iMeta最新文献

{"title":"A comprehensive atlas of endogenous peptides in maize","authors":"Usman Ali,&nbsp;Lei Tian,&nbsp;Ruihong Tang,&nbsp;Shunxi Wang,&nbsp;Weiwei Luo,&nbsp;Shanshan Liu,&nbsp;Jinghua Zhang,&nbsp;Liuji Wu","doi":"10.1002/imt2.247","DOIUrl":"10.1002/imt2.247","url":null,"abstract":"<p>In this study, we present a comprehensive peptidomic atlas of 13 maize tissues, covering both vegetative and reproductive phases. Using a three-frame translation of canonical coding sequences, we identified 6100 nonredundant endogenous peptides, significantly expanding the known plant peptide repertoire. By integrating peptidomic coexpression profiles with previously reported proteomic profiles, we found that the peptide abundance did not consistently correlate with the abundance of their source proteins, suggesting the presence of complex regulatory mechanisms. This integrated peptidomic and proteomic map can serve as a valuable resource for exploring the functional roles of endogenous peptides in maize development and facilitates the investigation of the functional relationship among genes, peptides, and proteins across various biological contexts.\u0000 <figure>\u0000 <div><picture>\u0000 <source></source></picture><p></p>\u0000 </div>\u0000 </figure></p>","PeriodicalId":73342,"journal":{"name":"iMeta","volume":"3 6","pages":""},"PeriodicalIF":23.7,"publicationDate":"2024-11-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11683474/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142916078","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}

{"title":"MetOrigin 2.0: Advancing the discovery of microbial metabolites and their origins","authors":"Gang Yu,&nbsp;Cuifang Xu,&nbsp;Xiaoyan Wang,&nbsp;Feng Ju,&nbsp;Junfen Fu,&nbsp;Yan Ni","doi":"10.1002/imt2.246","DOIUrl":"10.1002/imt2.246","url":null,"abstract":"<p>First introduced in 2021, MetOrigin has quickly established itself as a powerful web server to distinguish microbial metabolites and identify the bacteria responsible for specific metabolic processes. Building on the growing understanding of the interplay between the microbiome and metabolome, and in response to user feedback, MetOrigin has undergone a significant upgrade to version 2.0. This enhanced version incorporates three new modules: (1) Quick search module that facilitates the rapid identification of bacteria associated with a particular metabolite; (2) Orthology analysis module that links metabolic enzyme genes with their corresponding bacteria; (3) Mediation analysis module that investigates potential causal relationships among bacteria, metabolites, and phenotypes, highlighting the mediating role of metabolites. Additionally, the backend MetOrigin database has been updated with the latest data from seven public databases (KEGG, HMDB, BIGG, ChEBI, FoodDB, Drugbank, and T3DB), with expanded coverage of 210,732 metabolites, each linked to its source organism. MetOrigin 2.0 is freely accessible at http://metorigin.met-bioinformatics.cn.</p>","PeriodicalId":73342,"journal":{"name":"iMeta","volume":"3 6","pages":""},"PeriodicalIF":23.7,"publicationDate":"2024-11-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11683456/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142916342","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}

