检索结果-南通市图书馆

NCAD v1.0: a database for non-coding variant annotation and interpretation

维普期刊数据库

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 Genetics and Genomics 2024年第2期51卷 230-242页

作者： Xiaoshu Feng Sihan liu ke Li Fengxiao Bu Huijun Yuan Institute of Rare Diseases West China HospitalSichuan UniversityChengduSichuan 610044China

The application of whole genome sequencing is expanding in clinical diagnostics across various genetic disorders, and the significance of non-coding variants in penetrant diseases is increasingly being demonstrated. Therefore, it is urgent to improve the diagnostic yield by exploring the pathogenic mechanisms of variants in non-coding regions. However, the interpretation of non-coding variants remains a significant challenge, due to the complex functional regulatory mechanisms of non-coding regions and the current limitations of available databases and tools. Hence, we develop the non-coding variant annotation database (NCAD, http://***/), encompassing comprehensive insights into 665,679,194 variants, regulatory elements, and element interaction details. Integrating data from 96 sources, spanning both GRCh37 and GRCh38 versions, NCAD v1.0 provides vital information to support the genetic diagnosis of non-coding variants, including allele frequencies of 12 diverse populations, with a particular focus on the population frequency information for 230,235,698 variants in 20,964 Chinese individuals. Moreover, it offers prediction scores for variant functionality, five categories of regulatory elements, and four types of non-coding RNAs. With its rich data and comprehensive coverage, NCAD serves as a valuable platform, empowering researchers and clinicians with profound insights into non-coding regulatory mechanisms while facilitating the interpretation of non-coding variants.

关键词： Non-coding variants Annotation Variant interpretation Database

Multi-Perspective Data Fusion Framework Based on Hierarchical BERT: Provide Visual Predictions of Business Processes

在线全文

维普期刊数据库

学校读者我要写书评

暂无评论

Computers, Materials & Continua 2024年第1期78卷 1227-1252页

作者： Yongwang Yuan Xiangwei liu ke Lu School of Mathematics and Big Data Anhui University of Science and TechnologyHuainan232001China School of Economics and Management Anhui University of Science and TechnologyHuainan232001China The key Laboratory of Embedded System and Service Computing Ministry of Education Tongji UniversityShanghai201804China

Predictive Business Process Monitoring(PBPM)is a significant research area in Business Process Management(BPM)aimed at accurately forecasting future behavioral events.At present,deep learning methods are widely cited in PBPM research,but no method has been effective in fusing data information into the control flow for multi-perspective process prediction.Therefore,this paper proposes a process prediction method based on the hierarchical BERT and multi-perspective data fusion.Firstly,the first layer BERT network learns the correlations between different category attribute data.Then,the attribute data is integrated into a weighted event-level feature vector and input into the second layer BERT network to learn the impact and priority relationship of each event on future predicted events.Next,the multi-head attention mechanism within the framework is visualized for analysis,helping to understand the decision-making logic of the framework and providing visual predictions.Finally,experimental results show that the predictive accuracy of the framework surpasses the current state-of-the-art research methods and significantly enhances the predictive performance of BPM.

关键词： Business process prediction monitoring deep learning attention mechanism BERT multi-perspective

Hydration lubrication modulated by water structure at TiO2–aqueous interfaces

在线全文

维普期刊数据库

学校读者我要写书评

暂无评论

Friction 2024年第4期12卷 591-605页

作者： Pingsu MA Yuan liu ke HAN Yu TIAN Liran MA State key Laboratory of Tribology in Advanced Equipment Department of Mechanical EngineeringTsinghua UniversityBeijing 100084China

