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Prediction of Driver Gene Matching in Lung Cancer NOG/PDX Models Based on Artificial Intelligence

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Engineering 2022年第8期8卷 102-114页

作者： Yayi He Haoyue Guo Li Diao Yu Chen Junjie Zhu Hiran C.Fernando Diego Gonzalez Rivas Hui Qi Chunlei Dai Xuzhen Tang Jun Zhu Jiawei Dai Kan He Dan Chan Yang Yang School of Medicin5 Tongji UniversityShanghai 200092China Department of Medical Oncology Shanghai Pulmonary HospitalSchool of Medicin5Tongji UniversityShanghai 200433China Department of Automation School of Electronic Information and Electrical Engineerin7Shanghai Jiao Tong UniversityShanghai 200240China Spine Center Orthopedic DepartmentShanghai Changzheng HospitalShanghai 200003China Department of Thoracic Surgery Shanghai Pulmonary HospitalSchool of Medicin5Tongji UniversityShanghai 200433China School of Materials Science and Engineerin7 Tongji UniversityShanghai 201804China Department of Thoracic Surgery Allegheny General HospitalPittsburg8PA 15212USA Department of Thoracic Surgery and Minimally Invasive Thoracic Surgery Unit(UCTMI) Coruna University HospitalCoruna 15006Spain Oncology and Immunology BU Research Service DivisionWuXi Appte3Shanghai 200131China SJTU–Yale Joint Center for Biostatistics and Data Scienc5 Department of Bioinformatics and BiostatisticsSchool of Life Sciences and BiotechnologyShanghai Jiao Tong UniversityShanghai 200240China Division of Medical Oncology Department of Medicin5University of Colorado Anschutz Medical CampusAuror1CO 80045USA

Patient-derived tumor xenografts(PDXs)are a powerful tool for drug discovery and screening in ***,current studies have led to little understanding of genotype mismatches in PDXs,leading to massive economic ***,we established PDX models from 53 lung cancer patients with a genotype matching rate of 79.2%(42/53).Furthermore,17 clinicopathological features were examined and input in stepwise logistic regression(LR)models based on the lowest Akaike information criterion(AIC),least absolute shrinkage and selection operator(LASSO)-LR,support vector machine(SVM)recursive feature elimination(SVM-RFE),extreme gradient boosting(XGBoost),gradient boosting and categorical features(Cat Boost),and the synthetic minority oversampling technique(SMOTE).Finally,the performance of all models was evaluated by the accuracy,area under the receiver operating characteristic curve(AUC),and F1 score in 100 testing *** multivariable LR models revealed that age,number of driver gene mutations,epidermal growth factor receptor(EGFR)gene mutations,type of prior chemotherapy,prior tyrosine kinase inhibitor(TKI)therapy,and the source of the sample were powerful ***,Cat Boost(mean accuracy=0.960;mean AUC=0.939;mean F1 score=0.908)and the eight-feature SVM-RFE(mean accuracy=0.950;mean AUC=0.934;mean F1 score=0.903)showed the best performance among the ***,application of the SMOTE improved the predictive capability of most models,except Cat *** on the SMOTE,the ensemble classifier of single models achieved the highest accuracy(mean=0.975),AUC(mean=0.949),and F1 score(mean=0.938).In conclusion,we established an optimal predictive model to screen lung cancer patients for non-obese diabetic(NOD)/Shi-scid,interleukin-2 receptor(IL-2R)γ^(null)(NOG)/PDX models and offer a general approach for building predictive models.

