血清淀粉样P物质在EV71感染小鼠肺和脑表达及其意义初探

目的 探讨2周龄BALB/c小鼠在EV71感染后,不同分期肺和脑组织中血清淀粉样P物质（SAP）表达水平。方法 2周龄BALB/c小鼠按笼号分组,实验组35只,对照组29只。实验组予1×107 TCID50·mL-1的EV71病毒液0.1 mL腹腔注射,对照组腹腔注射等容量PBS液。观察小鼠的活动状态、皮疹、反应性、毛色、肢体活动及瘫痪情况等,依据实验组感染症状分为5期：精神反应期（建模后第2天）、部分瘫痪期（第3天）、全身瘫痪期（第3天）、死亡（第3~4天）和恢复期（第10天仍存活）。分别于5个分期称重实验组和对照组小鼠后处死,采集肺和脑组织以ELISA法测定SAP水平,分析不同分期SAP水平变化趋势。结果 ①实验组建模后第2天均出现精神萎靡、活动减少,第3天部分小鼠出现肢体运动不协调、部分肢体瘫痪,甚至全身瘫痪至死亡,提示EV71感染小鼠模型建立成功。②建模后实验组精神反应期和对照组的体重差值差异无统计学意义,在部分瘫痪期、全身瘫痪期、死亡期和恢复期,两组体重差值的差异均有统计学意义。③实验组肺和脑组织中SAP水平在5个分期表达量均与对照组差异有统计学意义（P<0.05）,实验组脑组织SAP水平是对照组的2~9倍,肺组织SAP水平是对照组的1.5~8倍。实验组部分瘫痪期、全身瘫痪期和死亡期脑组织SAP水平均显著高于精神反应期（P<0.05）,肺组织SAP水平与精神反应期差异无统计学意义;脑和肺组织恢复期SAP水平均较精神反应期显著下降,但高于对照组水平。结论 SAP在EV71感染后小鼠的脑和肺组织中高表达,可能作为EV71感染后病情严重程度及预后判断的指标。     

Proteomics Approach Identifies Factors Associated With the Response to Low‐Density Lipoprotein Apheresis Therapy in Patients With Steroid‐Resistant Nephrotic Syndrome

Low‐density lipoprotein apheresis (LDL‐A) has been shown to reduce proteinuria in a subgroup of nephrotic syndrome patients refractory to immunosuppressive therapy. Factors influencing the efficacy of LDL‐A in nephrotic syndrome are completely unknown. Using a proteomics approach, we aimed to identify biological markers that predict the response to LDL‐A in patients with steroid‐resistant nephrotic syndrome (SRNS). Identification of plasma proteins bound to the dextran‐sulfate column at the first session of LDL‐A was determined by mass spectrometry. To investigate biological factors associated with the response to LDL‐A, we compared profiles of column‐bound proteins between responders (defined by more than 50% reduction of proteinuria after the treatment) and non‐responders by 2‐dimensional gel electrophoresis (2‐DE) coupled to mass spectrometry in seven patients with SRNS. Evaluation of proteins adsorbed to LDL‐A column in patients with SRNS revealed the identity of 62 proteins, which included apolipoproteins, complement components, and serum amyloid P‐component (SAP). Comparative analysis of the column‐bound proteins between responders and non‐responders by 2‐DE demonstrated that apolipoprotein E (APOE) and SAP levels were increased in non‐responders as compared with responders. These results were confirmed by western blotting. Moreover, serum levels of APOE and SAP were significantly higher in the non‐responder group than in the responder group by ELISA. Our data provide comprehensive analysis of proteins adsorbed by LDL‐A in SRNS, and demonstrate that the serum levels of APOE and SAP may be used to predict the response to LDL‐A in these patients.     

Mal de Meleda in Indonesia: Mutations in the SLURP1 gene appear to be ubiquitous

Mal de Meleda is a rare autosomal recessive genodermatosis caused by mutations in the ARS B (SLURP1) gene, with possible founder effects in the Mediterranean and Adriatic regions. We report an affected individual from Indonesia without known consanguinity in the family, suggesting that SLURP1 gene mutations are ubiquitous. Recognition of the phenotype can be confirmed by genetic testing, thus facilitating genetic counselling.     

