Pub Date : 2000-10-01DOI: 10.1002/1521-3838(200010)19:4<339::AID-QSAR339>3.0.CO;2-E
T. Schultz, J. Seward
Regression-type structure-toxicity relationships have been developed between Tetrahymena pyriformis population growth impairment toxicity data (log 1/IGC50) and the dimyristoyl phosphatidylcholine/water partition coefficient (log KDMPC) or the 1-octanol/water partition coefficient (log Kow). A statistically robust model [log(1/ IGC50)= 0.73 log (KDMPC)−1.62; n=23, r2=0.926, s=0.24, F=263, Pr/gt F=0.0001] was found for non-polar narcotics, polar narcotics, as well as esters with the DMPC partition coefficient. The above model was statistically better than the model [log(1/IGC50) = 0.71 (log Kow) − 1.60; n = 23, r2 = 0.828, s = 0.39, F = 101, Pr> F = 0.0001] developed for the same compounds with 1-octanol/water partitioning as the independent variable. The former equation does not explain the difference in the acute mechanisms of toxic action known to exist in fish for non-polar and polar narcotics. However, log KDMPC appears to correct for differences in the concentration of toxicant reaching the site of toxic action between narcotic mechanisms. Outliers to the log KDMPC model were primary aliphatic amines.
{"title":"Dimyristoyl Phosphatidylcholine/water Partitioning-dependent Modeling of Narcotic Toxicity toTetrahymena pyriformis","authors":"T. Schultz, J. Seward","doi":"10.1002/1521-3838(200010)19:4<339::AID-QSAR339>3.0.CO;2-E","DOIUrl":"https://doi.org/10.1002/1521-3838(200010)19:4<339::AID-QSAR339>3.0.CO;2-E","url":null,"abstract":"Regression-type structure-toxicity relationships have been developed between Tetrahymena pyriformis population growth impairment toxicity data (log 1/IGC50) and the dimyristoyl phosphatidylcholine/water partition coefficient (log KDMPC) or the 1-octanol/water partition coefficient (log Kow). A statistically robust model [log(1/ IGC50)= 0.73 log (KDMPC)−1.62; n=23, r2=0.926, s=0.24, F=263, Pr/gt F=0.0001] was found for non-polar narcotics, polar narcotics, as well as esters with the DMPC partition coefficient. The above model was statistically better than the model [log(1/IGC50) = 0.71 (log Kow) − 1.60; n = 23, r2 = 0.828, s = 0.39, F = 101, Pr> F = 0.0001] developed for the same compounds with 1-octanol/water partitioning as the independent variable. The former equation does not explain the difference in the acute mechanisms of toxic action known to exist in fish for non-polar and polar narcotics. However, log KDMPC appears to correct for differences in the concentration of toxicant reaching the site of toxic action between narcotic mechanisms. Outliers to the log KDMPC model were primary aliphatic amines.","PeriodicalId":20818,"journal":{"name":"Quantitative Structure-activity Relationships","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2000-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"80499396","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2000-06-01DOI: 10.1002/1521-3838(200006)19:3<257::AID-QSAR257>3.0.CO;2-2
T. Moon, M. Chi, Donghyun Kim, C. Yoon, Young-Sang Choi
The quantitative structure-activity relationships (QSAR) studies on flavonoid derivatives as cytochrome P450 1A2 inhibitors were performed using multiple linear regression analysis (MLR) and neural networks (NN). The results of MLR and NN show that Hammett constant, the highest occupied molecular orbital energy (HOMO), the nonoverlap steric volume, the partial charge of C3 carbon atom, and the HOMO π coefficients of C3, C3′ and C4′ carbon atoms of flavonoids play an important role in inhibitory activity. The correlations between the descriptors and the activities were improved by neural networks although the descriptors of optimum MLR model were used in the networks, which implies that the descriptors used in MLR model include nonlinear relationships. Moreover, neural networks using descriptors selected by the pruning method gave higher r2 value than neural networks using MLR descriptors.
