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Can NogoA Be a Suitable Target to Treat Ischemic Stroke?

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Neuroscience Bulletin 2024年第4期40卷 557-560页

作者： Suliman khan Abdul nasir Medical Research Center The Second Affiliated Hospital of Zhengzhou UniversityZhengzhou540014China

Treating stroke or restoring brain function after stroke remains challenging for clinicians[1,2].Researchers have largely focused on developing neuroprotective strategies and translating these discoveries from rodent experiments to the clinical setting;however,these have been typified by several failures[2].It is known that astrocytes play a crucial role in the pathogenesis of ischemic stroke[3,4].They are activated in response to stimuli arising from injury,characterized by drastic changes to their morphology and function-associated gene expression.Reactive astrocytes exacerbate secondary neurodegeneration(repair of nervous tissue by the generation of new neurons,glial cells,axons,myelin,or synapses)[5]as well as provide neuroprotection during CNS pathologies[6].It is worth noting that myelin-related neurite growth inhibitors induce the suppression of axon regeneration after stroke[7].

关键词： protective NogoA clinical

Federated Learning Security and Privacy-Preserving Algorithm and Experiments Research Under Internet of Things Critical Infrastructure

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Tsinghua Science and Technology 2024年第2期29卷 400-414页

作者： nasir Ahmad Jalali Hongsong Chen Department of Computer Science University of Science and Technology Beijing(USTB)Beijing 100083China

The widespread use of the Internet of Things(IoTs)and the rapid development of artificial intelligence technologies have enabled applications to cross commercial and industrial band settings.Within such systems,all participants related to commercial and industrial systems must communicate and generate data.However,due to the small storage capacities of IoT devices,they are required to store and transfer the generated data to third-party entity called“cloud”,which creates one single point to store their data.However,as the number of participants increases,the size of generated data also increases.Therefore,such a centralized mechanism for data collection and exchange between participants is likely to face numerous challenges in terms of security,privacy,and performance.To address these challenges,Federated Learning(FL)has been proposed as a reasonable decentralizing approach,in which clients no longer need to transfer and store real data in the central server.Instead,they only share updated training models that are trained over their private datasets.At the same time,FL enables clients in distributed systems to share their machine learning models collaboratively without their training data,thus reducing data privacy and security challeges.However,slow model training and the execution of additional unnecessary communication rounds may hinder FL applications from operating properly in a distributed system.Furthermore,these unnecessary communication rounds make the system vulnerable to security and privacy issues,because irrelevant model updates are sent between clients and servers.Thus,in this work,we propose an algorithm for fully homomorphic encryption called Cheon-kim-kim-Song(CkkS)to encrypt model parameters for their local information privacy-preserving function.The proposed solution uses the impetus term to speed up model convergence during the model training process.Furthermore,it establishes a secure communication channel between IoT devices and the server.We also use a lightweight secure transport protocol

关键词： Federated Learning(FL) Internet of Things(IoTs) lightweight Transport Layer Security(iTLS) Cheon-kim-kim-Song(CkkS)

Mixed convectional and chemical reactive flow of nanofluid with slanted MHD on moving permeable stretching/shrinking sheet through nonlinear radiation,energy omission

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Chinese Physics B 2024年第5期33卷 193-202页

作者： Saleem nasir Sekson Sirisubtawee Pongpol Juntharee Taza Gul Department of Mathematics Faculty of Applied ScienceKing Mongkut's University of Technology North BangkokBangkok 10800Thailand Department of Mathematics City University of Science and Information TechnologyPeshawarPakistan

Hybrid nanofluids are remarkable functioning liquids that are intended to reduce the energy loss while maximizing the heat transmission.In the involvement of suction and nonlinear thermal radiation effects,this study attempted to explore the energy transmission features of the inclined magnetohydrodynamic(MHD)stagnation flow of CNTs-hybrid nanofluid across the nonlinear permeable stretching or shrinking sheet.This work also included some noteworthy features like chemical reactions,variable molecular diffusivity,quadratic convection,viscous dissipation,velocity slip and heat omission assessment.Employing appropriate similarity components,the model equations were modified to ODEs and computed by using the HAM technique.The impact of various relevant flow characteristics on movement,heat and concentration profiles was investigated and plotted on a graph.Considering various model factors,the significance of drag friction,heat and mass transfer rate were also computed in tabular and graphical form.This leads to the conclusion that such factors have a considerable impact on the dynamics of fluid as well as other engineering measurements of interest.Furthermore,viscous forces are dominated by increasing the values ofλ_(p),δ_(m)andδ_(q),and as a result,F(ξ)accelerates while the opposite trend is observed for M andφ.The drag friction is boosted by the augmentation M,λ_(p)andφ,but the rate of heat transfer declined.According to our findings,hybrid nanoliquid effects dominate that of ordinary nanofluid in terms of F(ξ),Θ(ξ)andφ(ξ)profiles.The HAM and the numerical technique(shooting method)were found to be in good agreement.

