We discovered that the light entering a triangular ultramicrotome glass knife from the bottom exits the knife through its cutting edge, forming an oblique light sheet illumination suitable for imaging. We adopted this light sheet for side illumination of the sample blocks during sectioning on the ultramicrotome, for 3D imaging, and for targeting fluorescent features for confocal-, electron- and correlative microscopy. In this paper, we present a working prototype named CELS-3D (Cutting Edge Light Source, Three-Dimensional), a microscope mounted on an ultramicrotome. We characterised CELS-3D and applied it for 3D imaging of human liver spheroids with a diameter of approximately 500 μm. The structure of nuclei and tight junctions has been successfully reconstructed over the full spheroid volume. In contrast, a confocal microscope was unable to image spheroids to a depth of greater than 50 μm. CELS-3D shows fluorescence during serial sectioning in an online mode; therefore, it can apply for targeting fluorescence structures for correlative microscopy. We successfully applied CELS-3D for targeted correlative microscopy of human liver spheroids and C. elegans. The CELS-3D can be utilised for less- and non-transparent samples, which encompasses a range of applications, including operation biopsies, experimental organoids/spheroids, artificial cartilage, and bone, among others. The CELS-3D can be effortlessly mounted on the top of any commercially available ultramicrotome, and its operation is straightforward and intuitive.

Download full-text PDF

Source
http://dx.doi.org/10.1111/joa.14164DOI Listing

Publication Analysis

Top Keywords

correlative microscopy
16
edge light
8
light source
8
targeted correlative
8
cutting edge
8
light sheet
8
human liver
8
liver spheroids
8
cels-3d
6
light
5

Similar Publications

Microalgae are often used in different industrial sectors and can be used as indicators of aquatic environmental health. An essential step for cultivating microalgae is assessing the cell density, which is traditionally performed through cell counting by optical microscopy (OM). However, this method has limitations, mainly in terms of runtime and low reproducibility.

View Article and Find Full Text PDF

Background: Isolated microhematuria (IMH) can signal hidden glomerular disease, necessitating detailed evaluations for potential kidney donors, including kidney biopsies. The optimal strategy for deciding on kidney biopsies remains unclear. While the British Transplant Society supports dipstick analysis, KDIGO focuses solely on urine microscopy.

View Article and Find Full Text PDF

Memory is incorporated into the brain as physicochemical changes to engram cells. These are neuronal populations that form complex neuroanatomical circuits, are modified by experiences to store information, and allow for memory recall. At the molecular level, learning modifies synaptic communication to rewire engram circuits, a mechanism known as synaptic plasticity.

View Article and Find Full Text PDF

How specification mechanisms that generate neural diversity translate into specific neuronal targeting, connectivity, and function in the adult brain is not understood. In the medulla region of the optic lobe, neural progenitors generate different neurons in a fixed order by sequentially expressing a series of temporal transcription factors as they age. Then, Notch signaling in intermediate progenitors further diversifies neuronal progeny.

View Article and Find Full Text PDF

Quantifying Monomer-Dimer Distribution of Nanoparticles from Uncorrelated Optical Images Using Deep Learning.

ACS Omega

January 2025

Nanotechnology, IoT and Applied Machine Learning Research Group, BRAC University, Kha 224 Bir Uttam Rafiqul Islam Avenue, Merul Badda, Dhaka 1212, Bangladesh.

Nanoparticles embedded in polymer matrices play a critical role in enhancing the properties and functionalities of composite materials. Detecting and quantifying nanoparticles from optical images (fixed samples-in vitro imaging) is crucial for understanding their distribution, aggregation, and interactions, which can lead to advancements in nanotechnology, materials science, and biomedical research. In this article, we propose an ensembled deep learning approach for automatic nanoparticle detection and oligomerization quantification in a polymer matrix for optical images.

View Article and Find Full Text PDF

Want AI Summaries of new PubMed Abstracts delivered to your In-box?

Enter search terms and have AI summaries delivered each week - change queries or unsubscribe any time!