Molecular omics最新文献_第8页

A blood-based multi-omic landscape for the molecular characterization of kidney stone disease† 用于肾结石病分子特征描述的基于血液的多组学图谱

IF 2.9 4区生物学

Molecular omics Pub Date : 2024-04-16 DOI: 10.1039/D3MO00261F

Weibing Pan‡, Tianwei Yun, Xin Ouyang, Zhijun Ruan, Tuanjie Zhang, Yuhao An, Rui Wang and Peng Zhu

{"title":"A blood-based multi-omic landscape for the molecular characterization of kidney stone disease†","authors":"Weibing Pan‡, Tianwei Yun, Xin Ouyang, Zhijun Ruan, Tuanjie Zhang, Yuhao An, Rui Wang and Peng Zhu","doi":"10.1039/D3MO00261F","DOIUrl":"10.1039/D3MO00261F","url":null,"abstract":"Kidney stone disease (KSD, also named renal calculi, nephrolithiasis, or urolithiasis) is a common urological disease entailing the formation of minerals and salts that form inside the urinary tract, frequently caused by diabetes, high blood pressure, hypertension, and monogenetic components in most patients. 10% of adults worldwide are affected by KSD, which continues to be highly prevalent and with increasing incidence. For the identification of novel therapeutic targets in KSD, we adopted high-throughput sequencing and mass spectrometry (MS) techniques in this study and carried out an integrative analysis of exosome proteomic data and DNA methylation data from blood samples of normal and KSD individuals. Our research delineated the profiling of exosomal proteins and DNA methylation in both healthy individuals and those afflicted with KSD, finding that the overexpressed proteins and the demethylated genes in KSD samples are associated with immune responses. The consistency of the results in proteomics and epigenetics supports the feasibility of the comprehensive strategy. Our insights into the molecular landscape of KSD pave the way for a deeper understanding of its pathogenic mechanism, providing an opportunity for more precise diagnosis and targeted treatment strategies for KSD.","PeriodicalId":19065,"journal":{"name":"Molecular omics","volume":" 5","pages":" 322-332"},"PeriodicalIF":2.9,"publicationDate":"2024-04-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140577667","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

PerSEveML: a web-based tool to identify persistent biomarker structure for rare events using an integrative machine learning approach† PerSEveML：使用整合机器学习方法识别罕见事件持久生物标记物结构的网络工具

IF 2.9 4区生物学

Molecular omics Pub Date : 2024-04-16 DOI: 10.1039/D4MO00008K

Sreejata Dutta, Dinesh Pal Mudaranthakam, Yanming Li and Mihaela E. Sardiu

{"title":"PerSEveML: a web-based tool to identify persistent biomarker structure for rare events using an integrative machine learning approach†","authors":"Sreejata Dutta, Dinesh Pal Mudaranthakam, Yanming Li and Mihaela E. Sardiu","doi":"10.1039/D4MO00008K","DOIUrl":"10.1039/D4MO00008K","url":null,"abstract":"Omics data sets often pose a computational challenge due to their high dimensionality, large size, and non-linear structures. Analyzing these data sets becomes especially daunting in the presence of rare events. Machine learning (ML) methods have gained traction for analyzing rare events, yet there has been limited exploration of bioinformatics tools that integrate ML techniques to comprehend the underlying biology. Expanding upon our previously developed computational framework of an integrative machine learning approach, we introduce PerSEveML, an interactive web-based tool that uses crowd-sourced intelligence to predict rare events and determine feature selection structures. PerSEveML provides a comprehensive overview of the integrative approach through evaluation metrics that help users understand the contribution of individual ML methods to the prediction process. Additionally, PerSEveML calculates entropy and rank scores, which visually organize input features into a persistent structure of selected, unselected, and fluctuating categories that help researchers uncover meaningful hypotheses regarding the underlying biology. We have evaluated PerSEveML on three diverse biologically complex data sets with extremely rare events from small to large scale and have demonstrated its ability to generate valid hypotheses. PerSEveML is available at https://biostats-shinyr.kumc.edu/PerSEveML/ and https://github.com/sreejatadutta/PerSEveML.","PeriodicalId":19065,"journal":{"name":"Molecular omics","volume":" 5","pages":" 348-358"},"PeriodicalIF":2.9,"publicationDate":"2024-04-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://pubs.rsc.org/en/content/articlepdf/2024/mo/d4mo00008k?page=search","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140577568","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

