Small-world networks propensity in spontaneous speech signals of Alzheimer's disease: visibility graph analysis.

Exploiting complex network methods to describe dynamical behavior based on speech time series can provide fundamental insights into the function of underlying dynamical processes in Alzheimer's disease (AD). This study scrutinizes the dynamic alterations in Alzheimer's speech through abstract concepts of small-world networks. The visibility graph (VG) of the time series of spontaneous speech is introduced as a quantitative method to differentiate between healthy individuals and those with Alzheimer's.

Evaluation of Drug Abuse on Brain Function using Power Spectrum Analysis of Electroencephalogram Signals in Methamphetamine, Opioid, Cannabis, and Multi-Drug Abuser Groups.

Background: The effect of different types of substances on brain function is still challenging; however, many studies have shown the functional and structural damage to the brain under influence of substance abuse.

Objective: This study aimed to quantitatively compare the effect of opioid (Op), methamphetamine (Meth), cannabis (Can), and simultaneous methamphetamine and opioid (Multi-Drug (MD)) abuse on brain function. Furthermore, the impacts of pure Op and Meth abuse were considered with simultaneous substance abuse.

An automated drug dependence detection system based on EEG.

Objective: Substance abuse causes damage to the brain structure and function. This research aim is to design an automated drug dependence detection system based on EEG signals in a Multidrug (MD) abuser.

Methods: EEG signals were recorded from participants categorized into MD-dependents (n = 10) and Healthy Control (HC) (n = 12).

A Semi-Automated Algorithm for Segmentation of the Left Atrial Appendage Landing Zone: Application in Left Atrial Appendage Occlusion Procedures.

Background: Mechanical occlusion of the Left atrial appendage (LAA) using a purpose-built device has emerged as an effective prophylactic treatment in patients with atrial fibrillation at risk of stroke and a contraindication for anticoagulation. A crucial step in procedural planning is the choice of the device size. This is currently based on the manual analysis of the "Device Landing Zone" from echocardiographic images.

Drug design by machine-trained elastic networks: predicting Ser/Thr-protein kinase inhibitors' activities.

An elastic network model (ENM) represents a molecule as a matrix of pairwise atomic interactions. Rich in coded information, ENMs are hereby proposed as a novel tool for the prediction of the activity of series of molecules, with widely different chemical structures, but a common biological activity. The new approach is developed and tested using a set of 183 inhibitors of serine/threonine-protein kinase enzyme (Plk3) which is an enzyme implicated in the regulation of cell cycle and tumorigenesis.