This work was supported by the Project of Sichuan Traditional Chinese Medicine Administration (no. 2020JC0088, no. 2021MS203).

1. Methods for chemical fingerprint detection
<ol>
	<li>Chromatographic conditions
	<ol>
		<li>Prepare the acetonitrile (A)/water (B) mobile phase. Set a gradient program as follows in the HPLC software: 0-20 min, 3%A-10%A; 20-25 min, 10%A-13%A; 25-65 min, 13%A-25%A; 65-75 min, 25%A-40%A; 75-76 min, 40%A-3%A; 76-85 min, 3%A-3%A.</li>
		<li>Maintain the flow rate of the mobile phase at 1.0 mL/min.</li>
		<li>Conduct the chromatographic separation on a C18 column (250 mm x 4.6 mm, 5 &#181;m) maintained at 30 &#176;C.</li>
		<li>Set the injection volume to 10 &#181;L.</li>
		<li>Detect the samples at a wavelength of 205 nm. 
		NOTE: For the specific settings of chromatographic conditions, refer to the operating procedures of the working software of high-performance liquid chromatography (Table of Materials).</li>
	</ol>
	</li>
	<li>Preparation of the sample solution
	<ol>
		<li>Grind the raw materials to uniform particle size by passing them through a nylon mesh with an inner diameter of 850 &#181;m &#177; 29 &#181;m.</li>
		<li>Place 2 g of the ground raw material (accurately weighed) in a 50 mL conical flask with a stopper and add 50 mL of methanol. Place the stopper on the flask and ultrasonicate (600 W, 40 kHz) for 30 min.</li>
		<li>Then, cool the flask to room temperature (RT). Weigh the samples again, and make up for the initial weight by replacing the lost extractant.</li>
		<li>Pour 4 mL of the methanol solution containing the medicinal extracts into a 10 mL volumetric flask. Add 6 mL of H2O, mix, and allow it to settle for 10 min.</li>
		<li>Finally, filter the supernatant through a 0.45 &#181;m filter membrane and place it on standby.</li>
	</ol>
	</li>
	<li>Validation of fingerprint detection methods
	<ol>
		<li>Prepare the sample as described above (step 1.2) and subject it to HPLC analysis (step 1.1) six times a day. To evaluate the precision, calculate the relative standard deviation (RSD) of relative retention time and relative peak areas as described in step 1.3.5.</li>
		<li>Evaluate the stability of the sample solution by analyzing the same sample solution stored at RT for 0, 2, 4, 6, 8, 12, and 24 h, and calculate the RSD of relative retention time and relative peak areas as described in step 1.3.5.</li>
		<li>Take six replicates of the same sample (CMT-4), prepare the sample solution according to the above procedure (step 1.2), and detect its fingerprint in HPLC following step 1.1. Calculate the RSD of relative retention time and relative peak areas, and evaluate its repeatability as described in step 1.3.5.</li>
		<li>Then use peak number 10 in Figure 1B as the reference peak and calculate the RSD of the relative retention time and relative peak area of each common peak as described in step 1.3.5.</li>
		<li>Use the formulas mentioned below to calculate the relative retention time and relative peak area of each common peak: 
		Tre = Tcharacteristic/Treference 
		Are = Acharacteristic/Areference 
		Where Tre =relative retention time, Tcharacteristic = characteristic peak retention time, Treference = reference peak retention time, Are = relative peak area, Acharacteristic = characteristic peak area, and Areference = reference peak area. 
		&#8203;NOTE: The establishment of traditional Chinese medicine fingerprints generally requires selecting a chromatographic peak that is easy to obtain and has high resolution. This is used as a reference peak to identify the fingerprints and examine their stability and reproducibility.</li>
	</ol>
	</li>
</ol>
2. Establishment of Chuanmutong fingerprint and similarity analysis
<ol>
	<li>Use 10 batches of authentic samples and five batches of adulterants such as Clematis argentilucida (Levl. et Vant.) W. T. Wang (CC), Clematis apiifolia var. obtusidentata Rehd. et Wils. (DC), Clematis peterae Hand.-Mazz. (DE), Clematis gouriana Roxb. Var. finetii Rehd. et Wils (XS), and Clematis finetiana Levl. et Vaniot. (SMT) as samples for fingerprint analysis.</li>
	<li>Prepare the sample solutions as described in step 1.2. Perform fingerprint analysis of all sample solutions by HPLC according to the conditions described under step 1.1.</li>
	<li>Import the relevant data into the similarity evaluation system of chromatographic fingerprints of traditional Chinese medicine (SESCF-TCM, 2012 version).The system will designate the peaks with reasonable height and good resolution in the chromatograms of all samples as common peaks. 
	NOTE: The SESCF-TCM software can be downloaded after registration on the website of the Chinese Pharmacopoeia Commission (http://114.247.108.158:8888/login).
	<ol>
		<li>In the software, click the Set Reference Spectrum button in the menu.</li>
		<li>Then in the Parameter Settings window, set the Time Window Width to 0.5 and select Control Spectrum Generation Method as the Median Method.</li>
		<li>Click on Multi-point Calibration in the main menu, then select Peak Matching as Full Spectrum Peak Matching.</li>
		<li>Finally, click on Generate Control to generate the reference chromatographic fingerprint of the authentic species of Chuanmutong.</li>
	</ol>
	</li>
	<li>Import the retention time and peak area of 10 batches of authentic Chuanmutong samples and five batches of adulterants into SESCF-TCM for analysis. The specific operations are as follows:
	<ol>
		<li>In the software, click on the Set Reference Spectrum button in the main menu.</li>
		<li>In the Parameter Settings window, set the reference chromatographic fingerprint of the authentic species of Chuanmutong as the reference, select the Control Spectrum Generation Method as the Median Method, and set the Time Window Width to 0.5.</li>
		<li>Click on Multi-point Calibration in the main menu, then select Peak Matching as Full Spectrum Peak Matching.</li>
		<li>Finally, click on Calculate Similarity to calculate the similarity based on the reference chromatogram fingerprints of Chuanmutong. Finally, calculate the similarity of fingerprints using the Chinese Medicine Chromatographic Fingerprint Evaluation System (2012 version). 
		&#8203;NOTE: For the specific operations, refer to the operating specifications for the Chinese Medicine Chromatographic Fingerprint Evaluation System (2012 version).</li>
	</ol>
	</li>
</ol>
3. Multi-pattern recognition analysis of Chuanmutong fingerprint
<ol>
	<li>Cluster analysis (CA)
	<ol>
		<li>Use the peak areas of 12 common peaks in the fingerprints of 10 batches of authentic Chuanmutong samples and their five batches of adulterants as variables, and input them into statistical analysis software for systematic cluster analysis (CA).</li>
		<li>Choose the Between-Groups method and use the Pearson correlation coefficient as the classification basis to draw a cluster analysis diagram of Chuanmutong and its adulterants. The specific operations are as follows:
		<ol>
