Tissue Transparency Enhancement
Tissue Transparency Enhancement - Related Videos
08:12
A Web-Based Workflow for Selecting Gene- and Tissue-Specific Enhancers
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2025
We present a coding-free workflow for biologists to identify tissue-specific gene enhancers using only browser-based tools. Our protocol leverages public H3K4me1/H3K27ac histone marks and Hi-C data, enabling researchers without programming expertise to access, analyse, and identify potential regulatory elements associated with their genes of interest.
06:14
Novel Passive Clearing Methods for the Rapid Production of Optical Transparency in Whole CNS Tissue
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Cited by 7 •
2018
Here, we present two novel methodologies, psPACT and mPACT, for achieving maximal optical transparency and subsequent microscopic analysis of tissue vasculature in the intact rodent whole CNS.
07:28
Imaging Cell Viability on Non-transparent Scaffolds — Using the Example of a Novel Knitted Titanium Implant
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Cited by 6 •
2016
Here we present a fluorophore based imaging technique to detect cell viability on a non-transparent titanium scaffold as well as to detect glimpses of the scaffold impurities. This protocol troubleshoots the drawback of imaging cell-cell or cell-metal interactions on non-transparent scaffolds.
10:27
Fabrication of Nano-engineered Transparent Conducting Oxides by Pulsed Laser Deposition
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Cited by 15 •
2013
We describe the experimental method to deposit nanostructured oxide thin films by nanosecond Pulsed Laser Deposition (PLD) in the presence of a background gas. By using this method Al-doped ZnO (AZO) films, from compact to hierarchically structured as nano-tree forests, can be deposited.
26:16
Patterning Cells on Optically Transparent Indium Tin Oxide Electrodes
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Cited by 1 •
2007
Non-fouling PEG silane monolayer was desorbed from individually addressable ITO electrodes on glass by application of a reductive potential. Electrochemical stripping of PEG-silane layer from ITO microelectrodes allowed for cell adhesion to take place in a spatially defined fashion, with cellular patterns corresponding closely to electrode patterns.
FAQs
Optical scattering redirects light as it passes through tissue, obscuring structures located deeper within a specimen. Tissue transparency enhancement addresses this problem through chemical clearing, including lipid removal, and refractive-index matching, which adjusts the optical properties of the sample. Together, these changes improve light transmission and make internal cellular features more accessible to fluorescence microscopy.
These components address different requirements of the same imaging workflow. Lipid removal helps reduce a major source of optical obstruction, while refractive-index matching improves light passage through the prepared specimen. Labeling preserves or reveals selected cellular components so that increased transparency produces interpretable structural signals rather than simply a clearer but unmarked tissue volume.
Physical sectioning divides tissue into separate slices, which can make it difficult to follow structures continuously across a larger volume. By reducing the need for sectioning, the approach supports three-dimensional examination of connected features such as neurons and axons. This continuity can help researchers relate local cellular organization to broader neural-circuit architecture.
A typical workflow combines chemical preparation, labeling, and imaging rather than relying on transparency alone. The tissue is chemically cleared, with steps such as lipid removal or refractive-index matching, and relevant cellular components are labeled. The prepared thick specimen is then examined with fluorescence microscopy or another compatible imaging platform to visualize structures throughout its volume.
Fluorescence imaging can reveal three-dimensional arrangements of neurons, axons, and vasculature within a thick nervous-system specimen. Because the method improves access to structures across larger volumes, the resulting data can connect individual cellular features with their surrounding organization. This supports analysis of spatial relationships that are harder to assess when tissue is viewed only as separate sections.
The approach is particularly useful when researchers need to examine neural organization across substantial tissue volumes rather than isolated slices. In neuroscience, it can support visualization of neural circuits, vascular structure, and disease-related changes in brain or other nervous-system samples. Its value comes from linking cellular-scale observations with three-dimensional anatomical context.