Biology subjects

Hugonnet, H.

Publications and source records attributed to Hugonnet, H..

6 recordsLinked to original sources

bioRxiv2023

Label-free histological analysis of retrieved thrombi in acute ischemic stroke using optical diffraction tomography and deep learning

For patients with acute ischemic stroke, histological quantification of thrombus composition provides evidence for determining appropriate treatment. However, the traditional manual segmentation of stained thrombi is laborious and inconsistent. In this study, we propose a label-free method that combines optical diffraction tomography (ODT) and deep learning (DL) to automate the histological quantification process. The DL model classifies ODT image patches with 95% accuracy, and the collective prediction generates a whole-slide map of red blood cells and fibrin. The resulting whole-slide composition displays an average error of 1.1% and does not experience staining variability, facilitating faster analysis with reduced labor. The present approach will enable rapid and quantitative evaluation of blood clot composition, expediting the preclinical research and diagnosis of cardiovascular diseases.

bioengineering↗

bioRxiv2023

Volumetric refractive index measurement and quantitative density analysis of mouse brain tissue with sub-micrometer spatial resolution

High-resolution structural imaging of brain tissue is important for neuroscience research. However, conventional approaches have several limitations, such as the need for exogenous staining, limited accessibility to volumetric information, and qualitative analysis. Herein, we present high-resolution label-free volumetric imaging and analysis of mouse brain tissue using three-dimensional quantitative phase imaging. Measurement of the refractive index distribution of tissue enables direct imaging of the cellular and subcellular structures. Quantification of subcellular organelles is performed in the anatomical regions of the somatosensory cortex, corpus callosum, caudoputamen, and thalamus regions.

biophysics↗

bioRxiv2021

Label-free monitoring of 3D cortical neuronal growth in vitro using optical diffraction tomography

The highly complex central nervous systems of mammals are often studied using three-dimensional (3D) in vitro primary neuronal cultures. A coupled confocal microscopy and immunofluorescence labeling are widely utilized for visualizing the 3D structures of neurons. However, this requires fixation of the neurons and is not suitable for monitoring an identical sample at multiple time points. Thus, we propose a label-free monitoring method for 3D neuronal growth based on refractive index tomograms obtained by optical diffraction tomography. The 3D morphology of the neurons was clearly visualized, and the developmental processes of neurite outgrowth in 3D spaces were analyzed for individual neurons. O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=101 SRC="FIGDIR/small/454602v1_ufig1.gif" ALT="Figure 1"> View larger version (35K): org.highwire.dtl.DTLVardef@b858baorg.highwire.dtl.DTLVardef@c946caorg.highwire.dtl.DTLVardef@468168org.highwire.dtl.DTLVardef@da022c_HPS_FORMAT_FIGEXP M_FIG C_FIG

neuroscience↗

bioRxiv2020

Three-Dimensional Label-Free Imaging and Quantification of Migrating Cells during Wound Healing

The wound healing assay provides essential information about collective cell migration and cell-to-cell interactions. It is a simple, effective, and widely used tool for observing the effect of numerous chemical treatments on wound healing speed. To perform and analyze a wound healing assay, various imaging techniques have been utilized. However, image acquisition and analysis are often limited in two-dimensional space or require the use of exogenous labeling agents. Here, we present a method for imaging large-scale wound healing assays in a label-free and volumetric manner using optical diffraction tomography (ODT). We performed quantitative high-resolution three-dimensional (3D) analysis of cell migration over a long period without difficulties such as photobleaching or phototoxicity. ODT enables the reconstruction of the refractive index (RI) tomogram of unlabeled cells, which provides both structural and biochemical information about the individual cell at subcellular resolution. Stitching multiple RI tomograms enables long-term (24 h) and large field-of-view imaging (> 800 x 400 m2) with a lateral resolution of 110 nm. We demonstrated the thickness changes of leading cells and studied the effects of cytochalasin D. The 3D RI tomogram also revealed increased RI values in leading cells compared to lagging cells, suggesting the formation of a highly concentrated subcellular structure. STATEMENT OF SIGNIFICANCEThe wound healing assay is a simple but effective tool for studying collective cell migration (CCM) that is widely used in biophysical studies and high-throughput screening. However, conventional imaging and analysis methods only address two-dimensional properties in a wound healing assay, such as gap closure rate. This is unfortunate because biological cells are complex 3D structures, and their dynamics provide significant information about cell physiology. Here, we presented three-dimensional (3D) label-free imaging for wound healing assays and investigated the 3D dynamics of CCM. High-resolution subcellular structures as well as their collective dynamics were imaged and analyzed quantitatively. Our label-free quantitative 3D analysis method provides a unique opportunity to study the behavior of migrating cells during the wound healing process.

biophysics↗

bioRxiv2020

Multiscale label-free volumetric holographic histopathology of thick-tissue slides with subcellular resolution

Histopathology relies upon the staining and sectioning of biological tissues, which can be laborious and may cause artefacts and distort tissues. Here, we demonstrate label-free volumetric imaging of thick-tissue slides, exploiting refractive index distributions as intrinsic imaging contrast. The present method systematically exploits label-free quantitative phase imaging techniques, volumetric reconstruction of intrinsic refractive index distributions in tissues, and numerical algorithms for the seamless stitching of multiple 3D tomograms and for reducing scattering-induced image distortion. We demonstrate demonstrated label-free volumetric imaging of thick tissues with the field of view of 2 mm x 1.75 mm x 0.2 mm with a spatial resolution of 170 nm x 170 nm x 1200 nm. The number of optical modes, calculated as the reconstructed volume divided by the size of the point spread function, was approximately 20 Giga voxels. We have also demonstrated that different tumour types, and a variety of precursor lesions and pathologies can be visualized with the present method. O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=150 SRC="FIGDIR/small/205633v1_ufig1.gif" ALT="Figure 1"> View larger version (98K): org.highwire.dtl.DTLVardef@dcf15corg.highwire.dtl.DTLVardef@16a05d3org.highwire.dtl.DTLVardef@1a48860org.highwire.dtl.DTLVardef@f57430_HPS_FORMAT_FIGEXP M_FIG C_FIG

pathology↗

bioRxiv2020

Label-free three-dimensional observations and quantitative characterisation of on-chip vasculogenesis using optical diffraction tomography

Label-free, three-dimensional (3D) quantitative observations of on-chip vasculogenesis were achieved using optical diffraction tomography. Exploiting 3D refractive index maps as an intrinsic imaging contrast, the vascular structures, multicellular activities, and subcellular organelles of endothelial cells were imaged and analysed throughout vasculogenesis to characterise mature vascular networks without exogenous labelling. O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=176 SRC="FIGDIR/small/892620v1_ufig1.gif" ALT="Figure 1"> View larger version (98K): org.highwire.dtl.DTLVardef@12a786eorg.highwire.dtl.DTLVardef@14892dforg.highwire.dtl.DTLVardef@1a28091org.highwire.dtl.DTLVardef@1a6e9df_HPS_FORMAT_FIGEXP M_FIG C_FIG

bioengineering↗