			<li>In the statistical analysis software, click on File to import data.</li>
			<li>Click on Analysis in the menu and then click on System Clustering in Classification.</li>
			<li>Select the common peak area as a variable, and set the number of clusters to four.</li>
			<li>Click on Method, select the clustering method as Inter-Group Connection, select the measurement interval as Pearson Correlation, and click on OK to draw the CA map.</li>
		</ol>
		</li>
	</ol>
	</li>
	<li>Principal component analysis (PCA)
	<ol>
		<li>Import the relative common peak area of the authentic varieties and their adulterants into the analysis software for PCA analysis, and use the PCA score map to evaluate the score matrix map of sample differences. The specific operations are as follows:
		<ol>
			<li>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 a spreadsheet (e.g., excel format) from the HPLC system. Then click on Finish to complete the data import.</li>
			<li>Click on New to create a new model to set the model type with PCA. Click on Autofit and Add to fit the data, then click on Scores to get the PCA score map.</li>
		</ol>
		</li>
	</ol>
	</li>
	<li>Orthogonal partial least-squares discrimination analysis (OPLS-DA)
	<ol>
		<li>Use the Orthogonal partial least-squares discrimination analysis method with supervision mode to further analyze the relative common peak area peaks of the authentic Chuanmutong varieties and adulterants and draw an OPLS-DA classification score map of all samples. The specific operations are as follows:
		<ol>
			<li>In data analysis software, click on File in the menu to import a file and create a new regular project. Import the peak area of 12 common peaks in a spreadsheet from the HPLC system, then click on Finish to complete the data import.</li>
			<li>Click on New to create a new model to set the model type with PCA. Click on Autofit and Add to fit the data. Then click on Scores to get the PCA score map.</li>
			<li>Click on New and choose New as Model One to set the model type with OPLS-DA.</li>
			<li>Click on Scale and set type with Par for All. Click on Autofit first and then click on Scores to get the OPLS-DA score map.</li>
		</ol>
		</li>
		<li>In order to determine the influence of each common peak in Chuanmutong on its classification results and the difference between authentic Chuanmutong materials and related adulterants, use the variable importance in the projection (VIP) for analysis.</li>
		<li>Draw the VIP map of the different components of Chuanmutong. Use the resulting VIP map to assess the impact of each variable on the classification and to screen out components that contribute significantly to the differences between groups. The specific operations are as follows:
		<ol>
			<li>In the data analysis software, click on Analyse in the menu and click on Permutations, set the number of permutations to 200, and get the R2 and Q2 of the OPLS-DA score map.</li>
			<li>Click on VIP and choose VIP Predictive to get the VIP map.</li>
		</ol>
		</li>
	</ol>
	</li>
</ol>
4. Determination of &#946;-sitosterol in Chuanmutong by HPLC
<ol>
	<li>Chromatographic conditions (refer to step 1.1)
	<ol>
		<li>Prepare the mobile phase: methanol-water (97:3).</li>
		<li>Set the flow rate of the mobile phase to 1.0 mL/min.</li>
		<li>Conduct the chromatographic separation on a C18 column (250 mm x 4.6 mm, 5 &#181;m) maintained at 30 &#176;C.</li>
		<li>Set the injection volume to 10 &#181;L.</li>
		<li>Detect the component at a wavelength of 204 nm.</li>
	</ol>
	</li>
	<li>Preparation of the sample solution
	<ol>
		<li>Prepare the stock standard solution of &#946;-sitosterol (0.1 mg/mL) by dissolving an accurately weighed quantity of the corresponding reference standard in methanol.</li>
		<li>Grind the analysis sample of the raw material to uniform particle size by passing the sample through the nylon mesh with an inner diameter of 180 &#181;m &#177; 7.6 &#181;m.</li>
		<li>Place 2 g of the ground raw material (accurately weighed) in a round-bottomed flask and add 50 mL of chloroform to it.</li>
		<li>Connect the flask to a reflux condenser and heat it in a boiling water bath (moderate boiling) for 60 min. Filter the extraction solution with a 15-20 &#181;m filter paper.</li>
		<li>Evaporate the filtrate to near dryness on a boiling water bath (moderate boiling) for about 10 min.</li>
		<li>Dissolve the residue and make up the volume to 5 mL using methanol. Finally, pass the supernatant through a 0.45 &#181;m filter membrane, and place it on standby.</li>
	</ol>
	</li>
	<li>Method validation
	<ol>
		<li>Take the stock solution of &#946;-sitosterol prepared in sub-step 4.2.1, dilute it with 100% methanol, and prepare solutions with 100 &#181;g/mL, 80 &#181;g/mL, 60 &#181;g/mL, 50 &#181;g/mL, 40 &#181;g/mL, 30 &#181;g/mL, and 20 &#181;g/mL concentrations.</li>
		<li>Inject the samples under the chromatographic conditions described in step 4.1 to determine the peak area, perform regression analysis with the peak area to the injection volume, and obtain the regression equation and correlation coefficient to evaluate its linearity.</li>
		<li>Prepare the samples as described above (step 4.2) and subject them to HPLC analysis (step 4.1) six times on the same day. Then calculate the RSD of peak areas to evaluate the precision.</li>
		<li>Evaluate the stability of the sample solution by analyzing the same sample solutions stored at RT for 0, 2, 4, 6, 8, 12, and 24 h, as described in step 4.1. Then calculate the RSD of peak areas as described in step 1.3.5.</li>
		<li>Examine the repeatability by dissolving the same sample (CMT-4) in sextuplicate, prepared as described in step 4.2, and subjecting them to HPLC analysis as described in step 4.1. Then calculate the RSD of &#946;-sitosterol content in six samples.</li>
		<li>Assess the method&#39;s accuracy by employing the standard addition method. For this, add &#946;-sitosterol reference solutions to the samples at 80%, 100%, and 120% of the &#946;-sitosterol content and repeat each condition three times as described in step 4.1. Evaluate the method&#39;s accuracy by calculating the average recovery and RSD. 
		NOTE: The calculation formula of the rate of recovery (RR) is as follows: 
		RR % = [(Mt - M0) / Ms] &#215; 100 
		Where Mt = the quality of &#946;-sitosterol after adding the standard, M0 = the quality of the sample solution, and Ms = the quality of &#946;-sitosterol added.</li>
	</ol>
	</li>
	<li>Determination of &#946;-sitosterol content of samples
	<ol>
		<li>Take 10 batches of authentic Chinese medicinal materials and five batches of related adulterants to prepare sample solutions according to step 4.2.</li>
		<li>Then inject each sample solution and &#946;-sitosterol reference solution to determine the peak area under the conditions described in step 4.1, and calculate the &#946;-sitosterol content of each sample by using the external standard one-point method.</li>
	</ol>
	</li>
</ol>

