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Asian Journal of Andrology 2014年第4期16卷 536-540页

作者： Jianfeng Xu Fudan institute of Urology Huashan Hospital Shanghai State Key Laboratory of Genetic Engineering School of Life Science Shanghai School of Public Health Fudan University Shanghai China Center for Cancer Genomics Wake Forest School of Medicine. Winston-Salem. North Carolina. USA.

Elevated serum prostate-specific antigen （PSA） level is the primaryindication for prostate biopsy for detection of prostate cancer （PCa） in the modern era. The detection rate of PCa from biopsy is typically below 30%, especially among patients with PSA levels at 4-10 ng ml-1. In the past several years, additional biomarkers, such as Prostate Health Index, PCA3 and genetic risk score （GRS） derived from multiple PCa risk-associated single nucleotide polymorphisms （SNPs） have been shown to provide added value to PSA in discriminating prostate biopsy outcomes. However,

关键词： MOLECULAR URINE TEST 5 GENETIC-VARIANTS MULTICENTER EVALUATION RISK PCA3 MEN PREDICTION MARKERS SERUM SCORE

A hybrid deep learning model for robust prediction of the dimensional accuracy in precision milling of thin-walled structural components

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Frontiers of Mechanical Engineering 2022年第3期17卷 195-208页

作者： Long BAI Fei xu Xiao CHEN Xin SU Fuyao LAI Jianfeng Xu State Key Laboratory of Digital Manufacturing Equipment and Technology School of Mechanical Science and EngineeringHuazhong University of Science and TechnologyWuhan430074China Southwest Institution of Electronic Technology Chengdu610036China

The use of artificial intelligence to process sensor data and predict the dimensional accuracy of machined parts is of great interest to the manufacturing community and can facilitate the intelligent production of many key engineering components.In this study,we develop a predictive model of the dimensional accuracy for precision milling of thin-walled structural components.The aim is to classify three typical features of a structural component—squares,slots,and holes—into various categories based on their dimensional errors(i.e.,“high precision,”“pass,”and“unqualified”).Two different types of classification schemes have been considered in this study:those that perform feature extraction by using the convolutional neural networks and those based on an explicit feature extraction procedure.The classification accuracy of the popular machine learning methods has been evaluated in comparison with the proposed deep learning model.Based on the experimental data collected during the milling experiments,the proposed model proved to be capable of predicting dimensional accuracy using cutting parameters(i.e.,“static features”)and cutting-force data(i.e.,“dynamic features”).The average classification accuracy obtained using the proposed deep learning model was 9.55%higher than the best machine learning algorithm considered in this paper.Moreover,the robustness of the hybrid model has been studied by considering the white Gaussian and coherent noises.Hence,the proposed hybrid model provides an efficient way of fusing different sources of process data and can be adopted for prediction of the machining quality in noisy environments.

关键词： precision milling dimensional accuracy cutting force convolutional neural networks coherent noise

Translation of genomics and epigenomics in prostate cancer： progress and promising directions

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Asian Journal of Andrology 2016年第4期18卷 503-504页

作者： Wennuan Liu Jianfeng Xu NorthShore University HealthSystem Program for Personalized Cancer Care 1001 University Place Evanston IL 60201 USA.

During the last several years, exciting discoveries have been madein prostate cancer （PCa） as a result of significant advances in genomic technology and information. For example, using genome-wide association studies, more than 100 inherited genetic variants associated with PCa risk have been identified. Similarly, with the use of next-generation sequencing, various types of recurrent somatic DNA alterations in prostate tumors have been revealed. Some of these discoveries have potential clinical application to supplement existing tools for better decision-making regarding the need for screening, biopsy, and treatment of PCa. However, because of the complexity of these genomic findings and incomplete understanding of the genetics of this multifactorial disease, this potential has not yet been fully realized.

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Current progress and questions in germline genetics of prostate cancer

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Asian Journal of Urology 2019年第1期6卷 3-9页

作者： William B.Isaacs Jianfeng Xu Brady Urological Institute Johns Hopkins UniversitySchool of MedicineSidney Kimmel Comprehensive Cancer CenterBaltimoreMDUSA North Shore University Health System Research InstituteEvanstonILUSA

Dramatic progress has been made in the area of germline genetics of prostate cancer(PCa)in the past decade.Both common and rare genetic variants with effects on risk ranging from barely detectable to outright practice-changing have been identified.For men with high risk PCa,the application of genetic testing for inherited pathogenic mutations is becoming standard of care.A major question exists about which additional populations of men to test,as men at all risk levels can potentially benefit by knowing their unique genetic profile of germline susceptibility variants.This article will provide a brief overview of some current issues in understanding inherited susceptibility for PCa.

