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Objective To establish a method for simultaneous determination of 11 components of Solanum nigrum from different producing areas,and to evaluate the quality by chemometrics and entropy weight-technique for order preference by similarity to ideal solution(EW-TOPSIS).Methods The 17 batches of Solanum nigrum samples from 8 provinces were collected.The high performance liquid chromatography(HPLC)method was used to simultaneously determine the contents of medioresino,pinoresinol,quercetin,rutoside,solasonine,solamargine,khasianine,solasodine,desgalactotigonin,diosgenin and β-sitosterol,and the multi-components quantitative control mode of Solanum nigrum was established.The quality evaluation model of Solanum nigrum was established by using chemical recognition pattern and EW-TOPSIS method,and the overall quality was evaluated comprehensively.Results When the 11 components were in the 0.78-39.00,0.55-27.50,0.34-17.00,0.21-10.50,41.87-2 093.50,60.95-3 047.50,2.58-129.00,1.02-51.00,0.46-23.00,1.05-52.50 and 0.42-21.00 μg/mL(r＞0.999 0),their linear relationships were good.The average recovery was 96.81％-100.28％with the RSD＜2.0％(n=9).17 batches of samples clustered into 3 categories.Solamargine,solasonine,desgalactotigonin and medioresino may be the main potential markers affecting the quality of Solanum nigrum.The results of EW-TOPSIS method showed that,the quality evaluation closeness of 17 batches of Solanum nigrum were 0.433 6,0.416 8,0.624 2,0.500 8,0.479 1,0.636 1,0.568 3,0.250 0,0.190 9,0.222 1,0.170 7,0.720 0,0.698 3,0.744 7,0.717 9,0.720 9 and 0.718 3,respectively,indicating that the overall quality of Solanum nigrum from Liaoning,Jilin and Heilongjiang were better,followed by Jiangsu,Henan and Anhui.Conclusion The established HPLC method for simultaneous determination of 11 components in Solanum nigrum is convenient and accurate.Chemometrics and EW-TOPSIS method are objective and comprehensive,which can be used for the overall quality evaluation of Solanum nigrum.
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Objective To establish the HPLC fingerprint of Rosae Rugosae Flos;To provide references for the quality evaluation of Rosae Rugosae Flos.Methods The HPLC analysis was carried on a COSMOSIL 5C18-MS-Ⅱ column(4.6 mm×250 mm,5 μm);the mobile phase was 2.5 % acetonitrile + 0.1 % formic acid aqueous solution(A)-acetonitrile + 0.1 % formic acid(B)with gradient elution at the flow rate of 0.5 Ml/min;the column temperature was 40℃;the detection wavelength was 350 nm.The similarity of 13 batches of samples was evaluated by Similarity Evaluation System for Chromatographic Fingerprint of TCM(2012 edition).Qualitative analysis was carried out by LC-MS technology.The overall quality evaluation of Rosae Rugosae Flos was carried out by combining clustering analysis,principal component analysis and orthogonal partial least square discrimination.Results The common mode of HPLC fingerprints of Rosae Rugosae Flos was established,and the similarity of 13 samples was good.9 compounds were identified preliminary.13 batches of samples were aggregated into 3 categories by chemical pattern recognition.Conclusion The fingerprints of Rosae Rugosae Flos established in this study combines with chemical pattern recognition method,which has high sensitivity and strong specificity,can provide a basis for the quality evaluation of Rosae Rugosae Flos.
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Objective:To comprehensively evaluated the quality of Sargentodoxae Caulis from different habitats with a combination of indexes and characteristic chromatogram method from Chinese Pharmcopoeia (Edition 2020). Methods:The contents of water content, total ash, ethanolic extract, sulfur dioxide residue, heavy metals and harmful elements, total phenols, chlorogenic acid, salidroside and characteristic chromatogram of 17 batches of Sargentodoxae Caulis were determined. The quality of Sargentodoxae Caulis was comprehensively evaluated by combining chemical pattern recognition method. Results:The water content, total ash content, extracts, and content determination of 17 batches of Sargentodoxae Caulis from different habitats complyed with the provisions of the Chinese Pharmcopoeia (Edition 2020). There were differences in the contents of extracts, chlorogenic acid, and salidroside, among which the content of Anhui origin was higher. A total of 8 common peaks were identified from the 17 batches samples. Conclusion:Comprehensive evaluation of multiple indicators can demonstrate the quality of Sargentodoxae Caulis more correctly, and shows that the quality of Sargentodoxae Caulis from different habitats is different. The quality of Sargentodoxae Caulis from Anhui is better than that from other habitats.
