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通过开发优化的仿生脑微环境来推进阿尔茨海默病建模,以促进药理学治疗策略的高通量筛选。

Advancing Alzheimer's Disease Modelling by Developing a Refined Biomimetic Brain Microenvironment for Facilitating High-Throughput Screening of Pharmacological Treatment Strategies.

作者信息

Mohd Murshid Nuraqila, Mohd Sahardi Nur Fatin Nabilah, Makpol Suzana

机构信息

Department of Biochemistry, Faculty of Medicine, Level 17 Preclinical Building, Universiti Kebangsaan Malaysia, Jalan Yaacob Latif, Bandar Tun Razak, Cheras, Kuala Lumpur 56000, Malaysia.

Secretariat of Research and Innovation, Faculty of Medicine, Universiti Kebangsaan Malaysia, Jalan Yaacob Latif, Bandar Tun Razak, Cheras, Kuala Lumpur 56000, Malaysia.

出版信息

Int J Mol Sci. 2024 Dec 30;26(1):241. doi: 10.3390/ijms26010241.

DOI:10.3390/ijms26010241
PMID:39796097
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC11719782/
Abstract

Alzheimer's disease (AD) poses a significant worldwide health challenge, requiring novel approaches for improved models and treatment development. This comprehensive review emphasises the systematic development and improvement of a biomimetic brain environment to address the shortcomings of existing AD models and enhance the efficiency of screening potential drug treatments. We identify drawbacks in traditional models and emphasise the necessity for more physiologically accurate systems through an in-depth analysis of current literature. This review aims to study the development of an advanced AD model that accurately replicates key AD pathophysiological aspects using cutting-edge biomaterials and microenvironment design. Incorporating biomolecular elements like Tau proteins and beta-amyloid (Aβ) plaques improve the accuracy of illustrating disease mechanisms. The expected results involve creating a solid foundation for high-throughput screening with enhanced scalability, translational significance, and the possibility of speeding up drug discovery. Thus, this review fills the gaps in AD modelling and shows potential for creating precise and efficient drug treatments for AD.

摘要

阿尔茨海默病(AD)在全球范围内构成了重大的健康挑战,需要采用新方法来改进模型并开发治疗方法。这篇全面综述强调了仿生脑环境的系统开发与改进,以弥补现有AD模型的不足,并提高筛选潜在药物治疗方法的效率。我们通过对当前文献的深入分析,找出了传统模型的缺点,并强调了建立更符合生理实际系统的必要性。本综述旨在研究一种先进的AD模型的开发,该模型利用前沿生物材料和微环境设计准确复制AD的关键病理生理方面。纳入Tau蛋白和β-淀粉样蛋白(Aβ)斑块等生物分子元素,提高了阐释疾病机制的准确性。预期结果包括为高通量筛选奠定坚实基础,提高可扩展性、转化意义,并有可能加快药物发现进程。因此,本综述填补了AD建模方面的空白,并显示出为AD创建精确有效药物治疗方法的潜力。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/9495/11719782/f689ccc7d673/ijms-26-00241-g002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/9495/11719782/c01bbd080458/ijms-26-00241-g001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/9495/11719782/f689ccc7d673/ijms-26-00241-g002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/9495/11719782/c01bbd080458/ijms-26-00241-g001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/9495/11719782/f689ccc7d673/ijms-26-00241-g002.jpg

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解决动物模型与人类阿尔茨海默病病理学之间的差异:对转化研究的影响。
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Mitochondria in Alzheimer's Disease Pathogenesis.线粒体在阿尔茨海默病发病机制中的作用
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Biomaterial-based 3D modeling of glioblastoma multiforme.基于生物材料的多形性胶质母细胞瘤3D建模。
Cancer Pathog Ther. 2023 Jan 9;1(3):177-194. doi: 10.1016/j.cpt.2023.01.002. eCollection 2023 Jul.
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