Moorfields回归分析及多变量区别分析诊断开角型青光眼

目的研究Moorfields回归分析(MRA)及多变量区别分析(MDA)的2个指标FSM和RB诊断开角型青光眼的能力,及MRA在视盘整体和视盘分区间的差异。方法对23例正常人(26眼)、26例可疑开角型青光眼患者(32眼)和21例开角型青光眼患者(21眼)进行HRT-Ⅱ和OCTOPUS视野计G2-TOP程序两项检查。结果视盘整体MRA、FSM、RB与视野缺损指数间相关系数分别为0.537、-0.565、-0.716(P<0.01),且3个组间差异均有统计学意义(P<0.01),随着视盘面积增大,MRA、FSM和RB特异性均下降。可疑组中视盘分区MRA与视野检查一致率均高于整体,一致率最高分区为颞下(78.13%)。各分区中MRA敏感性、特异性最高的分区为颞上和颞下。结论MRA和MDA检测开角型青光眼能力较强,且与视野检查间存在较好的相关性,但应用于大视盘分析时须谨慎下结论。     

中期因子及MVD在胃癌中的表达及临床意义

目的探讨中期因子（midkine,MK）在胃癌组织中表达及其与微血管密度（MVD）和临床病理特征的关系,探讨影响胃癌患者长期生存的预后因素。方法应用免疫组化两步法检测107例胃癌组织中中期因子和CD34的表达,并以31例正常胃黏膜标本作对照。对CD34阳性血管进行MVD计数,并结合临床资料进行统计学分析。结合随访资料,应用Cox比例风险模型对可能影响胃癌预后结果的参数进行分析。结果胃癌组织中的中期因子阳性表达率分别为69．2％,MVD为32．74±6．46;正常胃黏膜组织中期因子0．00％,MVD为14．55±4．07,胃癌组织中中期因子表达率及MVD均明显高于正常胃黏膜组织（均P〈0．01）。中期因子表达与胃癌的大小、有无淋巴结转移、浸润深度、TNM分期有关（均P〈0．01）,而与患者年龄、性别无关。在胃癌组织中中期因子的表达与MVD呈正相关（r=0．592,P〈0．01）。MVD与胃癌的大小、浸润深度、有无淋巴结转移、TNM分期有关（均P〈0．01）。Cox单因素回归分析表明胃癌的大小、浸润深度、有无淋巴结转移、病理分期、中期因子表达与胃癌的预后有关（P〈0．05）,而性别、年龄等与预后无关（P〉0．05）。但经Cox多因素回归分析,只有肿瘤的病理分期、MK表达具有独立的预后意义（P〈0．05）。结论在胃癌组织中,中期因子的过度表达可能在肿瘤的血管生成和进展过程中起着重要作用。MK过表达可作为评估胃癌患者预后的独立指标,从而指导胃癌的治疗。     

四川省西昌市吸毒人群首次吸毒情况的调查分析

目的:调查四川省西昌市吸毒人群首次吸毒的发生情况。方法:在四川省凉山彝族自治州西昌市戒毒所、拘留所和看守所调查吸毒人员的人口学特征,吸毒前吸烟和饮酒的情况,朋友、亲戚和家人吸毒的人数,首次吸毒的时间和使用毒品的方式和种类,吸毒前是否有被治安处理或违法行为。结果:共调查了619名吸毒人员,从出生到首次吸毒的发生率为4·08/100(95%可信区间为3·76-4·40)人年。在多因素Cox比例风险模型中,15a以前开始吸烟(危险率比值为1·58;95%可信区间为1·35-1·86),朋友中吸毒的人数(朋友中有1-4人吸毒危险率比值为1·25;95%可信区间为1·04-1·51,朋友中有5人及以上吸毒危险率比值为1·71;95%可信区间为1·39-2·09)和研究对象来源(拘留所和看守所危险率比值为1·52;95%可信区间为1·18-1·96)与首次吸毒的发生率有统计学意义。结论:需进一步了解首次吸毒发生的情况及其影响因素,为开展健康教育和行为干预来预防吸毒和有关疾病的传播提供科学依据。     

地稔水提液抗氧化活性的紫外光谱快速预测方法

目的 建立基于紫外光谱和偏最小二乘回归算法的地稔水提液抗氧化活性快速预测方法.方法 采用1,1-二苯基-2-苦腈基(DPPH)自由基清除活性表征地稔水提液的抗氧化活性,采集190～600 nm的紫外光谱,通过优化光谱波长范围和预处理方法,建立抗氧化活性与紫外光谱的最优偏最小二乘回归模型.采用Visual Basic开发...     

