4d Cell Tracking
4d Cell Tracking - Related Videos
08:59
4D Imaging of Protein Aggregation in Live Cells
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Cited by 4 •
2013
Cellular viability depends on timely and efficient management of protein misfolding. Here we describe a method for visualizing the different potential fates of a misfolded protein: refolding, degradation, or sequestration in inclusions. We demonstrate the use of a folding sensor, Ubc9ts, for monitoring proteostasis and aggregation quality control in live cells using 4D microscopy.
12:00
4D Microscopy of Yeast
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Cited by 12 •
2019
This protocol describes the analysis of fluorescently labeled intracellular compartments in budding yeast using multi-color 4D (time-lapse 3D) confocal microscopy. The imaging parameters are chosen to capture adequate signals while limiting photodamage. Custom ImageJ plugins allow labeled structures to be tracked and quantitatively analyzed.
07:59
Tracking Cells in GFP-transgenic Zebrafish Using the Photoconvertible PSmOrange System
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Cited by 2 •
2016
We established the photoconvertible PSmOrange system as a powerful, straight-forward and cost inexpensive tool for in vivo cell tracking in GFP transgenic backgrounds. This protocol describes its application in the zebrafish model system.
07:19
Cell Tracking Using Photoconvertible Proteins During Zebrafish Development
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Cited by 17 •
2012
Here, we present a method for the photoactivated switch of photoconvertible fluorescent proteins (PCFPs) in the living zebrafish embryo and further tracking of photoconverted protein at specific time points during development. This methodology allows monitoring of cell biological events underlying different developmental processes in a live vertebrate organism.
22:49
Optimized Staining and Proliferation Modeling Methods for Cell Division Monitoring using Cell Tracking Dyes
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Cited by 45 •
2012
Successful use of cell tracking dyes to monitor immune cell function and proliferation involves several critical steps. We describe methods for: 1) obtaining bright, uniform, reproducible label-ing with membrane dyes; 2) selecting fluorochromes and data acquisition conditions; and 3) choosing a model to quantify cell proliferation based on dye dilution.
FAQs
Segmentation identifies individual cells within each image frame, while trajectory linking matches those identified cells across successive frames. Together, these steps convert separate observations into continuous movement paths. This connection allows researchers to follow changes in each cell’s position and shape rather than analyzing isolated images, providing a basis for measuring dynamic cellular behavior.
Position, directionality, speed, and persistence provide complementary descriptions of cellular movement. Position shows where a cell travels, directionality indicates whether movement follows a consistent orientation, speed quantifies how quickly its location changes, and persistence reflects how consistently it maintains its movement pattern. Examining these measures helps relate cell behavior to neural development and organization.
A three-dimensional image captures cellular arrangement at one moment, whereas adding time reveals how that arrangement changes. Repeated observations can show whether a cell shifts position, changes shape, or maintains a directional movement pattern. In neuroscience, this temporal information is important for distinguishing ongoing neuronal migration, axon extension, and progenitor behavior from static anatomical patterns.
A reconstructed trajectory summarizes a cell’s successive locations as a continuous path through three-dimensional space. Researchers can use that path to examine movement direction, speed, and persistence together with changes in cell shape. The resulting record links individual cellular actions to larger processes such as neural tissue organization, developmental movement, and interactions among brain cells.
The workflow begins with time-lapse microscopy to collect images across three-dimensional space and time. Image segmentation then identifies cells in individual frames, and trajectory linking connects corresponding cells between successive frames. The completed trajectories support quantitative analysis of position, shape, directionality, speed, and persistence, producing a time-resolved view of cellular behavior.
Neuroscientists can apply 4D Cell Tracking when they need to characterize neuronal migration, axon extension, or neural progenitor behavior over time. It is also useful for examining interactions among developing brain cells. By quantifying these dynamic processes, the approach connects individual cell movements with broader patterns of neural development and organization.
The method can provide quantitative descriptions of how individual neural cells move and change. Measurements of position, shape, speed, directionality, and persistence help researchers compare cellular behaviors and identify movement patterns associated with development or organization. These outcomes can also support investigation of disease-related changes when altered cellular dynamics are part of the research question.
4D Cell Tracking provides a way to examine disease-related changes through measurable differences in cellular movement and shape over time. Researchers can compare trajectories, directionality, speed, persistence, or interactions among cells to determine how dynamic behavior differs from expected neural organization. This makes cellular motion a quantitative link between imaging observations and disease-focused neuroscience studies.