检索结果-南通市图书馆

Chromatin accessibility profiling provides insights into larval cuticle color and adult longevity in butterflies

在线全文

学校读者我要写书评

暂无评论

Zoological Research 2021年第5期42卷 614-619页

作者： Wen-Ting Wan Zhi-Wei Dong Yan-Dong Ren Jie Yang xiang-yu pan Jin-Wu He Zhou Chang Wei Liu Gui-Chun Liu Ruo-Ping Zhao Ping Hu Chu-Yang Mao Jun Li Wen Wang Xue-Yan Li School of Ecology and Environment Northwestern Polytechnical UniversityXi’anShaanxi 710072China State Key Laboratory of Genetic Resources and Evolution Kunming Institute of ZoologyChinese Academy of SciencesKunmingYunnan 650223China Key Laboratory of Animal Genetics Breeding and Reproduction of Shanxi ProvinceCollege of Animal Science and TechnologyNorthwest A&F UniversityYanglingShaanxi 712100China Kunming College of Life Science University of Chinese Academy of SciencesKunmingYunnan 650204China Center for Excellence in Animal Evolution and Genetics KunmingYunnan 650223China

Butterflies are diverse in virtually all aspects of their ontogeny,including morphology,life history,and behavior.However,the developmental regulatory mechanisms underlying the important phenotypic traits of butterflies at different developmental stages remain unknown.Here,we investigated the developmental regulatory profiles of butterflies based on transposase accessible chromatin sequencing(ATAC-seq)at three developmental stages in two representative species(Papilio xuthus and Kallima inachus).

关键词： larval longe behavior

Genetically modified non-human primate models for research on neurodegenerative diseases

在线全文

学校读者我要写书评

暂无评论

Zoological Research 2024年第2期45卷 263-274页

作者： Ming-Tian pan Han Zhang Xiao-Jiang Li xiang-yu Guo Guangdong Key Laboratory of Non-human Primate Research Guangdong-Hongkong-Macao Institute of CNS RegenerationJinan UniversityGuangzhouGuangdong 510632China

Neurodegenerative diseases(NDs)are a group of debilitating neurological disorders that primarily affect elderly populations and include Alzheimer's disease(AD),Parkinson's disease(PD),Huntington's disease(HD),and amyotrophic lateral sclerosis(ALS).Currently,there are no therapies available that can delay,stop,or reverse the pathological progression of NDs in clinical settings.As the population ages,NDs are imposing a huge burden on public health systems and affected families.Animal models are important tools for preclinical investigations to understand disease pathogenesis and test potential treatments.While numerous rodent models of NDs have been developed to enhance our understanding of disease mechanisms,the limited success of translating findings from animal models to clinical practice suggests that there is still a need to bridge this translation gap.Old World nonhuman primates(NHPs),such as rhesus,cynomolgus,and vervet monkeys,are phylogenetically,physiologically,biochemically,and behaviorally most relevant to humans.This is particularly evident in the similarity of the structure and function of their central nervous systems,rendering such species uniquely valuable for neuroscience research.Recently,the development of several genetically modified NHP models of NDs has successfully recapitulated key pathologies and revealed novel mechanisms.This review focuses on the efficacy of NHPs in modeling NDs and the novel pathological insights gained,as well as the challenges associated with the generation of such models and the complexities involved in their subsequent analysis.

关键词： Neurodegeneration Non-human primate Macaque monkey Animal model Gene modification

Semi-Varying Coefficient panel Data Model with Technical Indicators Predicts Stock Returns in Financial Market

同方期刊数据库博看期刊评论

在线全文

学校读者我要写书评

暂无评论

Journal of Systems Science & Complexity 2024年第4期37卷 1638-1652页

作者： HU Xuemei pan Ying LI xiang School of Mathematics and Statistics Chongqing Technology and Business University Chongqing Key Laboratory of Social Economy and Applied Statistics Research Center for Economy of Upper Reaches of the Yangtse River Chongqing Technology and Business University