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Objective:To compare and analyze rhizome and main root of Ginseng Radix et Rhizoma (GRR); To provide the basis of whether removing the rhizome of Ginseng (RG) when processing by checking whole consistency of chromatographic fingerprints from rhizome and main root of GRR.Methods:The chromatographic consistency of different parts of GRR samples was compared using high performance thin layer chromatography (HPTLC); HPLC was used to determine the fingerprint of different parts of GRR, and combining it with the reference substance for common peak identification and similarity analysis; differences were analyzed using principal component analysis and orthogonal partial least squares discriminant analysis (OPLS-DA).Results:In the HPTLC spectrum, the characteristic spectra of rhizome and main root of GRR and whole GRR were similar, and there was a clear total of 7-9 spots. HPLC fingerprints of RRR presented 13 common peaks, and identified 6 peaks, including ginsenoside Rg1&Re (mixed), Rf, Rb1, Rc, Ro and Rd; the similarity of all samples ranged from 0.842 to 0.993; the differences in peak areas comprehensively contributed to the similarity differences between samples, with head being the main influence; ginsenoside Ro, Rb1 and other six components were differential markers, and the relative content in the head of GRR is significantly higher than that in the main root. Conlusions The analysis of differential profiling of chemical constituents showed that the chemical substances are almost the same between the head and the main root. The processing of GRR to remove head will result in the loss of ginsenosides, the overall effective component of GRR. Considering the human and resource costs, it was suggested that the whole root of GRR, instead of removing its rhizome, could be used in classical and traditional prescriptions.
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Objective:To optimize the different salt preparation processes of salt-processed Psoraleae Fructus and compare the differences among different salt products.Methods:Ultra-high performance liquid chromatography (UPLC) characteristic chromatogram of Psoraleae Fructus was established. By using the comprehensive scoring method, the total content of psoralen and isopsoralen and the peak area of the characteristic chromatogram were used as the evaluation index to optimize the four different processing technologies, including "stir-frying with salt-water", "steaming with salt-water", "spraying with salt-water" and "microwaving with salt-water". Meanwhile, entropy weight TOPSIS method, clustering analysis (HCA), principal component analysis (PCA) and other chemical pattern recognition methods were used to compare the quality difference of different salt-processed Psoraleae Fructus.Results:The optimized "stir-frying with salt-water" process of salt-processed Psoralea Fructus was 170 ℃ for 13 min, "steaming with salt-water" process for 1 h, "spraying with salt-water" process for 110 ℃ for 13 min and "microwaving with salt-water" process for 105 s microwave heating. TOPSIS comprehensive evaluation results of entropy weight showed that the quality of different salt products of Psoraleae Fructus ranked as product of stir-frying with salt-water > product of stir-frying with green salt-water > product of spraying with salt-water > product of microwaving with salt-water > product of steaming with salt-water; HCA results showed that different salt products of Psoraleae Fructus could be polymerized into two categories, between which product of stir-frying with salt-water and product of stir-frying with green salt-water were polymerized into one category; product of spraying with salt-water, product of microwaving with salt-water and product of steaming with salt-water were another category; the results of PCA showed that different salt products of Psoraleae Fructus could be clustered into 4 categories, among which product of stir-frying with salt-water, product of stir-frying with green salt-water and product of spraying with salt-water were clustered into the same category respectively, and product of microwaving with salt-water and product of steaming with salt-water were clustered into the same category.Conclusion:The chemical composition of Psoraleae Fructus processed by different salting methods is different. The results of this study can provide reference for processing optimization of salt-processed Psoraleae Fructus and identification of different salt products.
