Results 71 to 80 of about 215,880 (264)
Objective This study aims to develop hip morphology‐based radiographic hip osteoarthritis (RHOA) risk prediction models and investigates the added predictive value of hip morphology measurements and the generalizability to different populations. Methods We combined data from nine prospective cohort studies participating in the Worldwide Collaboration ...
Myrthe A. van den Berg +26 more
wiley +1 more source
Introduction Rheumatic and musculoskeletal diseases(RMDs) are leading causes of physical disability, necessitating support with activities of daily living(ADLs). This study describes social care received by patients with RMDs in two disperate regions of England: Salford(urban) and Norfolk(rural).
Mehreen Somro +6 more
wiley +1 more source
Trajectories of Physical Function in Canadian Children with Juvenile Idiopathic Arthritis
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
Tumor location may affect the clinicopathological features and prognosis of thymomas
Background The current staging systems do not consider the tumor location of thymomas, and its clinical relevance is poorly understood. This study aimed to evaluate the impact of tumor location on the clinicopathological features and prognosis of ...
Dong Tian +5 more
doaj +1 more source
Unleashing the Power of Machine Learning in Nanomedicine Formulation Development
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
Predicting Atomic Charges in MOFs by Topological Charge Equilibration
An atomic charge prediction method is presented that is able to accurately reproduce ab‐initio‐derived reference charges for a large number of metal–organic frameworks. Based on a topological charge equilibration scheme, static charges that fulfill overall neutrality are quickly generated.
Babak Farhadi Jahromi +2 more
wiley +1 more source
Stein-James Estimators of a Multivariate Location Parameter
Bounds on the risks, under squared error loss, of a family of estimators of a multivariate location parameter are given for both fixed and random unknown location parameters when the covariance matrix of the observed random variable is unknown. The class of estimators considered in this paper contains Cogburn's [2].
openaire +3 more sources
PREdicting LNP In Vivo Efficacy (PRELIVE) framework enables the prediction of lipid nanoparticle (LNPs) organ‐specific delivery through dual modeling approaches. Composition‐based models using formulation parameters and protein corona‐based models using biological fingerprints both achieve high predictive accuracy across multiple organs.
Belal I. Hanafy +3 more
wiley +1 more source
A two‐phase workflow (OFAT screening followed by central composite design) maps how processing variables tune PFCE‐PLGA nanoparticle size, dispersity, surface charge, loading, and 19F‐MRI signal. In situ, time‐resolved synchrotron SAXS tracks albumin‐corona growth on intact dispersions and reveals PFCE‐dependent adsorption pathways.
Joice Maria Joseph +11 more
wiley +1 more source
Analysis of Prognostic Factors of World Health Organization Grade Ⅲ Meningiomas
ObjectiveWHO grade III meningiomas are highly aggressive and lethal. However, there is a paucity of clinical information because of a low incidence rate, and little is known for prognostic factors.
Weidong Tian +7 more
doaj +1 more source

