Exploring the properties and potential of the neural extracellular matrix for next‐generation regenerative therapies

Publication date

2024-07-11T15:05:08Z

2024-07-11T15:05:08Z

2024-05-01

2024-06-25T09:16:45Z

Abstract

The extracellular matrix (ECM) is a dynamic and complex network of proteins and molecules that surrounds cells and tissues in the nervous system and orchestrates a myriad of biological functions. This review carefully examines the diverse interactions between cells and the ECM, as well as the transformative chemical and physical changes that the ECM undergoes during neural development, aging, and disease. These transformations play a pivotal role in shaping tissue morphogenesis and neural activity, thereby influencing the functionality of the central nervous system (CNS). In our comprehensive review, we describe the diverse behaviors of the CNS ECM in different physiological and pathological scenarios and explore the unique properties that make ECM-based strategies attractive for CNS repair and regeneration. Addressing the challenges of scalability, variability, and integration with host tissues, we review how advanced natural, synthetic, and combinatorial matrix approaches enhance biocompatibility, mechanical properties, and functional recovery. Overall, this review highlights the potential of decellularized ECM as a powerful tool for CNS modeling and regenerative purposes and sets the stage for future research in this exciting field. This article is categorized under: Implantable Materials and Surgical Technologies > Nanotechnology in Tissue Repair and Replacement Therapeutic Approaches and Drug Discovery > Nanomedicine for Neurological Disease Implantable Materials and Surgical Technologies > Nanomaterials and Implants

Document Type

Article


Published version

Language

English

Publisher

Wiley

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Reproducció del document publicat a: https://doi.org/10.1002/wnan.1962

WIREs Nanomedicine and Nanobiotechnology, 2024, vol. 16, num. 3

https://doi.org/10.1002/wnan.1962

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Rights

cc by (c) Ortega, J. Alberto et al., 2024

http://creativecommons.org/licenses/by/3.0/es/