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To study the material basis of cold and hot properties of traditional Chinese medicines (TCMs) in Lamiaceae and to establish a cold and hot properties identification model, a database of material components of TCMs in Lamiaceae was established. A three-level classification system of material components was used to obtain the material basis of cold and hot properties of the Lamiaceae family by using data mining methods such as frequency analysis, association rule analysis, logistic regression, and feature selection. Several identification models were established to recognize the cold and hot properties. The chi-square test results showed that the material composition ratios of cold and hot properties were significantly different at the first-level, second-level, and third-level classification (P < 0.05), and the differences varied as the levels of substance classification changed. The average coefficients of variation were 42.30%, 79.07%, and 91.51% at the first-level, second-level, and third-level classification levels, respectively. In other words, in terms of the percentage differences in material composition ratio, the first-level was smaller than the second-level, and the second-level was smaller than the third-level. The results of the association rule analysis showed that under the third-level classification, there were many effective association rules, and 27 core groups and 34 specific groups of chemical components were obtained based on these rules. 15 decisive groups were obtained from the feature selection results. Multinomial logistic regression analysis was used to successfully establish a cold and hot properties identification model with an overall accuracy of 89%. The material basis of cold and hot properties of TCMs in Lamiaceae is different and intersect with each other. Twenty-seven groups of chemical components, such as bicyclic diterpenes, are the core groups of cold and hot properties, of which 15 groups are the decisive groups. The cold and hot properties are often characterized by the interaction of multiple classes of substances, and a single class of substances often cannot be used to characterize the properties. The organic combination of multiple classes of substances is the material basis of cold and hot properties.
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OBJECTIVE@#To review targeted muscle reinnervation (TMR) surgery for the construction of intelligent prosthetic human-machine interface, thus providing a new clinical intervention paradigm for the functional reconstruction of residual limbs in amputees.@*METHODS@#Extensively consulted relevant literature domestically and abroad and systematically expounded the surgical requirements of intelligent prosthetics, TMR operation plan, target population, prognosis, as well as the development and future of TMR.@*RESULTS@#TMR facilitates intuitive control of intelligent prostheses in amputees by reconstructing the "brain-spinal cord-peripheral nerve-skeletal muscle" neurotransmission pathway and increasing the surface electromyographic signals required for pattern recognition. TMR surgery for different purposes is suitable for different target populations.@*CONCLUSION@#TMR surgery has been certified abroad as a transformative technology for improving prosthetic manipulation, and is expected to become a new clinical paradigm for 2 million amputees in China.
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Humanos , Miembros Artificiales , Músculo Esquelético , Procedimientos Neuroquirúrgicos , Procedimientos de Cirugía Plástica , Implantación de PrótesisRESUMEN
The gut microbiota plays a key role in host health and disease, particularly through their interactions with the immune system. Intestinal homeostasis is dependent on the symbiotic relationships between the host and the diverse gut microbiota, which is influenced by the highly co-evolved immune-microbiota interactions. The first step of the interaction between the host and the gut microbiota is the sensing of the gut microbes by the host immune system. In this review, we describe the cells of the host immune system and the proteins that sense the components and metabolites of the gut microbes. We further highlight the essential roles of pattern recognition receptors (PRRs), the G protein-coupled receptors (GPCRs), aryl hydrocarbon receptor (AHR) and the nuclear receptors expressed in the intestinal epithelial cells (IECs) and the intestine-resident immune cells. We also discuss the mechanisms by which the disruption of microbial sensing because of genetic or environmental factors causes human diseases such as the inflammatory bowel disease (IBD).
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Humanos , Enfermedades Inflamatorias del Intestino , Microbioma Gastrointestinal , Microbiota , Sistema Inmunológico , IntestinosRESUMEN
OBJECTIVE@#To rapidly identify the two morphologies and chemical properties of similar herbal medicines, Blumea riparia and B. megacephala as the basis for chemical constituent analysis.@*METHODS@#UPLC-Q-Exactive-MS/MS was utilized for profiling and identification of the constituents in B. riparia and B. megacephala. Chemical pattern recognition (CPR) was further used to compare and distinguish the two herbs and to identify their potential characteristic markers. Then, an HPLC method was established for quality evaluation.@*RESULTS@#A total of 93 constituents are identified, including 54 phenolic acids, 35 flavonoids, two saccharides, one phenolic acid glycoside, and one other constituent, of which 67 were identified in B. riparia and B. megacephala for the first time. CPR indicates that B. riparia and B. megacephala samples can be distinguished from each other based on the LC-MS data. The isochlorogenic acid A to cryptochlorogenic acid peak area ratio calculated from the HPLC chromatograms was proposed as a differentiation index for distinguishing and quality control of B. riparia and B. megacephala.@*CONCLUSION@#This study demonstrates significant differences between B. riparia and B. megacephala in terms of chemical composition. The results provide a rapid and simple strategy for the comparison and evaluation of the quality of B. riparia and B. megacephala.
