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Clinical relevance of circulating non-coding RNAs in metabolic diseases:Emphasis on obesity,diabetes,cardiovascular diseases and metabolic syndrome

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Genes & Diseases 2023年第6期10卷 2393-2413页

作者： Abdullahi Dandare Muhammad jawad khan Aisha Naeem Afrose Liaquat Department of Biosciences COMSATS University IslamabadIslamabad 45550Pakistan Department of Biochemistry Usmanu Danfodiyo UniversitySokoto 840104Nigeria Ministry of Public Health POB42DohaQatar Department of Oncology Lombardi Comprehensive Cancer CenterGeorgetown University Medical CenterWashingtonDC 20057USA Shifa College of Medicine Shifa Tameer-E-Millat UniversityIslamabad 45550Pakistan

Non-coding RNAs(ncRNAs)participate in the regulation of several cellular processes including transcription,RNA processing and genome *** aberrant expression of ncRNAs is associated with several pathological *** this review,we focused on recent information to elucidate the role of various regulatory ncRNAs i.e.,micro RNAs(miRNAs),circular RNAs(circRNAs)and long-chain non-coding RNAs(lncRNAs),in metabolic diseases,e.g.,obesity,diabetes mellitus(DM),cardiovascular diseases(CVD)and metabolic syndrome(MetS).The mechanisms by which ncRNAs participated in disease pathophysiology were also *** regulate the expression of genes at transcriptional and translational *** modulate the regulation of gene expression via miRNA sponging activity,interacting with RNA binding protein and polymerase II transcription *** regulate the expression of genes by acting as a protein decoy,miRNA sponging,miRNA host gene,binding to miRNA response elements(MRE)and the recruitment of transcriptional element or chromatin *** examined the role of ncRNAs in the disease pathogenesis and their potential role as molecular markers for diagnosis,prognosis and therapeutic *** showed the involvement of ncRNAs in the onset of obesity and its progression to MetS and ***-192,miRNA-122,and miRNA-221 were dysregulated in all these metabolic *** ncRNAs,implicated in at least three diseases include miRNA-15a,miRNA-26,miRNA-27a,miRNA-320,and *** of ncRNAs increased the risk of development of DM and MetS and its progression to CVD in obese ***,these molecules are potential targets to arrest or delay the progression of metabolic diseases.

关键词： Biomarkers CircRNAs LncRNAs Metabolic diseases miRNAs Non-coding RNAs Therapeutic targets

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Smart-City-based Data Fusion Algorithm for Internet of Things

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Computers, Materials & Continua 2022年第11期73卷 2407-2421页

作者： jawad khan Muhammad Amir khan N.Z.Jhanjhi Mamoona Humayun Abdullah Alourani Department of Computer Science IIC University of TechnologyPhnom PenhCambodia Department of Computer Science COMSATS University IslamabadAbbottabad Campus22060Pakistan School of Computer Science and Engineering SCETaylor’s UniversitySubang JayaSelangorMalaysia Department of Information Systems College of Computer and Information SciencesJouf Universityal-JoufKSA Department of Computer Science and Information College of Science in ZulfiMajmaah UniversityAl-Majmaah11952Saudi Arabia

Increasingly,Wireless Sensor Networks(WSNs)are contributing enormous amounts of *** the recent deployments of wireless sensor networks in Smart City infrastructures,significant volumes of data have been produced every day in several domains ranging from the environment to the healthcare system to *** wireless sensor nodes,a Smart City environment may now be shown for the benefit of *** Smart City delivers intelligent infrastructure and a stimulating environment to citizens of the Smart Society,including the elderly and ***,Quality of Service(QoS)and poor data performance are common problems in WSNs,caused by the data fusion method,where a small amount of bad data can significantly impact the total fusion *** our proposed research,a WSN multisensor data fusion technique employing fuzzy logic for event *** the new proposed Algorithm,sensor nodes will collect less repeated data,and redundant data will be used to increase the data’s overall *** network’s fusion delay problem is investigated,and a minimum fusion delay approach is provided based on the nodes’fusion waiting *** proposed algorithm performs well in fusion,according to the results of the *** a result of these discoveries,It is concluded that the algorithm describe here is effective and dependable instrument with a wide range of applications.

