Automated Microscope
Automated Microscope - Related Videos
09:27
Automation of Bio-Atomic Force Microscope Measurements on Hundreds of C. albicans Cells
0 Views •
Cited by 3 •
2021
This protocol aims to automate AFM measurements on hundreds of microbial cells. First, microbes are immobilized into PDMS stamp microstructures and then force spectroscopy measurements are performed automatically on hundreds of immobilized cells.
08:06
Automated Acoustic Dispensing for the Serial Dilution of Peptide Agonists in Potency Determination Assays
0 Views •
Cited by 1 •
2016
Peptide adsorption to plasticware during traditional tip-based serial dilutions can significantly impact potency determination and confound the understanding of structure-activity relationships used for lead identification and lead optimization phases of drug discovery. Here methods for automated acoustic non-contact serial dilution of peptide samples are described.
08:23
An Automated Microscopic Scoring Method for the γ-H2AX Foci Assay in Human Peripheral Blood Lymphocytes
0 Views •
Cited by 7 •
2021
This protocol presents the slide preparation and automated scoring of the γ-H2AX foci assay on peripheral blood lymphocytes. To illustrate the method and sensitivity of the assay, isolated lymphocytes were irradiated in vitro. This automated method of DNA DSB detection is useful for fast and high-throughput biological dosimetry applications.
04:57
Proper Care and Cleaning of the Microscope
0 Views •
Cited by 2 •
2008
Keeping the microscope optics clean is important for high-quality imaging. Dust, fingerprints, excess immersion oil, or mounting medium on or in a microscope causes reduction in contrast and resolution. DIC is especially sensitive to contamination and scratches on the lens surfaces. This protocol details the procedure for keeping the microscope clean.
08:08
Major Components of the Light Microscope
0 Views •
2008
The light microscope is a basic tool for the cell biologist, who should have a thorough understanding of how it works, how it should be aligned for different applications, and how it should be maintained as required to obtain maximum image-forming capacity and resolution. The components of the microscope are described in detail here.
FAQs
Computer-directed stage movement positions the specimen across multiple fields, while automated focusing adjusts image sharpness and programmable illumination controls imaging conditions. Software coordinates these actions according to defined settings, allowing successive observations to follow a consistent sequence. This coordination reduces dependence on manual repositioning and helps produce comparable images across fields or samples.
Automated focusing helps maintain image sharpness as the system examines different fields or samples. Programmable illumination keeps lighting conditions defined rather than dependent on moment-to-moment manual adjustment. Together, these controls support consistent acquisition, which is especially important when researchers compare quantitative measurements or cellular responses across many images.
Image-processing algorithms can analyze acquired images and organize the resulting data, rather than leaving interpretation entirely to visual inspection. This supports quantitative measurements across multiple fields and helps structure results from high-throughput experiments. In biological techniques, the approach makes it easier to evaluate cellular responses systematically and compare observations collected under defined conditions.
Conventional microscopy depends more heavily on user-controlled positioning, focusing, illumination, and image selection. Automated microscopy assigns these operations to motorized components and software using programmed conditions. The resulting workflow can reduce user-dependent variation and improve measurement consistency, making it more suitable for experiments that require repeated observations across many fields or samples.
A typical workflow establishes imaging conditions, then uses software to direct stage movement, focusing, and illumination while the system acquires images from selected fields or samples. After acquisition, image-processing algorithms analyze and organize the data. This sequence supports repeatable examination of many locations and creates measurements suitable for later comparison.
Researchers may choose it for high-throughput cell imaging, time-lapse studies, quantitative measurements, or screening cellular responses. The system can examine multiple fields or samples under defined conditions and follow changes over time. These capabilities are useful when experiments require more observations, faster image collection, or more consistent measurements than manual microscopy can readily provide.