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Celastrol enhances transcription factor EB (TFEB)-mediated autophagy and mitigates Tau pathology:Implications for Alzheimer's disease therapy

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Acta Pharmaceutica Sinica B 2022年第4期12卷 1707-1722页

作者： Chuanbin Yang Chengfu Su Ashok Iyaswamy senthil kumar krishnamoorthi Zhou Zhu Sichang Yang Benjamin Chunkit Tong Jia Liu Sravan G.Sreenivasmurthy Xinjie Guan Yuxuan Kan Aston Jiaxi Wu Alexis Shiying Huang Jieqiong Tan Kingho Cheung Juxian Song Min Li Mr.&Mrs.Ko Chi-Ming Centre for Parkinson’s Disease Research School of Chinese MedicineHong Kong Baptist UniversityHong Kong SARChina Department of Geriatrics Shenzhen People’s Hospital(the Second Clinical Medical CollegeJinan Universitythe First Affiliated HospitalSouthern University of Science and Technology)Shenzhen 518020China Institute for Research and Continuing Education Hong Kong Baptist UniversityShenzhen 518057China College of Pharmacy Henan University of Chinese MedicineZhengzhou 450000China Center for Medical Genetics and Hunan Key Laboratory of Animal Model for Human Diseases School of Life SciencesCentral South UniversityChangsha 410078China Medical College of Acupuncture-Moxibustion and Rehabilitation Guangzhou University of Chinese MedicineGuangzhou 510632China

Alzheimer's disease(AD),characterized by the accumulation of protein aggregates including phosphorylated Tau aggregates,is the most common neurodegenerative disorder with limited therapeutic *** plays a critical role in the degradation of phosphorylated Tau aggregates,and transcription factor EB(TFEB)is a master regulator of autophagy and lysosomal ***,small-molecule autophagy enhancers targeting TFEB hold promise for AD ***,we found that celastrol,an active ingredient isolated from the root extracts of Tripterygium wilfordii(Lei Gong Teng in Chinese)enhanced TFEB-mediated autophagy and lysosomal biogenesis in vitro and in mouse ***,celastrol reduced phosphorylated Tau aggregates and attenuated memory dysfunction and cognitive deficits in P301S Tau and 3xTg mice,two commonly used AD animal *** studies suggest that TFEB-mediated autophagy-lysosomal pathway is responsible for phosphorylated Tau degradation in response to ***,our findings indicate that Celastrol is a novel TFEB activator that promotes the degradation of phosphorylated Tau aggregates and improves memory in AD animal ***,Celastrol shows potential as a novel agent for the treatment and/or prevention of AD and other tauopathies.

关键词： TFEB Autophagy Lysosome biogenesis Alzheimer’s disease(AD) Tau Celastrol mTOR Therapeutic target

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Reliable Data Collection Model and Transmission Framework in Large-Scale Wireless Medical Sensor Networks

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Computer Modeling in Engineering & Sciences 2024年第7期140卷 1077-1102页

作者： Haosong Gou Gaoyi Zhang RenêRipardo Calixto senthil kumar Jagatheesaperumal Victor Hugo C.de Albuquerque China Mobile Group Sichuan Co. Ltd.Chengdu640041China Department of Teleinformatics Engineering Federal University of CearáFortaleza60455-970Brazil Department of Electronics&Communication Engineering Mepco Schlenk Engineering CollegeSivakasi626005India

Large-scale wireless sensor networks(WSNs)play a critical role in monitoring dangerous scenarios and responding to medical ***,the inherent instability and error-prone nature of wireless links present significant challenges,necessitating efficient data collection and reliable transmission *** paper addresses the limitations of existing data transmission and recovery protocols by proposing a systematic end-to-end design tailored for medical event-driven cluster-based large-scale *** primary goal is to enhance the reliability of data collection and transmission services,ensuring a comprehensive and practical *** approach focuses on refining the hop-count-based routing scheme to achieve fairness in forwarding ***,it emphasizes reliable data collection within clusters and establishes robust data transmission over multiple *** systematic improvements are designed to optimize the overall performance of the WSN in real-world *** results of the proposed protocol validate its exceptional performance compared to other prominent data transmission *** evaluation spans varying sensor densities,wireless channel conditions,and packet transmission rates,showcasing the protocol’s superiority in ensuring reliable and efficient data *** systematic end-to-end design successfully addresses the challenges posed by the instability of wireless links in *** prioritizing fairness,reliability,and efficiency,the proposed protocol demonstrates its efficacy in enhancing data collection and transmission services,thereby offering a valuable contribution to the field of medical event-drivenWSNs.

