Dynamic Domain Imaging
Dynamic Domain Imaging - Related Videos
14:56
Imaging Replicative Domains in Ultrastructurally Preserved Chromatin by Electron Tomography
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2022
This protocol presents a technique for high-resolution mapping of replication sites in structurally preserved chromatin in situ that employs a combination of pre-embedding EdU-streptavidin-Nanogold labeling and ChromEMT.
10:49
Intravital Longitudinal Imaging of Vascular Dynamics in the Calvarial Bone Marrow
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Cited by 1 •
2025
Intravital microscopy allows the study of dynamic biological processes such as tissue regeneration and tumor development. The calvarial bone marrow, a highly dynamic tissue, offers insights into hematopoiesis and vascular function. Using a biocompatible 3D-printed head fixation implant allows for repetitive longitudinal imaging, enhancing our understanding of tissue dynamics and the tumor microenvironment.
02:26
Conservation of Protein Domains Over Different Proteins
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2020
Protein domains are small structurally independent units that are part of a single amino acid chain. Although these domains are often structurally independent, they may rely on synergistic effects to perform their functions as part of a larger protein. Protein domains may be conserved within the same organism, as well as across different organisms. A limited set of protein domains often duplicate and recombine during evolution. These domains can be organized in different combinations to form...
14:21
Optical Frequency Domain Imaging of Ex vivo Pulmonary Resection Specimens: Obtaining One to One Image to Histopathology Correlation
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Cited by 21 •
2013
A method to image ex vivo pulmonary resection specimens with optical frequency domain imaging (OFDI) and obtain precise correlation to histology is described, which is essential to developing specific OFDI interpretation criteria for pulmonary pathology. This method is applicable to other tissue types and imaging techniques to obtain precise imaging to histology correlation for accurate image interpretation and assessment. Imaging criteria established with this technique would then be...
05:45
Uncovering Hidden Dynamics of Natural Photonic Structures Using Holographic Imaging
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Cited by 6 •
2022
The paper is primarily focused on the combined power of optical (linear and nonlinear) and holographic methods used to reveal phenomena at the nanoscale. The results obtained from the biophotonic and oscillatory chemical reactions' studies are given as representative examples, highlighting holography's ability to reveal dynamics at a nanoscale.
FAQs
The approach links time-lapse image acquisition with computational segmentation, which identifies spatial domains and estimates their boundaries. Quantitative tracking then follows changes in position, size, and intensity across successive images. This converts visual observations into spatial and temporal measurements, allowing researchers to compare local structural changes with biological activity over the course of an experiment.
Computational segmentation separates domains from surrounding regions so that each domain can be analyzed consistently throughout an image sequence. Accurate boundary identification supports measurements of domain size, intensity, and spatial arrangement. It also makes it possible to recognize events such as formation, movement, fusion, or dissolution rather than relying only on qualitative visual inspection.
A single image can show domain organization at one moment but cannot establish how that organization changes. Temporal measurements reveal whether domains form, move, merge, or disappear, while spatial measurements show where those changes occur. Together, they help connect local structural dynamics with biological function and expose heterogeneity that a static view may conceal.
A typical workflow begins by acquiring a time-lapse sequence that captures the system as it changes. Researchers then apply computational segmentation to identify domains and their boundaries, followed by quantitative tracking across frames. The resulting data can describe domain size, intensity, location, and dynamic events, providing a structured basis for interpreting evolving biological organization.
In engineered tissues and biomaterials, the method can quantify how spatial domains develop or reorganize during use or development. Measurements of boundaries, size, intensity, movement, fusion, or dissolution provide evidence of changing organization within the engineered system. These observations can support evaluation of how local structure evolves and how that evolution relates to biological function.
The measurements provide quantitative evidence about heterogeneity and changing organization in systems whose properties evolve over time. By comparing domain behavior across engineered tissues, biomaterials, or cellular arrangements, researchers can evaluate whether a design produces the intended spatial and temporal patterns. This supports more informed assessment and refinement of dynamic biological systems.