Astrocytic endothelin-1 overexpression impairs learning and memory ability in ischemic stroke via altered hippocampal neurogenesis and lipid metabolism

Vascular etiology is the second most prevalent cause of cognitive impairment globally.Endothelin-1,which is produced and secreted by endothelial cells and astrocytes,is implicated in the pathogenesis of stroke.However,the way in which changes in astrocytic endothelin-1 lead to poststroke cognitive deficits following transient middle cerebral artery occlusion is not well understood.Here,using mice in which astrocytic endothelin-1 was overexpressed,we found that the selective overexpression of endothelin-1 by astrocytic cells led to ischemic stroke-related dementia(1 hour of ischemia;7 days,28 days,or 3 months of reperfusion).We also revealed that astrocytic endothelin-1 overexpression contributed to the role of neural stem cell proliferation but impaired neurogenesis in the dentate gyrus of the hippocampus after middle cerebral artery occlusion.Comprehensive proteome profiles and western blot analysis confirmed that levels of glial fibrillary acidic protein and peroxiredoxin 6,which were differentially expressed in the brain,were significantly increased in mice with astrocytic endothelin-1 overexpression in comparison with wild-type mice 28 days after ischemic stroke.Moreover,the levels of the enriched differentially expressed proteins were closely related to lipid metabolism,as indicated by Kyoto Encyclopedia of Genes and Genomes pathway analysis.Liquid chromatography-mass spectrometry nontargeted metabolite profiling of brain tissues showed that astrocytic endothelin-1 overexpression altered lipid metabolism products such as glycerol phosphatidylcholine,sphingomyelin,and phosphatidic acid.Overall,this study demonstrates that astrocytic endothelin-1 overexpression can impair hippocampal neurogenesis and that it is correlated with lipid metabolism in poststroke cognitive dysfunction.

Dry environment on the expression of lacrimal gland S100A9,Anxa1,and Clu in rats via proteomics

●AIM:To investigate the underlying mechanism of dry environment(autumn dryness)affecting the lacrimal glands in rats.●METHODS:Twenty Sprague-Dawley rats were randomly divided into two groups.The rats were fed in specific pathogen free environment as the control group(n=10),and the rats fed in dry environment as the dryness group(n=10).After 24d,lacrimal glands were collected from the rats.The tissues morphology was observed by hematoxylineosin(HE)staining.Tandem mass tags(TMT)quantitative proteomics analysis technology was used to screen the differential expressed proteins of lacrimal glands between the two groups,then bioinformatics analysis was performed.Further,the immunohistochemical(IHC)method was used to verify the target proteins.●RESULTS:In dryness group,the lacrimal glands lobule atrophied,the glandular cavities enlarged,the sparse nuclear distribution and scattered inflammatory infiltration between the acinus were observed.The proteomics exhibited that a total of 195 up-regulated and 236 downregulated differential expressed proteins screened from the lacrimal glands of rats.It was indicated that the biological processes(BP)of differential expressed proteins mainly included cell processes and single BP.The cellular compositions of differential expressed proteins mainly located in cells,organelles.The molecular functions of differential expressed proteins mainly included binding,catalytic activity.Moreover,the Kyoto Encyclopedia of Genes and Genomes(KEGG)pathway analysis showed that the differential expressed proteins mainly involved lysosome,complement and coagulation cascade,and ribosome pathway.The IHC result verified that the up-regulated expression proteins of Protein S100A9(S100A9),Annexin A1(Anxa1),and Clusterin(Clu)in lacrimal glands of rats in dryness group were higher than control group.●CONCLUSION:The up-regulated expression proteins of S100A9,Anxa1,and Clu may be the potential mechanisms of dry eye symptoms caused by dry environment.This study provides clues of dry environments causing eye-related diseases for further studies.

