Examining Brain Structures and Cognitive Functions in Patients with Recovered COVID-19 Infection: A Multicenter Study Using 7T MRI.

Importance: Emerging evidence suggests that severe acute respiratory syndrome, COVID-19, negatively impacts brain health, with clinical magnetic resonance imaging (MRI) showing a wide range of neurologic manifestations but no consistent pattern. Compared with 3 Tesla (3T) MRI, 7 Tesla (7T) MRI can detect more subtle injuries, including hippocampal subfield volume differences and additional standard biomarkers such as white matter lesions. 7T MRI could help with the interpretation of the various persistent post-acute and distal onset sequelae of COVID-19 infection.

ALS-associated FUS mutation reshapes the RNA and protein composition of stress granules.

Stress granules (SG) are part of a cellular protection mechanism where untranslated messenger RNAs and RNA-binding proteins are stored upon conditions of cellular stress. Compositional variations due to qualitative or quantitative protein changes can disrupt their functionality and alter their structure. This is the case of different forms of amyotrophic lateral sclerosis (ALS) where a causative link has been proposed between the cytoplasmic de-localization of mutant proteins, such as FUS (Fused in Sarcoma), and the formation of cytotoxic inclusions.

Cross-modality image translation of 3 Tesla Magnetic Resonance Imaging to 7 Tesla using Generative Adversarial Networks.

The rapid advancements in magnetic resonance imaging (MRI) technology have precipitated a new paradigm wherein cross-modality data translation across diverse imaging platforms, field strengths, and different sites is increasingly challenging. This issue is particularly accentuated when transitioning from 3 Tesla (3T) to 7 Tesla (7T) MRI systems. This study proposes a novel solution to these challenges using generative adversarial networks (GANs)-specifically, the CycleGAN architecture-to create synthetic 7T images from 3T data.

A (sub)field guide to quality control in hippocampal subfield segmentation on high-resolution T-weighted MRI.

Inquiries into properties of brain structure and function have progressed due to developments in magnetic resonance imaging (MRI). To sustain progress in investigating and quantifying neuroanatomical details in vivo, the reliability and validity of brain measurements are paramount. Quality control (QC) is a set of procedures for mitigating errors and ensuring the validity and reliability of brain measurements.