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Relationship between left-behind status and cognitive function in older Chinese adults: a prospective 3-year cohort study

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General Psychiatry 2023年第3期36卷 148-157页

作者： hong-Guang Zhang Fang Fan bao-Liang Zhong helen Fung-Kum Chiu Department of Psychiatry Affiliated Wuhan Mental Health CenterTongji Medical College of Huazhong Universityof Science&TechnologyWuhanHubeiChina Department of Psychiatry Wuhan Mental Health CenterWuhanHubeiChina Department of Clinical Psychology Wuhan Hospital for PsychotherapyWuhanHubeiChina Department of Psychiatry The Chinese University of Hong KongHong KongChina

Background Due to the inaccuracy of the traditional geographical distance-based definition of left-behind status,data on the negative effect of left-behind status on cognitive function among older adults are *** This study examined the cross-sectional and longitudinal associations of left-behind status with cognitive function in older Chinese *** left-behind status definition was based on the frequency of face-to-face parent-child *** Data from a nationally representative sample of 8682 older adults(60+years)in 2015(5658 left behind and 3024 non-left behind),of which 6933 completed the follow-up in 2018,were obtained from the China health and Retirement Longitudinal ***-behind older adults werebroadlydefined as those aged 60+years who had living adult children and saw their children less than once per *** cognitive function was assessed with a composite cognitive test with higher total scores indicating better cognitive *** Left-behind older adults had significantly lower cognitive test scores than non-left-behind older adults in both 2015(11.1(6.0)vs 13.2(5.9),t=15.863,phic factors,lifestyle factors,chronic medical conditions and the baseline cognitive test score(in the longitudinal analysis only),on average,the cognitive test score of left-behind older adults was 0.628 lower than their non-left-behind counterparts in 2015(t=5.689,phis difference in cognitive test scores attenuated to 0.322 but remained significant in 2018(t=2.733,p=0.006).Conclusions Left-behind older Chinese adults have a higher risk of poor cognitive function and cognitive decline than their non-left-behind *** efforts targeting left-behind older adults,such as encouraging adult children to visit their parents more regularly,are warranted to maintain or delay the progression of cognitive decline.

关键词： function cognitive maintain

基于室内三维模型的超宽带基站布网优化算法研究

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测绘科学 2024年第2期49卷 37-46页

作者：刘巍峰程瑶鲍亚川徐彦田李玉星辽宁工程技术大学测绘与地理科学学院辽宁阜新123000 中国测绘科学研究院北京100036 卫星导航系统与装备技术国家重点实验室石家庄050081 中国电子科技集团公司第五十四研究所石家庄050081

针对室内环境复杂,UWB基站布设效率低和定位精度无法保证的问题,提出了一种基于室内真实三维场景的UWB基站几何网型优化算法,将三维场景划分为3 m×3 m×1 m立体格网,格网点组成基站布设向量空间,定位区域格网点的PDOP值作为目标函数,... 详细信息

针对室内环境复杂,UWB基站布设效率低和定位精度无法保证的问题,提出了一种基于室内真实三维场景的UWB基站几何网型优化算法,将三维场景划分为3 m×3 m×1 m立体格网,格网点组成基站布设向量空间,定位区域格网点的PDOP值作为目标函数,并通过海伦公式剔除基站的病态网型,实现UWB基站布设网形的快速优化。为了验证新方法的有效性,在某实验楼进行实测验证。实验结果表明,新方法相比于经验网形中矩形网形和菱形网形,其平均PDOP值分别提升了5.70%和6.06%,平均定位精度分别提升了46.34%和36.68%。

关键词：超宽带室内三维模型布网优化基站布设位置精度衰减因子

Chi-Chao Chan:passion is very important for the success

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Eye Science 2016年第3期31卷 199-200页

作者： helen Seliman YKxB

Introduction Chi-Chao Chan(Figure 1),M.D.,an American board certified ophthalmologist,is a Scientist Emerita of the National Eye Institute(NEI),National Institutes of health(NIh),*** studied at Zhongshan Medical College(now Sun Yat-sen University Medical School)in China[1961-1967],went to USA in *** USA,*** received both bachelor(BA,1972)and

关键词： NEI Chi-Chao Chan:passion is very important for the success very

海伦·斯诺女士对中国红军将领采访报道的重大时代影响和历史作用

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军事历史研究 2007年第4期21卷 159-164页

作者：鲍世修军事科学院

本文回顾了国际友人海伦.福斯特.斯诺70年前对中国红军将领的采访报道,并对其时代影响和历史作用作了剖析。

关键词：海伦·斯诺红军将领时代影响历史作用

中国与澳大利亚部分护理本科教育课程设置的比较与借鉴

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昆明医学院学报 2011年第7期32卷 142-146页

