基于弥散张量成像的脑白质微结构分析方法在视路损伤中的应用进展

视觉通路包括视神经、视交叉、视束、视放射及视皮质。常规磁共振检查技术难以发现视路损伤后白质纤维微结构改变,眼科学检查也存在一定的局限性及主观性,且不能探测后视路的变化。弥散张量成像(diffusion tensor imaging,DTI)作为一种新兴的磁共振成像技术,通过各种后处理分析方法结合不同的参数进行分析,可提供组织的微结构信息,并能够直观显示活体白质纤维束,在无创地探索疾病的神经病理机制、评估预后方面起着重要的作用。近年来随着DTI后处理方法的不断创新,其在视路损伤中的研究越来越多。本文在介绍DTI的主要参数及常见脑白质微结构分析方法的同时,阐述了其在视路损伤研究中的应用,并进一步对各种分析方法的优缺点进行总结。     

Bayesian consensus clustering for multivariate longitudinal data

In clinical and epidemiological studies, there is a growing interest in studying the heterogeneity among patients based on longitudinal characteristics to identify subtypes of the study population. Compared to clustering a single longitudinal marker, simultaneously clustering multiple longitudinal markers allow additional information to be incorporated into the clustering process, which reveals co-existing longitudinal patterns and generates deeper biological insight. In the current study, we propose a Bayesian consensus clustering (BCC) model for multivariate longitudinal data. Instead of arriving at a single overall clustering, the proposed model allows each marker to follow marker-specific local clustering and these local clusterings are aggregated to find a global (consensus) clustering. To estimate the posterior distribution of model parameters, a Gibbs sampling algorithm is proposed. We apply our proposed model to the primary biliary cirrhosis study to identify patient subtypes that may be associated with their prognosis. We also perform simulation studies to compare the clustering performance between the proposed model and existing models under several scenarios. The results demonstrate that the proposed BCC model serves as a useful tool for clustering multivariate longitudinal data.     

Method’s corner: Allergist’s guide to network meta-analysis

Network meta-analyses (NMAs) simultaneously estimate the effects of multiple possible treatment options for a given clinical presentation. For allergists to benefit optimally from NMAs, they must understand the process and be able to interpret the results. Through a worked example published in Pediatric Allergy and Immunology, we summarize how to identify credible NMAs and interpret them with a focus on recent innovations in the GRADE approach (Grading of Recommendations Assessment, Development, and Evaluation). NMAs build on traditional systematic reviews and meta-analyses that consider only direct paired comparisons by including indirect evidence, thus allowing the simultaneous assessment of the relative effect of all pairs of competing alternatives. Our framework informs clinicians of how to identify credible NMAs and address the certainty of the evidence. Trustworthy NMAs fill a critical gap in providing key inferences using direct and indirect evidence to inform clinical decision making when faced with more than two competing courses of treatment options. This document will help allergists to identify trustworthy NMAs to enhance patient care.     

空间统计学在食品污染物分布研究中的应用

目的 以2017年某省食品安全监测大米中砷含量数据为例，探讨空间统计学方法在食品污染物分析中的应用价值。方法 采用空间点模式估计、核密度分析，全局以及局部自相关性分析等空间统计学方法，在县级空间尺度下，对某省大米中砷含量进行探索性空间数据分析。结果 空间点模式分布图显示，该省大米砷污染的空间分布比较分散，核密度分析结果显示污染热点区域主要在该省中东部地区。全局自相关Moran''s I指数值为0.11，有统计学意义，大米样品中砷污染呈现出低度空间聚集性。有1个"高-高"聚集区，2个典型的"低-低"聚集区。结论 空间统计学运用于食物污染物分布研究上，可以很好地可视化展示、识别污染分布规律、热点地区和聚集区，为基于问题的监测工作的开展提供技术支持。     

Extending multilevel spatial models to include spatially varying coefficients

Multilevel models have long been used by health geographers working on questions of space, place, and health. Similarly, health geographers have pursued interests in determining whether or not the effect of an exposure on a health outcome varies spatially. However, relatively little work has sought to use multilevel models to explore spatial variability in the effects of a contextual exposure on a health outcome. Methodologically, extending multilevel models to allow intercepts and slopes to vary spatially is straightforward. The purpose of this paper, therefore, is to show how multilevel spatial models can be extended to include spatially varying covariate effects. We provide an empirical example on the effect of agriculture on malaria risk in children under 5 years of age in the Democratic Republic of Congo.     

