Parkinson's Disease

Decoding the impact of visual states on adaptive deep brain stimulation feedback signals in movement disorders.

We investigated the impact of visual states on basal ganglia oscillatory biomarkers, comparing local field potentials (LFPs) dynamics between Parkinson's disease (PD) and dystonia and developing a decoding model for state identification. Simultaneous LFPs recordings from the subthalamic nucleus (STN) or globus pallidus internus (GPi), and cortex were obtained from 18 PD and 18 dystonia patients. I...

Constructing fine-grained subcortical atlases with connectional consensus graph representation learning.

Objective.The complex internal organization of subcortical structures forms the foundation of critical neural circuits that support sensorimotor processing, emotion regulation, and memory. However, their complex internal organization poses a significant challenge to reliable, fine-scale parcellation.Approach.To overcome the trade-off between anatomical specificity and cross-subject consistency, we...

Smart assistive technologies for neurodisorders: A review on AI, IoT, and wearable systems for enhanced patient care.

Neurological disorders of the brain and spinal cord affect millions of individuals worldwide and continue to rise in prevalence. Conditions such as Al...

Multi-cohort, cross-species urinary proteomics reveals signatures of LRRK2 dysfunction in Parkinson's disease.

Pathogenic mutations in Leucine-rich repeat kinase 2 (LRRK2) are the predominant genetic cause of Parkinson's disease (PD) and often increase kinase a...

Rationalizing nose-to-brain drug delivery: Machine learning-guided optimization and mechanistic elucidation of olfactory deposition for nasal sprays.

Nose-to-brain drug delivery via nasal sprays is severely limited by low olfactory deposition. In this study, we integrate machine learning with high-t...

Neuroimmune Cross-Talk and Multilevel Cascades in Fentanyl Toxicity: Interplay of Hypoxic Stress, Glial Activation, and Synaptic Dysregulation in Systems-Level Neurodegeneration.

Fentanyl, an ultra-potent synthetic opioid, has traditionally been characterized by its acute toxic effects, particularly respiratory depression. Howe...

Correlation between oral disease and neurodegenerative disorders: Role of biological proteins for the modulation of oral-brain axis and gut-brain axis.

Biological proteins play a crucial role at the intersection of oral health and neuroscience, offering promising opportunities for improved diagnosis, ...

[Wolff-Parkinson-White syndrome : Comparison of different algorithms].

BACKGROUND: Wolff-Parkinson-White (WPW) syndrome is characterised by accessory pathways that bypass the normal atrioventricular conduction system. Pre...

Evaluation of the neurotrophic peptide mixture in pathogenetic therapy of patients with Parkinson's disease.

This exploratory, single-group, open-label study investigated 17 patients with Parkinson's disease (PD) using a pre-post design. Motor and non-motor o...

Machinability and tribological optimization of origami-inspired Almond Shell-PMMA via RSM, ML, and TOPSIS.

An integrated approach combining Response Surface Methodology (RSM), Machine Learning (ML-SVM) and TOPSIS optimization method is applied in this study...

Deep eutectic hydrogel with polyphenol metal coordination and size reduced cellulose for high performance strain sensing.

Deep eutectic solvent (DES)-based hydrogels are environmentally friendly and structurally tunable, yet their applications are often limited by poor co...

Personalized supervised and unsupervised intracranial sleep decoding during deep brain stimulation.

Impaired sleep in Parkinson's Disease (PD) is a significant unmet need. Targeting sleep stage-specific neurophysiologies with adaptive Deep Brain Stim...

Machine Learning-Driven Approach to Identify Freezing of Gait in Individuals with Parkinson's Disease Using Conventional Structural MRI and Clinical Measures.

BACKGROUND AND PURPOSE: Freezing of gait (FOG) presents a significant challenge in the management of Parkinson's disease (PD). Our study explored the ...

Novel Aggressive Subtype of Multiple System Atrophy Identified by Unsupervised Machine Learning.

OBJECTIVES: Multiple system atrophy (MSA) is classified into parkinsonian (MSA-P) and cerebellar (MSA-C) phenotypes based on predominant motor feature...

Multimodal Fusion and Transfer Learning for the Detection of Degenerative Parkinsonisms with Dopamine Transporter SPECT Imaging.

Dopamine transporter (DAT) SPECT is a validated biomarker for Parkinson's disease (PD) and related degenerative parkinsonisms. Interpretation relies o...

EEG microstate features under visual feedback gain conditions exhibit high sensitivity in identifying early Parkinson's disease patients.

BACKGROUND: Early Parkinson's disease (PD) presents with subtle symptoms and lacks specific diagnostic methods. Clinical diagnosis primarily relies on...

Multimodal diagnosis of Parkinson's disease with an internet-based collaborative agent architecture of medical language models.

Parkinson's disease (PD) remains one of the most prevalent neurodegenerative disorders, where delays in diagnosis compromise therapeutic outcomes and ...

Comparative analysis of machine learning algorithms for predicting stereotactic coordinates of the centromedian nucleus.

OBJECTIVE: Deep brain stimulation (DBS) of the centromedian nucleus (CM) of the thalamus is a promising treatment for drug-resistant epilepsy, Tourett...

Multi-omics Mendelian randomization and machine learning identify candidate therapeutic targets for Alzheimer's and Parkinson's diseases.

Neurodegenerative diseases (NDDs), including Alzheimer's disease (AD) and Parkinson's disease (PD), are major public health challenges lacking effecti...

A Mixed Dual-Branch Network for Detecting Cervical Spondylotic Myelopathy and Parkinsonian Syndromes via Gait Analysis.

Cervical spondylotic myelopathy (CSM) and parkinsonian syndromes (PS) present similar motor symptoms, often causing misdiagnosis due to current clinic...