Dataset Information

Effect of Regulatory Network of Exosomes and microRNAs on Neurodegenerative Diseases.

ABSTRACT: Objective:A comprehensive review of the network regulation of exosomes and microRNAs (miRNAs) in neurodegenerative diseases was done, centering on the mechanism of the formation of exosomes and miRNAs and the sorting mechanism of exosomal miRNAs, with the aim to provide a theoretical basis in the search of biomarkers and the treatment of neurodegenerative diseases. Data Sources:The comprehensive search used online literature databases including NCBI PubMed, Web of Science, Google Scholar, and Baidu Scholar. Study Selection:The study selection was based on the following keywords: exosomes, miRNAs, central nervous system (CNS), and neurodegenerative diseases. The time limit for literature retrieval was from the year 2000 to 2018, with language restriction in English. Relevant articles were carefully reviewed, with no exclusions applied to study design and publication type. Results:Exosomes are the smallest nanoscale membranous microvesicles secreted by cells and contain important miRNAs, among other rich contents. In the CNS, exosomes can transport amyloid ?-protein, ?-synuclein, Huntington-associated protein 1, and superoxide dismutase I to other cells. These events relieve the abnormal accumulation of proteins and aggravating neurological diseases. In some neurodegenerative diseases including Alzheimer's disease, Parkinson's disease, Huntington's disease, and amyotrophic lateral sclerosis, miRNAs are pathologically altered as an inexorable course, suggesting that miRNAs may contribute neurodegeneration. Exosomes and miRNAs form a network to regulate the homeostasis of the CNS, both synergistically and individually. Conclusion:The network of exosomes and miRNAs that regulates CNS homeostasis is a promising biomarker for the diagnosis and treatment of neurodegenerative diseases.

SUBMITTER: Li D

PROVIDER: S-EPMC6144844 | biostudies-literature | 2018 Sep

REPOSITORIES: biostudies-literature

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Effect of Regulatory Network of Exosomes and microRNAs on Neurodegenerative Diseases.

Li Dong D Li You-Ping YP Li Yun-Xiang YX Zhu Xiao-Hua XH Du Xiao-Gang XG Zhou Min M Li Wen-Bin WB Deng Hong-Yan HY

Chinese medical journal 20180901 18

<h4>Objective</h4>A comprehensive review of the network regulation of exosomes and microRNAs (miRNAs) in neurodegenerative diseases was done, centering on the mechanism of the formation of exosomes and miRNAs and the sorting mechanism of exosomal miRNAs, with the aim to provide a theoretical basis in the search of biomarkers and the treatment of neurodegenerative diseases.<h4>Data sources</h4>The comprehensive search used online literature databases including NCBI PubMed, Web of Science, Google ...[more]

PMID: 30203797

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Project description:Neurodegenerative diseases (NDs) such as Alzheimer's disease (AD), Parkinson's disease (PD), multiple sclerosis (MS), amyotrophic lateral sclerosis (ALS), and dementia pose one of the greatest health challenges this century. Although these NDs have been looked at as single entities, the underlying molecular mechanisms have never been collectively visualized to date. With the advent of high-throughput genomic and proteomic technologies, we now have the opportunity to visualize these diseases in a whole new perspective, which will provide a clear understanding of the primary and secondary events vital in achieving the final resolution of these diseases guiding us to new treatment strategies to possibly treat these diseases together. We created a knowledge base of all microRNAs known to be differentially expressed in various body fluids of ND patients. We then used several bioinformatic methods to understand the functional intersections and differences between AD, PD, ALS, and MS. These results provide a unique panoramic view of possible functional intersections between AD, PD, MS, and ALS at the level of microRNA and their cognate genes and pathways, along with the entities that unify and separate them. While the microRNA signatures were apparent for each ND, the unique observation in our study was that hsa-miR-30b-5p overlapped between all four NDS, and has significant functional roles described across NDs. Furthermore, our results also show the evidence of functional convergence of miRNAs which was associated with the regulation of their cognate genes represented in pathways that included fatty acid synthesis and metabolism, ECM receptor interactions, prion diseases, and several signaling pathways critical to neuron differentiation and survival, underpinning their relevance in NDs. Envisioning this group of NDs together has allowed us to propose new ways of utilizing circulating miRNAs as biomarkers and in visualizing diverse NDs more holistically . The critical molecular insights gained through the discovery of ND-associated miRNAs, overlapping miRNAs, and the functional convergence of microRNAs on vital pathways strongly implicated in neurodegenerative processes can prove immensely valuable in the identifying new generation of biomarkers, along with the development of miRNAs into therapeutics.

Project description:The two most generally diagnosed Neurodegenerative diseases are the Alzheimer and Parkinson diseases. So this paper presents a fully automated early screening system based on the Capsule network for the classification of these two Neurodegenerative diseases. In this study, we hypothesized that the Neurodegenerative diseases-Caps system based on the Capsule network architecture accurately performs the multiclass i.e. three class classification into either the Alzheimer class or Parkinson class or Healthy control and delivers better results in comparison other deep transfer learning models. The real motivation behind choosing the capsule network architecture is its more resilient nature towards the affine transformations as well as rotational & translational invariance, which commonly persists in the medical image datasets. Apart from this, the capsule networks overcomes the pooling layers related deficiencies from which conventional CNNs are mostly affected and unable to delivers accurate results especially in the tasks related to image classification. The various Computer aided systems based on machine learning for the classification of brain tumors and other types of cancers are already available. Whereas for the classification of Neurodegenerative diseases, the amount of research done is very limited and the number of persons suffering from this type of diseases are increasing especially in developing countries like India, China etc. So there is a need to develop an early screening system for the correct multiclass classification into Alzheimer's, Parkinson's and Normal or Healthy control cases. The Alzheimer disease and Parkinson progression (ADPP) dataset is used in this research study for the training of the proposed Neurodegenerative diseases-Caps system. This ADPP dataset is developed with the aid of both the Parkinson's Progression Markers Initiative (PPMI) and Alzheimer's disease Neuroimaging Initiative (ADNI) databases. There is no such early screening system exist yet, which can perform the accurate classification of these two Neurodegenerative diseases. For the sake of genuine comparison, other popular deep transfer learning models like VGG19, VGG16, ResNet50 and InceptionV3 are implemented and also trained over the same ADPP dataset. The proposed Neurodegenerative diseases-Caps system deliver accuracies of 97.81, 98, 96.81% for the Alzheimer, Parkinson and Healthy control or Normal cases with 70/30 (training/validation split) and performs way better as compare to the other popular Deep transfer learning models.Supplementary informationThe online version contains supplementary material available at 10.1007/s11571-022-09787-1.

Dataset Information

Effect of Regulatory Network of Exosomes and microRNAs on Neurodegenerative Diseases.

Publications

Effect of Regulatory Network of Exosomes and microRNAs on Neurodegenerative Diseases.

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