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Effects of mesenchymal stem cell on dopaminergic neurons,motor and memory functions in animal models of Parkinson's disease:a systematic review and meta-analysis

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Neural Regeneration Research 2024年第7期19卷 1584-1592页

作者： Jong Mi Park Masoud Rahmati Sang Chul Lee Jae Il Shin Yong Wook Kim Department and Research Institute of Rehabilitation Medicine Yonsei University College of MedicineSeoulSouth Korea Department of Physical Education and Sport Sciences Faculty of Literature and Human SciencesLorestan UniversityKhoramabadIran Department of Pediatrics Yonsei University College of MedicineSeoulSouth Korea

Parkinson’s disease is chara cterized by the loss of dopaminergic neurons in the substantia nigra pars com pacta,and although restoring striatal dopamine levels may improve symptoms,no treatment can cure or reve rse the disease itself.Stem cell therapy has a regenerative effect and is being actively studied as a candidate for the treatment of Parkinson’s disease.Mesenchymal stem cells are considered a promising option due to fewer ethical concerns,a lower risk of immune rejection,and a lower risk of teratogenicity.We performed a meta-analysis to evaluate the therapeutic effects of mesenchymal stem cells and their derivatives on motor function,memory,and preservation of dopamine rgic neurons in a Parkinson’s disease animal model.We searched bibliographic databases(PubMed/MEDLINE,Embase,CENTRAL,Scopus,and Web of Science)to identify articles and included only pee r-reviewed in vivo interve ntional animal studies published in any language through J une 28,2023.The study utilized the random-effect model to estimate the 95%confidence intervals(CI)of the standard mean differences(SMD)between the treatment and control groups.We use the systematic review center for laboratory animal expe rimentation’s risk of bias tool and the collaborative approach to meta-analysis and review of animal studies checklist for study quality assessment.A total of 33studies with data from 840 Parkinson’s disease model animals were included in the meta-analysis.Treatment with mesenchymal stem cells significantly improved motor function as assessed by the amphetamine-induced rotational test.Among the stem cell types,the bone marrow MSCs with neurotrophic factor group showed la rgest effect size(SMD[95%CI]=-6.21[-9.50 to-2.93],P=0.0001,I^(2)=0.0%).The stem cell treatment group had significantly more tyrosine hydroxylase positive dopamine rgic neurons in the striatum([95%CI]=1.04[0.59 to 1.49],P=0.0001,I^(2)=65.1%)and substantia nigra(SMD[95%CI]=1.38[0.89 to 1.87],P=0.0001,I^(2)=75.3%),indicating a protective effect on dopaminergic neurons.Subgro

关键词： animal animal experimentation mesenchymal stem cells models Parkinson’s disease stem cell transplantation

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Customized Convolutional Neural Network for Accurate Detection of Deep Fake Images in Video Collections

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Computers, Materials & Continua 2024年第5期79卷 1995-2014页

作者： Dmitry Gura Bo Dong Duaa Mehiar Nidal Al Said Department of Cadastre and Geoengineering Kuban State Technological UniversityKrasnodar350072Russian Federation Department of Geodesy Kuban State Agrarian UniversityKrasnodar350072Russian Federation School of Innovation and Entrepreneurship Liaoning UniversityLiaoning110031China Department of IT Middle East UniversityAmman11831Jordan College of Mass Communication Ajman UniversityP.O Box 346AjmanUnited Arab Emirates

The motivation for this study is that the quality of deep fakes is constantly improving,which leads to the need to develop new methods for their detection.The proposed Customized Convolutional Neural Network method involves extracting structured data from video frames using facial landmark detection,which is then used as input to the CNN.The customized Convolutional Neural Network method is the date augmented-based CNN model to generate‘fake data’or‘fake images’.This study was carried out using Python and its libraries.We used 242 films from the dataset gathered by the Deep Fake Detection Challenge,of which 199 were made up and the remaining 53 were real.Ten seconds were allotted for each video.There were 318 videos used in all,199 of which were fake and 119 of which were real.Our proposedmethod achieved a testing accuracy of 91.47%,loss of 0.342,and AUC score of 0.92,outperforming two alternative approaches,CNN and MLP-CNN.Furthermore,our method succeeded in greater accuracy than contemporary models such as XceptionNet,Meso-4,EfficientNet-BO,MesoInception-4,VGG-16,and DST-Net.The novelty of this investigation is the development of a new Convolutional Neural Network(CNN)learning model that can accurately detect deep fake face photos.

