Current Proteomics最新文献

{"title":"Machine Learning-based Virtual Screening Strategy Reveals Some Natural Compounds As Potential PAK4 Inhibitors In Triple Negative Breast Cancer","authors":"Opeyemi Iwaloye, O. Elekofehinti, Babatomiwa Kikiowo, E. Oluwarotimi, T. M. Fadipe","doi":"10.2174/1570164618999201223092209","DOIUrl":"https://doi.org/10.2174/1570164618999201223092209","url":null,"abstract":"\u0000\u0000 P-21 activating kinase 4 (PAK4) is implicated in poor prognosis of many cancers, especially in the\u0000progression of Triple Negative Breast Cancer (TNBC). The present study was aimed at designing some potential drug\u0000candidates as PAK4 inhibitors for breast cancer therapy.\u0000\u0000\u0000\u0000This study aimed to finding novel inhibitors of PAK4 from natural compounds using computational approach.\u0000\u0000\u0000\u0000\u0000An e-pharmacophore model was developed from docked PAK4-coligand complex and used to screen over a\u0000thousand natural compounds downloaded from BIOFACQUIM and NPASS databases to match a minimum of 5 sites for\u0000selected (ADDDHRR) hypothesis. The robustness of the virtual screening method was accessed by well-established\u0000methods including EF, ROC, BEDROC, AUAC, and the RIE. Compounds with fitness score greater than one were filtered\u0000by applying molecular docking (HTVS, SP, XP and Induced fit docking) and ADME prediction. Using Machine learningbased approach QSAR model was generated using Automated QSAR. The computed top model kpls_des_17 (R2= 0.8028,\u0000RMSE = 0.4884 and Q2 = 0.7661) was used to predict the pIC50 of the lead compounds. Internal and external validations\u0000were accessed to determine the predictive quality of the model. Finally the binding free energy calculation was computed.\u0000\u0000\u0000\u0000The robustness/predictive quality of the models were affirmed. The hits had better binding affinity than the\u0000reference drug and interacted with key amino acids for PAK4 inhibition. Overall, the present analysis yielded three potential\u0000inhibitors that are predicted to bind with PAK4 better than reference drug tamoxifen. The three potent novel inhibitors\u0000vitexin, emodin and ziganein recorded IFD score of -621.97 kcal/mol, -616.31 kcal/mol and -614.95 kcal/mol, respectively\u0000while showing moderation for ADME properties and inhibition constant.\u0000\u0000\u0000\u0000It is expected that the findings reported in this study may provide insight for designing effective and less toxic\u0000PAK4 inhibitors for triple negative breast cancer.\u0000","PeriodicalId":50601,"journal":{"name":"Current Proteomics","volume":null,"pages":null},"PeriodicalIF":0.8,"publicationDate":"2020-12-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"83944319","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Heteromerization As a Mechanism Modulating the Affinity of the ACE2 Receptor to the Receptor Binding Domain of SARS-CoV-2 Spike Protein","authors":"D. Guidolin, C. Tortorella, D. Anderlini, M. Marcoli, G. Maura","doi":"10.2174/1570164618999201216112244","DOIUrl":"https://doi.org/10.2174/1570164618999201216112244","url":null,"abstract":"\u0000\u0000 Angiotensin Converting Enzyme 2 (ACE2) is primarily involved in the maturation of angiotensin.\u0000It also represents the main receptor for the Severe Acute Respiratory Syndrome coronavirus 2 (SARS-CoV-2) that caused\u0000the serious epidemics COVID-19. Available evidence indicates that at the cell membrane ACE2 can form heteromeric\u0000complexes with other membrane proteins, including the amino acid transporter B0AT1 and G Protein-Coupled Receptors\u0000(GPCR).\u0000\u0000\u0000\u0000It is well known that during the formation of quaternary structures, the configuration of each single monomer is\u0000re-shaped by its interaction pattern in the macromolecular complex. Therefore, it can be hypothesized that the affinity of\u0000ACE2 to the viral receptor binding domain (RBD), when in a heteromeric complex, may depend on the associated partner.\u0000\u0000\u0000\u0000By using established docking and molecular dynamics procedures, the reshaping of monomer was explored in\u0000silico to predict possible heterodimeric structures between ACE2 and GPCR, such as angiotensin and bradykinin receptors.\u0000The associated possible changes in binding affinity between the viral RBD and ACE2 when in the heteromeric complexes\u0000were also estimated.