Results 211 to 220 of about 1,090,897 (359)

Non‐RASopathy Genetic Syndromes Identified as the Molecular Cause of Disease in Patients Previously Diagnosed With Noonan Syndrome

open access: yesAmerican Journal of Medical Genetics Part A, EarlyView.
ABSTRACT Noonan Syndrome (NS) is a clinically and genetically heterogeneous condition characterized by typical facial dysmorphisms, short stature, congenital heart defects, and developmental delays. While variants in genes such as PTPN11, SOS1, and RAF1 account for most genetically confirmed cases, diagnosis is challenging due to phenotypic overlap ...
Gabriela Jeesoo Kim   +9 more
wiley   +1 more source

Understanding the Housing and Support Experience of People With Complex Disability in Australia: A Qualitative Analysis of Submissions to the Disability Royal Commission

open access: yesAustralian Journal of Social Issues, EarlyView.
ABSTRACT In 2019, the Australian government established the Royal Commission into Violence, Abuse, Neglect and Exploitation of People with Disability (‘Disability Royal Commission’, DRC) to investigate widespread mistreatment of people with disability. Nearly 10,000 people with disability, their families and supporters engaged with the DRC.
Kate D'Cruz   +7 more
wiley   +1 more source

Cadherin‐26 Facilitates Transepithelial Migration of Eosinophils in Eosinophilic Chronic Rhinosinusitis

open access: yesInternational Forum of Allergy &Rhinology, EarlyView.
ABSTRACT Background Eosinophilic chronic rhinosinusitis with nasal polyps (eCRSwNP) is characterized by persistent sinonasal inflammation and marked eosinophilic infiltration. Although the relationship between eosinophils and NP formation has been extensively studied, the mechanisms governing eosinophil transepithelial migration into the nasal mucosa ...
Yeong‐In Jo   +7 more
wiley   +1 more source

Machine Learning‐Enhanced Clinical Decision Support for Diagnosing Sinusitis With Nasal Endoscopy

open access: yesInternational Forum of Allergy &Rhinology, EarlyView.
ABSTRACT Background Sinusitis is a prevalent disease for which nasal endoscopy (NE) is an optimal diagnostic modality. However, NE accuracy is limited by inter‐operator variability in landmark identification and localization of mucus that is necessary for sinusitis diagnosis. We sought to develop a novel multi‐class machine learning (ML) framework that
Dipesh Gyawali   +12 more
wiley   +1 more source

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