AIMC Topic: Mice
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Manifold learning analysis suggests strategies to align single-cell multimodal data of neuronal electrophysiology and transcriptomics.
Communications biology
Nov 19, 2021
Recent single-cell multimodal data reveal multi-scale characteristics of single cells, such as transcriptomics, morphology, and electrophysiology. However, integrating and analyzing such multimodal data to deeper understand functional genomics and ge...
Imaging flow cytometry data analysis using convolutional neural network for quantitative investigation of phagocytosis.
Biotechnology and bioengineering
Nov 18, 2021
Macrophages play an important role in the adaptive immune system. Their ability to neutralize cellular targets through Fc receptor-mediated phagocytosis has relied upon immunotherapy that has become of particular interest for the treatment of cancer ...
Open-source deep learning-based automatic segmentation of mouse Schlemm's canal in optical coherence tomography images.
Experimental eye research
Nov 16, 2021
The purpose of this study was to develop an automatic deep learning-based approach and corresponding free, open-source software to perform segmentation of the Schlemm's canal (SC) lumen in optical coherence tomography (OCT) scans of living mouse eyes...
Quantitative imaging of apoptosis following oncolytic virotherapy by magnetic resonance fingerprinting aided by deep learning.
Nature biomedical engineering
Nov 11, 2021
Non-invasive imaging methods for detecting intratumoural viral spread and host responses to oncolytic virotherapy are either slow, lack specificity or require the use of radioactive or metal-based contrast agents. Here we show that in mice with gliob...
Detecting fine and elaborate movements with piezo sensors provides non-invasive access to overlooked behavioral components.
Neuropsychopharmacology : official publication of the American College of Neuropsychopharmacology
Nov 11, 2021
Behavioral phenotyping devices have been successfully used to build ethograms, but many aspects of behavior remain out of reach of available phenotyping systems. We now report on a novel device, which consists in an open-field platform resting on hig...
Three-Dimensional Visualization of the Podocyte Actin Network Using Integrated Membrane Extraction, Electron Microscopy, and Machine Learning.
Journal of the American Society of Nephrology : JASN
Nov 10, 2021
BACKGROUND: Actin stress fibers are abundant in cultured cells, but little is known about them . In podocytes, much evidence suggests that mechanobiologic mechanisms underlie podocyte shape and adhesion in health and in injury, with structural change...
Ultrasound deep learning for monitoring of flow-vessel dynamics in murine carotid artery.
Ultrasonics
Nov 9, 2021
Several arterial diseases are closely related with mechanical properties of the blood vessel and interactions of flow-vessel dynamics such as mean flow velocity, wall shear stress (WSS) and vascular strain. However, there is an opportunity to improve...
High-Throughput, Label-Free and Slide-Free Histological Imaging by Computational Microscopy and Unsupervised Learning.
Advanced science (Weinheim, Baden-Wurttemberg, Germany)
Nov 7, 2021
Rapid and high-resolution histological imaging with minimal tissue preparation has long been a challenging and yet captivating medical pursuit. Here, the authors propose a promising and transformative histological imaging method, termed computational...
Chemometric analysis in Raman spectroscopy from experimental design to machine learning-based modeling.
Nature protocols
Nov 5, 2021
Raman spectroscopy is increasingly being used in biology, forensics, diagnostics, pharmaceutics and food science applications. This growth is triggered not only by improvements in the computational and experimental setups but also by the development ...
Deep learning is widely applicable to phenotyping embryonic development and disease.
Development (Cambridge, England)
Nov 5, 2021
Genome editing simplifies the generation of new animal models for congenital disorders. However, the detailed and unbiased phenotypic assessment of altered embryonic development remains a challenge. Here, we explore how deep learning (U-Net) can auto...
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