Intact cell lipidomics using the Bruker MBT lipid Xtract assay allows the rapid detection of glycosyl-inositol-phospho-ceramides from Aspergillus fumigatus† 利用布鲁克 MBT 脂质 Xtract 分析法进行完整细胞脂质组学分析，可快速检测曲霉菌中的糖基肌醇磷酰神经酰胺

IF 3 4区生物学

Molecular omics Pub Date : 2024-03-28 DOI: 10.1039/D4MO00030G

Aishani Chakraborty, Leila Alsharqi, Markus Kostrzewa, Darius Armstrong-James and Gerald Larrouy-Maumus

{"title":"Intact cell lipidomics using the Bruker MBT lipid Xtract assay allows the rapid detection of glycosyl-inositol-phospho-ceramides from Aspergillus fumigatus†","authors":"Aishani Chakraborty, Leila Alsharqi, Markus Kostrzewa, Darius Armstrong-James and Gerald Larrouy-Maumus","doi":"10.1039/D4MO00030G","DOIUrl":"10.1039/D4MO00030G","url":null,"abstract":"Glycosyl-inositol-phospho-ceramides (GIPCs) or glycosylphosphatidylinositol-anchored fungal polysaccharides are major lipids in plant and fungal plasma membranes and play an important role in stress adaption. However, their analysis remains challenging due to the multiple steps involved in their extraction and purification prior to mass spectrometry analysis. To address this challenge, we report here a novel simplified method to identify GIPCs from Aspergillus fumigatus using the new Bruker MBT lipid Xtract assay. A. fumigatus reference strains and clinical isolates were cultured, harvested, heat-inactivated and suspended in double-distilled water. A fraction of this fungal preparation was then dried in a microtube, mixed with an MBT lipid Xtract matrix (Bruker Daltonik, Germany) and loaded onto a MALDI target plate. Analysis was performed using a Bruker MALDI Biotyper Sirius system in the linear negative ion mode. Mass spectra were scanned from m/z 700 to m/z 2 000. MALDI-TOF MS analysis of cultured fungi showed a clear signature of GIPCs in Aspergillus fumigatus reference strains and clinical isolates. Here, we have demonstrated that routine MALDI-TOF in the linear negative ion mode combined with the MBT lipid Xtract is able to detect Aspergillus fumigatus GIPCs.","PeriodicalId":19065,"journal":{"name":"Molecular omics","volume":" 6","pages":" 390-396"},"PeriodicalIF":3.0,"publicationDate":"2024-03-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://pubs.rsc.org/en/content/articlepdf/2024/mo/d4mo00030g?page=search","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140316240","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

Implementation of multiomic mass spectrometry approaches for the evaluation of human health following environmental exposure 采用多组质谱方法评估暴露于环境后的人体健康状况

IF 2.9 4区生物学

Molecular omics Pub Date : 2024-03-26 DOI: 10.1039/D3MO00214D

Christina R. Ferreira, Paulo Clairmont F. de Lima Gomes, Kiley Marie Robison‡, Bruce R. Cooper‡ and Jonathan H. Shannahan