关键词： hybrid nanofluid(SWCNT+MWCNT/H_(2)O) velocity slip conditions nonlinear thermal radiation exponential stretching/shrinking sheet inclined magnetohydrodynamic(MHD)stagnation flow

Facile in situ synthesis and characterization of Fe@Si/zeolite Na composites with magnetic core–shell structures from natural materials for enhanced curcumin loading capacity

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Nanotechnology and Precision Engineering 2024年第2期7卷 69-86页

作者： Munasir nasir Nuhaa Faaizatunnisa Muhammad Naufal Ariesta Lydia Rohmawati Rifqi Aul Department of Physics Faculty of Mathematics and Natural ScienceUniversitas Negeri Surabaya(Unesa)Surabaya60231Indonesia Department of Chemistry Faculty of Science and Data AnalyticsInstitut Teknologi Sepuluh Nopember(ITS)Surabaya 60111Indonesia Department of Chemistry Faculty of Mathematics and Natural SciencesUniversitas Sebelas Maret(UNS)Surakarta57126Indonesia Department of Medicine Faculty of Medical and Health ScienceUniversitas Islam Negeri(UIN)Maulana Malik IbrahimMalang65151Indonesia

Curcumin is a natural polyphenol that is used in various traditional medicines.However,its inherent properties,such as its rapid degradation and metabolism,low bioavailability,and short half-life,are serious problems that must be resolved.To this end,a drug carrier incorporating natural magnetic cores in a zeolite framework was developed and applied to the loading of curcumin in ethanol solutions.In this system,curcumin is encapsulated in a zeolite Na(ZNA)magnetic core–shell structure(Fe@Si/ZNA),which can be easily synthesized using an in situ method.Synthesis of Fe_(3)O_(4) nanoparticles was carried out from natural materials using a co-precipitation method.Analysis of the prepared magnetic core–shell structures and composites was carried out using vibrating-sample magnetometery,Fourier transform infrared spectroscopy,transmission electron microscopy,and x-ray diffraction.The cumulative loading of curcumin in the ZNA composite with 9%nanoparticles was found to reach 90.70%with a relatively long half-life of 32.49 min.Stability tests of curcumin loading in the composite showed that adding magnetic particles to the zeolite framework also increased the stability of the composite structure.Adsorption kinetics and isotherm studies also found that the system follows the pseudo-second-order and Langmuir isotherm models.

关键词： Zeolite Na Magnetic core–shell nanoparticles(MNPs) ZNA Adsorption Curcumin

Tuning structural,electrical,dielectric and magnetic properties of Mg-Cu-Co ferrites via dysprosium(Dy^(3+))doping

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Journal of Rare Earths 2024年第1期42卷 137-146,I0005页

作者： Maria Akhtar M.S.Hasan nasir Amin N.A.Morley Muhammad Imran Arshad Department of Physics Government College UniversityFaisalabad38000Pakistan Department of Physics The University of Lahore53700Pakistan Department of Materials Science and Engineering The University of SheffieldS13JDUK Department of Physics&Astronomy University College LondonUK

In current research work,Dy3+substituted Mg0.5Cu0.25Co0.25Fe2-xDyxO4(0.0≤x≤0.04 with the step interval of 0.01)soft ferrites were synthesized by the sol-gel auto combustion method.The prepared samples were characterized by the techniques using X-ray diffraction(XRD),scanning electron microscopy(SEM),energy dispersive X-ray spectroscopy(EDS),Fourier transform infrared(FTIR)spectroscopy,curre nt-voltage(Ⅰ-Ⅴ)measurement,LCR meter,vibrating sample magnetometer(VSM)and Raman.XRD data reveal that the average crystallite size is 49.71 nm and the lattice constant is 0.83703 nm for sample x=0.03.The non-uniform grain growth was demonstrated by micrographs and impurity-free elemental composition was observed from EDX analysis.The DC resistivity has an increasing and decreasing trend in ferromagnetic and paramagnetic regions with an increase in temperature.Moreover,the high resistivity is observed with the order of 1010Ω·cm,and the activation energy is 0.944 eV for samples x=0.03.The dielectric parameters including dielectric constant,dielectric losses,and impedance gradually decrease with the increase in frequency from 8 Hz to 8 MHz.The minimum dielectric loss at high frequency is found for sample x=0.03.The coercivity(Hc)and saturation magnetization(Ms)are found in the ranges of 520.82-544.02 Oe and 20.5841-21.1473 emu/g,respectively.These observations confirm that dysprosium(x=0.03)doped MCC-soft ferrites may be applicable in transformer cores,microwave absorbance,and telecommunication devices.