{"title":"The crop mined phosphorus nutrition via modifying root traits and rhizosphere micro-food web to meet the increased growth demand under elevated CO2","authors":"Na Zhou,&nbsp;Xue Han,&nbsp;Ning Hu,&nbsp;Shuo Han,&nbsp;Meng Yuan,&nbsp;Zhongfang Li,&nbsp;Sujuan Wang,&nbsp;Yingchun Li,&nbsp;Hongbo Li,&nbsp;Zed Rengel,&nbsp;Yuji Jiang,&nbsp;Yilai Lou","doi":"10.1002/imt2.245","DOIUrl":"10.1002/imt2.245","url":null,"abstract":"<p>Elevated CO₂ (eCO₂) stimulates productivity and nutrient demand of crops. Thus, comprehensively understanding the crop phosphorus (P) acquisition strategy is critical for sustaining agriculture to combat climate changes. Here, wheat (<i>Triticum aestivum</i> L) was planted in field in the eCO₂ (550 µmol mol⁻¹) and ambient CO₂ (aCO₂, 415 µmol mol⁻¹) environments. We assessed the soil P fractions, root morphological and physiological traits and multitrophic microbiota [including arbuscular mycorrhizal fungi (AMF), alkaline phosphomonoesterase (ALP)-producing bacteria, protozoa, and bacterivorous and fungivorous nematodes] in the rhizosphere and their trophic interactions at jointing stage of wheat. Compared with aCO₂, significant 20.2% higher shoot biomass and 26.8% total P accumulation of wheat occurred under eCO₂. The eCO₂ promoted wheat root length and AMF hyphal biomass, and increased the concentration of organic acid anions and the ALP activity, which was accompanied by significant decreases in calcium-bound inorganic P (Ca-P_i) (by 16.7%) and moderately labile organic P (by 26.5%) and an increase in available P (by 14.4%) in the rhizosphere soil. The eCO₂ also increased the growth of ALP-producing bacteria, protozoa, and bacterivorous and fungivorous nematodes in the rhizosphere, governed their diversity and community composition. In addition, the eCO₂ strengthened the trophic interactions of microbiota in rhizosphere; specifically, the eCO₂ promoted the associations between protozoa and ALP-producing bacteria, between protozoa and AMF, whereas decreased the associations between ALP-producing bacteria and nematodes. Our findings highlighted the important role of root traits and multitrophic interactions among microbiota in modulating crop P-acquisition strategies, which could advance our understanding about optimal P management in agriculture systems under global climate changes.</p>","PeriodicalId":73342,"journal":{"name":"iMeta","volume":"3 6","pages":""},"PeriodicalIF":23.7,"publicationDate":"2024-10-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11683460/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142916408","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}

{"title":"Bioprospecting of culturable marine biofilm bacteria for novel antimicrobial peptides","authors":"Shen Fan,&nbsp;Peng Qin,&nbsp;Jie Lu,&nbsp;Shuaitao Wang,&nbsp;Jie Zhang,&nbsp;Yan Wang,&nbsp;Aifang Cheng,&nbsp;Yan Cao,&nbsp;Wei Ding,&nbsp;Weipeng Zhang","doi":"10.1002/imt2.244","DOIUrl":"10.1002/imt2.244","url":null,"abstract":"<p>Antimicrobial peptides (AMPs) have become a viable source of novel antibiotics that are effective against human pathogenic bacteria. In this study, we construct a bank of culturable marine biofilm bacteria constituting 713 strains and their nearly complete genomes and predict AMPs using ribosome profiling and deep learning. Compared with previous approaches, ribosome profiling has improved the identification and validation of small open reading frames (sORFs) for AMP prediction. Among the 80,430 expressed sORFs, 341 are identified as candidate AMPs with high probability. Most potential AMPs have less than 40% similarity in their amino acid sequence compared to those listed in public databases. Furthermore, these AMPs are associated with bacterial groups that are not previously known to produce AMPs. Therefore, our deep learning model has acquired characteristics of unfamiliar AMPs. Chemical synthesis of 60 potential AMP sequences yields 54 compounds with antimicrobial activity, including potent inhibitory effects on various drug-resistant human pathogens. This study extends the range of AMP compounds by investigating marine biofilm microbiomes using a novel approach, accelerating AMP discovery.</p>","PeriodicalId":73342,"journal":{"name":"iMeta","volume":"3 6","pages":""},"PeriodicalIF":23.7,"publicationDate":"2024-10-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11683478/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142916177","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}

