limitations and challenges in modeling diseases involving spinal motor neuron degeneration in vitro

limitations and challenges in modeling diseases involving spinal motor neuron degeneration in vitro

;Monica Bucchia;Samantha J. Merwin;Diane B. Re;Shingo Kariya
macromolecular bioscience 2018 Vol. 12 pp. -
156
bucchia2018frontierslimitations

Abstract

Pathogenic conditions involving degeneration of spinal motor neurons (MNs), such as amyotrophic lateral sclerosis, sarcopenia, and spinal cord injury, mostly occur in individuals whose spinal MNs are fully mature. There is currently no effective treatment to prevent death or promote axonal regeneration of the spinal MNs affected in these patients. To increase our understanding and find a cure for such conditions, easily controllable and monitorable cell culture models allow for a better dissection of certain molecular and cellular events that cannot be teased apart in whole organism models. To date, various types of spinal MN cultures have been described. Yet these models are all based on the use of immature neurons or neurons uncharacterized for their degree of maturity after being isolated and cultured. Additionally, studying only MNs cannot give a comprehensive and complete view of the neurodegenerative processes usually involving other cell types. To date, there is no confirmed in vitro model faithfully emulating disease or injury of the mature spinal MNs. In this review, we summarize the different limitations of currently available culture models, and discuss the challenges that have to be overcome for developing more reliable and translational platforms for the in vitro study of spinal MN degeneration.

Citation

ID: 246245
Ref Key: bucchia2018frontierslimitations
Use this key to autocite in SciMatic or Thesis Manager

References

Blockchain Verification

Account:
NFT Contract Address:
0x95644003c57E6F55A65596E3D9Eac6813e3566dA
Article ID:
246245
Unique Identifier:
10.3389/fncel.2018.00061
Network:
Scimatic Chain (ID: 481)
Loading...
Blockchain Readiness Checklist
Authors
Abstract
Journal Name
Year
Title
5/5
Creates 1,000,000 NFT tokens for this article
Token Features:
  • ERC-1155 Standard NFT
  • 1 Million Supply per Article
  • Transferable via MetaMask
  • Permanent Blockchain Record
Blockchain QR Code
Scan with Saymatik Web3.0 Wallet

Saymatik Web3.0 Wallet