1-取代吡唑烷酮类抗惊构效关系的研究

1-正癸基吡唑烷-3-酮(Ⅱ结构式见表1)是欧洲专利报道的一种新型减肥剂。White等报道该化合物可通过血脑屏障,并对γ-氨基丁酸氨基转移酶(GABA-T)有强烈的抑制活性,但对谷氨酸脱羧酶的抑制作用较弱,因此可引起脑内γ-氨基丁酸(GABA)水平的升高,故我们相信应有抗惊活性。经我们合成后,发现Ⅱ确有良好的抗癲痫活性,抗小鼠最大电     

灯盏细辛注射液疑似类过敏反应病例相关影响因素分析——巢式病例对照研究

灯盏细辛注射液临床不良反应主要为过敏反应,该研究基于全国20家三甲医院信息系统(hospital information system,HIS)数据库,采用巢式病例对照设计,将使用灯盏细辛注射液后使用地塞米松注射液的患者判断为 发生可疑类过敏反应者,与可能未发生过敏反应人群进行对比,应用单因素及多因素Logistic回归的方法,探讨入院病情、过敏史、单次用药剂量、疾病及合并用药与可疑类过敏反应发生的相关性。通过分析发现,入院病情对可疑类过敏反应有极显著影响,P为0.008 3, OR为5.642,在使用灯盏细辛注射液同时使用维生素B₆注射液、注射用氨溴索时也可能发生可疑类过敏反应,P分别为0.000 2,0.016 7,OR分别为9.545,3.194。基于现有HIS数据及研究方法发现,患者入院病情、使用维生素B₆注射液或注射用氨溴索可能为使用灯盏细辛注射液发生类过敏反应的危险因素,但仍需进一步研究加以验证。该研究结果可以为灯盏细辛注射液临床安全使用提供一定指导,也可为灯盏细辛注射液上市后临床安全性评价研究提供新方法。     

利用条件错误发现率方法识别抑郁症和失眠症的多效性位点

背景 抑郁症和失眠症常共病存在,两者存在一些共同的发病机制,并可能受相同的多效性基因调控。既往全基因组关联研究（GWAS）一般采用单性状研究,在解释基因多效性方面存在一定的狭窄性。目的 识别与失眠症和抑郁症相关的遗传变异位点,检验抑郁症和失眠症是否存在共同的遗传因素。方法 抑郁症GWAS数据来自精神疾病遗传学联盟（PGC）,共包含246 363例抑郁症患者和561 190例正常对照。失眠症GWAS数据来自睡眠障碍知识门户,共包含1 331 010例受试者。采用条件错误发现率（cFDR）和联合的条件错误发现率（ccFDR）方法筛选与抑郁症和失眠症相关的遗传位点,采用通路富集分析检验这些位点的生物学功能。结果 抑郁症和失眠症存在显著的多效性富集现象。利用cFDR方法,以cFDR<0.01作为显著性阈值,鉴定出21个易感位点与抑郁症相关（其中17个是新识别的）,38个易感位点与失眠症相关（其中28个是新识别的）。以ccFDR<0.05为显著性阈值,识别出16个多效性位点与抑郁症和失眠症均相关,其中15个是本研究新识别的。通路富集分析结果显示,与抑郁症和失眠症均关联的易感位点富集于突触传递相关通路,如突触后密度（GO：0014069,P=4.91E-04,FDR=4.84E-03）、不对称突触（GO：0032279,P=5.09E-0,FDR=4.84E-03）、突触后膜神经递质受体水平的调节（GO：0099072,P=5.11E-04,FDR=1.69E-02）。结论 失眠症与抑郁症之间存在多效性富集现象,其共病机制与突触传递有关。     

