Swiss-PO: a new tool to analyze the impact of mutations on protein three-dimensional structures for precision oncology.
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ABSTRACT:
SUBMITTER: Krebs FS
PROVIDER: S-EPMC7973488 | biostudies-literature |
REPOSITORIES: biostudies-literature
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Project description:BackgroundDiagnosis and treatment decisions in cancer increasingly depend on a detailed analysis of the mutational status of a patient's genome. This analysis relies on previously published information regarding the association of variations to disease progression and possible interventions. Clinicians to a large degree use biomedical search engines to obtain such information; however, the vast majority of scientific publications focus on basic science and have no direct clinical impact. We develop the Variant-Information Search Tool (VIST), a search engine designed for the targeted search of clinically relevant publications given an oncological mutation profile.ResultsVIST indexes all PubMed abstracts and content from ClinicalTrials.gov. It applies advanced text mining to identify mentions of genes, variants and drugs and uses machine learning based scoring to judge the clinical relevance of indexed abstracts. Its functionality is available through a fast and intuitive web interface. We perform several evaluations, showing that VIST's ranking is superior to that of PubMed or a pure vector space model with regard to the clinical relevance of a document's content.ConclusionDifferent user groups search repositories of scientific publications with different intentions. This diversity is not adequately reflected in the standard search engines, often leading to poor performance in specialized settings. We develop a search engine for the specific case of finding documents that are clinically relevant in the course of cancer treatment. We believe that the architecture of our engine, heavily relying on machine learning algorithms, can also act as a blueprint for search engines in other, equally specific domains. VIST is freely available at https://vist.informatik.hu-berlin.de/.
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Project description:Microfluidic devices are gaining extensive interest due to their potential applications in wide-ranging areas, including lab-on-a-chip devices, fluid delivery, and artificial vascular networks. Most current microfluidic devices are in a planar design with fixed configurations once formed, which limits their applications such as in engineered vascular networks in biology and programmable drug delivery systems. Here, shape-programmable three-dimensional (3D) microfluidic structures, which are assembled from a bilayer of channel-embedded polydimethylsiloxane (PDMS) and shape-memory polymers (SMPs) via compressive buckling, are reported. 3D microfluidics in diverse geometries including those in open-mesh configurations are presented. In addition, they can be programmed into temporary shapes and recover their original shape under thermal stimuli due to the shape memory effect of the SMP component, with fluid flow in the microfluidic channels well maintained in both deformed and recovered shapes. Furthermore, the shape-fixing effect of SMPs enables freestanding open-mesh 3D microfluidic structures without the need for a substrate to maintain the 3D shape as used in previous studies. By adding magnetic particles into the PDMS layer, magnetically responsive 3D microfluidic structures are enabled to achieve fast, remote programming of the structures via a portable magnet. A 3D design phase diagram is constructed to show the effects of the magnetic PDMS/SMP thickness ratio and the volume fraction of magnetic particles on the shape programmability of the 3D microfluidic structures. The developed shape-programmable, open-mesh 3D microfluidic structures offer many opportunities for applications including tissue engineering, drug delivery, and many others.
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