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Knowledge-embedded spatio-temporal analysis for euploidy embryos identification in couples with chromosomal rearrangements

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Chinese Medical Journal 2024年第6期137卷 694-703页

作者： Fangying Chen Xiang Xie Du Cai Pengxiang Yan Chenhui Ding Yangxing Wen Yanwen Xu Feng Gao Canquan Zhou Guanbin Li Qingyun Mai Reproductive Medicine Center The First Affiliated Hospital of Sun Yat-sen UniversityGuangzhouGuangdong 510080China Guangdong Provincial Key Laboratory of Reproductive Medicine GuangzhouGuangdong 510080China School of Computer Science and Engineering Sun Yat-sen UniversityGuangzhouGuangdong 510006China Department of General Surgery(Colorectal Surgery) The Sixth Affiliated Hospital of Sun Yat-sen UniversityGuangzhouGuangdong 510655China Guangdong Provincial Key Laboratory of Colorectal and Pelvic Floor Diseases The Sixth Affiliated HospitalSun Yat-sen UniversityGuangzhouGuangdong 510655China Biomedical Innovation Center The Sixth Affiliated HospitalSun Yat-sen UniversityGuangzhouGuangdong 510655China Shanghai Artificial Intelligence Laboratory Shanghai 200232China

Background:The goal of the assisted reproductive treatment is to transfer one euploid blastocyst and to help infertile women giving birth one healthy neonate.Some algorithms have been used to assess the ploidy status of embryos derived from couples with normal chromosome,who subjected to preimplantation genetic testing for aneuploidy(PGT-A)treatment.However,it is currently unknown whether artificial intelligence model can be used to assess the euploidy status of blastocyst derived from populations with chromosomal rearrangement.Methods:From February 2020 to May 2021,we collected the whole raw time-lapse videos at multiple focal planes from in vitro cultured embryos,the clinical information of couples,and the comprehensive chromosome screening results of those blastocysts that had received PGT treatment.Initially,we developed a novel deep learning model called the Attentive Multi-Focus Selection Network(AMSNet)to analyze time-lapse videos in real time and predict blastocyst formation.Building upon AMSNet,we integrated additional clinically predictive variables and created a second deep learning model,the Attentive Multi-Focus Video and Clinical Information Fusion Network(AMCFNet),to assess the euploidy status of embryos.The efficacy of the AMCFNet was further tested in embryos with parental chromosomal rearrangements.The receiver operating characteristic curve(ROC)was used to evaluate the superiority of the model.Results:A total of 4112 embryos with complete time-lapse videos were enrolled for the blastocyst formation prediction task,and 1422 qualified blastocysts received PGT-A(n=589)or PGT for chromosomal structural rearrangement(PGT-SR,n=833)were enrolled for the euploidy assessment task in this study.The AMSNet model using seven focal raw time-lapse videos has the best real-time accuracy.The real-time accuracy for AMSNet to predict blastocyst formation reached above 70%on the day 2 of embryo culture,and then increased to 80%on the day 4 of embryo culture.Combing with 4 clinical features of couples,the AUC of A

关键词： Euploidy status Embryo Time-lapse imaging Deep learning spatio-temporal analysis Preimplantation genetic testing for chromosomal structural rearrangement

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spatio-temporal analysis of the melt onset dates over Arctic sea ice from 1979 to 2017

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Acta Oceanologica Sinica 2022年第4期41卷 146-156页

作者： Shuang Liang Jiangyuan Zeng Zhen Li Dejing Qiao Key Laboratory of Digital Earth Science Aerospace Information Research InstituteChinese Academy of SciencesBeijing 100094China State Key Laboratory of Remote Sensing Science Aerospace Information Research InstituteChinese Academy of SciencesBeijing 100101China University of Chinese Academy of Sciences Beijing 100049China College of Surveying and Geo-Informatics North China University of Water Resources and Electric PowerZhengzhou 450045China

The melt onset dates(MOD)over Arctic sea ice plays an important role in the seasonal cycle of sea ice surface properties,which impacts Arctic surface solar radiation absorbed by the ice-ocean system.Monitoring interannual variations in MOD is valuable for understanding climate change.In this study,we investigated the spatio-temporal variability of MOD over Arctic sea ice and 14 Arctic sub-regions in the period of 1979 to 2017 from passive microwave satellite data.A set of mathematical and statistical methods,including the Sen’s slope and Mann-Kendall mutation tests,were used to comprehensively assess the variation trend and abrupt points of MOD during the past 39 years for different Arctic sub-regions.Additionally,the correlation between Arctic Oscillation(AO)and MOD was analyzed.The results indicate that:(1)all Arctic sub-regions show a trend toward earlier MOD except the Bering Sea and St.Lawrence Gulf.The East Siberian Sea exhibits a significantly earlier trend,with the highest rate of-9.45 d/decade;(2)the temporal variability and statistical significance of MOD trend exhibit large interannual differences with different time windows for most regions in the Arctic;(3)during the past 39 years,the MOD changed abruptly in different years for different sub-regions;(4)the seasonal AO has more influence on MOD than monthly AO.The findings in this study can improve our knowledge of MOD changes and are beneficial for further Arctic climate change study.