Accurately predicting stock returns is a conundrum in financial market. Solving this conundrum can bring huge economic benefits for investors and also attract the attention of all circles of people. In this paper the authors combine semi-varying coefficient model with technical analysis and statistical learning, and propose semi-varying coefficient panel data model with individual effects to explore the dynamic relations between the stock returns from five companies: CVX, DFS, EMN, LYB,and MET and five technical indicators: CCI, EMV, MOM, ln ATR, ln RSI as well as closing price(ln CP), combine semi-parametric fixed effects estimator, semi-parametric random effects estimator with the testing procedure to distinguish fixed effects(FE) from random effects(RE), and finally apply the estimated dynamic relations and the testing set to predict stock returns in December 2020 for the five companies. The proposed method can accommodate the varying relationship and the interactive relationship between the different technical indicators, and further enhance the prediction accuracy to stock returns.

关键词： Fixed effects random effects semi-varying coefficient panel data model stock returns technical indicators

Morphological Classification of Infrared Galaxies Based on WISE

在线全文

同方期刊数据库

学校读者我要写书评

暂无评论

Research in Astronomy and Astrophysics 2024年第4期24卷 222-236页

作者： Zhi-Ren pan Bo Qiu Cui-xiang Liu A-Li Luo Xia Jiang Xiao-yu Guo School of Electronic and Information Engineering Hebei University of TechnologyTianjin 300401China Key Laboratory of Optical Astronomy National Astronomical ObservatoriesChinese Academy of SciencesBeijing 100101China

This study introduces a novel convolutional neural network,the WISE Galaxy Classification Network(WGC),for classifying spiral and elliptical galaxies using Wide-field Infrared Survey Explorer(WISE)images.WGC attains an accuracy of 89.03%,surpassing the combined use of K-means or SVM with the Color-Color method in more accurately identifying galaxy morphologies.The enhanced variant,WGC_mag,integrates magnitude parameters with image features,further boosting the accuracy to 89.89%.The research also delves into the criteria for galaxy classification,discovering that WGC primarily categorizes dust-rich images as elliptical galaxies,corresponding to their lower star formation rates,and classifies less dusty images as spiral galaxies.The paper explores the consistency and complementarity of WISE infrared images with SDSS optical images in galaxy morphology classification.The SDSS Galaxy Classification Network(SGC),trained on SDSS images,achieved an accuracy of 94.64%.The accuracy reached 99.30% when predictions from SGC and WGC were consistent.Leveraging the complementarity of features in WISE and SDSS images,a novel variant of a classifier,namely the Multi-band Galaxy Morphology Integrated Classifier,has been developed.This classifier elevates the overall prediction accuracy to 95.39%.Lastly,the versatility of WGC was validated in other data sets.On the HyperLEDA data set,the distinction between elliptical galaxies and Sc,Scd and Sd spiral galaxies was most pronounced,achieving an accuracy of 90%,surpassing the classification results of the Galaxy Zoo 2 labeled WISE data set.This research not only demonstrates the effectiveness of WISE images in galaxy morphology classification but also represents an attempt to integrate multi-band astronomical data to enhance understanding of galaxy structures and evolution.

关键词： methods:data analysis infrared:galaxies galaxies:spiral galaxies:elliptical and lenticular cD

A Novel Fall Detection Framework Using Skip-DSCGAN Based on Inertial Sensor Data

在线全文

学校读者我要写书评

暂无评论

Computers, Materials & Continua 2024年第1期78卷 493-514页

作者： Kun Fang Julong pan Lingyi Li Ruihan xiang College of Information Engineering China Jiliang UniversityHangzhou310018China