<ol><li>Chen, C. R. <a target="_blank" href="http://scholar.google.com/scholar?hl=en&safe=off&q=author%3aChen%2C+CR+%22Chinese+Medicine+Specimen+Picture+Book%22">Chinese Medicine Specimen Picture Book</a>. , Shanghai World Book Company. Shanghai. 116(1935).</li>
<li>Xiong, J., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/pubmed?term=((Lignans+from+the+stems+of+Clematis+armandii+%28%26%2334%3BChuan-Mu-Tong%26%2334%3B%29+and+their+anti-neuroinflammatory+activities%5BTitle%5D)+AND+%22Journal+of+Ethnopharmacology%22%5BJournal%5D)">Lignans from the stems of Clematis armandii (&#34;Chuan-Mu-Tong&#34;) and their anti-neuroinflammatory activities.</a> Journal of Ethnopharmacology. 153 (3), 737-743 (2014).</li>
<li>Pan, L. L., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/pubmed?term=((a+lignan+from+the+Chinese+medicinal+plant+Clematis+armandii%2C+inhibits+A431+cell+growth+via+blocking+p70S6%2FS6+kinase+pathway%5BTitle%5D)+AND+%22Integrative+Cancer+Therapies%22%5BJournal%5D)">a lignan from the Chinese medicinal plant Clematis armandii, inhibits A431 cell growth via blocking p70S6/S6 kinase pathway.</a> Integrative Cancer Therapies. 16 (3), 351-359 (2017).</li>
<li>Chinese Pharmacopoeia Commission. <a target="_blank" href="http://scholar.google.com/scholar?hl=en&safe=off&q=%22Pharmacopoeia+of+The+People%27s+Republic+of+China%3A+%28Edition+2020%29%22">Pharmacopoeia of The People's Republic of China: (Edition 2020)</a>. , The Medicine Science and Technology Press of China. China., Beijing. 38(2020).</li>
<li>Wang, D. G., Guo, J. L. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/pubmed?term=((Textual+research+on+the+materia+medica+and+authenticity+of+Clematidis+armandii%5BTitle%5D)+AND+%22Lishizhen+Medicine+and+Materia+Medicine+Research%22%5BJournal%5D)">Textual research on the materia medica and authenticity of Clematidis armandii.</a> Lishizhen Medicine and Materia Medicine Research. 18 (11), 2696(2007).</li>
<li>Fang, Q. M., Zhang, M., Zhong, Y. Y. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/pubmed?term=((The+natural+resources+and+exploitation+of+Caulis+Clematidis+Armandii+in+Sichuan%5BTitle%5D)+AND+%22West+China+Journal+of+Pharmaceutical+Sciences%22%5BJournal%5D)">The natural resources and exploitation of Caulis Clematidis Armandii in Sichuan.</a> West China Journal of Pharmaceutical Sciences. 20 (5), 404-406 (2005).</li>
<li>Bai, M. N., Dai, Y. X., Wang, Y., Ren, Y. Y., Tan, R. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/pubmed?term=((Study+on+the+identi%EF%AC%81cation+of+Caulis+Clematidis+Armandii%5BTitle%5D)+AND+%22Research+and+Practice+on+Chinese+Medicines%22%5BJournal%5D)">Study on the identiﬁcation of Caulis Clematidis Armandii.</a> Research and Practice on Chinese Medicines. 31 (3), 13-16 (2017).</li>
<li>Zhou, P. J., Li, X. F., Fu, D. H., Pu, X. Y., Zhu, G. Q. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/pubmed?term=((Pharmacognosy+identification+of+Ethnomedicine+Clematis+ranunculoides+Franchet%5BTitle%5D)+AND+%22Journal+of+Guangzhou+University+of+Traditional+Chinese+Medicine%22%5BJournal%5D)">Pharmacognosy identification of Ethnomedicine Clematis ranunculoides Franchet.</a> Journal of Guangzhou University of Traditional Chinese Medicine. 34 (3), 432-436 (2017).</li>
<li>Guo, J. L., Tang, Y., Pei, J., Wang, D. G. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/pubmed?term=((Study+on+random+amplified+polymorphic+DNA+and+sequence+characterized+amplified+regions+of+Caulis+Clematidis+Armandii%5BTitle%5D)+AND+%22Journal+of+Chengdu+Medical+College%22%5BJournal%5D)">Study on random amplified polymorphic DNA and sequence characterized amplified regions of Caulis Clematidis Armandii.</a> Journal of Chengdu Medical College. 6 (4), 283-286 (2011).</li>
<li>Liu, M. Z., Li, M. N., Yao, H., Liu, P. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/pubmed?term=((Molecular+identification+of+Clematidis+Armandii+Caulis+and+its+adulterants+and+closely+related+species+by+ITS2+sequence%5BTitle%5D)+AND+%22Global+Traditional+Chinese+Medicine%22%5BJournal%5D)">Molecular identification of Clematidis Armandii Caulis and its adulterants and closely related species by ITS2 sequence.</a> Global Traditional Chinese Medicine. 4 (6), 446-450 (2011).</li>
<li>Liu, J. J., Chen, X., Wei, Z. Q., Li, B. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/pubmed?term=((Chemical+constituents+and+identification+of+the+caules+of+Clematis+armandii+Franch.and+Clematis+montana+Buch.-Ham%5BTitle%5D)+AND+%22Natural+Product+Research+and+Development%22%5BJournal%5D)">Chemical constituents and identification of the caules of Clematis armandii Franch.and Clematis montana Buch.-Ham.</a> Natural Product Research and Development. 22 (6), 998-1000 (2010).</li>
<li>Yang, T. R., Xu, Z., Shi, Y. N. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/pubmed?term=((Studies+on+four+compounds+from+Clematis+Montana%5BTitle%5D)+AND+%22Journal+of+Liaoning+University+of+Traditional+Chinese+Medicine%22%5BJournal%5D)">Studies on four compounds from Clematis Montana.</a> Journal of Liaoning University of Traditional Chinese Medicine. 10 (4), 142-143 (2008).</li>
<li>Yan, L. H., Xu, L. Z., Zhou, Z. M., Yang, S. L. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/pubmed?term=((Chemical+constituents+from+stems+of+Clematis+armandii%28I%29%5BTitle%5D)+AND+%22Chinese+Traditional+and+Herbal+Drugs%22%5BJournal%5D)">Chemical constituents from stems of Clematis armandii(I).</a> Chinese Traditional and Herbal Drugs. 38 (3), 340-342 (2007).</li>
<li>Li, X., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/pubmed?term=((Traditional+uses%2C+phytochemistry%2C+pharmacology%2C+and+toxicology+of+Akebiae+Caulis+and+its+synonyms%3A+A+review%5BTitle%5D)+AND+%22Journal+of+Ethnopharmacology%22%5BJournal%5D)">Traditional uses, phytochemistry, pharmacology, and toxicology of Akebiae Caulis and its synonyms: A review.</a> Journal of Ethnopharmacology. 277, 114245(2021).</li>