Key elements determining the intestinal region-specific environment of enteric neurons in type 1 diabetes

Diabetes,as a metabolic disorder,is accompanied with several gastrointestinal(GI)symptoms,like abdominal pain,gastroparesis,diarrhoea or constipation.Serious and complex enteric nervous system damage is confirmed in the background of these diabetic motility complaints.The anatomical length of the GI tract,as well as genetic,developmental,structural and functional differences between its segments contribute to the distinct,intestinal region-specific effects of hyperglycemia.These observations support and highlight the importance of a regional approach in diabetes-related enteric neuropathy.Intestinal large and microvessels are essential for the blood supply of enteric ganglia.Bidirectional morpho-functional linkage exists between enteric neurons and enteroglia,however,there is also a reciprocal communication between enteric neurons and immune cells on which intestinal microbial composition has crucial influence.From this point of view,it is more appropriate to say that enteric neurons partake in multidirectional communication and interact with these key players of the intestinal wall.These interplays may differ from segment to segment,thus,the microenvironment of enteric neurons could be considered strictly regional.The goal of this review is to summarize the main tissue components and molecular factors,such as enteric glia cells,interstitial cells of Cajal,gut vasculature,intestinal epithelium,gut microbiota,immune cells,enteroendocrine cells,prooxidants,antioxidant molecules and extracellular matrix,which create and determine a gut region-dependent neuronal environment in diabetes.

基于Sentinel-1/2改进极化指数和纹理特征的土壤含盐量反演模型

目前Sentinel-1/2协同反演植被土壤含盐量的研究大多是基于Sentinel-2光谱信息和Sentinel-1后向散射系数,没有考虑Sentinel-2光谱信息容易受土壤亮度等信息影响,Sentinel-1后向散射系数容易受土壤粗糙度和水分影响。为进一步提高Sentinel-1/2协同反演植被土壤含盐量的精度,用水云模型对雷达卫星后向散射系数进行校正,消除植被影响;然后协同Sentinel-2纹理特征,基于VIP、OOB、PCA 3种变量筛选和RF、ELM、Cubist 3种机器学习回归模型构建植被土壤含盐量反演模型。研究结果表明:经过水云模型去除植被影响后的雷达后向散射系数及其极化组合指数与土壤含盐量的相关性有一定程度的提高。不同变量选择方法与不同机器学习方法耦合模型在反演土壤含盐量中,OOB变量筛选方法与RF、ELM和Cubist 3种机器学习方法的耦合模型精度最佳,建模集和验证集的R2都在0.750以上,且验证集的RMSE和MAE均最小;其中OOB-Cubist耦合模型精度最高,且R_(v)^(2)/R_(c)^(2)为0.955,具有良好的鲁棒性。研究可为机器学习协同物理模型、光学卫星协同雷达卫星在土壤含盐量反演中的进一步应用提供思路。

塔里木盆地顺北1号断裂带奥陶系碳酸盐岩储层结构表征及三维地质建模

综合利用地震、测井、岩心以及动态生产资料,对塔里木盆地顺北1号断裂带断控型碳酸盐岩储集体的内部结构进行了层级划分;基于层级划分,通过地震资料属性提取与转换、深度学习、基于目标示性点过程模拟以及离散裂缝网络模拟(DFN)等方法建立了三维地质模型,并以模型进行油气储量和油藏数值模拟,将拟合结果与实际生产数据进行对比。研究结果表明:(1)顺北1号断裂带奥陶系断控型储层按层级由大到小分为走滑断裂影响带、断控体、类洞穴、类洞穴内簇充填和裂缝带共5个层级。(2)走滑断裂影响带受应力差异影响具有分段性,可细分为挤压段、拉分段和平移段;断控体在拉分段发育断裂交会型、单支走滑型,在平移段发育双断裂交错型和两断裂交会型,在挤压段发育双断裂扭曲型和双断裂交会型,共有6种平面组合样式;类洞穴在地震剖面上呈串珠状反射特征;类洞穴内部分为栅体与栅间(基岩),其中栅体又可进一步分为簇(角砾带)、簇间(裂缝带),整体表现为栅状结构,簇的物性更好;裂缝带为类洞穴的主要储集空间,在簇内部比簇间更发育,在一间房组比鹰山组更发育,一间房组和鹰山组均以发育高角度裂缝为主,在两者连接处则以发育水平缝为主。(3)地质模型预测的油气储量与地质分析储量误差为1.75%,模型模拟的生产井地层压力及累产液结果与生产动态吻合度较高,拟合误差小于10%。

