Abstract
Human diseases are treated and cured thanks to our understanding of cells and tissues. How the body’s cells behave during health and disease is seen through biomedical imaging. Each cell has millions of proteins that are invisible to the naked eye –200,000 times smaller than the width of a human hair. Electron microscopy (EM) visualizes even the tiniest proteins and reveals a high-resolution snapshot of the whole cell. Analysis of the gray-scale EM images is subjective. When the interpretation of cellular features is uncertain, additional experiments are required which can take extra days to months. What if we had a way to gather more information from an EM image without having to prepare another sample, or even change the microscope? Luckily, there are many analytical signals in the EM that can be utilized but few have been developed for use in biology. The additional information from the signals is evaluated with the gray-scale EM data as a false-color overlay and together it is termed ColorEM. This thesis describes the development and application of ColorEM with energy dispersive X-ray (EDX) analysis which detects elemental composition through the collection and interpretation of characteristic X-rays. The experimental design for impactful EDX data collection was optimized and applied in this thesis. Applications included barcoded nanoparticles imaged within cells to show how cells degrade and organize cargo and the identification of human cell types and features to study type 1 diabetes. ColorEM is the future for cellular feature identification at EM resolution.
Original language | English |
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Qualification | Doctor of Philosophy |
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Award date | 17-Jun-2022 |
Place of Publication | [Groningen] |
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Publication status | Published - 2022 |