\u0000\u0000\u0000\u0000 The results provided support to the hypothesis that the heteromerization state of ACE2 may\u0000modulate its affinity to the viral RBD. If experimentally confirmed, ACE2 heteromerization may contribute to explain the\u0000observed differences in susceptibility to virus infection among individuals and to devise new therapeutic opportunities.\u0000\u0000","PeriodicalId":50601,"journal":{"name":"Current Proteomics","volume":null,"pages":null},"PeriodicalIF":0.8,"publicationDate":"2020-12-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"86847460","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Proteomic study of the mechanism of talin-C as an inhibitor of HIV infection","authors":"L. Yin, Yujiao Zhang, Huichun Shi, Ya-ru Xing, Hong Zhou Lu, Lijun Zhang","doi":"10.2174/1570164618999201214153239","DOIUrl":"https://doi.org/10.2174/1570164618999201214153239","url":null,"abstract":"\u0000\u0000 Talin-1 is involved in human immunodeficiency virus (HIV) invasion and synapse development.\u0000We found that talin-1 was cleaved into a 38 KDa fragment (talin-C) in the peripheral blood mononuclear cells (PBMCs) of\u0000HIV patients; however, the underlying mechanisms remain unknown.\u0000\u0000\u0000\u0000This study aimed to determine the relationship between talin-C and HIV infection and identify the mechanisms\u0000underlying the ability of this protein to influence HIV infection.\u0000\u0000\u0000\u0000 PBMCs were derived from HIV-infected patients enrolled in this study. N- and C-terminal peptides matching the\u0000potential sequence of talin-C were detected in PBMCs by multiple reaction monitoring (MRM) mass spectrometry. TZM-b1\u0000cells were infected with HIV-1 pseudotyped virus (HIVpp) for different durations to detect the talin-C product. Three stable\u0000cell lines overexpressing talin head (TLN1-H) or TLN1-C or with TLN1 knockdown (shTLN1) were created and infected by\u0000HIVpp. The HIV marker protein (P24) was then detected by enzyme-linked immunosorbent assay. Finally, an isobaric tag\u0000for relative and absolute quantification (iTRAQ)-based proteomic study was performed to detect the TLN1-C-regulated proteins with or without HIVpp infection in TZM-bl cells. The identified proteins were analyzed by R version 4.0.2, and\u0000STRING software (Version: 11.0) (https://string-db.org).\u0000\u0000\u0000\u0000N- and C-peptides of talin-C were detected to have higher expression in patients with lower HIV load. Talin-C was\u0000produced during HIVpp infection. TLN1-C significantly inhibited HIVpp infection in the TZM-b1 cells. Additionally, a proteomic study found that TLN1-C regulated the expression of 99 proteins in TZM-b1 cells without and with HIVpp infection,\u0000respectively. According to Gene Ontology (GO) annotation, proteins with cellular metabolic process and binding function\u0000were found to be enriched. Thirty four proteins have protein-protein interaction, including 19 down- and 15 up- regulated\u0000proteins, respectively.\u0000\u0000\u0000\u0000Talin-C was produced following HIV infection, and is inversely proportional to HIV load. A proteomic study\u0000indicated that TLN1-C might be involved in HIV infection through regulating metabolic processes.\u0000","PeriodicalId":50601,"journal":{"name":"Current Proteomics","volume":null,"pages":null},"PeriodicalIF":0.8,"publicationDate":"2020-12-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"80337495","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Proteomic analysis of aqueous humor proteins associated with neovascular glaucoma secondary to proliferative diabetic retinopathy","authors":"Ying Wang, Shao-lin Xu, Junyi Li, Fujie Yuan, Yue Chen, Kelin Liu","doi":"10.2174/1570164618999201210224640","DOIUrl":"https://doi.org/10.2174/1570164618999201210224640","url":null,"abstract":"\u0000\u0000Extensive retinal ischemia caused by proliferative diabetic retinopathy (PDR) may develop into neo-vascular glaucoma (NVG). We searched for the proteins which might participate in neovascularization through the analysis of aqueous humor (AH) proteomics in patients with NVG secondary to PDR to increasing the understanding of the possible mechanism of neovascularization.