With the widespread use of Internet of Things(IoT)technology in daily life and the considerable safety risks of falls for elderly individuals,research on IoT-based fall detection systems has gainedmuch attention.This paper proposes an IoT-based spatiotemporal data processing framework based on a depthwise separable convolution generative adversarial network using skip-connection(Skip-DSCGAN)for fall detection.The method uses spatiotemporal data from accelerometers and gyroscopes in inertial sensors as input data.A semisupervised learning approach is adopted to train the model using only activities of daily living(ADL)data,which can avoid data imbalance problems.Furthermore,a quantile-based approach is employed to determine the fall threshold,which makes the fall detection frameworkmore robust.This proposed fall detection framework is evaluated against four other generative adversarial network(GAN)models with superior anomaly detection performance using two fall public datasets(SisFall&MobiAct).The test results show that the proposed method achieves better results,reaching 96.93% and 92.75% accuracy on the above two test datasets,respectively.At the same time,the proposed method also achieves satisfactory results in terms ofmodel size and inference delay time,making it suitable for deployment on wearable devices with limited resources.In addition,this paper also compares GAN-based semisupervised learning methods with supervised learning methods commonly used in fall detection.It clarifies the advantages of GAN-based semisupervised learning methods in fall detection.

关键词： Fall detection skip-connection depthwise separable convolution generative adversarial networks inertial sensor

DNA damage response-related immune activation signature predicts the response to immune checkpoint inhibitors: from gastrointestinal cancer analysis to pan-cancer validation

维普期刊数据库评论

在线全文

维普期刊数据库

学校读者我要写书评

暂无评论

Cancer Biology & Medicine 2024年第3期21卷 252-266页

作者： Junya Yan Shibo Wang Jing Zhang Qiangqiang yuan Xianchun Gao Nannan Zhang Yan pan Haohao Zhang Kun Liu Jun yu Linbin Lu Hui Liu Xiaoliang Gao Sheng Zhao Wenyao Zhang Abudurousuli Reyila yu Qi Qiujin Zhang Shundong Cang yuanyuan Lu Yanglin pan Yan Kong Yongzhan Nie State Key Laboratory of Holistic Integrative Management of Gastrointestinal Cancers and National Clinical Research Center for Digestive Diseases Xijing Hospital of Air Force Military Medical UniversityXi'an 710032China Department of Oncology Henan Provincial People's HospitalZhengzhou University People's HospitalZhengzhou 450o03China Faculty of Life Science Northwest UniversityXi'an 710069China Unit 73211 of the People's Liberation Army Nanjing 211800China Key Laboratory of Resource Biology and Biotechnology in Western China(Ministry of Education) School of MedicineNorthwest UniversityXi'an 710069China Shaanxi University of Chinese Medicine Second Clinical Medicine FacultyXi'an 712046China Key Laboratory of Carcinogenesis and Translational Research(Ministry of Education) Department of Renal Cancer and MelanomaPeking University Cancer Hospital and InstituteBeijing 100142China

Objective: DNA damage response(DDR) deficiency has emerged as a prominent determinant of tumor immunogenicity. This study aimed to construct a DDR-related immune activation(DRIA) signature and evaluate the predictive accuracy of the DRIA signature for response to immune checkpoint inhibitor(ICI) therapy in gastrointestinal(GI) cancer.Methods: A DRIA signature was established based on two previously reported DNA damage immune response assays. Clinical and gene expression data from two published GI cancer cohorts were used to assess and validate the association between the DRIA score and response to ICI therapy. The predictive accuracy of the DRIA score was validated based on one ICI-treated melanoma and three pan-cancer published cohorts.Results: The DRIA signature includes three genes(CXCL10, IDO1, and IFI44L). In the discovery cancer cohort, DRIA-high patients with gastric cancer achieved a higher response rate to ICI therapy than DRIA-low patients(81.8% vs. 8.8%;P pancreatic adenocarcinoma who received dual PD-1 and CTLA-4 blockade with radiation therapy. Furthermore, the predictive performance of the DRIA score was shown to be robust through an extended validation in melanoma, urothelial cancer, and pan-cancer.Conclusions: The DRIA signature has superior and robust predictive accuracy for the efficacy of ICI therapy in GI cancer and pancancer, indicating that the DRIA signature may serve as a powerful biomarker for guiding ICI therapy decisions.

