Results 191 to 200 of about 15,095,322 (254)
White Matter and Perivascular Imaging Changes in Alzheimer's Disease and Cerebral Amyloid Angiopathy
ABSTRACT Objective Peak‐width of skeletonized mean diffusivity (PSMD) and diffusion tensor imaging–analysis along the perivascular space (DTI‐ALPS), reflecting white matter integrity and glymphatic function, are altered in Alzheimer's disease (AD).
Debina Laishram +3 more
wiley +1 more source
Metabolic and Fluid Biomarkers Support Microglia Activation in Amyotrophic Lateral Sclerosis
ABSTRACT Amyotrophic lateral sclerosis is an incurable neurodegenerative disease involving motor neuron degeneration and metabolic and immune dysfunction. We combined clinical data, cerebrospinal fluid biomarkers and fluorodeoxyglucose positron emission tomography with magnetic resonance imaging to investigate the role of reactive microglia in disease ...
Matteo Zanovello +10 more
wiley +1 more source
Boundary‐Dependent Sleep–Wake Dysregulation in Idiopathic Hypersomnia
ABSTRACT Objective Idiopathic hypersomnia (IH) presents with excessive daytime sleepiness (EDS) despite apparently preserved nocturnal sleep, challenging traditional models of hypersomnolence based on sleep loss or fragmentation. We aimed to test the hypothesis that EDS in IH reflects excessive stabilization of the sleep state, consistent with ...
Samantha Mombelli +13 more
wiley +1 more source
ABSTRACT Variants in KCNA1, encoding the Kv1.1 potassium channel, cause neurological disorders including episodic ataxia and developmental and epileptic encephalopathy. We identified a novel KCNA1 variant (A401T) in a 16‐year‐old patient with autism spectrum disorder, borderline intellectual disability, and tremor, without episodic ataxia or epilepsy ...
Juan Darío Ortigoza‐Escobar +7 more
wiley +1 more source
microRNA‐7‐5p and α‐Synuclein SAA Predict Parkinson's Disease Phenoconversion
ABSTRACT Objective Corroborate blood neuron‐derived extracellular vesicle (NDEV) alpha‐synuclein (αSyn), the CSF αSyn seed amplification assay (αSyn‐SAA), and blood microRNA‐7‐5p (miR‐7‐5p) as markers for Parkinson's disease (PD) phenoconversion and determine if combining these markers would help select subjects who would be more likely to phenoconvert.
Shayan Zadegan +4 more
wiley +1 more source
Objective The aim of this study was to evaluate the sensitivity of the 2023 American College of Rheumatology (ACR)/EULAR classification criteria for antiphospholipid syndrome (APS) in a real‐world cohort of women diagnosed with primary obstetric APS (oAPS) and to assess their ability to identify patients at risk of future pregnancy complications ...
Francesca Ruffilli +10 more
wiley +1 more source
Objective To investigate the association between rheumatoid arthritis (RA) and coronary artery calcium (CAC) prevalence, incidence, and progression over four years in adults without prior cardiovascular disease. Methods A case‐cohort study within the Brazilian Longitudinal Study of Adult Health (ELSA‐Brasil) included 585 participants (86 patients with ...
Patrícia Fonseca Estrada +7 more
wiley +1 more source
Objective Orofacial manifestations are significantly impactful in patients with systemic sclerosis (SSc) yet remain understudied, with no dedicated clinical guidelines to inform their management. Methods An international online survey comprised38 questions addressing orofacial manifestations of SSc, including patients’ confidence in their treating ...
Eleni Deligianni +4 more
wiley +1 more source
Observer‐Based Adaptive Event‐Triggered Tracking Control for Fuzzy TS Systems With Premise Mismatch
This paper presents an adaptive logistic event‐triggered observer‐based tracking controller for Takagi‐Sugeno fuzzy systems under constrained inputs and network delays. Leveraging a hybrid LMI and Secretary Bird Optimization approach, this strategy significantly minimizes communication overhead and computational burden while ensuring optimal reference ...
Oussama Djadane +3 more
wiley +1 more source
dynoGP: Deep Gaussian Processes for Dynamic System Identification
This work introduces a novel class of deep models for system identification, dynamical deep Gaussian processes, which combine the strengths of data‐driven methods, such as those based on neural network architectures, with the ability to output a probability distribution for uncertainty representation.
Alessio Benavoli +3 more
wiley +1 more source