{"title":"Implementation of multiomic mass spectrometry approaches for the evaluation of human health following environmental exposure","authors":"Christina R. Ferreira, Paulo Clairmont F. de Lima Gomes, Kiley Marie Robison‡, Bruce R. Cooper‡ and Jonathan H. Shannahan","doi":"10.1039/D3MO00214D","DOIUrl":"10.1039/D3MO00214D","url":null,"abstract":"Omics analyses collectively refer to the possibility of profiling genetic variants, RNA, epigenetic markers, proteins, lipids, and metabolites. The most common analytical approaches used for detecting molecules present within biofluids related to metabolism are vibrational spectroscopy techniques, represented by infrared, Raman, and nuclear magnetic resonance (NMR) spectroscopies and mass spectrometry (MS). Omics-based assessments utilizing MS are rapidly expanding and being applied to various scientific disciplines and clinical settings. Most of the omics instruments are operated by specialists in dedicated laboratories; however, the development of miniature portable omics has made the technology more available to users for field applications. Variations in molecular information gained from omics approaches are useful for evaluating human health following environmental exposure and the development and progression of numerous diseases. As MS technology develops so do statistical and machine learning methods for the detection of molecular deviations from personalized metabolism, which are correlated to altered health conditions, and they are intended to provide a multi-disciplinary overview for researchers interested in adding multiomic analysis to their current efforts. This includes an introduction to mass spectrometry-based omics technologies, current state-of-the-art capabilities and their respective strengths and limitations for surveying molecular information. Furthermore, we describe how knowledge gained from these assessments can be applied to personalized medicine and diagnostic strategies.","PeriodicalId":19065,"journal":{"name":"Molecular omics","volume":" 5","pages":" 296-321"},"PeriodicalIF":2.9,"publicationDate":"2024-03-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://pubs.rsc.org/en/content/articlepdf/2024/mo/d3mo00214d?page=search","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140316073","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

Genome-scale metabolic models in translational medicine: the current status and potential of machine learning in improving the effectiveness of the models 转化医学中的基因组尺度代谢模型：机器学习在提高模型有效性方面的现状和潜力

IF 2.9 4区生物学

Molecular omics Pub Date : 2024-02-20 DOI: 10.1039/D3MO00152K

Beste Turanli, Gizem Gulfidan, Ozge Onluturk Aydogan, Ceyda Kula, Gurudeeban Selvaraj and Kazim Yalcin Arga

{"title":"Genome-scale metabolic models in translational medicine: the current status and potential of machine learning in improving the effectiveness of the models","authors":"Beste Turanli, Gizem Gulfidan, Ozge Onluturk Aydogan, Ceyda Kula, Gurudeeban Selvaraj and Kazim Yalcin Arga","doi":"10.1039/D3MO00152K","DOIUrl":"10.1039/D3MO00152K","url":null,"abstract":"The genome-scale metabolic model (GEM) has emerged as one of the leading modeling approaches for systems-level metabolic studies and has been widely explored for a broad range of organisms and applications. Owing to the development of genome sequencing technologies and available biochemical data, it is possible to reconstruct GEMs for model and non-model microorganisms as well as for multicellular organisms such as humans and animal models. GEMs will evolve in parallel with the availability of biological data, new mathematical modeling techniques and the development of automated GEM reconstruction tools. The use of high-quality, context-specific GEMs, a subset of the original GEM in which inactive reactions are removed while maintaining metabolic functions in the extracted model, for model organisms along with machine learning (ML) techniques could increase their applications and effectiveness in translational research in the near future. Here, we briefly review the current state of GEMs, discuss the potential contributions of ML approaches for more efficient and frequent application of these models in translational research, and explore the extension of GEMs to integrative cellular models.","PeriodicalId":19065,"journal":{"name":"Molecular omics","volume":" 4","pages":" 234-247"},"PeriodicalIF":2.9,"publicationDate":"2024-02-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139911187","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

Pancreatic cancer environment: from patient-derived models to single-cell omics 胰腺癌环境：从患者衍生模型到单细胞全息研究

IF 2.9 4区生物学

Molecular omics Pub Date : 2024-02-14 DOI: 10.1039/D3MO00250K

Ao Gu, Jiatong Li, Shimei Qiu, Shenglin Hao, Zhu-Ying Yue, Shuyang Zhai, Meng-Yao Li and Yingbin Liu

引用次数: 0

Prediction of quality markers in Maren Runchang pill for constipation using machine learning and network pharmacology† 利用机器学习和网络药理学预测马仁润肠丸中有关便秘的质量指标