作者：余华李保刚范萍金婧 helen Edwards 昆明医学院护理学院云南昆明650032 School of Nursing and Midwifery Queensland University of Technology Brisbane QLD Australia 4059

目的对比分析部分中澳高校护理本科课程设置,探索护理本科课程的改革依据.方法采用同类横向比较、定性与定量比较相结合的方法,对课程设置进行比较分析.结果中澳护理本科教育课程设置在培养目标、课程内容结构和实践教学等方面存在差异... 详细信息

目的对比分析部分中澳高校护理本科课程设置,探索护理本科课程的改革依据.方法采用同类横向比较、定性与定量比较相结合的方法,对课程设置进行比较分析.结果中澳护理本科教育课程设置在培养目标、课程内容结构和实践教学等方面存在差异.结论借鉴澳大利亚高校,我国护理本科教育课程设置应逐步走出依附临床医学专业的教育模式,突出护理专业特色;应更强调学生人文素质的全面培养;应采取理论课与实践课同步进行学习课程教学模式,促进教学与临床实践紧密结合.

关键词：中国澳大利亚护理本科教育改革比较研究课程设置

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寻找解决方案--中国的下一代肿瘤免疫研究

药学进展 2020年第1期44卷 66-80页

作者： DOWDEN helen MUNRO Jamie 鲍书馨胡大龙 LIChTENFIELD Michele 郑晓南张娟王刚科睿唯安中国药科大学

肿瘤免疫(I-O)目前是投资高度密集的领域,特别是随着第一代靶向程序性死亡蛋白(PD-1/PD-L1)的免疫检查点抑制剂的成功开发,该领域进入了跳跃式发展。基于此,为进一步提高药物的药效和临床疗效,研发者开始寻找其他免疫治疗靶点,即"下一代... 详细信息

肿瘤免疫(I-O)目前是投资高度密集的领域,特别是随着第一代靶向程序性死亡蛋白(PD-1/PD-L1)的免疫检查点抑制剂的成功开发,该领域进入了跳跃式发展。基于此,为进一步提高药物的药效和临床疗效,研发者开始寻找其他免疫治疗靶点,即"下一代"I-O药物。从商业上来看,I-O药物的开发一直由大型跨国制药公司主导。中国虽然拥有全球第二大制药市场,但是在开发这类创新药物方面已滞后于西方国家。意识到这一点,目前正在努力改善现状。截至完稿,中国已有7个抗PD-1/PD-L1抗体产品获批上市,其中2个为全球市场引领者--默克公司的可瑞达■(Keytruda■,通用名为帕博利珠单抗)和百时美施贵宝的欧狄沃(Opdivo■,通用名为纳武利尤单抗),其中4个均由中国的公司开发。不止于此,中国的投资项目正在积极布局下一代免疫治疗靶点,包括采用诸如CAR-T等顶尖技术。在本报告中,我们分析了一些具有前瞻性的下一代I-O靶点,特别关注全球视野下中国的研发情况,同时也预测了随着时间的推移中国的I-O市场发展趋势,以及其对全球市场的潜在影响。

关键词：肿瘤免疫 I-O药物肿瘤免疫治疗靶点

A multiple-tissue-specific magnetic resonance imaging model for diagnosing Parkinson’s disease: a brain radiomics study

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Neural Regeneration Research 2022年第12期17卷 2743-2749页

作者： xiao-Jun Guan Tao Guo Cheng Zhou Ting Gao Jing-Jing Wu Victor han Steven Cao hong-Jiang Wei Yu-Yao Zhang Min xuan Quan-Quan Gu Pei-Yu huang Chun-Lei Liu Jia-Li Pu bao-Rong Zhang Feng Cui xiao-Jun xu Min-Ming Zhang Department of Radiology the Second Affiliated HospitalZhejiang University School of MedicineHangzhouZhejiang ProvinceChina Department of Neurology the Second Affiliated HospitalZhejiang University School of MedicineHangzhouZhejiang ProvinceChina Department of Electrical Engineering and Computer Sciences University of CaliforniaBerkeleyCAUSA Institute for Medical Imaging Technology School of Biomedical EngineeringShanghai Jiao Tong UniversityShanghaiChina School of Information Science and Technology ShanghaiTech UniversityShanghaiChina helen Wills Neuroscience Institute University of CaliforniaBerkeleyCAUSA Department of Radiology Hangzhou Hospital of Traditional Chinese MedicineHangzhouZhejiang ProvinceChina

