Imagexpress Ultra
Imagexpress Ultra - Related Videos
08:53
Angle-resolved Photoemission Spectroscopy At Ultra-low Temperatures
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Cited by 8 •
2012
The overall goal of this method is to determine the low-energy electronic structure of solids at ultra-low temperatures using Angle-Resolved Photoemission Spectroscopy with synchrotron radiation.
07:51
Fabrication of Silica Ultra High Quality Factor Microresonators
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Cited by 22 •
2012
We describe the use of a carbon dioxide laser reflow technique to fabricate silica resonant cavities, including free-standing microspheres and on-chip microtoroids. The reflow method removes surface imperfections, allowing long photon lifetimes within both devices. The resulting devices have ultra high quality factors, enabling applications ranging from telecommunications to biodetection.
05:28
MALDI Sample Preparation: the Ultra Thin Layer Method
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Cited by 31 •
2007
This video demonstrates the preparation of an ultra-thin matrix/analyte layer for analyzing peptides and proteins by Matrix-Assisted Laser Desorption Ionization Mass Spectrometry (MALDI-MS).
03:03
Generating an Ultra-Low-Density Neuronal Culture Using a High-Density Neuronal Feeder Layer
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2025
This video demonstrates the method for culturing ultra-low-density neurons in the presence of a high-density neuronal feeder layer. It establishes a co-culture of varying-density neurons, ensuring close physical proximity. The growth factors secreted by high-density neurons help neuronal survival and growth, maintaining ultra-low-density neurons for a longer time period.
11:19
A Simplified Method for Ultra-Low Density, Long-Term Primary Hippocampal Neuron Culture
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Cited by 45 •
2016
Low density cultures of primary hippocampal neurons usually require glia feeder layer to supply neurotrophic factors and sustain longevity. We describe here a simplified method to culture ultra-low density neurons on glass coverslips in the presence of a high density neuronal feeder layer, which facilitates investigation of specific neuronal-autonomous mechanisms.
FAQs
The motorized stage moves samples through multiple fields of view, allowing the system to collect images from many locations rather than relying on a single visual area. Optical components then capture fluorescence and confocal information, while software organizes measurements across those images. This coordinated process supports comparisons at scale and helps reveal patterns that may not be apparent in one field.
Fluorescence microscopy supplies fluorescence-based image information, whereas confocal imaging adds another optical imaging mode within the same platform. Using both enables researchers to build multiparametric datasets instead of relying on one image characteristic alone. The combined information can support analysis of morphology, fluorescence intensity, and subcellular localization, giving a broader view of how cells or tissues respond.
Quantitative image analysis translates image content into numerical measurements, including cell morphology, fluorescence intensity, and subcellular localization. Those measurements allow researchers to compare biological states across fields of view and experimental conditions rather than relying only on visual impressions. The resulting data can highlight informative phenotypes and support more consistent evaluation of cellular responses.
Responses can be compared by linking measured features to the experimental perturbation. Changes in morphology, fluorescence intensity, or subcellular localization may distinguish cells exposed to drugs, altered by genes, or subjected to environmental conditions. Examining several features together creates a multiparametric view, which helps researchers identify phenotypes associated with a particular biological state.
A typical workflow begins by placing the sample on the motorized stage and selecting fields of view for imaging. The optical system then captures fluorescence and confocal images from those locations. Specialized software measures selected cellular or tissue features, such as morphology or fluorescence intensity, and the resulting values are compared across samples or experimental conditions.
It is useful when researchers need to examine cellular behavior in living samples or screen for visible cellular phenotypes across many image fields. The platform supports measurements that can reveal how cells respond to drugs, genes, or environmental conditions. This makes it suitable for comparing biological states and identifying responses that merit further investigation.
By quantifying cellular and tissue features, the platform helps researchers compare biological states associated with disease-related changes or treatment exposure. Measurements of morphology, fluorescence intensity, and subcellular localization can reveal informative phenotypes and differences in cellular response. These results support investigations of disease mechanisms and help characterize how biological systems respond to potential treatments.