关键词： Deep fake detection video analysis convolutional neural network machine learning video dataset collection facial landmark prediction accuracy models

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Relationship between clinical belonging,professional identity,and nursing information ability among nursing interns:Model construction

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World Journal of Clinical Cases 2024年第13期12卷 2210-2217页

作者： Gai Zhang Shao-Juan Huang Shu-Fang Li Department of Nursing Foshan Hospital of Traditional Chinese MedicineFoshan 528000Guangdong ProvinceChina

BACKGROUND Clinical belonging refers to the feeling that clinical medical staff feel recognized and accepted by others or groups.The level of clinical belonging of nursing interns affects students’learning motivation and confidence,which in turn affects their clinical practice behavior.AIM To explore the effects of professional identity and nursing information ability on clinical belonging among nursing interns and establish a relationship model for these factors.METHODS The researchers used the convenience sampling method to select 682 nursing interns from China.The survey was conducted using a general information questionnaire,clinical sense of belonging scale,nursing information ability self-assessment scale,and a nursing student professional identity questionnaire.The mediating effect of nursing information ability between their professional identity and clinical sense of belonging was analyzed using SPSS 21.0 and the path analysis in structural equation modeling.RESULTS The total scores of clinical belonging,professional identity,and nursing information ability of nursing interns were(104.29±13.11)points,(57.89±7.16)points,and(70.29±6.20)points,respectively.Nursing information ability had a direct effect on the clinical sense of belonging(effect value=0.46,P<0.05).Occupational identity had a direct effect(effect value=0.52,P<0.05)and an indirect effect(effect value=0.21,P<0.05)on clinical belonging.CONCLUSION Nursing administrators in nursing colleges and hospitals should take effective measures to improve the professional identity and nursing information ability of nursing interns,as well as the clinical sense of belonging among nursing interns.

关键词： Belongingness Nursing Education Undergraduate Information literacy models

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Efficacy of Ganshuang granules(肝爽颗粒)on non-alcoholic fatty liver and underlying mechanism:a network pharmacology and experimental verification

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Journal of Traditional Chinese Medicine 2024年第1期44卷 122-130页

作者： ZHI Guoguo SHAO Bingjie ZHENG Tianyan JI Shaoxiu LI Jingwei DANG Yanni LIU Feng WANG Dong School of Basic Medicine Chengdu University of Traditional Chinese MedicineChengdu 611137China Shanxi Buchang Pharmaceutical Company LimitedXi’an 712000China

OBJECTIVE:To investigate the potential pharmacological mechanisms of Ganshuang granules(肝爽颗粒,GSG)in treating non-alcoholic fatty liver(NAFLD).METHODS:All the active components and targets of GSG were retrieved from the Traditional Chinese Medicine Systems Pharmacology Database and Analysis Platform.Protein-Protein interaction network,Kyoto Encyclopedia of Genes and Genomes and Gene Ontology function annotation of common targets were analyzed to predict the mechanisms of action of GSG in the treatment of NAFLD.Then,the mouse models of NAFLD were constructed in a diet-induced manner and treated with GSG.The levels of interleukin 6(IL-6),tumor necrosis factor-alpha(TNF-α)and phosphatidylinositol 3-kinase/protein kinase B(PI3K/AKT)pathway-related proteins in the liver of mice in each group were measured by enzyme linked immunosorbent assay and Western blot,respectively.RESULTS:Network pharmacology revealed a total of 159 potential targets of GSG for the treatment of NAFLD.Functional enrichment analysis indicated that the PI3K/AKT signaling pathway may be involved during GSG treatment of NAFLD.Further experiments showed that the significantly decreased alanine aminotransferase,aspartate aminotransferase,alkaline phosphatase,total cholesterol,triglyceride and low-density lipoprotein cholesterol levels in NAFLD model mice serum after GSG treatment,as well as the expression levels of IL-6 and TNF-αin the liver.Furthermore,drug intervention increased the protein expression levels of phosphorylated-PI3K(P-PI3K)and P-AKT in the liver of the model group mice,and decreased the protein expression level of sterol regulatory element-binding protein 1.CONCLUSION:We found that GSG is effective in treating NAFLD and the potential therapeutic targets may be involved in PI3K/AKT signaling pathway.