Brain radiomics can reflect the characteristics of brain ***,the value of T1-weighted images,quantitative susceptibility mapping,and R2*mapping in the diagnosis of Parkinson’s disease(PD)was underestimated in previous *** this prospective study to establish a model for PD diagnosis based on brain imaging information,we collected high-resolution T1-weighted images,R2*mapping,and quantitative susceptibility imaging data from 171 patients with PD and 179 healthy controls recruited from August 2014 to August *** to the inclusion time,123 PD patients and 121 healthy controls were assigned to train the diagnostic model,while the remaining 106 subjects were assigned to the external validation *** extracted 1408 radiomics features,and then used data-driven feature selection to identify informative features that were significant for discriminating patients with PD from normal controls on the training *** informative features so identified were then used to construct a diagnostic model for *** constructed model contained 36 informative radiomics features,mainly representing abnormal subcortical iron distribution(especially in the substantia nigra),structural disorganization(e.g.,in the inferior temporal,paracentral,precuneus,insula,and precentral gyri),and texture misalignment in the subcortical nuclei(e.g.,caudate,globus pallidus,and thalamus).The predictive accuracy of the established model was 81.1±8.0%in the training *** the external validation dataset,the established model showed predictive accuracy of 78.5±2.1%.In the tests of identifying early and drug-naïve PD patients from healthy controls,the accuracies of the model constructed on the same 36 informative features were 80.3±7.1%and 79.1±6.5%,respectively,while the accuracies were 80.4±6.3%and 82.9±5.8%for diagnosing middle-to-late PD and those receiving drug management,*** accuracies for predicting tremor-dominant and non-tremor-dominant PD w

关键词： diagnosis imaging biomarker iron magnetic resonance imaging neuroimaging Parkinson’s disease quantitative susceptibility mapping R2*mapping radiomics T1-weighted imaging

Fungal diversity notes 1036-1150:taxonomic and phylogenetic contributions on genera and species of fungal taxa

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Fungal Diversity 2019年第3期96卷 1-242页

作者： Kevin D.hyde Danushka S.Tennakoon Rajesh Jeewon DJayarama Bhat Sajeewa S.N.Maharachchikumbura Walter Rossi Marco Leonardi hyang Burm Lee hye Yeon Mun Jos houbraken Thuong T.T.Nguyen Sun Jeong Jeon Jens Christian Frisvad Dhanushka N.Wanasinghe Robert Lucking Andre Aptroot Marcela E.S.Caceres Samantha C.Karunarathna Sinang hongsanan Rungtiwa Phookamsak Nimali Ide Silva Kasun M.Thambugala Ruvishika S.Jayawardena Indunil C.Senanayake Saranyaphat Boonmee Jie Chen Zong-Long Luo Chayanard Phukhamsakda Olinto L.Pereira Vanessa P.Abreu Andre Wilson Campos Rosado Buyck Bart Emile Randrianjohany Vale rie hofstetter Tatiana B.Gibertoni Adriene Mayrada Silva Soares helio Longoni Plautz Jr helen Maria Pontes Sotao William Kalhy Silva xavier Jadson Diogo Pereira Bezerra Thays Gabrielle Linsde Oliveira Cristina Mariade Souza-Motta Oliane Maria Correia Magalhaes Digvijayini Bundhun Dulanjalee harishchandra Ishara S.Manawasinghe Wei Dong Sheng-Nan Zhang Dan-Feng bao Milan C.Samarakoon Dhandevi Pem Anuruddha Karunarathna Chuan-Gen Lin Jing Yang Rekhani h.Perera Vinit Kumar Shi-Ke huang Monika C.Dayarathne Anusha h.Ekanayaka Subashini C.Jayasiri Yuanpin xiao Sirinapa Konta Tuula Niskanen Kare Liimatainen Yu-Cheng Dai xiao-hong Ji xue-Mei Tian Armin Mesic Sanjay K.Singh Kunthida Phutthacharoen Lei Cai Touny Sorvongxay Vinodhini Thiyagaraja Chada Norphanphoun Napalai Chaiwan Yong-Zhong Lu hong-Bo Jiang Jin-Feng Zhang Pranami D.Abeywickrama Janith V.S.Aluthmuhandiram Rashika S.Brahmanage Ming Zeng Thilini Chethana Deping Wei Martina Reblova Jacques Fournier Jana Nekvindova Renan do Nascimento Barbosa Jose Ewerton Felintodos Santos Neiva Tintide Oliveira Guo-Jie Li Damien Ertz Qiu-Ju Shang Alan J.L.Phillips Chang-hsin Kuo Erio Camporesi Timur S.Bulgakov Saisamorn Lumyong E.B.Gareth Jones Putarak Chomnunti Eleni Gentekaki Frank Bungartz xiang-Yu Zeng Sally Fryar Zdenko Tkalcec Junmin Liang Guangshuo Li Ting-Chi Wen Paras Nath Singh Yusufjon Gafforov Itthayakorn Promputtha Erandi Yasanthika Ishani D.Goonasekara Rui-Lin Zhao Qi Zhao Paul M Key Laboratory for Plant Diversity and Biogeography of East Asia Kunming Institute of BotanyChinese Academy of ScienceKunming 650201YunnanPeople’s Republic of China School of Science Mae Fah Luang UniversityChiang Rai 57100Thailand Center of Excellence in Fungal Research Mae Fah Luang UniversityChiang Rai 57100Thailand East and Central Asia Regional Office World Agroforestry Centre(ICRAF)Kunming 650201YunnanPeople’s Republic of China Department of Biology Faculty of ScienceChiang Mai UniversityChiang Mai 50200Thailand Mushroom Research Foundation 128 M.3 Ban Pa Deng T.Pa PaeA.Mae TaengChiang Mai 50150Thailand Department of Plant Medicine National Chiayi University300 Syuefu RoadChiayi City 60004TaiwanPeople’s Republic of China Department of health Sciences Faculty of ScienceUniversity of MauritiusReduitMauritius Formerly Department of Botany Goa UniversityGoaIndia No.128/1-J Azad Housing SocietyCurcaGoa Velha 403108India Department of Crop Sciences College of Agricultural and Marine SciencesSultan Qaboos UniversityPO Box 8123 Al KhoudOman Sect.Environmental Sciences Dept.MeSVAUniversity of L’Aquila67100 CoppitoAQItaly Division of Food Technology Biotechnology&AgrochemistryCollege of Agriculture&Life SciencesChonnam National UniversityGwangju 61186Korea Fungal Resources Research Division NNIBRSangju-si 37242Korea Westerdijk Fungal Biodiversity Institute Uppsalalaan 83584 CT UtrechtThe Netherlands Department of Biotechnology and Biomedicine DTUBioengineeringTechnical University of Denmark2800 Kongens LyngbyDenmark Botanischer Garten und Botanisches Museum Berlin Freie Universitat BerlinKonigin-Luise-StraßBe 6-814195 BerlinGermany Laboratorio de Botanica/Liquenologia Instituto de BiocienciasUniversidade Federal de Mato Grosso do SulAvenida Costa e Silva s/nBairro UniversitarioCampo GrandeMatto Grosso do Sul CEP 79070-900Brazil Departamento de Biociencias Universidade Federal de SergipeItabaianaSergipe CEP:49500-000Brazil Shenzhen Key Laboratory of Microbial