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Objective To establish the fingerprint of Fangshu Qingre mixture and evaluate its quality in combination with chemical pattern recognition.Methods Using 3,5-O-dicaffeoyl quinic acid as the reference peak,ultra performance liquid chrmatography(UPLC)fingerprint of 10 batches of Fangshu Qingre mixture were established with Similarity Evaluation System for Chromatographic Fingerprint of TCM(2012 edition).The common peaks were identified and similarity evaluation were conducted,to determine the attribution of each common peak.The cluster analysis(CA),principal component analysis(PCA)and orthogonal partial least squares method-discriminant analysis(OPLS-DA)in the chemical pattern recognition method were used to determine the differential components affecting the quality of the preparations.Results There were 31 common peaks in the fingerprints of 10 batches of Fangshu Qingre mixture,and their similarities were between 0.975 and 0.996.Six common peaks were identified,including peak 9(chlorogenic acid),peak 19(luteolin-7-O-β-D-glucoside),peak 21(3,5-O-dicafeoyl quinic acid),peak 23(hesperidin),peak 29(linarin),and peak 31(patchoulone).CA and PCA divided 10 batches of Fangshu Qingre mixture into 3 categories.The results of PCA showed that the cumulative variance contribution rate of principal components 1～6 was 95.947％.The results of OPLS-DA showed that there were 13 peaks VIP greater than 1,which was the difference component.Conclusion The method is simple and sensitive,can be used to evaluate the quality of Fangshu Qingre mixture.
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OBJECTIVE To establish the HPLC fingerprint of Mongolian medicine Sanzisan ，and to evaluate its internal quality by chemical pattern recognition technique comprehensively. METHODS HPLC method was used. Using geniposide as reference，HPLC fingerprints of 15 batches of Sanzisan were drawn with Similarity Evaluation System of TCM Chromatogram Fingerprint（2012 edition）. Similarity evaluation and common peaks identification were conducted. Combined with cluster analysis （CA），principal component analysis （PCA），and orthogonal partial least squares-discriminant analysis （OPLS-DA），the quality of 15 batches of Sanzisan was evaluated ，and the differential markers that affected its quality were screened. RESULTS There were 29 common peaks in 15 batches of Sanzisan ，and the similarity was no less than 0.952，indicating that the chemical composition of the 15 batches of Sanzisan had good consistency. A total of 13 common peaks were identified ，which were chebulic acid ，gallic acid，punicalin，punicalagin A ，punicalagin B ，jasminoside B ，caffeic acid ，corilagin，geniposide，chebulagic acid ，1，2，3，4，6- O-galloylglucose，chebulinic acid ，ellagic acid. Both CA and PCA could divide 15 batches of Sanzisan into four categories ，and the classification results were consistent ，indicating that the quality of 15 batches of Sanzisan had certain differences. Fourteen differential markers （chebulic acid ，gallic acid ，ellagic acid ，etc）that lead to the quality difference between batches were screened out by OPLS-DA. CONCLUSIONS Established HPLC fingerprint analysis method is simple and stable. Combined with chemical pattern recognition analysis ，it can be used for the quality control of Sanzisan.