\u0000\u0000\u0000\u0000We collected 12 samples (group A) of AH from patients with NVG secondary to PDR as the experimental group and 7 samples (group B) of AH from patients with primary acute angle-closure glaucoma (PAACG) & diabetes mellitus without diabetic retinopathy (NDR) as the control group. Differential quantitative proteome analysis of the aqueous humor samples was performed based on data-independent acquisition (DIA) method. The differentially expressed proteins were functionally annotated by Ingenuity Pathway Analysis (IPA). The important differentially expressed proteins were validated in another group (group A: 5 samples and group B: 5 samples) by parallel reaction monitor (PRM) approach .\u0000\u0000\u0000\u0000A total of 636 AH proteins were identified, and 82 proteins were differentially expressed between two groups. Functional annotation showed that the differentially expressed proteins were mainly associated with angiogenesis and cell migration. Signaling pathways analysis showed that the proteins up-regulated in group A were mainly related to Liver X re-ceptor/Retinoid X receptor (LXR/RXR) activation and acute reaction.\u0000\u0000\u0000\u0000This study presented a pilot work related to NVG secondary to PDR, which provided a better understanding of the mechanisms governing the pathophysiology of NVG.\u0000","PeriodicalId":50601,"journal":{"name":"Current Proteomics","volume":null,"pages":null},"PeriodicalIF":0.8,"publicationDate":"2020-12-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"90355930","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"A Useful Tool for the Identification of DNA-binding Proteins Using Graph Convolutional Network","authors":"Dasheng Chen, Leyi Wei","doi":"10.2174/1570164618999201210225354","DOIUrl":"https://doi.org/10.2174/1570164618999201210225354","url":null,"abstract":"\u0000\u0000Both DNAs and proteins are important components of living organisms. DNA-binding proteins are\u0000a kind of helicase, which is a protein specifically responsible for binding to DNA single stranded regions. It plays a key role\u0000in the function of various biomolecules. Although there are some prediction methods for the DNA-binding proteins sequences,\u0000the use of graph neural networks in this research is still limited.\u0000\u0000\u0000\u0000In this article, using graph neural networks, we developed a novel predictor GCN-DBP for protein classification\u0000prediction.\u0000\u0000\u0000\u0000Each protein sequence is treated as a document in this study, and then document is segmented according to the\u0000concept of k-mer. This research aims to use document word relationships and word co-occurrence as a corpus to construct a\u0000text graph. Then, the predictor learns protein sequence information by two-layer graph convolutional networks.\u0000\u0000\u0000\u0000In order to compare the proposed method with other four existing methods, we have conducted more experiments.\u0000Finally, we tested GCN-DBP on the independent data set PDB2272. Its accuracy reached 64.17% and MCC reached\u000028.32%.\u0000\u0000\u0000\u0000The results show that the proposed method is superior to the other four methods and will be a useful tool for\u0000protein classification.\u0000","PeriodicalId":50601,"journal":{"name":"Current Proteomics","volume":null,"pages":null},"PeriodicalIF":0.8,"publicationDate":"2020-12-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"89400245","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"A Combined Method of Protein Extraction from Unorthodox Plant Samples for Proteomics","authors":"C. Yılmaz, M. Işcan","doi":"10.2174/1570164618999201209221340","DOIUrl":"https://doi.org/10.2174/1570164618999201209221340","url":null,"abstract":"\u0000\u0000This study aimed to generate an improved method of protein extraction and purification from plant tissues\u0000containing very high amounts of phenolic compounds and other interfering biomolecules.\u0000\u0000\u0000\u0000Protein extraction at proteomic studies on some plant species including conifers is challenging and the yield\u0000and quality is unpredictable.\u0000\u0000\u0000\u0000Two popular protocols were combined with each other to construct a novel one with enhanced abilities to\u0000produce higher purity of samples compatible for high precision molecular systems and analysis.\u0000\u0000\u0000\u0000The new method was compared with the other two for their efficiencies in classical SDS-PAGE, 2-DE and\u0000capillary chromatography applications.