The nature of solid-liquid interfaces is of great significance in lubrication.Remarkable advances have been made in lubrication based on hydration effects.However,a detailed molecular-level understanding is still lacking.Here,we investigated water molecule behaviors at the TiO2-aqueous interfaces by the sum-frequency generation vibrational spectroscopy(SFG-VS)and atomic force microscope(AFM)to elucidate the fundamental role of solid-liquid interfaces in lubrication.Combined contributions of water structures and hydration effects were revealed,where water structures played the dominant role in lubrication for TiO2 surfaces of varying hydrophilicity,while hydration effects dominated with the increasing of ion concentrations.Superior lubrication is observed on the initial TiO2 surfaces with strongly H-bonded water molecules compared to the hydrophilic TiO2 surfaces with more disordered water.The stable ordered water arrangement with strong hydrogen bonds and the shear plane occurring between the ordered water layer and subsequent water layer may play a significant role in achieving lower friction.More adsorbed hydrated molecules with the increasing ionic concentration perturb ordered water but lead to the enhancement of hydration effects,which is the main reason for the improved lubrication for both TiO2.This work provides more insights into the detailed molecular-level understanding of the mechanism of hydration lubrication.

关键词： hydration lubrication interfacial water structures hydration effects titanium dioxide(TiO2)

Open-vessel Synthesis of Poly-N-methoxyethylglycine

在线全文

维普期刊数据库

学校读者我要写书评

暂无评论

Chemical Research in Chinese Universities 2024年第1期40卷 153-158页

作者： liu Guojan MA ke CHEN Qi ZHANG Donghui liu Runhui State key Laboratory of Bioreactor Engineering East China University of Science and TechnologyShanghai200237P.R.China key Laboratory for Ultrafine Materials of Ministry of Education Frontiers Science Center for Materiobiology and Dynamic ChemistryShanghai Frontiers Science Center of Optogenetic Techniques for Cell MetabolismResearch Center for Biomedical Materials of Ministry of EducationSchool of Materials Science and EngineeringEast China University of Science and TechnologyShanghai200237P.R.China School of Biotechnology East China University of Science and TechnologyShanghai200237P.R.China

Polypeptoids are widely used in biological applications owing to their diverse functions and proteolytic stability.One type of polypeptoids,poly-N-methoxyethylglycine(P-Nmeg),has been found to possess remarkable hydrophilicity and notable properties in terms of protein,cell,and bacterial antifouling.However,the currently known synthesis methods of P-Nmeg include solid-phase synthesis,which is time-consuming and difficult to scale up,and N-substituted N-carboxyanhydride(NNCA)ring-opening polymerization,whose monomers were difficult to store.In this study,we used the chemical stable Nmeg N-phenoxycarbonyl(NPC)as the monomer,which was obtained without the use of highly toxic reactants,such as phosgene or phosphorus halide,to synthesize P-Nmeg under open-vessel conditions.By adding BnNH_(2) as an initiator at 80℃,we can obtain controllable short chain length P-Nmeg with narrow dispersity.

关键词： Open-vessel Polypeptoid synthesis Poly-N-methoxyethylglycine Stable monomer Narrow dispersity

Pituitary metastasis from lung adenocarcinoma:A case report

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 Clinical Cases 2024年第15期12卷 2597-2605页

作者： Qing Wang Xiao-Wei liu ke-Yu Chen Department of Critical Care Medicine Chengdu First People’s HospitalChengdu 610000Sichuan ProvinceChina Department of Neurosurgery Chengdu Second People's HospitalChengdu 610017Sichuan ProvinceChina Department of the First Clinical Medical College Lanzhou UniversityLanzhou 730000Gansu ProvinceChina Evidence Based Medicine Center School of Basic Medical SciencesLanzhou UniversityLanzhou 730000Gansu ProvinceChina

BACKGROUND Pituitary gland metastasis is an unusual event,and pituitary metastasis from lung adenocarcinoma is extremely rare and associated with poor prognosis.To date,approximately 15 cases have been reported.CASE SUMMARY Here,we present the case of a 64-year-old woman with pituitary metastasis derived from lung adenocarcinoma,which was difficult to distinguish from other sellar tumors.The patient presented to the neurosurgery clinic with blurred vision and intermittent headache.During hospitalization,brain computed tomography(CT)and magnetic resonance imaging revealed a pituitary macroadenoma.Chest CT revealed irregular nodules in the basal segment of the lower lobe of the left lung,which were likely lung cancer.Positron emission tomography-CT revealed a carbohydrate metabolism tumor in the lungs and sellar region,which was considered malignant.Postoperative pathological examination of the sellar tumor revealed lung adenocarcinoma.CONCLUSION Excision of pituitary metastases combined with radiotherapy and chemotherapy should be a priority treatment for patients with pituitary metastasis.