{"title":"Novel microbial modifications of bile acids and their functional implications","authors":"Dan Zheng,&nbsp;Huiheng Zhang,&nbsp;Xiaojiao Zheng,&nbsp;Aihua Zhao,&nbsp;Wei Jia","doi":"10.1002/imt2.243","DOIUrl":"https://doi.org/10.1002/imt2.243","url":null,"abstract":"<p>This review outlines the recent discoveries of bile acids that have undergone novel microbial modifications, highlighting their biological roles and the profound implications for the development of innovative therapeutic strategies. The review aims to provide valuable insights and breakthroughs for future drug candidates in the expanding field of bile acid therapeutics.\u0000 <figure>\u0000 <div><picture>\u0000 <source></source></picture><p></p>\u0000 </div>\u0000 </figure></p>","PeriodicalId":73342,"journal":{"name":"iMeta","volume":"3 5","pages":""},"PeriodicalIF":23.7,"publicationDate":"2024-10-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1002/imt2.243","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142451250","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}

{"title":"The rheumatoid arthritis gut microbial biobank reveals core microbial species that associate and effect on host inflammation and autoimmune responses","authors":"Hao-Jie Huang,&nbsp;Chang Liu,&nbsp;Xin-Wei Sun,&nbsp;Rui-Qi Wei,&nbsp;Ling-Wei Liu,&nbsp;Hao-Yu Chen,&nbsp;Rashidin Abdugheni,&nbsp;Chang-Yu Wang,&nbsp;Xiao-Meng Wang,&nbsp;He Jiang,&nbsp;Han-Yu Niu,&nbsp;Li-Juan Feng,&nbsp;Jia-Hui He,&nbsp;Yu Jiang,&nbsp;Yan Zhao,&nbsp;Yu-Lin Wang,&nbsp;Qiang Shu,&nbsp;Ming-Xia Bi,&nbsp;Lei Zhang,&nbsp;Bin Liu,&nbsp;Shuang-Jiang Liu","doi":"10.1002/imt2.242","DOIUrl":"https://doi.org/10.1002/imt2.242","url":null,"abstract":"<p>Gut microbiota dysbiosis has been implicated in rheumatoid arthritis (RA) and influences disease progression. Although molecular and culture-independent studies revealed RA patients harbored a core microbiome and had characteristic bacterial species, the lack of cultured bacterial strains had limited investigations on their functions. This study aimed to establish an RA-originated gut microbial biobank (RAGMB) that covers and further to correlates and validates core microbial species on clinically used and diagnostic inflammation and immune indices. We obtained 3200 bacterial isolates from fecal samples of 20 RA patients with seven improved and 11 traditional bacterial cultivation methods. These isolates were phylogenetically identified and selected for RAGMB. The RAGMB harbored 601 bacterial strains that represented 280 species (including 43 novel species) of seven bacterial phyla. The RAGMB covered 93.2% at species level of medium- and high-abundant (relative abundances ≥0.2%) RA gut microbes, and included four rare species of the phylum <i>Synergistota</i>. The RA core gut microbiome was defined and composed of 20 bacterial species. Among these, <i>Mediterraneibacter tenuis</i> and <i>Eubacterium rectale</i> were two species that statistically and significantly correlated with clinically used diagnostic indices such as erythrocyte sedimentation rate (ESR) and IL-10. Thus, <i>M. tenuis</i> and <i>E. rectale</i> were selected for experimental validation using DSS-treated and not DSS-treated mice model. Results demonstrated both <i>M. tenuis</i> and <i>E. rectale</i> exacerbated host inflammatory responses, including shortened colon length and increased spleen weight, decreased IL-10 and increased IL-17A levels in plasma. Overall, we established the RAGMB, defined the RA core microbiome, correlated and demonstrated core microbial species effected on host inflammatory and immune responses. This work provides diverse gut microbial resources for future studies on RA etiology and potential new targets for new biomedical practices.</p>","PeriodicalId":73342,"journal":{"name":"iMeta","volume":"3 5","pages":""},"PeriodicalIF":23.7,"publicationDate":"2024-10-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1002/imt2.242","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142449103","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}

