Long QT syndrome refers to a characteristic abnormality of the electrocardiogram and it is associated with a form of ventricular tachycardia known as torsade-de-pointes and sudden arrhythmic death. It can occur as part of a hereditary syndrome or can be acquired usually because of drug administration. Here we review recent genetic, molecular and cellular discoveries and outline how they have furthered our understanding of this disease. Specifically we focus on compound mutations, genome wide association studies of QT interval, modifier genes and the therapeutic implications of this recent work.
Background: Hypertension or elevated blood pressure (BP) is a worldwide clinical challenge and the leading primary risk factor for kidney dysfunctions, heart failure, and cerebrovascular disease. The kidney is a central regulator of BP by maintaining sodium-water balance. Multiple genome-wide association studies revealed that BP is a heritable quantitative trait, modulated by several genetic, epigenetic, and environmental factors.
Aim: Anorectal diseases, often requiring surgical intervention and careful post-operative wound management, pose substantial challenges in healthcare. This study presents a novel application of artificial intelligence, specifically machine learning, aimed at improving the classification and analysis of post-surgical wound images. By doing so, it seeks to enhance patient outcomes through personalized and optimized wound care strategies.
We recently reviewed the article titled "Outcomes of Bolus Dose Furosemide Versus Continuous Infusion in Patients With Acute Decompensated Left Ventricular Failure and Atrial Fibrillation" published in Clinical Cardiology by [khan et al.] (1) with great interest. This study addresses a crucial area of clinical practice, and we appreciate the authors' efforts in exploring this topic.
Central Laboratory of The Lishui Hospital of Wenzhou Medical University, The First Affiliated Hospital of Lishui University, Lishui People's Hospital, Lishui, Zhejiang, China.
Introduction: Spinal cord injury (SCI) is a severe neurological disease characterized by significant motor, sensory, and autonomic dysfunctions. SCI is a major global disability cause, often resulting in long-term neurological impairments due to the impeded regeneration and remyelination of axons. A SCI interferes with communication between the brain and the spinal cord networks that control neurological functions.
Introduction: Functional magnetic resonance imaging (fMRI) data is highly complex and high-dimensional, capturing signals from regions of interest (ROIs) with intricate correlations. Analyzing such data is particularly challenging, especially in resting-state fMRI, where patterns are less identifiable without task-specific contexts. Nonetheless, interconnections among ROIs provide essential insights into brain activity and exhibit unique characteristics across groups.
