Confluency Detection
Confluency Detection - Related Videos
11:39
Measuring the Confluence of iPSCs Using an Automated Imaging System
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2020
The goal of the protocol is to compare different extracellular matrix (ECM) coating conditions to assess how differential coating affects the growth rate of induced pluripotent stem cells (iPSCs). In particular, we aim to set up conditions to obtain optimal growth of iPSC cultures.
09:10
Combination of Adhesive-tape-based Sampling and Fluorescence in situ Hybridization for Rapid Detection of Salmonella on Fresh Produce
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Cited by 17 •
2010
This protocol describes a simple adhesive-tape-based approach for sampling of tomato and other fresh produce surfaces, followed by rapid whole cell detection of Salmonella using fluorescence in situ hybridization (FISH).
10:24
Detection of Ligand-activated G Protein-coupled Receptor Internalization by Confocal Microscopy
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Cited by 2 •
2017
This protocol describes confocal microscopy detection of G protein-coupled receptor (GPCR) internalization in mammalian cells. It includes the basic cell culture, transfection, and confocal microscopy procedure and provides an efficient and easily interpretable method to detect the subcellular localization and internalization of fusion-expressed GPCR.
09:00
Detection of Protein Ubiquitination
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Cited by 96 •
2009
Ubiquitination is a key posttranslational modification carried out by a set of three enzymes. Mutations of genes involved in this modification are associated with many different human diseases. Here, we describe protocols to detect protein ubiquitination in cultured cells in vivo and test tubes in vitro.
07:15
Standardized Method to Detect Tunneling Nanotubes in Human Skin Cells for Tissue Engineering Applications
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2026
Here, a standardized protocol to visualize tunneling nanotubes between human epidermal keratinocytes and dermal fibroblasts using membrane and F-actin labeling with z-stack confocal imaging is shown, with optional α-tubulin co-staining, enabling reproducible detection and cytoskeletal characterization for tissue-engineering applications.
FAQs
The assessment compares regions occupied by adherent cells with regions where the underlying culture surface remains exposed. In microscope images, this distinction supports an estimate of surface occupancy, while direct visual assessment provides a human judgment of the same relationship. The resulting percentage summarizes how extensively the cells have spread across the available surface.
Automated image analysis applies a consistent approach to microscope images, reducing differences between observers who might judge the same culture differently. This improves comparability across time points and experiments. More consistent estimates help researchers monitor growth, coordinate culture decisions, and strengthen quality control when visual judgments alone could introduce observer bias.
The percentage indicates the proportion of the culture surface occupied by adherent cells at the time of observation. Comparing this value across observations can show changes in culture growth and status. Because the measure is tied to surface coverage, it provides a practical basis for judging whether the culture is approaching a condition that requires further handling.
Visual assessment relies on a researcher examining the culture directly and estimating the occupied surface, whereas image-based analysis uses microscope images to support the estimate. Both approaches address the same culture feature, but automated analysis can make repeated measurements more consistent. The choice affects how easily results can be compared across observers, samples, and experiments.
A basic workflow begins by obtaining a microscope image of the adherent-cell culture surface. The cell-covered regions are then distinguished from the remaining substrate, and the occupied area is expressed as a percentage of the available surface. Researchers can repeat this assessment across observations to follow growth and evaluate the culture's status.
Researchers use these measurements when deciding whether a culture is ready for routine handling or an experimental intervention. The estimate can inform the timing of medium changes, passaging, or treatment. Applying the same assessment before these steps helps align culture management with the observed growth state and supports more reproducible experimental timing.
In biology, confluency estimates help connect cell-culture status with assay timing and experimental readiness. Tracking surface coverage can reveal whether cultures are progressing as expected and provide a record for quality control. Consistent measurements also support reproducibility by helping investigators compare culture conditions and coordinate procedures across experiments.