基于GF-1卫星遥感反演排水河沟水体溶存N_(2)O浓度模型对比研究

[目的]探究利用GF-1卫星数据反演水体溶存氧化亚氮(N_(2)O)浓度的可行性,为实现低成本、高效率的水质实时监测提供有效途径。[方法]以宁夏青铜峡灌区第1和第5排水河沟为研究对象,选取与排水河沟水体溶存N_(2)O浓度相关性高的GF-1卫星影像波段反射率和水质参数作为自变量,通过最优子集筛选法确定最优自变量组合,分别构建了多元线性回归、BP神经网络和支持向量机模型,对水体溶存N_(2)O浓度进行预测对比。[结果]水温(T)、溶解性有机碳(DOC)等是影响水体溶存N_(2)O浓度的主要因素,同时近红外(NIR)等卫星波段与水体溶存N_(2)O浓度变化趋势显著相关。当自变量包括T,NIR等7个因素时,模型预测效果最佳。在3种模型中,BP神经网络模型验证结果R^(2)为0.64,具有最高预测精度。[结论]GF-1卫星数据以及水质参数与水体溶存N_(2)O浓度存在复杂的相关性关系,且BP神经网络能够实现利用GF-1卫星数据较高精度地反演水体溶存N_(2)O浓度。

慢性间断缺氧通过上调大鼠海马HMGB1和NF-κB损伤学习记忆

目的:探索慢性间断缺氧(CIH)导致大鼠学习记忆功能障碍,以及对海马区高迁移率族蛋白1(HMGB1)和核转录因子-κB(NF-κB)表达的影响。方法:制作CIH大鼠模型,40只SD大鼠分为常氧组(normoxia)、缺氧4周组(CIH4组)、缺氧8周组(CIH8组)和缺氧12周组(CIH12组)。采用Morris水迷宫评估大鼠学习记忆能力,免疫组织化学染色和ELISA法检测大鼠海马区HMGB1和NF-κB的表达。结果:与常氧组相比,CIH12和CIH8组的逃避潜伏期延长,穿越平台次数和平台所在象限停留时间显著缩短,CIH4组的无显著差异。另外,常氧组海马区HMGB1和NF-κB的表达未见明显表达,CIH4组可见少许表达,CIH8组和CIH12组可见明显表达,同时CIH12组的表达显著高于CIH8组。结论:CIH可导致大鼠的学习记忆功能下降,且间断缺氧时间越长对其学习记忆功能的影响越显著。此外,CIH还导致海马区HMGB1和NF-κB的表达水平升高,并且缺氧12周比8周增加更为明显。

多目标系统化学习的PD-L1切片分析方法

在肿瘤尤其是如肺鳞癌(lung squamous cell carcinoma,LUSC)的非小细胞肺癌的治疗中,基于程序性死亡受体-配体1(programmed cell death-ligand 1,PD-L1)染色切片的阳性肿瘤细胞比例评分(tumor proportion score,TPS)可为治疗方案的选择提供重要依据。肿瘤细胞(tumor cell,TC)的许多参数对癌症诊断至关重要。虽然可以通过计算分析来预测这些参数,但很少有一个统一的框架可以同时获得细胞的不同病理信息。为此,提出了一种多目标学习框架(multi-objective learning pipeline,MOLP),从LUSC的PD-L1切片中预测TPS、细胞数目、细胞核轮廓和类别。主干网络包括两个分支:一个分支通过细胞分析估算TPS,另一个分支直接通过回归分析估算TPS。MOLP通过最小化两个分支的TPS预测差值来提高其鲁棒性。细胞分析支路可实现细胞核分割、分类和计数,不仅增强了TPS估计的可信度,还使得MOLP能够估计肿瘤细胞的外观参数以用于LUSC诊断。在大规模图像集上的实验结果证明了MOLP的可行性和有效性。MOLP预测的TPS与病理医师的评分呈现出统计学上的显著相关性:平均绝对误差仅为4.97(95%置信区间:-0.56~10.49),皮尔逊相关系数为0.97(p<0.001)。

Distribution and geochemical significance of alkylbenzenes for crude oil with different depositional environments and thermal maturities