关键词： Wireless sensor networks reliable data transmission medical emergencies cluster data collection routing scheme

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Deep Transfer Learning Techniques in Intrusion Detection System-Internet of Vehicles: A State-of-the-Art Review

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Computers, Materials & Continua 2024年第8期80卷 2785-2813页

作者： Wufei Wu Javad Hassannataj Joloudari senthil kumar Jagatheesaperumal Kandala N.V.P.SRajesh Silvia Gaftandzhieva Sadiq Hussain Rahimullah Rabih Najibullah Haqjoo Mobeen Nazar Hamed Vahdat-Nejad Rositsa Doneva School of Information Engineering Nanchang UniversityNanchang330031China Department of Computer Engineering Technical and Vocational University(TVU)Tehran***Iran Department of Computer Engineering University of BirjandBirjand***Iran Department of Computer Engineering Babol BranchIslamic Azad UniversityBabol***Iran Department of Electronics&Communication Engineering Mepco Schlenk Engineering CollegeSivakasi626005India School of Electronics Engineering VIT-AP UniversityNear Vijayawada522237India Faculty of Mathematics and Informatics University of Plovdiv Paisii HilendarskiPlovdiv4000Bulgaria Examination Branch Dibrugarh UniversityDibrugarh786004India Department of Computer Engineering Faculty of EngineeringUniversity of BirjandBirjand***Iran Faculty of Electrical and Computer Engineering University of BirjandBirjand***Iran Malaysian Institute of Information Technology Universiti Kuala LumpurKuala Lumpur50250Malaysia Faculty of Physics and Technology University of Plovdiv Paisii HilendarskiPlovdiv4000Bulgaria

The high performance of IoT technology in transportation networks has led to the increasing adoption of Internet of Vehicles(IoV)*** functional advantages of IoV include online communication services,accident prevention,cost reduction,and enhanced traffic *** these benefits,IoV technology is susceptible to cyber-attacks,which can exploit vulnerabilities in the vehicle network,leading to perturbations,disturbances,non-recognition of traffic signs,accidents,and vehicle *** paper reviews the state-of-the-art achievements and developments in applying Deep Transfer Learning(DTL)models for Intrusion Detection Systems in the Internet of Vehicles(IDS-IoV)based on anomaly ***-IoV leverages anomaly detection through machine learning and DTL techniques to mitigate the risks posed by *** systems can autonomously create specific models based on network data to differentiate between regular traffic and *** these techniques,transfer learning models are particularly promising due to their efficacy with tagged data,reduced training time,lower memory usage,and decreased computational *** evaluate DTL models against criteria including the ability to transfer knowledge,detection rate,accurate analysis of complex data,and *** review highlights the significant progress made in the field,showcasing how DTL models enhance the performance and reliability of IDS-IoV *** examining recent advancements,we provide insights into how DTL can effectively address cyber-attack challenges in IoV environments,ensuring safer and more efficient transportation networks.

关键词： Cyber-attacks internet of things internet of vehicles intrusion detection system

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Recent antibacterial agents from biomass derivatives:Characteristics and applications

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Journal of Bioresources and Bioproducts 2024年第3期9卷 283-309页

作者： Nissa Nurfajrin Solihat Alif Faturahman Hidayat R.A.Ilyas senthil Muthu kumar Thiagamani Nur Izyan Wan Azeele Fahriya Puspita Sari Maya Ismayati Mohammad Irfan Bakshi Zaharaddeen N.Garba M.Hazwan Hussin Witta Kartika Restu Wasrin Syafii Harits Atika Ariyanta Widya Fatriasari Research Center for Biomass and Bioproducts National Research and Innovation Agency(BRIN)Kawasan KST SoekarnoJl Raya Bogor KM 46 Cibinong Bogor 16911Indonesia Department of Bioproducts and Biosystems School of Chemical EngineeringAalto UniversityEspoo 16300Finland Department of Chemical Engineering Faculty of Chemical and Energy EngineeringUniversiti Teknologi MalaysiaJohor 81310Malaysia Centre for Advanced Composite Materials Universiti Teknologi MalaysiaJohor 81310Malaysia Institute of Tropical Forestry and Forest Products Universiti Putra MalaysiaSerdang 43400Malaysia Centre of Excellence for Biomass Utilization Universiti Malaysia PerlisPerlis 02600Malaysia Department of Mechanical Engineering Kalasalingam Academy of Research and EducationKrishnankoil 626126India Institute of Bioproduct Development(IBD) Universiti Teknologi MalaysiaJohor 81310Malaysia Department of Chemistry Ahmadu Bello UniversityZaria 810211Nigeria Materials Technology Research Group(MaTReC) School of Chemical SciencesUniversiti Sains MalaysiaMinden 11800Malaysia Research Center for Chemistry National Research and Innovation Agency(BRIN)Kawasan Puspiptek SerpongSouth Tangerang 15314Indonesia Department of Forest Products Faculty of Forestry and EnvironmentIPB UniversityBogor 16680Indonesia Department of Pharmacy Gunadarma UniversityDepok 16424Indonesia Research Collaboration Center of Biomass-Based Nano Cosmetic In collaboration with National Research and Innovation Agency(BRIN)SamarindaEast KalimantanIndonesia

