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- fMRI time series (2)
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This work presents the first ILT observations of high redshift blazars and their study in terms of jet evolution, morphology, and interaction with the surrounding medium. Each of these represents a highly topical area of astronomywith a large number of open questions. To better understand Active Galactic Nuclei (AGN) and their fundamental inner workings, new techniques are needed to exploit the full potential of the next generation of radio interferometers. Some of these tools are presented here and applied to one of the latest generation of software radio telescopes. A major focus of the studies presented is on the unification model, where the observed blazars are discussed for their properties to be rotated counterparts of Fanaroff-Riley Class II (FR-II) radio galaxies, when classified as Flat Spectrum Radio Quasars (FSRQs). In addition, multiwavelength information has been included in the analysis. Both studies are feasibility studies that will serve as a basis for future similar studies. The characteristics discussed and their interpretation do not allow conclusions to be drawn for their respective populations. However, by applying them to a larger number of targets, population studies will be possible. The first chapters introduce the necessary topics, AGN, principles of radio observations and ILT, in the necessary depth to provide the reader with a solid knowledge base. They are particularly important for understanding the current limits and influences of uncertainties in the observation, calibration and imaging process. But they also shed light on realistic future improvements. A particular focus is on the development and evolution of the LOw-Frequency ARray (LOFAR)-Very Long Baseline Interferometry (VLBI) pipeline. With the tools at hand, the first study addresses the high redshift blazar S5 0836+710 $(z=2.218)$, which has been observed at various wavelengths and resolutions. It has a disrupted one-sided jet with an associated extended region further out. Despite the excellent wavelength coverage, only the additional ILT observations provided a complete picture of the source. With the data, the extended region could be classified as a hotspot moving at slightly relativistic speeds.. With the ILT data it was also possible to extract the flux of the core region of the AGN, and in projection to reveal the mixed counter-hotspot behind it. This also allowed constraints on jet parameters and environmental properties to be modelled, which were previously inconclusive. Technically, this study shows that the ILT can be used as an effective VLBI array for compact sources with small angular scales. However, the detection of faint components beyond redshifts of $z=2$ may require the capabilities of the Square Kilometre Array (SKA) to provide a significant number of detections to enable statistical conclusions. The second study uses a much improved calibration pipeline to analyse the high redshift blazar GB1508+5714 $(z=4.30)$. The ILT data revealed a previously unseen component in the eastern direction. A spectral index map was generated from the Karl G. Jansky Very Large Array (VLA) data, showing spectral index values of $-1.2_{-0.2}^{+0.4}$ for the western component, steeper than $-1.1$ for the eastern region, and $0.023 \pm 0.007$ for the core. Using the information provided by the ILT observation, as well as multi-wavelength information from other observations ranging from the long radio wavelengths to the $\gamma$ regime, four models were developed to interpret the observed flux with different emission origins. This also allowed to test a proposed interaction channel of the electrons provided by the jet, to cool off via inverse compton scattering with the Cosmic Microwave Background (CMB) photons, rather than by the usual synchrotron emission. This is referred to as cmb quenching in the literature, which could be shown in the study, to be necessary in any case. Finally, one of the four models was considered in which the hotspots in the detected components are unresolved and mixed by the lobe emission, with the X-ray emission coming from the lobes and partially mixed by the bright core region. The results of this preferred model are consistent with hotspots in a state of equipartition and lobes almost so. The study shows that high redshift blazars can be studied with the ILT, and expanding the sample of high redshift blazars resolved at multiple frequencies will allow a statistical study of the population. Finally, this work successfully demonstrates the powerful capabilities of the ILT to address questions that were previously inaccessible. The current state of the LOFAR-VLBI pipeline, when properly executed, allows work on the most challenging objects and will only improve in the future. In particular, this gives a glimpse of the possibilities that SKA will bring to astronomy.
Lung cancer is the main cause of cancer-related deaths worldwide. Despite the availability of several targeted therapies and immunotherapies in the clinics, the prognosis for lung cancer remains poor. A major problem for the low benefit of these therapies is intrinsic and acquired resistance, asking for pre-clinical models for closer investigation of predictive biomarkers for refined personalized medicine and testing of possible combination therapies as well as novel therapeutic approaches to break resistances.
One third of all lung adenocarcinoma harbor mutations in the KRAS gene, of which 39 % are transitions from glycine to cysteine in codon 12 (KRASG12C). Being considered “undruggable” in previous decades, KRASG12C-inhibitors now paved the way into the standard-of-care for lung adenocarcinoma treatment in the clinics. Still, the overall response rates as well as overall survival of patients treated with KRASG12C-inhibitors are sobering. Therefore, 3D KRASG12C-biomarker in vitro models were developed based on a decellularized porcine jejunum (SISmuc) using commercial and PDX-derived cell lines and characterized in regards of epithelial-mesenchymal-transition (EMT), stemness, proliferation, invasion and c-MYC expression as well as the sensitivity towards KRASG12C-inhibiton. The phenotype of lung tumors harboring KRAS mutations together with a c-MYC overexpression described in the literature regarding invasion and proliferation for in vivo models was well represented in the SISmuc models. A higher resistance towards targeted therapies was validated in the 3D models compared to 2D cultures, while reduced viability after treatment with combination therapies were exclusively observed in the 3D models. In the test system neither EMT, stemness nor the c-MYC expression were directly predictive for drug sensitivity. Testing of a panel of combination therapies, a sensitizing effect of the aurora kinase A (AURKA) inhibitor alisertib for the KRASG12C-inhibitor ARS-1620 directly correlating with the level of c-MYC expression in the corresponding 3D models was observed. Thereby, the capability of SISmuc tumor models as an in vitro test system for patient stratification was demonstrated, holding the possibility to reduce animal experiments.
Besides targeted therapies the treatment of NSCLC with oncolytic viruses (OVs) is a promising approach. However, a lack of in vitro models to test novel OVs limits the transfer from bench to bedside. In this study, 3D NSCLC models based on the SISmuc were evaluated for their capability to perform efficacy and risk assessment of oncolytic viruses (OVs) in a pre-clinical setting. Hereby, the infection of cocultures of tumor cells and fibroblasts on the SISmuc with provided viruses demonstrated that in contrast to a wildtype herpes simplex virus 1 (HSV-1) based OV, the attenuated version of the OV exhibited specificity for NSCLC cells with a more advanced and highly proliferative phenotype, while fibroblasts were no longer permissive for infection. This approach introduced SISmuc tumor models as novel test system for in vitro validation of OVs.
Finally, a workflow for validating the efficacy of anti-cancer therapies in 3D tumor spheroids was established for the transfer to an automated platform based on a two-arm-robot system. In a proof-of-concept process, H358 spheroids were characterized and treated with the KRASG12C-inhibitor ARS-1620. A time- and dose-dependent reduction of the spheroid area after treatment was defined together with a live/dead-staining as easy-to-perform and cost-effective assays for automated drug testing that can be readily performed in situ in an automated system.
