Interferon-induced Transmembrane Protein 3 Prevents Acute Influenza Pathogenesis in Mice

Objective Interferon-induced transmembrane protein 3(IFITM3) is an important member of the IFITM family. However, the molecular mechanisms underlying its antiviral action have not been completely elucidated. Recent studies on IFITM3, particularly those focused on innate antiviral defense mechanisms, have shown that IFITM3 affects the body's adaptive immune response. The aim of this study was to determine the contribution of IFITM3 proteins to immune control of influenza infection in vivo.Methods We performed proteomics, flow cytometry, and immunohistochemistry analysis and used bioinformatics tools to systematically compare and analyze the differences in natural killer(NK) cell numbers, their activation, and their immune function in the lungs of Ifitm3-/-and wild-type mice.Results Ifitm3-/-mice developed more severe inflammation and apoptotic responses compared to wild-type mice. Moreover, the NK cell activation was higher in the lungs of Ifitm3-/-mice during acute influenza infection.Conclusions Based on our results, we speculate that the NK cells are more readily activated in the absence of IFITM3, increasing mortality in Ifitm3-/-mice.     

社区“5+1”糖尿病分阶段达标管理对2型糖尿病患者生存质量干预效果分析

目的 分析社区"5+1"糖尿病分阶段达标管理对2型糖尿病患者生存质量的干预效果及其影响因素，为提高患者生存质量提供依据。方法 采用分层整群抽样的方法在山西省、江苏省和宁夏回族自治区选择12个社区卫生服务中心，分别作为干预组（管理方式：社区"5+1"糖尿病分阶段达标管理）、对照组[管理方式：依据《国家基本公共卫生服务规范（2011年版）》的相关要求]，进行为期2年的随访观察。采用面对面问卷调查的方式，收集患者的人口学信息等基本信息；采用健康调查简表（SF-36）对患者在干预前后测量生存质量。采用SAS 9.4软件进行双重差分法以及多重线性回归模型分析。结果 基线时共纳入2 467名研究对象，终末时共1 924人接受了为期2年完整的随访管理。干预后，干预组、对照组患者生理健康维度（PCS）、心理健康维度（MCS）评分变化净差值分别为13.6分、29.8分。多重线性回归分析结果显示，影响患者PCS得分的主要因素有年龄、医保类型、基线PCS得分以及所在地区，影响患者MCS得分的主要因素有年龄、医保类型、基线MCS得分、是否合并高血压以及所在地区。结论 社区"5+1"糖尿病分阶段达标管理对2型糖尿病患者生存质量的干预效果较好。     

The Health Belief Model in predicting healthcare workers' intention for influenza vaccine uptake in Jordan

BackgroundTheories of health behavior change are being inadequately adopted to understand the reasons behind low influenza vaccination rates among healthcare workers (HCWs). The Theory of Planned Behavior (TPB) is being used to predict intention-behavior relationship while the Health Belief Model (HBM) is being employed to predict actual behavior. The purpose of this study was to test a conceptual model based on the HBM’s constructs to predict Jordanian HCWs’ intentions for influenza vaccine uptake as an alternative to the TPB.MethodA cross-sectional questionnaire-based study was conducted in 2016 in a tertiary teaching hospital in Amman-Jordan including a convenience sample of 477 HCWs with direct patient contact. The study instrument was tested for validity and reliability. A conceptual regression model was proposed incorporating the constructs of the primary HBM with some modifications in the threat construct as well as an additional variable about explicit past vaccination behavior (in the past year and/or any previous history of influenza vaccine uptake).ResultsAlmost all the constructs of the HBM demonstrated significant differences between participants intending and those who did not intend to vaccinate against influenza. After adjusting for the confounding variables in the final conceptual regression model, past vaccination behavior (OR= 4.50, 95%Confidence Interval 3.38–6.00, P< 0.0005) and the perceived benefit scale (OR= 1.19, 95% Confidence Interval 1.11–1.28, P< 0.0005) were the only significant predictors of intentions to vaccinate against influenza in the next season.ConclusionTaking into consideration the altruistic beliefs of HCWs and their explicit past vaccination history augments the utility of the original HBM tool in predicting HCWs’ intentions to vaccinate against influenza in a way that is consistent with the predictive ability of the Theory of Planned Behavior.     

微滴式数字PCR和实时荧光定量PCR对新型冠状病毒肺炎患者不同时间血便尿中核酸检测结果初步探讨

目的 分析微滴式数字PCR(droplet digital PCR, ddPCR)和实时荧光定量PCR(quantitative real-time PCR,qPCR)的核酸检测结果,比较两种方法检测各类样本的差异性,为改进新型冠状病毒核酸检测方案提供数据支持。 方法 利用ddPCR和qPCR技术对已经确诊的3例新型冠状病毒肺炎患者发病不同时间的全血、尿液、粪便共22份标本进行新型冠状病毒核酸检测。 结果 两种方法对人保守区域基因扩增结果一致:全血标本信号最强,尿液次之,粪便最少;ddPCR在1份全血,1份尿液,5份粪便中检出ORF-1ab和N基因的阳性微滴,qPCR仅在3份粪便中检出上述基因,漏检的3个标本基因拷贝数平均浓度为128 copies/ml;ddPCR在发病<5、5~15、>15 d的各类标本中都有检出,qPCR检出以中晚期为主;重症病例用ddPCR均可测到阳性微滴,qPCR检测的各类标本均为阴性;轻症病例的各类标本中qPCR只有粪便核酸检测阳性,ddPCR检出率高于qPCR。 结论 ddPCR可以有效克服qPCR 灵敏度不足的难题,是对qPCR 的有益补充,尤其是针对病毒载量比较低的血液、尿液和可疑的粪便或肛拭子标本,适用于早期感染的判断及患者治愈后出院诊断。     

An assessment of population-based screening guidelines versus clinical prediction rules for chlamydia and gonorrhea case finding

IntroductionMuch remains to be learned regarding the epistemology and utility of guidelines and clinical prediction rules (CPR), as well as the extent to which knowledge about risk at a population level might be pertinent to any given patient in terms of case finding accuracy. In the current paper, we offer an empirical examination that juxtaposes population-based guidelines and CPR for sexual health decision-making.Materials and methodsWe analyzed electronic medical records from asymptomatic patient visits involving tests for chlamydia or gonorrhea between 2000 and 2012 at nine publicly funded STI clinics in British Columbia to compare the case-finding accuracy for infection risk under two scenarios: (1) if the population had been screened using the Public Health Agency of Canada (PHAC) screening guidelines for chlamydia and gonorrhea; or (2) if the population has been screened using a CPR. Performance metrics evaluated included the area under the ROC curve (AUC).ResultsIn total, 35,818 individuals met the study inclusion criteria. The overall infection rate was 3.0%. Using the PHAC guidelines, the discriminatory performance of using any versus no risk factors and counts of risk factors were: AUC = 0.55, 95% CI: 0.54–0.56 and AUC = 0.64, 95% CI: 0.63–0.66, respectively. The model used to derive the CPR demonstrated good discrimination (AUC = 0.73, 95% CI: 0.71–0.74).ConclusionsThe current paper provides empirical evidence that demonstrates that population-based guidelines may not necessarily be a perfect fit for application at the individual level. Thus, we recommend risk estimation algorithms for use in sexual health services and programs.