Enhancing awareness of personal cleanliness and antibacterial resistance has intensified the antibacterial substance request on consumable products. Antibacterial agents that have been commercialized nowadays are produced from inorganic and non-renewable substances. This provides several drawbacks, particularly against health and environmental issues. Therefore, many scientists work on substituting fossil-fuel-based antibacterial agents with natural ones such as from biomass. Biomass derivatives, natural abundances of biopolymers in the world, amount to major compounds including polysaccharides (cellulose, hemicellulose, and chitosan) and polyphenol (tannin and lignin) substances which are capable to combat the growth of Gram-positive bacteria and Gram-negative bacteria. To date, no report focuses on a deep understanding of antibacterial properties derived from biomass and the internal and external factors effects. This work provides that gap because comprehensive knowledge is necessary before applying biomass to the products. The potency of biomass derivatives as antibacterial additives is also summarized. Basic knowledge of antibacterial characteristics to the application in products is highlighted in this review. Besides, the discussion about challenges and future perspectives is also delivered.

关键词： Antibacterial Application Biomass derivatives Challenge Future perspectives

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Early Detection Glaucoma and Stargardt’s Disease Using Deep Learning Techniques

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Intelligent Automation & Soft Computing 2023年第5期36卷 1283-1299页

作者： Somasundaram Devaraj senthil kumar Arunachalam Department of Electronics and Communication Engineering Sri Shakthi Institute of Engineering and TechnologyCoimabatore641062TamilnaduIndia

Retinal fundus images are used to discover many *** Machine learning algorithms are designed to identify the Glaucoma *** the accuracy and time consumption performance were not *** address this problem Max Pool Convolution Neural Kuan Filtered Tobit Regres-sive Segmentation based Radial Basis Image Classiﬁer(MPCNKFTRS-RBIC)Model is used for detecting the Glaucoma and Stargardt’s disease by early period using higher accuracy and minimal *** MPCNKFTRS-RBIC Model,the ret-inal fundus image is considered as an input which is preprocessed in hidden layer 1 using weighted adaptive Kuanﬁ***,preprocessed retinal fundus is given for hidden layer 2 for extracting the features like color,intensity,texture with higher *** extracting these features,the Tobit Regressive Segmenta-tion process is performed by hidden layer 3 for partitioning preprocessed image within more segments by analyzing the pixel with the extracted features of the fundus ***,the segmented image was given to output *** radial basis function analyzes the testing image region of a particular class as well as training image region with higher accuracy and minimum time *** is performed with retinal fundus image dataset with various perfor-mance metrics namely peak signal-to-noise ratio,accuracy and time,error rate concerning several retina fundus image and image size.

关键词： Glaucoma detection max pool convolution neural network kuanﬁlter radial basis function

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Evaporative/radiative electrospun membrane for personal cooling

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Nano Research 2023年第2期16卷 2563-2571页

作者： Mohammad Irfan Iqbal Shuo Shi Gokula Manikandan senthil kumar Jinlian Hu Institute of Textiles and Clothing The Hong Kong Polytechnic UniversityHong Kong 999077China Department of Biomedical Engineering City University of Hong KongHong Kong 999077China Department of Building Environment and Energy Engineering The Hong Kong Polytechnic UniversityHong Kong 999077China

