Combination of Aβ clearance and neurotrophic factors as a potential treatment for Alzheimer’s disease

There is no effective drug to treat Alzheimer’s disease (AD), a neurodegenerative disease affecting an estimated 30 million people around the world. Strongly supported by preclinical and clinical studies, amyloid-beta (Aβ) may be a target for developing drugs against AD. Meanwhile, the fact that localized neuronal death/loss and synaptic impairment occur in AD should also be considered. Neuronal regeneration, which does not occur normally in the mammalian central nervous system, can be promoted by neurotrophic factors (NTFs). Evidence from clinical trials has shown that both Aβ clearance and NTFs are potentially effective in treating AD, thus a new approach combining Aβ clearance and administration of NTFs may be an effective therapeutic strategy.     

Level set evolution with local uncertainty constraints for unsupervised change detection

This letter presents a novel method for unsupervised change detection (CD) from remote sensing images using level set evolution with local uncertainty constraints (LSELUC). Uncertainty analysis of pixel labels was implemented as prior information to guide the evolution of level curves. Then, local uncertainty and gradient information of level curves were incorporated into the level set energy function to construct local energy constraints. The proposed method can reduce noise, while preserving details in change regions. Furthermore, an advanced regularization strategy of the level set function was adopted to improve the computational efficiency. The performance of the proposed method was validated on two remote sensing data sets. Experimental results show that the proposed method can produce satisfactory CD results.     

原癌基因Bmi-1 B细胞抗原表位及 HLA I类限制性CTL表位的生物信息学分析

目的:预测原癌基因Bmi-1(B-cell-specific Moloney murine leukemia virus insertion site 1)的B细胞抗原表位及HLA I类限制性细胞毒性T细胞（cytotoxic T cell）表位。方法:采用Ellipro(http://tools.immuneepitope.org/ellipro/)预测Bmi-1蛋白中可能存在的线性B细胞表位和构象B细胞表位；采用ProtParam、NetCTL等软件和方法预测Bmi-1中可能存在的HLA I类限制性CTL表位。结果:Bmi-1蛋白中含有6个线性B细胞表位和8个构象B细胞表位；结合HLA结合力、蛋白酶体切割效率和TAP转运效率，经过NetCTL程序预测表明:针对不同的HLA I类分子，原癌基因Bmi-1中都存在多个HLA I类分子的限制性CTL表位。结论:综合运用多个程序预测了原癌基因Bmi-1中的B细胞抗原表位及HLA I类分子的限制性CTL表位，为下一步开展针对Bmi-1的免疫靶向治疗等研究打下了基础。     

广州市2015-2016年50~74岁社区人群大肠癌筛查结果分析

目的 分析广州市开展现行大肠癌筛查策略的效果。方法 收集、整理2015－2016年广州市大肠癌筛查数据，评价问卷调查、便隐血检查和全结肠镜检查的筛查效果。结果 2015－2016年广州市50～74岁重点人群完成初筛220 834人，初筛阳性37 040例（16.77%）。全结肠镜检7 821人，肠镜检查顺应率为21.12%（7 821/37 040）。发现各类肠道病变4 126例（52.76%），其中进展性腺瘤614例（7.85%）、伴中/重度异型增生的其他病变73例（0.93%），大肠癌230例（2.94%）；各类病变中男性检出率均高于女性（P<0.01）。病变早诊率为87.24%；筛查发现早期癌99例，占总大肠癌的46.26%。大肠癌筛查发现率为104.15/10万，明显高于相应年龄段（50～74岁）大肠癌监测发病率81.18/10万（P<0.001），表现为≤69岁年龄段大肠癌发现率明显高于相应发病率，≥70岁年龄段则相反。结论 广州市大肠癌筛查策略可以发现大肠癌高危人群，提高全结肠镜病变检出率、癌前病变早诊率和早期大肠癌的诊断比例，≤69岁人群受益高于70～74岁人群，是大肠癌筛查重点关注人群，应需进一步促进高危人群肠镜检查顺应性。     

脂多糖受体簇和大电导Ca2+活K+通道在脂多糖信号识别中的作用

背景 细菌脂多糖(lipopolysaccharide,LPS)可激活细胞合成和释放多种细胞因子,导致全身炎症反应.LPS识别及跨膜信号转导是引起细胞效应的关键,成为近年的研究热点.目的 对新近提出的“LPS受体簇”理论和大电导Ca2+激活K+通道(MaxiK)在LPS信号识别中的作用研究进展进行综述.内容 LPS与CD14结合后,不同的信号分子在脂质筏内聚集,LPS被释放到脂质双分子层,并与由多种受体分子组成的受体簇相互作用.根据不同的细胞类型和细菌刺激,形成了不同的LPS受体簇.MaxiK通道在LPS诱导的巨噬细胞信号转导过程的早期即被激活.并且以IκB-α/NF-κB为中心的促炎症反应依赖MaxiK的功能.趋向 需要进一步研究来阐明LPS受体簇在细胞膜特定区域内形成的确切分子机制,以及组成受体簇的几种蛋白分子在刺激识别和信号转导过程中的作用.