Database: The Journal of Biological Databases and Curation最新文献_第2页

The Genomic SSR Millets Database (GSMDB): enhancing genetic resources for sustainable agriculture. 基因组 SSR Millets 数据库（GSMDB）：为可持续农业加强遗传资源。

IF 3.4 4区生物学

Database: The Journal of Biological Databases and Curation Pub Date : 2024-11-15 DOI: 10.1093/database/baae114

Sonu Kumar, Sangeeta Singh, Rakesh Kumar, Dinesh Gupta

{"title":"The Genomic SSR Millets Database (GSMDB): enhancing genetic resources for sustainable agriculture.","authors":"Sonu Kumar, Sangeeta Singh, Rakesh Kumar, Dinesh Gupta","doi":"10.1093/database/baae114","DOIUrl":"10.1093/database/baae114","url":null,"abstract":"The global population surge demands increased food production and nutrient-rich options to combat rising food insecurity. Climate-resilient crops are vital, with millets emerging as superfoods due to nutritional richness and stress tolerance. Given limited genomic information, a comprehensive genetic resource is crucial to advance millet research. Whole-genome sequencing provides an unprecedented opportunity, and molecular genetic methodologies, particularly simple sequence repeats (SSRs), play a pivotal role in DNA fingerprinting, constructing linkage maps, and conducting population genetic studies. SSRs are composed of repetitive DNA sequences where one to six nucleotides are repeated in tandem and distributed throughout the genome. Different millet species exhibit genomic variations attributed to the presence of SSRs. While SSRs have been identified in a few millet species, the existing information only covers some of the sequenced genomes. Moreover, there is an absence of complete gene annotation and visualization features for SSRs. Addressing this disparity and leveraging the de-novo millet genome assembly available from the NCBI, we have developed the Genomic SSR Millets Database (GSMDB; https://bioinfo.icgeb.res.in/gsmdb/). This open-access repository provides a web-based tool offering search functionalities and comprehensive details on 6.747645 million SSRs mined from the genomic sequences of seven millet species. The database, featuring unrestricted public access and JBrowse visualization, is a pioneering resource for the research community dedicated to advancing millet cultivars and related species. GSMDB holds immense potential to support myriad studies, including genetic diversity assessments, genetic mapping, marker-assisted selection, and comparative population investigations aiming to facilitate the millet breeding programs geared toward ensuring global food security. Database URL: https://bioinfo.icgeb.res.in/gsmdb/.","PeriodicalId":10923,"journal":{"name":"Database: The Journal of Biological Databases and Curation","volume":"2024 ","pages":""},"PeriodicalIF":3.4,"publicationDate":"2024-11-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11566590/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142638644","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Peptipedia v2.0: a peptide sequence database and user-friendly web platform. A major update. Peptipedia v2.0：多肽序列数据库和用户友好型网络平台。重大更新。

IF 3.4 4区生物学

Database: The Journal of Biological Databases and Curation Pub Date : 2024-11-08 DOI: 10.1093/database/baae113

Gabriel Cabas-Mora, Anamaría Daza, Nicole Soto-García, Valentina Garrido, Diego Alvarez, Marcelo Navarrete, Lindybeth Sarmiento-Varón, Julieta H Sepúlveda Yañez, Mehdi D Davari, Frederic Cadet, Álvaro Olivera-Nappa, Roberto Uribe-Paredes, David Medina-Ortiz

