More Than the Sum of Its Parts: Disrupted Core Periphery of Multiplex Brain Networks in Multiple Sclerosis.

Disruptions to brain networks, measured using structural (sMRI), diffusion (dMRI), or functional (fMRI) MRI, have been shown in people with multiple sclerosis (PwMS), highlighting the relevance of regions in the core of the connectome but yielding mixed results depending on the studied connectivity domain. Using a multilayer network approach, we integrated these three modalities to portray an enriched representation of the brain's core-periphery organization and explore its alterations in PwMS. In this retrospective cross-sectional study, we selected PwMS and healthy controls with complete multimodal brain MRI acquisitions from 13 European centers within the MAGNIMS network.

Volume and distribution of white matter hyperintensities in rheumatoid arthritis and ulcerative colitis patients.

Brain white matter disruptions have been implicated in contributing to fatigue, brain fog and other central symptoms commonly reported in inflammatory diseases. In this study, we included 252 RA patients with 756 age and sex matched controls and 240 UC patients with 720 age and sex matched controls using the UK Biobank imaging dataset. We looked for differences in total volume of white matter hyperintensities (WMH) between patients compared to controls.

Development and evaluation of high fidelity, multidisciplinary simulation training course for high consequence infectious diseases using fluorescence visualisation.

Background: High consequence infectious diseases (HCID) include contact-transmissible viral haemorrhagic fevers and airborne-transmissible infections such as Middle Eastern Respiratory Syndrome. Assessing suspected HCID cases requires specialised infection control measures including patient isolation, personal protective equipment (PPE), and decontamination. There is need for an accessible course for NHS staff to improve confidence and competence in using HCID PPE outside specialist HCID centres.

1924-2024: First centennial of EEG.

On July 6th of 1924 Hans Berger -a German psychiatrist- first recorded electric signals from the human brainvia scalp electrodes. This date marks the beginning of Electroencephalography. In this review a representative panel of past and present Officers of the International Federation of Clinical Neurophysiology (IFCN) and of its Official Journal briefly summarizes the past, present and future of Electroencephalographic and related neurophysiological techniques' impact and the role of the IFCN in global collaboration, education, standardization, research innovation, and clinical practice.

Automatic Prediction of Molecular Properties Using Substructure Vector Embeddings within a Feature Selection Workflow.

Machine learning (ML) methods provide a pathway to accurately predict molecular properties, leveraging patterns derived from structure-property relationships within materials databases. This approach holds significant importance in drug discovery and materials design, where the rapid, efficient screening of molecules can accelerate the development of new pharmaceuticals and chemical materials for highly specialized target application. Unsupervised and self-supervised learning methods applied to graph-based or geometric models have garnered considerable traction.