A total of 45 alkylbenzenes were detected and identified in crude oils with different depositional environments and thermal maturities from the Tarim Basin,Beibuwan Basin,and Songliao Basin using comprehensive two-dimensional gas chromatography time-of-flight mass spectrometry(GC×GCTOFMS).By analyzing the distribution characteristics of C0-C5alkylbenzenes,it is found that the content of some alkylbenzenes varies greatly in crude oils.Based on the distribution characteristics of 1,2,4,5-tetramethylbenzene(Te MB)and 1,2,3,4-Te MB,the ratio of 1,2,4,5-Te MB to 1,2,3,4-Te MB is proposed to indicate the organic matter origin and depositional environment of ancient sediments.Oil samples originated mainly from lower hydrobiont,algae,bacteria and source rocks deposited under reducing/anoxic conditions have low 1,2,4,5-/1,2,3,4-Te MB values(less than 0.6),while oil samples originated mainly from terrestrial higher plants and source rocks deposited under oxic/sub-oxic conditions have higher 1,2,4,5-/1,2,3,4-Te MB values(greater than 1.0).The significant difference of 1,2,4,5-/1,2,3,4-Te MB values is controlled by 1,2,4,5-Te MB content.1,2,4,5-Te MB content in oils derived from source rocks deposited in oxidized sedimentary environment(greater than 1.0 mg/g whole oil)is higher than that in oils from source rocks deposited in reduced sedimentary environment(less than 1.0 mg/g whole oil).1,2,4,5-/1,2,3,4-Te MB ratio might not or slightly be affected by evaporative fractionation,biodegradation and thermal maturity.1,2,4,5-/1,2,3,4-Te MB ratio and 1,2,4,5-Te MB content can be used as supplementary parameter for the identification of sedimentary environment and organic matter input.It should be noted that compared to the identification of organic matter sources,the 1,2,4,5-/1,2,3,4-Te MB parameter is more effective in identifying sedimentary environments.

1型神经纤维瘤病发病机制及治疗进展

1型神经纤维瘤病(neurofibromatosis type 1,NF1)是一种常见的遗传性神经皮肤综合征,发病率为1/3500,主要表现为皮肤、神经、骨骼等多个系统的肿瘤形成。NF1基因突变导致神经纤维蛋白功能丧失,受神经纤维蛋白负调控的Ras信号失去抑制,导致MAPK信号通路组成型激活,该信号通路的异常激活与肿瘤微环境等机制促使NF1肿瘤发生。目前,主流的治疗方式包括针对Raf/MEK/ERK通路和/或mTOR通路的靶向抑制剂。近年来,对NF1的遗传学、临床特征、肿瘤起源、异常信号通路以及相关靶向抑制剂的疗效等方面的研究日益增多。深入了解NF1的病理生物学和分子机制将为开发更有效的靶向治疗方法提供坚实的基础。

过表达海马LINGO-1对小鼠学习和记忆能力及海马各亚区Spinophilin+树突棘的影响

目的 脑立体定位注射腺相关病毒特异性过表达海马LINGO-1,探讨其对小鼠空间学习和记忆能力以及海马各亚区体积和Spinophilin+树突棘的影响。方法 将7月龄雄性C57小鼠按照简单随机法分为对照组和LINGO-1过表达组,对照组小鼠海马立体定位注射携带绿色荧光的空载腺相关病毒(adeno-associated virus, AAV),LINGO-1过表达组小鼠海马立体定位注射同时携带绿色荧光和LINGO-1过表达载体的AAV。运用Morris水迷宫评估小鼠的空间学习和记忆能力,荧光定量PCR及免疫荧光染色方法分别检测小鼠海马内LINGO-1基因表达水平和各亚区荧光强度,体视学三维定量小鼠海马各亚区体积及Spinophilin+树突棘总数。结果 对照组和LINGO-1过表达组病毒注射前后体质量差异无统计学意义;LINGO-1过表达诱导小鼠海马LINGO-1的mRNA水平升高、荧光强度增强(P<0.01);与对照组相比,LINGO-1过表达组小鼠在Morris水迷宫实验中的表现明显更差(P<0.05);LINGO-1过表达诱导小鼠海马各亚区体积显著下降(P<0.05,P<0.01),Spinophilin+树突棘密度显著降低(P<0.01,P<0.05),Spinophilin+树突棘数量显著减少(P<0.05)。结论 海马立体定位注射过表达LINGO-1腺相关病毒能够特异性上调小鼠海马内LINGO-1水平,海马LINGO-1的异常高表达可导致小鼠海马体积减小及Spinophilin+树突棘突触丢失,并在一定程度上损伤其空间学习与记忆能力。