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Objective:To establish the HPLC fingerprint of Centellae herba and determine the content of asiaticoside, madecassic acid and asiaticoside B simultaneously; To compare the quality differences of Centellae herba collected in different months. Methods:The chromatographic condition was a Shimadzu InertSustain C18 column (4.6 mm×250 mm, 5 μm) with a mobile phase consisting of acetonitrile and 2 mmol/L beta cyclodextrin in gradient elution at the flow rate of 0.8 ml/min. The detection wavelength was 204 nm, and the column temperature was 30 ℃. The different Centellae herba materials of collected in 2-12 months from Chenzhou were studied by the similarity evaluation combined with cluster analysis, principal component analysis and the three contents determination. Results:The HPLC fingerprint of Centellae herba was established and 9 common peaks were designated. The eleven samples were different, which can be aggregated into 4 categories and the quality of Centellae herba collected in July was the best. Conclusion:The established fingerprint and multi-components quantitative method are stable and reliable, which can provide a reference for the quality control and the utilization of Centellae herba resource.
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The quality control and evaluation methods of Schizonepeta tenuifolia were established by HPLC fingerprint, multi index component content determination and chemical pattern recognition to provide basis for the quality control of medicinal materials. The chemical components of 25 batches of Schizonepeta tenuifolia panicle medicinal materials and decoction pieces collected were analyzed by high performance liquid chromatography, and the common pattern of fingerprint was established. A total of 22 common chromatographic peaks were calibrated, and their similarity was more than 0.9. The samples were divided into three categories according to different producing areas by cluster analysis. The results of principal component analysis and cluster analysis were consistent. Finally, five differential markers of different batches of Schizonepeta tenuifolia were selected by orthogonal partial least squares discriminant analysis. Through the identification of the reference substance, it was determined that peak 9 was hesperidin, peak 10 was rosmarinic acid, peak 13 was tilianin, peak 14 was quercetin, and peak 20 was pulegone. The quality evaluation method established in this study is stable and reliable, and is suitable for the quality control of Schizonepeta tenuifolia.
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OBJECTIVE To determine the conte nts of 4 main components in Rougui renshen granules ，and to establish the fingerprint and to screen differential markers affecting its quality. METHODS HPLC method was employed to determine the contents of ammonium glycyrrhizinate ，glycyrrhizin，cinnamic acid and cinnamaldehyde. HPLC fingerprints of 10 batches of Rougui renshen granules were established simultaneously. Similarity Evaluation System of Chromatographic Fingerprint of TCM （2012 edition）was used to evaluate the similarity and determine the common peak ；SPSS 25.0 and SIMCA 14.1 software were applied for cluster analysis （CA），principal component analysis （PCA）and partial least square-discriminant analysis （OPLS-DA）. The differential markers affecting sample quality were screened by using the variable importance in projection （VIP）value＞ 1 as standard. RESULTS The methodology of content determination met the relevant requirements. The contents of ammonium glycyrrhizinate，glycyrrhizin，cinnamic acid and cinnamaldehyde were 1.808 4-2.770 0，1.137 2-1.481 4，0.076 5-0.091 8 and 0.130 9-0.478 4 mg/g，respectively. A total of 16 common peaks were found in the fingerprints of 10 batches of Rougui renshen granules. Four chromatographic peaks were identified ，i.e. glycyrrhizin （peak 6），cinnamic acid （peak 10），cinnamaldehyde（peak 11）and ammonium glycyrrhizinate （peak 15）. The similarities of samples were ＞0.95. Results of CA showed that 10 batches of samples could be classified into three categories ：S3 was grouped into one category ；S1-S2，S4-S5 and S 10 were grouped into one category；S6-S9 were grouped into one category. The results of PCA showed that the cumulative contribution rate of the first three principal components was 91.918％，and the classification results were consistent with CA. The results of OPLS-DA showed that the four peaks with VIP value ＞1 were peak 11（cinnamaldehyde），peak 15（ammonium glycyrrhizinate ），peak 6（glycyrrhizin） and peak 9. CONCLUSIONS Established methods of content determination and fingerprint are accurate and reproducible ，and can be used for the quality evaluation of Rougui renshen granules. The components as ammonium glycyrrhizinate ，cinnamaldehyde， glycyrrhizin may be differential markers affecting the quality of Rougui renshen granules.