{"title":"Quantitative Structure-Activity Relationships (QSAR) Study of Flavonoid Derivatives for Inhibition of Cytochrome P450 1A2","authors":"T. Moon, M. Chi, Donghyun Kim, C. Yoon, Young-Sang Choi","doi":"10.1002/1521-3838(200006)19:3<257::AID-QSAR257>3.0.CO;2-2","DOIUrl":"https://doi.org/10.1002/1521-3838(200006)19:3<257::AID-QSAR257>3.0.CO;2-2","url":null,"abstract":"The quantitative structure-activity relationships (QSAR) studies on flavonoid derivatives as cytochrome P450 1A2 inhibitors were performed using multiple linear regression analysis (MLR) and neural networks (NN). The results of MLR and NN show that Hammett constant, the highest occupied molecular orbital energy (HOMO), the nonoverlap steric volume, the partial charge of C3 carbon atom, and the HOMO π coefficients of C3, C3′ and C4′ carbon atoms of flavonoids play an important role in inhibitory activity. The correlations between the descriptors and the activities were improved by neural networks although the descriptors of optimum MLR model were used in the networks, which implies that the descriptors used in MLR model include nonlinear relationships. Moreover, neural networks using descriptors selected by the pruning method gave higher r2 value than neural networks using MLR descriptors.","PeriodicalId":20818,"journal":{"name":"Quantitative Structure-activity Relationships","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2000-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"90397522","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2000-06-01DOI: 10.1002/1521-3838(200006)19:3<264::AID-QSAR264>3.0.CO;2-A
Åsa Nyström, P. Andersson, T. Lundstedt
{"title":"Multivariate Data Analysis of Topographically Modified α‐Melanotropin Analogues using Auto and Cross Auto Covariances (ACC)","authors":"Åsa Nyström, P. Andersson, T. Lundstedt","doi":"10.1002/1521-3838(200006)19:3<264::AID-QSAR264>3.0.CO;2-A","DOIUrl":"https://doi.org/10.1002/1521-3838(200006)19:3<264::AID-QSAR264>3.0.CO;2-A","url":null,"abstract":"","PeriodicalId":20818,"journal":{"name":"Quantitative Structure-activity Relationships","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2000-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"74460195","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2000-06-01DOI: 10.1002/1521-3838(200006)19:3<227::AID-QSAR227>3.0.CO;2-E
S. Chicu, K. Herrmann, S. Berking
{"title":"An Approach to Calculate the Toxicity of Simple Organic Molecules on the Basis of QSAR Analysis inHydractinia echinata (Hydrozoa, Cnidaria)","authors":"S. Chicu, K. Herrmann, S. Berking","doi":"10.1002/1521-3838(200006)19:3<227::AID-QSAR227>3.0.CO;2-E","DOIUrl":"https://doi.org/10.1002/1521-3838(200006)19:3<227::AID-QSAR227>3.0.CO;2-E","url":null,"abstract":"","PeriodicalId":20818,"journal":{"name":"Quantitative Structure-activity Relationships","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2000-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"82310882","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2000-06-01DOI: 10.1002/1521-3838(200006)19:3<247::AID-QSAR247>3.0.CO;2-6
Y. Martín-Biosca, M. Molero-Monfort, S. Sagrado, R. Villanueva-Camañas, M. Medina-Hernández
The need to get a tool for biological parameters estimation of new compounds for clinical applications, supports the postulation of predictive models as an alternative to conventional classical assays being no necessary the use of experimentation in animals. Our main aim in this work is to determine correlations between the logarithm of capacity factors and preclinical pharmacology and therapeutic efficacy parameters of barbiturates. The predictive and interpretative capability of quantitative chromatographic retention-biological activity models is supported by the fact that in adequate experimental conditions the solute partitioning into chromatographic system can emulate the solute partitioning into lipid bilayers of biological membranes, which is the basis for drug and metabolite uptake, passive transport across membranes and bioaccumulation. Thirteen barbiturates were included in the study. The RP-HPLC capacity factors of barbiturates were determined using different Brij35 concentrations as micellar mobile phases. Relationships between sixteen biological activities of barbiturates reported in bibliography and retention data are established and their predictive and interpretative ability are evaluated. These logarithmic relationships were significant between preclinical pharmacology parameters and the retention factors of barbiturates; so the regression coefficients (R2) for ED, EC50-LRR and duration of action were 0.97, 0.98 and 0.95, respectively. These relationships were great too for therapeutic efficacy parameters; i.e for IC50, Ki (50% inhibition displaceable [14C]-amobarbital binding to acetylcholine receptor-rich membranes) and Ki (for PIP-kinase) (R2=0.98). The results indicate, the retention of compounds in MLC, which depends on hydrophobic, electronic and steric features of compounds and is measured in flow conditions, is capable to describe and predict in vitro the biological responses of barbiturates. This approach merits further exploration in other classes of compounds.