Functional textiles that promote daily comfort and productivity must efficiently release body sweats and transmit radiative heat through sweat evaporation and mid-infrared radiation(MIR)(8–13μm).However,most of the traditional clothing cannot provide simultaneous sweat evaporation and mid-infrared radiation transmission efficiently,leading to a poor design of personal cooling ***,an evaporative/radiative integrated functional fibrous electrospun membrane is meticulously designed and controllably fabricated via facile electrospinning technology for personal cooling *** developed membrane can be applied as a smart wearable with distinct personal thermal management *** promising temperature and humidity responsive vapor transmission of the membrane grants 1.2 times of evaporative cooling than that of traditional ***,based on its high mid-infrared radiation transmission(53%)property in the range of 8–13μm,the as-spun membrane provides extra cooling of 1.5°C than that of ***,the building energy saving performances demonstrated that 47.1%annual building cooling can be achieved using the developed electrospun *** general,the evaporative/radiative electrospun membrane creates a passive cooling microclimate for the human body,meeting the growing demand of wearable for personal cooling.

关键词： building energy cooling management electrospinning evaporative cooling radiative cooling

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Data augmentation and machine learning techniques for control strategy development in bio-polymerization process

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Environmental Science and Ecotechnology 2022年第3期11卷 40-48页

作者： Sizhou Wei Zhiyuan Chen senthil kumar Arumugasamy Irene Mei Leng Chew School of Computer Science University of NottinghamNottinghamNG81BBUnited Kingdom School of Computer Science University of Nottingham MalaysiaSemenyih43500Malaysia Department of Chemical and Environmental Engineering University of Nottingham MalaysiaSemenyih43500Malaysia School of Engineering Monash University MalaysiaSubang Jaya47500Malaysia

Machine learning has been increasingly used in ***,in organic chemistry and other experiment-based fields,data collected from real experiments are inadequate and the current coronavirus disease(COVID-19)pandemic has made the situation even *** limited data resources may result in the low performance of modeling and affect the proper development of a control *** paper proposes a feasible machine learning solution to the problem of small sample size in the biopolymerization *** avoid overfitting,the variational auto-encoder and generative adversarial network algorithms are used for data *** random forest and artificial neural network algorithms are implemented in the modeling *** results prove that data augmentation techniques effectively improve the performance of the regression *** machine learning models were compared and the experimental results show that the random forest model with data augmentation by the generative adversarial network technique achieved the best performance in predicting the molecular weight on the training set(with an R^(2) of 0.94)and on the test set(with an R^(2) of 0.74),and the coefficient of determination of this model was 0.74.

关键词： Bio-polymerization Variational autoencoder generative adversarial network Random forest Artificial neural network

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Gaussian PI Controller Network Classifier for Grid-Connected Renewable Energy System

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Intelligent Automation & Soft Computing 2023年第1期35卷 983-995页

作者： Ravi Samikannu K.Vinoth Narasimha Rao Dasari senthil kumar Subburaj Department of Electrical Computer and Telecommunications Engineering Botswana International University of Science and TechnologyBotswana Department of Electrical and Electronics Engineering Vel Tech Rangarajan Dr.Sagunthala R&D Institute of Science and TechnologyChennaiTamil NaduIndia Department of Electrical Power Engineering College of EngineeringDefence UniversityEthiopia Department Electrical and Electronics Engineering New Prince Shri Bhavani College of Engineering and TechnologySembakkamTamil NaduIndia

Multi-port converters are considered as exceeding earlier period decade owing to function in a combination of different energy sources in a single processing *** energy sources are playing a significant role in the modern energy system with rapid *** renewable sources like fuel combustion and solar energy,the generated voltages change due to their environmental *** develop energy resources,electric power generation involved huge *** power and output voltages are plays important role in our work but it not considered in the existing *** considering the power and voltage,Gaussian PI Controller-Maxpooling Deep Convolutional Neural Network Classifier(GPIC-MDCNNC)Model is introduced for the grid-connected renewable energy *** input information is collected from two input *** that,input layer transfer information to hidden layer 1 fuzzy PI is employed for controlling voltage in GPIC-MDCNNC *** layer 1 is transferred to hidden layer *** activation is employed for determining the output voltage with help of the *** last,the output layer offers the last value in GPIC-MDCNNC *** designed method was confirmed using one and multiple sources by stable and unpredictable input ***-MDCNNC Model increases the performance of grid-connected renewable energy systems by enhanced voltage value compared with state-of-the-art *** control technique using GPIC-MDCNNC Model increases the dynamics of hybrid energy systems connected to the grid.