The unicellular pathogen Trypanosoma brucei is the causative agent of African
trypanosomiasis, an endemic disease prevalent in sub-Saharan Africa. Trypanosoma brucei alternates between a mammalian host and the tsetse fly vector. The extracellular parasite survives in the mammalian bloodstream by periodically exchanging their ˈvariant surface glycoproteinˈ (VSG) coat to evade the host immune response. This antigenic variation is achieved through monoallelic expression of one VSG variant from subtelomeric ˈbloodstream
form expression sitesˈ (BES) at a given timepoint. During the differentiation from the bloodstream form (BSF) to the procyclic form (PCF) in the tsetse fly midgut, the stage specific surface protein is transcriptionally silenced and replaced by procyclins. Due to their subtelomeric localization on the chromosomes, VSG transcription and silencing is partly regulated by homologues of the mammalian telomere complex such as TbTRF, TbTIF2 and TbRAP1 as well as by ˈtelomere-associated proteinsˈ (TelAPs) like TelAP1. To gain more insights into transcription regulation of VSG genes, the identification and characterization of other TelAPs is critical and has not yet been achieved. In a previous study, two biochemical approaches were used to identify other novel TelAPs. By using ˈco-immunoprecipitationˈ (co-IP) to enrich possible interaction partners of TbTRF and by affinity chromatography using telomeric repeat oligonucleotides, a listing of TelAP candidates has been conducted. With this approach TelAP1 was identified as a novel component of the telomere complex, involved in the kinetics of transcriptional BES silencing during BSF to PCF differentiation. To gain further insights into the telomere complex composition, other previously enriched proteins were characterized through a screening process using RNA interference to deplete potential candidates. VSG expression profile changes and overall proteomic changes after depletion were analyzed by mass spectrometry. With this method, one can gain insights into the functions of the proteins and their involvement in VSG expression site regulation. To validate the interaction of proteins enriched by co-IP with TbTRF and TelAP1 and to identify novel interaction proteins, I performed reciprocal affinity purifications of the four most promising candidates (TelAP2, TelAP3, PPL2 and PolIE) and additionally confirmed colocalization of two candidates with TbTRF via immunofluorescence (TelAP2, TelAP3). TelAP3 colocalizes with TbTRF and potentially interacts with TbTRF, TbTIF2, TelAP1 and TelAP2, as well as with two translesion polymerases PPL2 and PolIE in BSF. PPL2 and PolIE seem to be in close contact to each other at the telomeric ends and fulfill different roles as only PolIE is involved in VSG regulation while PPL2 is not. TelAP2 was previously characterized to be associated with telomeres by partially colocalizing with TbTRF and cells show a VSG derepression phenotype when the protein was depleted. Here I show that TelAP2 interacts with the telomere-binding proteins TbTRF and TbTIF2 as well as with the telomere-associated protein TelAP1 in BSF and that TelAP2 depletion results in a loss of TelAP1 colocalization with TbTRF in BSF.
In conclusion, this study demonstrates that characterizing potential TelAPs is effective in gaining insights into the telomeric complex's composition and its role in VSG regulation in Trypanosoma brucei. Understanding these interactions could potentially lead to new therapeutic targets for combatting African trypanosomiasis.
Two-dimensional lattices are in the focus of research in modern solid state physics due to their novel and exotic electronic properties with tremendous potential for seminal future applications. Of particular interest within this research field are quantum spin Hall insulators which are characterized by an insulating bulk with symmetry-protected metallic edge states. For electrons within these one-dimensional conducting channels, spin-momentum locking enables dissipationless transport - a property which promises nothing short of a revolution for electronic devices. So far, however, quantum spin Hall materials require enormous efforts to be realized such as cryogenic temperatures or ultra-high vacuum. A potential candidate to overcome these shortcomings are two-dimensional lattices of the topological semi-metal antimony due to their potential to host the quantum spin Hall effect while offering improved resilience against oxidation.
In this work, two-dimensional lattices of antimony on different substrates, namely Ag(111), InSb(111) and SiC(0001), are investigated regarding their atomic structure and electronic properties with complimentary surface sensitive techniques. In addition, a systematic oxidation study compares the stability of Sb-SiC(0001) with that of the two-dimensional topological insulators bismuthene-SiC(0001) and indenene-SiC(0001).
A comprehensive experimental analysis of the \((\sqrt{3}\times\sqrt{3})R30^\circ\) Sb-Ag(111) surface, including X-ray standing wave measurements, disproves the proclaimed formation of a buckled antimonene lattice in literature. The surface lattice can instead be identified as a metallic Ag\(_2\)Sb surface alloy.
Antimony on InSb(111) shows an unstrained Volmer-Weber island growth due to its large lattice mismatch to the substrate. The concomitant moir\'{e} situation at the interface imprints mainly in a periodic height corrugation of the antimony islands which as observed with scanning tunneling microscopy. On islands with various thicknesses, quasiparticle interference patterns allow to trace the topological surface state of antimony down to the few-layer limit.
On SiC(0001), two different two-dimensional antimony surface reconstructions are identified. Firstly, a metallic triangular $1\times1$ lattice which constitutes the antimony analogue to the topological insulator indenene. Secondly, an insulating asymmetric kagome lattice which represents the very first realized atomic surface kagome lattice.
A comparative, systematic oxidation study of elemental (sub-)monolayer materials on SiC(0001) reveals a high sensitivity of indenene and bismuthene to small dosages of oxygen. An improved resilience is found for Sb-SiC(0001) which, however, oxidizes nevertheless if exposed to oxygen. These surface lattices are therefore not suitable for future applications without additional protective measures.
African trypanosomes are unicellular parasites that cause nagana and sleeping sickness in livestock and man, respectively. The major pathogens for the animal disease include Trypanosoma vivax, T. congolense, and T. brucei brucei, whereas T. b. gambiense and T. b. rhodesiense are responsible for human infections. Given that the bloodstream form (BSF) of African trypanosomes is exclusively extracellular, its cell surface forms a critical boundary with the host environment. The cell surface of the BSF African trypanosomes is covered by a dense coat of immunogenic variant surface glycoproteins (VSGs). This surface protein acts as an impenetrable shield that protects the cells from host immune factors and is also involved in antibody clearance and antigenic variation, which collectively ensure that the parasite stays ahead of the host immune system. Gene expression in T. brucei is markedly different from other eukaryotes: most genes are transcribed as long polycistronic units, processed by trans-splicing a 39-nucleotide mini exon at the 5′ and polyadenylation at the 3′ ends of individual genes to generate the mature mRNA.
Therefore, gene expression in T. brucei is regulated post-transcriptionally, mainly by the action of RNA binding proteins (RBPs) and conserved elements in the 3′ untranslated regions (UTR) of transcripts. The expression of VSGs is highly regulated, and only a single VSG gene is expressed at a time from one of the ~15 subtelomeric domains termed bloodstream expression sites (BES). When cells are engineered to simultaneously express two VSGs, the total VSG mRNA do not exceed the wild type amounts. This suggests that a robust VSG mRNA balancing mechanism exists in T. brucei. The present study uses inducible and constitutive expression of ectopic VSG genes to show that the endogenous VSG mRNA is regulated only if the second VSG is properly targeted to the ER. Additionally, the endogenous VSG mRNA response is triggered when high amounts of the GFP reporter with a VSG 3′UTR is targeted to the ER. Further evidence that non-VSG ER import signals can efficiently target VSGs to the ER is presented. This study suggests that a robust trans-regulation of the VSG mRNA is elicited at the ER through a feedback loop to keep the VSG transcripts in check and avoid overshooting the secretory pathway capacity.