关键词： DNA damage response-related immune activation immune checkpoint inhibitors biomarker gastrointestinal cancer pan-cancer

Des-Arg(9)bradykinin as a causal metabolite for autism spectrum disorder

在线全文

学校读者我要写书评

暂无评论

World Journal of Psychiatry 2024年第1期14卷 88-101页

作者： Zhong-yu Huang Zi-pan Lyu Hong-Gui Li Hua-Zhi You xiang-Na Yang Cai-Hui Cha Center for Medical Research on Innovation and Translation Institute of Clinical MedicineGuangzhou First People’s HospitalSchool of MedicineSouth China University of TechnologyGuangzhou 510000Guangdong ProvinceChina School of Biological Sciences Nanyang Technological UniversityNanyang Ave 639798Singapore Department of Pediatrics First Affiliated Hospital of Guangzhou University of Chinese MedicineGuangzhou 510405Guangdong ProvinceChina Department of Nutrition First Affiliated Hospital of Guangzhou University of Chinese MedicineGuangzhou 510405Guangdong ProvinceChina Department of Pediatric Traditional Chinese Medicine Clinic Guangzhou Women and Children's Medical CenterGuangzhou 510632Guangdong ProvinceChina Department of Psychology Guangzhou Women and Children's Medical CenterGuangzhou 510632Guangdong ProvinceChina

BACKGROUND Early diagnosis and therapeutic interventions can greatly enhance the developmental trajectory of children with autism spectrum disorder(ASD).However,the etiology of ASD is not completely understood.The presence of confounding factors from environment and genetics has increased the difficulty of the identification of diagnostic biomarkers for ASD.AIM To estimate and interpret the causal relationship between ASD and metabolite profile,taking into consideration both genetic and environmental influences.METHODS A two-sample Mendelian randomization(MR)analysis was conducted using summarized data from large-scale genome-wide association studies(GWAS)including a metabolite GWAS dataset covering 453 metabolites from 7824 European and an ASD GWAS dataset comprising 18381 ASD cases and 27969 healthy controls.Metabolites in plasma were set as exposures with ASD as the main outcome.The causal relationships were estimated using the inverse variant weight(IVW)algorithm.We also performed leave-one-out sensitivity tests to validate the robustness of the results.Based on the drafted metabolites,enrichment analysis was conducted to interpret the association via constructing a protein-protein interaction network with multi-scale evidence from databases including Infinome,SwissTargetPrediction,STRING,and Metascape.RESULTS Des-Arg(9)-bradykinin was identified as a causal metabolite that increases the risk of ASD(β=0.262,SE=0.064,P_(IVW)=4.64×10^(-5)).The association was robust,with no significant heterogeneity among instrument variables(P_(MR Egger)=0.663,P_(IVW)=0.906)and no evidence of pleiotropy(P=0.949).Neuroinflammation and the response to stimulus were suggested as potential biological processes mediating the association between Des-Arg(9)bradykinin and ASD.CONCLUSION Through the application of MR,this study provides practical insights into the potential causal association between plasma metabolites and ASD.These findings offer perspectives for the discovery of diagnostic or predictive biomarkers to support clinical

关键词： Des-Arg(9)bradykinin Autism spectrum disorder Mendelian randomization Metabolite Enrichment analysis

Development and validation of a nomogram to predict allograft survival after pediatric liver transplantation

维普期刊数据库评论

在线全文

维普期刊数据库

学校读者我要写书评

暂无评论

World Journal of Pediatrics 2024年第3期20卷 239-249页

作者： Guang-xiang Gu Shu-Ting pan Yi-Chen Fan Chen Chen Qiang Xia Department of Liver Surgery Renji HospitalShanghai Jiaotong University School of MedicineNo.160 Pujian RoadPudong New DistrictShanghai 200128China Department of Liver Transplantation Sun Yet-Sen Memorial HospitalSun Yat-Sen UniversityNo.107 Yanjiang West RoadGuangzhou 510080China Clinical Center for Investigation Renji HospitalShanghai Jiaotong University School of MedicineShanghaiChina Department of Anesthesiology Renji HospitalShanghai Jiaotong University School of MedicineShanghaiChina