Assessing the Association between Important Dietary Habits and Osteoporosis: A Genetic Correlation and Two-Sample Mendelian Randomization Study

Objective: Osteoporosis (OP) is the most common bone disease. The genetic and metabolic factors play important roles in OP development. However, the genetic basis of OP is still elusive. The study aimed to explore the relationships between OP and dietary habits. Methods: This study used large-scale genome-wide association study (GWAS) summary statistics from the UK Biobank to explore potential associations between OP and 143 dietary habits. The GWAS summary data of OP included 9434 self-reported OP cases and 444,941 controls, and the GWAS summary data of the dietary habits included 455,146 participants of European ancestry. Linkage disequilibrium score regression (LDSC) was used to detect the genetic correlations between OP and each of the 143 dietary habits, followed by Mendelian randomization (MR) analysis to further assess the causal relationship between OP and candidate dietary habits identified by LDSC. Results: The LDSC analysis identified seven candidate dietary habits that showed genetic associations with OP including cereal type such as biscuit cereal (coefficient = −0.1693, p value = 0.0183), servings of raw vegetables per day (coefficient = 0.0837, p value = 0.0379), and spirits measured per month (coefficient = 0.115, p value = 0.0353). MR analysis found that OP and PC17 (butter) (odds ratio [OR] = 0.974, 95% confidence interval [CI] = (0.973, 0.976), p value = 0.000970), PC35 (decaffeinated coffee) (OR = 0.985, 95% CI = (0.983, 0.987), p value = 0.00126), PC36 (overall processed meat intake) (OR = 1.035, 95% CI = (1.033, 1.037), p value = 0.000976), PC39 (spirits measured per month) (OR = 1.014, 95% CI = (1.011, 1.015), p value = 0.00153), and servings of raw vegetables per day (OR = 0.978, 95% CI = (0.977, 0.979), p value = 0.000563) were clearly causal. Conclusions: Our findings provide new clues for understanding the genetic mechanisms of OP, which focus on the possible role of dietary habits in OP pathogenesis.     

多元回归分析大黄不同炮制品中蒽醌与抑菌活性相关性

目的:采用多元回归分析不同大黄炮制品蒽醌含量和大黄抑菌能力之间的相互关系.方法:采用HPLC法建立大黄中蒽醌的指纹图谱,流动相为乙腈-0.1％磷酸溶液梯度洗脱,检測波长为254 nm.通过大黄不同炮制样品对大肠埃希菌、金黄色葡萄球菌、铜绿假单胞菌的抑制效果来评价其抑菌活性,采用主成分、多元线性回归分析大黄不同蒽醌与抑菌...     

Explaining the Varying Patterns of COVID-19 Deaths Across the United States: 2-Stage Time Series Clustering Framework

BackgroundSocially vulnerable communities are at increased risk for adverse health outcomes during a pandemic. Although this association has been established for H1N1, Middle East respiratory syndrome (MERS), and COVID-19 outbreaks, understanding the factors influencing the outbreak pattern for different communities remains limited.ObjectiveOur 3 objectives are to determine how many distinct clusters of time series there are for COVID-19 deaths in 3108 contiguous counties in the United States, how the clusters are geographically distributed, and what factors influence the probability of cluster membership.MethodsWe proposed a 2-stage data analytic framework that can account for different levels of temporal aggregation for the pandemic outcomes and community-level predictors. Specifically, we used time-series clustering to identify clusters with similar outcome patterns for the 3108 contiguous US counties. Multinomial logistic regression was used to explain the relationship between community-level predictors and cluster assignment. We analyzed county-level confirmed COVID-19 deaths from Sunday, March 1, 2020, to Saturday, February 27, 2021.ResultsFour distinct patterns of deaths were observed across the contiguous US counties. The multinomial regression model correctly classified 1904 (61.25%) of the counties’ outbreak patterns/clusters.ConclusionsOur results provide evidence that county-level patterns of COVID-19 deaths are different and can be explained in part by social and political predictors.