基于文本挖掘和生物医学数据库的新型冠状病毒肺炎药物发现

目的 基于文本挖掘技术和生物医学数据库对新型冠状病毒肺炎（COVID-19）相关文献进行数据挖掘分析，探究COVID-19及其主要症状发热、咳嗽、呼吸障碍相关基因靶点，筛选潜在有效的化学药和中药。方法 使用GenCLiP 3网站获取COVID-19和其主要症状咳嗽、发热、呼吸障碍共4个关键词的共有靶点，在METASCAPE数据库中对其进行基因本体（GO）和通路富集分析，再利用String数据库和Cytoscape软件构建共有靶点的蛋白质相互作用网络，筛选获得核心基因，运用DGIdb数据库、SymMap数据库针对核心基因进行中西医治疗药物预测。结果 获得COVID-19及其主要症状共有基因靶点28个，其中有IL2、IL1B、CCL2等核心基因16个，使用DGIdb数据库筛选获得与16个关键靶点相互作用的化学药包括沙利度胺、来氟米特、环孢素等28种，中药包括虎杖、黄芪、芦荟等70味。结论 COVID-19及其主要症状的病理机制可能和CD4、KNG1、VEGFA等28个共有基因相关，可能通过介导TNF、IL-17等信号通路参与COVID-19病理过程。潜在有效药物可能通过作用相关靶点通路起到治疗COVID-19的作用。     

基于真实世界数据探讨中医药治疗糖尿病肾病用药规律的研究＊

目的 基于临床信息系统分析总结真实世界的数据，采用数据挖掘的方法探讨中医药治疗糖尿病肾病的用药规律。方法 收集2018年1月-2020年12月上海中医药大学附属曙光医院宝山分院健康信息系统确诊的糖尿病肾病的门诊或住院患者的诊疗信息，建立Excel数据库，采用Excel 2010软件统计高频药物的四气、五味、归经及功效；使用SPSS Modeler 18.0软件中的Apriori算法分析关联规则，采用web节点建构药对关联网状图；运用SPSS 25统计软件进行因子分析。结果 本研究最终纳入477例接受中药饮片治疗的DKD患者，在1203条方剂信息中，涉及中药462种；使用频数排名前5位的中药分别是黄芪、黄精、石斛、山茱萸、麦冬；使用频数前5类的中药类别分别是补气药、补阴药、清热燥湿药、活血调经药、息风止痉药；在30味高频药物中，苦、甘、辛药味最为常见；药性寒、温数量接近；归脾经、肝经、肺经、肾经居多；关联规则提示，药物组合中置信度最高的组合为地龙-当归-僵蚕，因子分析共得到5个有效因子，累积贡献率为47.33%。结论 中医药治疗DKD在补益气血阴阳的同时，兼顾对瘀血、湿邪和痰饮的治疗，结合证型，可考虑使用黄芪、黄精、石斛、山茱萸、麦冬、金蝉花等药物的使用，清热燥湿药物如黄连、黄芩、黄柏可适当加入，为使邪有去处，大黄、车前子或可增添疗效。     

Reference set for performance testing of pediatric vaccine safety signal detection methods and systems

BackgroundSafety signal detection in spontaneous reporting system databases and electronic healthcare records is key to detection of previously unknown adverse events following immunization. Various statistical methods for signal detection in these different datasources have been developed, however none are geared to the pediatric population and none specifically to vaccines. A reference set comprising pediatric vaccine-adverse event pairs is required for reliable performance testing of statistical methods within and across data sources.MethodsThe study was conducted within the context of the Global Research in Paediatrics (GRiP) project, as part of the seventh framework programme (FP7) of the European Commission. Criteria for the selection of vaccines considered in the reference set were routine and global use in the pediatric population. Adverse events were primarily selected based on importance. Outcome based systematic literature searches were performed for all identified vaccine-adverse event pairs and complemented by expert committee reports, evidence based decision support systems (e.g. Micromedex), and summaries of product characteristics. Classification into positive (PC) and negative control (NC) pairs was performed by two independent reviewers according to a pre-defined algorithm and discussed for consensus in case of disagreement.ResultsWe selected 13 vaccines and 14 adverse events to be included in the reference set. From a total of 182 vaccine-adverse event pairs, we classified 18 as PC, 113 as NC and 51 as unclassifiable. Most classifications (91) were based on literature review, 45 were based on expert committee reports, and for 46 vaccine-adverse event pairs, an underlying pathomechanism was not plausible classifying the association as NC.ConclusionA reference set of vaccine-adverse event pairs was developed. We propose its use for comparing signal detection methods and systems in the pediatric population.     

