Download full-text PDF |
Source |
|---|---|
| http://dx.doi.org/10.1159/000114585 | DOI Listing |
Publication Analysis
Top Keywords
Similar Publications
The challenge of long-term stroke outcome prediction and how statistical correlates do not imply predictive value.
Brain Commun
January 2025
Department of Neurology, Inselspital, University Hospital Bern, University of Bern, 3010 Bern, Switzerland.
Personalized prediction of stroke outcome using lesion imaging markers is still too imprecise to make a breakthrough in clinical practice. We performed a combined prediction and brain mapping study on topographic and connectomic lesion imaging data to evaluate (i) the relationship between lesion-deficit associations and their predictive value and (ii) the influence of time since stroke. In patients with first-ever ischaemic stroke, we first applied high-dimensional machine learning models on lesion topographies or structural disconnection data to model stroke severity (National Institutes of Health Stroke Scale 24 h/3 months) and functional outcome (modified Rankin Scale 3 months) in cross-validation.
View Article and Find Full Text PDFConventional MRI-Based Structural Disconnection and Morphometric Similarity Networks and Their Clinical Correlates in Multiple Sclerosis.
Neurology
February 2025
Department of Advanced Biomedical Sciences, University "Federico II," Naples, Italy.
Background And Objectives: Although multiple sclerosis (MS) can be conceptualized as a network disorder, brain network analyses typically require advanced MRI sequences not commonly acquired in clinical practice. Using conventional MRI, we assessed cross-sectional and longitudinal structural disconnection and morphometric similarity networks in people with MS (pwMS), along with their relationship with clinical disability.
Methods: In this longitudinal monocentric study, 3T structural MRI of pwMS and healthy controls (HC) was retrospectively analyzed.
Identifying multilayer network hub by graph representation learning.
Med Image Anal
January 2025
Department of Psychiatry, University of North Carolina at Chapel Hill, USA; Department of Computer Science, University of North Carolina at Chapel Hill, USA.
The recent advances in neuroimaging technology allow us to understand how the human brain is wired in vivo and how functional activity is synchronized across multiple regions. Growing evidence shows that the complexity of the functional connectivity is far beyond the widely used mono-layer network. Indeed, the hierarchical processing information among distinct brain regions and across multiple channels requires using a more advanced multilayer model to understand the synchronization across the brain that underlies functional brain networks.
View Article and Find Full Text PDFUnveiling cell-type-specific microRNA networks through alternative polyadenylation in glioblastoma.
BMC Biol
January 2025
Faculty of Biology, Johannes Gutenberg University Mainz, Mainz, Germany.
Background: Glioblastoma multiforme (GBM) is characterized by its cellular complexity, with a microenvironment consisting of diverse cell types, including oligodendrocyte precursor cells (OPCs) and neoplastic CD133 + radial glia-like cells. This study focuses on exploring the distinct cellular transitions in GBM, emphasizing the role of alternative polyadenylation (APA) in modulating microRNA-binding and post-transcriptional regulation.
Results: Our research identified unique APA profiles that signify the transitional phases between neoplastic cells and OPCs, underscoring the importance of APA in cellular identity and transformation in GBM.
Reward Decision Network Disconnection in Poststroke Apathy: A Prospective Multimodality Imaging Study.
Hum Brain Mapp
February 2025
Department of Neurology, Centre for Leading Medicine and Advanced Technologies of IHM, the First Affiliated Hospital of USTC, Division of Life Sciences and Medicine, University of Science and Technology of China, Hefei, Anhui, China.
Apathy is a common neuropsychiatric symptom following stroke, characterized by reduced goal-directed behavior. The reward decision network (RDN), which plays a crucial role in regulating goal-directed behaviors, is closely associated with apathy. However, the relationship between poststroke apathy (PSA) and RDN dysfunction remains unclear due to apathy heterogeneity, the confounding effect of depression and individual variability in lesion impacts.
View Article and Find Full Text PDFWant AI Summaries of new PubMed Abstracts delivered to your In-box?
Enter search terms and have AI summaries delivered each week - change queries or unsubscribe any time!