Identification of key genes and pathways in discoid lupus skin via bioinformatics analysis

Discoid lupus erythematosus (DLE) is the most common skin manifestation of lupus; however, the molecular mechanisms underlying DLE remain unknown. Therefore, we aimed to identify key differentially expressed genes (DEGs) in discoid lupus skin and investigate their potential pathways.To identify candidate genes involved in the occurrence and development of the disease, we downloaded the microarray datasets {"type":"entrez-geo","attrs":{"text":"GSE52471","term_id":"52471"}}GSE52471 and {"type":"entrez-geo","attrs":{"text":"GSE72535","term_id":"72535"}}GSE72535 from the Gene Expression Database (GEO). DEGs between discoid lupus skin and normal controls were selected using the GEO2R tool and Venn diagram software (http://bioinformatics.psb.ugent.be/webtools/Venn/). The Database for Annotation, Visualization, and Integrated Discovery (DAVID), Enrichr, and Cytoscape ClueGo were used to analyze the Kyoto Encyclopedia of Gene and Genome pathways and gene ontology. Protein-protein interactions (PPIs) of these DEGs were further assessed using the Search Tool for the Retrieval Interacting Genes version 10.0.Seventy three DEGs were co-expressed in both datasets. DEGs were predominantly upregulated in receptor signaling pathways of the immune response. In the PPI network, 69 upregulated genes were selected. Furthermore, 4 genes (CXCL10, ISG15, IFIH1, and IRF7) were found to be significantly upregulated in the RIG-I-like receptor signaling pathway, from analysis of Enrichr and Cytoscape ClueGo.The results of this study may provide new insights into the potential molecular mechanisms of DLE. However, further experimentation is required to confirm these findings.     

“人工智能+X”背景下医学信息管理专业研究生培养模式

阐述当前“人工智能+X”背景下市场对医学信息管理专业人才能力的需求，分析医学信息管理专业人才培养现状，提出从重塑学科人才培养目标、优化课程内容与课程设置、建设“双师型”导师队伍、搭建多方协同共建共享在线平台及设立“政用产学研”联合培养基地等方面探索医学信息管理专业研究生培养模式，以期培养适应人工智能时代发展，具备学科优势特色的高层次、高水平、高质量的复合型、应用型、创新型人才。     

同型半胱氨酸对高血压患者脑卒中复发风险的影响

目的探讨高血压合并脑卒中患者的血浆同型半胱氨酸（Hcy）水平与其他危险因素对于脑卒中复发的影响。 方法分析徐州市中心医院心内科和徐州医科大学附属医院神经外科自2012年5月至2013年12月收治的1623例高血压脑卒中患者的基线资料，中位随访4.9年，根据随访事件中是否发生脑卒中分为复发组（312例）与未复发组（1311例）。Kaplan-Meier生存分析比较不同危险因素脑卒中复发率的差异，单因素与多因素Cox回归模型分析影响脑卒中复发的独立危险因素，以及危险因素之间的交互作用。 结果复发组年龄、空腹血糖、Lg Hcy的水平，以及糖尿病、房颤的患病率均高于未复发组（P<0.05）。Kaplan-Meier生存分析显示，糖尿病、房颤、年龄≥60岁、空腹血糖≥7.0 mmol/L、Hcy≥15 μmol/L的脑卒中复发率明显升高（Log-rank检验，P<0.05）。多因素Cox回归模型分析显示，高龄、Lg Hcy水平升高，以及房颤、糖尿病是脑卒中复发的独立危险因素。Lg Hcy分别与糖尿病、空腹血糖、年龄存在交互作用。 结论血浆Hcy水平升高既是高血压合并脑卒中患者卒中复发的独立危险因素，又通过与糖尿病、高龄、空腹血糖水平升高的交互作用显著增加脑卒中复发风险。     

健康支持性环境对四川农村人群的不同血压水平的影响分析

目的 探讨健康支持性环境中的不同特征变量对四川省农村人群的不同血压水平的影响。方法 采用多阶段整群抽样的方法，随机抽取四川省7个县（区）8400名的18岁以上常住居民为调查对象。问卷调查一般人口学特征、身体活动行为特征和环境等信息。采用标准方法测量身高、体重、腰围和血压。采用无序多分类logistic回归分析。结果 本调查人群中共检出正常高值血压者4270例，检出率为50.83%，标化率为37.02%，平均年龄（56.22±14.89）岁；高血压患者1498例，检出率为17.83%，标化率为7.92%，平均年龄（65.26±11.28）岁。无序多分类logistic回归结果显示，住宿环境好、获得运动方面的健康信息和参与中等强度活动150Symbol~A@300min/周是正常高值血压和高血压人群的共同保护因素；住宿便利（OR=0.789, 95%CI:0.649~0.958, P=0.017）、医疗服务可及性便利（OR=0.686, 95%CI:0.509~0.924, P=0.013）、对健身步道和健身广场满意为高血压人群的保护因素。结论 多途径合理构建健康支持性环境，对农村正常高值血压者和高血压患者具有保护作用，对遏制农村高血压的流行现状起到一定作用。     