关键词： Internet of things data fusion wireless sensor network fuzzy inference system

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Integrated CWT-CNN for Epilepsy Detection Using Multiclass EEG Dataset

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Computers, Materials & Continua 2021年第10期69卷 471-486页

作者： Sidra Naseem Kashif Javed Muhammad jawad khan Saddaf Rubab Muhammad Attique khan Yunyoung Nam Robotics and Machine Intelligence Engineering School of Mechanical and Manufacturing EngineeringNational University of Sciences and Technology(NUST)Islamabad44000Pakistan National University of Sciences and Technology(NUST) Islamabad44000Pakistan Department of Computer Science HITEC University TaxilaTaxilaPakistan Department of Computer Science and Engineering Soonchunhyang UniversityAsanKorea

Electroencephalography is a common clinical procedure to record brain signals generated by human *** are useful in Brain controlled interfaces and other intelligent Neuroscience applications,but manual analysis of these brainwaves is complicated and time-consuming even for the experts of *** EEG analysis and classification techniques have been proposed to address this problem however,the conventional classification methods require identification and learning of specific EEG characteristics *** learning models can learn features from data without having in depth knowledge of data and prior feature *** of the great implementations of deep learning is Convolutional Neural Network(CNN)which has outperformed traditional neural networks in pattern recognition and image *** Wavelet Transform(CWT)is an efficient signal analysis technique that presents the magnitude of EEG signals as timerelated Frequency *** deep learning architectures suffer from poor performance when classifying EEG signals in the Time-frequency *** improve classification accuracy,we propose an integrated CWT and CNN technique which classifies five types of EEG signals *** compared the results of proposed integrated CWT and CNN method with existing deep learning models e.g.,GoogleNet,VGG16,***,the accuracy and loss of the proposed integrated CWT and CNN method have been cross validated using Kfold cross *** average accuracy and loss of Kfold cross-validation for proposed integrated CWT and CNN method are,76.12%and 56.02%*** model produces results on a publicly available dataset:Epilepsy dataset by UCI(Machine Learning Repository).

关键词： Deep learning electroencephalography epilepsy continuous wavelet transform

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Identification of hsa_circ_0092576 regulatory network in the pathogenesis of coronary heart disease

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Genes & Diseases 2023年第1期10卷 26-28页

作者： Abdullahi Dandare Muhammad Rafiq Afrose Liaquat Afraz Ahmad Raj Muhammad jawad khan Department of Biosciences COMSATS University IslamabadIslamabad 45550Pakistan Department of Biochemistry Usmanu Danfodiyo University SokotoSokoto P.M.B.2346Nigeria Department of Biochemistry Shifa College of MedicineShifa Tameer-E-Millat UniversityIslamabad 45550Pakistan Department of Psychosomatic Medicine and Psychotherapy University Medical CenterGottingen 37075Germany

Cardiovascular diseases(CVDs)are responsible for 30%of all deaths *** heart disease(CHD),is the most common form of CVD,accounting for 46%of male and 38%female cardiovascular deaths.1 CHD is characterized by chronic inflammation and endothelial injuries in coronary arteries,and subsequent development of atherosclerotic plaques which eventually leads to myocardial ischemia.

关键词： coronary injuries inflammation

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Hemodynamic Response Detection Using Integrated EEG-fNIRS-VPA for BCI

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Computers, Materials & Continua 2022年第1期70卷 535-555页

作者： Arshia Arif M.jawad khan Kashif Javed Hasan Sajid Saddaf Rubab Noman Naseer Talha Irfan khan National University of Sciences and Technology(NUST) IslamabadPakistan Intelligent Robotics Lab National Center of Artificial IntelligenceNational University of Sciences and Technology(NUST)IslamabadPakistan Department of Mechatronics Engineering Air UniversityIslamabadPakistan Institute of Space Technology IslamabadPakistan

For BCI systems,it is important to have an accurate and less complex architecture to control a device with enhanced *** this paper,a novel methodology for more accurate detection of the hemodynamic response has been developed using a multimodal brain-computer interface(BCI).An integrated classifier has been developed for achieving better classification accuracy using two *** integrated EEG-fNIRS-based vector-phase analysis(VPA)has been *** open-source dataset collected at the TechnischeUniversit鋞Berlin,including simultaneous electroencephalography(EEG)and functional near-infrared spectroscopy(fNIRS)signals of 26 healthy participants during n-back tests,has been used for this *** and physiological noise removal has been done using preprocessing techniques followed by individually detecting activity in both *** resting state threshold circle,VPA has been used to detect a hemodynamic response in fNIRS signals,whereas phase plots for EEG signals have been constructed using Hilbert Transform to detect the activity in each *** threshold circles are drawn in the vector plane,where each circle is drawn after task completion in each trial of EEG ***,both processes are integrated into one vector-phase plot to get combined detection of hemodynamic response for *** of this study illustrate that the combined EEG-fNIRS VPA yields considerably higher average classification accuracy,that is 91.35%,as compared to other classifiers such as support vector machine(SVM),convolutional neural networks(CNN),deep neural networks(DNN)and VPA(with dual-threshold circles)with classification accuracies 82%,89%,87%and 86%*** of this research demonstrate that improved classification performance can be feasibly achieved using multimodal VPA for EEG-fNIRS hybrid data.