关键词： Soft ferrites DC resistivity Dielectric loss Impedance Coercivity Rare earths

Identifying the stability of housekeeping genes to be used for the quantitative real-time PCR normalization in retinal tissue of streptozotocin-induced diabetic rats

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International Journal of Ophthalmology(English edition) 2024年第5期17卷 794-805页

作者： Muhammad Zulfiqah Sadikan Nurul Alimah Abdul nasir Mohammad Johari Ibahim Igor Iezhitsa Renu Agarwal Department of Pharmacology Faculty of MedicineManipal University College Malaysia(MUCM)Bukit BaruMelaka 75150Malaysia Centre for Neuroscience Research(NeuRon) Faculty of MedicineUniversiti Teknologi MARASungai Buloh CampusSungai BulohSelangor 47000Malaysia Department of Medical Education Faculty of MedicineUniversiti Teknologi MARASungai Buloh CampusSungai BulohSelangor 47000Malaysia Department of Biochemistry and Molecular Medicine Faculty of MedicineUniversiti Teknologi MARASungai Buloh CampusSungai BulohSelangor 47000Malaysia School of Medicine International Medical UniversityBukit JalilKuala Lumpur 57000Malaysia Department of Pharmacology and Bioinformatics Volgograd State Medical UniversityVolgograd 400131Russia

AIM:To investigate the stability of the seven housekeeping genes:beta-actin(ActB),glyceraldehyde-3-phosphate dehydrogenase(GAPDH),18s ribosomal unit 5(18s),cyclophilin A(CycA),hypoxanthine-guanine phosphoribosyl transferase(HPRT),ribosomal protein large P0(36B4)and terminal uridylyl transferase 1(U6)in the diabetic retinal tissue of rat model.METHODS:The expression of these seven genes in rat retinal tissues was determined using real-time quantitative reverse transcription polymerase chain reaction(RT-qPCR)in two groups;normal control rats and streptozotocininduced diabetic rats.The stability analysis of gene expression was investigated using geNorm,NormFinder,Bestkeeper,and comparative delta-Ct(ΔCt)algorithms.RESULTS:The 36B4 gene was stably expressed in the retinal tissues of normal control animals;however,it was less stable in diabetic retinas.The 18s gene was expressed consistently in both normal control and diabetic rats’retinal tissue.That this gene was the best reference for data normalisation in RT-qPCR studies that used the retinal tissue of streptozotocin-induced diabetic rats.Furthermore,there was no ideal gene stably expressed for use in all experimental settings.CONCLUSION:Identifying relevant genes is a need for achieving RT-qPCR validity and reliability and must be appropriately achieved based on a specific experimental setting.

关键词： housekeeping genes stability real-time reverse transcription polymerase chain reaction retinal tissue streptozotocin-induced diabetic rats

Algorithm for Visualization of Zero Divisor Graphs of the Ring ℤ_n Using MAPLE Coding

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Open Journal of Discrete Mathematics 2024年第1期14卷 1-8页

作者： nasir Ali Department of Mathematics Lahore Campus COMSATS University Islamabad Lahore Pakistan Department of Mathematics Vehari Campus COMSATS University Islamabad Vehari Pakistan

This research investigates the comparative efficacy of generating zero divisor graphs (ZDGs) of the ring of integers ℤn modulo n using MAPLE algorithm. Zero divisor graphs, pivotal in the study of ring theory, depict relationships between elements of a ring that multiply to zero. The paper explores the development and implementation of algorithms in MAPLE for constructing these ZDGs. The comparative study aims to discern the strengths, limitations, and computational efficiency of different MAPLE algorithms for creating zero divisor graphs offering insights for mathematicians, researchers, and computational enthusiasts involved in ring theory and mathematical computations.