关键词： Arctic sea ice melt onset dates spatio-temporal analysis abrupt changes Arctic Oscillation

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Visceral leishmaniasis in northwest China from 2004 to 2018:a spatio-temporal analysis

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Infectious Diseases of Poverty 2020年第6期9卷 29-41页

作者： Canjun Zheng Liping Wang Yi Li Xiao-Nong Zhou Chinese Center for Diseases Control and Prevention(China CDC) Beijing102206China State Key Laboratory of Severe Weather&Key Laboratory of Atmospheric Chemistry of CMA Chinese Academy of Meteorological SciencesBeijing100081China Chinese Center for Diseases Control and Prevention National Institute of Parasitic DiseasesShanghai200025China

Background: Although visceral leishmaniasis(VL),a disease caused by parasites,is controlled in most provinces in China,it is still a serious public health problem and remains fundamentally uncontrolled in some northwest provinces and autonomous regions.The objective of this study is to explore the spatial and temporal characteristics of VL in Sichuan Province,Gansu Province and Xinjiang Uygur Autonomous Region in China from 2004 to 2018 and to identify the risk areas for VL transmission.Methods:: spatiotemporal models were applied to explore the spatio-temporal distribution characteristics of VL and the association between VL and meteorological factors in western China from 2004 to 2018.Geographic information of patients from the National Diseases Reporting Information System operated by the Chinese Center for Disease Control and Prevention was defined according to the address code from the surveillance data.Results: During our study period,nearly 90%of cases occurred in some counties in three western regions(Sichuan Province,Gansu Province and Xinjiang Uygur Autonomous Region),and a significant spatial clustering pattern was observed.With our spatiotemporal model,the transmission risk,autoregressive risk and epidemic risk of these counties during our study period were also well predicted.The number of VL cases in three regions of western China concentrated on a few of counties.VL in Kashi Prefecture,Xinjiang Uygur Autonomous Region is still serious prevalent,and integrated control measures must be taken in different endemic areas.Conclusions: The number of VL cases in three regions of western China concentrated on a few of counties.VL in Kashi Prefecture,Xinjiang Uygur Autonomous Region is still serious prevalent,and integrated control measures must be taken in different endemic areas.Our findings will strengthen the VL control programme in China.

关键词： Visceral leishmaniasis spatio-temporal analysis Spatial regression China

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Modeling and analysis of Production Logistics spatio-temporal Graph Network Driven by Digital Twin

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Journal of Donghua University(English Edition) 2022年第5期39卷 461-474页

作者：郑龙辉孙奕程张辉辉鲍劲松陈晓川赵振洪陈钟浩管瑞峰 College of Mechanical Engineering Donghua UniversityShanghai 201620China Shanghai Frontier Science Research Center for Modern Textiles Donghua UniversityShanghai 201620China Guangzhou Zhijing Information Technology Co. Ltd.Guangzhou 510220China

In the process of logistics distribution of manufacturing enterprises, the automatic scheduling method based on the algorithm model has the advantages of accurate calculation and stable operation, but it excessively relies on the results of data calculation, ignores historical information and empirical data in the solving process, and has the bottleneck of low processing dimension and small processing scale. Therefore, in the digital twin(DT) system based on virtual and real fusion, a modeling and analysis method of production logistics spatio-temporal graph network model is proposed, considering the characteristics of road network topology and time-varying data. In the DT system, the temporal graph network model of the production logistics task is established and combined with the network topology, and the historical scheduling information about logistics elements is stored in the nodes. When the dynamic task arrives, a multi-stage links probability prediction method is adopted to predict the possibility of loading, driving, and other link relationships between task-related entity nodes at each stage. Several experiments are carried out, and the prediction accuracy of the digital twin-based temporal graph network(DTGN) model trained by historical scheduling information reaches 99.2% when the appropriate batch size is selected. Through logistics simulation experiments, the feasibility and the effectiveness of production logistics spatio-temporal graph network analysis methods based on historical scheduling information are verified.

