Synthetic biology (Oxford, England)最新文献_第8页

Speaking to nature: a deep learning representational model of proteins ushers in protein linguistics. 与自然对话:蛋白质的深度学习表征模型引入了蛋白质语言学。

Synthetic biology (Oxford, England) Pub Date : 2019-05-21 eCollection Date: 2019-01-01 DOI: 10.1093/synbio/ysz013

Daniel Bojar

{"title":"Speaking to nature: a deep learning representational model of proteins ushers in protein linguistics.","authors":"Daniel Bojar","doi":"10.1093/synbio/ysz013","DOIUrl":"https://doi.org/10.1093/synbio/ysz013","url":null,"abstract":"Understanding, modifying and designing proteins require an intimate knowledge of their 3D structure. Even structure-agnostic protein engineering approaches, such as directed evolution, are limited in scope because of the vast potential sequence space and the epistatic effects that multiple mutations have on protein function. To overcome these difficulties, a holistic understanding of sequence–structure–function relationships has to be established. In their recent preprint, members of the Church Group at the Wyss Institute and collaborators describe a novel approach to predicting protein stability and functionality from raw sequence (1). Their representational model UniRep (unified representation), for the first time, demonstrates an advanced understanding of protein features by means of language modeling. Using deep learning techniques, which were recently recognized with the prestigious Turing Award, Alley et al. built a language model for proteins with amino acids as characters based on natural language processing (NLP) techniques. NLP has not only revolutionized our computational understanding of language—think for instance voice-to-text software—but has been coopted for exciting applications in synthetic biology. The recurrent neural network (RNN; a type of neural network which can process sequential inputs such as text) used by Alley et al. was trained by iteratively predicting the next amino acid given the preceding amino acids for the 24 million protein sequences contained in the UniRef50 database. The RNN thus gathered implicit knowledge about the context of a given amino acid and higher-level features such as secondary structure. The authors then averaged the protein representation of their RNN at every sequence position to yield a protein language representation they call UniRep. They then extended UniRep by adding representations of the final sequence position of their RNN to generate the more complete representation called ‘UniRep Fusion’, which serves as an overview of the entire protein sequence. UniRep Fusion was then used as an input for a machine learning model to predict protein stability. Notably, this architecture was more accurate than Rosetta, the de facto state-ofthe-art for predicting protein stability. Their protein language representation allowed the authors to predict the relative brightness of 64 800 GFP mutants differing in as few as one amino acids. Remarkably, their predicted relative brightness values correlated strongly with experimental observation (r1⁄4 0.98). UniRep, as the representation of 24 million proteins, captures many phenomena of general importance for protein structure and function. These general features can be complemented by dataset-specific attributes when training on a subset of protein mutants or de novo designed proteins. This approach could for instance be adopted for screening novel proteins generated by deep learning models. Analogous to de novo designed proteins by Rosetta, generating prote","PeriodicalId":74902,"journal":{"name":"Synthetic biology (Oxford, England)","volume":"4 1","pages":"ysz013"},"PeriodicalIF":0.0,"publicationDate":"2019-05-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1093/synbio/ysz013","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"38439143","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Turning G protein-coupled receptors into tunable biosensors. 将G蛋白偶联受体转化为可调生物传感器。

Synthetic biology (Oxford, England) Pub Date : 2019-05-21 eCollection Date: 2019-01-01 DOI: 10.1093/synbio/ysz011