Further, it was shown that induction of expression of the T. vivax VSG ILDat1.2 in T. brucei causes a dual cell cycle arrest, with concomitant upregulation of the protein associated with differentiation (PAD1) expression. It could be shown that T. vivax VSG ILDat1.2 can only be sufficiently expressed in T. brucei after replacing its native GPI signal peptide with that of a T. brucei VSG. Taken together, these data indicate that inefficient VSG GPI anchoring and expression of low levels of the VSG protein can trigger differentiation from slender BSF to stumpy forms. However, a second T. vivax VSG, ILDat2.1, is not expressed in T. brucei even after similar modifications to its GPI signals. An X-ray crystallography approach was utilized to solve the N-terminal domain (NTD) structure of VSG ILDat1.2. This is first structure of a non-T. brucei VSG, and the first of a surface protein of T. vivax to be solved. VSG ILDat1.2 NTD maintains the three-helical bundle scaffold conserved in T. brucei surface proteins. However, it is likely that there are variations in the architecture of the membrane proximal region of the ILDat1.2 NTD and its CTD from T. brucei VSGs. The tractable T. brucei system is presented as a model that can be used to study surface proteins of related trypanosome species, thus creating avenues for further characterization of trypanosome surface coats.
Electrochemical impedance spectroscopy (EIS) is a valuable technique analyzing electrochemical behavior of biological systems such as electrical characterization of cells and biomolecules, drug screening, and biomaterials in biomedical field. In EIS, an alternating current (AC) power signal is applied to the biological system, and the impedance of the system is measured over a range of frequencies.
In vitro culture models of endothelial or epithelial barrier tissue can be achieved by culturing barrier tissue on scaffolds made with synthetic or biological materials that provide separate compartments (apical and basal sides), allowing for further studies on drug transport. EIS is a great candidate for non-invasive and real-time monitoring of the electrical properties that correlate with barrier integrity during the tissue modeling. Although commercially available transendothelial/transepithelial electrical resistance (TEER) measurement devices are widely used, their use is particularly common in static transwell culture. EIS is considered more suitable than TEER measurement devices in bioreactor cultures that involve dynamic fluid flow to obtain accurate and reliable measurements. Furthermore, while TEER measurement devices can only assess resistance at a single frequency, EIS measurements can capture both resistance and capacitance properties of cells, providing additional information about the cellular barrier's characteristics across various frequencies. Incorporating EIS into a bioreactor system requires the careful optimization of electrode integration within the bioreactor setup and measurement parameters to ensure accurate EIS measurements. Since bioreactors vary in size and design depending on the purpose of the study, most studies have reported using an electrode system specifically designed for a particular bioreactor. The aim of this work was to produce multi-applicable electrodes and established methods for automated non-invasive and real-time monitoring using the EIS technique in bioreactor cultures. Key to the electrode material, titanium nitride (TiN) coating was fabricated on different substrates (materials and shape) using physical vapor deposition (PVD) and housed in a polydimethylsiloxane (PDMS) structure to allow the electrodes to function as independent units. Various electrode designs were evaluated for double-layer capacitance and morphology using EIS and scanning electron microscopy (SEM), respectively. The TiN-coated tube electrode was identified as the optimal choice. Furthermore, EIS measurements were performed to examine the impact of influential parameters related to culture conditions on the TiN-coated electrode system. In order to demonstrate the versatility of the electrodes, these electrodes were then integrated into in different types of perfusion bioreactors for monitoring barrier cells. Blood-brain barrier (BBB) cells were cultured in the newly developed dynamic flow bioreactor, while human umblical vascular endothelial cells (HUVECs) and Caco-2 cells were cultured in the miniature hollow fiber bioreactor (HFBR). As a result, the TiN-coated tube electrode system enabled investigation of BBB barrier integrity in long-term bioreactor culture. While EIS measurement could not detect HUVECs electrical properties in miniature HFBR culture, there was the possibility of measuring the barrier integrity of Caco-2 cells, indicating potential usefulness for evaluating their barrier function. Following the bioreactor cultures, the application of the TiN-coated tube electrode was expanded to hemofiltration, based on the hypothesis that the EIS system may be used to monitor clotting or clogging phenomena in hemofiltration. The findings suggest that the EIS monitoring system can track changes in ion concentration of blood before and after hemofiltration in real-time, which may serve as an indicator of clogging of filter membranes. Overall, our research demonstrates the potential of TiN-coated tube electrodes for sensitive and versatile non-invasive monitoring in bioreactor cultures and medical devices.
Barth Syndrome (BTHS) is an inherited X-chromosomal linked disorder, characterized by early development of cardiomyopathy, immune system defects, skeletal muscle myopathy and growth retardation. The disease displays a wide variety of symptoms including heart failure, exercise intolerance and fatigue due to the muscle weakness. The cause of the disease are mutations in the gene encoding for the mitochondrial transacylase Tafazzin (TAZ), which is important for remodeling of the phospholipid cardiolipin (CL). All mutations result in a pronounced decrease of the functional enzyme leading to an increase of monolysocardiolipin (MLCL), the precursor of mature CL, and a decrease in mature CL itself. CL is a hallmark phospholipid of mitochondrial membranes, highly enriched in the inner mitochondrial membrane (IMM). It is not only important for the formation of the cristae structures, but also for the function of different protein complexes associated with the mitochondrial membrane. Reduced levels of mature CL cause remodeling of the respiratory chain supercomplexes, impaired respiration, defects in the Krebs cycle and a loss of mitochondrial calcium uniporter (MCU) protein. The defective Ca2+ handling causes impaired redox homeostasis and energy metabolism resulting in cellular arrhythmias and defective electrical conduction. In an uncompensated situation, blunting mitochondrial Ca2+ uptake provokes increased mitochondrial emission of H2O2 during workload transitions, related to oxidation of NADPH, which is required to regenerate anti-oxidative enzymes. However, in the hearts and cardiac myocytes of mice with a global knock-down of the Taz gene (Taz-KD), no increase in mitochondrial ROS was observed, suggesting that other metabolic pathways may have compensated for reduced Krebs cycle activation.
The healthy heart produces most of its energy by consuming fatty acids. In this study, the fatty acid uptake into mitochondria and their further degradation was investigated, which showed a switch of the metabolism in general in the Taz-KD mouse model. In vivo studies revealed an increase of glucose uptake into the heart and decreased fatty acid uptake and oxidation. Disturbed energy conversion resulted in activation of retrograde signaling pathways, implicating overall changes in the cell metabolism. Upregulated integrated stress response (ISR) was confirmed by increased levels of the downstream target, i.e., the activating transcription factor 4 (ATF4). A Tafazzin knockout mouse embryonal fibroblast cell model (TazKO) was used to inhibit the ISR using siRNA transfection or pharmaceutical inhibition. This verified the central role of
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the ISR in regulating the metabolism in BTHS. Moreover, an increased metabolic flux into glutathione biosynthesis was observed, which supports redox homeostasis. In vivo PET-CT scans depicted elevated activity of the xCT system in the BTHS mouse heart, which transports essential amino acids for the biosynthesis of glutathione precursors. Furthermore, the stress induced signaling pathway also affected the glutamate metabolism, which fuels into the Krebs cycle via -ketoglutarate and therefore supports energy converting pathways. In summary, this thesis provides novel insights into the energy metabolism and redox homeostasis in Barth syndrome cardiomyopathy and its regulation by the integrated stress response, which plays a central role in the metabolic alterations. The aim of the thesis was to improve the understanding of these metabolic changes and to identify novel targets, which can provide new possibilities for therapeutic intervention in Barth syndrome.