关键词： fatty liver alcoholic network pharmacology models animal phosphatidylinositol 3-kinase proto-oncogene proteins c-akt signal transduction Ganshuang granules

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Controlled Environment Ecosystem:A plant growth system to combat climate change through soilless culture

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Crop Design 2024年第1期3卷 1-10页

作者： Avinash Sharma Mainu Hazarika Punabati Heisnam Himanshu Pandey V.S.Devadas Mannu Wangsu Faculty of Agricultural Sciences Arunachal University of StudiesNamsaiArunachal Pradesh792103India College of Agriculture Central Agricultural UniversityIroisembaManipur795004India PG Department of Agriculture Khalsa CollegeAmritsarPunjab143002India Vanavarayar Institute of Agriculture PollachiTamil Nadu642103India Department of Agricultural Engineering North Eastern Regional Institute of Science and TechnologyNirjuliArunachal Pradesh791109India

The variations in climatic factors can lead to morphological changes like male sterility,self-incompatibility,embryo abortions,poor seed setting,low nutrient content,growth retardation,yield loss and even crop failure of agricultural or horticultural crops under open land ecosystem.The traditional agricultural systems involve using a large quantity of water on a large arable land,along with a lot of agro chemicals,which can lead to leaching of nutrients and chemical residues into the soil and water bodies,insect competition,weed emergence,or soil erosion.The controlled environment plant growth chamber reserves 80%land use,90%water use and runs off or translocates nutrients more efficiently than traditional agriculture.The controlled environment plant growth chamber utilizes standard nutrient diffusion for plant growth and regulates stable nutrient use efficiency,water use efficiency,photosynthetic assimilation product,metabolic use efficiency,climatic factors,greenhouse gases emission,carbon sequestration,carbon foot print with the mechanistic model with machine learning examines critical or non critical levels,dynamics and influences of water,climate and nutrient in controlled environment system.The controlled environment plant growth chamber enables production of outstanding physical and chemical quality enriched plants.The controlled environment witnesses the combat against climate change and the restoration or conservation of natural resources,as well as the generation of research,employment,and industrial development.More comparative investigations are required to understand and justify climate combating with major plants in controlled environment ecosystem and natural environment ecosystem with or without soil.

关键词： Crops Microgreens Controlled environment Dynamics models Climate

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A Survey on Deep Learning-Based 2D Human Pose Estimation models

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Computers, Materials & Continua 2023年第8期76卷 2385-2400页

作者： Sani Salisu A.S.A.Mohamed M.H.Jaafar Ainun S.B.Pauzi Hussain A.Younis School of Computer Science Universiti Sains MalaysiaPenang11800Malaysia Department of Information Technology Faculty of ComputingFederal University DutseJigawa720211Nigeria School of Industrial Technology Universiti Sains MalaysiaPenang11800Malaysia College of Education for Women University of BasrahBasrah61004Iraqi

In this article,a comprehensive survey of deep learning-based(DLbased)human pose estimation(HPE)that can help researchers in the domain of computer vision is presented.HPE is among the fastest-growing research domains of computer vision and is used in solving several problems for human endeavours.After the detailed introduction,three different human body modes followed by the main stages of HPE and two pipelines of twodimensional(2D)HPE are presented.The details of the four components of HPE are also presented.The keypoints output format of two popular 2D HPE datasets and the most cited DL-based HPE articles from the year of breakthrough are both shown in tabular form.This study intends to highlight the limitations of published reviews and surveys respecting presenting a systematic review of the current DL-based solution to the 2D HPE model.Furthermore,a detailed and meaningful survey that will guide new and existing researchers on DL-based 2D HPE models is achieved.Finally,some future research directions in the field of HPE,such as limited data on disabled persons and multi-training DL-based models,are revealed to encourage researchers and promote the growth of HPE research.

关键词： Human pose estimation deep learning 2D dataset models body parts

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Theoretical and Experimental Sets of Choice Anode/Cathode Architectonics for High-Performance Full-Scale LIB Built-up models

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Nano-Micro Letters 2019年第4期11卷 485-507页

作者： H.Khalifa S.A.El-Safty A.Reda M.A.Shenashen M.M.Selim A.Elmarakbi H.A.Metawa National Institute for Materials Science(NIMS) Sengen 1-2-1TsukubaIbaraki 305-0047Japan Department of Mathematics Al-Aflaj College of Science and Human StudiesPrince Sattam Bin Abdulaziz UniversityAl-Aflaj 710-11912Saudi Arabia Department of Mechanical and Construction Engineering Faculty of Engineering and EnvironmentNorthumbria UniversityNewcastle upon Tyne NE18STUK Department of Physics Faculty of ScienceDamanhur UniversityDamanhurEgypt