关键词： EEG-fNIRS hybrid BCI vector-phase analysis hemodynamic response detection

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Enhanced Accuracy for Motor Imagery Detection Using Deep Learning for BCI

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Computers, Materials & Continua 2021年第9期68卷 3825-3840页

作者： Ayesha Sarwar Kashif Javed Muhammad jawad khan Saddaf Rubab Oh-Young Song Usman Tariq National University of Sciences and Technology(NUST) Islamabad44000Pakistan Department of Software Sejong UniversitySeoulGwangjin-guKorea College of Computer Engineering and Sciences Prince Sattam bin Abdulaziz UniversityAl-Kharj11942Saudi Arabia

Brain-Computer Interface(BCI)is a system that provides a link between the brain of humans and the hardware *** recorded brain data is converted directly to the machine that can be used to control external *** are four major components of the BCI system:acquiring signals,preprocessing of acquired signals,features extraction,and *** traditional machine learning algorithms,the accuracy is insignificant and not up to the mark for the classification of multi-class motor imagery *** major reason for this is,features are selected manually,and we are not able to get those features that give higher accuracy *** this study,motor imagery(MI)signals have been classified using different deep learning *** have explored two different methods:Artificial Neural Network(ANN)and Long Short-Term Memory(LSTM).We test the classification accuracy on two datasets:BCI competition III-dataset IIIa and BCI competition IV-dataset *** outcome proved that deep learning algorithms provide greater accuracy results than traditional machine learning *** the deep learning classifiers,LSTM outperforms the ANN and gives higher classification accuracy of 96.2%.

关键词： Brain-computer interface motor imagery artificial neural network long-short term memory classification

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Circulating miR-548c-3p possesses good diagnostic potential for metabolic syndrome

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Genes & Diseases 2023年第3期10卷 683-686页

作者： Abdullahi Dandare Afrose Liaquat Muhammad Rafiq Mbah Ntepe Leonel Javeres Sidra Younis Muhammad jawad khan Department of Biosciences COMSATS University IslamabadIslamabad 45550Pakistan Department of Biochemistry Usmanu Danfodiyo University SokotoSokoto PMB 2346Nigeria Department of Biochemistry Shifa College of MedicineShifa Tameer-E-Millat UniversityIslamabad 45550Pakistan Institute of Medical Research and Medical Plant Studies Ministry of Scientific ResearchYaoindeCameroon Department of Biological Sciences National University of Medical SciencesRawalpindiPunjab 46000Pakistan

Studies have shown that dysregulated expression of miRNAs is a major underlying event in the onset and progression of many metabolic *** pathological role of miR-548c-3p in various cancer types,including breast cancer,glioma,prostate cancer,and gastric cancer,has been documented.1 However,experimental evidences validating the role of miR-548c-3p in the development of metabolic diseases are still lacking,and no data is available on its diagnostic potential for metabolic syndrome(MS).Recently,we predicted the involvement of miR-548c-3p in the pathogenesis of MS and its progression to cardiovascular diseases(CVD)via the regulation of target genes necessary for the proper function of insulin resistance,mTOR,and JAK/STAT signaling pathways.2 Therefore,we deemed it necessary to engage in wet laboratory analysis and validate these claims in patients with metabolic syndrome compared to healthy individuals.

关键词： JAK/STAT involvement diseases

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舰船雷达散射截面预报与控制

舰船雷达散射截面预报与控制

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作者： jawad khan 哈尔滨工程大学

学位级别：硕士

随着先进的检测系统日益发展，各种作战平台完成任务的成效已经受到威胁。因而，减小平台的探测性来增强作战平台生存能力越来越受到强烈的关注。现代的传感器采用各种信号对作战平台进行探测，包括雷达，红外，声，磁等。现代平台设计... 详细信息