Graphs provide a key means to model relationships between entities.
They consist of vertices representing the entities,
and edges representing relationships between pairs of entities.
To make people conceive the structure of a graph,
it is almost inevitable to visualize the graph.
We call such a visualization a graph drawing.
Moreover, we have a straight-line graph drawing
if each vertex is represented as a point
(or a small geometric object, e.g., a rectangle)
and each edge is represented as a line segment between its two vertices.
A polyline is a very simple straight-line graph drawing,
where the vertices form a sequence according to which the vertices are connected by edges.
An example of a polyline in practice is a GPS trajectory.
The underlying road network, in turn, can be modeled as a graph.
This book addresses problems that arise
when working with straight-line graph drawings and polylines.
In particular, we study algorithms
for recognizing certain graphs representable with line segments,
for generating straight-line graph drawings,
and for abstracting polylines.
In the first part, we first examine,
how and in which time we can decide
whether a given graph is a stick graph,
that is, whether its vertices can be represented as
vertical and horizontal line segments on a diagonal line,
which intersect if and only if there is an edge between them.
We then consider the visual complexity of graphs.
Specifically, we investigate, for certain classes of graphs,
how many line segments are necessary for any straight-line graph drawing,
and whether three (or more) different slopes of the line segments
are sufficient to draw all edges.
Last, we study the question,
how to assign (ordered) colors to the vertices of a graph
with both directed and undirected edges
such that no neighboring vertices get the same color
and colors are ascending along directed edges.
Here, the special property of the considered graph is
that the vertices can be represented as intervals
that overlap if and only if there is an edge between them.
The latter problem is motivated by an application
in automated drawing of cable plans with vertical and horizontal line segments,
which we cover in the second part.
We describe an algorithm that
gets the abstract description of a cable plan as input,
and generates a drawing that takes into account
the special properties of these cable plans,
like plugs and groups of wires.
We then experimentally evaluate the quality of the resulting drawings.
In the third part, we study the problem of abstracting (or simplifying)
a single polyline and a bundle of polylines.
In this problem, the objective is to remove as many vertices as possible from the given polyline(s)
while keeping each resulting polyline sufficiently similar to its original course
(according to a given similarity measure).
This thesis investigates the charged moments and the symmetry-resolved
entanglement entropy in the context of the AdS3/CFT2 duality. In the
first part, I focus on the holographic U(1) Chern-Simons-Einstein gravity,
a toy model of AdS3/CFT2 with U(1) Kac-Moody symmetry. I
start with the vacuum background with a single entangling interval. I
show that, apart from a partition function in the grand canonical ensemble,
the charged moments can also be interpreted as the two-point
function of vertex operators on the replica surface. For the holographic
description, I propose a duality between the bulk U(1) Wilson line and
the boundary vertex operators. I verify this duality by deriving the
effective action for the Chern-Simons fields and comparing the result
with the vertex correlator. In the twist field approach, I show that the
charged moments are given by the correlation function of the charged
twist operators and the additional background operators. To solve the
correlation functions involved, I prove the factorization of the U(1) extended
conformal block into a U(1) block and a Virasoro block. The
general expression for the U(1) block is derived by directly summing
over the current descendant states, and the result shows that it takes
an identical form as the vertex correlators. This leads to the conclusion
that the disjoint Wilson lines compute the neutral U(1) block. The final
result for the symmetry-resolved entanglement entropy shows that
it is always charge-independent in this model. In the second part, I
study charged moments in higher spin holography, where the boundary
theory is a CFT with W3 symmetry. I define the notion of the
higher spin charged moments by introducing a spin-3 modular charge
operator. Restricting to the vacuum background with a single entangling
interval, I employ the grand canonical ensemble interpretation
and calculate the charged moments via the known higher spin black
hole solution. On the CFT side, I perform a perturbative expansion for
the higher spin charged moments in terms of the connected correlation
functions of the spin-3 modular charge operators. Using the recursion
relation for the correlation functions of the W3 currents, I evaluate the
charged moments up to the quartic order of the chemical potential. The
final expression matches with the holographic result. My results both
for U(1) Chern-Simons Einstein gravity and W3 higher spin gravity
constitute novel checks of the AdS3/CFT2 correspondence.
Over the years, hydrogels have been developed and used for a huge variety of different applications ranging from drug delivery devices to medical products. In this thesis, a poly(2-methyl-2-oxazoline) (POx) / poly(2-n-propyl-2-oxazine) (POzi) bioink was modified and analyzed for the use in biofabrication and targeted drug delivery. In addition, the protein fibrinogen (Fbg) was genetically modified for an increased stability towards plasmin degradation for its use as wound sealant.
In Chapter 1, a thermogelling, printable POx/POzi-based hydrogel was modified with furan and maleimide moieties in the hydrophilic polymer backbone facilitating post-printing maturation of the constructs via Diels-Alder chemistry. The modification enabled long-term stability of the hydrogel scaffolds in aqueous solutions which is necessary for applications in biofabrication or tissue engineering. Furthermore, we incorporated RGD-peptides into the hydrogel which led to cell adhesion and elongated morphology of fibroblast cells seeded on top of the scaffolds. Additional printing experiments demonstrate that the presented POx/POzi system is a promising platform for the use as a bioink in biofabrication.
Chapter 2 highlights the versatility of the POx/POzi hydrogels by adapting the system to a use in targeted drug delivery. We used a bioinspired approach for a bioorthogonal conjugation of insulin-like growth factor I (IGF-I) to the polymer using an omega-chain-end dibenzocyclooctyne (DBCO) modification and a matrix metalloprotease-sensitive peptide linker. This approach enabled a bioresponsive release of IGF-I from hydrogels as well as spatial control over the protein distribution in 3D printed constructs which makes the system a candidate for the use in personalized medicine.
Chapter 3 gives a general overview over the necessity of wound sealants and the current generations of fibrin sealants on the market including advantages and challenges. Furthermore, it highlights trends and potential new strategies to tackle current problems and broadens the toolbox for future generations of fibrin sealants.
Chapter 4 applies the concepts of recombinant protein expression and molecular engineering to a novel generation of fibrin sealants. In a proof-of-concept study, we developed a new recombinant fibrinogen (rFbg) expression protocol and a Fbg mutant that is less susceptible to plasmin degradation. Targeted lysine of plasmin cleavage sites in Fbg were exchanged with alanine or histidine in different parts of the molecule. The protein was recombinantly produced and restricted plasmin digest was analyzed using high resolution mass spectrometry. In addition to that, we developed a novel time resolved screening protocol for the detection of new potential plasmin cleavage sites for further amino acid exchanges in the fibrin sealant.