<li>Ye, X., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/pubmed?term=((Diuretic+effect+and+material+basis+of+Clematidis+Armandii+Caulis+in+rats%5BTitle%5D)+AND+%22China+Journal+of+Chinese+Materia+Medica%22%5BJournal%5D)">Diuretic effect and material basis of Clematidis Armandii Caulis in rats.</a> China Journal of Chinese Materia Medica. 44 (9), 1889-1894 (2019).</li>
<li>Kuang, Y., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/pubmed?term=((Consistency+study+of+Caulis+Clematidis+Armandii+and+its+traditionally+used+products+and+counterfeit+species+based+on+efficacy+and+pharmacognosy%5BTitle%5D)+AND+%22Pharmacology+and+Clinics+of+Chinese+Materia+Medica%22%5BJournal%5D)">Consistency study of Caulis Clematidis Armandii and its traditionally used products and counterfeit species based on efficacy and pharmacognosy.</a> Pharmacology and Clinics of Chinese Materia Medica. 36 (3), 115-121 (2020).</li>
<li>Li, Y., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/pubmed?term=((Quality+assessment+of+Asarum+heterotropoides+var.+mandshuricum+based+on+HPLC+multi-component+determination+and+multiple+pattern+recognition+method+of+fingerprint%5BTitle%5D)+AND+%22Chinese+Traditional+and+Herbal+Drugs%22%5BJournal%5D)">Quality assessment of Asarum heterotropoides var. mandshuricum based on HPLC multi-component determination and multiple pattern recognition method of fingerprint.</a> Chinese Traditional and Herbal Drugs. 53 (1), 238-243 (2022).</li>
<li>Li, Y., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/pubmed?term=((Determination+of+multi-components+of+Paeoniae+Alba+Radix+based+on+fingerprints+and+chemical+pattern+recognition%5BTitle%5D)+AND+%22Chinese+Traditional+and+Herbal+Drugs%22%5BJournal%5D)">Determination of multi-components of Paeoniae Alba Radix based on fingerprints and chemical pattern recognition.</a> Chinese Traditional and Herbal Drugs. 53 (1), 231-237 (2022).</li>
<li>Li, H. H., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/pubmed?term=((Comparative+investigation+for+raw+and+processed+products+of+Euodiae+Fructus+based+on+high-performance+liquid+chromatography+fingerprints+and+chemical+pattern+recognition%5BTitle%5D)+AND+%22Chemistry+%26+Biodiversity%22%5BJournal%5D)">Comparative investigation for raw and processed products of Euodiae Fructus based on high-performance liquid chromatography fingerprints and chemical pattern recognition.</a> Chemistry & Biodiversity. 18 (8), 2100281(2021).</li>
<li>Dong, L. J., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/pubmed?term=((Study+on+suitable+distribution+areas+of+Kawa+Kimichi+produced+in+Sichuan+province-based+on+remote+sensing+and+GIS-A+case+study+of+Clematis+Armandii%5BTitle%5D)+AND+%22Modernization+of+Traditional+Chinese+Medicine+and+Materia+Medica-World+Science+and+Technology%22%5BJournal%5D)">Study on suitable distribution areas of Kawa Kimichi produced in Sichuan province-based on remote sensing and GIS-A case study of Clematis Armandii.</a> Modernization of Traditional Chinese Medicine and Materia Medica-World Science and Technology. 17 (11), 2398-2404 (2015).</li>
<li>Tang, S. W., Pei, J., Li, F. Y. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/pubmed?term=((Morphological+and+histological+identification+of+Chuanmutong%5BTitle%5D)+AND+%22West+China+Journal+of+Pharmaceutical+Sciences%22%5BJournal%5D)">Morphological and histological identification of Chuanmutong.</a> West China Journal of Pharmaceutical Sciences. 15 (1), 19-21 (2000).</li>
<li>Li, B., Chen, X., Fang, Q. M., Zhang, B. J., Wei, Z. Q. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/pubmed?term=((Quality+Research+of+Chuanmutong%5BTitle%5D)+AND+%22Journal+of+Sichuan+of+Traditional+Chinese+Medicine%22%5BJournal%5D)">Quality Research of Chuanmutong.</a> Journal of Sichuan of Traditional Chinese Medicine. 27 (6), 58-60 (2009).</li>
<li>Wu, W. J., Wan, M. M., Cao, Y. H., Tan, R., Song, L. K. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/pubmed?term=((Research+on+the+Quality+Standard+of+Chuanmutong%5BTitle%5D)+AND+%22Chinese+Archives+of+Traditional+Chinese+Medicine%22%5BJournal%5D)">Research on the Quality Standard of Chuanmutong.</a> Chinese Archives of Traditional Chinese Medicine. 33 (2), 313-315 (2015).</li>
<li>Wei, Z. Q., Chen, X., Li, B., Dong, X. P. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/pubmed?term=((Determination+of+stigmasterol+in+Clematis+armandii+Franch+and+Clematis+montana+Buch-Ham.+by+HPLC%5BTitle%5D)+AND+%22Lishizhen+Medicine+and+Materia+Medica+Research%22%5BJournal%5D)">Determination of stigmasterol in Clematis armandii Franch and Clematis montana Buch-Ham. by HPLC.</a> Lishizhen Medicine and Materia Medica Research. 20 (3), 574-575 (2009).</li>
<li>Qing, L. S., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/pubmed?term=((Determination+of+oleanolic+acid+in+Caulis+clematidis+armandii+by+HPLC%5BTitle%5D)+AND+%22West+China+Journal+of+Pharmaceutical+Sciences%22%5BJournal%5D)">Determination of oleanolic acid in Caulis clematidis armandii by HPLC.</a> West China Journal of Pharmaceutical Sciences. 21 (3), 273-274 (2006).</li>
<li>Yang, S. D., Wang, R., Fu, D. Y., Guo, J. J., Tan, W. Y. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/pubmed?term=((Determination+on+oleanolic+acid+in+caulis+clematidis+armandii+by+microwave+assisted+extraction-HPLC%2FMS%5BTitle%5D)+AND+%22Anhui+Academy+of+Agricultural+Sciences%22%5BJournal%5D)">Determination on oleanolic acid in caulis clematidis armandii by microwave assisted extraction-HPLC/MS.</a> Anhui Academy of Agricultural Sciences. 38 (13), 6929-6931 (2010).</li>
</ol>