{"title":"Peptipedia v2.0: a peptide sequence database and user-friendly web platform. A major update.","authors":"Gabriel Cabas-Mora, Anamaría Daza, Nicole Soto-García, Valentina Garrido, Diego Alvarez, Marcelo Navarrete, Lindybeth Sarmiento-Varón, Julieta H Sepúlveda Yañez, Mehdi D Davari, Frederic Cadet, Álvaro Olivera-Nappa, Roberto Uribe-Paredes, David Medina-Ortiz","doi":"10.1093/database/baae113","DOIUrl":"https://doi.org/10.1093/database/baae113","url":null,"abstract":"In recent years, peptides have gained significant relevance due to their therapeutic properties. The surge in peptide production and synthesis has generated vast amounts of data, enabling the creation of comprehensive databases and information repositories. Advances in sequencing techniques and artificial intelligence have further accelerated the design of tailor-made peptides. However, leveraging these techniques requires versatile and continuously updated storage systems, along with tools that facilitate peptide research and the implementation of machine learning for predictive systems. This work introduces Peptipedia v2.0, one of the most comprehensive public repositories of peptides, supporting biotechnological research by simplifying peptide study and annotation. Peptipedia v2.0 has expanded its collection by over 45% with peptide sequences that have reported biological activities. The functional biological activity tree has been revised and enhanced, incorporating new categories such as cosmetic and dermatological activities, molecular binding, and antiageing properties. Utilizing protein language models and machine learning, more than 90 binary classification models have been trained, validated, and incorporated into Peptipedia v2.0. These models exhibit average sensitivities and specificities of 0.877±0.0530 and 0.873±0.054, respectively, facilitating the annotation of more than 3.6 million peptide sequences with unknown biological activities, also registered in Peptipedia v2.0. Additionally, Peptipedia v2.0 introduces description tools based on structural and ontological properties and user-friendly machine learning tools to facilitate the application of machine learning strategies to study peptide sequences. Database URL: https://peptipedia.cl/.","PeriodicalId":10923,"journal":{"name":"Database: The Journal of Biological Databases and Curation","volume":"2024 ","pages":""},"PeriodicalIF":3.4,"publicationDate":"2024-11-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142603627","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}

引用次数: 0

athisomiRDB: A comprehensive database of Arabidopsis isomiRs. athisomiRDB：拟南芥同源异构体综合数据库。

IF 4.3 4区生物学

Database: The Journal of Biological Databases and Curation Pub Date : 2024-11-08 DOI: 10.1093/database/baae115

A T Vivek, Ajay Arya, Supriya P Swain, Shailesh Kumar

{"title":"athisomiRDB: A comprehensive database of Arabidopsis isomiRs.","authors":"A T Vivek, Ajay Arya, Supriya P Swain, Shailesh Kumar","doi":"10.1093/database/baae115","DOIUrl":"10.1093/database/baae115","url":null,"abstract":"Several pieces of evidence challenge the traditional view of miRNAs as static molecules, revealing dynamic isomiRs originating from each miRNA precursor arm. In plants, isomiRs, which result from imprecise cleavage during pre-miRNA processing and post-transcriptional alterations, serve as crucial regulators of target microRNAs (miRNAs). Despite numerous studies on Arabidopsis miRNAs, the systematic identification and annotation of isomiRs across various tissues and conditions remain limited. Due to the lack of systematically collected isomiR information, we introduce the athisomiRDB database, which houses 20 764 isomiRs from Arabidopsis small RNA-sequencing (sRNA-seq) libraries. It comprises >2700 diverse samples and allows exploration at the sample, miRNA, or isomiR levels, offering insights into the presence or absence of isomiRs. The athisomiRDB includes exclusive and ambiguous isomiRs, each with features such as transcriptional origin, variant-containing isomiRs, and identifiers for frequent single-nucleotide polymorphisms from the 1001 Genomes Project. It also provides 3' nontemplated post-transcriptional additions, isomiR-target interactions, and trait associations for each isomiR. We anticipate that athisomiRDB will play a pivotal role in unraveling the regulatory nature of the Arabidopsis miRNAome and enhancing sRNA research by leveraging isomiR profiles from extensive sRNA-seq datasets. Database URL: https://www.nipgr.ac.in/athisomiRDB.","PeriodicalId":10923,"journal":{"name":"Database: The Journal of Biological Databases and Curation","volume":"2024 ","pages":""},"PeriodicalIF":4.3,"publicationDate":"2024-11-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11544919/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142603625","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

PheNormGPT: a framework for extraction and normalization of key medical findings. PheNormGPT：关键医学发现的提取和规范化框架。

IF 3.4 4区生物学

Database: The Journal of Biological Databases and Curation Pub Date : 2024-10-23 DOI: 10.1093/database/baae103

Ekin Soysal, Kirk Roberts

引用次数: 0

Is metadata of articles about COVID-19 enough for multilabel topic classification task? 关于 COVID-19 的文章元数据是否足以完成多标签主题分类任务？

