2019冠状病毒病(COVID-19)基于推荐诊疗方案的中医用药特点分析

目的分析国家卫生健康委员会（卫健委）、国家中医药管理局（中管局）及各省市自治区卫健委、中管局通过公开渠道发布的2019冠状病毒病（COVID-19）治疗方案中中医药处方用药特点。方法收集自我国COVID-19疫情发生以来至2020年2月19日国家及各省市自治区卫健委、中管局通过公开渠道发布的COVID-19推荐诊疗方案中中医药相关内容，并进行所有数据的频数分析、关联分析和聚类分析。结果共收集国家诊疗方案4个，各省市自治区防治方案34个，样本578条，得到有名称的传统方剂84首，中成药60种，涉及单味药230味。高频用药有甘草、黄芩、杏仁、石膏等，常见方剂有麻杏石甘汤、银翘散、宣白承气汤等，常用中成药有安宫牛黄丸、血必净注射液、连花清瘟胶囊等，高频药对有“麻黄，杏仁”“连翘，甘草”等，挖掘出核心药物组合2个，新处方1个。结论COVID-19卫分证以银翘散、藿朴夏苓汤为基础方，气分证可以麻杏石甘汤、凉膈散、清瘟败毒饮、达原饮等为基础方。用药特点以宣肺清热、解毒祛浊为主，体现中医治疫解毒透邪的处方思路。     

PROTEIN DISULFIDE ISOMERASE LIKE 5-1 is a susceptibility factor to plant viruses

Protein disulfide isomerases (PDIs) catalyze the correct folding of proteins and prevent the aggregation of unfolded or partially folded precursors. Whereas suppression of members of the PDI gene family can delay replication of several human and animal viruses (e.g., HIV), their role in interactions with plant viruses is largely unknown. Here, using a positional cloning strategy we identified variants of PROTEIN DISULFIDE ISOMERASE LIKE 5–1 (HvPDIL5-1) as the cause of naturally occurring resistance to multiple strains of Bymoviruses. The role of wild-type HvPDIL5-1 in conferring susceptibility was confirmed by targeting induced local lesions in genomes for induced mutant alleles, transgene-induced complementation, and allelism tests using different natural resistance alleles. The geographical distribution of natural genetic variants of HvPDIL5-1 revealed the origin of resistance conferring alleles in domesticated barley in Eastern Asia. Higher sequence diversity was correlated with areas with increased pathogen diversity suggesting adaptive selection for bymovirus resistance. HvPDIL5-1 homologs are highly conserved across species of the plant and animal kingdoms implying that orthologs of HvPDIL5-1 or other closely related members of the PDI gene family may be potential susceptibility factors to viruses in other eukaryotic species.Infectious diseases caused by plant viruses threaten agricultural productivity and reduce globally attainable agricultural production by about 3% (1). In specific pathosystems, plant viruses can result in the loss of the entire crop. For example, the devastation of cassava production by cassava mosaic geminiviruses (CMGs) in Uganda during the 1990s led to widespread food shortages and famine-related deaths (2). Unfortunately protecting plants against viruses (especially soil-borne viruses) by using agrochemicals to control virus vectors is seldom efficient from economic or ecological perspectives. Therefore, crop protection based on naturally occurring virus resistance is key to minimizing losses and achieving sustainable crop yields.Positive-strand RNA viruses represent the largest group of plant viruses (3). They cause a very high proportion of the important infectious virus diseases in agriculture (4, 5). Such plant viruses carry a reduced genome that encodes a limited set of functional proteins (4–10 viral proteins)—insufficient to complete the entire virus replication and proliferation cycle (6). Instead, over evolutionary time, viruses recruited host factors to perform the infectious life cycle (7). This dependence on host factors establishes a possibility that plants can evolve escape, tolerance, or resistance mechanisms to ameliorate the consequences of viral infection. The absence of essential host factors could interfere with the infection process or restrict proliferation (8) leading to either mono- or polygenic recessive resistance (5). Prominent examples of such susceptibility factors that are conserved in multiple plant–virus systems are the EUKARYOTIC TRANSLATION INITIATION FACTORS (EIF)4E, iso4E, 4G, and iso4G (9). Translation initiation factors may interact directly with viral RNA where they catalyze the initiation of translation of viral polyproteins (10, 11). In addition, to establish replication and assembly complexes during infection, viruses typically create membrane-bound environments, referred to as “virus factories” (12). There, cellular chaperones such as HSP70 and DNAJ-like proteins likely contribute to the correct folding and translocation of substrates (12, 13). However, only a few such host factors are known (7, 9, 14).Barley yellow mosaic virus disease caused by barley yellow mosaic virus (BaYMV) and barley mild mosaic virus (BaMMV) (both belong to Bymoviruses) seriously threatens winter barley production in Europe and East Asia (4). Infection leads to yellow discoloration and stunted growth and may result in yield loss of up to 50% (15). Soil-borne transmission via the plasmodiophorid Polymyxa graminis prohibits plant protection by chemical measures, and breeding for resistant cultivars is therefore the only practicable way to prevent yield loss. The naturally occurring recessive resistance locus rym11 confers complete broad-spectrum resistance to all known European isolates of BaMMV and BaYMV (16–19). In the present study, we used a positional cloning strategy to identify the gene underlying rym11-based resistance. We show that it is a susceptibility factor belonging to a gene family of PROTEIN DISULFIDE ISOMERASES (PDIs), and is highly conserved across eukaryotic species. We observe a strong correlation between natural allelic variation and geographic distribution, suggesting that both the origin and subsequent adaptive selection for rym11-based resistance in winter barley occurred in East Asia.     