The authors have nothing to disclose.

The sample collection for research is the first key step to constructing multi-pattern recognition in identifying the authenticity of Chinese medicinal materials. Through market research, we found that Sichuan Ya&#39;an, Liangshan, and Leshan are the main production areas of wild resources of Chuanmutong. The related varieties of the same genus also have the same geographical distribution6,20; CC, DC, DE, XS, and SMT are often misused as Chuangmutong<sup class="x...

Chuanmutong, dry Caulis of Clematis armandii Franch. or Clematis montana Buch.-Ham., is a traditional Chinese medicine commonly used in clinics1,2,3. It is used for treating urinary problems, edema, sores on the tongue and mouth, decreased milk secretion, joint stiffness, and muscle pain caused by damp heat4. Chuanmutong has always been obtained from wild varieties, mainly distributed in southwest China, especially in Sichuan, where the best quality can be found5,6. It is difficult to distinguish between authentic varieties and their closely related adulterants due to their similar characteristics7,8,9,10. The quality standard of Chuanmutong in the 2020 edition of Chinese Pharmacopoeia only stipulates the properties, microscopic identification, and thin-layer identification without content determination, which cannot effectively identify adulterants, and hence has potential risks. Moreover, there are few reports comparing and identifying Chuanmutong and related plants. Consequently, a quality control method to ensure the authenticity of Chuanmutong is worthy of further study.
The chemical constituents of Chuanmutong are mainly composed of oleanane-type pentacyclic triterpenoids and their glycosides, flavonoids, and organic acids11,12,13,14. Among them, oleanolic acid, &#946;-sitosterol, stigmasterol, and ergosterol have diuretic effects of different intensities, which may be potential pharmacodynamic substances for promoting diuresis and relieving stranguria15,16. Chemical fingerprints are obtained by separating and detecting many chemical components contained in samples by high-performance liquid chromatography (HPLC), gas chromatography (GC), etc. Adopting appropriate statistical analysis methods to analyze the characteristics of Chuanmutong can determine the overall quality control and scientific identification of traditional Chinese medicine17,18,19.
In this study, 10 batches of Chuanmutong authentic varieties and five batches of adulterants were collected. Their quality was compared and analyzed by the HPLC fingerprint method combined with multi-pattern recognition, including cluster analysis (CA), principal component analysis (PCA), orthogonal partial least-squares discrimination analysis (OPLS-CA), and content determination of the pharmacodynamic component. This protocol establishes a method for identifying authentic varieties with high specificity, a new strategy for the scientific identification of authentic varieties and adulterants of Chinese medicinal materials.

<table><tbody><tr><td>Acetic acid</td><td>Zhiyuan Chemical Reagent Co., Ltd., Tianjin, China</td><td>2017381038</td><td></td></tr><tr><td>Acetonitrile</td><td>Sigma-Aldrich&amp;nbsp; Trading Co., Ltd., Shanghai, China</td><td>WXBD5243V</td><td></td></tr><tr><td>&amp;beta;-Sitosterol</td><td>Meisai Biological Technology Co., Ltd., Chongqing, China</td><td>20210201</td><td></td></tr><tr><td>&amp;nbsp;C18 column</td><td>Yuexu Material Technology Co., Ltd., Shanghai, China</td><td>Welch Ultimate LP</td><td></td></tr><tr><td>Chuanmutong</td><td>Guoqiang Chinese Herbal Pieces Co., Ltd., Sichuan, China&amp;nbsp;</td><td>19020103</td><td>CMT-1</td></tr><tr><td>Chuanmutong</td><td>Hongya Wawushan Pharmaceutical Co., Ltd., Sichuan, China&amp;nbsp;</td><td>200701</td><td>CMT-2</td></tr><tr><td>Chuanmutong</td><td>Hongpu Pharmaceutical Co., Ltd., Sichuan, China&amp;nbsp;</td><td>200701</td><td>CMT-3</td></tr><tr><td>Chuanmutong</td><td>Hongpu Pharmaceutical Co., Ltd., Sichuan, China&amp;nbsp;</td><td>200901</td><td>CMT-4</td></tr><tr><td>Chuanmutong</td><td>Xinrentai Pharmaceutical Co., Ltd., Sichuan, China&amp;nbsp;</td><td>210701</td><td>CMT-5</td></tr><tr><td>Chuanmutong</td><td>Haobo Pharmaceutical Co., Ltd., Sichuan, China&amp;nbsp;</td><td>210401</td><td>CMT-6</td></tr><tr><td>Chuanmutong</td><td>Xinrentai Pharmaceutical Co., Ltd., Sichuan, China&amp;nbsp;</td><td>200901</td><td>CMT-7</td></tr><tr><td>Chuanmutong</td><td>Wusheng Pharmaceutical Group Co., Ltd., Sichuan, China&amp;nbsp;</td><td>201201</td><td>CMT-8</td></tr><tr><td>Chuanmutong</td><td>Limin Chinese Herbal Pieces Co., Ltd., Sichuan, China&amp;nbsp;</td><td>201001</td><td>CMT-9</td></tr><tr><td>Chuanmutong</td><td>Yuhetang Pharmaceutical Co., Ltd., Sichuan, China</td><td>210501</td><td>CMT-10</td></tr><tr><td>Clematis argentilucida (Levl. et Vant.) W. T. Wang</td><td>Madzi Bridge, Sanlang Township, Tianquan County, Sichuan, China&amp;nbsp;</td><td>-</td><td>CC</td></tr><tr><td>Clematis apiifolia var. obtusidentata Rehd. et Wils.</td><td>Heilin Village, Qiliping Township, Hongya County, Sichuan, China&amp;nbsp;</td><td>-</td><td>DC</td></tr><tr><td>Clematis peterae Hand.-Mazz.</td><td>Huangmu Village, Huangmu Township, Hanyuan County, Sichuan, China&amp;nbsp;</td><td>-</td><td>DE</td></tr><tr><td>Clematis gouriana Roxb. Var. finetii Rehd. et Wils</td><td>Mixedang Mountain, Huangwan Township, Emei County, Sichuan, China&amp;nbsp;</td><td>-</td><td>XS</td></tr><tr><td>Clematis finetiana Levl. et Vaniot.</td><td>Wannian Village, Huangwan Township, Emei County, Sichuan, China&amp;nbsp;</td><td>-</td><td>SMT</td></tr><tr><td>Electronic balance</td><td>Haozhuang Hengping Scientific Instrument Co., Ltd., Shanghai,&amp;nbsp; China&amp;nbsp;</td><td>FA1204</td><td></td></tr><tr><td>Ergosterol</td><td>Meisai Biological Technology Co., Ltd, Chongqing, China</td><td>20210201</td><td></td></tr><tr><td>Ethanol</td><td>Kelon Chemical Co., Ltd., Chengdu, China</td><td>2021112602</td><td></td></tr><tr><td>Ethyl acetate</td><td>Zhiyuan Chemical Reagent Co., Ltd., Tianjin, China</td><td>2017042043</td><td></td></tr><tr><td>Formic acid</td><td>Kelon Chemical Co., Ltd., Chengdu, China</td><td>2016062901</td><td></td></tr><tr><td>High performance liquid chromatography</td><td>Agilent, USA.</td><td>1260</td><td></td></tr><tr><td>IBM SPSS Statistics version 26.0</td><td>International Business Machines Corporation, USA</td><td>-</td><td></td></tr><tr><td>Methanol</td><td>Sigma-Aldrich&amp;nbsp; Trading Co., Ltd., Shanghai, China</td><td>WXBD6409V</td><td></td></tr><tr><td>Methanol</td><td>Kelon Chemical Co., Ltd., Chengdu, China</td><td>202010302</td><td></td></tr><tr><td>n-butyl alcohol</td><td>Zhiyuan Chemical Reagent Co., Ltd., Tianjin, China</td><td>2020071047</td><td></td></tr><tr><td>Petroleum ether</td><td>Zhiyuan Chemical Reagent Co., Ltd., Tianjin, China</td><td>2020090125</td><td></td></tr><tr><td>Phosphoric acid</td><td>Comeo Chemical Reagent Co., Ltd., Tianjin, China</td><td>20200110</td><td></td></tr><tr><td>SESCF-TCM version 2012</td><td>National Pharmacopoeia Commission, China</td><td>-</td><td>http://114.247.108.158:8888/login</td></tr><tr><td>Stigmasterol</td><td>Meisai Biological Technology Co., Ltd., Chongqing, China</td><td>20210201</td><td></td></tr><tr><td>Trichloromethane</td><td>Sinopharm Group Chemical Reagent Co., Ltd., Shanghai, China</td><td>20200214</td><td></td></tr><tr><td>Umetrics SIMCA version 14.1.0.2047</td><td>Umetrics, Sweden</td><td>-</td><td>https://www.sartorius.com/en/products/process-analytical-technology/data-analytics-software/mvda-software/simca/simca-free-trial-download</td></tr><tr><td>Ultrapure water machine</td><td>Youpu Ultrapure Technology Co., Ltd., Sichuan, China</td><td>UPH-II-10T</td><td></td></tr><tr><td>Ultrasonic cleaner</td><td>Kunshan Hechuang Ultrasound Instrument Co., Ltd., Jiangsu, China</td><td>KH3200E</td><td></td></tr></tbody></table>

hplc coupled with chemical fingerprinting for multi-pattern recognition for identifying the authenticity of clematidis armandii caulis

