抗γ-氨基丁酸B型受体脑炎五例分析

目的:探讨抗γ-氨基丁酸B型受体(GABA BR)脑炎患者的临床特点、治疗及预后。方法:回顾性总结2017年9月至2019年6月香港大学深圳医院神经内科诊治的5例抗GABA BR脑炎病例,分析其临床资料、辅助检查、治疗经过,随访3.5~23.0个月并评估预后。结果:5例抗GABA BR脑炎患者(19~81岁)均急性起病,以难治性癫痫为主要临床表现,其中4例颅脑磁共振成像显示颞叶及海马为主的T 2/液体衰减反转恢复序列高信号。脑电图均提示慢波或癫痫样放电。4例肺部发现占位,病理均确诊为小细胞肺癌。5例接受一线免疫抑制治疗(激素联合丙种球蛋白或血浆置换)效果均欠佳,3例接受了二线免疫治疗(利妥昔单抗、环磷酰胺),其中2例合并肿瘤者同时接受了肿瘤治疗,接受二线治疗及肿瘤治疗的患者疗效明显好于单纯一线治疗者。结论:抗GABA BR脑炎主要表现为以难治性癫痫为特征的边缘性脑炎综合征。一线治疗效果欠佳的抗GABA BR脑炎尽快启动二线治疗可明显改善预后。     

血脑屏障通透性与接受溶栓的急性脑梗死患者预后的相关性

目的 探讨血脑屏障通透性与接受溶栓治疗的急性脑梗死患者预后的相关性。方法 纳入绵阳市盐亭县人民医院在2018年5月-2019年5月收治的急性脑梗死且接受溶栓治疗的患者共76例,随访3个月,根据预后情况分为预后良好组和预后不佳组,比较2组患者临床资料、实验室检查指标水平、血脑屏障通透性等。结果 所有研究对象随访3个月后共有8例患者失访,其中mRs评分为良好(0～1分)共32例,为预后良好组,余为预后不佳组(2～6分)共36例; 2组患者性别、BMI、梗死部位、冠心病史、高血压病史、糖尿病史、高脂血症史、脑卒中史、发病时间、吸烟史、饮酒史、家族史、应用药物、基线NIHSS评分、Cr,BUN,HDLc,LDLc,PLT,HGB,APTT,DD、空腹血糖、糖化血红蛋白水平均无明显差异(P>0.05); 预后良好组患者年龄、房颤史的比例、UA水平与预后不佳组比较均有明显差异(P<0.05); 2组患者AUC无明显差异(P>0.05); 预后良好组患者K_trans及V_P与预后不佳组比较均有明显差异(P<0.05); 进行logistics回归分析显示年龄(OR=1.190,P=0.026)、K_trans(OR=1.104,P=0.005)为预后不佳的危险因素,V_P(OR=0.556,P=0.022)为保护因素。结论 血脑屏障通透性为影响接受溶栓治疗的急性脑梗死患者预后的相关因素。     

靶向测序诊断黑棘皮病1家系

【摘要】 报道临床症状不典型的家族性黑棘皮病1家系。先证者女，4岁，自1周岁时，颈部、腹部出现黑色斑片，近年来逐渐扩大至唇周、躯干前部。腹部皮肤全反式共聚焦显微镜检查可见乳头环下延扭曲及沟壑结构，乳头环内可见中高折光颗粒结构。先证者父亲及祖母既往有类似病史，但随着年龄增长色素沉着自发性消退，仅有局部皮纹增粗。采集先证者及父母、祖母外周血，对先证者外周血DNA行Panel靶向测序，结果显示，先证者存在FGFR3基因14号外显子c.1949A>C（p.Lys650Thr）错义突变，Sanger测序验证证实先证者及其父亲和祖母均存在此突变。诊断：家族性黑棘皮病。     

新型冠状病毒感染的肺炎疫情医疗废物应急处置管理实践——以重庆市为例

新型冠状病毒感染的肺炎(COVID-19)具有传播速度快、波及范围广和病死率较高等特点。加强新型冠状病毒肺炎疫情期间医疗废物管理是生态环境系统守好疫情防控的最后一道防线。以重庆市为例,分析疫情期间医疗废物应急处置管理现状,找准应急处置和管理过程存在的问题,从应急处置管理认识、处置政策、处置技术、处置监管、处置评估、应急价格、应急宣传等7方面提出应对具有高感染性病毒疫情废物管理的建议。     

Parameter Transfer Deep Neural Network for Single-Modal B-Mode Ultrasound-Based Computer-Aided Diagnosis

