3D-Printing in Science: Conference Co-Staged with LABVOLUTION
News Oct 06, 2016
The LABVOLUTION trade show, which next runs from 16 to 18 May 2017 in Hannover, Germany, is dedicated to innovative lab equipment and laboratory workflow optimization. One of the added highlights for professionals attending the show next year will be “3D-Printing in Science”, a two-day conference that will run alongside LABVOLUTION. 3D-Printing in Science is produced by the UK- based conference organizer SELECTBIO.
3D-Printing has proven itself to be the best solution when it comes to rapid, ad hoc modification and manufacturing of tools and medical instruments. More and more science institutions, ranging in size from small labs right up to NASA-scale, are using this technology to explore new areas of research and streamline work processes. The 3D-Printing in Science conference, which will be held on 16 and 17 May in the conference area of Hall 19/20 – and hence right next door to LABVOLUTION – will explore the many advantages of 3D-Printing in prosthetics manufacturing, laboratory supplies and the production of bio-materials for tissue cultivation in medical and non-medical applications.
LABVOLUTION is a B2B platform for laboratory equipment, automation solutions, diagnostic and analytical systems, digitalization and workflow optimization. It brings together innovative commercial enterprises and R&D institutions from the life sciences and analytical chemistry, focusing primarily on the markets of Northern Europe. One of the highlights of LABVOLUTION in 2017, as in previous years, is the “smartLAB – the intelligent lab of the future” showcase. LABVOLUTION is staged alongside BIOTECHNICA, a key European life sciences event that functions as an incubator of new biotech methods and processes and is thus an important meeting hub for biotechnology experts.
The spatial and temporal dynamics of proteins or organelles plays a crucial role in controlling various cellular processes and in development of diseases. However, acute control of activity at distinct locations within a cell cannot be achieved. A new chemo-optogenetic method enables tunable, reversible, and rapid control of activity at multiple subcellular compartments within a living cell.
Scientists have used machine learning to train computers to see parts of the cell the human eye cannot easily distinguish. Using 3D images of fluorescently labeled cells, the research team taught computers to find structures inside living cells without fluorescent labels, using only black and white images generated by an inexpensive technique known as brightfield microscopy.READ MORE
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