关键词： Genetic susceptibility BRCA2 Single-nucleotide polymorphisms Mutations Germline genetics Prostate cancer

Personalized prostate cancer care： from screening totreatment

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Asian Journal of Andrology 2016年第4期18卷 505-508页

作者： Carly A Conran Charles B Brendler Jianfeng Xu Program for Personalized Cancer Care NorthShore University HealthSystem 1001 University Place Evanston IL 60201 USA.

Unprecedented progress has been made in genomic personalized medicine in the last several years, allowing for more individualized healthcare assessments and recommendations than ever before. However, most of this progress in prostate cancer （PCa） care has focused on developing and selecting therapies for late-stage disease. To address this issue of limited focus, we propose a model for incorporating genomic-based personalized medicine into all levels of PCa care, from prevention and screening to diagnosis, and ultimately to the treatment of both early-stage and late-stage cancers. We have termed this strategy the ＂Pyramid Model＂ of personalized cancer care. In this perspective paper, our objective is to demonstrate the potential application of the Pyramid Model to PCa care. This proactive and comprehensive personalized cancer care approach has the potential to achieve three important medical goals： reducing mortality, improving quality of life and decreasing both individual and societal healthcare costs.

关键词： genetic risk score prostate cancer pyramid model single nucleotide polymorphisms

Foundations and Applications of Information Systems Dynamics

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Engineering 2023年第8期27卷 254-265页

作者： Jianfeng Xu Zhenyu Liu Shuliang Wang Tao Zheng Yashi Wang Yingfei Wang Yingxu Dang Information Technology Service Center of People’s Court Beijing 100745China School of Information Management for Law China University of Political Science and LawBeijing 102249China School of Computer Science and Technology Beijing Institute of TechnologyBeijing 100081China School of Mathematics and Statistics Beijing Institute of TechnologyBeijing 100081China

Although numerous advances have been made in information technology in the past decades,there is still a lack of progress in information systems dynamics(ISD),owing to the lack of a mathematical foundation needed to describe information and the lack of an analytical framework to evaluate information systems.The value of ISD lies in its ability to guide the design,development,application,and evaluation of largescale information system-of-systems(So Ss),just as mechanical dynamics theories guide mechanical systems engineering.This paper reports on a breakthrough in these fundamental challenges by proposing a framework for information space,improving a mathematical theory for information measurement,and proposing a dynamic configuration model for information systems.In this way,it establishes a basic theoretical framework for ISD.The proposed theoretical methodologies have been successfully applied and verified in the Smart Court So Ss Engineering Project of China and have achieved significant improvements in the quality and efficiency of Chinese court informatization.The proposed ISD provides an innovative paradigm for the analysis,design,development,and evaluation of large-scale complex information systems,such as electronic government and smart cities.

关键词： System-of-systems engineering Information theory Information measurement Information systems dynamics Judicial informatization

Prostate cancer risk-associated genetic markers and their potential clinical utility

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Asian Journal of Andrology 2013年第3期15卷 314-322页

作者： Jianfeng Xu Jielin Sun S Lilly Zheng Fudan Institute of Urology Huashan Hospital Fudan University Shanghai 200040 China State Key Laboratory of Genetic Engineering Fudan University Shanghai 200433 China Center for Genetic Epidemiology School of Life Sciences Fudan University Shanghai 200433 China Center for Cancer Genomics Wake Forest School of Medicine Winston-Salem NC 27157 USA

Prostate cancer （PCa） is one of the most common cancers among men in Western developed countries and its incidence has increased considerably in many other parts of the world, including China. The etiology of PCa is largely unknown but is thought to be multifactorial, where inherited genetics plays an important role. In this article, we first briefly review results from studies of familial aggregation and genetic susceptibility to PCa. We then recap key findings of rare and high-penetrance PCa susceptibility genes from linkage studies in PCa families. We devote a significant portion of this article to summarizing discoveries of common and Iow-penetrance PCa risk-associated single-nucleotide polymorphisms （SNPs） from genetic association studies in PCa cases and controls, especially those from genome-wide association studies （GWASs）. A strong focus of this article is to review the literature on the potential clinical utility of these implicated genetic markers. Most of these published studies described PCa risk estimation using a genetic score derived from multiple risk-associated SNPs and its utility in determining the need for prostate biopsy. Finally, we comment on the newly proposed concept of genetic score; the notion is to treat it as a marker for genetic predisposition, similar to family history, rather than a diagnostic marker to discriminate PCa patients from non-cancer patients. Available evidence to date suggests that genetic score is an objective and better measurement of inherited risk of PCa than family history. Another unique feature of this article is the inclusion of genetic association studies of PCa in Chinese and Japanese populations.