Background Liver transplantation is the main treatment for cholestatic liver disease and some metabolic liver diseases in children.However,no accurate prediction model to determine the survival probability of grafts prior to surgery exists.This study aimed to develop an effective prognostic model for allograft survival after pediatric liver transplantation.Methods This retrospective cohort study included 2032 patients who underwent pediatric liver transplantation between January 1,2006,and January 1,2020.A nomogram was developed using Cox regression and validated based on bootstrap sampling.Predictive and discriminatory accuracies were determined using the concordance index and visualized using calibration curves;net benefits were calculated for model comparison.An online Shiny application was developed for easy access to the model.Results Multivariable analysis demonstrated that preoperative diagnosis,recipient age,body weight,graft type,preoperative total bilirubin,interleukin-1β,portal venous blood flow direction,spleen thickness,and the presence of heart disease and cholangitis were independent factors for survival,all of which were selected in the nomogram.Calibration of the nomogram indicated that the 1-,3-,and 5-year predicted survival rates agreed with the actual survival rate.The concordance indices for graft survival at 1,3,and 5 years were 0.776,0.757,and 0.753,respectively,which were significantly higher than those of the Pediatric End-Stage Liver Disease and Child-Pugh scoring systems.The allograft dysfunction risk of a recipient could be easily predicted using the following URL:https://aspelt.***.io/ASPELT/l Conclusion The allograft survival after pediatric liver transplantation(ASPELT)score model can effectively predict the graft survival rate after liver transplantation in children,providing a simple and convenient evaluation method for clinicians and patients.

关键词： Allograft survival Nomogram Pediatric liver transplantation

Real-time,single-particle chemical composition,volatility and mixing state measurements of urban aerosol particles in southwest China

维普期刊数据库评论

在线全文

维普期刊数据库

学校读者我要写书评

暂无评论

Journal of Environmental Sciences 2024年第2期136卷 361-371页

作者： Luyao Chen Junke Zhang Jiaqi Li Xiaojuan Huang yuzheng xiang Jing Chen Tingru pan Wei Zhang Faculty of Geosciences and Environmental Engineering Southwest Jiaotong UniversityChengdu 611756China School of Atmospheric Sciences Chengdu University of Information TechnologyChengdu 610225China Sichuan Environmental Monitoring Center Chengdu 610074China

To investigate the volatility of atmospheric particulates and the evolution of other particulate properties(chemical composition,particle size distribution and mixing state)with temperature,a thermodenuder coupled with a single particle aerosol mass spectrometer was used to conduct continuous observations of atmospheric fine particles in Chengdu,southwest China.Because of their complex sources and secondary reaction processes,the average mass spectra of single particles contained a variety of chemical components(including organic,inorganic and metal species).When the temperature rose from room temperature to280℃,the relative areas of volatile and semi-volatile components decreased,while the relative areas of less or non-volatile components increased.Most(>80%)nitrate and sulfate existed in the form of NH_(4)NO_(3)and(NH_(4))_(2)SO_(4),and their volatilization temperatures were50–100℃and 150–280℃,respectively.The contribution of biomass burning(BB)and vehicle emission(VE)particles increased significantly at 280℃,which emphasized the important role of regional biomass burning and local motor vehicle emissions to the core of particles.With the increase in temperature,the particle size of the particles coated with volatile or semi-volatile components was reduced,and their mixing with secondary inorganic components was significantly weakened.The formation of K-nitrate(KNO_(3))and K-sulfate(KSO_(4))particles was dominated by liquid-phase processes and photochemical reactions,respectively.Reducing KNO_(3)and BB particles is the key to improving visibility.These new results are helpful towards better understanding the initial sources,pollution formation mechanisms and climatic effects of fine particulate matter in this megacity in southwest China.

关键词： Atmospheric fine particles TD-SPAMS Chemical composition Volatility Mixing state