随着先进的检测系统日益发展，各种作战平台完成任务的成效已经受到威胁。因而，减小平台的探测性来增强作战平台生存能力越来越受到强烈的关注。现代的传感器采用各种信号对作战平台进行探测，包括雷达，红外，声，磁等。现代平台设计要求精细的控制各种信号特征并达到平衡。本文主要针对雷达信号特征即雷达散射截面进行研究，目标是探索雷达散射截面规律以便对舰船平台雷达散射截面进行预报和控制。RCS指的是目标在雷达方向反射回来的能量的强度的测量，因此，通过雷达来检测物体。降低作战平台的RCS值意味着被发现需要的时间更长，这样可以优化作战平台的突击性和主动性。因而RCS成为了所有作战平台设计中非常重要的设计参数。本文对基于隐形技术的船舶设计的的研究进展进行了评估。得到的结论是，综合发展研究船舶隐形技术是促进隐形技术在国防工业中应用的关键。本文对电磁波散射机制和降低RSC值的方法在降低船舶RSC值中的应用进行了详细的探索，讨论了舰船设计师在雷达隐身性设计中的地位，对阻碍降低船舶RSC值的问题也进行了研讨。对RSC理论在确定船舶RCS值中的应用也进行了详细的研究，目前RCS软件也正被研究以确定对船舶RCS分析合适的软件。RCS代码也是基于前述步骤的知识编开发的。研究中对基本形状RCS值进行了模拟并与有效的结果进行了比较，对基本形状进行深入的RCS分析对于精通隐身设计是非常重要的。对基本形状的尺寸和频率对RCS值的影响的理解是，在设计像船或者航母等复杂的目标时最重要的是选择合适的形状。进行了船舶雷达散射截面模拟的目标设计。根据国际海事组织（IMO）SOLAS的公约相关条款，这项技术应用到了小船避免碰撞的雷达反射器的设计中。另外，一些规律还可以用于测试反舰艇导弹雷达导航能力的目标设计中。最后进行了舰船模型DTMB5145的RCS模拟结果的分析。

关键词：隐形舰船舰船雷达散射截面分析舰船雷达散射截面分析软件雷达反射器雷达目标

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Radar Cross Section Prediction and Reduction for Naval Ships

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Journal of Marine Science and Application 2012年第2期11卷 191-199页

作者： jawad khan Wenyang Duan Salma Sherbaz College of Shipbuilding Engineering Harbin Engineering University Harbin 150001 China

Radar cross section（RCS） is the measurement of the reflective strength of a *** the RCS of a naval ship enables its late detection,which is useful for capitalizing on elements of surprise and ***,the RCS of a naval ship has become a very important design factor for achieving surprise,initiative,and ***,accurate RCS determination and RCS reduction are of extreme importance for a naval *** purpose of this paper is to provide an understanding of the theoretical background and engineering approach to deal with RCS prediction and reduction for naval *** importance of RCS,radar fundamentals,RCS basics,RCS prediction methods,and RCS reduction methods for naval ships is also discussed.

关键词： stealth ship naval ship radar cross section RCS

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IoTFLiP： IoT-based flipped learning platform for medical education

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Digital Communications and Networks 2017年第3期3卷 188-194页

作者： Maqbool Ali Hafiz Syed Muhammad Bilal Muhammad Asif Razzaq jawad khan Sungyoung Lee Muhammad Idris Mohammad Aazam Taebong Choi Soyeon Caren Han Byeong Ho Kang Department of Computer Science and Engineering Kyung Hee University Yongin 446-701 Republic of Korea IT4BI Universite Libre de Bruxelles Belgium Carleton University Canada Hanwha Systems as Senior Manager Communication PM Team Seongnam 13524 Republic of Korea School of Engineering and ICT Uniuersity of Tasmania Hobart Tasmania 7005 Australia

Case-Based Learning （CBL） has become an effective pedagogy for student-centered learning in medical education, which is founded on persistent patient cases. Flippped learning and Internet of Things （IoTs） concepts have gained significant attention in recent years. Using these concepts in conjunction with CBL can improve learning ability by providing real evolutionary medical eases. It also enables students to build confidence in their decision making, and efficiently enhances teamwork in the learning environment. We propose an IoT-based Flip Learning Platform, called IoTFLiP, where an IoT infrastrneture is exploited to support flipped case-based learning in a cloud environment with state of the art security and privacy measures for personalized medical data. It also provides support for application delivery in private, public, and hybrid approaches. The proposed platform is an extension of our Interactive Case-Based Flipped Learning Tool （ICBFLT）, which has been developed based on current CBL practices. ICBFLT formulates summaries of CBL cases through synergy between students＇ and medical expert knowledge. The low cost and reduced size of sensor device, support of IoTs, and recent flipped learning advancements can enhance medical students＇ academic and practical experiences. In order to demonstrate a working scenario for the proposed IoTFLiP platform, real-time data from IoTs gadgets is collected to generate a real-world case for a medical student using ICBFLT.

关键词： Internet of things Cloud environment Flipped learning Case-based learning Medical education

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