Challenges and Innovation in Neurodegenerative Diseases
A special issue of International Journal of Molecular Sciences (ISSN 1422-0067). This special issue belongs to the section "Molecular Neurobiology".
Deadline for manuscript submissions: closed (30 May 2024) | Viewed by 17566
Special Issue Editor
Interests: ion channels; electrophysiology; epithelial transport; Alzheimer’s disease; neurodegenerative diseases; new drug development
Special Issues, Collections and Topics in MDPI journals
Special Issue Information
Dear Colleagues,
The umbrella of neurodegeneration covers a group of heterogeneous diseases including Alzheimer's disease (AD), Parkinson’s disease (PD), amyotrophic lateral sclerosis (ALS), and others that account for more than 5% of the global burden of all diseases. Although considerable advances in understanding the triggers of neurodegenerative diseases had led to the development of new drugs, there are a handful of challenges that remain in the field that we must overcome to allow cures for the diseases. For example, good disease models that more faithfully recapitulate human disease are devastatingly needed. A full understanding of the involvement of protein aggregation in disease progression and the identification of disease-specific biomarkers would allow the early detection of neurodegeneration and permit reliable disease progression monitoring. The recent application of machine learning and artificial intelligence in new drug discovery and development from natural products as well as the use of stem cell therapy also brings hope to patients with neurodegenerative diseases.
This Special Issue aims to collect views on the current challenges in the field, the exciting progress in deciphering the disease pathogenesis, and the cutting-edge technologies for the early detection of neurodegeneration. The accumulation of innovative findings in these areas may pave the way for the development of therapeutic interventions for neurogenerative diseases.
Dr. King-Ho Cheung
Guest Editor
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Keywords
- neurodegenerative diseases
- pathogenesis
- biomarkers
- disease model
- natural product
- new drug discovery
- therapy
- machine learning
- stem cell therapy
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