Konstantinos Vavitsas

{"title":"Turning G protein-coupled receptors into tunable biosensors.","authors":"Konstantinos Vavitsas","doi":"10.1093/synbio/ysz011","DOIUrl":"https://doi.org/10.1093/synbio/ysz011","url":null,"abstract":"In 2012, the Nobel prize in Chemistry was awarded to Robert Lefkowitz and Brian Kobilka for their work in understanding the structure and function of G protein-coupled receptors (GPCRs), one of the largest families of signaling proteins. GPCRs are notoriously difficult to work with (due to their many transmembrane domains) and they operate in a complex way, interacting with several compounds and many internal metabolic pathways. What is more, GPCRs are present in most lifeforms and have an important role in many vital signaling processes. They therefore seem like a very unlikely choice for a biosensor. However, William Shaw and his colleagues proved otherwise in their recent article published in Cell (1). The research group from Imperial College, UK, heavily modified the yeast Saccharomyces cerevisiae to obtain a platform for their biosensors. A sensor can be roughly divided into three parts: the detector, the signal transduction/translation component and the reporter. The idea was to create a modular system where GPCRs act as plug-ins dedicated to a compound, while the signal transduction and reporting mechanism will remain the same. S. cerevisiae already contains a signaling pathway with its own self-regulation, the MAP kinase cascade, that can be used to translate a GPCR signal to a linear and graded translational response. Using CRISPR-mediated editing the researchers modified 18 genetic loci and removed the rest of the GPCRrelated genes, generating a ‘clean’ environment without crosspathway interactions. In theory, the derived strain can heterologously express a GPCR that recognizes any compound, and receptor activation will stimulate the same pathway and the same reporting event. Shaw and colleagues modified components of the GPCR receptor and measured the impact on its biosensor properties: the detection threshold, the saturation point and the linearity of response. The experiments took place using the yeast mating pheromone response pathway, where the presence of a-Factor pheromone stimulates a transcriptional response (2). By varying the expression levels of the GPCR components, using different promoters, the researchers showed that it is possible to titrate the signal response, generate a mathematical model with robust predictions and tune the receptor and reporter to function in a certain operational range. To alter the linearity of response—whether the sensor operates in a linear manner or as an on-off switch—the researchers employed microbial consortia with differently tuned strains. This was displayed in two different scenarios. In the first instance, the presence of melatonin in the media was quantified. The researchers employed two strains with different sensitivities to melatonin, thus increasing the operational range. In the second instance, the presence of the pathogenic fungus Paracoccidioides brasiliensis was detected in a yes/no manner. The two cell types used here had different functions: one detected the fungus and release","PeriodicalId":74902,"journal":{"name":"Synthetic biology (Oxford, England)","volume":"4 1","pages":"ysz011"},"PeriodicalIF":0.0,"publicationDate":"2019-05-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1093/synbio/ysz011","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"38439142","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 4

Principles of synthetic biology: a MOOC for an emerging field. 合成生物学原理:面向新兴领域的MOOC。

Synthetic biology (Oxford, England) Pub Date : 2019-05-10 eCollection Date: 2019-01-01 DOI: 10.1093/synbio/ysz010

Daniel A Anderson, Ross D Jones, Adam P Arkin, Ron Weiss

引用次数: 9

Erratum: New adaptive laboratory evolution database highlights the need for consolidating directed evolution data. 勘误:新的适应实验室进化数据库强调需要巩固定向进化数据。

Synthetic biology (Oxford, England) Pub Date : 2019-03-25 eCollection Date: 2019-01-01 DOI: 10.1093/synbio/ysz009

Bojar Daniel

引用次数: 0

Marionette strains aim to make refining metabolic pathways faster and easier. 木偶菌株旨在使精炼代谢途径更快、更容易。

Synthetic biology (Oxford, England) Pub Date : 2019-02-04 eCollection Date: 2019-01-01 DOI: 10.1093/synbio/ysz007