关键词： biopsy Chinese family history genetic score heritability prostate cancer （PCa） prostate-specific antigen （PSA） PSA screen singie-nucleotide polymorphisms （SNPs）

Clinically available RNA profiling tests of prostate tumors： utility and comparison

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Asian Journal of Andrology 2016年第4期18卷 575-579页

作者： Rong Na Yishuo Wu Qiang Ding Jianfeng Xu Fudan Institute of UrologY Huashan Hospital Fudan University Shanghai China Department of Urology Huashan Hospital Fudan University Shanghai China Program for Personalized Cancer Care NorthShore University HealthSystem Evanston IL USA.

In the postscreening era, physicians are in need of methods to discriminate aggressive from nonaggressive prostate cancer （PCa） to reduce overdiagnosis and overtreatment. However, studies have shown that prognoses （e.g., progression and mortality） differ even among individuals with similar clinical and pathological characteristics. Existing risk classifiers （TMN grading system, Gleason score, etc.） are not accurately enough to represent the biological features of PCa. Using new genomic technologies, novel biomarkers and classifiers have been developed and shown to add value to clinical or pathological risk factors for predicting aggressive disease. Among them, RNA testing （gene expression analysis） is useful because it can not only reflect genetic variations but also reflect epigenetic regulations. Commercially available RNA profiling tests （Oncotype Dx, Prolaris, and Decipher） have demonstrated strong abilities to discriminate PCa with poor prognosis from less aggressive diseases. For instance, these RNA profiling tests can predict disease progression in active surveillance patients or early recurrence after radical treatments. These tests may offer more dependable methods for PCa prognosis prediction to make more accurate and personal medical decisions.

关键词： precision medicine prostate cancer RNA profiling

Effects of Different Raw Materials and Additions on Wave Transparency of Alumina Fiber Products

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China's Refractories 2024年第1期33卷 40-43页

作者： WANG Jia SUN Xiaofei xu jianfeng xu Peipei Sinosteel Luoyang Institute of Refractories Research Co. Ltd.Luoyang 471039China

Fiber products for microwave kilns were prepared using alumina fibers with alumina contents of 72 mass%and 80 mass%,and calcined alumina powder(4-6μm)as the main raw materials,silica sol as the binder,and cationic starch as the flocculant.Effects of different raw materials and their additions on the wave transparency of fiber products were researched.The results show that as the alumina fiber(72%)addition increases,the heating rate of the samples first decreases and then increases,and the corresponding wave transparency of the sample first increases and then decreases.When the alumina fibers addition is 40 mass%and the alumina powder addition is 30 mass%,the prepared microwave kiln lining material has a higher mullite content,which improves the wave transparency of the sample.The sample prepared from alumina fibers with an alumina content of 80%has a suitable glass-mullite phase ratio,performs lower overall dielectric constant and good wave transparency,and is a suitable lining material for microwave kilns.

关键词： alumina fibers microwave kiln wave transparency

A hybrid physics-data-driven surface roughness prediction model for ultra-precision machining

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Science China(Technological Sciences) 2023年第5期66卷 1289-1303页

作者： BAI Long YANG QiZhong CHENG Xin DING Yue xu jianfeng State Key Laboratory of Digital Manufacturing Equipment and Technology School of Mechanical Science and EngineeringHuazhong University of Science and TechnologyWuhan430074China Wuhan Digital Design and Manufacturing Innovation Center Co. LtdWuhan430074China

The surface finish quality is critical to the service performance of a machined part,and single-point diamond ultra-precision machining can achieve excellent surface quality for many engineering materials.This study studied the problem of predicting the surface roughness for titanium alloy workpieces in ultra-precision machining.Process data and surface roughness measurement results were obtained during end-face machining experiments.A deep learning neural network model was built based on the ResNet-50 architecture to predict surface roughness.We propose increasing prediction accuracy by using the energy ratio difference(ERD)as a stability feature that can be extracted using fast iterative variational mode decomposition(FI-VMD).The roughness value obtained with an analytic model was also used as an input feature of the prediction model.The prediction accuracy of the proposed approach was depicted to be improved by 8.7%with the two newly introduced roughness predictors.The influence of the tool parameters on the prediction accuracy was investigated,and the proposed hybrid-driven model exhibited higher robustness to errors of the tool parameters than the analytic roughness model.

关键词： surface roughness ultra-precision machining prediction model stability feature