Parkinson's Disease

Biocatalytic production of a monoamine oxidase B/catechol-O-methyltransferase inhibitor from piperine by engineered P450 BM3.

The single-step biotransformation of the natural compound piperine into a known dual inhibitor of monoamine oxidase B (MAO-B) and catechol-O-methyltransferase (COMT), was achieved by cytochrome P450 BM3 wild-type and the D251G/Q307H double mutant. This compound is used for research in neurodegenerative disorders, such as Parkinson's disease, and its value in the market is ∼14,000 €/g. Currently, i...

Tailored pharmacotherapy monitoring in Parkinson's disease and Schizophrenia using a rapid and sensitive α-Synuclein assay.

BACKGROUND: While Parkinson's disease is a low dopamine neurodegenerative disorder, Schizophrenia is considered a high dopamine psychiatric disorder. Pharmacological interventions that are directed to normalize dopamine concentrations in the mid-brain for an extended duration lead to unintended consequences. Parkinson's disease patients experience psychosis, and Schizophrenia patients develop extr...

Deep Learning-Based Algorithm for Automatic Quantification of Nigrosome-1 and Parkinsonism Classification Using Susceptibility Map-Weighted MRI.

BACKGROUND AND PURPOSE: The diagnostic performance of deep learning model that simultaneously detecting and quantifying nigrosome-1 abnormality by usi...

Discovering Novel Biomarkers and Potential Therapeutic Targets of Amyotrophic Lateral Sclerosis Through Integrated Machine Learning and Gene Expression Profiling.

Amyotrophic lateral sclerosis (ALS) is a progressive neurodegenerative disorder that has multiple factors that make its molecular pathogenesis difficu...

A swin transformer and CNN fusion framework for accurate Parkinson disease classification in MRI.

Parkinson's disease ranks as the second most prevalent neurological disorder after Alzheimer's disease. Convolutional neural networks (CNNs) have been...

Therapeutic potential of enzymes, neurosteroids, and synthetic steroids in neurodegenerative disorders: A critical review.

Neurodegenerative disorders present a significant challenge to healthcare systems, mainly due to the limited availability of effective treatment optio...

Parkinson's disease detection using inceptionV3: A Deep learning approach.

Parkinson's disease (PD) is a neurodegenerative condition that progressively affects motor function and causes tremors, rigidity, and bradykinesia. De...

Machine Learning-Based Diagnostic Prediction Model Using T1-Weighted Striatal Magnetic Resonance Imaging for Early-Stage Parkinson's Disease Detection.

RATIONALE AND OBJECTIVES: Diagnosing Parkinson's disease (PD) typically relies on clinical evaluations, often detecting it in advanced stages. Recentl...

An integrated bioinformatics and machine learning approach to identifying biomarkers connecting parkinson's disease with purine metabolism-related genes.

BACKGROUND: Parkinson's disease (PD), a prevalent neurodegenerative disorder in the aging population, poses significant challenges in unraveling its p...

Voice biomarkers as prognostic indicators for Parkinson's disease using machine learning techniques.

Many people suffer from Parkinson's disease globally, a complicated neurological condition caused by the deficiency of dopamine, an organic chemical r...

Innovative diagnostic framework for shoulder instability: a narrative review on machine learning-enhanced scapular dyskinesis assessment in sports injuries.

A common shoulder problem that significantly detracts from patients' quality of life is shoulder instability (SI). Abnormal scapular positioning and m...

Explainable artificial intelligence to diagnose early Parkinson's disease via voice analysis.

Parkinson's disease (PD) is a neurodegenerative disorder affecting motor control, leading to symptoms such as tremors and stiffness. Early diagnosis i...

A quantum inspired machine learning approach for multimodal Parkinson's disease screening.

Parkinson's disease, currently the fastest-growing neurodegenerative disorder globally, has seen a 50% increase in cases within just two years. As dis...

A lightweight approach to gait abnormality detection for At Home health monitoring.

Gait abnormality detection is a growing application in machine learning based health assessment due to its potential in domains from clinical health r...

The third wheel or the game changer? How AI could team up with neurologists in Parkinson's care.

INTRODUCTION: Parkinson's disease (PD) is a progressive neurodegenerative disorder marked by diverse motor and non-motor symptoms. AI appears to be th...

A deep learning approach to remotely assessing essential tremor with handwritten images.

Essential tremor (ET) is the most prevalent movement disorder, with its incidence increasing with age, significantly impacting motor functions and qua...

Cell Wall-Based Machine Learning Models to Predict Plant Growth Using Onion Epidermis.

The plant cell wall (CW) is a physical barrier that plays a dual role in plant physiology, providing structural support for growth and development. Un...

Transforming neurodegenerative disorder care with machine learning: Strategies and applications.

Neurodegenerative diseases (NDs), characterized by progressive neuronal degeneration and manifesting in diverse forms such as memory loss and movement...

Neuro_DeFused-Net: A novel multi-scale 2DCNN architecture assisted diagnostic model for Parkinson's disease diagnosis using deep feature-level fusion of multi-site multi-modality neuroimaging data.

BACKGROUND: Neurological disorders, particularly Parkinson's Disease (PD), are serious and progressive conditions that significantly impact patients' ...

Data-Driven Modeling and Design of Sustainable High Tg Polymers.

This paper develops a machine learning methodology for the rapid and robust prediction of the glass transition temperature (Tg) for polymers for the t...