{"title":"Akkermansia muciniphila administration ameliorates streptozotocin-induced hyperglycemia and muscle atrophy by promoting IGF2 secretion from mouse intestine","authors":"Chi Zhang,&nbsp;Zhihong Wang,&nbsp;Xu Liu,&nbsp;Xiangpeng Liu,&nbsp;Tong Liu,&nbsp;Yu Feng,&nbsp;Zhengrong Yuan,&nbsp;Zhihao Jia,&nbsp;Yong Zhang","doi":"10.1002/imt2.237","DOIUrl":"https://doi.org/10.1002/imt2.237","url":null,"abstract":"<p>Type 1 diabetes mellitus (T1DM) is an autoimmune disease that can lead to severe diabetic complications. While the changes and correlations between gut microbiota and the pathogenesis of T1DM have been extensively studied, little is known about the benefits of interventions on gut bacterial communities, particularly using probiotics, for this disease. In the present study, we reported that the mice surviving after 5 months of streptozotocin (STZ) injection had reduced blood glucose level and recovered gut microbiota with increased <i>Akkermansia muciniphila</i> proportion. Gavage of heat-killed <i>A. muciniphila</i> increases the diversity of gut microbiota and elevated immune and metabolic signaling pathways in the intestine. Mechanistically, <i>A. muciniphila</i> treatment promoted the secretion of insulin-like growth factor 2 (IGF2) which subsequently activated IGF2 signaling in skeletal muscles and enhanced muscle and global metabolism. Our results suggest that the administration of heat-killed <i>A. muciniphila</i> could be a potential therapeutic strategy for T1DM and its associated hyperglycemia.\u0000\u0000 <figure>\u0000 <div><picture>\u0000 <source></source></picture><p></p>\u0000 </div>\u0000 </figure></p>","PeriodicalId":73342,"journal":{"name":"iMeta","volume":"3 5","pages":""},"PeriodicalIF":23.7,"publicationDate":"2024-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1002/imt2.237","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142449073","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}

{"title":"iNAP 2.0: Harnessing metabolic complementarity in microbial network analysis","authors":"Xi Peng,&nbsp;Kai Feng,&nbsp;Xingsheng Yang,&nbsp;Qing He,&nbsp;Bo Zhao,&nbsp;Tong Li,&nbsp;Shang Wang,&nbsp;Ye Deng","doi":"10.1002/imt2.235","DOIUrl":"https://doi.org/10.1002/imt2.235","url":null,"abstract":"<p>With the widespread adoption of metagenomic sequencing, new perspectives have emerged for studying microbial ecological networks, yielding metabolic evidence of interspecies interactions that traditional co-occurrence networks cannot infer. This protocol introduces the integrated Network Analysis Pipeline 2.0 (iNAP 2.0), which features an innovative metabolic complementarity network for microbial studies from metagenomics sequencing data. iNAP 2.0 sets up a four-module process for metabolic interaction analysis, namely: (I) Prepare genome-scale metabolic models; (II) Infer pairwise interactions of genome-scale metabolic models; (III) Construct metabolic interaction networks; and (IV) Analyze metabolic interaction networks. Starting from metagenome-assembled or complete genomes, iNAP 2.0 offers a variety of methods to quantify the potential and trends of metabolic complementarity between models, including the PhyloMint pipeline based on phylogenetic distance-adjusted metabolic complementarity, the SMETANA (species metabolic interaction analysis) approach based on cross-feeding substrate exchange prediction, and metabolic distance calculation based on parsimonious flux balance analysis (pFBA). Notably, iNAP 2.0 integrates the random matrix theory (RMT) approach to find the suitable threshold for metabolic interaction network construction. Finally, the metabolic interaction networks can proceed to analysis using topological feature analysis such as hub node determination. In addition, a key feature of iNAP 2.0 is the identification of potentially transferable metabolites between species, presented as intermediate nodes that connect microbial nodes in the metabolic complementarity network. To illustrate these new features, we use a set of metagenome-assembled genomes as an example to comprehensively document the usage of the tools. iNAP 2.0 is available at https://inap.denglab.org.cn for all users to register and use for free.</p>","PeriodicalId":73342,"journal":{"name":"iMeta","volume":"3 5","pages":""},"PeriodicalIF":23.7,"publicationDate":"2024-09-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1002/imt2.235","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142449229","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}