IF 2.9 4区生物学

Molecular omics Pub Date : 2024-01-30 DOI: 10.1039/D3MO00221G

Yunxiao Liu, Lanping Guo, Qi Li, Wencui Yang and Hongjing Dong

{"title":"Prediction of quality markers in Maren Runchang pill for constipation using machine learning and network pharmacology†","authors":"Yunxiao Liu, Lanping Guo, Qi Li, Wencui Yang and Hongjing Dong","doi":"10.1039/D3MO00221G","DOIUrl":"10.1039/D3MO00221G","url":null,"abstract":"Maren Runchang pill (MRRCP) is a Chinese patent medicine used to treat constipation in clinics. It has multi-component and multi-target characteristics, and there is an urgent need to screen markers to ensure its quality. The aim of this study was to screen quality markers of MRRCP based on a “differential compounds-bioactivity” strategy using machine learning and network pharmacology to ensure the effectiveness and stability of MRRCP. In this study, UPLC-Q-TOF-MS/MS was used to identify chemical compounds in MRRCP and machine learning algorithms were applied to screen differential compounds. The quality markers were further screened by network pharmacology. Meanwhile, molecular docking was used to verify the screening results of machine learning and network pharmacology. A total of 28 constituents in MRRCP were identified, and four differential compounds were screened by machine learning algorithms. Subsequently, a total of two quality markers (rutin and rubiadin) in MRRCP. Additionally, the molecular docking results showed that quality markers could spontaneously bind to core targets. This study provides a reference for improving the quality evaluation method of MRRCP to ensure its quality. More importantly, it provided a new approach to screen quality markers in Chinese patent medicines.","PeriodicalId":19065,"journal":{"name":"Molecular omics","volume":" 4","pages":" 283-288"},"PeriodicalIF":2.9,"publicationDate":"2024-01-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139648257","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

Metabolomics approach to understand molecular mechanisms involved in fungal pathogen–citrus pathosystems 通过代谢组学方法了解涉及真菌病原体-柑橘病理系统的分子机制。

IF 2.9 4区生物学

Molecular omics Pub Date : 2024-01-26 DOI: 10.1039/D3MO00182B

Evandro Silva, Rodolfo Dantas, Júlio César Barbosa, Roberto G. S. Berlinck and Taicia Fill

{"title":"Metabolomics approach to understand molecular mechanisms involved in fungal pathogen–citrus pathosystems","authors":"Evandro Silva, Rodolfo Dantas, Júlio César Barbosa, Roberto G. S. Berlinck and Taicia Fill","doi":"10.1039/D3MO00182B","DOIUrl":"10.1039/D3MO00182B","url":null,"abstract":"Citrus is a crucial crop with a significant economic impact globally. However, postharvest decay caused by fungal pathogens poses a considerable threat, leading to substantial financial losses. Penicillium digitatum, Penicillium italicum, Geotrichum citri-aurantii and Phyllosticta citricarpa are the main fungal pathogens, causing green mold, blue mold, sour rot and citrus black spot diseases, respectively. The use of chemical fungicides as a control strategy in citrus raises concerns about food and environmental safety. Therefore, understanding the molecular basis of host–pathogen interactions is essential to find safer alternatives. This review highlights the potential of the metabolomics approach in the search for bioactive compounds involved in the pathogen–citrus interaction, and how the integration of metabolomics and genomics contributes to the understanding of secondary metabolites associated with fungal virulence and the fungal infection mechanisms. Our goal is to provide a pipeline combining metabolomics and genomics that can effectively guide researchers to perform studies aiming to contribute to the understanding of the fundamental chemical and biochemical aspects of pathogen–host interactions, in order to effectively develop new alternatives for fungal diseases in citrus cultivation. We intend to inspire the scientific community to question unexplored biological systems, and to employ diverse analytical approaches and metabolomics techniques to address outstanding questions about the non-studied pathosystems from a chemical biology perspective.","PeriodicalId":19065,"journal":{"name":"Molecular omics","volume":" 3","pages":" 154-168"},"PeriodicalIF":2.9,"publicationDate":"2024-01-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139564516","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

Open-tubular trap columns: towards simple and robust liquid chromatography separations for single-cell proteomics 开放管状捕集柱：为单细胞蛋白质组学实现简单稳健的液相色谱分离

IF 2.9 4区生物学

Molecular omics Pub Date : 2024-01-26 DOI: 10.1039/D3MO00249G

Kei G. I. Webber, Siqi Huang, Thy Truong, Jacob L. Heninger, Michal Gregus, Alexander R. Ivanov and Ryan T. Kelly