Cognition refers to the ability to of animals to acquire, process, store and use vital information from the environment. Cognitive processes are necessary to predict the future and reduce the uncertainty of the ever-changing environment. Classically, research on animal cognition focuses on decisive cognitive tests to determine the capacity of a species by the testing the ability of a few individuals. This approach views variability between these tested key individuals as unwanted noise and is thus often neglected. However, inter-individual variability provides important insights to behavioral plasticity, cognitive specialization and brain modularity. Honey bees Apis mellifera are a robust and traditional model for the study of learning, memory and cognition due to their impressive capabilities and rich behavioral repertoire. In this thesis I have applied a novel view on the learning abilities of honey bees by looking explicitly at individual differences in a variety of learning tasks. Are some individual bees consistently smarter than some of her sisters? If so, will a smart individual always perform good independent of the time, the context and the cognitive requirements or do bees show distinct isolated ‘cognitive modules’?
My thesis presents the first comprehensive investigation of consistent individual differences in the cognitive abilities of honey bees. To speak of an individual as behaving consistently, a crucial step is to test the individual multiple times to examine the repeatability of a behavior. I show that free-flying bees remain consistent in a visual discrimination task for three consecutive days. Successively, I explored individual consistency in cognitive proficiency across tasks involving different sensory modalities, contexts and cognitive requirements. I found that free-flying bees show a cognitive specialization between visual and olfactory learning but remained consistent across a simple discrimination task and a complex concept learning task. I wished to further explore individual consistency with respect to tasks of different cognitive complexity, a question that has never been tackled before in an insect. I thus performed a series of four experiments using either visual or olfactory stimuli and a different training context (free-flying and restrained) and tested bees in a discrimination task, reversal learning and negative patterning. Intriguingly, across all these experiments I evidenced the same results: The bees’ performances were consistent across the discrimination task and reversal learning and negative patterning respectively. No association was evidenced between reversal learning and negative patterning. After establishing the existence of consistent individual differences in the cognitive proficiency of honey bees I wished to determine factors which could underlie these differences. Since genetic components are known to underlie inter-individual variability in learning abilities, I studied the effects of genetics on consistency in cognitive proficiency by contrasting bees originating from either from a hive with a single patriline (low genetic diversity) or with multiple patrilines (high genetic diversity). These two groups of bees showed differences in the patterns of individually correlated performances, indicating a genetic component accounts for consistent cognitive individuality. Another major factor underlying variability in learning performances is the individual responsiveness to sucrose solution and to visual stimuli, as evidenced by many studies on restrained bees showing a positive correlation between responsiveness to task relevant stimuli and learning performances. I thus tested whether these relationships between sucrose/visual responsiveness and learning performances are applicable for free-flying bees. Free-flying bees were again subjected to reversal learning and negative patterning and subsequently tested in the laboratory for their responsiveness to sucrose and to light. There was no evidence of a positive relationship between sucrose/visual responsiveness and neither performances of free-flying bees in an elemental discrimination, reversal learning and negative patterning. These findings indicate that relationships established between responsiveness to task relevant stimuli and learning proficiency established in the laboratory with restrained bees might not hold true for a completely different behavioral context i.e. for free-flying bees in their natural environment.
These results show that the honey bee is an excellent insect model to study consistency in cognitive proficiency and to identify the underlying factors. I mainly discuss the results with respect to the question of brain modularity in insects and the adaptive significance of individuality in cognitive abilities for honey bee colonies. I also provide a proposition of research questions which tie in this theme of consistent cognitive proficiency and could provide fruitful areas for future research.
Among the defense strategies developed in microbes over millions of years, the innate adaptive CRISPR-Cas immune systems have spread across most of bacteria and archaea. The flexibility, simplicity, and specificity of CRISPR-Cas systems have laid the foundation for CRISPR-based genetic tools. Yet, the efficient administration of CRISPR-based tools demands rational designs to maximize the on-target efficiency and off-target specificity. Specifically, the selection of guide RNAs (gRNAs), which play a crucial role in the target recognition of CRISPR-Cas systems, is non-trivial. Despite the fact that the emerging machine learning techniques provide a solution to aid in gRNA design with prediction algorithms, design rules for many CRISPR-Cas systems are ill-defined, hindering their broader applications.
CRISPR interference (CRISPRi), an alternative gene silencing technique using a catalytically dead Cas protein to interfere with transcription, is a leading technique in bacteria for functional interrogation, pathway manipulation, and genome-wide screens. Although the application is promising, it also is hindered by under-investigated design rules. Therefore, in this work, I develop a state-of-art predictive machine learning model for guide silencing efficiency in bacteria leveraging the advantages of feature engineering, data integration, interpretable AI, and automated machine learning. I first systematically investigate the influential factors that attribute to the extent of depletion in multiple CRISPRi genome-wide essentiality screens in Escherichia coli and demonstrate the surprising dominant contribution of gene-specific effects, such as gene expression level. These observations allowed me to segregate the confounding gene-specific effects using a mixed-effect random forest (MERF) model to provide a better estimate of guide efficiency, together with the improvement led by integrating multiple screens. The MERF model outperformed existing tools in an independent high-throughput saturating screen. I next interpret the predictive model to extract the design rules for robust gene silencing, such as the preference for cytosine and disfavoring for guanine and thymine within and around the protospacer adjacent motif (PAM) sequence. I further incorporated the MERF model in a web-based tool that is freely accessible at www.ciao.helmholtz-hiri.de.
When comparing the MERF model with existing tools, the performance of the alternative gRNA design tool optimized for CRISPRi in eukaryotes when applied to bacteria was far from satisfying, questioning the robustness of prediction algorithms across organisms. In addition, the CRISPR-Cas systems exhibit diverse mechanisms albeit with some similarities. The captured predictive patterns from one dataset thereby are at risk of poor generalization when applied across organisms and CRISPR-Cas techniques. To fill the gap, the machine learning approach I present here for CRISPRi could serve as a blueprint for the effective development of prediction algorithms for specific organisms or CRISPR-Cas systems of interest. The explicit workflow includes three principle steps: 1) accommodating the feature set for the CRISPR-Cas system or technique; 2) optimizing a machine learning model using automated machine learning; 3) explaining the model using interpretable AI. To illustrate the applicability of the workflow and diversity of results when applied across different bacteria and CRISPR-Cas systems, I have applied this workflow to analyze three distinct CRISPR-Cas genome-wide screens. From the CRISPR base editor essentiality screen in E. coli, I have determined the PAM preference and sequence context in the editing window for efficient editing, such as A at the 2nd position of PAM, A/TT/TG downstream of PAM, and TC at the 4th to 5th position of gRNAs. From the CRISPR-Cas13a screen in E. coli, in addition to the strong correlation with the guide depletion, the target expression level is the strongest predictor in the model, supporting it as a main determinant of the activation of Cas13-induced immunity and better characterizing the CRISPR-Cas13 system. From the CRISPR-Cas12a screen in Klebsiella pneumoniae, I have extracted the design rules for robust antimicrobial activity across K. pneumoniae strains and provided a predictive algorithm for gRNA design, facilitating CRISPR-Cas12a as an alternative technique to tackle antibiotic resistance.