{"title":"Development of Predictive Retention-Activity Relationship Models of Barbiturates by Micellar Liquid Chromatography","authors":"Y. Martín-Biosca, M. Molero-Monfort, S. Sagrado, R. Villanueva-Camañas, M. Medina-Hernández","doi":"10.1002/1521-3838(200006)19:3<247::AID-QSAR247>3.0.CO;2-6","DOIUrl":"https://doi.org/10.1002/1521-3838(200006)19:3<247::AID-QSAR247>3.0.CO;2-6","url":null,"abstract":"The need to get a tool for biological parameters estimation of new compounds for clinical applications, supports the postulation of predictive models as an alternative to conventional classical assays being no necessary the use of experimentation in animals. Our main aim in this work is to determine correlations between the logarithm of capacity factors and preclinical pharmacology and therapeutic efficacy parameters of barbiturates. The predictive and interpretative capability of quantitative chromatographic retention-biological activity models is supported by the fact that in adequate experimental conditions the solute partitioning into chromatographic system can emulate the solute partitioning into lipid bilayers of biological membranes, which is the basis for drug and metabolite uptake, passive transport across membranes and bioaccumulation. Thirteen barbiturates were included in the study. The RP-HPLC capacity factors of barbiturates were determined using different Brij35 concentrations as micellar mobile phases. Relationships between sixteen biological activities of barbiturates reported in bibliography and retention data are established and their predictive and interpretative ability are evaluated. These logarithmic relationships were significant between preclinical pharmacology parameters and the retention factors of barbiturates; so the regression coefficients (R2) for ED, EC50-LRR and duration of action were 0.97, 0.98 and 0.95, respectively. These relationships were great too for therapeutic efficacy parameters; i.e for IC50, Ki (50% inhibition displaceable [14C]-amobarbital binding to acetylcholine receptor-rich membranes) and Ki (for PIP-kinase) (R2=0.98). The results indicate, the retention of compounds in MLC, which depends on hydrophobic, electronic and steric features of compounds and is measured in flow conditions, is capable to describe and predict in vitro the biological responses of barbiturates. This approach merits further exploration in other classes of compounds.","PeriodicalId":20818,"journal":{"name":"Quantitative Structure-activity Relationships","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2000-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"73707669","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2000-04-01DOI: 10.1002/1521-3838(200004)19:2<142::AID-QSAR142>3.0.CO;2-0
Mathias Weigt, M. Wiese
{"title":"A Comparative Molecular Field Analysis of Inhibitors of Tubulin Polymerization","authors":"Mathias Weigt, M. Wiese","doi":"10.1002/1521-3838(200004)19:2<142::AID-QSAR142>3.0.CO;2-0","DOIUrl":"https://doi.org/10.1002/1521-3838(200004)19:2<142::AID-QSAR142>3.0.CO;2-0","url":null,"abstract":"","PeriodicalId":20818,"journal":{"name":"Quantitative Structure-activity Relationships","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2000-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"80158149","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2000-04-01DOI: 10.1002/1521-3838(200004)19:2<127::AID-QSAR127>3.0.CO;2-P
C. Marot, P. Chavatte, D. Lesieur
The 3D-QSAR approach has been used to obtain informations about the active conformation of selective cyclo-oxygenase-2 (COX-2) inhibitors. In this paper, we have compared different combinations of two fields (steric and electrostatic) in order to optimize the 3D-QSAR models of selective COX-2 inhibitors. Assuming that all the compounds interact at the same binding site at the enzyme level, DuP697 pharmacophoric conformation served as a template for the superimposition of 54 structurally heterogeneous COX-2 inhibitors constituting both the training and test sets used to perform a 3D-QSAR study via the CoMFA method. A statistically significant model was obtained with 38 compounds of the training set (n=38, q2=0,70, N=3, r2=0,93, s=0,38, F=156) with steric and electrostatic relative contributions of 40% and 60%, respectively. The predictive power of the proposed model was discerned by successfully testing the 16 compounds constituting the test set. The so obtained and validated model brings important structural insights to aid the design of novel anti-inflammatory drugs prior to their synthesis.
