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In vivo fluorescence miniature microscopy has recently proven a major advance, enabling cellular imaging in freely behaving animals. However, fluorescence imaging suffers from autofluorescence, phototoxicity, photobleaching and non- homogeneous illumination artifacts. These factors limit the quality and time course of data collection. Bioluminescence provides an alternative kind of activity-dependent light indicator. Bioluminescent calcium indicators do not require light input, instead generating photons through chemiluminescence. As such, limitations inherent to the requirement for light presentation are eliminated. Further, bioluminescent indicators also do not require excitation light optics: the removal of these components should make a lighter and lower cost microscope with fewer assembly parts. While there has been significant recent progress in making brighter and faster bioluminescence indicators, the advances in imaging hardware have not yet been realized. A hardware challenge is that despite potentially higher signal-to-noise of bioluminescence, the signal strength is lower than that of fluorescence. An open question we address in this report is whether fluorescent miniature microscopes can be rendered sensitive enough to detect bioluminescence. We demonstrate this possibility in vitro and in vivo by implementing optimizations of the UCLA fluorescent miniscope v3.2. These optimizations yielded a miniscope (BLmini) which is 22% lighter in weight, has 45% fewer components, is up to 58% less expensive, offers up to 15 times stronger signal and is sensitive enough to capture spatiotemporal dynamics of bioluminescence in the brain with a signal-to-noise ratio of 34 dB.
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http://dx.doi.org/10.1109/EMBC44109.2020.9175375 | DOI Listing |
Sci Rep
September 2025
Department of Electrical and Computer Engineering, Johns Hopkins University, Baltimore, MD, 21218, USA.
Hum Brain Mapp
September 2025
Department of Neuropediatrics, General Pediatrics, Diabetology, Endocrinology, Social Pediatrics, University Children's Hospital, Tübingen, Germany.
Subject motion is a significant problem for the analysis of functional MRI data and is usually described by "total displacement" or "scan-to-scan displacement". Neither parameter, however, takes into account voxel size, which clearly is relevant for the actual effects of motion on the data. Consequently, it is hitherto impossible to compare motion between subjects/studies acquired using different voxel dimensions, precluding the development of generally applicable recommendations for fMRI quality control procedures.
View Article and Find Full Text PDFPLoS Comput Biol
September 2025
Université Grenoble Alpes, CNRS, Grenoble INP, TIMC, Grenoble, France.
Background And Objectives: We present a new Finite Element (FE) tongue model that was designed to precisely account for 3D tongue shapes produced during isolated French speech sounds by a male individual (RS). Such a high degree of realism will enable scientists to precisely and quantitatively assess, in a speaker-specific manner, hypotheses about speech motor control and the impact of tongue anatomy, muscle arrangements, and tongue dynamics in this context.
Methods: The shape and topology of the FE model were generated from 3D high resolution orofacial MR images of RS having his tongue in "neutral" posture.
Front Aging Neurosci
August 2025
Laboratory of Molecular Neurodegeneration, Graduate School of Biomedical Systems and Technologies, Institute of Biomedical Systems and Biotechnology, Peter the Great St. Petersburg Polytechnic University, Saint Petersburg, Russia.
Alzheimer's disease (AD) is a neurodegenerative disorder that leads to progressive cognitive decline and significant disruptions in hippocampal neural networks, critically impacting memory and learning. Understanding the neural mechanisms underlying these impairments is essential for developing effective therapies. The 5xFAD mouse model, known for progressive neurodegeneration and cognitive deficits, provides a valuable platform for investigating associative learning and memory impairments related to AD.
View Article and Find Full Text PDFBrief Bioinform
August 2025
Department of Biostatistics, Vanderbilt University Medical Center, 2525 West End Avenue, Suite 1100, Nashville, TN 37232, United States.
Spatial transcriptomics (ST) integrates gene expression data with the spatial organization of cells and their associated histology, offering unprecedented insights into tissue biology. While existing methods incorporate either location-based or histology-informed information, none fully synergize gene expression, histological features, and precise spatial coordinates within a unified framework. Moreover, these methods often exhibit inconsistent performance across diverse datasets and conditions.
View Article and Find Full Text PDF