William G Alexander

{"title":"Marionette strains aim to make refining metabolic pathways faster and easier.","authors":"William G Alexander","doi":"10.1093/synbio/ysz007","DOIUrl":"https://doi.org/10.1093/synbio/ysz007","url":null,"abstract":"The Voigt lab at The Massachusetts Institute of Technology recently reported the optimization of 12 transcription factor sensors and their integration into a series of E. coli strains, collectively referred to as the Marionette strains (1). While transcription factors that can be controlled with small molecules are not new (the lactose and tetracycline inducible systems have been around for decades), synthetic biologists are limited to using only a few simultaneously in a cell due to issues such as unintended activation by cognate or non-cognate molecules, cross-interactions with the other sensors, and ‘leakiness’, or low-level transcription in the absence of the activating molecule. Previously, the maximum number of transcription factor sensors used simultaneously in a cell was four. The Marionette strains could make optimizing heterologous metabolic pathways faster and easier by expanding the design space for complex genetic circuits. The Voigt lab used directed evolution to find variants of sensors with high specificity, low leakiness and greater activation ranges (in other words the difference between the ‘off’ and ‘on’ states). A dual selection system was designed: a negativeselection marker (the promiscuous PheS allele) would kill cells with sensor variants that had leaky expression or were reactive with unintended small molecules, while positive selection to find highly sensitive and specific variants was achieved by the expression of a DNA polymerase (DNAP) and subsequent emulsified polymerase chain reaction. The emulsification isolates the sensors, and those responsible for the highest levels of expression are amplified more strongly. In addition, the DNAP used in the positive selection could be alternated between a stringent or error-prone polymerase in order to produce and control the diversity on which the selections would act, and these mutagenized sequences would be incorporated into the next round of selections. To demonstrate the utility of a Marionette strain in tuning the expression of a metabolic pathway, the lycopene synthesis pathway was used as a model (2). The five genes in the lycopene synthesis pathway were placed under the control of five different sensors, and three levels (zero, maximum and 50% maximum) of each inducer were added to the culture resulting in 243 combinations. Lycopene concentrations were measured for all 243 combinations, and new minima, maxima and midpoints were derived for each of the five transcription factors. The experiment was repeated this way for a total of four iterations, resulting in a maximum lycopene titer of 90 mg/l. To equal the design space explored in the Marionette lycopene optimization example (243 combinations screened four times), you would have to synthesize 972 constructs. Synthesizing these 972 constructs (7 Mb total), would cost $700 000 (assuming $0.10/base), not to mention the enzyme and labor costs to clone all of those variants, the lost time due to human error, unforeseen i","PeriodicalId":74902,"journal":{"name":"Synthetic biology (Oxford, England)","volume":"4 1","pages":"ysz007"},"PeriodicalIF":0.0,"publicationDate":"2019-02-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1093/synbio/ysz007","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"38439140","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

New adaptive laboratory evolution database highlights the need for consolidating directed evolution data. 新的自适应实验室进化数据库强调了整合定向进化数据的需求。

Synthetic biology (Oxford, England) Pub Date : 2019-02-04 eCollection Date: 2019-01-01 DOI: 10.1093/synbio/ysz004

Daniel Bojar

{"title":"New adaptive laboratory evolution database highlights the need for consolidating directed evolution data.","authors":"Daniel Bojar","doi":"10.1093/synbio/ysz004","DOIUrl":"https://doi.org/10.1093/synbio/ysz004","url":null,"abstract":"Directed evolution, honored by the 2018 chemistry Nobel prize, uses mutagenesis and selective pressure to drive proteins towards the development of new and improved functionalities. A closely related approach, known as Adaptive Laboratory Evolution (ALE) applies similar principles to optimize whole strains for desired growth conditions. While these approaches have resulted in considerable advances in the realms of enzyme and strain optimization, they remain isolated endeavors. A new resource, the Adaptive Laboratory Evolution Database (ALEdb), is a first step towards concentrating efforts to harness the power of evolution for new and improved phenotypes. In ALE experiments, organisms such as Escherichia coli or Saccharomyces cerevisiae are grown for extended periods of time under specified culture conditions to enable the acquisition of advantageous or adaptive mutations. Developed as a web-based platform hosted by the University of California, San Diego, ALEdb was launched with over 11 000 mutations and the corresponding culture conditions gathered from 11 publications and is built to be expanded by further studies. The mutations stored at ALEdb are characterized by the genome position, the affected gene, the type of mutation, and the cell culture conditions used in the ALE experiment. Data from different studies can be exported and analyzed from ALEdb by data mining for trends or patterns in mutations to generalize and advance the pursuit of improved and novel functionalities. Additionally, ALEdb serves as a knowledge database where scientists can functionally characterize new mutations discovered by comparing them to records stored in ALEdb. To showcase the utility of ALEdb, the authors investigated mutation type distributions from already cataloged studies. Single nucleotide polymorphisms (SNPs) were found to be the most frequent. The authors argue that this trend suggests the importance of SNPs for adaptive evolution, though it is hard to support this claim without taking into account the baseline frequency of different mutation types. In the context of synthetic biology, a concerted database of adaptive mutations like ALEdb could help guide the rational design of new and improved functionalities. However, ALEdb currently catalogs ALE-derived mutations only in naturally occurring genes. Expanding the database to include variations resulting from directed evolution of standard genetic parts that may not be native to the host organism would greatly increase its influence. Additionally, databases such as ALEdb are dependent on continued submissions. Since it was first described in early October, the publication count on ALEdb has expanded from 11 to 33. This early momentum is a promising sign, but it is unclear how the authors envision the assured spread and maintenance of ALEdb. Potential ways forward could include a pledge by journals to require data submission—similar to the way the protein data bank PDB (Protein Data Bank) handles 3D protei","PeriodicalId":74902,"journal":{"name":"Synthetic biology (Oxford, England)","volume":"4 1","pages":"ysz004"},"PeriodicalIF":0.0,"publicationDate":"2019-02-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1093/synbio/ysz004","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"38439137","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 2