Physics-embedded machine learning search for Sm-doped PMN-PT piezoelectric ceramics with high performance

Pb(Mg_(1/3)Nb_(2/3))O_(3)–PbTiO_(3)(PMN-PT)piezoelectric ceramics have excellent piezoelectric properties and are used in a wide range of applications.Adjusting the solid solution ratios of PMN/PT and different concentrations of elemental doping are the main methods to modulate their piezoelectric coefficients.The combination of these controllable conditions leads to an exponential increase of possible compositions in ceramics,which makes it not easy to extend the sample data by additional experimental or theoretical calculations.In this paper,a physics-embedded machine learning method is proposed to overcome the difficulties in obtaining piezoelectric coefficients and Curie temperatures of Sm-doped PMN-PT ceramics with different components.In contrast to all-data-driven model,physics-embedded machine learning is able to learn nonlinear variation rules based on small datasets through potential correlation between ferroelectric properties.Based on the model outputs,the positions of morphotropic phase boundary(MPB)with different Sm doping amounts are explored.We also find the components with the best piezoelectric property and comprehensive performance.Moreover,we set up a database according to the obtained results,through which we can quickly find the optimal components of Sm-doped PMN-PT ceramics according to our specific needs.

基于Keap1/Nrf2/HO-1通路探讨虎杖苷对衰老小鼠学习认知障碍的作用机制

目的研究虎杖苷对D-半乳糖致衰老模型小鼠的调节作用。方法将56只ICR小鼠(雌雄各半)分为正常组、模型组、阳性组、虎杖苷低、中、高治疗组,通过每日颈后部皮下注射D-半乳糖(500 mg·kg^(-1))建立衰老模型。造模期间,阳性组灌胃盐酸多奈哌齐片(0.75 mg·kg^(-1)),治疗组灌胃虎杖苷(40、70、100 mg·kg^(-1)),正常组给予等量生理盐水。通过筑巢实验、新型物体识别实验与Morris水迷宫实验评估小鼠学习认知能力;取小鼠心、肝、脾、肾、胸腺计算脏器指数;苏木精-伊红(HE)染色观察小鼠全脑组织病理变化;ELISA检测小鼠血清与全脑组织中T-SOD、MDA、GSH-Px、AchE水平;Western blot检测小鼠海马组织Keap1、Nrf2、HO-1蛋白表达水平。结果较模型组相比,阳性组与虎杖苷低、中、高剂量组小鼠的筑巢能力、对新物体的识别能力与水下寻找站台的能力有所上升;脏器指数增加;大脑皮层与海马组织的神经元损伤明显改善;血清与脑组织中T-SOD、GSH-Px活性升高,MDA、AchE活性下降;海马组织中Nrf2、HO-1蛋白表达水平上升,Keap1蛋白表达水平降低。结论虎杖苷对D-半乳糖致衰老模型小鼠的学习认知障碍具有改善作用,其机制可能与Keap1/Nrf2/HO-1通路有关。

苏里格气田S区块山西组山1段沉积微相特征研究

上古生界山西组山1段为鄂尔多斯盆地苏里格气田S区块的主力产气层,厘清其沉积相特征,对指导该地区的天然气勘探具有一定意义。运用沉积学基础原理和方法,综合岩心观察、测井曲线、微量元素特征、沉积构造及古生物化石等资料,对苏里格气田S区块山1段进行系统研究。并结合单井相、沉积相连井剖面及砂地比特征,刻画山1段沉积微相展布特征。研究结果表明,研究区岩性主要为中-细砂岩,总体表现出牵引流的沉积特征,沉积环境为气候较湿润的弱还原-还原的水下沉积环境。岩心上见冲刷面、板状交错层理、平行层理和水平层理等沉积构造,古生物化石以碳化植物茎杆化石或植物叶片化石印模为主。山1段为曲流河三角洲前缘沉积,划分为水下分流河道、水下分流间湾、席状砂沉积微相,主要发育近北南向的水下分流河道砂体,为研究区最主要的储集体。

