Mapping Diffusion Properties in Living Cells

The function of living cells is based on chemical reactions. It has been shown that the velocity of these reactions is limited by the molecular transport in the cell. Therefore also the spatial organization of a cell plays a major role. In order to investigate such transport processes, fluorescence correlation spectroscopy (FCS) is often used in combination with fluorescently labeled proteins. In FCS a small subvolume of the cell (~1µm³) is observed with a laser-based microscope. The fluctuations of the fluorescence, emitted from this subvolume, are acquired. An autocorrelation analysis of these fluctuations reveals the concentrations and diffusion coefficients of the labeled particles. Usually, FCS is implemented using a confocal microscope, which can observe only a single spot at any time. For this thesis, FCS was extended to an imaging method, by combining it with light sheet fluorescence microscopy (SPIM). This relatively new widefield microscopy technique allows to observe an arbitrarily positionable, thin plane (diameter: 1-3µm) in the cell. By using a fast electron-multiplying charge-coupled device camera, the combination of SPIM and FCS allowed to map the motion also of relatively small autofluorescent proteins in living cells. At first, the setup of a light sheet microscope is described. This microscope was designed and optimized for SPIM-FCS measurements in living cells. Several test measurements show the applicability of SPIM-FCS to in vitro samples and to all larger compartments of a living cell (nucleus, cytoplasm, cellular membrane). Afterwards, the usability of several commercially available cameras as image sensor for SPIM-FCS measurements is assessed. At the time of writing, EM-CCD cameras offer the best trade-off between photosensitivity and achievable temporal resolution (~ 500µs). In addition to these linear cameras, also the use of single-photon avalanche diode (SPAD) arrays is investigated. These offer a significantly better temporal resolution (1-10µs) than current EM-CCD cameras, which would render them the ideal image sensor for SPIM-FCS. However, they do not yet reach the photo-sensitivity of EM-CCDs. Two different SPAD arrays were characterized in detail and first successful SPIM-FCS measurements of solute fluorescent molecules could be demonstrated. In a second step, SPIM-FCS was extended by a cross-correlation analysis (SPIM-FCCS), which allowed for the first time to map the interactions of differently labeled cytosolic molecules in living cells. For this purpose, the cross-correlation function between the fluorescence fluctuations from two different color channels is analyzed. A non-zero amplitude of this cross-correlation function is found only, if the differently labeled molecules interact and move together. Finally, the methods developed during this project were applied to different cellular systems. The mapping of the mobility of inert tracer molecules of different sizes allowed to measure the viscosity of the cytoplasm in different cells. A position-dependence of this mobility could only be found in the nucleoli. In addition, an important step in the remodelling cycle of the keratin intermediate filament system was investigated. As a third application, SPIM-F(C)CS measurements of different chromatin-associated proteins demonstrated the dynamics in the cellular nucleus. Mobility maps of labeled histone proteins revealed the organization of chromatin in interphase nuclei. In addition, the activity of the nuclear receptor RXR and a transcription factor were mapped

Optimizing the context of support of web-based self-help in individuals with mild to moderate depressive symptoms: A randomized full factorial trial.

Web-based self-help programs for individuals with depressive symptoms are efficacious. Differences in effect sizes and adherence rates might be due to contextual factors. This randomized factorial trial investigated the effects of four potentially supportive contextual factors on outcome and adherence. Two factors were provided through human contact (guidance and a diagnostic interview), and two factors were provided without human contact (a motivational interviewing module and automated emails). We recruited 316 adults with mild to moderate depressive symptoms (Patient Health Questionnaire-9 score: 5-14). All participants received access to a problem-solving therapy program. Participants were randomized across the four experimental factors (present or absent), resulting in a 16-condition design. The primary outcome was depressive symptoms 10 weeks after baseline. The secondary outcome was program adherence. Overall, results showed significant symptom reduction for the primary depression measure (Cohen's d = 0.38-0.91). Guided participants showed significantly less severe symptoms of depression at post-treatment (d = 0.15) and higher treatment adherence (d = 0.53). At follow-up, these differences were no longer present. The remaining three factors did not influence primary outcome and adherence. These findings indicate that guidance leads to a faster reduction of depressive symptoms and higher treatment adherence

FPGA implementation of a 32x32 autocorrelator array for analysis of fast image series

With the evolving technology in CMOS integration, new classes of 2D-imaging detectors have recently become available. In particular, single photon avalanche diode (SPAD) arrays allow detection of single photons at high acquisition rates (\geq 100 kfps), which is about two orders of magnitude higher than with currently available cameras. Here we demonstrate the use of a SPAD array for imaging fluorescence correlation spectroscopy (imFCS), a tool to create 2D maps of the dynamics of fluorescent molecules inside living cells. Time-dependent fluorescence fluctuations, due to fluorophores entering and leaving the observed pixels, are evaluated by means of autocorrelation analysis. The multi-{\tau} correlation algorithm is an appropriate choice, as it does not rely on the full data set to be held in memory. Thus, this algorithm can be efficiently implemented in custom logic. We describe a new implementation for massively parallel multi-{\tau} correlation hardware. Our current implementation can calculate 1024 correlation functions at a resolution of 10{\mu}s in real-time and therefore correlate real-time image streams from high speed single photon cameras with thousands of pixels.Comment: 10 pages, 7 figure

Exploiting Transformer-based Multitask Learning for the Detection of Media Bias in News Articles

Media has a substantial impact on the public perception of events. A one-sided or polarizing perspective on any topic is usually described as media bias. One of the ways how bias in news articles can be introduced is by altering word choice. Biased word choices are not always obvious, nor do they exhibit high context-dependency. Hence, detecting bias is often difficult. We propose a Transformer-based deep learning architecture trained via Multi-Task Learning using six bias-related data sets to tackle the media bias detection problem. Our best-performing implementation achieves a macro $F_{1}$ of 0.776, a performance boost of 3\% compared to our baseline, outperforming existing methods. Our results indicate Multi-Task Learning as a promising alternative to improve existing baseline models in identifying slanted reporting

Ligand binding shifts highly mobile RXR to chromatin-bound state in a coactivator-dependent manner as revealed by single cell imaging.

Retinoid X Receptor (RXR) is a promiscuous nuclear receptor forming heterodimers with several other receptors, which activate different sets of genes. Upon agonist treatment the occupancy of its genomic binding regions increased, but only a modest change in the number of sites was revealed by ChIP-Seq, suggesting a rather static behavior. However, such genome-wide and biochemical approaches do not take into account the dynamic behavior of a transcription factor. Therefore we characterized the nuclear dynamics of RXR during activation in single cells on the sub-second scale using live-cell imaging. By applying FRAP and fluorescence correlation spectroscopy (FCS), techniques with different temporal and spatial resolution, a highly dynamic behavior could be uncovered, which is best described by a two-state model of receptor mobility. In the unliganded state most RXRs belonged to the fast population, leaving approximately 15% for the slow, chromatin bound fraction. Upon agonist treatment, this ratio increased to approximately 43% as a result of an immediate and reversible redistribution. Coactivator binding appears to be indispensable for redistribution and has a major contribution to chromatin association. A nuclear mobility map recorded by light sheet microscopy-FCS shows that the ligand-induced transition from the fast to the slow population occurs throughout the nucleus. Our results support a model in which RXR has a distinct, highly dynamic nuclear behavior and follows hit-and-run kinetics upon activation