IF 3.4 4区生物学

Database: The Journal of Biological Databases and Curation Pub Date : 2024-10-21 DOI: 10.1093/database/baae106

Shuo Xu, Yuefu Zhang, Liang Chen, Xin An

{"title":"Is metadata of articles about COVID-19 enough for multilabel topic classification task?","authors":"Shuo Xu, Yuefu Zhang, Liang Chen, Xin An","doi":"10.1093/database/baae106","DOIUrl":"10.1093/database/baae106","url":null,"abstract":"The ever-increasing volume of COVID-19-related articles presents a significant challenge for the manual curation and multilabel topic classification of LitCovid. For this purpose, a novel multilabel topic classification framework is developed in this study, which considers both the correlation and imbalance of topic labels, while empowering the pretrained model. With the help of this framework, this study devotes to answering the following question: Do full texts, MeSH (Medical Subject Heading), and biological entities of articles about COVID-19 encode more discriminative information than metadata (title, abstract, keyword, and journal name)? From extensive experiments on our enriched version of the BC7-LitCovid corpus and Hallmarks of Cancer corpus, the following conclusions can be drawn. Our framework demonstrates superior performance and robustness. The metadata of scientific publications about COVID-19 carries valuable information for multilabel topic classification. Compared to biological entities, full texts and MeSH can further enhance the performance of our framework for multilabel topic classification, but the improved performance is very limited. Database URL: https://github.com/pzczxs/Enriched-BC7-LitCovid.","PeriodicalId":10923,"journal":{"name":"Database: The Journal of Biological Databases and Curation","volume":"2024 ","pages":""},"PeriodicalIF":3.4,"publicationDate":"2024-10-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11492800/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142459944","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

SesamumGDB: a comprehensive platform for Sesamum genetics and genomics analysis. SesamumGDB：芝麻遗传学和基因组学分析综合平台。

IF 3.4 4区生物学

Database: The Journal of Biological Databases and Curation Pub Date : 2024-10-19 DOI: 10.1093/database/baae105

Cao Hengchun, Guo Hui, Yang Weifei, Li Guiting, Ju Ming, Duan Yinghui, Tian Qiuzhen, Ma Qin, Feng Xiaoxu, Zhang Zhanyou, Zhang Haiyang, Miao Hongmei

{"title":"SesamumGDB: a comprehensive platform for Sesamum genetics and genomics analysis.","authors":"Cao Hengchun, Guo Hui, Yang Weifei, Li Guiting, Ju Ming, Duan Yinghui, Tian Qiuzhen, Ma Qin, Feng Xiaoxu, Zhang Zhanyou, Zhang Haiyang, Miao Hongmei","doi":"10.1093/database/baae105","DOIUrl":"10.1093/database/baae105","url":null,"abstract":"Sesame (Sesamum indicum L., 2n = 26) is a crucial oilseed crop cultivated worldwide. The ancient evolutionary position of the Sesamum genus highlights its value for genomics and molecular genetics research among the angiosperms of other genera. However, Sesamum is considered a small orphan genus with only a few genomic databases for cultivated sesame to date. The urgent need to construct comprehensive, curated genome databases that include genus-specific gene resources for both cultivated and wild Sesamum species is being recognized. In response, we developed Sesamum Genomics Database (SesamumGDB), a user-friendly genomic database that integrates extensive genomic resources from two cultivated sesame varieties (S. indicum) and seven wild Sesamum species, covering all three chromosome groups (2n = 26, 32, and 64). This database showcases a total of 352 471 genes, including 6026 related to lipid metabolism and 17 625 transcription factors within Sesamum. Equipped with an array of bioinformatics tools such as BLAST (basic local alignment search tool) and JBrowse (the Javascript browser), SesamumGDB facilitates data downloading, screening, visualization, and analysis. As the first centralized Sesamum genome database, SesamumGDB offers extensive insights into the genomics and genetics of sesame, potentially enhancing the molecular breeding of sesame and other oilseed crops in the future. Database URL: http://www.sgbdb.com/sgdb/.","PeriodicalId":10923,"journal":{"name":"Database: The Journal of Biological Databases and Curation","volume":"2024 ","pages":""},"PeriodicalIF":3.4,"publicationDate":"2024-10-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11490215/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142460043","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