基于基线等比增减设计法优选黄芪多糖-皂苷的免疫调节最佳配比

目的:考察黄芪多糖、黄芪皂苷配伍应用对环磷酰胺模型小鼠的免疫调节活性,筛选最优配比。方法:采用环磷酰胺(40 mg·kg^-1)制造免疫抑制小鼠模型,制备脾淋巴细胞悬液,分别进行正常培养和刀豆蛋白诱导培养,同时给予黄芪多糖与皂苷不同配比药液(10:0,4:1,3:2,1:4,0:10),作用48 h后行MTT微量比色法检测OD值;采用该模型,连续5 d灌胃给予相应受试药液,检测各药物组对模型鼠血清TNF-α含量、脾脏指数、胸腺指数的影响。结果:糖-苷10:0组、4:1组、3:2组均可促进体外模型鼠正常培养的脾淋巴细胞增殖(P<0.01),以4:1组作用显著,各配比组均抑制体外模型鼠经ConA诱导培养的脾淋巴细胞增殖,以糖-苷4:1组抑制最弱;与模型组比较,灌胃给药后除0:10组外,各组均能明显提高模型小鼠血清TNF-α含量(P<0.05或P<0.01),亦以4:1组作用显著,且4:1组、3:2组对脾脏指数有明显提高作用(P<0.05),而对胸腺指数各配比组均无显著影响(P>0.05)。结论:黄芪多糖与皂苷不同比例配伍对免疫抑制模型小鼠均表现出不同程度的免疫调节作用,尤以糖-苷4:1组作用最强,为最佳配比。     

集成综合评价法在农村环境卫生质量评价中的应用研究

目的 评价农村环境卫生质量,探索主成分分析法和熵值法相结合的综合评价方法,为提高评价结果的准确度和客观反映福建省农村环境卫生现状提供参考依据。 方法 分别采用主成分分析法、熵值法和集成综合评价法对福建省19个县农村环境卫生质量进行综合评价。 结果 主成分分析法提取的3个主成分累计方差贡献率为87.14%,其中第1主成分与农村户厕卫生状况密切相关,第2主成分与农村病媒生物状况密切相关,第3主成分与农村供水卫生状况密切相关;熵值法确定的指标权重显示,供水卫生及病媒生物指标在农村环境卫生质量评价中占据相对重要的位置;集成综合评价法综合得分显示闽南沿海经济发达地区环境卫生质量优于闽北经济欠发达地区。 结论 主成分分析法和熵值法对福建省农村环境卫生质量的评价结论具有一致性,将两种评价法相结合进行综合评价能起到优势互补的效果,并可以对农村环境卫生质量及存在的问题做出客观、科学的综合判断,为有关部门科学制定改善农村环境卫生对策和措施提供科学指导。     

Independent component model of the default-mode brain function: Assessing the impact of active thinking

The “default-mode” network is an ensemble of cortical regions, which are typically deactivated during demanding cognitive tasks in functional magnetic resonance imaging (fMRI) studies. Using functional connectivity, this network can be conceptualized and studied as a “stand-alone” function or system. Regardless of the task, independent component analysis (ICA) produces a picture of the “default-mode” function even when the subject is performing a simple sensori-motor task or just resting in the scanner. This has boosted the use of default-mode fMRI for non-invasive research in brain disorders. Here, we studied the effect of cognitive load modulation of fMRI responses on the ICA-based pictures of the default-mode function. In a standard graded working memory study based on the n-back task, we used group-level ICA to explore the variability of the default-mode network related to the engagement in the task, in 10 healthy volunteers.

The analysis of the default-mode components highlighted similarities and differences in the layout under three different cognitive loads. We found a load-related general increase of deactivation in the cortical network. Nonetheless, a variable recruitment of the cingulate regions was evident, with greater extension of the anterior and lesser extension of the posterior clusters when switching from lower to higher working memory loads. A co-activation of the hippocampus was only found under no working memory load.

As a generalization of our results, the variability of the default-mode pattern may link the default-mode system as a whole to cognition and may more directly support use of the ICA model for evaluating cognitive decline in brain disorders.     

A method for multitask fMRI data fusion applied to schizophrenia

It is becoming common to collect data from multiple functional magnetic resonance imaging (fMRI) paradigms on a single individual. The data from these experiments are typically analyzed separately and sometimes directly subtracted from one another on a voxel-by-voxel basis. These comparative approaches, although useful, do not directly attempt to examine potential commonalities between tasks and between voxels. To remedy this we propose a method to extract maximally spatially independent maps for each task that are "coupled" together by a shared loading parameter. We first compute an activation map for each task and each individual as "features," which are then used to perform joint independent component analysis (jICA) on the group data. We demonstrate our approach on a data set derived from healthy controls and schizophrenia patients, each of which carried out an auditory oddball task and a Sternberg working memory task. Our analysis approach revealed two interesting findings in the data that were missed with traditional analyses. First, consistent with our hypotheses, schizophrenia patients demonstrate "decreased" connectivity in a joint network including portions of regions implicated in two prevalent models of schizophrenia. A second finding is that for the voxels identified by the jICA analysis, the correlation between the two tasks was significantly higher in patients than in controls. This finding suggests that schizophrenia patients activate "more similarly" for both tasks than do controls. A possible synthesis of both findings is that patients are activating less, but also activating with a less-unique set of regions for these very different tasks. Both of the findings described support the claim that examination of joint activation across multiple tasks can enable new questions to be posed about fMRI data. Our approach can also be applied to data using more than two tasks. It thus provides a way to integrate and probe brain networks using a variety of tasks and may increase our understanding of coordinated brain networks and the impact of pathology upon them.