关键词： Pituitary metastasis Lung adenocarcinoma Prolactin Sellar region tumors Case report

A hybrid attention model based on first-order statistical features for smoke recognition

在线全文

维普期刊数据库

学校读者我要写书评

暂无评论

Science China(Technological Sciences) 2024年第3期67卷 809-822页

作者： GUO Nan liu JiaHui DI keXin GU ke QIAO JunFei Beijing Laboratory of Smart Environmental Protection Beijing Key Laboratory of Computational Intelligence and Intelligent SystemBeijing Artificial Intelligence InstituteBeijing 100124China Faculty of Information Technology Beijing University of TechnologyBeijing 100124China

Smoke and fire recognition are of great importance on foreseeing fire disasters and preventing environmental pollution by monitoring the burning process of objects(e.g., straw, fuels). However, since fire images suffer from problems like the variability of the features, complexity of scenarios, interference from background, changeable weather conditions as well as image quality problems, identifying smoke and fire accurately and promptly from a given image still remains a substantial challenge. Automatically learning the features of smoke images by CNNs has improved the target recognition ability compared to traditional approaches,nonetheless, convolutions and pooling operations in CNNs may cause severe information loss which may lead to misjudgment.To tackle the above problems, this paper proposed a hybrid attention model based on the characteristics of smoke images. This model adopted multiple optimized attention mechanism in several stages to quickly and precisely capture the important features,achieving state-of-the-art performance on smoke and fire recognition in terms of accuracy and speed. Our proposed module mainly consists of two stages: pooling and attention. In the first stage, we conducted several newly proposed first-order pooling methods. Through traversing the data space in a larger scope, features are better reserved, thus constructing a more intact feature space of smoke and fire in an image. In the second stage, feature maps are aggregated together to perform channel and spatial attention. The channel and spatial dependencies allow us to quickly catch the important features presented in an image. By fully exploring the feature space and prominent salient features, characteristics of smoke and fire are better presented so as to obtain better smoke and fire detection results. Experiments have been conducted on public smoke detection dataset and new proposed fine-grained smoke and fire detection database. Experimental results revealed that the proposed method outperformed popular deep CNNs and exis

关键词： hybrid attention first-order pooling smoke and fire detection deep convolutional neural networks

Smart Contract Vulnerability Detection Method Based on Feature Graph and Multiple Attention Mechanisms

维普期刊数据库

同方期刊数据库评论

在线全文

学校读者我要写书评

暂无评论

Computers, Materials & Continua 2024年第5期79卷 3023-3045页

作者： Zhenxiang He Zhenyu Zhao ke Chen Yanlin liu School of Cyber Security Gansu University of Political Science and LawLanzhou730070China

The fast-paced development of blockchain technology is evident.Yet,the security concerns of smart contracts represent a significant challenge to the stability and dependability of the entire blockchain ecosystem.Conventional smart contract vulnerability detection primarily relies on static analysis tools,which are less efficient and accurate.Although deep learning methods have improved detection efficiency,they are unable to fully utilize the static relationships within contracts.Therefore,we have adopted the advantages of the above two methods,combining feature extraction mode of tools with deep learning techniques.Firstly,we have constructed corresponding feature extraction mode for different vulnerabilities,which are used to extract feature graphs from the source code of smart contracts.Then,the node features in feature graphs are fed into a graph convolutional neural network for training,and the edge features are processed using a method that combines attentionmechanismwith gated units.Ultimately,the revised node features and edge features are concatenated through amulti-head attentionmechanism.The result of the splicing is a global representation of the entire feature graph.Our method was tested on three types of data:Timestamp vulnerabilities,reentrancy vulnerabilities,and access control vulnerabilities,where the F1 score of our method reaches 84.63%,92.55%,and 61.36%.The results indicate that our method surpasses most others in detecting smart contract vulnerabilities.