Bibliometric analysis of orthopaedic related publications by Indian authors from the last decade

PurposeBibliometric studies have been established methods of analysing publications on a particular topic. These studies have been done on various orthopaedic topics and are increasing. The advantages of these studies have been highlighted in previous publications. Although some studies have been done on Indian publications from other specialties, those analysing Indian Orthopaedic Publications are lacking.MethodsWe performed a search in Scopus to look for all publications related to orthopaedics from India. Our search strategy in Scopus included ((TITLE-ABS-KEY(Orthopaedics OR Orthopaedics) AND AFFIL(India)) AND PUBYEAR > 2009 AND PUBYEAR < 2020) which resulted in 3270 articles on 02/11/2021. We analyzed the most publishing universities, city, state, specialty, authors, and anatomic location of these publications. We also mined the data to draw word clouds based on data obtained from the titles of articles, keywords and the affiliations of each of the articles published.ResultsTamil Nadu and New Delhi and their institutes appear to be the epicenter of publication activities in Orthopaedics in India. There has been a healthy trend of growth of articles in the orthopaedic specialty. Since there is a significant overlap of technology and engineering, it is not surprising to see engineering and technology institutes among the top 10 published institutes and even journals for the publications on orthopaedics.ConclusionThere has been a steady increase in the number of publications in the last decade. New Delhi and its Universities and Institutes appear to contribute the majority of citations and publications related to orthopaedics. Journal of Clinical Orthopaedics and Trauma was the most publishing journal for Indian authors on Orthopaedic related articles.     

中药复方配伍的研究方法及其进展

中药复方是由2味或2味以上中药遵循中医理论组合而成的方剂。多味中药在合适的剂量配比之下,协同发挥作用,实现中医的整体调节治疗。研究中药复方的配伍对推动中药现代化发展、新药开发以及临床应用有着重要意义。近年来,研究者们在传统的"七情和合"与"君臣佐使"的基础上,运用新技术和新方法对中药复方的成分、药效活性和药代动力学性质等进行了研究,从不同角度探讨了中药复方配伍的科学内涵。同时,多种数理方法和模型的建立、网络药理学和数据挖掘方法的发展与应用,也对中药复方配伍研究提供了很大帮助。研究方法的发展虽促进了中药复方配伍的科学研究,但还需进一步建立适合中药复方配伍复杂关系的研究方法,以阐明中药复方及其成分/组分配伍的内在规律,进而构建新的现代中药复方,这也是目前中药复方配伍研究的重点任务。     

应用数据挖掘技术获取周围型肺癌临床和CT诊断规则的初步研究

目的探讨数据挖掘技术对周围型肺癌影像诊断规则提取的价值。方法收集58例经过临床病理证实的周围型肺癌病例,对其临床及CT表现属性进行标准化认定,输入数据库,分别采用自主开发的基于关联规则知识发现程序与通用数据分析工具ROSETTA中的粗糙集约简算法和遗传分类算法对58例周围型肺癌临床及影像学数据进行挖掘对比研究。结果由Johnson’s Algorithm粗糙集约简算法产生诊断规则51条,由ROSETTA遗传分类算法所产生的诊断规则有5千多条,基于关联规则的挖掘算法所产生的诊断规则有123条。这3种不同的数据挖掘方法产生的最重要的诊断规则基本上都将性别、年龄、位置、毛刺、形状、毛玻璃样密度等属性作为诊断周围型肺癌的主要依据。结论数据挖掘技术在医学影像诊断和鉴别诊断中具有潜在的应用价值。     

A retrospective mortality study of workers exposed to arsenic in a gold mine and refinery in France

A historical mortality study of a cohort of employees of a gold mining and refining company was carried out in Salsigne, France. A major goal of the study was to investigate the relationship between lung cancer mortality and exposure to arsenic, radon, silica, and other contaminants of the working environment. A twofold excess of lung cancer was found both among miners and smelters, mainly concentrated among workers who had experienced exposure to past levels of arsenic, radon, and silica. The consistency of the results in the mine and the refinery are suggestive of a carcinogenic risk from both soluble and insoluble arsenic, although the potential role of other factors cannot be dismissed. © 1994 Wiley-Liss, Inc.     