王浆主蛋白1(MRJP-1)及其对蜜蜂学习记忆影响的研究进展

蜂王浆由蜜蜂幼年工蜂所产,是蜂王及工蜂小幼虫的唯一食物来源,同时也因蜂王浆的丰富营养价值而为人们所熟知。蜂王浆主蛋白(MRJPs)是蜂王浆中最为丰富的水溶性蛋白,其中的MRJP-1除提供营养外,对蜜蜂的个体发育、神经系统发育、行为调控、级型分化等方面均有很好的生理调节作用。文章介绍了MRJP-1的理化特性和在蜜蜂体内的表达情况,并对MRJP-1在蜜蜂学习记忆方面的影响研究作简要概括,以期为王浆主蛋白在蜜蜂认知行为方面的研究提供一些思路和理论支撑。

SERINC1表达在肺癌中的预后作用及与肿瘤免疫浸润的关系

目的本研究旨在探讨血清素转运蛋白1(SERINC1)在肺癌预后中的作用。方法从GEO数据库下载了肺癌的单细胞测序scRNA数据,提取上皮细胞显著表达基因。同时Xena数据库下载TCGA数据,并进行了差异分析。将以上两者差异显著表达基因取交集,得到了上皮细胞差异基因。使用LASSO、随机森林、GBM、XGBoost等多种机器学习算法取交集,得到了FAM107A、SERINC1、MDK、GGCT、AVL9和FEZ16个交集基因。由于SERINC1在肺癌中还未被研究,对SERINC1进行了一系列的临床相关性分析,包括诊断ROC分析、表达分析、富集分析、生存分析、蛋白表达、蛋白互作分析以及免疫浸润分析。结果通过单细胞测序和机器学习筛选出了目标基因SERINC1。ROC分析SERINC1的AUC值高达0.972,显示出很高的诊断效能。K-M曲线显示,SERINC1表达高的患者的预后明显好于表达量低的患者,其HR值为0.71(95%CI:0.63~0.81)和0.48(95%CI:0.39~0.61),这表明基因表达量越高的患者预后更好。免疫浸润分析揭示,SERINC1与多种免疫细胞相关,且与多种T细胞的标志基因集相关。结论SERINC1是肺癌的一个有前景的预后标志物,且与免疫浸润相关。

锦州25-1油田X井古生物特征及其地质意义

渤海湾盆地锦州25-1油田是辽西凹陷内首次发现的三级油气当量近亿吨级的优质油田,针对该油田的X井开展古近纪生物组合特征研究,掌握了X井区生物相演化规律,并结合岩性、电性特征,开展沉积环境、水深等综合研究,助力锦州25-1油田的进一步勘探。

The MOOC/SPOC Based"1+M+N"Multi-University Collaborative Teaching and Learning Mode:Practice and Experience

Since 2012, the MOOCs, the massive open online courses, have brought big influences on the higher education in the world. How to use MOOCs to help universities rather than bother them to improve their education level and quality becomes an important issue. In China, many universities have explored the new modes and approaches for MOOC/SPOC-based teaching and learning. Especially, the China MOOC Association on Computing Education(CMOOC association), established in 2014, has done a set of successful practice and achieved fruitful experiences on MOOC courses development and computer education reform. Based on the practical experiences, a MOOC/SPOC based "1+M+N" multi-university collaborative teaching and learning mode is presented, which is adapted to the real situation of Chinese university education. In the paper, the practices and experiences of CMOOC association are introduced, the MOOC/SPOC based "1+M+N" multi-university collaborative teaching and learning mode and its approaches are described. Finally, the suggestions for MOOCs development and applications are also presented.