A method for identifying Chinese medicinal materials and their related adulterants was constructed by taking Clematidis Armandii Caulis (Chuanmutong, a universally used traditional Chinese medicine) as an example. Ten batches of genuine Chuanmutong varieties and five batches of related adulterants were analyzed and compared based on the high-performance liquid chromatography (HPLC) fingerprints combined with chemometrics, including cluster analysis (CA), principal component analysis (PCA), and orthogonal partial least-squares discrimination analysis (OPLS-DA). In addition, the content of &#946;-sitosterol was determined. The control chemical fingerprint of Chuanmutong was established, and 12 common peaks were identified. The similarity between the fingerprint of 10 batches of genuine Chuanmutong varieties and the control fingerprint was 0.910-0.989, while the similarity of five batches of adulterants was only 0.133-0.720. Based on the common peaks in the chromatogram, 15 batches of samples were classified into three content levels by PCA, and were aggregated into four categories by CA, achieving a clear distinction between authentic Chuanmutong and adulterants of Chuanmutong. Further, seven differential components that can effectively identify authentic Chuanmutong and adulterants of Chuanmutong were found through OPLS-DA. The &#946;-sitosterol content of 10 batches of genuine Chuanmutong varieties was 97.53-161.56 &#181;g/g, while the &#946;-sitosterol content of the five batches of adulterants varied greatly, among which the &#946;-sitosterol content of Clematis peterae Hand.-Mazz. and Clematis gouriana Roxb. Var. finetii Rehd. et Wils. was significantly lower than that of authentic varieties of Chuanmutong. The HPLC index component content and chemical fingerprint multi-pattern recognition method established in this study provide a new strategy for effectively identifying authentic Chinese medicinal materials and related adulterants.

Chromatographic fingerprint of Chuanmutong and similarity analysis (SA) 
The RSD values of the relative retention time of precision, repeatability, and stability were below 0.46%, 1.65%, and 0.53%, respectively; the RSD values of the relative peak area were below 4.23%, 3.56%, and 3.96%, respectively. As shown in Figures 1A,B, there were 12 distinct common peaks (from peak 1 to peak 12) in the HPLC fingerprints in the 10 authentic Chuanmutong samples. S...

Watch this Scientific Journal Video about HPLC Coupled with Chemical Fingerprinting for Multi-Pattern Recognition for Identifying the Authenticity of Clematidis Armandii Caulis at JoVE.com

HPLC Coupled with Chemical Fingerprinting for Multi-Pattern Recognition for Identifying the Authenticity of Clematidis Armandii Caulis

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.

HPLC Coupled with Chemical Fingerprinting for Multi-Pattern Recognition for Identifying the Authenticity of Clematidis Armandii Caulis

A method for identifying Chinese medicinal materials and their related adulterants was constructed by taking Clematidis Armandii Caulis (Chuanmutong, a ...

hplc-coupled-with-chemical-fingerprinting-for-multi-pattern

Research

JoVE Journal

Chemistry

1.9K Views.  Chengdu Medical College. Dit protocol kan een nieuwe strategie bieden voor het effectief identificeren van de echte materialen van Clematidis armandii caulis en zijn overspeligen. Deze methode kan worden gebruikt in onderzoek naar de kwaliteit van medicinale materialen en biedt een referentie voor het bestuderen van de kwaliteitsnormen van andere Chinese medicinale materialen. Om de monstervoorbereiding te beginnen, maalt u de grondstof tot een uniforme deeltjesgrootte door ze door een nylon gaas met een geschikte bi...

Video: HPLC Coupled with Chemical Fingerprinting for Multi-Pattern Recognition for Identifying the Authenticity of Clematidis Armandii Caulis

Subtyping of Campylobacter jejuni ssp. doylei Isolates Using Mass Spectrometry-based PhyloProteomics (MSPP)

MALDI-TOF MS offers the possibility to differentiate some bacteria not only at the species and subspecies level but even below, at the strain level. Allelic isoforms of the detectable biomarker ions result in isolate-specific mass shifts. Mass spectrometry-based phyloproteomics (MSPP) is a novel technique that combines the mass spectrometric detectable biomarker masses in a scheme that allows deduction of phyloproteomic relations from isolate specific mass shifts compared to a genome sequenced reference strain. The deduced amino acid sequences are then used to calculate MSPP-based dendrograms.
Here we describe the workflow of MSPP by typing a Campylobacter jejuni ssp. doylei isolate collection of seven strains. All seven strains were of human origin and multilocus sequence typing (MLST) demonstrated their genetic diversity. MSPP-typing resulted in seven different MSPP sequence types, sufficiently reflecting their phylogenetic relations.
The C. jejuni ssp. doylei MSPP scheme includes 14 different biomarker ions, mostly ribosomal proteins in the mass range of 2 to 11 kDa. MSPP can in principle, be adapted to other mass spectrometric platforms with an extended mass range. Therefore, this technique has the potential to become a useful tool for strain level microbial typing.

Subtyping of Campylobacter jejuni ssp. doylei Isolates Using Mass Spectrometry-based PhyloProteomics MSPP

Mass spectrometry-based phyloproteomics (MSPP) was used to type a collection of Campylobacter jejuni ssp. doylei isolates at the strain level in comparison to multilocus sequence typing (MLST).

MALDI-TOF MS offers the possibility to differentiate some bacteria not only at the species and subspecies level but even below, at the strain level. ...

Genetics

Untargeted Metabolomics from Biological Sources Using Ultraperformance Liquid Chromatography-High Resolution Mass Spectrometry (UPLC-HRMS)

Here we present a workflow to analyze the metabolic profiles for biological samples of interest including; cells, serum, or tissue. The sample is first separated into polar and non-polar fractions by a liquid-liquid phase extraction, and partially purified to facilitate downstream analysis. Both aqueous (polar metabolites) and organic (non-polar metabolites) phases of the initial extraction are processed to survey a broad range of metabolites. Metabolites are separated by different liquid chromatography methods based upon their partition properties. In this method, we present microflow ultra-performance (UP)LC methods, but the protocol is scalable to higher flows and lower pressures. Introduction into the mass spectrometer can be through either general or compound optimized source conditions. Detection of a broad range of ions is carried out in full scan mode in both positive and negative mode over a broad m/z range using high resolution on a recently calibrated instrument. Label-free differential analysis is carried out on bioinformatics platforms. Applications of this approach include metabolic pathway screening, biomarker discovery, and drug development.