关键词： Machine learning Patient-derived tumor xenografts NOG mice

The expanded development and application of CRISPR system for sensitive nucleotide detection

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Protein & Cell 2020年第9期11卷 624-629页

作者： Fengjing Jia Xuewen Li Chao Zhang Xueming Tang Translational Medical Center for Stem Cell Therapy and Institute for Regenerative Medicine Shanghai East HospitalShanghai Key Laboratory of Signaling and Disease ResearchSchool of Life Sciences and TechnologyTongji UniversityShanghai 200000China Institute of Biotechnology Research Shanghai Academy of Agricultural SciencesKey Laboratory of Agricultural Genetics and BreedingShanghai 201106China Crops Ecological Environment Security Inspection and Supervision Center(shanghai) Ministry of Agriculture and Rural AffairsShanghai 201106China Silicon Gene Tech Co. Ltd.Shanghai 200124China

CRISPR/Cas system,originally developed as genetic editing tool,also shows great potentials for nucleotide detection.A recent study published in Molecular Cell(Freije et al.,2019)developed a Cas13a-based CARVER(Cas13-assisted restriction of viral expression and readout)to detect RNA viruses such as lymphocytic choriomeningitis,influenza A and vesicular stomatitis,which provided a potential expanded application for the detection of a broad range of viral nucleotides in disease diagnosis.

关键词： CRISPR/Cas expanded application

石墨烯氢氧化钴复合催化剂的一步合成及其对酸性橙的催化降解(英文)

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物理化学学报 2014年第9期30卷 1720-1726页

作者：李洁冰伊玉时鹏辉王倩李登新 ASIF Hussain 杨明东华大学环境科学与工程学院国家环境保护纺织工业污染防治工程技术中心上海201620 上海电力学院环境与化学工程学院上海200090 东华大学分析测试中心上海201620

用一步合成自组装法制备出了氢氧化钴与还原氧化石墨烯(Co(OH)2/rGO)的复合催化剂,并将其用于水中染料的催化降解实验.通过X射线衍射(XRD),激光拉曼(Raman)光谱,透射电镜(TEM),X射线能量色散谱(EDS)以及X射线光电子能谱(XPS)等一系列分... 详细信息

用一步合成自组装法制备出了氢氧化钴与还原氧化石墨烯(Co(OH)2/rGO)的复合催化剂,并将其用于水中染料的催化降解实验.通过X射线衍射(XRD),激光拉曼(Raman)光谱,透射电镜(TEM),X射线能量色散谱(EDS)以及X射线光电子能谱(XPS)等一系列分析手段对催化剂的结构形貌进行了详细的表征,表征结果证实氢氧化钴很好地附着在还原石墨烯的表面.最后初步考察了催化剂催化单过硫酸钾(PMS)降解酸性橙(AO7)的性能.结果表明,催化剂显示出了高效的催化性能,酸性橙的色度可在12 min内完全去除,总有机碳(TOC)实验也表明染料降解的同时也可获得较高的矿化度.循环稳定性实验表明在进行到第三次实验时,催化剂仍能保持高的催化活性,将酸性橙在16 min内降解完毕.

关键词：高级氧化单过硫酸氢钾氢氧化钴石墨烯酸性橙

COVID-19 and Alzheimer’s disease:how one crisis worsens the other

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Translational Neurodegeneration 2021年第2期10卷 178-194页

作者： Xiaohuan Xia Yi Wang Jialin Zheng Center for Translational Neurodegeneration and Regenerative Therapy Tenth People’s Hospital of Tongji UniversityShanghai 200072China Translational Research Institute of Brain and Brain-Like Intelligence Shanghai Fourth People’s Hospital Affiliated to Tongji University School of MedicineShanghai 200434China Collaborative Innovation Center for Brain Science Tongji UniversityShanghai 200092China Department of Pharmacology and Experimental Neuroscience University of Nebraska Medical CenterOmahaNE 68198-5930USA