关键词： Zero Divisor Graph Ring Theory Maple Algorithm ℤn Modulo n Graph Theory Mathematical Computing

Cervical Cancer Prediction Empowered with Federated Machine Learning

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Computers, Materials & Continua 2024年第4期79卷 963-981页

作者： Muhammad Umar nasir Omar kassem khalil karamath Ateeq Bassam SaleemAllah Almogadwy M.A.khan khan Muhammad Adnan Department of Computer Sciences Bahria University Lahore CampusLahore54000Pakistan Faculty of Information Technology Liwa CollegeAbu Dhabi20009UAE Department of Computing Skyline University CollegeSharjah999041UAE Department of Computer Science Taibah UniversityMedina42315Saudi Arabia Riphah School of Computing and Innovation Faculty of ComputingRiphah International UniversityLahore54000Pakistan Department of Software Faculty of Artificial Intelligence and SoftwareGachon UniversitySeongnam13120Korea

Cervical cancer is an intrusive cancer that imitates various women around the world. Cervical cancer ranks in thefourth position because of the leading death cause in its premature stages. The cervix which is the lower end of thevagina that connects the uterus and vagina forms a cancerous tumor very slowly. This pre-mature cancerous tumorin the cervix is deadly if it cannot be detected in the early stages. So, in this delineated study, the proposed approachuses federated machine learning with numerous machine learning solvers for the prediction of cervical cancer totrain the weights with varying neurons empowered fuzzed techniques to align the neurons, Internet of MedicalThings (IoMT) to fetch data and blockchain technology for data privacy and models protection from hazardousattacks. The proposed approach achieves the highest cervical cancer prediction accuracy of 99.26% and a 0.74%misprediction rate. So, the proposed approach shows the best prediction results of cervical cancer in its early stageswith the help of patient clinical records, and all medical professionals will get beneficial diagnosing approachesfrom this study and detect cervical cancer in its early stages which reduce the overall death ratio of women due tocervical cancer.

关键词： Cervical cancer federated machine learning neurons blockchain technology

Federated Machine Learning Based Fetal Health Prediction Empowered with Bio-Signal Cardiotocography

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Computers, Materials & Continua 2024年第3期78卷 3303-3321页

作者： Muhammad Umar nasir Omar kassem khalil karamath Ateeq Bassam SaleemAllah Almogadwy Muhammad Adnan khan Muhammad Hasnain Azam khan Muhammad Adnan Department of Computer Sciences Bahria University Lahore CampusLahore54000Pakistan Faculty of Information Technology Liwa CollegeAbu Dhabi00000United Arab Emirates Department of Computing Skyline University CollegeSharjah1797United Arab Emirates Department of Computer Science Taibah UniversityMedina42353Saudi Arabia Riphah School of Computing and Innovation Faculty of ComputingRiphah International UniversityLahore CampusLahore54000Pakistan Department of Engineering and Development Dubizzle LabsLahore54000Pakistan Department of Software Faculty of Artificial Intelligence and SoftwareGachon UniversitySeongnam-si13120Korea

Cardiotocography measures the fetal heart rate in the fetus during pregnancy to ensure physical health because cardiotocography gives data about fetal heart rate and uterine shrinkages which is very beneficial to detect whether the fetus is normal or suspect or pathologic.Various cardiotocography measures infer wrongly and give wrong predictions because of human error.The traditional way of reading the cardiotocography measures is the time taken and belongs to numerous human errors as well.Fetal condition is very important to measure at numerous stages and give proper medications to the fetus for its well-being.In the current period Machine learning(ML)is a well-known classification strategy used in the biomedical field on various issues because ML is very fast and gives appropriate results that are better than traditional results.ML techniques play a pivotal role in detecting fetal disease in its early stages.This research article uses Federated machine learning(FML)and ML techniques to classify the condition of the fetus.This study proposed a model for the detection of bio-signal cardiotocography that uses FML and ML techniques to train and test the data.So,the proposed model of FML used numerous data preprocessing techniques to overcome data deficiency and achieves 99.06%and 0.94%of prediction accuracy and misprediction rate,respectively,and parallel the proposed model applying k-nearest neighbor(kNN)and achieves 82.93%and 17.07%of prediction accuracy and misprediction accuracy,respectively.So,by comparing both models FML outperformed the kNN technique and achieved the best and most appropriate prediction results as compared with previous studies the proposed study achieves the best and most accurate results.

关键词： Cardiotocography ML FML fetal disease bio-signal