Parkinson's Disease

Predicting the Effect of Single and Multiple Mutations on Protein Structural Stability.

Predicting how a point mutation alters a protein's stability can guide pharmaceutical drug design initiatives which aim to counter the effects of serious diseases. Conducting mutagenesis studies in physical proteins can give insights about the effects of amino acid substitutions, but such wet-lab work is prohibitive due to the time as well as financial resources needed to assess the effect of even...

Semi-Supervised Discriminative Classification Robust to Sample-Outliers and Feature-Noises.

Discriminative methods commonly produce models with relatively good generalization abilities. However, this advantage is challenged in real-world applications (e.g., medical image analysis problems), in which there often exist outlier data points (sample-outliers) and noises in the predictor values (feature-noises). Methods robust to both types of these deviations are somewhat overlooked in the li...

Extraction, selection and comparison of features for an effective automated computer-aided diagnosis of Parkinson's disease based on [I]FP-CIT SPECT images.

PURPOSE: This work aimed to assess the potential of a set of features extracted from [I]FP-CIT SPECT brain images to be used in the computer-aided "in...

Investigation of the effects of carbon-based nanomaterials on A53T alpha-synuclein aggregation using a whole-cell recombinant biosensor.

The aggregation of alpha-synuclein (αS), natively unstructured presynaptic protein, is a crucial factor leading to the pathogenesis of Parkinson's dis...

Metabolism of Dopamine in Nucleus Accumbens Astrocytes Is Preserved in Aged Mice Exposed to MPTP.

Parkinson disease (PD) is prevalent in elderly individuals and is characterized by selective degeneration of igrotriatal opmine (NSDA) neurons. Intere...

A bicentric controlled study on the effects of aquatic Ai Chi in Parkinson disease.

OBJECTIVES: Various exercise strategies have been suggested to address movement deficits in order to improve motor function and quality of life for in...

Nonlinear predictive control for adaptive adjustments of deep brain stimulation parameters in basal ganglia-thalamic network.

The efficacy of deep brain stimulation (DBS) for Parkinson's disease (PD) depends in part on the post-operative programming of stimulation parameters....

Tensor Decomposition of Gait Dynamics in Parkinson's Disease.

OBJECTIVE: The study of gait in Parkinson's disease is important because it can provide insights into the complex neural system and physiological beha...

Multi-class parkinsonian disorders classification with quantitative MR markers and graph-based features using support vector machines.

BACKGROUND AND PURPOSE: In this study we attempt to automatically classify individual patients with different parkinsonian disorders, making use of pa...

A Treatment-Response Index From Wearable Sensors for Quantifying Parkinson's Disease Motor States.

The goal of this study was to develop an algorithm that automatically quantifies motor states (off, on, dyskinesia) in Parkinson's disease (PD), based...

A Diadochokinesis-based expert system considering articulatory features of plosive consonants for early detection of Parkinson's disease.

BACKGROUND AND OBJECTIVE: A new expert system is proposed to discriminate healthy people from people with Parkinson's Disease (PD) in early stages by ...

High-accuracy automatic classification of Parkinsonian tremor severity using machine learning method.

MOTIVATION: Although clinical aspirations for new technology to accurately measure and diagnose Parkinsonian tremors exist, automatic scoring of tremo...

Decoding of Human Movements Based on Deep Brain Local Field Potentials Using Ensemble Neural Networks.

Decoding neural activities related to voluntary and involuntary movements is fundamental to understanding human brain motor circuits and neuromotor di...

Pronation and supination analysis based on biomechanical signals from Parkinson's disease patients.

In this work, a fuzzy inference model to evaluate hands pronation/supination exercises during the MDS-UPDRS motor examination is proposed to analyze d...

A machine learning approach for predicting CRISPR-Cas9 cleavage efficiencies and patterns underlying its mechanism of action.

The adaptation of the CRISPR-Cas9 system as a genome editing technique has generated much excitement in recent years owing to its ability to manipulat...

A hierarchical structure for human behavior classification using STN local field potentials.

BACKGROUND: Classification of human behavior from brain signals has potential application in developing closed-loop deep brain stimulation (DBS) syste...

Dynamical analysis and development of a biologically inspired SMA caterpillar robot.

With the goal of robustly designing and fabricating a soft robot based on a caterpillar featuring shape memory alloy (SMA) actuators, analytical and n...

Towards Robot-Assisted Retinal Vein Cannulation: A Motorized Force-Sensing Microneedle Integrated with a Handheld Micromanipulator .

Retinal vein cannulation is a technically demanding surgical procedure where therapeutic agents are injected into the retinal veins to treat occlusion...

Refining diagnosis of Parkinson's disease with deep learning-based interpretation of dopamine transporter imaging.

Dopaminergic degeneration is a pathologic hallmark of Parkinson's disease (PD), which can be assessed by dopamine transporter imaging such as FP-CIT S...

NutriNet: A Deep Learning Food and Drink Image Recognition System for Dietary Assessment.

Automatic food image recognition systems are alleviating the process of food-intake estimation and dietary assessment. However, due to the nature of f...