Untargeted Metabolomics from Biological Sources Using Ultraperformance Liquid Chromatography-High Resolution Mass Spectrometry UPLC-HRMS

Untargeted metabolomics provides a hypothesis generating snapshot of a metabolic profile. This protocol will demonstrate the extraction and analysis of metabolites from cells, serum, or tissue. A range of metabolites are surveyed using liquid-liquid phase extraction, microflow ultraperformance liquid chromatography/high-resolution mass spectrometry (UPLC-HRMS) coupled to differential analysis software.

Here we present a workflow to analyze the metabolic profiles for biological samples of interest including; cells, serum, or tissue. The sample is first ...

Thin-layer Chromatographic (TLC) Separations and Bioassays of Plant Extracts to Identify Antimicrobial Compounds

A common screen for plant antimicrobial compounds consists of separating plant extracts by paper or thin-layer chromatography (PC or TLC), exposing the chromatograms to microbial suspensions (e.g. fungi or bacteria in broth or agar), allowing time for the microbes to grow in a humid environment, and visualizing zones with no microbial growth.&#160;The effectiveness of this screening method, known as bioautography, depends on both the quality of the chromatographic separation and the care taken with microbial culture conditions.&#160;This paper describes standard protocols for TLC and contact bioautography&#160;with a novel application to amino acid-fermenting bacteria. The extract is separated on flexible (aluminum-backed) silica TLC plates, and bands are visualized under ultraviolet (UV) light.&#160;Zones are cut out and incubated face down onto agar inoculated with the test microorganism.&#160;Inhibitory bands are visualized by staining the agar plates with tetrazolium red.&#160;The method is applied to the separation of red clover (Trifolium pratense cv. Kenland) phenolic compounds and their screening for activity against Clostridium sticklandii, a hyper ammonia-producing bacterium (HAB) that is native to the bovine rumen.&#160;The TLC methods apply to many types of plant extracts&#160;and other bacterial species (aerobic or anaerobic), as well as fungi, can be used as test organisms if culture conditions are modified to fit the growth requirements of the species.

Thin-layer Chromatographic TLC Separations and Bioassays of Plant Extracts to Identify Antimicrobial Compounds

Methods are described for thin-layer chromatographic (TLC) separation of plant extracts and contact bioautography to identify antibacterial metabolites. The methods are applied to the screening of red clover phenolic compounds inhibiting hyper&#160;ammonia-producing bacteria (HAB) native to the bovine rumen.

A common screen for plant antimicrobial compounds consists of separating plant extracts by paper or thin-layer chromatography (PC or TLC), exposing the ...

Rapid High-throughput Species Identification of Botanical Material Using Direct Analysis in Real Time High Resolution Mass Spectrometry

We demonstrate that direct analysis in real time-high resolution mass spectrometry can be used to produce mass spectral profiles of botanical material, and that these chemical fingerprints can be used for plant species identification. The mass spectral data can be acquired rapidly and in a high throughput manner without the need for sample extraction, derivatization or pH adjustment steps. The use of this technique bypasses challenges presented by more conventional techniques including lengthy chromatography analysis times and resource intensive methods. The high throughput capabilities of the direct analysis in real time-high resolution mass spectrometry protocol, coupled with multivariate statistical analysis processing of the data, provide not only class characterization of plants, but also yield species and varietal information. Here, the technique is demonstrated with two psychoactive plant products, Mitragyna speciosa (Kratom) and Datura (Jimsonweed), which were subjected to direct analysis in real time-high resolution mass spectrometry followed by statistical analysis processing of the mass spectral data. The application of these tools in tandem enabled the plant materials to be rapidly identified at the level of variety and species.

A method for species identification of botanical material by direct analysis in real time-high resolution mass spectrometry and multivariate statistical analysis is presented.

We demonstrate that direct analysis in real time-high resolution mass spectrometry can be used to produce mass spectral profiles of botanical material, ...

Using Capillary Electrophoresis to Quantify Organic Acids from Plant Tissue: A Test Case Examining Coffea arabica Seeds

Carboxylic acids are organic acids containing one or more terminal carboxyl (COOH) functional groups. Short chain carboxylic acids (SCCAs; carboxylic acids containing three to six carbons), such as malate and citrate, are critical to the proper functioning of many biological systems, where they function in cellular respiration and can serve as indicators of cell health. In foods, organic acid content can have significant impact on taste, with increased SCCA levels resulting in a sour or &#34;acid&#34; taste. Because of this, methods for the rapid analysis of organic acid levels are of particular interest to the food and beverage industries. Unfortunately, however, most methods used for SCCA quantification are dependent on time-consuming protocols requiring the derivatization of samples with hazardous reagents, followed by costly chromatographic and/or mass spectrometric analyses. This method details an alternate method for the detection and quantification of organic acids from plant material and food samples using free zonal capillary electrophoresis (CZE), sometimes simply referred to as capillary electrophoresis (CE). CZE provides a cost-effective method for measuring SCCAs with a low limit of detection (0.005 mg/ml). This article details the extraction and quantification of SCCAs from plant samples. While the method provided focuses on measurement of SCCAs from coffee beans, the method provided can be applied to multiple plant-based food materials.

Using Capillary Electrophoresis to Quantify Organic Acids from Plant Tissue: A Test Case Examining Coffea arabica Seeds

This article presents a method for the detection and quantification of organic acids from plant material using free zonal capillary electrophoresis. An example of the potential application of this method, determining the effects of a secondary fermentation on organic acid levels in coffee seeds, is provided.

Carboxylic acids are organic acids containing one or more terminal carboxyl (COOH) functional groups. Short chain carboxylic acids (SCCAs; carboxylic ...

Identifying Per- and Polyfluorinated Chemical Species with a Combined Targeted and Non-Targeted-Screening High-Resolution Mass Spectrometry Workflow

Historical and emerging per- and polyfluoroalkyl substances (PFASs) have garnered significant interest from the public and government agencies from the local to federal levels. The continuing evolution of PFAS chemistries presents a challenge to the environmental monitoring, where ongoing development of targeted methods necessarily lags the discovery of new chemical compounds. There is a need, therefore, to have forward-looking methodologies that can detect emerging and unexpected compounds, monitor these species over time, and resolve details of their chemical structure to enable future work in human health. To this end, non-targeted analysis by high-resolution mass spectrometry offers a broad base detection approach that can be combined with almost any sample preparation scheme and provides significant capabilities for compound identification after detection. Herein, we describe a solid-phase extraction (SPE) based sample concentration method tuned for shorter chain and more hydrophilic PFAS chemistries, such as per fluorinated ether acids and sulfonates, and describe analysis of samples prepared in this fashion in both targeted and non-targeted modes. Targeted methods provide superior quantification when reference standards are available but are intrinsically limited to expected compounds when performing analysis. In contrast, a non-targeted approach can identify the presence of unexpected compounds and provide some information about their chemical structure. Information about chemical features can be used to correlate compounds across sample locations and track abundance and occurrence over time.