To control the power hierarchy design of lithium-ion battery(LIB)builtup sets for electric vehicles(EVs),we offer intensive theoretical and experimental sets of choice anode/cathode architectonics that can be modulated in full-scale LIB built-up models.As primary structural tectonics,heterogeneous composite superstructures of full-cell-LIB(anode//cathode)electrodes were designed in closely packed flower agave rosettes TiO2@C(FRTO@C anode)and vertical-star-tower LiFePO4@C(VST@C cathode)building blocks to regulate the electron/ion movement in the three-dimensional axes and orientation pathways.The superpower hierarchy surfaces and multi-directional orientation components may create isosurface potential electrodes with mobile electron movements,in-to-out interplay electron dominances,and electron/charge cloud distributions.This study is the first to evaluate the hotkeys of choice anode/cathode architectonics to assemble different LIB-electrode platforms with high-mobility electron/ion flows and high-performance capacity functionalities.Density functional theory calculation revealed that the FRTO@C anode and VST-(i)@C cathode architectonics are a superior choice for the configuration of full-scale LIB built-up models.The integrated FRTO@C//VST-(i)@C full-scale LIB retains a huge discharge capacity(~94.2%),an average Coulombic efficiency of 99.85%after 2000 cycles at 1 C,and a high energy density of 127 Wh kg?1,thereby satisfying scale-up commercial EV requirements.

关键词： Lithium-ion battery 3D super-scalable hierarchal anode/cathode models Density functional theory Anode/cathode architectonics Electric vehicle applications

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models of vacuum energy interacting with cold dark matter:Constraints and comparison

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Science China(Physics,Mechanics & Astronomy) 2019年第12期62卷 19-27页

作者： Hai-Li Li Lu Feng Jing-Fei Zhang Xin Zhang Department of Physics College of SciencesNortheastern UniversityShenyang 110819China College of Physical Science and Technology Shenyang Normal UniversityShenyang 110034China Ministry of Education Key Laboratory of Data Analytics and Optimization for Smart Industry Northeastern UniversityShenyang 110819China Center for High Energy Physics Peking UniversityBeijing 100080China

In this paper, we investigate the observational constraints on the scenario of vacuum energy interacting with cold dark matter.We consider eight typical interaction forms in such an interacting vacuum energy scenario. The observational data used in this work to constrain these models include the JLA sample of type Ia supernovae observation, the Planck 2015 distance priors data of cosmic microwave background anisotropies observation, the baryon acoustic oscillations data, and the Hubble constant direct measurement. We find that the current observational data almost equally favor these interacting vacuum energy models. We also find that for all these models of vacuum energy interacting with cold dark matter the case of no interaction is actually well consistent with the current observational data within 1σ range.

关键词： interacting dark energy interacting vacuum energy models cosmological observations cosmological constraints modelcomparison

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The Rapid Assessment and Early Warning models for COVID-19

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Virologica Sinica 2020年第3期35卷 272-279页

作者： Zhihua Bai Yue Gong Xiaodong Tian Ying Cao Wenjun Liu Jing Li CAS Key Laboratory of Pathogenic Microbiology and Immunology Institute of MicrobiologyChinese Academy of SciencesBeijing 100101China University of Chinese Academy of Sciences Beijing 100049China National Science Library Chinese Academy of SciencesBeijing 100190China Institute of Microbiology Center for Biosafety MegaScienceChinese Academy of SciencesBeijing 100101China

Human beings have experienced a serious public health event as the new pneumonia(COVID-19), caused by the severe acute respiratory syndrome coronavirus has killed more than 3000 people in China, most of them elderly or people with underlying chronic diseases or immunosuppressed states. Rapid assessment and early warning are essential for outbreak analysis in response to serious public health events. This paper reviews the current model analysis methods and conclusions from both micro and macro perspectives. The establishment of a comprehensive assessment model, and the use of model analysis prediction, is very efficient for the early warning of infectious diseases. This would significantly improve global surveillance capacity, particularly in developing regions, and improve basic training in infectious diseases and molecular epidemiology.

关键词： COVID-19 SARS-CoV-2 models Rapid assessment Early warning

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Electroencephalography studies of hypoxic ischemia in fetal and neonatal animal models

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Neural Regeneration Research 2020年第5期15卷 828-837页

作者： Hamid Abbasi Charles P.Unsworth Department of Engineering Science the University of Auckland

Alongside clinical achievements,experiments conducted on animal models (including primate or non-primate) have been effective in the understanding of various pathophysiological aspects of perinatal hypoxic/ ischemic encephalopathy (HIE).Due to the reasonably fair degree of flexibility with experiments,most of the research around HIE in the literature has been largely concerned with the neurodevelopmental outcome or how the frequency and duration of HI seizures could relate to the severity of perinatal brain injury,following HI insult.This survey concentrates on how EEG experimental studies using asphyxiated animal models (in rodents,piglets,sheep and non-human primate monkeys) provide a unique opportunity to examine from the exact time of HI event to help gain insights into HIE where human studies become difficult.

关键词： animal models automatic detection clinical EEG fetal HIE hypoxic-ischemic encephalopathy neonatal non-human primates review seizure

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