Parkinson's Disease

Subthalamic spatio-spectral-connectivity of psychiatric symptoms in Parkinson's disease.

Psychiatric symptoms in Parkinson's disease (PD) are highly prevalent and challenging to treat. This study maps oscillatory neural activity to diverse psychiatric symptoms in PD, using resting-state subthalamic nucleus (STN) local field potentials (LFPs) and frontal EEG in 55 PD patients undergoing deep brain stimulation (DBS). We tested whether 1) distinct psychiatric symptoms are associated with...

A wearable patch for continuous levodopa monitoring in sweat: Towards exertion and power-free pharmacodynamic assessment in Parkinson's disease.

Precision management of Parkinson's disease (PD) requires frequent levodopa (L-dopa) dose adjustments, yet current monitoring relies on subjective symptom reporting and infrequent blood testing. Here, we present a soft, fingertip-mounted wearable platform for continuous, noninvasive L-dopa monitoring. By combining osmotically harvested passive sweat with soft hydrogels, a potentiometric sensing st...

Machine Learning Prediction of Hoehn and Yahr Scores at 5-Years Post-123I-Ioflupane SPECT Imaging in a Real-World Parkinson's Disease Dataset.

BACKGROUND: Parkinson's disease (PD) progression is highly heterogeneous, complicating clinical management and prognostication. While machine learning...

Research advances in key genes and regulatory mechanisms of posttranslational modifications in Parkinson's disease.

BACKGROUND: The genesis of Parkinson's disease (PD), a common central neurodegenerative disorder, involves dysregulation of protein posttranslational ...

Large language models as a screening tool for the qualification of patients with Parkinson's disease for device-aided therapies.

Motor complications become increasingly prominent as Parkinson's disease (PD) progresses. Although device-aided therapies (DAT) improve symptoms contr...

Diagnosis of Parkinson's Disease Based on Voice and Speech Using Machine Learning and Deep Learning: A Systematic Umbrella Review.

OBJECTIVES: Early diagnosis of Parkinson's disease (PD) is complicated. Speech impairment, as an early symptom of PD, offers a noninvasive, scalable b...

Gut Microbiome in Depression with and without REM Sleep Behavior Disorder.

Major depressive disorder (MDD) is a risk factor for neurodegeneration, yet its heterogeneity makes identifying at-risk subtype challenging. Notably, ...

Crowdsourcing and machine learning contests in Parkinson's disease research - when do they work?

ObjectiveTo review the application of crowdsourcing and machine learning contests in Parkinson's disease (PD) research, identify best practices for su...

A highly efficient detection model for early-stage Parkinson's disease using non-contact, multi-modality measurement and artificial intelligence.

Early diagnosis of Parkinson's disease (PD) is challenging due to the difficulty in identification of various early motor signs. We aimed to develop a...

Explainable machine learning for automated robotic surgical skill assessment using rich kinematic features.

Robotic-assisted surgery (RAS) extends minimally invasive surgery by restoring dexterity, tremor filtration, and ergonomic console control compared wi...

Brain organoids in Parkinson's disease drug development: Human-specific models for translational discovery.

Parkinson's disease (PD) poses a major unmet therapeutic challenge, with most drug candidates failing in clinical translation despite promising animal...

Context-agnostic machine learning for Parkinson's disease motor symptom detection using wearable sensors.

BACKGROUND: Parkinson's disease is a rapidly growing neurodegenerative disorder with various motor and non-motor symptoms, affecting millions of peopl...

α-Synuclein Seeds Amplification Assays for Parkinson's Disease and Related Synucleinopathies.

Parkinson's disease (PD) is a progressive neurodegenerative disorder characterized by the pathological misfolding and aggregation of α-synuclein (α-sy...

Artificial intelligence in deep brain stimulation for movement disorders: a systematic review and technology readiness assessment.

Artificial intelligence (AI) is increasingly explored across deep brain stimulation (DBS) for movement disorders, yet whether current systems are appr...

Digital profiling of dysarthria in late- and early-onset Parkinson's disease.

BackgroundDigital speech analysis affords robust markers of Parkinson's disease (PD). However, most studies target late-onset PD (LOPD), neglecting ea...

Ketogenic β-hydroxybutyrate-regulated β-hydroxybutyrylation of HSPE1 alleviates neuronal apoptosis in MPTP/MPP+ induced Parkinson's disease models.

Lysine β-hydroxybutyrylation (Kbhb) is an emerging post-translational modification regulated by β-hydroxybutyrate (BHB), a key metabolic intermediate ...

Cognitive structure and progression in Parkinson's disease: insights from a tablet-based assessment.

Cognitive impairment is an important constraint for PwPD with Parkinson's disease (PwPD). Digital assessments potentially provide more accessible meas...

Hydrogen Vacancies Heal Pb-Dimer Deep Traps and Suppress Coupled Ionic-Electronic Losses in Hybrid Perovskites.

Organic-inorganic hybrid perovskites combine strong optical absorption, long carrier lifetimes, and unusual defect tolerance, yet these favorable prop...

Metabolomic signatures for diagnosis and clinical severity in Parkinson's disease.

BACKGROUND: Parkinson's disease (PD) remains challenging to diagnose at early stages owing to subtle and heterogeneous clinical manifestations and the...

Spatiotemporal deep learning for early detection of isolated REM sleep behavior disorder and Parkinson's disease using functional MRI data.

This study aimed to develop and evaluate a spatiotemporal deep-neural-network (stDNN) using resting-state fMRI (rs-fMRI) data to identify brain biomar...