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。     

基于冰山模型构建护士综合素质测评指标体系

[目的] 基于冰山模型构建护士综合素质测评指标体系，为临床护士综合素质测评提供可视化工具。[方法] 在冰山模型的基础上，通过查阅国内外文献、小组讨论和运用德尔菲法对16名专家进行2轮专家函询，建立了系统、全面的护士综合素质测评体系。[结果] 最终确定了护士综合素质测评指标体系，包括3项一级指标，8项二级指标和31项三级指标。两轮专家有效应答率均为100%，第2轮函询专家权威系数为0.887 5，二级、三级指标的Kendall W系数分别为0.492和0.387（P<0.05）。[结论] 基于冰山模型的护士综合素质测评指标体系科学、客观、内容全面，可用于对临床护士综合素质的测评，并对其他医院护理团队建设有借鉴价值。     

师承教育在医教协同创新中医人才培养中的作用

中医师承教育是当今社会中医传承的主要方式,其培养了大量的中医优秀人才,促进中医药文化和中医学术思想传播,是现代中医药发展不可缺少的组成部分。但近代以来,人们脑海中逐渐形成了以西方医学为体系的思维模式时,中医学教育该如何的发展与传承。针对这一现象,我们分析了现代院校教育与师承教育的特点,阐述师承教育在现代中医人才培养中的作用,以期探讨高等中医药院校教育改革的模式。     

免疫性卵巢早衰模型鼠制备的时间

文题释义：免疫性卵巢早衰：近年来卵巢早衰在育龄女性中的发病率逐年上升，且向低龄化发展, 成为女性不孕的常见重要原因之一。卵巢早衰的病因复杂，很多患者(50%-60%)找不到明确的原因，迄今为止卵巢早衰的发病机制不明，临床研究显示10%-30%的卵巢早衰是由免疫因素所致，其早期诊断困难，治疗也相当棘手。因此对于免疫导致卵巢早衰的研究，已成为目前国内外研究的热点。免疫性卵巢早衰模型：免疫性卵巢早衰动物模型的建立为临床研究奠定了基础，因此需要一个建模方法简单，成功率较高，而且卵巢的形态和功能与人类卵巢早衰相似的动物模型。 背景：研究已经证实抗透明带抗体可以加速卵母细胞的破坏和耗竭而致卵巢早衰。 目的：探讨以透明带3多肽(pZP3)诱导BALB/c小鼠建立免疫性的卵巢早衰模型的时间。方法：6-8周龄的健康雌性BALB/c小鼠30只，随机分为免疫实验组(20只)和空白对照组(10只)。实验组小鼠首次免疫注射时间为0周，给予0.15 mL免疫试剂注射双足底及下腹部皮下，每日晨阴道脱落细胞涂片观察小鼠动情周期的变化；2周后给予0.15 mL免疫强化试剂皮下注射相同部位，第4周和第6周的第1天，分别注射免疫试剂或免疫强化试剂各1次(交替注射)。在每次注射前采血用酶联免疫法测小鼠血清性激素；最后观察小鼠卵巢组织及子宫形态。结果与结论：①实验组小鼠初次免疫注射及注射后2周，2组间血清促卵泡生长激素及雌激素水平差异无显著性意义；注射后4周实验组血清雌激素水平明显低于对照组，但促卵泡生长激素水平差异无显著性意义；注射后6周实验组血清雌激素水平明显低于对照组(P < 0.05)，促卵泡生长激素水平明显高于对照组(P < 0.01)；②实验组小鼠卵巢间质纤维化程度较对照组明显，卵巢体积减小，子宫萎缩，小鼠原始卵泡、初级及次级卵泡数均显著低于对照组，闭锁卵泡数量高于对照组(P < 0.05)；③结论：75 μg透明带3多肽诱导BALB/c小鼠，建立自身免疫性卵巢早衰疾病模型，免疫后6周即可达到良好的建模效果。 ORCID: 0000-0001-8035-616X(田海清) 中国组织工程研究杂志出版内容重点：组织构建；骨细胞；软骨细胞；细胞培养；成纤维细胞；血管内皮细胞；骨质疏松；组织工程     

Economic Evaluation of Factorial Trials: Cost-Utility Analysis of the Atorvastatin in Factorial With Omega EE90 Risk Reduction in Diabetes 2 × 2 × 2 Factorial Trial of Atorvastatin,Omega-3 Fish Oil,and Action Planning