Overall, this thesis presents an accurate prediction algorithm for CRISPRi guide efficiency in bacteria, providing insights into the determinants of efficient silencing and guide designs. The systematic exploration has led to a robust machine learning approach for effective model development in other bacteria and CRISPR-Cas systems. Applying the approach in the analysis of independent CRISPR-Cas screens not only sheds light on the design rules but also the mechanisms of the CRISPR-Cas systems. Together, I demonstrate that applied machine learning paves the way to a deeper understanding and a broader application of CRISPR-Cas systems.
Anxiety patients overgeneralize fear, also because of an inability to perceptually discriminate threat and safety signals. Therefore, some studies have developed discrimination training that successfully reduced the occurrence of fear generalization. The present work is the first to take a treatment-like approach by using discrimination training after generalization has occurred. Therefore, two studies were conducted with healthy participants using the same fear conditioning and generalization paradigm, with two faces as conditioned stimuli (CSs), and four facial morphs between CSs as generalization stimuli (GSs). Only one face (CS+) was followed by a loud scream (unconditioned stimulus, US). In Study 1, participants underwent either fear-relevant (discriminating faces) or fear-irrelevant discrimination training (discriminating width of lines) or a non-discriminative control training between the two generalization tests, each with or without feedback (n = 20 each). Generalization of US expectancy was reduced more effectively by fear-relevant compared to fear-irrelevant discrimination training. However, neither discrimination training was more effective than non-discriminative control training. Moreover, feedback reduced generalization of US expectancy only in discrimination training. Study 2 was designed to replicate the effects of the discrimination-training conditions in a large sample (N = 244) and examine their benefits in individuals at risk for anxiety disorders. Again, feedback reduced fear generalization particularly well for US expectancy. Fear relevance was not confirmed to be particularly fear-reducing in healthy participants, but may enhance training effects in individuals at risk of anxiety disorder. In summary, this work provides evidence that existing fear generalization can be reduced by discrimination training, likely involving several (higher-level) processes besides perceptual discrimination (e.g., motivational mechanisms in feedback conditions). Its use may be promising as part of individualized therapy for patients with difficulty discriminating similar stimuli.
Interactions between host and pathogen determine the development, progression and outcomes
of disease. Medicine benefits from better descriptions of these interactions through increased
precision of prevention, diagnosis and treatment of diseases. Single-cell genomics is a
disruptive technology revolutionizing science by increasing the resolution with which we study
diseases. Cell type specific changes in abundance or gene expression are now routinely investigated
in diseases. Meanwhile, detecting cellular phenotypes across diseases can connect
scientific fields and fuel discovery. Insights acquired through systematic analysis of high resolution
data will soon be translated into clinical practice and improve decision making. Therefore,
the continued use of single-cell technologies and their application towards clinical samples will
improve molecular interpretation, patient stratification, and the prediction of outcomes.
In the past years, I was fortunate to participate in interdisciplinary research groups bridging
biology, clinical research and data science. I was able to contribute to diverse projects through
computational analysis and biological interpretation of sequencing data. Together, we were
able to discover cellular phenotypes that influence disease progression and outcomes as well
as the response to treatment. Here, I will present four studies that I have conducted in my PhD.
First, we performed a case study of relapse from cell-based immunotherapy in Multiple Myeloma.
We identified genomic deletion of the epitope as mechanism of immune escape and implicate
heterozygosity or monosomy of the genomic locus at baseline as a potential risk factor. Second,
we investigated the pathomechanisms of severe COVID-19 at the earliest stage of the COVID-
19 pandemic in Germany in March 2020. We discovered that profibrotic macrophages and
lung fibrosis can be caused by SARS-CoV-2 infection. Third, we used a mouse model of chronic
infection with Staphylococcus aureus that causes Osteomyelitis similar to the human disease.
We were able to identify dysregulated immunometabolism associated with the generation of
myeloid-derived suppressor cells (MDSC). Fourth, we investigated Salmonella infection of the
human small intestine in an in vitro model and describe features of pathogen invasion and host
response.
Overall, I have been able to successfully employ single-cell sequencing to discover important
aspects of diseases ranging from development to treatment and outcome. I analyzed samples
from the clinics, human donors, mouse models and organoid models to investigate different
aspects of diseases and managed to integrate data across sample types, technologies and
diseases. Based on successful studies, we increased our efforts to combine data from multiple
sources to build comprehensive references for the integration of large collections of clinical
samples. Our findings exemplify how single-cell sequencing can improve clinical research and
highlights the potential of mechanistic discoveries to drive precision medicine.
Since the prediction of the quantum spin Hall effect in graphene by Kane and Mele, \(Z_2\) topology in hexagonal monolayers is indissociably linked to high-symmetric honeycomb lattices. This thesis breaks with this paradigm by focusing on topological phases in the fundamental two-dimensional hexagonal crystal, the triangular lattice. In contrast to Kane-Mele-type systems, electrons on the triangular lattice profit from a sizable, since local, spin-orbit coupling (SOC) and feature a non-trivial ground state only in the presence of inversion symmetry breaking. This tends to displace the valence charge form the atomic position. Therefore, all non-trivial phases are real-space obstructed. Inspired by the contemporary conception of topological classification of electronic systems, a comprehensive lattice and band symmetry analysis of insulating phases of a \(p\)-shell on the triangular lattice is presented. This reveals not only the mechanism at the origin of band topology, the competition of SOC and symmetry breaking, but sheds also light on the electric polarization arising from a displacement of the valence charge centers from the nuclei, i. e., real-space obstruction. In particular, the competition of SOC versus horizontal and vertical reflection symmetry breaking gives rise to four topologically distinct insulating phases: two kinds of quantum spin Hall insulators (QSHI), an atomic insulator and a real-space obstructed higher-order topological insulator. The theoretical analysis is complemented with state-of-the-art first principles calculations and experiments on trigonal monolayer adsorbate systems. This comprises the recently discovered triangular QSHI indenene, formed by In atoms, and focuses on its topological classification and real-space obstruction. The analysis reveals Kane-Mele-type valence bands which profit from the atomic SOC of the triangular lattice. The realization of a HOTI is proposed by reducing SOC by considering lighter adsorbates. Further the orbital Rashba effect is analyzed in AgTe, a consequence of mirror symmetry breaking, the formation of local angular momentum polarization and SOC. As an outlook beyond topology, the Fermi surface and electronic susceptibility of Group V adsorbates on silicon carbide are investigated.
In summary, this thesis elucidates the interplay of symmetry breaking and SOC on the triangular lattice, which can promote non-trivial insulating phase.