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OBJECTIVE To e stablish the fingerprint of Qings hen tiaozhi xiaoke tablets （QTXT）and carry out the analysis of chemical pattern recognition ，and determine the contents of seven active components simultaneously. METHODS Using coptisine hydrochloride as reference ，the Similarity Evaluation System for Chromatographic Fingerprint of TCM （2012 edition）was utilized to establish the HPLC fingerprints of 13 batches of QTXT and analyze their similarity. The common peaks were confirmed by comparing with the chromatogram of the mixed control ；the attribution of the common peak was determined by comparing the chromatograms of the sample solutions of single decoction pieces and negative sample solutions ；using SPSS 22.0 and SIMCA 14.1 software，cluster analysis （CA），principal component analysis （PCA）and orthogonal partial least squares-discriminant analysis （OPLS-DA）were carried out ，and the markers affecting the quality of QTXT were screened ，using the variable importance in projection（VIP）value greater than 1 as the standard. Using coptisine hydrochloride as internal reference ，the contents of naringin ， hesperidin，neohesperidin，berberine hydrochloride ，palmatine hydrochloride and lovastatin were determined by quantitative analysis of multicomponents by single marker （QAMS），and then compared wi th the result s（except for coptisine hydrochloride ） of external standard method. RESULTS There were 17 Δ 基金项目：江苏省“双创团队”项目[No.（2018）2024号] ＊硕士研究生。研究方向：中药新药药学。E-mail：2769544062@ common peaks in 13 batches of QTXT ，and the similarity was qq.com 0.987-0.999. Seven chromatographic peaks were identified ， # 通信作者：副研究员，硕士生导师，博士。研究方向：中药药剂 namely naringin （peak 4）， hesperidin （peak 5）， 学。E-mail：tsliur411@sina.com neohesperidin（peak 6），coptisine hydrochloride （peak 8）， ·1204· China Pharmacy 2022Vol. 33 No. 10 中国药房 2022年第33卷第10期 palmatine hydrochloride （peak 9），berberine hydrochlo ride（peak 10），lovastatin（peak 14）. Peaks 7-10 were the exclusive peaks of Coptis chinensis ；peaks 3-6 and 11-13 were the exclusive peaks of bran-fried Fructus aurantii ；peak 14 was the exclusive peak of Monascus purpureus ；peak 1 was the common peak of C. chinensis and M. purpureus . Peak 2 and 15 were the common peak of bran-fried F. aurantii and M. purpureus ；peaks 16 and 17 were the common peaks of 6 traditional Chinese medicines. The results of CA showed that 13 batches of QTXT could be divided into three categories ，S2 was clustered into one category ，S1，S9，S10 were clustered into one category ，S3-S8 and S 11-S13 were clustered into one category. The results of PCA showed that accumulative variance contribution of the first three principal components was 85.120％. Compared with CA ，S1 was further distinguished from S9 and S 10 by PCA. OPLS-DA showed that 7 common peaks with VIP value greater than 1（from large to small ）were peak 10 （berberine hydrochloride ），peak 9（palmatine hydrochloride ），peak 5（hesperidin），peak 11 and peak 8（coptisine hydrochloride ）， peak 12 and peak 6（neohesperidin）. The contents of naringin ，hesperidin，neohesperidin，berberine hydrochloride ，palmatine hydrochloride and lovastatin measured by QAMS were 40.198-77.552，6.138-13.413，71.823-125.868，11.274-49.951，3.303- 5.367，1.821-3.185 mg/g，respectively. The contents of naringin ，hesperidin，neohesperidin，berberine hydrochloride ，coptisine hydrochloride，palmatine hydrochloride and lovastatin measured by external reference method were 41.454-79.976，6.404-13.993， 74.068-129.081，11.627-51.512，5.922-12.020，3.158-5.131 and 1.901-3.325 mg/g，respectively. The deviations of the two methods （except for coptisine hydrochloride ）were all less than 3.00％. CONCLUSIONS The established HPLC fingerprint and the method of QAMS are simple ，accurate and reproducible. Combined with chemical pattern recognition analysis ，it can be used for the quality evaluation of QTXT. Berberine hydrochloride ，palmatine hydrochloride and other components may be the markers affecting the quality of the drug.