关键词： Multi-port converters renewable sources fuzzy PI controller gaussian activation function fuel cell

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Deep Learning for Wind Speed Forecasting Using Bi-LSTM with Selected Features

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Intelligent Automation & Soft Computing 2023年第3期35卷 3829-3844页

作者： Siva Sankari Subbiah senthil kumar Paramasivan Karmel Arockiasamy Saminathan Senthivel Muthamilselvan Thangavel Department of Computer Science and Engineering Sreenivasa Institute of Technology and Management StudiesChittoor517127India School of Information Technology&Engineering Vellore Institute of TechnologyVellore632014India School of Computer Science and Engineering Vellore Institute of TechnologyChennai600127India School of Computing College of Engineering and TechnologySRM Institute of Science and TechnologyKattankulathur603203India

Wind speed forecasting is important for wind energy *** the modern era,the increase in energy demand can be managed effectively by fore-casting the wind speed *** main objective of this research is to improve the performance of wind speed forecasting by handling uncertainty,the curse of dimensionality,overﬁtting and non-linearity *** curse of dimensionality and overﬁtting issues are handled by using Boruta feature *** uncertainty and the non-linearity issues are addressed by using the deep learning based Bi-directional Long Short Term Memory(Bi-LSTM).In this paper,Bi-LSTM with Boruta feature selection named BFS-Bi-LSTM is proposed to improve the performance of wind speed *** model identiﬁes relevant features for wind speed forecasting from the meteorological features using Boruta wrapper feature selection(BFS).Followed by Bi-LSTM predicts the wind speed by considering the wind speed from the past and future time *** proposed BFS-Bi-LSTM model is compared against Multilayer perceptron(MLP),MLP with Boruta(BFS-MLP),Long Short Term Memory(LSTM),LSTM with Boruta(BFS-LSTM)and Bi-LSTM in terms of Root Mean Square Error(RMSE),Mean Absolute Error(MAE),Mean Square Error(MSE)and *** BFS-Bi-LSTM surpassed other models by producing RMSE of 0.784,MAE of 0.530,MSE of 0.615 and R2 of *** experimental result shows that the BFS-Bi-LSTM produced better forecasting results compared to others.

关键词： Bi-directional long short term memory boruta feature selection deep learning machine learning wind speed forecasting

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Highlighting novel genes associated with the classical Rett syndrome patient from India

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Genes & Diseases 2022年第6期9卷 1394-1396页

作者： Gomathi Mohan Ranjan Jyoti Sarma Mahalaxmi Iyer Nachimuthu senthil kumar Balachandar Vellingiri UGC-RGNF Senior Research Fellow Human Molecular Cytogenetics and Stem Cell LaboratoryDepartment of Human Genetics and Molecular BiologyBharathiar UniversityCoimbatore 641046Tamil NaduIndia Department of Biotechnology Mizoram University(A Central University)Aizawl 796004MizoramIndia Livestock Farming&Bioresource Technology Tamil NaduIndia Human Molecular Cytogenetics and Stem Cell Laboratory Department of Human Genetics and Molecular BiologyBharathiar UniversityCoimbatore 641046Tamil NaduIndia

Rett syndrome(RTT)is a rare X-linked brain disorder predominantly in females,caused by mutations in Methyl-CpGBinding Protein2(MECP2)gene with the characteristic features of progressive developmental delay,severe intellectual disability,microcephaly,retarded growth,loss of communication abilities,loss of purposeful hand movements,abnormal walking or gait abnormalities,repetitive hand movements,abnormal breathing,irritability and abnormal behaviours.1 Over the last five years,more than eighty genes related to RTT were found using next generation sequencing.2 Here we presented a comprehensive clinical report of a 38-year-old RTT woman having de novo heterozygous Laminin Subunit Gamma 3 gene(LAMC3)mutation G>A(Chr9:133944387;p.C947Y)links with RTT neurological dysfunctions,brain malformations,reduced brain volume and hypoplasia of corpus *** new finding supports the possibility of targeting LAMC3 gene for rescuing the neuropathology of *** deleterious mutations found in genes such as,CACNA1B(rs4422842),CUBN(rs2271460),GPATCH3(rs779537923),TUBB1(rs463312),KCNJ5(rs768906222),VWA5A(rs551469534),DNAAF1(rs751148678),and PARP1(rs3219145)were unreported in RTT patients.

关键词： RTT lighting delay

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