{"title":"Comparative Molecular Field Analysis of Selective Cyclooxygenase‐2 (COX‐2) Inhibitors","authors":"C. Marot, P. Chavatte, D. Lesieur","doi":"10.1002/1521-3838(200004)19:2<127::AID-QSAR127>3.0.CO;2-P","DOIUrl":"https://doi.org/10.1002/1521-3838(200004)19:2<127::AID-QSAR127>3.0.CO;2-P","url":null,"abstract":"The 3D-QSAR approach has been used to obtain informations about the active conformation of selective cyclo-oxygenase-2 (COX-2) inhibitors. In this paper, we have compared different combinations of two fields (steric and electrostatic) in order to optimize the 3D-QSAR models of selective COX-2 inhibitors. Assuming that all the compounds interact at the same binding site at the enzyme level, DuP697 pharmacophoric conformation served as a template for the superimposition of 54 structurally heterogeneous COX-2 inhibitors constituting both the training and test sets used to perform a 3D-QSAR study via the CoMFA method. A statistically significant model was obtained with 38 compounds of the training set (n=38, q2=0,70, N=3, r2=0,93, s=0,38, F=156) with steric and electrostatic relative contributions of 40% and 60%, respectively. The predictive power of the proposed model was discerned by successfully testing the 16 compounds constituting the test set. The so obtained and validated model brings important structural insights to aid the design of novel anti-inflammatory drugs prior to their synthesis.","PeriodicalId":20818,"journal":{"name":"Quantitative Structure-activity Relationships","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2000-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"82361957","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2000-04-01DOI: 10.1002/1521-3838(200004)19:2<162::AID-QSAR162>3.0.CO;2-T
Romy Fleischer, P. Frohberg, A. Büge, P. Nuhn, M. Wiese
An evaluation of quantitative structure-activity relationships (QSAR) for 28 N1-phenyl-2-phenylhydrazonoacetamides, that are inhibitors of soybean 15-lipoxygenase was carried out with different statistical methods. Initially the variation of structure was characterized by the Free-Wilson method and analyzed by multiple linear regression (MLR) and partial least squares analysis (PLS). Both methods revealed an increase in activity, if the N1-phenyl substituent of the parent molecule is meta-substituted with groups, that show a positive resonance effect at the annular structure. To include physicochemical aspects a combined Free-Wilson-Hansch approach was used. Because of high intercorrelations among some physicochemical parameters a principal component-analysis (PCA) was performed to extract information from those intercorrelated variables in a few principal components (PC's). The resulting equations indicate that besides an electron donating group at the central amidrazone moiety electronic effects at the arylhydrazone substituent play an important role for the biological activity.