This article is the tenth series of the Fungal Diversity Notes,where 114 taxa distributed in three phyla,ten classes,30 orders and 53 families are described and *** described in the present study include one new family(*** in Dothideomycetes),five new genera(Caatingomyces,Cryptoschizotrema,Neoacladium,Paramassaria and Trochilispora)and 71 new species,(*** thailandica,Amniculicola aquatica,***,Angustimassarina sylvatica,Blackwellomyces lateris,Boubovia gelatinosa,Buellia viridula,Caatingomyces brasiliensis,Calophoma humuli,Camarosporidiella mori,Canalisporium dehongense,Cantharellus brunneopallidus,***,Castanediella meliponae,Coprinopsis psammophila,Cordyceps succavus,Cortinarius minusculus,***,Diaporthe italiana,***,Diatrypella delonicis,Dictyocheirospora aquadulcis,***,Digitodesmium chiangmaiense,Distoseptispora dehongensis,***,Dothiorella styphnolobii,Ellisembia aurea,Falciformispora aquatic,Fomitiporia carpinea,***,Grammothele aurantiaca,***,hermatomyces bauhiniae,Jahnula queenslandica,Kamalomyces mangrovei,Lecidella yunnanensis,Micarea squamulosa,Muriphaeosphaeria angustifoliae,Neoacladium indicum,Neodidymelliopsis sambuci,Neosetophoma miscanthi,***,Nodulosphaeria aquilegiae,***,Paramassaria samaneae,Penicillium circulare,***,***-pumilae,***,***,Phaeoisaria siamensis,Phaeopoacea asparagicola,Phaeosphaeria penniseti,Plectocarpon galapagoense,Porina sorediata,Pseudoberkleasmium chiangmaiense,Pyrenochaetopsis sinensis,Rhizophydium koreanum,Russula prasina,Sporoschisma chiangraiense,Stigmatomyces chamaemyiae,***,***,***,***,Thysanorea uniseptata,Torula breviconidiophora,***,Trochilispora schefflerae and Vaginatispora palmae).Further,twelve new combinations(*** cryptotrema,Prolixandromyces australi,***,***,***,P.

关键词： 71 new taxa Ascomycota Basidiomycota Dothideomycetes Eurotiomycetes Lecanoromycetes Leotiomycetes Pezizomycetes Phylogeny Taxonomy