SMCVdb: a database of experimental cellular toxicity information for drug candidate molecules. SMCVdb：候选药物分子实验细胞毒性信息数据库。

IF 3.4 4区生物学

Database: The Journal of Biological Databases and Curation Pub Date : 2024-10-18 DOI: 10.1093/database/baae100

Abhay Deep Pandey, Ghanshyam Sharma, Anshula Sharma, Sudhanshu Vrati, Deepak T Nair

{"title":"SMCVdb: a database of experimental cellular toxicity information for drug candidate molecules.","authors":"Abhay Deep Pandey, Ghanshyam Sharma, Anshula Sharma, Sudhanshu Vrati, Deepak T Nair","doi":"10.1093/database/baae100","DOIUrl":"10.1093/database/baae100","url":null,"abstract":"Many drug discovery exercises fail because small molecules that are effective inhibitors of target proteins exhibit high cellular toxicity. Early and effective assessment of toxicity and pharmacokinetics is essential to accelerate the drug discovery process. Conventional methods for toxicity profiling, including in vitro and in vivo assays, are laborious and resource-intensive. In response, we introduce the Small Molecule Cell Viability Database (SMCVdb), a comprehensive resource containing toxicity data for over 24 000 compounds obtained through high-content imaging (HCI). SMCVdb seamlessly integrates chemical descriptions and molecular weight data, offering researchers a holistic platform for toxicity data aiding compound prioritization and selection based on biological and economic considerations. Data collection for SMCVdb involved a systematic approach combining HCI toxicity profiling with chemical information and quality control measures ensured data accuracy and consistency. The user-friendly web interface of SMCVdb provides multiple search and filter options, allowing users to query the database based on compound name, molecular weight range, or viability percentage. SMCVdb empowers users to access toxicity profiles, molecular weights, compound names, and chemical descriptions, facilitating the exploration of relationships between compound properties and their effects on cell viability. In summary, the database provides experimentally derived cellular toxicity information for over 24 000 drug candidate molecules to academic researchers, and pharmaceutical companies. The SMCVdb will keep growing and will prove to be a pivotal resource to expedite research in drug discovery and compound evaluation. Database URL: http://smcvdb.rcb.ac.in:4321/.","PeriodicalId":10923,"journal":{"name":"Database: The Journal of Biological Databases and Curation","volume":"2024 ","pages":""},"PeriodicalIF":3.4,"publicationDate":"2024-10-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11488516/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142460044","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

RettDb: the Rett syndrome omics database to navigate the Rett syndrome genomic landscape. RettDb：Rett 综合征组学数据库，用于浏览 Rett 综合征基因组图谱。

IF 3.4 4区生物学

Database: The Journal of Biological Databases and Curation Pub Date : 2024-10-16 DOI: 10.1093/database/baae109

Nico Cillari, Giuseppe Neri, Nadia Pisanti, Paolo Milazzo, Ugo Borello

引用次数: 0

AbAMPdb: a database of Acinetobacter baumannii specific antimicrobial peptides. AbAMPdb：鲍曼不动杆菌特异抗菌肽数据库。

IF 3.4 4区生物学

Database: The Journal of Biological Databases and Curation Pub Date : 2024-10-12 DOI: 10.1093/database/baae096

Farha Anwer, Ahmad Navid, Fiza Faiz, Uzair Haider, Samavi Nasir, Muhammad Farooq, Maryam Zahra, Anosh Bano, Hafiza Hira Bashir, Madiha Ahmad, Syeda Aleena Abbas, Shah E Room, Muhammad Tariq Saeed, Amjad Ali