Adoptive cellular immunotherapy with chimeric antigen receptor (CAR) T cells is highly effective in haematological malignancies. This success, however, has not been achieved in solid tumours so far. In contrast to hematologic malignancies, solid tumours include a hostile tumour microenvironment (TME), that poses additional challenges for curative effects and consistent therapeutic outcome. These challenges manifest in physical and immunological barriers that dampen efficacy of the CAR T cells. Preclinical testing of novel cellular immunotherapies is performed mainly in 2D cell culture and animal experiments. While 2D cell culture is an easy technique for efficacy analysis, animal studies reveal information about toxicity in vivo. However, 2D cell culture cannot fully reflect the complexity observed in vivo, because cells are cultured without anchorage to a matrix and only short-term periods are feasible. Animal studies provide a more complex tissue environment, but xenografts often lack human stroma and tumour inoculation occurs mostly ectopically. This emphasises the need for standardisable and scalable tumour models with incorporated TME-aspects, which enable preclinical testing with enhanced predictive value for the clinical outcome of immunotherapies. Therefore, microphysiologic 3D tumour models based on the biological SISmuc (Small Intestinal mucosa and Submucosa) matrix with preserved basement membrane were engaged and improved in this work to serve as a modular and versatile tumour model for efficacy testing of CAR T cells. In order to reflect a variety of cancer entities, TME-aspects, long-term stability and to enhance the read-out options they were further adapted to achieve scalable and standardisable defined microphysiologic 3D tumour models. In this work, novel culture modalities (semi-static, sandwich-culture) were characterised and established that led to an increased and organised tissue generation and long-term stability. Application of the SISmuc matrix was extended to sarcoma and melanoma models and serial bioluminescence intensity (BLI)-based in vivo imaging analysis was established in the microphysiologic 3D tumour models, which represents a time-efficient read-out method for quality evaluation of the models and treatment efficacy analysis, that is independent of the cell phenotype. Isolation of cancer-associated-fibroblasts (CAFs) from lung (tumour) tissue was demonstrated and CAF-implementation further led to stromal-enriched microphysiologic 3D tumour models with in vivo-comparable tissue-like architecture. Presence of CAFs was confirmed by CAF-associated markers (FAP, α-SMA, MMP-2/-9) and cytokines correlated with CAF phenotype, angiogenesis, invasion and immunomodulation. Additionally, an endothelial cell barrier was implemented for static and dynamic culture in a novel bioreactor set-up, which is of particular interest for the analysis of immune cell diapedesis. Studies in microphysiologic 3D Ewing’s sarcoma models indicated that sarcoma cells could be sensitised for GD2-targeting CAR T cells. After enhancing the scale of assessment of the microphysiologic 3D tumour models and improving them for CAR T cell testing, the tumour models were used to analyse their sensitivity towards differently designed receptor tyrosine kinase-like orphan receptor 1 (ROR1) CAR T cells and to study the effects of the incorporated TME-aspects on the CAR T cell treatment respectively. ROR1 has been described as a suitable target for several malignancies including triple negative breast cancer (TNBC), as well as lung cancer. Therefore, microphysiologic 3D TNBC and lung cancer models were established. Analysis of ROR1 CAR T cells that differed in costimulation, spacer length and targeting domain, revealed, that the microphysiologic 3D tumour models are highly sensitive and can distinguish optimal from sub-optimal CAR design. Here, higher affinity of the targeting domain induced stronger anti-tumour efficacy and anti-tumour function depended on spacer length, respectively. Long-term treatment for 14 days with ROR1 CAR T cells was demonstrated in dynamic microphysiologic 3D lung tumour models, which did not result in complete tumour cell removal, whereas direct injection of CAR T cells into TNBC and lung tumour models represented an alternative route of application in addition to administration via the medium flow, as it induced strong anti-tumour response. Influence of the incorporated TME-aspects on ROR1 CAR T cell therapy represented by CAF-incorporation and/or TGF-β supplementation was analysed. Presence of TGF-β revealed that the specific TGF-β receptor inhibitor SD-208 improves ROR1 CAR T cell function, because it effectively abrogated immunosuppressive effects of TGF-β in TNBC models. Implementation of CAFs should provide a physical and immunological barrier towards ROR1 CAR T cells, which, however, was not confirmed, as ROR1 CAR T cell function was retained in the presence of CAFs in stromal-enriched microphysiologic 3D lung tumour models. The absence of an effect of CAF enrichment on CAR T cell efficacy suggests a missing component for the development of an immunosuppressive TME, even though immunomodulatory cytokines were detected in co-culture models. Finally, improved gene-edited ROR1 CAR T cells lacking exhaustion-associated genes (PD-1, TGF-β-receptor or both) were challenged by the combination of CAF-enrichment and TGF-β in microphysiologic 3D TNBC models. Results indicated that the absence of PD-1 and TGF-β receptor leads to improved CAR T cells, that induce strong tumour cell lysis, and are protected against the hostile TME. Collectively, the microphysiologic 3D tumour models presented in this work reflect aspects of the hostile TME of solid tumours, engage BLI-based analysis and provide long-term tissue homeostasis. Therefore, they present a defined, scalable, reproducible, standardisable and exportable model for translational research with enhanced predictive value for efficacy testing and candidate selection of cellular immunotherapy, as exemplified by ROR1 CAR T cells.
Colon carcinomas (CRC) are statistically among the most fatal cancer types and hence one of the top reasons for premature mortality in the developed world. CRC cells are characterized by high proliferation rates caused by deregulation of gene transcription of proto-oncogenes and general chromosomal instability. On macroscopic level, CRC cells show a strongly altered nutrient and energy metabolism.
This work presents research to understand general links between the metabolism and transcription alteration. Mainly focussing on glutamine dependency, shown in colon carcinoma cells and expression pathways of the pro-proliferation protein c-MYC.
Previous studies showed that a depletion of glutamine in the cultivation medium of colon carcinoma cell lines caused a proliferation arrest and a strong decrease of overall c-MYC levels. Re-addition of glutamine quickly replenished c-MYC levels through an unknown mechanism. Several proteins altering this regulation mechanism were identified and proposed as possible starting point for further in detail studies to unveil the precise biochemical pathway controlling c-MYC translation repression and reactivation in a rapid manner.
On a transcriptional level the formation of RNA:DNA hybrids, so called R-loops, was observed under glutamine depleted conditions. The introduction and overexpression of RNaseH1, a R-loop degrading enzyme, in combination with an ectopically expressed c-MYC variant, independent of cellular regulation mechanisms by deleting the regulatory 3’-UTR of the c-MYC gene, lead to a high rate of apoptotic cells in culture. Expression of a functionally inactive variant of RNaseH1 abolished this effect. This indicates a regulatory function of R-loops formed during glutamine starvation in the presence of c-MYC protein in a cell. Degradation of R-loops and high c-MYC levels in this stress condition had no imminent effect on the cell cycle progression is CRC cells but disturbed the nucleotide metabolism. Nucleotide triphosphates were strongly reduced in comparison to starving cells without R-loop degradation and proliferating cells.
This study proposes a model of a terminal cycle of transcription termination, unregulated initiation and elongation of transcription leading to a depletion of energy resources of cells. This could finally lead to high apoptosis of the cells. Sequencing experiments to determine a coinciding of termination sites and R-loop formation sides failed so far but show a starting point for further studies in this essential survival mechanism involving R-loop formation and c-MYC downregulation.
Learning accompanies us throughout our lives, from early childhood education through
school, training and university to learning at work. However, much of what we learn is quickly
forgotten. The use of practice tests is a learning strategy that contributes to the acquisition of
sustainable knowledge, i.e. knowledge that is permanently available and can be retrieved when
it is needed. This dissertation first presents findings from previous research on testing in real
educational contexts and discusses theoretically why certain learner or situational
characteristics might influence the effectiveness of the testing effect. Furthermore, a cycle of
three experiments is presented, which were used to investigate whether the positive effect of
practice tests on retention (testing effect) depends on personal or situational characteristics and
also promotes the retention of lecture content that was not directly tested (transfer) in the context
of regular psychology lectures in teacher training courses. In an additional chapter, feedback
from students on the implementation of the study in the classroom context is examined in more
detail. Finally, the results of the three studies are discussed and placed in relation to the theories
presented. The central conclusion from the studies presented is that the testing effect appears to
be a very effective learning strategy that can be used effectively in university teaching and leads
to better learning outcomes regardless of learner characteristics. However, the practice tests
should cover the entire range of relevant content, as transfer effects to non-tested content are
not to be expected.