Arch enemy no more: designing the first synthetic globular all-beta proteins with beta-arches. 不再是宿敌了:设计出第一个带有-拱门的合成球形全-蛋白。

Synthetic biology (Oxford, England) Pub Date : 2019-02-04 eCollection Date: 2019-01-01 DOI: 10.1093/synbio/ysz002

Daniel Bojar

{"title":"Arch enemy no more: designing the first synthetic globular all-beta proteins with beta-arches.","authors":"Daniel Bojar","doi":"10.1093/synbio/ysz002","DOIUrl":"https://doi.org/10.1093/synbio/ysz002","url":null,"abstract":"De novo protein design, taking its first steps at the turn of the century (1), aims to create novel proteins without an existing protein scaffold wholly from foundational structural principles and simulations. These designed proteins often have sequences and functions that are unlike anything found in nature and can even exhibit completely novel protein folds. The wholesale design of new proteins thus requires an exquisite understanding of their 3D structure. Thanks to their modular properties, proteins consisting solely of alpha-helices were the first to yield to protein design de novo. In a recent publication in the journal Nature Structural & Molecular Biology, David Baker’s team at the University of Washington made a foray into uncharted territory and for the first time succeeded in designing a globular all-beta protein de novo (2). To understand their success, it is paramount to understand why it is so difficult to design globular proteins consisting only of beta-sheets. In contrast to amino acid residues in alphahelices, which establish most of their contacts with residues nearby, residues in beta-sheets frequently interact with residues that are farther apart on the sequence, making them harder to design. For example, beta-arches are loops that connect two beta-strands that do not form a continuous beta-sheet. In this publication, the authors discovered and utilized structural principles of all-beta proteins to facilitate their design process. These principles for instance constrained the geometry of beta-arches by assigning amino acid frequencies as well as the orientation of their side chains to specific types of beta-arches. Led by researchers Enrique Marcos and Tamuka M. Chidyausiku, the team used the protein modeling software Rosetta to construct candidates for globular all-beta proteins with differing lengths of beta-strands and beta-arches. Choosing 19 of these final jellyroll protein structure candidates consisting of eight antiparallel beta-strands for experimental characterization, they recombinantly expressed them in E. coli. Obtaining an nuclear magnetic resonance (NMR) spectroscopy structure of one of these expressed designer proteins, the authors could demonstrate that the actual protein structure closely resembled their de novo design. While proteins consisting of beta-strands connected by tight loops (effectively forming a flowing carpet of paired beta-strands) have been attempted before, the de novo design of beta-arches is definitely a novelty. This characteristic allows all-beta proteins to fold into globular proteins, in contrast to the previous elongated designs, and is needed for complex proteins such as antibodies. Why is all of this important? In addition to a profound conceptual leap in our ability to design proteins de novo, this work furthers our structural understanding of all-beta proteins. Many important proteins, such as the nucleosome-chaperone nucleoplasmin and many viral capsid proteins, contain jellyroll ","PeriodicalId":74902,"journal":{"name":"Synthetic biology (Oxford, England)","volume":"4 1","pages":"ysz002"},"PeriodicalIF":0.0,"publicationDate":"2019-02-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1093/synbio/ysz002","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"38537364","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Developing a graduate training program in Synthetic Biology: SynBioCDT. 开发合成生物学研究生培训计划:SynBioCDT。

Synthetic biology (Oxford, England) Pub Date : 2019-01-30 eCollection Date: 2019-01-01 DOI: 10.1093/synbio/ysz006

Idil Cazimoglu, Alexander P S Darlington, Aurelija Grigonyte, Charlotte E G Hoskin, Juntai Liu, Robert Oppenheimer, Jesús A Siller-Farfán, Claire Grierson, Antonis Papachristodoulou

引用次数: 3

An educational module to explore CRISPR technologies with a cell-free transcription-translation system. 一个教育模块，探索CRISPR技术与无细胞转录翻译系统。

Synthetic biology (Oxford, England) Pub Date : 2019-01-21 eCollection Date: 2019-01-01 DOI: 10.1093/synbio/ysz005

