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The Benchtop mesoSPIM: a next-generation open-source light-sheet microscope for large cleared samples

Abstract

In 2015, we launched the mesoSPIM initiative (www.mesospim.org), an open-source project for making light-sheet microscopy of large cleared tissues more accessible. Meanwhile, the demand for imaging larger samples at higher speed and resolution has increased, requiring major improvements in the capabilities of light-sheet microscopy. Here, we introduce the next-generation mesoSPIM ("Benchtop") with significantly increased field of view, improved resolution, higher throughput, more affordable cost and simpler assembly compared to the original version. We developed a new method for testing objectives, enabling us to select detection objectives optimal for light-sheet imaging with large-sensor sCMOS cameras. The new mesoSPIM achieves high spatial resolution (1.5 μm laterally, 3.3 μm axially) across the entire field of view, a magnification up to 20x, and supports sample sizes ranging from sub-mm up to several centimetres, while being compatible with multiple clearing techniques. The new microscope serves a broad range of applications in neuroscience, developmental biology, and even physics.

Additional indexing

Item Type:Working Paper
Communities & Collections:04 Faculty of Medicine > Institute of Anatomy
04 Faculty of Medicine > Center for Microscopy and Image Analysis
04 Faculty of Medicine > Neuroscience Center Zurich
07 Faculty of Science > Institute of Molecular Life Sciences
07 Faculty of Science > Physics Institute
04 Faculty of Medicine > University Hospital Zurich > Institute of Neuropathology
04 Faculty of Medicine > Brain Research Institute
07 Faculty of Science > Department of Quantitative Biomedicine
08 Research Priority Programs > Adaptive Brain Circuits in Development and Learning (AdaBD)
Dewey Decimal Classification:610 Medicine & health
530 Physics
570 Life sciences; biology
Language:English
Date:12 December 2023
Deposited On:12 Jan 2024 11:44
Last Modified:20 Jun 2024 11:31
Series Name:bioRxiv
Number of Pages:65
ISSN:2164-7844
OA Status:Hybrid
Publisher DOI:https://doi.org/10.1101/2023.06.16.545256
PubMed ID:38168219
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