关键词： digital twin(DT) production logistics job scheduling spatio-temporal analysis

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Infuence of urbanization on schistosomiasis infection risk in Anhui Province based on sixteen year’s longitudinal surveillance data:a spatio-temporal modelling study

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Infectious Diseases of Poverty 2023年第6期12卷 99-100页

作者： Xin Liu Yang Sun Yun Yin Xiaofeng Dai Robert Bergquist Fenghua Gao Rui Liu Jie Liu Fuju Wang Xiao Lv Zhijie Zhang College of Geodesy and Geomatics Shandong University of Science and Technology Qingdao China No. 8 Institute of Geology and Mineral Resources Exploration of Shandong Province Rizhao China School of Public Health Fudan University Shanghai China Key Laboratory of Public Health Safety Ministry of Education Shanghai China Ingerod Brastad Sweden Anhui Institute of Schistosomiasis Control Hefei China

Background Urbanization greatly afects the natural and social environment of human existence and may have a multifactoral impact on parasitic diseases.Schistosomiasis,a common parasitic disease transmitted by the snail Oncomelania hupensis,is mainly found in areas with population aggregations along rivers and lakes where snails live.Previous studies have suggested that factors related to urbanization may infuence the infection risk of schistosomiasis,but this association remains unclear.This study aimed to analyse the efect of urbanization on schistosomiasis infection risk from a spatial and temporal perspective in the endemic areas along the Yangtze River Basin in China.Methods County-level schistosomiasis surveillance data and natural environmental factor data covering the whole Anhui Province were collected.The urbanization level was characterized based on night-time light data from the Defense Meteorological Satellite Program Operational Linescan System(DMSP-OLS)and the National Polar-Orbiting Partnership’s Visible Infrared Imaging Radiometer Suite(NPP-VIIRS).The geographically and temporally weighted regression model(GTWR)was used to quantify the infuence of urbanization on schistosomiasis infection risk with the other potential risk factors controlled.The regression coefcient of urbanization was tested for signifcance(α=0.05),and the infuence of urbanization on schistosomiasis infection risk was analysed over time and across space based on signifcant regression coefcients.Variables studied included climate,soil,vegetation,hydrology and topography.Results The mean regression coefcient for urbanization(0.167)is second only to the leached soil area(0.300),which shows that the urbanization is the most important infuence factors for schistosomiasis infection risk besides leached soil area.The other important variables are distance to the nearest water source(0.165),mean minimum temperature(0.130),broadleaf forest area(0.105),amount of precipitation(0.073),surface temperature(0.066),soil bulk density(0.037)and gr

关键词： Urbanization Night-time light data Schistosomiasis spatio-temporal analysis Geographically and temporally weighted regression

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Land use change in Bohai Rim: a spatial-temporal analysis

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Journal of Geographical Sciences 2001年第3期11卷 305-312页

作者： ZHU Hui-yi, LI Xiu-bin, HE Shu-jin, ZHANG Ming (Institute of Geographic Sciences and Natural Resources Research, CAS, Beijing 100101, China) Institute of Geographic Sciences and Natural Resources Research

Based on RS and GIS methods, land use information for 1985 and 1995 was acquired from TM images and analyzed. Then on both spatial and temporal aspects, this paper analyzes land use change in three provinces of Hebei, Shandong and Liaoning and two municipalities of Beijing and Tianjin in the Bohai Rim covering the period of 1985 to 1995. The extent, rate, areal difference and trend of various types of land use changes in the region, as well as spatial changes of major types of land use, their distribution characteristics and regional orientation are revealed. The regional characteristics of land use are elaborated, so as to provide effective policy support for sustainable land use in the area around the Bohai Bay.

关键词： Bohai Rim land use change spatio-temporal analysis

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MODIS-based air temperature estimation in the southeastern Tibetan Plateau and neighboring areas

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Journal of Geographical Sciences 2012年第1期22卷 152-166页

作者：姚永慧张百平 State Key Laboratory of Resource and Environmental Information System Institute of Geographic Sciences and Natural Resources Research CAS

Climatic conditions are difficult to obtain in high mountain regions due to few meteorological stations and, if any, their poorly representative location designed for convenient operation. Fortunately, it has been shown that remote sensing data could be used to estimate near-surface air temperature （Ta） and other climatic conditions. This paper makes use of recorded meteorological data and MODIS data on land surface temperature （Ts） to estimate monthly mean air temperatures in the southeastern Tibetan Plateau and its neighboring areas. A total of 72 weather stations and 84 MODIS images for seven years （2001 to 2007） are used for analysis. Regression analysis and spatio-temporal analysis of monthly mean Ts vs. monthly mean Ta are carried out, showing that recorded Ta is closely related to MODIS Ts in the study region. The regression analysis of monthly mean Ts vs. Ta for every month of all stations shows that monthly mean Ts can be rather accurately used to estimate monthly mean Ta （R2 ranging from 0.62 to 0.90 and standard error between 2.25℃ and 3.23℃）. Thirdly, the retrieved monthly mean Ta for the whole study area varies between 1.62℃ （in January, the coldest month） and 17.29℃ （in July, the warmest month）, and for the warm season （May-September）, it is from 13.1℃ to 17.29℃. Finally, the elevation of isotherms is higher in the central mountain ranges than in the outer margins; the 0℃ isotherm occurs at elevation of about 4500±500 m in October, dropping to 3500±500 m in January, and ascending back to 4500±500 m in May next year. This clearly shows that MODIS Ts data combining with observed data could be used to rather accurately estimate air temperature in mountain regions.