2009-2019年西安市肺结核流行特征及治疗转归分析

目的 了解2009-2019年西安市肺结核的流行特征及治疗转归情况，为完善西安市肺结核防治策略提供依据。方法 收集2009-2019年《传染病信息管理系统》中登记的肺结核患者病案信息数据，通过描述性研究方法对肺结核流行病学特征和治疗转归情况进行分析。结果 2009-2019年间西安市肺结核年平均发病率为49.06/10万。郊县、郊区、城区肺结核年平均发病率分别为54.13/10万、47.46/10万和46.19/10万；男性发病率是女性的1.85倍。职业分布排在前5位的为农民（47.48%），家政、家务及待业（14.65%），离退人员（9.55%），学生（8.63%）和工人（5.23%）。利福平敏感或耐药性未知患者的成功治疗率平均为98.03%，利福平耐药患者治疗成功率为51.47%。结论 西安市近年来肺结核发病率和治疗率呈增长趋势，利福平耐药患者治疗成功率较低，要加强对重点人群的健康促进工作，加大肺结核发现力度及患者治疗管理工作。     

Unexpected Return for Follow-up During the First Year of Multidisciplinary Care May Be Predictive of Rapid Deterioration of Renal Function

Multidisciplinary predialysis education and team care (MDC) may slow the decline in renal function in patients with chronic kidney disease (CKD). However, associations between unexpected return during MDC and progression of renal dysfunction have not been characterized in patients with CKD. Our study aimed to determine the association between exacerbation of renal dysfunction and the frequency of unexpected return during follow-up.A total of 437 patients with CKD receiving multidisciplinary care between January 2009 and June 2013 at the Shin-Kong Wu Ho-Su Memorial Hospital were included in this retrospective observational cohort study, and multiple imputations were performed for missing data. The predictor was the frequency of unexpected return for follow-up during the first year after entering MDC. Main outcome was monthly declines in estimated glomerular filtration rates (eGFR). Moreover, the demographic data, comorbidities, history of medication, and routine laboratory data for patients with CKD were collected.Among all patients, 59.7% were male, the mean age at initiation of MDC was 69.4 ± 13.2 years, and the duration of follow-up was 21.4 ± 3.3 months. The subjects were divided into 2 groups according to frequencies of follow-up (≤4 and > 4 visits) during the 1st year of MDC. The patients with CKD were regularly followed up every 3 months as a part of MDC in our hospital, and patients who returned for more than 4 follow-up visits were included in the unexpected return group. In crude regression analyses, unexpected return was significantly associated with higher monthly declines of eGFR (β = 0.092, 95% confidence interval, 0.014–0.170). This association remained after adjustments for multiple variables, and subgroup analyses of unexpected return showed that male gender, older age, CKD stage 1 to 3, hypertension, history of coronary artery disease, and use of renin–angiotensin system blockade were significantly associated with declines in renal function.In conclusion, unexpected return for follow-up during the 1st year of MDC was significantly associated with the deterioration of renal function.     

替考拉宁在中国成人患者中的群体药动学研究

目的建立中国成年患者的替考拉宁(teicoplanin,TEC)群体药动学(population pharmacokinetics,PPK)模型,考察TEC药动学参数的影响因素。方法前瞻性收集139例革兰阳性球菌感染患者静脉注射TEC后的222份常规监测血药浓度和相关信息,采用一级消除的一室模型进行数据拟合,并应用非线性混合效应模型(nonlinear mixed effect model,NONMEM)程序建立PPK模型。采用Bootstrap、正态预测分布误差法(normalized predictive distribution error,NPDE)进行最终模型评价。利用蒙特卡洛模拟法对给药方案进行优化。结果确定了肌酐清除率(creatinine clearance,CLcr)、白蛋白(albumin,ALB)为影响TEC清除率的主要因素。最终模型为:CL(L·h^-1)=1.24×(CLcr/77)0.564×31/ALB;V(L)=69.2。验证表明,模型稳定、有效,且有较好的预测效能。对于不同ALB和CLcr的多数患者起始负荷剂量400 mg/q12h,iv,3次,维持剂量400~800 mg·d^-1的给药方案可达有效治疗谷浓度。严重感染者需调整负荷剂量至800 mg/q12h,iv,3次,维持剂量400~800 mg·d^-1的给药方案来确保血药浓度达到15 mg·L^-1以上。结论本实验报道了CLcr、ALB对TEC清除率有显著影响,所建模型对TEC在中国成人患者中实现个体化给药具有重要应用价值。