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。     

Medication Adherence App for Food Pantry Clients With Diabetes: A Feasibility Study

Low-income food pantry clients are unable to adhere to the diet and physical activity recommendations of the American Diabetes Association. The aim of the study is to test the feasibility of using a mobile phone app to improve diabetes medication adherence. Clients with uncontrolled type 2 diabetes were enrolled in a mobile phone app featuring 70 days of text message reminders and incentives. The app and the 4-item Morisky Medication Adherence Scale evaluated medication adherence. Clinically significant medication adherence of 93% was achieved with use of the app. Phone app use is feasible among urban low-income clients to improve medication adherence.     

Evaluating alcohol and marijuana use among emerging adult males via analysis of text messages

Background: Advances in social technologies offer new tools for large scale data collection and analysis of peer influence and social networks on substance use attitudes and behaviors. Objective: The objective of this study was to determine if text message content can predict alcohol and marijuana use attitudes and behaviors. Methods: Text messages from 91 males ages 18–25 were monitored over a period of 6 months and examined for content related to alcohol and marijuana. Self-report data indicating alcohol and marijuana use attitudes and behaviors were used to determine relationships between text message content, social network structure, and substance use attitudes and behaviors. Results: In total, 23,173 text messages were analyzed with 166 text messages including alcohol related terms and 195 text messages including drug related terms. Individuals who sent text messages related to alcohol use were more likely to have problem alcohol use and positive attitudes toward alcohol use, and individuals who sent text messages related to marijuana use reported higher frequency of marijuana use and more positive attitudes toward marijuana use. Individuals with multiple daily marijuana use were in positions that had less control over network structure. Conclusions: The results of this study indicate that monitoring text message content and social network structure among emerging adult males can potentially predict alcohol and marijuana use attitudes and behaviors. Text message content analysis is a novel technique increasing our understanding of the role of peer influence and social network on substance use attitudes and behaviors.     

The Effects of Text Message and Infographic on Reducing the Number Cigarettes Consumption: A Randomized Controlled Trial

Objective: To test the effect of a text-message and infographic to promote smokers quit smoking. Methods: A randomized control trial was conducted in two provinces of northeast Thailand. Three hundred and ninety-six participants were allocated to either a text-message and infographic group or a control group. We assessed the primary outcome by self-reported 7-day point prevalence smoking abstinence. Multiple logistic regression was used to test the effect of quitting smoking. Results: At 3-month follow-up, lost to follow-up 16 participants, 380 participants were included for analysis. The difference in the rate of quitting smoking between the intervention and control groups was not found a statistical significance (17.8% versus 11.6%). However, we found a statistically significant difference in the number of cigarettes smokes (the difference: -1.74; 95%CI: -2.63, -0.84).Conclusion: No effect of text message and infographic for help smokers to quit smoking. However, the intervention showed a decrease in the number of cigarettes smoked.     

INAUGURAL ARTICLE by a Recently Elected Academy Member:Lexical shifts,substantive changes,and continuity in State of the Union discourse, 1790–2014

This study reveals that the entry into World War I in 1917 indexed the decisive transition to the modern period in American political consciousness, ushering in new objects of political discourse, a more rapid pace of change of those objects, and a fundamental reframing of the main tasks of governance. We develop a strategy for identifying meaningful categories in textual corpora that span long historic durées, where terms, concepts, and language use changes. Our approach is able to account for the fluidity of discursive categories over time, and to analyze their continuity by identifying the discursive stream as the object of interest.When did modern political discourse emerge in the United States? What is distinctive of basic understandings of the tasks of governance today, in contrast to those that organized the politics of an earlier period? Can the origins of contemporary political understandings be located in the discourse of the past? The annual State of the Union address (hereafter, SoU), in which the US president reports broadly on the progress and challenges of his administration, provides a singular standpoint from which to address the evolution of the tasks of governance. It can thus be used to investigate old questions like those above using network-based text analysis strategies.This study reveals that the entry into World War I (WWI) in 1917 indexed the decisive transition to the modern period in American political consciousness, ushering in new objects of political discourse, a more rapid pace of change of those objects, and a fundamental reframing of the main tasks of governance. At the same time, this study demonstrates that discourse distinctive to modern politics, although it later crystalized around the liberal welfare state, in fact emerged before the transition to the modern period.We offer a unique view of American political history, which tracks the articulation of the major tasks of governance in American political and social discourse. To do so, we develop a strategy for identifying meaningful categories in textual corpora that span long historic durées. We are able to account for the fluidity of discursive categories over time, and to analyze their continuity by identifying the discursive stream as the object of interest. The methodological approach developed in this article can be used to meaningfully analyze texts produced over very long historical periods, where terms, concepts, and language use changes—to our knowledge, a problem not satisfactorily solved.     

何首乌“九蒸九晒”炮制工艺优选及对L02肝细胞生长的影响

目的探索何首乌"九蒸九晒"最佳炮制工艺及不同炮制品对正常人L02肝细胞生长的影响。方法选择蒸制时间、炮制次数、晒制时间3个因素,采用L9(34)正交试验,以二苯乙烯苷、游离蒽醌、结合蒽醌含量为考察指标,优选炮制工艺;以细胞抑制率为评价指标,考察何首乌不同炮制品对L02肝细胞生长的影响。结果优选的何首乌"九蒸九晒"最佳炮制工艺为:蒸制4 h,晒制4 h,蒸晒11次。优选炮制品的肝细胞抑制率为2.86%,药典法炮制品的肝细胞抑制率为23.67%。结论本研究优选的何首乌"九蒸九晒"炮制工艺结果可靠,评价指标可控,所得炮制品的肝细胞抑制率低于药典法炮制品。     

Automating the generation of lexical patterns for processing free text in clinical documents

Objective Many tasks in natural language processing utilize lexical pattern-matching techniques, including information extraction (IE), negation identification, and syntactic parsing. However, it is generally difficult to derive patterns that achieve acceptable levels of recall while also remaining highly precise.Materials and Methods We present a multiple sequence alignment (MSA)-based technique that automatically generates patterns, thereby leveraging language usage to determine the context of words that influence a given target. MSAs capture the commonalities among word sequences and are able to reveal areas of linguistic stability and variation. In this way, MSAs provide a systemic approach to generating lexical patterns that are generalizable, which will both increase recall levels and maintain high levels of precision.Results The MSA-generated patterns exhibited consistent F1-, F.5-, and F2- scores compared to two baseline techniques for IE across four different tasks. Both baseline techniques performed well for some tasks and less well for others, but MSA was found to consistently perform at a high level for all four tasks.Discussion The performance of MSA on the four extraction tasks indicates the method’s versatility. The results show that the MSA-based patterns are able to handle the extraction of individual data elements as well as relations between two concepts without the need for large amounts of manual intervention.Conclusion We presented an MSA-based framework for generating lexical patterns that showed consistently high levels of both performance and recall over four different extraction tasks when compared to baseline methods.