Faculty Opinions recommendation of Data-driven modeling of sleep EEG and EOG reveals characteristics indicative of pre-Parkinson's and Parkinson's disease.

2014 ◽  
Author(s):  
Mario Manto ◽  
Florian Bodranghien
Keyword(s):  
Parkinson’S Disease ◽  
Parkinson's Disease ◽  
Sleep Eeg ◽  
Data Driven ◽  
Data Driven Modeling

P1046: Data-driven modeling of sleep EEG and EOG reveals stages indicative of pre-Parkinson and Parkinson’s disease

2014 ◽  
Vol 125 ◽  
pp. S327
Author(s):  
J.A.E. Christensen ◽  
H. Koch ◽  
R. Frandsen ◽  
L. Arvastson ◽  
S. Christensen ◽  
...  
Keyword(s):  
Parkinson’S Disease ◽  
Parkinson's Disease ◽  
Sleep Eeg ◽  
Data Driven ◽  
Data Driven Modeling

Data-driven modeling of sleep EEG and EOG reveals characteristics indicative of pre-Parkinson's and Parkinson's disease

2014 ◽  
Vol 235 ◽  
pp. 262-276 ◽  
Author(s):  
Julie A.E. Christensen ◽  
Marielle Zoetmulder ◽  
Henriette Koch ◽  
Rune Frandsen ◽  
Lars Arvastson ◽  
...  
Keyword(s):  
Parkinson’S Disease ◽  
Parkinson's Disease ◽  
Sleep Eeg ◽  
Data Driven ◽  
Data Driven Modeling

Motor patterns in Parkinson's disease: A data-driven approach

2009 ◽  
Vol 24 (7) ◽  
pp. 1042-1047 ◽  
Author(s):  
Stephanie M. van Rooden ◽  
Martine Visser ◽  
Dagmar Verbaan ◽  
Johan Marinus ◽  
Jacobus J. van Hilten
Keyword(s):  
Parkinson’S Disease ◽  
Parkinson's Disease ◽  
Data Driven ◽  
Motor Patterns ◽  
Data Driven Approach

Reply to “Studying reproducibility of data-driven Parkinson's disease subtypes”

2019 ◽  
Vol 66 ◽  
pp. 245-246
Author(s):  
Tiago A. Mestre ◽  
Shirley Eberly ◽  
Caroline Tanner ◽  
David Grimes ◽  
Anthony E. Lang ◽  
...  
Keyword(s):  
Parkinson’S Disease ◽  
Parkinson's Disease ◽  
Data Driven ◽  
Disease Subtypes

scholarly journals Data-driven evolution of neurosurgical gene therapy delivery in Parkinson’s disease

2020 ◽  
Vol 91 (11) ◽  
pp. 1210-1218 ◽  
Author(s):  
R Mark Richardson ◽  
Krystof S Bankiewicz ◽  
Chadwick W Christine ◽  
Amber D Van Laar ◽  
Robert E Gross ◽  
...  
Keyword(s):  
Parkinson’S Disease ◽  
Gene Therapy ◽  
Parkinson's Disease ◽  
Viral Vector ◽  
Data Driven ◽  
Surgical Approaches ◽  
Acid Decarboxylase ◽  
Projection Neurons ◽  
Virus Serotype ◽  
Vector Delivery

Loss of nigrostriatal dopaminergic projection neurons is a key pathology in Parkinson’s disease, leading to abnormal function of basal ganglia motor circuits and the accompanying characteristic motor features. A number of intraparenchymally delivered gene therapies designed to modify underlying disease and/or improve clinical symptoms have shown promise in preclinical studies and subsequently were evaluated in clinical trials. Here we review the challenges with surgical delivery of gene therapy vectors that limited therapeutic outcomes in these trials, particularly the lack of real-time monitoring of vector administration. These challenges have recently been addressed during the evolution of novel techniques for vector delivery that include the use of intraoperative MRI. The preclinical development of these techniques are described in relation to recent clinical translation in an adeno-associated virus serotype 2-mediated human aromatic L-amino acid decarboxylase gene therapy development programme. This new paradigm allows visualisation of the accuracy and adequacy of viral vector delivery within target structures, enabling intertrial modifications in surgical approaches, cannula design, vector volumes and dosing. The rapid, data-driven evolution of these procedures is unique and has led to improved vector delivery.

The spectrum of cognitive disorders in Parkinson's disease: A data-driven approach

2013 ◽  
Vol 28 (2) ◽  
pp. 183-189 ◽  
Author(s):  
Kathy Dujardin ◽  
Albert F.G. Leentjens ◽  
Carole Langlois ◽  
Anja J.H. Moonen ◽  
Annelien A. Duits ◽  
...  
Keyword(s):  
Parkinson’S Disease ◽  
Parkinson's Disease ◽  
Cognitive Disorders ◽  
Data Driven ◽  
Data Driven Approach

scholarly journals The Combination of Tradition and Future: Data-Driven Natural-Product-Based Treatments for Parkinson’s Disease

2021 ◽  
Vol 2021 ◽  
pp. 1-8
Author(s):  
Zhijun Miao ◽  
Jinwei Bai ◽  
Li Shen ◽  
Rajeev K. Singla
Keyword(s):  
Parkinson’S Disease ◽  
Parkinson's Disease ◽  
Natural Products ◽  
Natural Product ◽  
Neurodegenerative Disorder ◽  
Data Driven ◽  
Natural Product Discovery ◽  
Challenges And Opportunities ◽  
Future Data ◽  
Personalized Diagnosis

Parkinson’s disease (PD) is a neurodegenerative disorder in elderly people. The personalized diagnosis and treatment remain challenges all over the world. In recent years, natural products are becoming potential therapies for many complex diseases due to their stability and low drug resistance. With the development of informatics technologies, data-driven natural product discovery and healthcare is becoming reality. For PD, however, the relevant research and tools for natural products are quite limited. Here in this review, we summarize current available databases, tools, and models for general natural product discovery and synthesis. These useful resources could be used and integrated for future PD-specific natural product investigations. At the same time, the challenges and opportunities for future natural-product-based PD care will also be discussed.

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