Alzheimer’s disease(AD)has emerged as a key comorbidity of coronavirus disease 2019(COVID-19)caused by severe acute respiratory syndrome coronavirus-2(SARS-CoV-2).The morbidity and mortality of COVID-19 are elevated in AD due to multiple pathological changes in AD patients such as the excessive expression of viral receptor angiotensin converting enzyme 2 and pro-inflammatory molecules,various AD complications including diabetes,lifestyle alterations in AD,and drug-drug ***,COVID-19 has also been reported to cause various neurologic symptoms including cognitive impairment that may ultimately result in AD,probably through the invasion of SARS-CoV-2 into the central nervous system,COVID-19-induced inflammation,long-term hospitalization and delirium,and post-COVID-19 *** addition,the COVID-19 crisis also worsens behavioral symptoms in uninfected AD patients and poses new challenges for AD *** this review,we first introduce the symptoms and pathogenesis of COVID-19 and ***,we provide a comprehensive discussion on the aggravating effects of AD on COVID-19 and the underlying mechanisms from molecular to social *** also highlight the influence of COVID-19 on cognitive function,and propose possible routes of viral invasion into the brain and potential mechanisms underlying the COVID-19-induced cognitive ***,we summarize the negative impacts of COVID-19 pandemic on uninfected AD patients and dementia prevention.

关键词： COVID-19 SARS-CoV-2 Alzheimer’s disease Central nervous system Inflammation Cognitive impairment Angiotensin converting enzyme 2

The excessive response： a preparation for harder conditions

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Protein & Cell 2017年第10期8卷 707-710页

作者： Yaguang Ren Chao Zhang Translational Medical Center for Stem Cell Therapy and Institute for Regenerative Medicine Shanghai East Hospital Shangha Key Laboratory of Signaling and Disease Research School of Life Sciences and Technology Tongji University Shangha 200433 China

Reactive oxygen species （ROS） are kinds of reactive chemicals mainly formed in mitochondria as byproduct of normal metabolism of oxygen （Balaban et al., 2005）. Because of the high reactiveness they usually react with proteins, lipid, and nuclear acids （Labuschagne and Brenkman, 2013; Landolfo et al., 2008）, and in theory may participate in every aspects of cellular metabolism.

关键词： Excessive Response Prooxidant Stress Worm Level Devasagayam Paraquat Levels

BMAL1 functions as a cAMP-responsive coactivator of HDAC5 to regulate hepatic gluconeogenesis

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Protein & Cell 2018年第11期9卷 976-980页

作者： Jian Li Sihan Lv Xinchen Qiu Jiamin Yu Junkun Jiang Yalan Jin Wenxuan Guo| Ruowei Zhao Zhen-Ning Zhang Chao Zhang Bing Luan Department of Endocrinology Shanghai Tenth People's HospitalSchool of Medicine Tongji University Shanghai China Translational Medical Center for Stem Cell Therapy & Institute forRegenerative Medicine Shanghai East Hospital Shanghai KeyLaboratory of Signaling and Disease Research School of LifeSciences and Technology Tongji University Shanghai China

Dear Editor, Gluconeogenesis is one of the major mechanisms to main- tain hepatic glucose homeostasis and dysregulation of hepatic gluconeogenesis contributes to hyperglycemia in type 2 diabetes. Under fasted conditions, increases in cir- culating glucagon promote hepatic glucose production through activation of gluconeogenic pathway by HDAC5 and CREB coactivator CRTC2 （Lv et al., 2016; Lv et al., 2017; Qiu et al., 2017）. The circadian clock coordinates behavior and metabolism into rhythms not only in the central hypothalamus but also in peripheral tissues （Marcheva et al., 2010; Vollmers et al., 2009）. Transcription factor BMAL1 heterodimerizes with CLOCK to activate the expression of Per and Cry, which in turn suppress CLOCK/BMAL1 activity （Reppert ＆ Weaver, 2002）. Although BMAL1 knockout mice show fasting hypoglycemia （Rudic et al., 2004）, the detailed mechanism of BMAL1 regulation on hepatic gluco- neogenesis has not been thoroughly understood.