关键词： Blockchain smart contracts deep learning graph neural networks

Recent advances in zwitterionic nanoscale drug delivery systems to overcome biological barriers

在线全文

维普期刊数据库

学校读者我要写书评

暂无评论

Asian Journal of Pharmaceutical Sciences 2024年第1期19卷 49-68页

作者： Xumei Ouyang Yu liu ke Zheng Zhiqing Pang Shaojun Peng Zhuhai Institute of Translational Medicine Zhuhai Precision Medical CenterZhuhai People’s Hospital(Zhuhai Hospital Affiliated with Jinan University)Zhuhai 519000China key Laboratory of Smart Drug Delivery Ministry of EducationDepartment of PharmaceuticsSchool of PharmacyFudan UniversityShanghai 201203China School of Materials Science and Engineering Dongguan University of TechnologyDongguan 523808China

Nanoscale drug delivery systems(nDDS)have been employed widely in enhancing the therapeutic efficacy of drugs against diseases with reduced side effects.Although several nDDS have been successfully approved for clinical use up to now,biological barriers between the administration site and the target site hinder the wider clinical adoption of nDDS in disease treatment.Polyethylene glycol(PEG)-modification(or PEGylation)has been regarded as the gold standard for stabilising nDDS in complex biological environment.However,the accelerated blood clearance(ABC)of PEGylated nDDS after repeated injections becomes great challenges for their clinical applications.Zwitterionic polymer,a novel family of antifouling materials,have evolved as an alternative to PEG due to their super-hydrophilicity and biocompatibility.Zwitterionic nDDS could avoid the generation of ABC phenomenon and exhibit longer blood circulation time than the PEGylated analogues.More impressively,zwitterionic nDDS have recently been shown to overcome multiple biological barriers such as nonspecific organ distribution,pressure gradients,impermeable cell membranes and lysosomal degradation without the need of any complex chemical modifications.The realization of overcoming multiple biological barriers by zwitterionic nDDS may simplify the current overly complex design of nDDS,which could facilitate their better clinical translation.Herein,we summarise the recent progress of zwitterionic nDDS at overcoming various biological barriers and analyse their underlyingmechanisms.Finally,prospects and challenges are introduced to guide the rational design of zwitterionic nDDS for disease treatment.

关键词： Zwitterionic polymer Nano drug delivery system Biological barrier Targeting delivery Disease treatment

The Combined Effects of High Temperatures and Ozone Pollution on Medical Emergency Calls—Jinan City,Shandong Province,China,2013–2019

在线全文

维普期刊数据库

学校读者我要写书评

暂无评论

China CDC weekly 2024年第2期6卷 30-35,I0001-I0007页

作者： Huiyun Chang Chong liu Xingyi Geng Xiumiao Peng ke Huang Liheng Wang Liangliang Cui Department of Scientific Research and Education Jinan Municipal Center for Disease Control and PreventionJinan Municipal Center for Disease Control and Prevention Affiliated to Shandong UniversityJinan CityShandong ProvinceChina Jinan Health Well Development Center Jinan CityShandong ProvinceChina Department of Environmental Health Jinan Municipal Center for Disease Control and PreventionJinan CityShandong ProvinceChina Department of Emergency Jinan Medical Emergency CenterJinan CityShandong ProvinceChina

What is already known about this topic?Studies have extensively documented the separate and independent effects of extreme temperature and ozone on morbidity and mortality associated with respiratory and circulatory diseases.What is added by this report?The study revealed a significant association between elevated temperature,ozone pollution,and the combined effect of high temperature and ozone pollution with an increased risk of all-cause medical emergency calls(MECs)and MECs specifically related to neurological diseases.What are the implications for public health practice?Interventional measures should be implemented to mitigate exposure to high temperatures and ozone levels.Specifically,during the warm season,it is crucial for relevant authorities to focus on disseminating scientific information regarding the health impacts of elevated temperatures and ozone pollution.Additionally,timely public health advisories should be issued to alert the public effectively.

关键词： ozone elevated pollution