screen out the polymerase chain reaction ( PCR) primers for specifically identifying Pheretima aspergillum (E. Perrier) , so as to establish a rapid and accurate method to identify the origin of Pheretima aspergillum. Methods Four kinds of earthworms recorded in pharmacopoeia and six kinds of their adulterants commonly seen in the market were collected. The 12SrRNA sequences related to earthworm were downloaded from GenBank database. PCR amplification for ten kinds of samples was performed using the universal primers, and then the products were sequenced. According to the differences between the above sequences, three pairs of specific primers in the non-conservative district were designed for identification of Pheretima aspergillum. Results High-specificity PCR amplification for Pheretima aspergillum with 12St/12Stf primer occurred when the annealing temperature was increased to 64℃, and only Pheretima aspergillum had single amplification strip, while no strips were found in the other adulterants under the same condition. The achieved specific primers could be well verified in 15 kinds of medicinal materials of earthworm purchased in the market, which had the same morphological features showed by the traditional identifying method. Conclusion With 12St/12Stf primer as a specific marker, the identifica tion of Pheretima aspergillum is rapid and accurate in related species of Pheretima aspergillum, and avoids the effect of some factors such as integrity of experimental materials and drying process.

Application of gene technology in quality control of Chinese materia medica Ⅱ. Identification of Chinese Rhizoma Dioscoreae by DNA sequencing / 中草药

Object To distinguish the genuine Dioscorea polystachya Turcz. from other species of Dioscorea L. such as D. persimilis Prain et Burkill, D. japonica Thunb., and D. alata L., conventionally used in some localities by sequencing their nuclear ribosomal RNA subunit (18S rRNA), to provide mole cular evidences for the quality control of drugs of Dioscorea L. Methods By direct PCR sequencing to detect the homology of 18S rRNA sequence of different species of Dioscorea L.. Results The 18S rRNA gene sequence of genuine D. polystachya, D. persimilis and D. japonica showed identical length of 1810 bp, whereas that of D. alata was 1807 bp. Multiple sequence alignment of 18S rRNA gene showed that the homology was identical between D.persimilis and the genuine D. polystachya; but a difference of 99.89% with D. japonica and 97.51% with D. alata. Conclusion DNA sequencing can provide an accurate and reliable mean for the identification of the origin and genuineness of Dioscorea L..