{"title":"QSAR Analysis of Substituted 2‐Phenylhydrazonoacetamides Acting as Inhibitors of 15‐Lipoxygenase","authors":"Romy Fleischer, P. Frohberg, A. Büge, P. Nuhn, M. Wiese","doi":"10.1002/1521-3838(200004)19:2<162::AID-QSAR162>3.0.CO;2-T","DOIUrl":"https://doi.org/10.1002/1521-3838(200004)19:2<162::AID-QSAR162>3.0.CO;2-T","url":null,"abstract":"An evaluation of quantitative structure-activity relationships (QSAR) for 28 N1-phenyl-2-phenylhydrazonoacetamides, that are inhibitors of soybean 15-lipoxygenase was carried out with different statistical methods. Initially the variation of structure was characterized by the Free-Wilson method and analyzed by multiple linear regression (MLR) and partial least squares analysis (PLS). Both methods revealed an increase in activity, if the N1-phenyl substituent of the parent molecule is meta-substituted with groups, that show a positive resonance effect at the annular structure. To include physicochemical aspects a combined Free-Wilson-Hansch approach was used. Because of high intercorrelations among some physicochemical parameters a principal component-analysis (PCA) was performed to extract information from those intercorrelated variables in a few principal components (PC's). The resulting equations indicate that besides an electron donating group at the central amidrazone moiety electronic effects at the arylhydrazone substituent play an important role for the biological activity.","PeriodicalId":20818,"journal":{"name":"Quantitative Structure-activity Relationships","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2000-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"81578008","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2000-04-01DOI: 10.1002/1521-3838(200004)19:2<135::AID-QSAR135>3.0.CO;2-T
M. Jalali-Heravi, E. Konouz
The CMC of a set of 51 alkylpolyoxyethylene glycol ethers, R(EO)m, and alkylphenol (ethylene oxide) ethers, Rϕ(EO)m, was related to topological, electronic and molecular structure parameters using a stepwise regression method. In development of the models linear and quadratic terms were used without the use of cross terms. Different strategies including Akaike Information Criterion (AIC) were used for choosing the best model. Specification of the best model in agreement with the experiment indicates that volume of the hydrophobic group and surface area of the molecule play a major role in the mechanism of micellization of nonionic surfactants. It was demonstrated that the CMC of these compounds depend upon the orientation of carbon atoms at the interface of two phases. The predicted values of CMC using the best model for R(EO)m molecules containing even number of EO groups are better than that for the molecules with odd number of EOs.
采用逐步回归方法对51种烷基聚氧乙二醇醚R(EO)m和烷基酚(环氧乙烷)醚rφ (EO)m的CMC与拓扑结构、电子结构和分子结构参数的关系进行了研究。在模型的开发中，使用了线性项和二次项，而不使用交叉项。采用赤池信息准则(Akaike Information Criterion, AIC)等不同策略选择最佳模型。最佳模型的确定与实验结果一致，表明疏水基团的体积和分子的表面积对非离子表面活性剂的胶束化机理起主要作用。结果表明，这些化合物的CMC取决于两相界面上碳原子的取向。最佳模型对含有偶数个EO基团的R(EO)m分子的CMC预测值优于含有奇数个EO基团的R(EO)m分子的CMC预测值。
{"title":"Use of Quantitative Structure Activity Relationships in Prediction of CMC of Nonionic Surfactants","authors":"M. Jalali-Heravi, E. Konouz","doi":"10.1002/1521-3838(200004)19:2<135::AID-QSAR135>3.0.CO;2-T","DOIUrl":"https://doi.org/10.1002/1521-3838(200004)19:2<135::AID-QSAR135>3.0.CO;2-T","url":null,"abstract":"The CMC of a set of 51 alkylpolyoxyethylene glycol ethers, R(EO)m, and alkylphenol (ethylene oxide) ethers, Rϕ(EO)m, was related to topological, electronic and molecular structure parameters using a stepwise regression method. In development of the models linear and quadratic terms were used without the use of cross terms. Different strategies including Akaike Information Criterion (AIC) were used for choosing the best model. Specification of the best model in agreement with the experiment indicates that volume of the hydrophobic group and surface area of the molecule play a major role in the mechanism of micellization of nonionic surfactants. It was demonstrated that the CMC of these compounds depend upon the orientation of carbon atoms at the interface of two phases. The predicted values of CMC using the best model for R(EO)m molecules containing even number of EO groups are better than that for the molecules with odd number of EOs.","PeriodicalId":20818,"journal":{"name":"Quantitative Structure-activity Relationships","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2000-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"89572069","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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