\u0000\u0000\u0000\u0000All three methods were comparable in SDS-PAGE procedure; however, only the new method created acceptable\u0000gel images in 2-DE. Bioanalyzer results, also, demonstrated that the new method provided protein samples pure enough to\u0000be used in capillary chromatography with 2 times more peaks in electropherograms with lower noise and higher total\u0000relative protein concentrations closest to the applied amount.\u0000\u0000\u0000\u0000The new combined method is a successful alternative for plant proteomicists with higher yield and quality of\u0000proteins from recalcitrant tissues.\u0000\u0000\u0000\u0000The new method could be preferred, especially, for high-tech, sensitive proteomic analysis.\u0000","PeriodicalId":50601,"journal":{"name":"Current Proteomics","volume":null,"pages":null},"PeriodicalIF":0.8,"publicationDate":"2020-12-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"78472972","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Meet Our Editorial Board Members","authors":"N. B. Maheswarappa","doi":"10.2174/157016461801201204091436","DOIUrl":"https://doi.org/10.2174/157016461801201204091436","url":null,"abstract":"","PeriodicalId":50601,"journal":{"name":"Current Proteomics","volume":null,"pages":null},"PeriodicalIF":0.8,"publicationDate":"2020-12-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"82591627","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Proteomic Analysis of Intra- and Extracellular Proteins of Aspergillus niveus during Submerged Bioprocess Culturing under Different pH Conditions","authors":"J. A. Leite, Nathália Gonsales da Rosa-Garzon, H. Laure, J. Rosa, O. Franco, Cristina Maria de Souza Motta, H. Cabral","doi":"10.2174/1570164617999201202120657","DOIUrl":"https://doi.org/10.2174/1570164617999201202120657","url":null,"abstract":"\u0000\u0000 Proteomics facilitates understanding of the complexity of molecular and physiological mechanisms\u0000involved in the metabolic and biological fungal adaptations to pH changes. Proteomics enables the identification of enzymes\u0000and fungal proteins involved in these adaptations. This approach may be used to investigate such fungi as Aspergillus niveus, whose proteome has not yet been analyzed, changes the intra- and extracellular protein profiles in response to extracellular pH.\u0000\u0000\u0000\u0000 In the current study, we used two-dimensional gel electrophoresis (2DE) and mass spectrometry to evaluate the\u0000response of A. niveus to grow at pH 5, 6, 7, and 8 for 96 hours submerged bioprocess culturing.\u0000\u0000\u0000\u0000 This study evaluated the response of A. niveus to grow at pH 5, 6, 7, and 8 for 96 h submerged bioprocess culturing, by analysis of two-dimensional gel electrophoresis (2DE), of the intracellular proteomes and the secretome, protein\u0000spots of interest were submitted to tryptic digestion and analyzed by matrix-assisted laser desorption/ionization time-offlight tandem mass spectrometry (MALDI-TOF/TOF-MS).\u0000\u0000\u0000\u0000 This approach revealed substantial differences between the functions of intra- and extracellular proteins of A. niveus. The data suggested that pH-modulated global proteins are involved in important, mainly metabolic, processes, in the\u0000pentose phosphate pathway, protein regulation, cell wall maintenance, and others. Moreover, the change in extracellular pH\u0000could have altered the availability of nutrients, and induced the production of enzymes that respond to oxidative and other\u0000stresses.\u0000\u0000\u0000\u0000 Proteomic facilitates understanding of the complexity of molecular and physiological mechanisms involved in\u0000the metabolic and biological adaptations of fungi to pH changes.\u0000","PeriodicalId":50601,"journal":{"name":"Current Proteomics","volume":null,"pages":null},"PeriodicalIF":0.8,"publicationDate":"2020-12-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"85311137","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"A bottom-up proteomic approach in bone marrow plasma cells of newly diagnosed multiple myeloma patients","authors":"B. Ayhan, S. Turan, N. Barkan, K. Dalva, M. Beksaç, D. Demiralp","doi":"10.2174/1570164617999201124142232","DOIUrl":"https://doi.org/10.2174/1570164617999201124142232","url":null,"abstract":"\u0000\u0000 Multiple myeloma (MM) is characterized by infiltration of bone marrow (BM) with clonal malignant\u0000plasma cells. The percentage of plasma cells in the BM is required for both diagnosis and prognosis.