中药生产过程质量控制关键技术研究进展

中医药发展已上升到国家战略层面,在医药行业贯彻实施"中国制造2025"战略的新形势下,中药生产过程质量控制是中药工业需要加快突破的关键领域之一。对中药生产过程质量控制领域在工艺设计、分析检测、过程建模、制造装备等方面的关键共性问题进行解析,综述了中药生产过程质量控制体系中工艺过程理解、生产过程实时分析方法开发、过程控制策略建立3个方面的研究进展;并结合企业研究实践,介绍了质量源于设计(quality by design,Qb D)、过程分析技术(process analytical technology,PAT)、实验设计(design of experiment,DOE)、多变量统计分析等关键技术在上述3个研究方向中的应用进展,分析了实际工业应用的难点问题并对其应用前景进行展望,旨在为中药企业应用和提升生产过程质量控制技术提供参考。     

基于多元统计分析和网络药理学的五味子醋制前后质量标志物预测分析

目的基于多元统计分析和网络药理学分析预测五味子醋制前后潜在的质量标志物。方法采用UPLC-Q/TOF-MS解析生、醋五味子饮片中主要的木脂素类成分,并运用多元统计方法筛选出炮制前后潜在的差异化学成分,即化学标记物。进一步通过网络药理学以及生物信息学分析显著差异成分相关的主要作用靶点和通路,构建"成分-靶点-通路"网络关系,预测生、醋五味子潜在的质量标志物。结果筛选了五味子醋制前后差异性成分40个,其中8个为生、醋五味子之间显著性差异成分(即化学标记物)。鉴定并确认了其中的5个化学成分,分别是5-羟甲基糠醛、五味子甲素及其同分异构体、五味子乙素和五味子酯丁。而其余3个化学标记物通过解析一级、二级质谱信息,推测它们很可能也属于木脂素类成分。网络药理学分析结果表明,鉴定并确认的5个潜在质量标志物与五味子的主要药理作用密切相关。最终五味子乙素和5-羟甲基糠醛被确定为最具代表性的潜在质量标志物。结论五味子醋制前后其化学成分发生了一系列复杂的变化,经研究分析确定五味子乙素和5-羟甲基糠醛可作为五味子醋制前后代表性的潜在质量标志物,并推测木脂素类成分可能为五味子醋制保肝的重要效应物质基础。     

Agreement between blood draw techniques for assessing platelet activation by flow cytometry

It is widely believed that assays of platelet activation are susceptible to preanalytical variables related to blood draw technique. We assessed platelet activation by whole blood flow cytometry and investigated the effects of: (1) drawing blood into vacuum tubes or manually aspirated syringes, and (2) discarding the first drawn blood sample (discard tube). Platelet P-selectin expression and platelet-monocyte complexes were measured by flow cytometry under both basal conditions and following stimulation with 0.1, 1, or 10 µM ADP. Bland-Altman plots demonstrated agreement between results for vacuum tube and syringe-aspirated samples with an a priori-defined clinically relevant agreement limit of 5%. Agreement of results was also observed between discard tube and second draw samples for both vacuum-driven and manually aspirated blood. We conclude that a vacuum tube or a manually-aspirated syringe can be used when assessing platelet activation by flow cytometry and that there is no need for a discard tube.     

青海地区获得性耐药结核病产生的危险因素及其预测模型的构建

目的探讨青海地区原发性与获得性耐药结核病的危险因素及临床发病风险预测模型构建。方法选取2018年7月-2019年7月青海地区132例耐药结核病患者为观察组,青海地区132例非耐药结核病患者为对照组,查阅患者的的临床资料,并自制调查问卷,以问卷调查的方式收集患者的相关信息,分析两组患者的临床指征,采用多因素Logistic回归分析完成风险模型建立,绘制ROC曲线分析风险模型的预测效能。结果单因素结果表明:青海地区原发性与获得性耐药结核病发生率与年龄、性别、与患者接触、3月底痰涂片结果无统计学意义(P>0.05);与居住地、婚姻状况、家庭收入、治疗末痰涂片结果、体重指数、抗结核药物性肝损害、结核病灶数、结核空洞、合并糖尿病及登记分类初治具有统计学意义(P<0.05);多因素logistic结果表明:青海地区原发性与获得性耐药结核病发生率与居住地、登记分类、体重指数、抗结核药物性肝损害、3月末肺结核病灶数及痰涂片结果,具有统计学意义(P<0.05);ROC曲线结果表明:构建获得性耐药结核病发病风险预测模型用于青海地区原发性与获得性耐药结核病患者中ACU值为0.847,预测敏感性为87.46%,特异性为90.29%。结论青海地区原发性与获得性耐药结核病危险因素较多,不同因素能相互作用、相互影响,构建获得性耐药结核病发病风险预测模型,能较好的预测临床发病,有助于指导临床诊疗。