0000000000142145
AUTHOR
Eduardo Villamor
Risk Assessment of Hip Fracture Based on Machine Learning
[EN] Identifying patients with high risk of hip fracture is a great challenge in osteoporosis clinical assessment. Bone Mineral Density (BMD) measured by Dual-Energy X-Ray Absorptiometry (DXA) is the current gold standard in osteoporosis clinical assessment. However, its classification accuracy is only around 65%. In order to improve this accuracy, this paper proposes the use of Machine Learning (ML) models trained with data from a biomechanical model that simulates a sideways-fall. Machine Learning (ML) models are models able to learn and to make predictions from data. During a training process, ML models learn a function that maps inputs and outputs without previous knowledge of the probl…
Ceramide Mediates Acute Oxygen Sensing in Vascular Tissues
AbstractAims: A variety of vessels, such as resistance pulmonary arteries (PA) and fetoplacental arteries and the ductus arteriosus (DA) are specialized in sensing and responding to changes in oxygen tension. Despite opposite stimuli, normoxic DA contraction and hypoxic fetoplacental and PA vasoconstriction share some mechanistic features. Activation of neutral sphingomyelinase (nSMase) and subsequent ceramide production has been involved in hypoxic pulmonary vasoconstriction (HPV). Herein we aimed to study the possible role of nSMase-derived ceramide as a common factor in the acute oxygen-sensing function of specialized vascular tissues. Results: The nSMase inhibitor GW4869 and an anticera…