{"title":"Open-tubular trap columns: towards simple and robust liquid chromatography separations for single-cell proteomics","authors":"Kei G. I. Webber, Siqi Huang, Thy Truong, Jacob L. Heninger, Michal Gregus, Alexander R. Ivanov and Ryan T. Kelly","doi":"10.1039/D3MO00249G","DOIUrl":"10.1039/D3MO00249G","url":null,"abstract":"Nanoflow liquid chromatography-mass spectrometry is key to enabling in-depth proteome profiling of trace samples, including single cells, but these separations can lack robustness due to the use of narrow-bore columns that are susceptible to clogging. In the case of single-cell proteomics, offline cleanup steps are generally omitted to avoid losses to additional surfaces, and online solid-phase extraction/trap columns frequently provide the only opportunity to remove salts and insoluble debris before the sample is introduced to the analytical column. Trap columns are traditionally short, packed columns used to load and concentrate analytes at flow rates greater than those employed in analytical columns, and since these first encounter the uncleaned sample mixture, trap columns are also susceptible to clogging. We hypothesized that clogging could be avoided by using large-bore porous layer open tubular trap columns (PLOTrap). The low back pressure ensured that the PLOTraps could also serve as the sample loop, thus allowing sample cleanup and injection with a single 6-port valve. We found that PLOTraps could effectively remove debris to avoid column clogging. We also evaluated multiple stationary phases and PLOTrap diameters to optimize performance in terms of peak widths and sample loading capacities. Optimized PLOTraps were compared to conventional packed trap columns operated in forward and backflush modes, and were found to have similar chromatographic performance of backflushed traps while providing improved debris removal for robust analysis of trace samples.","PeriodicalId":19065,"journal":{"name":"Molecular omics","volume":" 3","pages":" 184-191"},"PeriodicalIF":2.9,"publicationDate":"2024-01-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139589835","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

Chemical diversity of Brittonodoxa subpinnata, a Brazilian native species of moss† 巴西本土苔藓物种 Brittonodoxa subpinnata 的化学多样性

IF 2.9 4区生物学

Molecular omics Pub Date : 2024-01-23 DOI: 10.1039/D3MO00209H

Wilton Ricardo Sala-Carvalho, Denilson Fernandes Peralta and Cláudia Maria Furlan

{"title":"Chemical diversity of Brittonodoxa subpinnata, a Brazilian native species of moss†","authors":"Wilton Ricardo Sala-Carvalho, Denilson Fernandes Peralta and Cláudia Maria Furlan","doi":"10.1039/D3MO00209H","DOIUrl":"10.1039/D3MO00209H","url":null,"abstract":"Plants should be probably thought of as the most formidable chemical laboratory that can be exploited for the production of an incredible number of molecules with remarkable structural and chemical diversity that cannot be matched by any synthetic libraries of small molecules. The bryophytes chemistry has been neglected for too long, but in the last ten years, this scenery is changing, with several studies being made using extracts from bryophytes, aimed at the characterization of interesting metabolites, with their metabolome screened. The main objective of this study was to analyze the metabolome of Brittonodoxa subpinnata, a native Brazilian moss species, which occurs in the two Brazilian hotspots. GC-MS and LC-MS2 were performed. All extracts were analyzed using the molecular networking approach. The four extracts of B. subpinnata (polar, non-polar, soluble, and insoluble) resulted in 928 features detected within the established parameters. 189 (20.4%) compounds were annotated, with sugars, fatty acids, flavonoids, and biflavonoids as the major constituents. Sucrose was the sugar with the highest quantity; palmitic acid the major fatty acid but with great presence of very long-chain fatty acids rarely found in higher plants, glycosylated flavonoids were the major flavonoids, and biflavonoids majorly composed by units of flavones and flavanones, exclusively found in the cell wall. Despite the high percentage, this work leaves a significant gap for future works using other structure elucidation techniques, such as NMR.","PeriodicalId":19065,"journal":{"name":"Molecular omics","volume":" 3","pages":" 203-212"},"PeriodicalIF":2.9,"publicationDate":"2024-01-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139552584","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