@misc{Gross2022,
  type      = {Master Thesis},
  author    = {Groß, Lennart},
  title     = {Point-spread function engineering for single-molecule localization microscopy in brain slices},
  doi       = {10.25972/OPUS-28259},
  url       = {http://nbn-resolving.de/urn:nbn:de:bvb:20-opus-282596},
  school      = {Universit{\"a}t W{\"u}rzburg},
  year      = {2022},
  abstract  = {Single-molecule localization microscopy (SMLM) is the method of choice to study biological specimens on a nanoscale level. Advantages of SMLM imply its superior specificity due to targeted molecular fluorescence labeling and its enhanced tissue preservation compared to electron microscopy, while reaching similar resolution. To reveal the molecular organization of protein structures in brain tissue, SMLM moves to the forefront: Instead of investigating brain slices with a thickness of a few µm, measurements of intact neuronal assemblies (up to 100 µm in each dimension) are required. As proteins are distributed in the whole brain volume and can move along synapses in all directions, this method is promising in revealing arrangements of neuronal protein markers. However, diffraction-limited imaging still required for the localization of the fluorophores is prevented by sample-induced distortion of emission pattern due to optical aberrations in tissue slices from non-superficial planes. In particular, the sample causes wavefront dephasing, which can be described as a summation of Zernike polynomials. To recover an optimal point spread function (PSF), active shaping can be performed by the use of adaptive optics. The aim of this thesis is to establish a setup using a deformable mirror and a wavefront sensor to actively shape the PSF to correct the wavefront phases in a super-resolution microscope setup. Therefore, fluorescence-labeled proteins expressed in different anatomical regions in brain tissue will be used as experiment specimen. Resolution independent imaging depth in slices reaching tens of micrometers is aimed.},
  subject      = {Einzelmolek{\"u}lmikroskopie},
  language  = {en}
}
@misc{Fronczek2009,
  type      = {Master Thesis},
  author    = {Fronczek, David Norman},
  title     = {Integration of fluorescence and atomic force microscopy for single molecule studies of protein complexes},
  url       = {http://nbn-resolving.de/urn:nbn:de:bvb:20-opus-70731},
  school      = {Universit{\"a}t W{\"u}rzburg},
  year      = {2009},
  abstract  = {The scope of this work is to develop a novel single-molecule imaging technique by combining atomic force microscopy (AFM) and optical fluorescence microscopy. The technique is used for characterizing the structural properties of multi-protein complexes. The high-resolution fluorescence microscopy and AFM are combined (FIONA-AFM) to allow for the identification of individual proteins in such complexes. This is achieved by labeling single proteins with fluorescent dyes and determining the positions of these fluorophores with high precision in an optical image. The same area of the sample is subsequently scanned by AFM. Finally, the two images are aligned and the positions of the fluorophores are displayed on top of the topographical data. Using quantum dots as fiducial markers in addition to fluorescently labeled proteins, fluorescence and AFM information can be aligned with an accuracy better than 10 nm, which is sufficient to identify single fluorescently labeled proteins in most multi-protein complexes. The limitations of localization precision and accuracy in fluorescence and AFM images are investigated, including their effects on the overall registration accuracy of FIONA-AFM hybrid images. This combination of the two complementary techniques opens a wide spectrum of possible applications to the study of protein interactions, because AFM can yield high resolution (5-10 nm) information about the conformational properties of multi-protein complexes while the fluorescence can indicate spatial relationships of the proteins within the complexes. Additionally, computer simulations are performed in order to validate the accuracy of the registration algorithm.},
  subject      = {Kraftmikroskopie},
  language  = {en}
}