Elastography ultrasound (EUS) imaging has shown its effectiveness for diagnosis of tumors by providing additional information about tissue stiffness to the conventional B-mode ultrasound (BUS). However, due to the lack of EUS devices and experienced sonologists, EUS is not widely used, especially in rural areas. It is still a challenging task to improve the performance of the single-modal BUS-based computer-aided diagnosis (CAD) for tumors. In this work, we propose a novel transfer learning (TL)–based deep neural network (DNN) algorithm, named CW-PM-DNN, for the BUS-based CAD by transferring diagnosis knowledge from EUS during model training. CW-PM-DNN integrates both the feature-level and classifier-level knowledge transfer into a unified framework. In the feature-level TL, a bichannel DNN is learned by the cross-weight-based multimodal DL (MDL-CW) algorithm to transfer informative features from EUS to BUS. In the classifier-level TL, a projective model (PM)–based classifier is then embedded to the pretrained bichannel DNN to implement the parameter transfer in the classifier model at the second stage. The back-propagation procedure is then applied to optimize the whole CW-PM-DNN to further improve its performance. Experimental results on two bimodal ultrasound tumor datasets demonstrate that the proposed CW-PM-DNN achieves the best classification accuracy, sensitivity, and specificity of 89.02 ± 1.54%, 88.37 ± 4.72%, and 89.63 ± 4.06%, respectively, for the breast ultrasound dataset, and the corresponding values of 80.57 ± 3.41%, 76.67 ± 3.85%, and 83.94 ± 3.95%, respectively, for the prostate ultrasound dataset. The proposed two-stage TL-based CW-PM-DNN algorithm outperforms all the compared algorithms. It is also proved that the performance of the BUS-based CAD can be significantly improved by transferring the knowledge of EUS. It suggests that CW-PM-DNN has the potential for more applications in the field of medical image–based CAD.

     

Effective Two-Level Domain Decomposition Preconditioners for Elastic Crack Problems Modeled by Extended Finite Element Method

In this paper, we propose some effective one- and two-level domain decomposition preconditioners for elastic crack problems modeled by extended finite element method. To construct the preconditioners, the physical domain is decomposed into the "crack tip" subdomain, which contains all the degrees of freedom (dofs) of the branch enrichment functions, and the "regular" subdomains, which contain the standard dofs and the dofs of the Heaviside enrichment function. In the one-level additive Schwarz and restricted additive Schwarz preconditioners, the "crack tip" subproblem is solved directly and the "regular" subproblems are solved by some inexact solvers, such as ILU. In the two-level domain decomposition preconditioners, traditional interpolations between the coarse and the fine meshes destroy the good convergence property. Therefore, we propose an unconventional approach in which the coarse mesh is exactly the same as the fine mesh along the crack line, and adopt the technique of a non-matching grid interpolation between the fine and the coarse meshes. Numerical experiments demonstrate the effectiveness of the two-level domain decomposition preconditioners applied to elastic crack problems.     

Partitioning heritability analyses unveil the genetic architecture of human brain multidimensional functional connectivity patterns

Resting‐state functional connectivity profiles have been increasingly shown to be important endophenotypes that are tightly linked to human cognitive functions and psychiatric diseases, yet the genetic architecture of this multidimensional trait is barely understood. Using a unique sample of 1,704 unrelated, young and healthy Chinese Han individuals, we revealed a significant heritability of functional connectivity patterns in the whole brain and several subnetworks. We further proposed a partitioned heritability analysis for multidimensional functional connectivity patterns, which revealed the common and unique enrichment patterns of the genetic contributions to brain connectivity patterns for several gene sets linked to brain functions, including the genes expressed preferentially in the central nervous system and those associated with intelligence, educational attainment, attention‐deficit/hyperactivity disorder, and schizophrenia. These results for the first time reveal the genetic architecture of multidimensional brain connectivity patterns across different networks and advance our understanding of the complex relationship between gene sets, neural networks, and behaviors.     

心脑血管类药品应用评价

目的:对心脑血管类药品应用进行合理的评价,加强此类药品的管理,使临床用药更具有规范性与科学性。方法:收集2013年1~6月本医院门诊心脑血管类药品的应用数据,对药品针剂、口服制剂、中成药类、西药类的应用情况进行分析、统计。结果:在药品销售中,心脑血管类药品金额占全部销售药品金额30.01%。在心脑血管类药品中,中成药类的百分率为61.16%。在门诊中成药针剂类药品中,心脑血管类药品百分率为34.27%。结论:结合医院的办院特点,加强心脑血管类药品的应用管理,将中成药广泛应用于心脑血管疾病的临床治疗中,以提高疾病的治疗效果。     

A morphometric study of the lumbar spinous process in the Chinese population

Our goal was to analyze the anatomical parameters of the lumbar spine spinous process for an interspinous stabilization device designed for the Chinese population and to offer an anatomical basis for its clinical application. The posterior lumbar spines (T₁₂-S₁) of 52 adult cadavers were used for measuring the following: distance between two adjacent spinous processes (DB), distance across two adjacent spinous processes (DA), thickness of the central spinous processes (TC), thickness of the superior margin of the spinous processes (TS), thickness of the inferior margin of the spinous processes (TI), and height of the spinous processes (H). Variance and correlation analyses were conducted for these data, and the data met the normal distribution and homogeneity of variance. DB decreased gradually from L_1-2 to L₅-S₁. DA increased from T₁₂-L₁ to L_2-3 and then decreased from L_2-3 to L_4-5. The largest H in males was noted at L₃ (25.45±5.96 mm), whereas for females the largest H was noted at L₄ (18.71±4.50 mm). Usually, TS of the adjacent spinous process was lower than TI. Based on the anatomical parameters of the lumbar spinous processes obtained in this study, an “H”-shaped coronal plane (posterior view) was proposed as an interspinous stabilization device for the Chinese population. This study reports morphometric data of the lumbar spinous processes in the Chinese population, which provides an anatomical basis for future clinical applications.