Alzheimer's disease is a widespread disease that has devastating effects on the human brain and mind. Ultimately, it leads to death and there are currently no treatment methods available that can stop the disease progression. The mechanisms involved behind the disease are not fully understood although it is known that amyloid fibrils play an important role in the disease development. These fibrils are able to form plaques that can trigger neuronal death, by interacting with receptors on the cell surface and the synaptic cleft or by entering the cell and disturb important functions such as metabolic pathways. To study the plaque formation of amyloid proteins, both in vitro and in vivo methods are used to investigate the characteristics of the protein. Luminescent conjugated oligothiophene probes are able to bind in to amyloid beta fibrils and emit light when excited by an external light source. This way fibrillation properties of the protein can be studied. Developing probes that can serve as biomarkers for detection of amyloid fibrils could change the way Alzheimer's is treated. Being able to detect the disease in its early disease course, and start treatments early, is suggested to stop the progression of neural breakdown. In this project a software is developed to analyze fluorescent microscopy images, taken on tissue stained with these probes. The software is able to filter out background noise and capture parts of the picture that are of interest when studying the amyloid plaques. This software generates results similar to if the images were to be analyzed using any software where the regions to analyze are selected manually, suggesting that the software developed produce reliable results unbiased by background noise.
Identifer | oai:union.ndltd.org:UPSALLA1/oai:DiVA.org:liu-166672 |
Date | January 2020 |
Creators | Haglund, Samuel |
Publisher | Linköpings universitet, Institutionen för fysik, kemi och biologi |
Source Sets | DiVA Archive at Upsalla University |
Language | English |
Detected Language | English |
Type | Student thesis, info:eu-repo/semantics/bachelorThesis, text |
Format | application/pdf |
Rights | info:eu-repo/semantics/openAccess |
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