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Based on ITS sequences, the molecular identification of Cordyceps cicadae and Tolypocladium dujiaolongae was carried out, and high-performance liquid chromatography(HPLC) fingerprint combined with chemical pattern recognition method was established to differentiate C. cicadae from its adulterant T. dujiaolongae. The genomic DNA from 10 batches of C. cicadae and five batches of T. dujiaolongae was extracted, and ITS sequences were amplified by PCR and sequenced. The stable differential sites of these two species were compared and the phylogenetic tree was constructed via MEGA 7.0. HPLC was used to establish the fingerprints of C. cicadae and T. dujiaolongae, and similarity evaluation, cluster analysis(CA), principal component analysis(PCA), and partial least squares discriminant analysis(PLS-DA) were applied to investigate the chemical pattern recognition. The result showed that the sources of these two species were different, and there were 115 stable differential sites in ITS sequences of C. cicadae and T. dujiao-longae. The phylogenetic tree could distinguish them effectively. HPLC fingerprints of 18 batches of C. cicadae and 5 batches of T. dujiaolongae were established. The results of CA, PCA, and PLS-DA were consistent, which could distinguish them well, indicating that there were great differences in chemical components between C. cicadae and T. dujiaolongae. The results of PLS-DA showed that six components such as uridine, guanosine, adenosine, and N~6-(2-hydroxyethyl) adenosine were the main differential markers of the two species. ITS sequences and HPLC fingerprint combined with the chemical pattern recognition method can serve as the identification and differentiation methods for C. cicadae and T. dujiaolongae.
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Cromatografía Líquida de Alta Presión/métodos , Cordyceps/genética , Hypocreales , FilogeniaRESUMEN
The present study detected the component content in Dalbergiae Odoriferae Lignum by HPLC fingerprint and the multi-component determination method. HPLC analysis was performed on the Agilent ZORBAX SB-C_(18) column(4.6 mm×250 mm, 5 μm). Acetonitrile-0.5% phosphoric acid aqueous solution with gradient elution was employed as the mobile phase. The flow rate was 1.0 mL·min~(-1) and the column temperature was maintained at 30 ℃. The detection wavelength was 210 nm and the sample volume was 10 μL. The similarity of 18 batches of Dalbergiae Odoriferae Lignum was 0.343-0.779, indicating that there were great differences between different batches of Dalbergiae Odoriferae Lignum. Eighteen common peaks were identified, including eight flavonoids such as liquiritigenin and latifolin. The mass fractions of liquiritigenin, luteolin, naringenin, isoliquiritigenin, formononetin, dalbergin, latifolin, and pinocembrin were in the ranges of 0.134 1%-0.495 2%, 0.028 2%-0.167 0%, 0.016 3%-0.591 3%, 0.053 5%-0.188 0%, 0.142 4%-0.640 1%, 0.068 0%-0.590 7%, 0.003 2%-1.980 7%, and 0.009 6%-0.740 2%, respectively. Eighteen batches of Dalbergiae Odoriferae Lignum were divided into three categories by cluster analysis and eight differential components in Dalbergiae Odoriferae Lignum were marked by partial least-squares discriminant analysis(PLS-DA). The cumulative variance contribution rate was 90.5%. The HPLC fingerprint combined with the multi-component determination method for Dalbergiae Odoriferae Lignum is easy in operation and accurate in results, with good repeatability and reliability. The quality of Dalbergiae Odoriferae Lignum can be evaluated and analyzed by the PLS-DA model. This study is expected to provide a reference for the quality control and clinical application of Dalbergiae Odoriferae Lignum.