{"title":"AbAMPdb: a database of Acinetobacter baumannii specific antimicrobial peptides.","authors":"Farha Anwer, Ahmad Navid, Fiza Faiz, Uzair Haider, Samavi Nasir, Muhammad Farooq, Maryam Zahra, Anosh Bano, Hafiza Hira Bashir, Madiha Ahmad, Syeda Aleena Abbas, Shah E Room, Muhammad Tariq Saeed, Amjad Ali","doi":"10.1093/database/baae096","DOIUrl":"10.1093/database/baae096","url":null,"abstract":"Acinetobacter baumannii has emerged as a prominent nosocomial pathogen, exhibiting a progressive rise in resistance to therapeutic interventions. This rise in resistance calls for alternative strategies. Here, we propose an alternative yet specialized resource on antimicrobial peptides (AMPs) against A. baumannii. Database 'AbAMPdb' is the manually curated collection of 300 entries containing the 250 experimental AMP sequences and 50 corresponding synthetic or mutated AMP sequences. The mutated sequences were modified with reported amino acid substitutions intended for decreasing the toxicity and increasing the antimicrobial potency. AbAMPdb also provides 3D models of all 300 AMPs, comprising 250 natural and 50 synthetic or mutated AMPs. Moreover, the database offers docked complexes comprising 5000 AMPs and their corresponding A. baumannii target proteins. These complexes, accessible in Protein Data Bank format, enable the 2D visualization of the interacting amino acid residues. We are confident that this comprehensive resource furnishes vital information concerning AMPs, encompassing their docking interactions with virulence factors and antibiotic resistance proteins of A. baumannii. To enhance clinical relevance, the characterized AMPs could undergo further investigation both in vitro and in vivo. Database URL: https://abampdb.mgbio.tech/.","PeriodicalId":10923,"journal":{"name":"Database: The Journal of Biological Databases and Curation","volume":"2024 ","pages":""},"PeriodicalIF":3.4,"publicationDate":"2024-10-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11470754/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142459942","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

ELiAH: the atlas of E3 ligases in human tissues for targeted protein degradation with reduced off-target effect. ELiAH：人体组织中的 E3 连接酶图谱，用于靶向降解蛋白质，减少脱靶效应。

IF 3.4 4区生物学

Database: The Journal of Biological Databases and Curation Pub Date : 2024-10-12 DOI: 10.1093/database/baae111

Hyojung Paik, Chunryong Oh, Sajid Hussain, Sangjae Seo, Soon Woo Park, Tae Lyun Ko, Ari Lee

{"title":"ELiAH: the atlas of E3 ligases in human tissues for targeted protein degradation with reduced off-target effect.","authors":"Hyojung Paik, Chunryong Oh, Sajid Hussain, Sangjae Seo, Soon Woo Park, Tae Lyun Ko, Ari Lee","doi":"10.1093/database/baae111","DOIUrl":"10.1093/database/baae111","url":null,"abstract":"The development of therapeutic agents has mainly focused on designing small molecules to modulate target proteins or genes which are conventionally druggable. Therefore, targeted protein degradation (TPD) for undruggable cases has emerged as promising pharmaceutical approach. TPD, often referred PROTACs (PROteolysis TArgeting Chimeras), uses a linker to degrade target proteins by hijacking the ubiquitination system. Therefore, unravel the relationship including reversal and co-expression between E3 ligands and other possible target genes in various human tissues is essential to mitigate off-target effects of TPD. Here, we developed the atlas of E3 ligases in human tissues (ELiAH), to prioritize E3 ligase-target gene pairs for TPD. Leveraging over 2900 of RNA-seq profiles consisting of 11 human tissues from the GTEx (genotype-tissue expression) consortium, users of ELiAH can identify tissue-specific genes and E3 ligases (FDR P-value of Mann-Whitney test < .05). ELiAH unravels 933 830 relationships consisting of 614 E3 ligases and 20 924 of expressed genes considering degree of tissue specificity, which are indispensable for ubiquitination based TPD development. In addition, docking properties of those relationships are also modeled using RosettaDock. Therefore, ELiAH presents comprehensive repertoire of E3 ligases for ubiquitination-based TPD drug development avoiding off-target effects. Database URL: https://eliahdb.org.","PeriodicalId":10923,"journal":{"name":"Database: The Journal of Biological Databases and Curation","volume":"2024 ","pages":""},"PeriodicalIF":3.4,"publicationDate":"2024-10-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11470751/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142459943","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0