Results 171 to 180 of about 1,482,534 (311)

Relationship Between Neurologic Symptoms and Signs and FMR1 Genotype in Premutation Carriers

Annals of Clinical and Translational Neurology, EarlyView.
ABSTRACT Background and Objectives Fragile X‐associated Tremor/Ataxia Syndrome (FXTAS) is the most severe late‐onset condition caused by a premutation in the FMR1 gene, characterized by expanded CGG triplet repeats of 55–200. Clinical presentations of FXTAS, including gait ataxia, kinetic tremor, cognitive decline, and rare Parkinsonism, are linked to ...
Flora Tassone, Freddy Chafota, Miguel E. Rentería, Randi J. Hagerman, Ellery Santos, Anna Atkinson, Nicholas G. Martin, Elsdon Storey, Danuta Z. Loesch   +8 more
wiley   +1 more source

Regulating Availability with Demand Uncertainty [PDF]

I evaluate German regulation that requires retail discounters to guarantee the availability of their products in bargain sales. The regulation is meant to prevent loss leaders.
Roland Strausz
core  

Uncertainty estimation and probabilistic skull shape reconstruction using bayesian neural networks. [PDF]

Sci Rep
Li J, Sengupta A, Zachow S.
europepmc   +1 more source

RNA Sequencing Resolves Cryptic Pathogenic Variants in Mitochondrial Disease

Annals of Clinical and Translational Neurology, EarlyView.
ABSTRACT Objective Mitochondrial diseases are the most common inherited metabolic disorders, characterized by pronounced clinical and genetic heterogeneity that complicates molecular diagnosis. Although DNA‐based sequencing approaches have become standard in genetic testing, up to half of patients remain without a definitive diagnosis.
Zhimei Liu, Xin Duan, Fatemeh Peymani, Jia Wang, Chengjia Bao, Chaolong Xu, Ying Zou, Zixuan Zhang, Yunxi Zhang, Tongyue Li, Martin Pavlov, Junling Wang, Minhan Song, Tianyu Song, Xiaodi Han, Mingxi Sun, Danmin Shen, Ruoyu Duan, Huafang Jiang, Manting Xu, Holger Prokisch, Fang Fang   +21 more
wiley   +1 more source

Accounting for uncertainty and bias in archaeological and historical evidence on wealth inequality. [PDF]

Proc Natl Acad Sci U S A
Fochesato M, Bowles S.
europepmc   +1 more source

Advancing Age Modulates Associations Between Cognitive Impairment and Brain Volumes in Early MS

Annals of Clinical and Translational Neurology, EarlyView.
ABSTRACT Introduction Cognitive impairment is common in multiple sclerosis (MS), but manifestations following the first demyelinating event are relatively unexplored. We investigated cross‐sectional associations between magnetic resonance imaging (MRI)–derived brain volumes and the presence of cognitive impairment outcomes five years after the first ...
Piriyankan Ananthavarathan, Marco Pitteri, Michael Foster, Sara Collorone, Sara Salama, Elisa Colato, Ferran Prados, Baris Kanber, Marios Yiannakas, Claudia A. M. Gandini Wheeler‐Kingshott, Indran Davagnanam, Frederik Barkhof, Declan Chard, Olga Ciccarelli, Ahmed Toosy   +14 more
wiley   +1 more source

Does inflation uncertainty increase with inflation? [PDF]

One of the most important costs of inflation is the uncertainty it creates about future inflation. This uncertainty clouds the decisionmaking of consumers and businesses and reduces economic well-being.
John E. Golob
core  

Uncertainty quantification of U-Net based segmentation tool using conformal prediction. [PDF]

J Appl Clin Med Phys
Borden BJ, Graham-Knight JB, Lasserre P, Lucas S, Rajapakshe RD.   +4 more
europepmc   +1 more source

Understanding Further the Phenotypic Spectrum of Central Nervous System Inflammatory Demyelinating Disorders Using Unsupervised Clustering

Annals of Clinical and Translational Neurology, EarlyView.
ABSTRACT Background Central nervous system (CNS) inflammatory demyelinating syndromes, including multiple sclerosis (MS), aquaporin‐4 antibody–positive neuromyelitis optica spectrum disorder (AQP4 + NMOSD), and myelin oligodendrocyte glycoprotein (MOG) antibody–associated disease (MOGAD), occasionally overlap.
Bade Gulec, Elif Everest, Melih Tutuncu, Ugur Bilge, Sabahattin Saip, Ugur Uygunoglu, Aksel Siva   +6 more
wiley   +1 more source

Autonomous Uncertainty Quantification for Computational Point-of-Care Sensors. [PDF]

ACS Nano
Goncharov A, Ghosh R, Joung HA, Di Carlo D, Ozcan A.   +4 more
europepmc   +1 more source