{"title":"Interaction between intestinal mycobiota and microbiota shapes lung inflammation","authors":"Youxia Wang,&nbsp;Fang He,&nbsp;Bingnan Liu,&nbsp;Xiaoyan Wu,&nbsp;Ziyi Han,&nbsp;Xuefei Wang,&nbsp;Yuexia Liao,&nbsp;Jielin Duan,&nbsp;Wenkai Ren","doi":"10.1002/imt2.241","DOIUrl":"https://doi.org/10.1002/imt2.241","url":null,"abstract":"<p>Gut microbiota is an intricate microbial community containing bacteria, fungi, viruses, archaea, and protozoa, and each of them contributes to diverse aspects of host health. Nevertheless, the influence of interaction among gut microbiota on host health remains uncovered. Here, we showed that the interaction between intestinal fungi and bacteria shaped lung inflammation during infection. Specifically, antifungal drug-induced dysbiosis of gut mycobiota enhanced lung inflammation during infection. Dysbiosis of gut mycobiota led to gut <i>Escherichia coli</i> (<i>E. coli</i>) overgrowth and translocation to the lung during infection, which induced lung accumulation of the CD45⁺F4/80⁺Ly6G⁻Ly6C⁻CD11b⁺CD11c⁺ macrophages. Clearance of macrophages or deletion of TLR4 (Toll-like receptor 4, recognition of LPS) rather than Dectin-1 (recognition of beta-1,3/1,6 glucans on fungi) blocked the antifungal drug-induced aggravation of lung inflammation during infection. These findings suggest that the interaction between intestinal mycobiota and commensal bacteria affects host health through the gut–lung axis, offering a potential therapeutic target for ameliorating lung inflammation during infection.</p>","PeriodicalId":73342,"journal":{"name":"iMeta","volume":"3 5","pages":""},"PeriodicalIF":23.7,"publicationDate":"2024-09-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1002/imt2.241","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142451157","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}

{"title":"ImageGP 2 for enhanced data visualization and reproducible analysis in biomedical research","authors":"Tong Chen,&nbsp;Yong-Xin Liu,&nbsp;Tao Chen,&nbsp;Mei Yang,&nbsp;Siqing Fan,&nbsp;Minglei Shi,&nbsp;Buqing Wei,&nbsp;Huijiao Lv,&nbsp;Wandi Cao,&nbsp;Chongming Wang,&nbsp;Jianzhou Cui,&nbsp;Jiwen Zhao,&nbsp;Yilai Han,&nbsp;Jiao Xi,&nbsp;Ziqiang Zheng,&nbsp;Luqi Huang","doi":"10.1002/imt2.239","DOIUrl":"https://doi.org/10.1002/imt2.239","url":null,"abstract":"<p>ImageGP is an extensively utilized, open-access platform for online data visualization and analysis. Over the past 7 years, it has catered to more than 700,000 usages globally, garnering substantial user feedback. The updated version, ImageGP 2 (available at https://www.bic.ac.cn/BIC), introduces a redesigned interface leveraging cutting-edge web technologies to enhance functionality and user interaction. Key enhancements include the following: (i) Addition of modules for data format transformation, facilitating operations such as matrix merging, subsetting, and transformation between long and wide formats. (ii) Streamlined workflows with features like preparameter selection data validation and grouping of parameters with similar attributes. (iii) Expanded repertoire of visualization functions and analysis tools, including Weighted Gene Co-Expression Network Analysis, differential gene expression analysis, and FASTA sequence processing. (iv) Personalized user space for uploading large data sets, tracking analysis history, and sharing reproducible analysis data, scripts, and results. (v) Enhanced user support through a simplified error debugging feature accessible with a single click. (vi) Introduction of an R package, ImageGP, enabling local data visualization and analysis. These updates position ImageGP 2 as a versatile tool serving both wet-lab and dry-lab researchers with expanded capabilities.</p>","PeriodicalId":73342,"journal":{"name":"iMeta","volume":"3 5","pages":""},"PeriodicalIF":23.7,"publicationDate":"2024-09-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1002/imt2.239","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142449210","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}