The automatic recognition of chemical names and their corresponding database identifiers in biomedical text is an important first step for many downstream text-mining applications. The task is even more challenging when considering the identification of these entities in the article's full text and, furthermore, the identification of candidate substances for that article's metadata [Medical Subject Heading (MeSH) article indexing]. The National Library of Medicine (NLM)-Chem track at BioCreative VII aimed to foster the development of algorithms that can predict with high quality the chemical entities in the biomedical literature and further identify the chemical substances that are candidates for article indexing.
View Article and Find Full Text PDFIn this study, a composite scaffold consisting of an electrospun polyurethane and poly(ethylene glycol) hydrogel was investigated for aortic valve tissue engineering. This multilayered approach permitted the fabrication of a scaffold that met the desired mechanical requirements while enabling the 3D culture of cells. The scaffold was tuned to mimic the tensile strength, anisotropy, and extensibility of the natural aortic valve through design of the electrospun polyurethane mesh layer.
View Article and Find Full Text PDFAdvanced tissue engineered heart valves must be constructed from multiple materials to better mimic the heterogeneity found in the native valve. The trilayered structure of aortic valves provides the ability to open and close consistently over a full human lifetime, with each layer performing specific mechanical functions. The middle spongiosa layer consists primarily of proteoglycans and glycosaminoglycans, providing lubrication and dampening functions as the valve leaflet flexes open and closed.
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