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| 1 | Behaviour of a series piezoelectric sensorin electrolyte solution 显示文摘 | Zhong Shenda Ha Nieli | 1993 | Enzyme Microb Anal China Aeta1993，276，1： | 1 |
| 2 | Antibacterial action of a novel functionalized chitosan-arginine against Gram-negative bacteria显示文摘 | Hong Tang Peng Zhang Thomas L. Kieft Shannon J. Ryan Shenda M. Baker William P. Wiesmann Snezna Rogelj | 2010 | Acta Biomaterialia2010，，7： | 1 |
| 3 | Artificial Intelligence in Skin Diseases:Fulfilling its Potentials to Meet the Real Needs in Dermatology Practice显示文摘Artificial intelligence(AI)medical image analysis techniques based on deep learning and machine learning have developed rapidly in recent years.Since the diagnosis of skin diseases is mainly based on the morphology of lesions,dermatology is considered a promising area for AI image analysis techniques.In 2017,scientists from Stanford University published a milestone paper in Nature to show the performance of AI was comparable to dermatologists in the classification and recognition of skin cancer,using convolutional neural network(CNN)models trained on nearly 130,000 clinical images[1].Since then,many countries have been actively developing similar products.So far,the U.S.Food and Drug Administration has approved 3Drem,Google DeepMind,and SkinVision.In China,Youzhi Pifu,Voxel-Cloud DermX,and Meitueve have entered the public view.The public’s interest in AI roars,and the imagination of AI replacing dermatologists seems to be a reality in the foreseen future. | Yicen Yan Shenda Hong Wensheng Zhang Hang Li | 2022 | Health Data Science2022，，1： | 0 |
| 4 | An Investigation of Regional Variations in the Biaxial Mechanical Properties of Porcine Mitral Valve显示文摘Objective Mitral valve(MV)plays an importance role in regulating blood flow from left atrium to left ventricle and preventing backflow to left atrium.Mitral Valve consist of four important parts;anterior leaflet,posterior leaflet,chordae tendineae,and papillary muscles,which all work in harmony.The material properties alteration on the leaflet causes MV malfunction,and leading to valve diseases such as regurgitation and stenosis.The alteration may be caused by several factors such as calcification,genetic disorders,and infection,which usually have an influence to the mechanical properties,and thus affecting the mechanical behavior of MV.In consequence,some of the patients need MV replacement or repair to restore the normal function of MV.The important point for succeeding such a medical treatment depends on the technique,design,and material used in the treatment shall help rebuild the normal mechanical environment and behavior of MV.Therefore,the mechanical and materials characteristics of MV become a magnetism to explore.In this study,we present an integrated experimental and mathematical constitutive study base in collagen distribution aiming at the mechanical property differences in various region on MV.Methods and materials Both the size and composition of porcine valves are similar to human’s,so the porcine heart valve is often being used in experimental research.Mitral valve was isolated from fresh eight porcine hearts(250-500 gr),and perfused in PBS solution to maintain moist.Anterior and posterior leaflets were separated and dissected into 4 part(two 8~*8 mm rough zone and two clear zone samples)and 2 part(8~*8 mm belly and edge of the clear zone)respectively.Tracking markers(glass bean)were stickled on specimen with superglue(cyanoacrylate adhesive).Then,the specimen was mounted onto biaxial tester machine(CeIIScale,Biotester),and the tests are run by force control.During mechanical test,the specimen is immersed into PBS solution in physiological temperature(37℃).Every test procedure contains 8 preconditioning cycles and 8 loading cycles.The mechanical behavior was determined from the relationship between first Piola-Kirchoff stress and stretch.Constitutive model was reconstructed and material parameters were fitted from biaxial tensile result.Histological analyses were performed in the specimen before and after test.First,a piece of the specimen was cut and immersed in fixation solution(4%paraformaldehyde),then it was dehydrated in graded alcohol solution,and next embedding in paraffin wax block.Paraffin block was then cut and stained with VVG and Picro-sirius red.The collagen fibril orientation was observed from those histological results.Results The experimental results of the clear zone of MV’s first Piola-Kirchhoff stress and stretch curve are similar to those of the recent study from others,while result of the rough zone shows a different trend.This can be explained by differences in collagen distribution between clear zone and rough zone of MV.Our result thus allows for a refinement of computational models for more accurately predicting MV condition,where tissue heterogeneity plays an important role in the MV function. | Candra Ratna Sari Shenda Chen Yang Lei Hao Gao Guixue Wang Xingsuang Ma | 2019 | 医用生物力学2019，34，A01： | 0 |
