5results about How to "Realize authentication" patented technology

The invention relates to the technical field of quality control of traditional Chinese medicines, in particular to a thin-layer chromatography identification method for 8 medicines in 11 medicines in the whole formula of Qingjin phlegm-reducing decoction. The core of the method is that three different test solutions are adopted to realize the identification of eight medicines, namely scutellaria baicalensis, rhizoma anemarrhenae, exocarpium citri rubrum, fructus gardeniae, liquorice, thunberg fritillary bulb, platycodon grandiflorum and radix ophiopogonis. Wherein the first test solution is prepared by extracting water-saturated n-butyl alcohol, and can be simultaneously used for identifying scutellaria baicalensis, rhizoma anemarrhenae, exocarpium citri rubrum, fructus gardeniae and liquorice; the second solution is subjected to ammoniation and dichloromethane extraction to be used for thunberg fritillary bulb identification; the third solution is extracted by dichloromethane after being hydrolyzed by hydrochloric acid, and platycodon grandiflorum and radix ophiopogonis can be identified at the same time. According to the method, by optimizing a test sample preparation and development system, sharing of test samples of multiple medicines and synchronous identification are achieved, the detection efficiency is remarkably improved, the method has the advantages of being easy and convenient to operate, clear in spot, good in separation degree, high in specificity, negative, free of interference and the like, and a reliable basis is provided for quality control of the Qingjin phlegm reducing decoction.

The embodiment of the application provides a drug component identification method and related equipment, and belongs to the technical field of drug identification. The method comprises the following steps: obtaining preset drug sample data, including positive drug sample data and negative drug sample data, wherein the positive drug sample data comprises a first thin layer chromatogram, and the negative drug sample data comprises a second thin layer chromatogram; constructing a model training atlas set through the first thin layer chromatogram, so as to train a preset twin neural network model, and obtain a first twin neural network model; constructing a model test atlas set through the first thin layer chromatogram and the second thin layer chromatogram, so as to optimize parameters of the model in combination with the model training atlas set, and obtain a target neural network model; and inputting a to-be-identified thin layer chromatogram into the target neural network model for component identification analysis, and obtaining a component identification result. The embodiment of the application can try not to use control samples and control medicinal materials in drug identification, so that the economic, green and environmentally-friendly purposes are achieved.

The application provides a kind of Fuling drink piece, fried Fuling drink piece and the construction method and application of its preparation characteristic map, the construction method of fried Fuling and its preparation characteristic map, comprising: preparing test sample solution;Using high performance liquid chromatography to detect test sample solution, chromatographic conditions include with octadecylsilane bonded silica as filler, with methanol as mobile phase A, with 0.08%-0.4% formic acid as mobile phase B, and using specific elution procedure, while shortening the detection time also significantly improves the separation effect of multiple effective components, so that the characteristic map contains more characteristic peaks, greatly enriches the atlas information, realizes the effective separation of characteristic peaks such as uridine, thymine, gallic acid and guanosine, the characteristic of the obtained characteristic map is obvious, fully reflects the integrity and characteristic of the drug preparation of fried Fuling, and the baseline is stable, the peak shape is good, which provides basis for comprehensively detecting the quality of Fuling drink piece, fried Fuling and its pharmaceutical preparations.

This application relates to the field of otolaryngology technology, specifically a method and system for predicting the risk of papillary thyroid carcinoma. By combining multiple sets of clinical indicators and multiple imaging feature data, this application can effectively assess and predict the risk of papillary thyroid carcinoma. The scoring data provides a more intuitive determination of the severity of papillary thyroid carcinoma, thereby enabling the differentiation between atypical subacute thyroiditis and papillary thyroid carcinoma. Compared to existing technologies, the discrimination results of the embodiments in this application are more accurate.

The invention relates to the technical field of forensic scientific detection, in particular to a feeding bottle material identification and brand tracing method. The concentration of the VOCs in the baby feeding bottle is low, and the HS-GC-IMS is used for capturing and analyzing the residual trace VOCs in the sample, so that the detection sensitivity is improved; hierarchical modeling methods of chemometrics and machine learning show strong ability in the aspects of processing high-dimensional chemical data sets and identifying complex modes. According to the method disclosed by the invention, the volatile components in the baby feeding bottle are detected and analyzed by adopting a chemometrics and machine learning assisted HS-GC-IMS method for the first time, and a rapid and accurate detection method is established, so that the identification and traceability of the material and brand of the feeding bottle are realized.