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Cromatografía Líquida de Alta Presión/métodos , Medicamentos Herbarios Chinos/análisis , Flavonoides/análisis , Control de Calidad , Reproducibilidad de los ResultadosRESUMEN
OBJECTIVE To establish the fingerprints of Kangfuyan capsules and carry out chemical pattern recognition analysis，and simultaneously determine the contents of five components so as to promote the quality standard of the drug. METHODS High performance liquid chromatography （HPLC）fingerprints of 11 batches of Kangfuyan capsules （S1-S11）were established by Similarity Evaluation System of TCM Chromatographic Fingerprint （2012 edition）；identification and attribution analysis of chromatographic peaks were carried out by comparison with the chromatograms of the reference substance and the decoction pieces of single ingredient. SPSS 26.0 and SIMCA 14.1 software were used for cluster analysis and principal component analysis. HPLC method was used to determine the contents of matrine ，phellodendrine chloride ，rutin，forsythoside A and berberine hydrochloride. RESULTS There were 29 common peaks in the fingerprints for 11 batches of samples ，and the similarity was higher than 0.99. A total of 5 chromatographic peaks were identified ，which are matrine （peak 3），phellodendron chloride （peak 14），rutin （peak 20），forsythiaside A （peak 22） and berberine hydrochloride （peak 28）. The results of cluster analysis and principal component analysis showed that S 1-S9 were clustered into one category ，and S 10 and S 11 were clustered into another category. The contents of above 5 components were 29.320 5-60.144 3，0.621 6-1.076 6，1.025 9-2.830 5，2.899 3-6.212 7 and 4.425 1-8.581 6 mg/g， respectively. CONCLUSIONS The established fingerprint and content determination method are stable and reliable ，and can provide reference for the quality control of the preparation in combination with chemical pattern recognition analysis.
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Ischemia-reperfusion injury (IRI) is a pathophysiological process, which widely exists in organ transplantation and surgery. IRI is mainly manifested with hypoxia injury of organs or tissues during the ischemia period, which could be further aggravated after reperfusion. Ischemia-reperfusion induces tissue cell injury, releases damage-associated molecular pattern and further activates multiple immune cells via pattern recognition receptor, leading to aseptic inflammation and aggravating tissue injury. Cyclic guanosine monophosphate-adenosine monophosphate synthase (cGAS), as a critical member of pattern recognition receptor, could activate the stimulator of interferon genes (STING) signal pathway and play an important regulatory role in innate immune response. At present, increasing evidences have shown that cGAS-STING signal pathway plays a significant role in organ IRI. In this article, STING signaling pathway, its role and mechanism in IRI of different organs were reviewed, aiming to provide novel ideas for clinical interventions.
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OBJECTIVE To establish the method for simultaneous determination of 11 components as narirutin in Biantong capsules，to conduct chemical pattern recognition analysis and to screen differential markers affecting their quality . METHODS HPLC method was adopted . The separation was carried out on Venusil XBP C 18 column with mobile phase consisted of acetonitrile - 0.1％ phosphoric acid solution with gradient elution at flow rate of 1.0 mL/min. The sample size was 10 µL，and column temperature was set at 30 ℃. The detection wavelengths were set at 283，330，520，220 nm，respectively. Using verbascoside as an internal standard ，the contents were determined by quantitative analysis of mult -components by single marker （QAMS），and the results were compared with those of external standard method . Cluster analysis ，principle component analysis and orthogonal partial least squares -discriminant analysis were performed with SPSS 26.0 and SIMCA 14.1 software. The differential markers affecting the quality of Biantong capsules were screened using the variable importance in projection （VIP）value greater than 1 as the standard . RESULTS The contents of narirutin ，naringin，neohesperidin，echinacoside，tubuloside A ，isoacteoside，cyanidin-3-O-glucoside， cyanidin-3-O-rutoside，atractylolide Ⅲand atractylolide Ⅰ were 0.739-1.265，1.134-2.158，1.407-2.359，1.368-2.502，0.304-0.522， 0.257-0.521，0.423-0.727，0.375-0.733，0.130-0.283 and 0.062-0.166 mg/g，respectively. The relative average deviation of them from the external standard method was less than 2％. The results of cluster analysis showed that 15 batches of samples could be grouped into three categories ，S1-S7 as a category ，S8-S10 as a category ，and S 11-S15 as a category ，which was consistent with the classification results of principal component analysis . The results of orthogonal partial least squares -discriminant analysis showed that the VIP values of cyanidin -3-O-rutoside，atractylolide Ⅲ， naringin，neohesperidin，echinacoside and verbascoside were all greater than 1. CONCLUSIONS The method for simultaneous determination of 11 components in Biantongcapsules， including narirutin ， is successfully established . Combined with chemical pattern recognition analysis ，it can be used for the quality control of Biantong capsules . Six components such as cyanidin -3-O-rutoside may be the differential markers that affect the quality of Biantong capsules .