Here, we present a protocol for the sequential targeted quantification and non-targeted analysis of fluorinated compounds in water by mass spectrometry. This methodology provides quantitative levels of known fluorochemical compounds and identifies unknown chemicals in related samples with semi-quantitative estimates of their abundance.

Historical and emerging per- and polyfluoroalkyl substances (PFASs) have garnered significant interest from the public and government agencies from the ...

Environment

Chromatographic Fingerprinting by Template Matching for Data Collected by Comprehensive Two-Dimensional Gas Chromatography

Data processing and evaluation are critical steps of comprehensive two-dimensional gas chromatography (GCxGC), particularly when coupled to mass spectrometry. The rich information encrypted in the data may be highly valuable but difficult to access efficiently. Data density and complexity can lead to long elaboration times and require laborious, analyst-dependent procedures. Effective yet accessible data processing tools, therefore, are key to enabling the spread and acceptance of this advanced multidimensional technique in laboratories for daily use. The data analysis protocol presented in this work uses chromatographic fingerprinting and template matching to achieve the goal of highly automated deconstruction of complex two-dimensional chromatograms into individual chemical features for advanced recognition of informative patterns within individual chromatograms and across sets of chromatograms. The protocol delivers high consistency and reliability with little intervention. At the same time, analyst supervision is possible in a variety of settings and constraint functions that can be customized to provide flexibility and capacity to adapt to different needs and goals. Template matching is shown here to be a powerful approach to explore extra-virgin olive oil volatilome. Cross-alignment of peaks is performed not only for known targets, but also for untargeted compounds, which significantly increases the characterization power for a wide range of applications. Examples are presented to evidence the performance for the classification and comparison of chromatographic patterns from sample sets analyzed under similar conditions.

This protocol presents an approach to fingerprint and explore multi-dimensional data collected by comprehensive two-dimensional gas chromatography coupled to mass spectrometry. Dedicated pattern recognition algorithms (template matching) are applied to explore the chemical information encrypted in the extra-virgin olive oil volatile fraction (i.e., volatilome).

Data processing and evaluation are critical steps of comprehensive two-dimensional gas chromatography (GCxGC), particularly when coupled to mass ...

Ultra High-Performance Liquid Chromatography-Mass Spectrometry and Self-established Database Analysis of Chinese Herbal Medicine Components

Chinese herbal medicine is complex and has numerous unknown compounds, making qualitative research crucial. Ultra-high-performance liquid chromatography quadrupole time-of-flight mass spectrometry (UPLC-Q-TOF-MS) is the most widely used method in qualitative analysis of compounds. The method includes standardized and programmed protocols for sample pretreatment, MS tune, MS acquisition, and data processing. The sample pretreatments include collection, pulverization, solvent extraction, ultrasound, centrifugation, and filtration. Data post-processing was described in detail and includes data importing, self-established database construction, method establishment, data processing, and other manual operations. The above-ground part of the alpine yarrow herb, Achillea millefolium L., is used to treat inflammation, gastrointestinal disturbances, and pain and its 3-oxa-guaianolides could be useful leads for anti-inflammatory drug development. Three representative compounds in AML were identified, combining TOF-MS with a self-established database. Moreover, the differences from existing literature, liquid-phase parameter optimization, scan mode selection, ion source suitability, collision energy adjustment, isomer screening, method limitation, and possible solutions were discussed. This standardized analysis method is universal and can be applied to identify complex compounds in Chinese herbal medicine.

We describe a general protocol and systematic design that could be applied to separate and recognize complex components in alpine yarrow herb, Achillea millefolium L., a Chinese herbal medicine.

Chinese herbal medicine is complex and has numerous unknown compounds, making qualitative research crucial. Ultra-high-performance liquid chromatography ...

Analyzing Tibetan Medicinal Plant APB Using 2D-HPLC-MS with Molecular Networking

2D-HPLC-MS Technology Combined with Molecular Network for the Identification of Components in Tibetan Medicine Aconitum pendulum

In this study, a comprehensive approach was employed, utilizing 2D-HPLC-MS technology in conjunction with the molecular network to unravel the intricate chemical composition of the Tibetan medicinal plant APB. Through the implementation of 2D-HPLC, enhanced separation of complex mixtures was achieved, enabling the isolation of individual compounds for subsequent analysis. The molecular network approach further aided in elucidating structural relationships among these compounds, contributing to the determination of potential bioactive molecules. This integrated strategy efficiently identified a wide array of chemical components present within the plant. The findings revealed a diverse spectrum of chemical constituents within APB, including alkaloids, among others. This research not only advances understanding of the phytochemical profile of this traditional Tibetan medicine but also provides valuable insights into its potential therapeutic properties. The integration of 2D-HPLC-MS and molecular network proves to be a powerful tool for systematically exploring and identifying complex chemical compositions in herbal medicines, paving the way for further research and development in the field of natural product discovery.

Author Spotlight: Integrating 2D-HPLC-MS and Molecular Networking in Natural Medicine Analysis

This study utilizes two-dimensional high-performance liquid chromatography-mass spectrometry (2D-HPLC-MS) technology in conjunction with molecular networking to unravel the intricate chemical composition of the Tibetan medicinal plant Aconitum pendulum Busch (APB). The article provides a detailed protocol for the systematic exploration and identification of complex chemical components of herbal medicines.

In this study, a comprehensive approach was employed, utilizing 2D-HPLC-MS technology in conjunction with the molecular network to unravel the intricate ...

Medicine

Field Identification of Matricaria chamomilla using a Portable qPCR System

Quality control in botanical products begins with the raw material supply. Traditionally, botanical identification is performed through morphological assessment and chemical analytical methods. However, the lack of availability of botanists, especially in recent years, coupled with the need to enhance quality control to combat the stresses on the supply chain brought by increasing consumer demand and climate change, necessitates alternative approaches. The goal of this protocol is to facilitate botanical species identification using a portable qPCR system on the field or in any setting, where access to laboratory equipment and expertise is limited. Target DNA is amplified using dye-based qPCR, with DNA extracted from botanical reference materials serving as a positive control. The target DNA is identified by its specific amplification and matching its melting peak against the positive control. A detailed description of the steps and parameters, from hands-on field sample collection, to DNA extraction, PCR amplification, followed by data interpretation, has been included to ensure that readers can replicate this protocol. The results produced align with traditional laboratory botanical identification methods. The protocol is easy to perform and cost-effective, enabling quality testing on raw materials as close to the point of origin of the supply chain as possible.

Field Identification of Matricaria chamomilla using a Portable qPCR System

Presented here is a protocol for field identification of Matricaria chamomilla using a portable qPCR system. This easy-to-perform protocol is ideal as a method to confirm the identity of a botanical species at locations where access to laboratory equipment and expertise is limited, such as farms and warehouses.

Quality control in botanical products begins with the raw material supply. Traditionally, botanical identification is performed through morphological ...

HPLC Coupled with Chemical Fingerprinting for Multi-Pattern Recognition for Identifying the Authenticity of Clematidis Armandii Caulis

Samenvatting

Meer video's verkennen