关键词： land surface temperature MODIS air temperature estimation spatio-temporal analysis the Heng-duan Mountains Tibetan Plateau

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temporal trends in areas at risk for concomitant tuberculosis in a hyperendemic municipality in the Amazon region of Brazil

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Infectious Diseases of Poverty 2020年第4期9卷 162-162页

作者： Alexandre Tadashi Inomata Bruce Thais Zamboni Berra Felipe Lima dos Santos Yan Mathias Alves Ludmilla Leidianne Limirio Souza Antônio Carlos Vieira Ramos Luiz Henrique Arroyo Juliane de Almeida Crispim Ione Carvalho Pinto Pedro Fredemir Palha Aline Aparecida Monroe Mellina Yamamura Regina Célia Fiorati Ana Carolina Scarpel Moncaio Dulce Maria de Oliveira Gomes Ricardo Alexandre Arcêncio Department of Maternal-Infant and Public Health Nursing University of São Paulo at Ribeirão Preto College of NursingRibeirão PretoSão PauloBrazil Department of Nursing Federal University of São CarlosSão CarlosSão PauloBrazil Department of Neurosciences and Behavioral Sciences Ribeirão Preto Medical School of the University of São PauloRibeirão PretoSão PauloBrazil Department of Nursing Federal University of CatalãoCatalãoGoiásBrazil Mathematics Department University ofÉvoraÉvoraPortugal

Background Although preventable and curable,tuberculosis(TB)still occurs in poor or developing countries,mainly in metropolitan regions of larger cities.The disease is a serious public health problem,and is directly linked to social issues.We analyzed temporal trend variations in areas at risk for concomitant TB,and characterized the clinical and epidemiological profiles of cases in a hyperendemic municipality in the Amazon region of Brazil.Methods This ecological study was performed in the municipality of Manaus,in northern Brazil.The population comprised cases with concomitant pulmonary and extrapulmonary TB,registered on the Notifiable Diseases Information System(SINAN),between January 1,2009 and December 31,2018.For risk cluster detection,spatial and spatiotemporal scanning statistical techniques were used.The Spatial Variation in temporal Trends(SVTT)approach was used to detect and infer clusters for significantly different time trends.Results Between 2009 and 2018,873 concomitant TB cases were registered in Manaus.By using purely spatial scanning statistics,we identified two risk clusters.The relative risk(RR)of the clusters was 2.21(95%confidence interval[CI]:1.57–2.88;P=0.0031)and 2.03(95%CI:1.58–2.58;P=0.0029).Using space-time scanning,we identified a risk cluster with an RR of 3.57(95%CI:2.84–4.41;P=0.014),between 2017 and 2018.For SVTT analyses,three clusters with spatial variations were detected in the significant temporal trends:SVTT 1(P=0.042),SVTT 2(P=0.046)and SVTT 3(P=0.036).Conclusions In Brazil,several TB-determining factors such as race/color,gender,low educational level and low income overlap in needy urban areas and communities,demonstrating that it is unlikely to reach the goals,agreed and launched with the END TB Strategy within the deadlines of international agreements,if there is no reduction in existing inequities determinants and risk of illness in the country.

关键词： Tuberculosis Public health Epidemiology Spatial analysis spatio-temporal analysis

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环渤海地区土地利用的时空变化分析

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地理 2001年第5期 253-260页

作者：朱会义李秀彬何书金张明

根据1985和1995年2期TM影像资料，运用遥感影像机助解译方法、地理信息系统空间分析方法以及数理统计方法，全面分析了环渤海地区3省2市1985～1995年间分类土地利用的数量变化和空间变化特征。揭示了该区各类土地利用数量变化的幅度、... 详细信息

根据1985和1995年2期TM影像资料，运用遥感影像机助解译方法、地理信息系统空间分析方法以及数理统计方法，全面分析了环渤海地区3省2市1985～1995年间分类土地利用的数量变化和空间变化特征。揭示了该区各类土地利用数量变化的幅度、速度和区域差异以及土地利用空间变化的主要类型、分布特征和区域方向。阐明了该区土地利用变化的区域特点，为土地可持续利用提供有效的决策支持。

关键词：环渤海地区土地利用时空变化 the Bohai Rim land use change spatio-temporal analysis

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