基于FAERS的地舒单抗安全警戒信号挖掘与评价

基于FAERS数据库挖掘安全警戒信号,分析评估地舒单抗潜在不良反应信号,为其临床使用提供一定参考依据。方法 通过Openvigil 2.1访问 FAERS 数据库,将地舒单抗作为主要药物,检索自该药首次上市时间（2010年5月—2021年9月）的数据,获得与地舒单抗相关的不良事件报告记录。使用报告比值比法（ROR）和贝叶斯置信度递进神经网络法（BCPNN）筛选地舒单抗安全警戒信号,挖掘潜在的不良反应,并通过工具BioPortal对不良事件信号挖掘结果进行系统分类,通过判断信号间置信区间的变化,发现与药物不良事件关联性较大的信号。结果 从FAERS数据库中收集到270503份不良反应事件（ADE）报告,根据ROR法和BCPNN法共得到343个不良事件信号,通过信号间同义合并、剔除与药物无关的信号后,得到316个不良事件信号。地舒单抗的不良事件系统分类主要为肌肉骨骼和结缔组织疾病、医学检查、胃肠道疾病。FAERS数据库的信号挖掘结果发现,高风险且说明书中未收录的安全警戒信号包括颞下颌关节综合征、下颌脓肿、雌激素缺乏症、血液甲状旁腺激素增加,计算高风险信号的置信区间显示颞下关节综合征较有可能发展成为新的不良反应;另外,也发现种植体周围炎为具有临床意义的可疑警戒信号,但有待进一步观察研究。结论 基于FAERS数据库的信号挖掘结果提示临床应规范使用地舒单抗,治疗期间需警惕患者是否出现颞下颌关节综合征、下颌脓肿、雌激素缺乏症、血液甲状旁腺激素增加等不良反应事件,以便尽早发现尽早处理,从而有效降低临床用药风险     

基于网络药理和实验验证探究中药通过健脾作用治疗白细胞减少症的作用机制

摘要 目的 运用数据挖掘、网络药理学和实验验证探讨中药通过健脾作用治疗白细胞减少症的用药规律、药效物质基础及潜在的作用机制。方法 在中国知网、万方数据知识服务平台、维普网和PubMed数据库中检索健脾中药复方治疗白细胞减少症的临床文献,运用古今医案云平台在线分析软件和SPSS Modeler 18 统计分析软件寻求核心药物组;利用中药系统药理学数据库和分析平台（TCMSP）、GeneCards数据库、OMIM数据库检索、Cytoscape3.7.2软件、STRING数据库获取关键基因和主要有效成分,利用Metascape进行基因本体（GO）功能富集分析和京都基因与基因组百科全书（KEGG）通路富集分析;采用MTT法检测细胞增殖率,采用qPCR法检测关键基因信使核糖核酸（mRNA）水平表达。结果 共筛选得到90篇有效文献,共计91首中药复方,党参-当归-黄芪为核心药物组合。肿瘤坏死因子（TNF）、白细胞介素-6（IL-6）、白细胞介素-1β（IL-1β）、白细胞介素-10（IL-10）、JUN为核心靶点,槲皮素、木犀草素、山奈酚、芒柄花素、豆甾醇为主要有效成分,其主要作用机制可能通过癌症的途径、TNF信号通路、p53信号通路等来实现。健脾中药黄芪、党参、当归提取物和有效成分芒柄花素、槲皮素对人单核细胞白血病细胞（THP-1）具有促进增殖作用,芒柄花素对化疗诱导的THP-1细胞生长具有促进增殖的作用,芒柄花素能够抑制炎症细胞因子IL-6、IL-1β、TNF-α和刺激抗炎因子IL-10、原癌基因JUN的分泌。结论 初步揭示黄芪等多种中药通过多成分、多靶点发挥健脾作用,参与抗肿瘤、抗炎、免疫调节等相关信号通路,治疗白细胞减少症。     

心脏超声诊断数据挖掘尝试--粗糙集理论运用

本文的目的是要寻找心脏超声实测指标与心脏病变类型的关系,以建立模型,协助临床医生更科学更准确地进行诊断。但超声实测数据函数关系复杂,难以用传统的统计方法进行分析。因此本文采用粗糙集理论挖掘心脏超声实测指标与心脏病变类型的规则。结果把挖掘出的规则应用到心脏超声诊断上,取得了令人满意的效果。