Chemistry
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HPLC Coupled with Chemical Fingerprinting for Multi-Pattern Recognition for Identifying the Authenticity of Clematidis Armandii Caulis
Chapters
Summary November 11th, 2022
Here, we present a protocol to establish high-performance liquid chromatography (HPLC), coupled with chemical fingerprint multi-pattern recognition, which provides a new strategy for effectively identifying the genuine varieties of Clematidis Armandii Caulis and its adulterants.
Transcript
This protocol can provide a new strategy for effectively identifying the genuine materials of Clematidis armandii caulis and its adulterants. This method can be used in medicinal material quality research and it provides a reference for studying the quality standards of other Chinese medicinal materials. To begin sample preparation grind the raw material to uniform particle size by passing them through a nylon mesh with an appropriate inner diameter.
Transfer accurately weighed two grams of the ground raw material into a stoppered 50 milliliter conical flask before adding 50 milliliters of methanol into the flask. Put the stopper on the flask in ultrasonic heated at 600 watts and 40 kilohertz for 30 minutes. At the end of the incubation, strain the medicinal extract solution through the filter paper.
After straining, transfer four milliliters of the methanol solution containing the medicinal extracts into a 10 milliliter volumetric flask. Then add six milliliters of water to it and mix the solution. Allow the solution to settle for 10 minutes.
For HPLC analysis of the samples. Start by preparing the mobile phases and set the HPLC gradient program as described in the manuscript. Filter the sample through a 0.45 micron micro porous filter membrane and subject it to HPLC analysis.
For each sample, perform analysis six times a day. To evaluate the stability of the sample solution, analyze the same sample solution stored at room temperature for 0, 2, 4, 6, 8, 12, and 24 hours after preparation. Take six replicates of the same sample and detect its fingerprint in HPLC.
Import the relevant data into the software named Similarity Evaluation System of Chromatographic Fingerprints of Traditional Chinese Medicine or SESCF TCM version 2012. Import the retention time and peak area for all 10 batches of authentic Chuanmutong samples as well as five batches of adulterants into SESCF TCM for analysis. In the main menu, click on the set reference spectrum and go to the parameter settings window to set the reference chromatographic fingerprint of the authentic species of Chuanmutong as the reference.
Next, set control spectrum generation method as the median method with the time window width of 0.5. Then, click multi-point calibration in the main menu, select the peaks and then select the peak matching option as marked peaks. Finally, click Calculate Similarity to perform a similarity analysis of the samples based on the reference chromatogram fingerprints of Chuanmutong.
To perform systemic cluster analysis open relevant statistical analysis software, and click on file to import the data of 10 batches of authentic samples and five batches of adulterants into the software. In the menu, Under the Classification tab go to click Analysis and System Clustering. Select the common peak areas of 10 batches of authentic samples and five batches of adulterants as variables.
Set the number of clusters to four. Next, click on Method to select the Clustering Method as intergroup connection. Choose the measurement interval as Pearson correlation and use the Okay tab to draw the cluster analysis map.
For principle component analysis or PCA, open the data analysis software. Click on file on the menu, and create a new regular project. Import the peak area of 12 common peaks in an Excel or similar spreadsheet from the HPLC system.
Hit the Finish button to complete the data import. To set the model type with PCA, Click on New to create a new model and then fit the data using autofit and add tabs. Go to scores to get the PCA score map.
To use the Orthogonal Partial Least Squares Discrimination Analysis or OPLSDA. Generate the PCA score map as demonstrated earlier. Set the model type with the OPLSDA by clicking New and New As model one Before going to scale in selecting par for all, Then hit on AutoFit in scores to generate the OPLSDA score map.
To estimate the variable importance and projection go to the data analysis software menu and go to Analyze followed by setting the number to 200 under per mutations. Obtain the R square and Q square values from the OPLSDA score and click on VIP and VIP predictive to get the VIP map. HPLC fingerprints of the 10 authentic Chuanmutong samples showed 12 distinct common peaks of which the relatively large and well resolved.
Peak number 10 was used as the reference peak to estimate the relative retention times of the rest peaks. The authentic samples demonstrated similarity degrees very close to one implying high similarity in good consistency. However, the similarity degrees between the five batches of adulterants and the control Chuanmutong were quite low.
The HPLC fingerprints of the five adulterants were observed to differ from the authentic samples, mainly in the region having retention times ranging from 28 to 55 minutes. PCA showed an obvious similarity between the authentic varieties and their difference from the adulterants, except for the adulterant CC.Similar results were also obtained from cluster analysis when the classification distance was 20. The score matrix generated from OPLSDA indicated no intersection between the sample points of authentic samples and the adulterants.
Again, adulterant CC resembled the authentic varieties more than the other adulterants. According to the VIP map the peaks having values greater than one were identified as the main marker components causing the difference between authentic samples and the adulterants. The content of beta-sitosterol, an active component found in Chuanmutong was detected in all five batches of adulterants, but the content varied greatly.
This protocol establishes various analysis methods to reflect all the information about medicinal materials from multiple angles and in all around the way to estimate the authenticity of Chuanmutong medicinal materials.
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