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Superresolution Microscopy Images Common Alzheimer’s Protein

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DOUGLAS FARMER, SENIOR EDITOR
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As superresolution microscopy has advanced, so too has scientists’ ability to dive deep into the neural network and the compounds that accumulate in conjunction with a variety of conditions. And a team at the VIB-KU Leuven Center for Brain & Disease Research has seized on this technology to understand a protein complex that is common in patients with Alzheimer’s disease and with cancer. The γ-secretase complex is an enzyme composed of catalytic presenilin (PSEN), nicastrin (NCT), anterior-pharynx defective 1 (APH1), and presenilin enhancer 2 (PEN2) in a 1:1:1:1...Read full article

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    Published: July 2020
    Glossary
    superresolution
    Superresolution refers to the enhancement or improvement of the spatial resolution beyond the conventional limits imposed by the diffraction of light. In the context of imaging, it is a set of techniques and algorithms that aim to achieve higher resolution images than what is traditionally possible using standard imaging systems. In conventional optical microscopy, the resolution is limited by the diffraction of light, a phenomenon described by Ernst Abbe's diffraction limit. This limit sets a...
    photobleaching
    Photobleaching is a phenomenon in which the fluorescence of a fluorophore (a fluorescent molecule or dye) is permanently reduced or eliminated upon prolonged exposure to light. This process occurs due to the photochemical destruction or alteration of the fluorophore molecules, rendering them non-fluorescent. Key points about photobleaching: Mechanism: Photobleaching is typically a result of chemical reactions induced by the absorbed photons. The excessive light exposure causes the...
    neural network
    A computing paradigm that attempts to process information in a manner similar to that of the brain; it differs from artificial intelligence in that it relies not on pre-programming but on the acquisition and evolution of interconnections between nodes. These computational models have shown extensive usage in applications that involve pattern recognition as well as machine learning as the interconnections between nodes continue to compute updated values from previous inputs.
    Research & TechnologyMicroscopysuperresolutionsuperresolution microscopyphotobleachingImagingneural networkneural networksAlzheimers diseaseBioScan

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