Genetic Polymorphisms in the APOA1 Gene and their Relationship with Serum HDL Cholesterol Levels

Low high density lipoprotein cholesterol (HDL-C) is a known risk factor of coronary artery disease. Apolipoprotein A1 (APOA1) is the most abundant component of HDL-C. This study aimed at identifying sequence variations (rare and common) in the APOA1 gene and its association with serum HDL-C levels. This study was conducted from April 2012 to February 2013 on 79 Tehranians (participants of Tehran Lipid and Glucose Study) with extremely low HDL-C (within the 5th percentile) and 63 individuals with extremely high HDL-C (within the 95th percentile) levels. After DNA amplification by PCR, DNA sequencing of all three exons and 700 bps of promoter region of the APOA1 gene was performed. Sequence results were analyzed and interpreted using the appropriate software and variants were identified. After sequencing 42 common and rare variants were identified, 11 of which were known variants and the others had been unreported so far. Of the exonic variants, 11 were missense, 6 were synonymous and 1 was nonsense. There was a significant association between serum HDL-C and variant of rs2070665 as well as variants Chr.11:116707788, Chr.11:116708059, Chr.11:116708036, Chr.11:116707729, rs201148448, Chr.11:116707018, Chr.11:116707801, Chr.11:116708530, Chr.11:116708088, rs121912724 and Chr.11:116706966 (p < 0.001). Variants Chr.11:116707018, rs121912724 and 2070665 were independent predictors of the HDL-C level (p < 0.001). SNP Chr.11:116707018 was the strongest predictor of the HDL-C level (OR 7.527, p < 0.001). This study identified 42 variants in APOA1 gene, 31 of which were new variants. Three variants of rs2070665, rs121912724 and Chr.11:116707018 could predict the HDL-C level independently. Variant rs2070665 was protective against low-HDL-C levels while variants rs121912724 and Chr.11:116707018 were risk factors for that in our population.     

水库中长期发电优化调度解析方法及应用

水库中长期发电优化调度是实现水能资源高效利用的重要技术手段。由于水库特性曲线的离散数值表达,现行水库中长期发电优化调度模型与求解方法主要集中在数值方法层面,且优化计算效率低下。针对这一问题,提出了水库中长期发电优化调度的解析方法,即通过水库特性曲线的函数化,建立了优化调度的解析函数模型,并基于POA算法原理提出了解析优化方法——APOA算法。通过实例应用和传统方法对比研究表明,该方法在保证计算精度的前提下,长系列优化计算时间仅为POA算法的1/20。因此,该方法不仅具有算法稳定、计算效率高的特点,而且在水库中长期发电优化调度的解析研究途径方面进行了有益的探索。     

广义回归神经网络预测适应值的人工植物算法

人工植物算法是最近几年提出来的一种新颖的智能优化算法,把一个植物的生长过程映射为一个智能优化问题。它为那些高维多模问题提出了一种新的解决方法,但是,当把人工植物算法应用到现实问题中时,有时会遇到适应值很耗时的计算,如优化目标和随机问题中存在随机因素的不确定规划问题,或适应值需要通过很多复杂计算才能近似计算等问题。所以,在人工植物算法中需要采取一些预测适应值的策略,采取了基于代进化控制的结合神经网络预测模型的策略(GAPOA)。     

Serum APOA4 Pharmacodynamically Represents Administered Recombinant Human Hepatocyte Growth Factor (E3112)

Background: Hepatocyte growth factor (HGF) is an endogenously induced bioactive molecule that has strong anti-apoptotic and tissue repair activities. In this research, we identified APOA4 as a novel pharmacodynamic (PD) marker of the recombinant human HGF (rh-HGF), E3112. Methods: rh-HGF was administered to mice, and their livers were investigated for the PD marker. Candidates were identified from soluble proteins and validated by using human hepatocytes in vitro and an animal disease model in vivo, in which its c-Met dependency was also ensured. Results: Among the genes induced or highly enhanced after rh-HGF exposure in vivo, a soluble apolipoprotein, Apoa4, was found to be induced by rh-HGF in the murine liver. By using primary cultured human hepatocytes, the significant induction of human APOA4 was observed at the mRNA and protein levels, and it was inhibited in the presence of a c-Met inhibitor. Although mice constitutively expressed Apoa4 mRNA in the small intestine and the liver, the liver was the primary organ affected by administered rh-HGF to strongly induce APOA4 in a dose- and c-Met-dependent manner. Serum APOA4 levels were increased after rh-HGF administration, not only in normal mice but also in anti-Fas-induced murine acute liver failure (ALF), which confirmed the pharmacodynamic nature of APOA4. Conclusions: APOA4 was identified as a soluble PD marker of rh-HGF with c-Met dependency. It should be worthwhile to clinically validate its utility through clinical trials with healthy subjects and ALF patients.