Interaction of methylenetetrahydrofolate reductase C677T,cytochrome P4502E1 polymorphism and environment factors in esophageal cancer in Kazakh population

AIM： To evaluate the association and interaction of genetic polymorphisms in methylenetetrahydrofolate reductase （MTHER） and cytochrome P4502E1 （CY- P4502E1）, environment risk factors with esophageal cancer （EC） in Kazakh, a high EC incidence area of Xinjiang Uygur Autonomous Region, China. METHODS： A 1：2 matched case-control study was conducted with 120 cases of EC and 240 populationor hospital-based controls. The controls were matched for sex, nationality, area of residence and age within a 5-year difference. MTHER and CYP4502E1 genotypes were identified by PCR-based restriction fragment length polymorphism （RFLP）. A conditional logistic regression model was established to identify risk factors. The strata method was adopted in interaction analysis. RESULTS： Low consumption of green vegetables and fresh fruits, alcohol drinking, and unsafe water （shallow well, or river） were found to be the risk factors for EC. Individuals with the MTHFR677 （C/T ＋ T/T） genotype had a 2.62-fold （95% CI： 1.61-4.28） risk of developing EC compared with those who carried the C/C genotype. Individuals with the CYP4502EIC1/C1 genotype had a 3.00-fold （95% CI： 1.82-4.96） risk compared with those who carried the CYP4502E1 （C1/C2 ＋ C2/C2） genotype. Gene-environment interaction analysis showed that MTHFR677 gene polymorphism was correlated with consumption of green vegetables and fresh fruit, while CYP4502E1 C1/C1 was correlated with alcohol drinking and unsafe drinking water. MTHFR and CYP4502E1 analysis of gene-gene interaction showed that individuals with the MTHFR677 （C/T ＋ T/T） and CYP4502EIC1/ C1 genotypes had a 7.41-fold （95% CI： 3.60-15.25） risk of developing EC compared with those who carried the MTHFR677C/C and CYP4502E1 RsaI C1/C2 ＋ C2/C2 genes, and the interaction rate was higher than that of the two factors alone. CONCLUSION： Low consumption of green vegetables and fresh fruits, alcohol drinking, and unsafe water （shallow well, or river） and polymorphisms in MTHFR and CYP4502E1 genes are important risk factors for EC. There is a synergistic interaction among polymorphisms in MTHFR and CYP4502E1 genes and environment factors. MTHFR and CYP4502E1 genes can be used as biomarkers for prevention of EC in Kazakh, Xinjiang Uygur Autonomous Region, China.

Snow cover estimation from MODIS and Sentinel-1 SAR data using machine learning algorithms in the western part of the Tianshan Mountains

Obtaining the spatial distribution of snow cover in mountainous areas using the optical image of remote sensing technology is difficult because of cloud and fog. In this study, the object-based principle component analysis–support vector machine(PCA–SVM) method is proposed for snow cover mapping through the integration of moderateresolution imaging spectroradiometer(MODIS) snow cover products and the Sentinel-1 synthetic aperture radar(SAR) scattering characteristics. First, derived from the Sentinel-1 A SAR images, the feature parameters, including VV/VH backscatter, scattering entropy, and scattering alpha, were used to describe the variations of snow and non-snow covers. Second, the optimum feature combinations of snow cover were formed from the feature parameters using the principle component analysis(PCA) algorithm. Finally, using the optimum feature combinations, a snow cover map with a 20 m spatial resolution was extracted by means of an object-based SVM classifier. This method was applied in the study area of the Xinyuan County, which is located in the western part of the Tianshan Mountains in Xinjiang, China. The accuracies in this method were analyzed according to the data observed at different experimental sites. Results showed that the snow cover pixels of the extraction were less than those in the actual situation(FB1=93.86, FB2=59.78). The evaluation of the threat score(TS), probability of detection(POD), and false alarm ratio(FAR) for the snow-covered pixels obtained from the two-stage SAR images were different(TS1=86.84, POD1=90.10, FAR1=4.01;TS2=56.40, POD2=57.62, FAR2=3.62). False and misclassifications of the snow cover and non-snow cover pixels were found. Although the classifications were not highly accurate, the approach showed potential for integrating different sources to retrieve the spatial distribution of snow covers during a stable period.