Daphne Collias, Ryan Marshall, Scott P Collins, Chase L Beisel, Vincent Noireaux

{"title":"An educational module to explore CRISPR technologies with a cell-free transcription-translation system.","authors":"Daphne Collias, Ryan Marshall, Scott P Collins, Chase L Beisel, Vincent Noireaux","doi":"10.1093/synbio/ysz005","DOIUrl":"https://doi.org/10.1093/synbio/ysz005","url":null,"abstract":"Within the last 6 years, CRISPR-Cas systems have transitioned from adaptive defense systems in bacteria and archaea to revolutionary genome-editing tools. The resulting CRISPR technologies have driven innovations for treating genetic diseases and eradicating human pests while raising societal questions about gene editing in human germline cells as well as crop plants. Bringing CRISPR into the classroom therefore offers a means to expose students to cutting edge technologies and to promote discussions about ethical questions at the intersection of science and society. However, working with these technologies in a classroom setting has been difficult because typical experiments rely on cellular systems such as bacteria or mammalian cells. We recently reported the use of an E. coli cell-free transcription-translation (TXTL) system that simplifies the demonstration and testing of CRISPR technologies with shorter experiments and limited equipment. Here, we describe three educational modules intended to expose undergraduate students to CRISPR technologies using TXTL. The three sequential modules comprise (i) designing the RNAs that guide DNA targeting, (ii) measuring DNA cleavage activity in TXTL and (iii) testing how mutations to the targeting sequence or RNA backbone impact DNA binding and cleavage. The modules include detailed protocols, questions for group discussions or individual evaluation, and lecture slides to introduce CRISPR and TXTL. We expect these modules to allow students to experience the power and promise of CRISPR technologies in the classroom and to engage with their instructor and peers about the opportunities and potential risks for society.","PeriodicalId":74902,"journal":{"name":"Synthetic biology (Oxford, England)","volume":"4 1","pages":"ysz005"},"PeriodicalIF":0.0,"publicationDate":"2019-01-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1093/synbio/ysz005","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"38439138","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 24

Expanding the toolbox of synthetic riboswitches with guanine-dependent aptazymes. 用鸟嘌呤依赖性适配酶扩展合成核糖开关工具箱。

Synthetic biology (Oxford, England) Pub Date : 2019-01-12 eCollection Date: 2019-01-01 DOI: 10.1093/synbio/ysy022

Julia Stifel, Maike Spöring, Jörg Steffen Hartig

{"title":"Expanding the toolbox of synthetic riboswitches with guanine-dependent aptazymes.","authors":"Julia Stifel, Maike Spöring, Jörg Steffen Hartig","doi":"10.1093/synbio/ysy022","DOIUrl":"https://doi.org/10.1093/synbio/ysy022","url":null,"abstract":"Artificial riboswitches based on ribozymes serve as versatile tools for ligand-dependent gene expression regulation. Advantages of these so-called aptazymes are their modular architecture and the comparably little coding space they require. A variety of aptamer-ribozyme combinations were constructed in the past 20 years and the resulting aptazymes were applied in diverse contexts in prokaryotic and eukaryotic systems. Most in vivo functional aptazymes are OFF-switches, while ON-switches are more advantageous regarding potential applications in e.g. gene therapy vectors. We developed new ON-switching aptazymes in the model organism Escherichia coli and in mammalian cell culture using the intensely studied guanine-sensing xpt aptamer. Utilizing a high-throughput screening based on fluorescence-activated cell sorting in bacteria we identified up to 9.2-fold ON-switches and OFF-switches with a dynamic range up to 32.7-fold. For constructing ON-switches in HeLa cells, we used a rational design approach based on existing tetracycline-sensitive ON-switches. We discovered that communication modules responding to tetracycline are also functional in the context of guanine aptazymes, demonstrating a high degree of modularity. Here, guanine-responsive ON-switches with a four-fold dynamic range were designed. Summarizing, we introduce a series of novel guanine-dependent ribozyme switches operative in bacteria and human cell culture that significantly broaden the existing toolbox.","PeriodicalId":74902,"journal":{"name":"Synthetic biology (Oxford, England)","volume":"4 1","pages":"ysy022"},"PeriodicalIF":0.0,"publicationDate":"2019-01-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1093/synbio/ysy022","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"38537362","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 21