ObjectivesWe applied principles for conducting economic evaluations of factorial trials to a trial-based economic evaluation of a cluster-randomized 2 × 2 × 2 factorial trial. We assessed the cost-effectiveness of atorvastatin, omega-3 fish oil, and an action-planning leaflet, alone and in combination, from a UK National Health Service perspective.MethodsThe Atorvastatin in Factorial With Omega EE90 Risk Reduction in Diabetes (AFORRD) Trial randomized 800 patients with type 2 diabetes to atorvastatin, omega-3, or their respective placebos and randomized general practices to receive a leaflet-based action-planning intervention designed to improve compliance or standard care. The trial was conducted at 59 UK general practices. Sixteen-week outcomes for each trial participant were extrapolated for 70 years using the United Kingdom Prospective Diabetes Study Outcomes Model v2.01. We analyzed the trial as a 2 × 2 factorial trial (ignoring interactions between action-planning leaflet and medication), as a 2 × 2 × 2 factorial trial (considering all interactions), and ignoring all interactions.ResultsWe observed several qualitative interactions for costs and quality-adjusted life-years (QALYs) that changed treatment rankings. However, different approaches to analyzing the factorial design did not change the conclusions. There was a ≥99% chance that atorvastatin is cost-effective and omega-3 is not, at a £20 000/QALY threshold.ConclusionsAtorvastatin monotherapy was the most cost-effective combination of the 3 trial interventions at a £20 000/QALY threshold. Omega-3 fish oil was not cost-effective, while there was insufficient evidence to draw firm conclusions about action planning. Recently-developed methods for analyzing factorial trials and combining parameter and sampling uncertainty were extended to estimate cost-effectiveness acceptability curves within a 2x2x2 factorial design with model-based extrapolation.     

断藤益母汤对类风湿关节炎成纤维样滑膜细胞MEKK2及CIA小鼠关节炎的影响

目的:为了研究断藤益母汤(DTYMD)在类风湿关节炎中对丝裂原活化蛋白激酶(MAPK)上游激酶的调控作用,阐明DTYMD抗炎的分子机制。方法:培养成纤维样滑膜细胞,将细胞分为空白组,模型组,DTYMD高、中、低质量浓度组(1 000,800,600 mg·l~(-1)),甲氨蝶呤(MTX)组(20μmol·l~(-1))组,采用蛋白免疫印迹法(Western blot),实时荧光定量聚合酶链式反应(Real-time PCR)对丝分裂原活化蛋白激酶激酶激酶2(MEKK2)的蛋白和mRNA表达进行分析。将42只雄性DBA/1J小鼠随机分为6组,每组7只,分别为正常组,模型组,MTX组(2 mg·kg~(-1)),DTYMD低、中、高剂量组(6. 25,12. 5,25 mg·kg~(-1))。除正常组外,其他5组均采用二次免疫法构建胶原诱导型关节炎(CIA)模型。给药结束后,取小鼠后肢踝关节行苏木素-伊红(HE)染色并进行关节病理评分。结果:与模型组比较,DTYMD以浓度依赖方式抑制成纤维样滑膜细胞活性(P 0. 01);与空白组比较,模型组细胞增殖率升高(P 0. 01)。与模型组比较,DTYMD高、中质量浓度组降低MEKK2蛋白及mRNA的表达(P 0. 05,P 0. 01)。与模型组比较,DTYMD不同剂量组均降低细胞基质金属蛋白酶-1(MMP-1),肿瘤坏死因子-α(TNF-α),白细胞介素-6(IL-6)的表达(P 0. 01);与空白组比较,模型组MMP-1,IL-6,TNF-α表达明显上升(P 0. 05,P 0. 01)。在动物实验中,与模型组比较,DTYMD高、中剂量组可以降低CIA小鼠关节肿胀度(P 0. 05,P 0. 01);与正常组比较,模型组小鼠二次免疫后关节明显肿胀(P 0. 05)。在CIA小鼠踝关节HE染色中,与空白组比较,模型组小鼠病理学评分升高(P 0. 01);与模型组比较,DTYMD高、中剂量小鼠关节病理评分明显下降(P 0. 05,P 0. 01)。结论:DTYMD可能通过下调MEKK2对细胞因子IL-6,TNF-α,MMP-1负性调控,从而缓解类风湿关节炎的炎症反应。     

Brief digital sleep questionnaire powered by machine learning prediction models identifies common sleep disorders

IntroductionWe developed and validated an abbreviated Digital Sleep Questionnaire (DSQ) to identify common societal sleep disturbances including insomnia, delayed sleep phase syndrome (DSPS), insufficient sleep syndrome (ISS), and risk for obstructive sleep apnea (OSA).MethodsThe DSQ was administered to 3799 community volunteers, of which 2113 were eligible and consented to the study. Of those, 247 were interviewed by expert sleep physicians, who diagnosed ≤2 sleep disorders. Machine Learning (ML) trained and validated separate models for each diagnosis. Regularized linear models generated 15–200 features to optimize diagnostic prediction. Models were trained with five-fold cross-validation (repeated five times), followed by robust validation testing. ElasticNet models were used to classify true positives and negatives; bootstrapping optimized probability thresholds to generate sensitivities, specificities, accuracies, and area under the receiver operating curve (AUC).ResultsCompared to reference subgroups, physician-diagnosed sleep disorders were marked by DSQ evidence of sleeplessness (insomnia, DSPS, OSA), sleep debt (DSPS, ISS), airway obstruction during sleep (OSA), blunted circadian variability in alertness (DSPS), sleepiness (DSPS and ISS), increased alertness (insomnia) and global impairment in sleep-related quality of life (all sleep disorders). ElasticNet models validated each diagnosis with high sensitivity (80–83%), acceptable specificity (63–69%), high AUC (0.80–0.85) and good accuracy (agreement with physician diagnoses, 68–73%).DiscussionA brief DSQ readily engaged and efficiently screened a large population for common sleep disorders. Powered by ML, the DSQ can accurately classify sleep disturbances, demonstrating the potential for improving the sleep, health, productivity and safety of populations.