关键词： FOXO

Rapid seismic analysis methodology for in-service wind turbine towers

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Earthquake Engineering and Engineering Vibration 2015年第3期14卷 539-548页

作者： Dai Kaoshan Huang Yichao Gong Changqing Huang Zhenhua Ren Xiaosong State Key Laboratory of Disaster Reduction in Civil Engineering and College of Civil Engineering Tongji University State Key Lab of Power Transmission Equipment & System Security and New Technology Chongqing University Department of Engineering Technology University of North Texas

The wind energy industry has been growing rapidly during the past *** with this growth,engineering problems have gradually emerged in the wind power industry,including those related to the structural reliability of turbine *** study proposes a rapid seismic analysis methodology for existing wind turbine tower *** method is demonstrated and validated using a case study on a 1.5 MW tubular steel wind turbine *** finite element(FE)models are developed *** tests are conducted to obtain the turbine tower’s vibrational *** tests include(1) remotely measuring the tower vibration frequencies using a long range laser Doppler Vibrometer and(2) monitoring the tower structural vibration by mounting accelerometers along the height of the tubular ***-situ measurements are used to validate and update the FE models of the wind turbine *** the updated FE model that represents the practical structural conditions,seismic analyses are performed to study the structural failure,which is defined by the steel yielding of the tubular *** research is anticipated to benefit the management of the increasing number of wind energy converters by providing an understanding of the seismic assessment of existing tubular steel wind turbine towers.

关键词： wind turbine tower fi eld testing laser sensing se

A dynamic simulation model of passenger flow distribution on schedule-based rail transit networks with train delays

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Journal of Traffic and Transportation Engineering(English Edition) 2016年第4期3卷 364-373页

作者： Wei Li Key Laboratory of Road and Traffic Engineering of Ministry of Education Tongji Unioersity Shanghai 201804 China College of Transportation Engineering Tongji University Shanghai 201804 China

In a schedule-based rail transit system, passenger route choices are affected by train delays, and, consequently, the relevant passenger flow distribution of the network will differ from the normal state. In this paper, a passenger＇s alternative choices, such as selecting another route, waiting, and switching to other transportation modes, and the corresponding influence mechanism are analyzed in detail. Given train time-space diagrams and the time-varying travel demands between the origin and destination （O-D）, a dynamic simulation model of passenger flow distribution on schedule-based transit networks with train delays is proposed. Animation demonstration and statistical indices, including the passenger flow volume of each train and station, can be generated from simulation results. A numerical example is given to illustrate the application of the proposed model. Nu- merical results indicate that, compared with conventional methods, the proposed model performs better for a passenger flow distribution with train delays.

关键词： Urban rail transitPassenger flow distributionSimulation modelTrain delayPassenger choice behavior

A Normalizing Field Flow Induced Two-Stage Stochastic Homogenization Method for Random Composite Materials

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Communications in Computational Physics 2023年第8期34卷 787-812页

作者： Zihao Yang Xintong Wang Xiaofei Guan Jizu Huang Xixin Wu School of Mathematics and Statistics Northwestern Polytechnical UniversityXi’an 710072China Institute of Mathematics Henan Academy of SciencesZhengzhou 450046China MOE Key Laboratory for Complexity Science in Aerospace Northwestern Polytechnical UniversityXi’an 710072China School of Mathematical Sciences Tongji UniversityShanghai 200092China LSEC Academy of Mathematics and Systems ScienceChinese Academy of SciencesBeijing 100190China School of Mathematical Sciences University of Chinese Academy of SciencesBeijing 100049China

The traditional stochastic homogenization method can obtain homogenized solutions of elliptic problems with stationary random ***,many random composite materials in scientific and engineering computing do not satisfy the stationary *** overcome the difficulty,we propose a normalizing field flow induced two-stage stochastic homogenization method to efficiently solve the random elliptic problem with non-stationary *** applying the two-stage stochastic homogenization method,the original elliptic equation with random and fast oscillatory coefficients is approximated as an equivalent elliptic equation,where the equivalent coefficients are obtained by solving a set of cell *** the stationary assumption,the number of cell problems is large and the corresponding computational cost is *** improve the efficiency,we apply the normalizing field flow model to learn a reference Gaussian field for the random equivalent coefficients based on a small amount of data,which is obtained by solving the cell problems with the finite element *** results demonstrate that the newly proposed method is efficient and accurate in tackling high dimensional partial differential equations in composite materials with complex random microstructures.

关键词： Two-stage stochastic homogenization normalizing field flows multi-modes Monte Carlo method random composite materials non-stationary random