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Background: Long-term endurance training is associated with structural, functional, and biochemical markers of cardiac dysfunction in highly trained athletes. Many studies have focused on structural changes in the right ventricle (RV) and few have examined functional adaptation of the right ventricle. This meta-analysis aims to compare the changes in right ventricular systolic function between endurance athletes and controls before and after exercise using speckle tracking echocardiography (STE).

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Background: Memory decline is common in multiple sclerosis (MS), although pathophysiological mechanisms are not fully understood.

Objective: The objective was to investigate the relationship of changes in structural and functional neuroimaging markers to memory decline over 3-year follow-up.

Methods: Participants with MS underwent cognitive evaluation and structural, diffusion, and functional 3T magnetic resonance imaging (MRI) scans at baseline and 3-year follow-up.

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Members of the genus and lactobacilli are the most commonly used probiotics to promote human health. In this context, genome-based analyses have been demonstrated as a fast and reliable tool for identifying and characterizing health-promoting activities imputed to probiotics. This study is an extension of the Integrated Probiotic Database (IPDB) previously created on probiotics of the genus , facilitating a comprehensive understanding of the genetic characteristics that contribute to the diverse spectrum of beneficial effects of probiotics.

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Connectomes' topological organization can be quantified using graph theory. Here, we investigated brain networks in higher dimensional spaces defined by up to 10 graph theoretic nodal properties. These properties assign a score to nodes, reflecting their meaning in the network.

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A spatially constrained independent component analysis jointly informed by structural and functional network connectivity.

Netw Neurosci

December 2024

Tri-institute Translational Research in Neuroimaging and Data Science (TReNDS Center), Georgia State University, Georgia Institute of Technology, Emory University, Atlanta, GA, USA.

There are a growing number of neuroimaging studies motivating joint structural and functional brain connectivity. The brain connectivity of different modalities provides an insight into brain functional organization by leveraging complementary information, especially for brain disorders such as schizophrenia. In this paper, we propose a multimodal independent component analysis (ICA) model that utilizes information from both structural and functional brain connectivity guided by spatial maps to estimate intrinsic connectivity networks (ICNs).

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