\u0000\u0000\u0000\u0000Intracellular protein screening and quantitative proteomic analysis was performed in myeloma plasma cells with\u0000an aim to compare expressions between low (0-9%), intermediate (10-20%) and high (>20%) plasma cell infiltration groups.\u0000\u0000\u0000\u0000BM aspiration samples were collected from newly diagnosed untreated patients with MM. The samples\u0000were pooled into three groups according to the plasma cell content (PCC) in the BM: group 1 (0-9%),\u0000group 2 (10-20%) and group 3 (>20%). Protein profiles were obtained and proteins were identified by peptide mass\u0000fingerprinting analysis.\u0000\u0000\u0000\u0000 Differentially expressed proteins were detected between all groups. The identified proteins are Endoplasmin, Calreticulin,\u0000Protein Disulfide-isomerase, Marginal zone B and B1 cell specific protein/pERp1, Actin cytoplasmic 1, Myeloblastin,\u0000Thioredoxin domain-containing protein 5, Ig kappa chain C region, Apoptosis regulator B-cell lymphoma 2 and Peroxiredoxin-\u00004.\u0000\u0000\u0000\u0000Proteins involved in cell proliferation, apoptosis, redox homeostasis and unfolded protein disposal through endoplasmic\u0000reticulum-associated degradation machinery has been found to be correlated to PCC. Our results confirm earlier\u0000reports in regards to the potential effects of identified proteins in the major signaling pathways that lead to cancer. Moreover,\u0000this study reveals a novel association between PCC levels and MM. It further highlights the roles of Marginal zone B\u0000and B1 cell specific proteins in MM, which could be used as candidate biomarkers in future studies.\u0000","PeriodicalId":50601,"journal":{"name":"Current Proteomics","volume":null,"pages":null},"PeriodicalIF":0.8,"publicationDate":"2020-11-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"89420017","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Identifying protein subcellular location with embedding features learned from networks","authors":"Hongwei Liu, Bin Hu, Lei Chen, Lin Lu","doi":"10.2174/1570164617999201124142950","DOIUrl":"https://doi.org/10.2174/1570164617999201124142950","url":null,"abstract":"\u0000\u0000Identification of protein subcellular location is an important problem because the subcellular location\u0000is highly related to protein function. It is fundamental to determine the locations with biology experiments. However,\u0000these experiments are of high costs and time-consuming. The alternative way to address such problem is to design effective\u0000computational methods.\u0000\u0000\u0000\u0000To date, several computational methods have been proposed in this regard. However, these methods mainly\u0000adopted the features derived from proteins themselves. On the other hand, with the development of network technique, several\u0000embedding algorithms have been proposed, which can encode nodes in the network into feature vectors. Such algorithms\u0000connected the network and traditional classification algorithms. Thus, they provided a new way to construct models\u0000for the prediction of protein subcellular location.\u0000\u0000\u0000\u0000 In this study, we analyzed features produced by three network embedding algorithms (DeepWalk, Node2vec and\u0000Mashup) that were applied on one or multiple protein networks. Obtained features were learned by one machine learning algorithm\u0000(support vector machine or random forest) to construct the model. The cross-validation method was adopted to\u0000evaluate all constructed models.\u0000\u0000\u0000\u0000After evaluating models with the cross-validation method, embedding features yielded by Mashup on multiple networks\u0000were quite informative for predicting protein subcellular location. The model based on these features were superior to\u0000some classic models.\u0000\u0000\u0000\u0000 Embedding features yielded by a proper and powerful network embedding algorithm were effective for building\u0000the model for prediction of protein subcellular location, providing new pipelines to build more efficient models.\u0000","PeriodicalId":50601,"journal":{"name":"Current Proteomics","volume":null,"pages":null},"PeriodicalIF":0.8,"publicationDate":"2020-11-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"73451117","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}