高血压患者高额住院费用的影响因素

目的基于高血压患者住院费用的影响因素,挖掘各因素与高额住院费用之间的关联规则,为减轻患者就医负担提供参考。方法收集山西省太原市8所医院2017年高血压住院患者信息,在多元线性逐步回归筛选出住院费用影响因素的基础上,利用Apriori算法挖掘各因素与高额住院费用之间潜在的强关联规则。结果多元线性回归结果显示住院天数对高血压患者住院费用的影响最大(β=0.490,P<0.001);关联规则模型挖掘出的12条与高额住院费用相关联的强规则中10条均与住院天数有关,满足规则前项条件的患者产生高额住院费用的概率均为原来的2倍以上。结论挖掘出的强关联规则提示,高血压患者发生高额住院费用主要来源于住院天数。     

针刺治疗青少年近视眼中的数据清洗技术

本文以数据清洗在针刺治疗青少年近视眼疗效评价中的实际应用为目的,对可能影响数据挖掘结果的源数据及其可能产生的噪声情况进行了分析,并结合研究领域现有的知识,通过改进算法,实现在属性级别上对噪声数据的处理,并且通过实例用关联规则来进行模式识别、实施数据清洗。     

Quality assessment of data discrimination using self-organizing maps

MotivationOne of the important aspects of the data classification problem lies in making the most appropriate selection of features. The set of variables should be small and, at the same time, should provide reliable discrimination of the classes. The method for the discriminating power evaluation that enables a comparison between different sets of variables will be useful in the search for the set of variables.ResultsA new approach to feature selection is presented. Two methods of evaluation of the data discriminating power of a feature set are suggested. Both of the methods implement self-organizing maps (SOMs) and the newly introduced exponents of the degree of data clusterization on the SOM. The first method is based on the comparison of intraclass and interclass distances on the map. Another method concerns the evaluation of the relative number of best matching unit’s (BMUs) nearest neighbors of the same class. Both methods make it possible to evaluate the discriminating power of a feature set in cases when this set provides nonlinear discrimination of the classes.AvailabilityCurrent algorithms in program code can be downloaded for free at http://mekler.narod.ru/Science/Articles_support.html, as well as the supporting data files.     

Procedure prediction from symbolic Electronic Health Records via time intervals analytics

Prediction of medical events, such as clinical procedures, is essential for preventing disease, understanding disease mechanism, and increasing patient quality of care. Although longitudinal clinical data from Electronic Health Records provides opportunities to develop predictive models, the use of these data faces significant challenges. Primarily, while the data are longitudinal and represent thousands of conceptual events having duration, they are also sparse, complicating the application of traditional analysis approaches. Furthermore, the framework presented here takes advantage of the events duration and gaps. International standards for electronic healthcare data represent data elements, such as procedures, conditions, and drug exposures, using eras, or time intervals. Such eras contain both an event and a duration and enable the application of time intervals mining – a relatively new subfield of data mining. In this study, we present Maitreya, a framework for time intervals analytics in longitudinal clinical data. Maitreya discovers frequent time intervals related patterns (TIRPs), which we use as prognostic markers for modelling clinical events. We introduce three novel TIRP metrics that are normalized versions of the horizontal-support, that represents the number of TIRP instances per patient. We evaluate Maitreya on 28 frequent and clinically important procedures, using the three novel TIRP representation metrics in comparison to no temporal representation and previous TIRPs metrics. We also evaluate the epsilon value that makes Allen’s relations more flexible with several settings of 30, 60, 90 and 180 days in comparison to the default zero. For twenty-two of these procedures, the use of temporal patterns as predictors was superior to non-temporal features, and the use of the vertically normalized horizontal support metric to represent TIRPs as features was most effective. The use of the epsilon value with thirty days was slightly better than the zero.     

Dissociating retrieval interference and reanalysis in the P600 during sentence comprehension

We investigated the relative independence of two key processes in language comprehension, as reflected in the P600 ERP component. Numerous studies have linked the P600 to sentence‐ or message‐level reanalysis; however, much research has shown that skilled, cue‐based memory retrieval operations are also important to successful language processing. Our goal was to identify whether these cue‐based retrieval operations are part of the reanalysis processes indexed by the P600. To this end, participants read sentences that were either grammatical or ungrammatical via subject‐verb agreement violations, and in which there was either no possibility for retrieval interference or there was an attractor noun interfering with the computation of subject‐verb agreement (e.g., “The slogan on the political poster(s) was/were …”). A stimulus onset asynchrony manipulation (fast, medium, or slow presentation rate) was designed to modulate participants' ability to engage in reanalysis processes. Results showed a reliable attraction interference effect, indexed by reduced behavioral sensitivity to ungrammaticalities and P600 amplitudes when there was an opportunity for retrieval interference, as well as an effect of presentation rate, with reduced behavioral sensitivity and smaller P600 effects at faster presentation rates. Importantly, there was no interaction between the two, suggesting that retrieval interference and sentence‐level reanalysis processes indexed by the P600 can be neurocognitively distinct processes.