| 5 | Targeting HSPA1A in ARID2-deficient lung adenocarcinoma显示文摘Somatic mutations of the chromatin remodeling gene ARID2 are observed in~7%of human lung adenocarcinomas(LUADs).However,the role of ARID2 in the pathogenesis of LUADs remains largely unknown.Here we find that ARID2 expression is decreased during the malignant progression of both human and mice LUADs.Using two Kras^(G12D)-based genetically engineered murine models,we demonstrate that ARID2 knockout significantly promotes lung cancer malignant progression and shortens overall survival.Consistently,ARID2 knockdown significantly promotes cell proliferation in human and mice lung cancer cells.Through integrative analyses of Ch IP-Seq and RNA-Seq data,we find that Hspa1 a is up-regulated by Arid2 loss.Knockdown of Hspa1 a specifically inhibits malignant progression of Arid2-deficient but not Arid2-wt lung cancers in both cell lines as well as animal models.Treatment with an HSPA1 A inhibitor could significantly inhibit the malignant progression of lung cancer with ARID2 deficiency.Together,our findings establish ARID2 as an important tumor suppressor in LUADs with novel mechanistic insights,and further identify HSPA1 A as a potential therapeutic target in ARID2-deficient LUADs. | Xue Wang Yuetong Wang Zhaoyuan Fang Hua Wang Jian Zhang Longfu Zhang Hsinyi Huang Zhonglin Jiang Yujuan Jin Xiangkun Han Shenda Hou Bin Zhou Feilong Meng Luonan Chen Kwok-Kin Wong Jinfeng Liu Zhiqi Zhang Xin Zhang Haiquan Chen Yihua Sun Liang Hu Hongbin Ji | 2021 | National Science Review2021，8，10： | 0 |
| 6 | Status quo of textile industry of 2016显示文摘In 2016,in the complex situation of global economic downturn and sluggish market demand,China’s textile industry achieved steady increase with stable profitability and sustainable improvement of operation quality throughout the year,by virtue of further improving transformation and upgrading as well as positively implementing supplyfront structural reform,while the enterprises still faced the pressure of heavy cost burden. | shenda | 2017 | China Textile2017，，3： | 0 |
| 7 | Evolution from genetics to phenotype: reinterpretation of NSCLC plasticity, heterogeneity, and drug resistance显示文摘肺癌症是世界范围的癌症相关的死亡的领先的原因。指向的治疗作为到好预后的一个障碍在药抵抗看台的大多数情况,而是发展中是有益的。多重机制被探索例如基因改变,激活绕过发信号,并且 phenotypic 转变。这些内在或外来的动态规定在遇见在不同刺激下面发信号的要求便于肿瘤房间幸存。这评论介绍有药抵抗的肺癌症粘性和异质和他们的关联。当癌症粘性和异质在药抵抗的发展起一个必要作用时,他们的操作可以把一些灵感带到癌症预后和治疗。那是说,肺癌症粘性和异质与不仅挑战而且机会介绍我们。 | Yingjiao Xue Shenda Hou Hongbin Ji Xiangkun Han | 2017 | Protein & Cell2017，8，3： | 0 |
| 8 | Predicting Risk of Mortality in Pediatric ICU Based on Ensemble Step-Wise Feature Selection显示文摘Background.Prediction of mortality risk in intensive care units(ICU)is an important task.Data-driven methods such as scoring systems,machine learning methods,and deep learning methods have been investigated for a long time.However,few datadriven methods are specially developed for pediatric ICU.In this paper,we aim to amend this gap—build a simple yet effective linear machine learning model from a number of hand-crafted features for mortality prediction in pediatric ICU.Methods.We use a recently released publicly available pediatric ICU dataset named pediatric intensive care(PIC)from Children’s Hospital of Zhejiang University School of Medicine in China.Unlike previous sophisticated machine learning methods,we want our method to keep simple that can be easily understood by clinical staffs.Thus,an ensemble step-wise feature ranking and selection method is proposed to select a small subset of effective features from the entire feature set.A logistic regression classifier is built upon selected features for mortality prediction.Results.The final predictive linear model with 11 features achieves a 0.7531 ROC-AUC score on the hold-out test set,which is comparable with a logistic regression classifier using all 397 features(0.7610 ROC-AUC score)and is higher than the existing well known pediatric mortality risk scorer PRISM III(0.6895 ROC-AUC score).Conclusions.Our method improves feature ranking and selection by utilizing an ensemble method while keeping a simple linear form of the predictive model and therefore achieves better generalizability and performance on mortality prediction in pediatric ICU. | Shenda Hong Xinlin Hou Jin Jing Wendong Ge Luxia Zhang | 2021 | Health Data Science2021，，1： | 0 |
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