Results 101 to 110 of about 334,720 (282)
Arthritis Care &Research, Accepted Article.Objective We developed a novel EHR sidecar application to visualize key rheumatoid arthritis (RA) outcomes, including disease activity, physical function, and pain, via a patient‐facing graphical interface designed for use during outpatient visits (“RA PRO dashboard”).
Gabriela Schmajuk +16 more
wiley +1 more source
Arthritis Care &Research, EarlyView.Objective We examined whether 18 months of strength training in individuals with knee varus alignment and medial tibiofemoral osteoarthritis (OA) reduced knee joint loads during walking compared to an attention control group. Methods This study was a secondary analysis of a randomized clinical trial that compared the effects of strength training to a ...
Stephen P. Messier +12 more
wiley +1 more source
Arthritis Care &Research, Accepted Article.Objective We aimed to estimate the prevalence and cumulative incidence of hydroxychloroquine retinopathy (HCQ‐R) and its risk factors among long‐term HCQ users with rheumatic diseases through a systematic review and meta‐analysis of observational studies that used spectral‐domain OCT (SD‐OCT) for screening. Methods A systematic search of PubMed, Scopus,
Narsis Daftarian +4 more
wiley +1 more source
Arthritis Care &Research, Accepted Article.Background Clinical response to Mycophenolic acid (MPA) is highly heterogeneous; thus, therapeutic drug monitoring (TDM) may help improve treatment efficacy. This systematic review and meta‐analysis examined therapeutic ranges for MPA levels associated with better outcomes and safety in patients with SLE, particularly those with extra‐renal ...
Zahraa Qamhieh +5 more
wiley +1 more source
Trajectories of Physical Function in Canadian Children with Juvenile Idiopathic Arthritis
Arthritis Care &Research, Accepted Article.Objectives We describe trajectories of physical function in children newly diagnosed with juvenile idiopathic arthritis (JIA) and identify trajectories with persisting functional impairments and associated baseline characteristics. Methods We included patients enrolled in the Canadian Alliance of Pediatric Rheumatology Investigators (CAPRI) Registry ...
Clare Cunningham +14 more
wiley +1 more source
Advanced Engineering Materials, EarlyView.Fungal mycelia grown into biodegradable scaffolds and infused with titania nanoparticles show enhanced ultraviolet shielding, thermal protection, and surface nonwettability. Properties were tuned by drying methods, revealing structure–function relationships.
Juwon S. Afolayan +2 more
wiley +1 more source
Wetland Classification with Multi-Angle/Temporal SAR Using Random Forests
Remote Sensing, 2019 To better understand and mitigate threats to the long-term health and functioning of wetlands, there is need to establish comprehensive inventorying and monitoring programs.
Sarah Banks +7 more
doaj +1 more source
Advanced Functional Materials, EarlyView.Biofabrication aims at providing innovative technologies and tools for the fabrication of tissue‐like constructs for tissue engineering and regenerative medicine applications. By integrating multiple biofabrication technologies, such as 3D (bio) printing with fiber fabrication methods, it would be more realistic to reconstruct native tissue's ...
Waseem Kitana +2 more
wiley +1 more source
Advanced Functional Materials, EarlyView.A previously unreported coordination motif stabilising single Fe atoms by indigo chelation and pyridyl coordination on Au(111) has been revealed. By using planar tritopic pyridyl linkers (TPyB), extended 2D porous networks of indigo3(TPyB)2Fe6 form. These networks can be crystalline or vitreous and offer an environment where individual coordination ...
Hongxiang Xu +9 more
wiley +1 more source
Unleashing the Power of Machine Learning in Nanomedicine Formulation Development
Advanced Functional Materials, EarlyView.A random forest machine learning model is able to make predictions on nanoparticle attributes of different nanomedicines (i.e. lipid nanoparticles, liposomes, or PLGA nanoparticles) based on microfluidic formulation parameters. Machine learning models are based on a database of nanoparticle formulations, and models are able to generate unique solutions
Thomas L. Moore +7 more
wiley +1 more source