This work illustrates how the targeted tailoring of supramolecular cavities can not only accomplish high binding due to optimized stereoelectronic shape matches between host and guest but also how molecular engineering of the binding site by a refined substitution periphery of the cavity makes enantiospecific guest recognition and host mediated chirality transfer feasible. Moreover, an enzyme mimic, following the Pauling-Jencks model of enzyme catalysis was realized by the smart design of a PBI host composed of moderately twisted chromophores, which drives the substrate inversion according to the concepts of transition state stabilization and ground state destabilization. The results of this thesis contribute to a better understanding of structure-specific interactions in host-guest complexes as well as the corresponding thermodynamic and kinetic properties and represent an appealing blueprint for the design of new artificial complex structures of high stereoelectronic shape complementarity in order to achieve the goal of sophisticated supramolecular receptors and enzyme mimicry.
In this work, we evaluate the status of both theory and empirical evidence in the field of experimental rest-break research based on a framework that combines mental-chronometry and psychometric-measurement theory. To this end, we (1) provide a taxonomy of rest breaks according to which empirical studies can be classified (e.g., by differentiating between long, short, and micro-rest breaks based on context and temporal properties). Then, we (2) evaluate the theorizing in both the basic and applied fields of research and explain how popular concepts (e.g., ego depletion model, opportunity cost theory, attention restoration theory, action readiness, etc.) relate to each other in contemporary theoretical debates. Here, we highlight differences between all these models in the light of two symbolic categories, termed the resource-based and satiation-based model, including aspects related to the dynamics and the control (strategic or non-strategic) mechanisms at work. Based on a critical assessment of existing methodological and theoretical approaches, we finally (3) provide a set of guidelines for both theory building and future empirical approaches to the experimental study of rest breaks. We conclude that a psychometrically advanced and theoretically focused research of rest and recovery has the potential to finally provide a sound scientific basis to eventually mitigate the adverse effects of ever increasing task demands on performance and well-being in a multitasking world at work and leisure.
Merkel cell carcinoma (MCC) is an aggressive skin cancer frequently caused by the Merkel cell polyomavirus (MCPyV), and proliferation of MCPyV-positive MCC tumor cells depends on the expression of a virus-encoded truncated Large T antigen (LT) oncoprotein. Here, we asked in which phases of the cell cycle LT activity is required for MCC cell proliferation. Hence, we generated fusion-proteins of MCPyV-LT and parts of geminin (GMMN) or chromatin licensing and DNA replication factor1 (CDT1). This allowed us to ectopically express an LT, which is degraded either in the G1 or G2 phase of the cell cycle, respectively, in MCC cells with inducible T antigen knockdown. We demonstrate that LT expressed only in G1 is capable of rescuing LT knockdown-induced growth suppression while LT expressed in S and G2/M phases fails to support proliferation of MCC cells. These results suggest that the crucial function of LT, which has been demonstrated to be inactivation of the cellular Retinoblastoma protein 1 (RB1) is only required to initiate S phase entry.
Studies with monolingual infants show that the gestural behavior of 1–2-year-olds is a strong predictor for later language competencies and, more specifically, that the absence of index-finger pointing at 12 months seems to be a valid indicator for risk of language delay (LD). In this study a lack of index-finger pointing at 12 months was utilized as diagnostic criterion to identity infants with a high risk for LD at 24 months in a sample of 42 infants growing up bilingually. Results confirm earlier findings from monolinguals showing that 12-month-olds who point with the extended index finger have an advanced language status at 24 months and are less likely language delayed than infants who only point with the whole hand and do not produce index-finger points at 12 months.
For the current study the Lazarian stress-coping theory and the appendant model of psychosocial adjustment to chronic illness and disabilities (Pakenham, 1999) has shaped the foundation for identifying determinants of adjustment to ALS. We aimed to investigate the evolution of psychosocial adjustment to ALS and to determine its long-term predictors. A longitudinal study design with four measurement time points was therefore, used to assess patients' quality of life, depression, and stress-coping model related aspects, such as illness characteristics, social support, cognitive appraisals, and coping strategies during a period of 2 years. Regression analyses revealed that 55% of the variance of severity of depressive symptoms and 47% of the variance in quality of life at T2 was accounted for by all the T1 predictor variables taken together. On the level of individual contributions, protective buffering, and appraisal of own coping potential accounted for a significant percentage in the variance in severity of depressive symptoms, whereas problem management coping strategies explained variance in quality of life scores. Illness characteristics at T2 did not explain any variance of both adjustment outcomes. Overall, the pattern of the longitudinal results indicated stable depressive symptoms and quality of life indices reflecting a successful adjustment to the disease across four measurement time points during a period of about two years. Empirical evidence is provided for the predictive value of social support, cognitive appraisals, and coping strategies, but not illness parameters such as severity and duration for adaptation to ALS. The current study contributes to a better conceptualization of adjustment, allowing us to provide evidence-based support beyond medical and physical intervention for people with ALS.
No abstract available.
Background
Simulator training is an effective way of acquiring laparoscopic skills but there remains a need to optimize teaching methods to accelerate learning. We evaluated the effect of the mental exercise ‘deconstruction into key steps’ (DIKS) on the time required to acquire laparoscopic skills.
Methods
A randomized controlled trial with undergraduate medical students was implemented into a structured curricular laparoscopic training course. The intervention group (IG) was trained using the DIKS approach, while the control group (CG) underwent the standard course. Laparoscopic performance of all participants was video-recorded at baseline (t0), after the first session (t1) and after the second session (t2) nine days later. Two double-blinded raters assessed the videos. The Impact of potential covariates on performance (gender, age, prior laparoscopic experience, self-assessed motivation and self-assessed dexterity) was evaluated with a self-report questionnaire.
Results
Both the IG (n = 58) and the CG (n = 68) improved their performance after each training session (p < 0.001) but with notable differences between sessions. Whereas the CG significantly improved their performance from t0 –t1 (p < 0.05), DIKS shortened practical exercise time by 58% so that the IG outperformed the CG from t1 -t2, (p < 0.05). High self-assessed motivation and dexterity associated with significantly better performance (p < 0.05). Male participants demonstrated significantly higher overall performance (p < 0.05).
Conclusion
Mental exercises like DIKS can improve laparoscopic performance and shorten practice times. Given the limited exposure of surgical residents to simulator training, implementation of mental exercises like DIKS is highly recommended. Gender, self-assessed dexterity, and motivation all appreciably influence performance in laparoscopic training.
Background
Dislocations of the elbow are the second most common dislocations of humeral joints following the shoulder. Besides numerous possible concomitant injuries of the collateral ligaments or the extensor or flexor apparatus, an accompanying disruption of the brachial artery is a rare occurrence. In the following, such a case is presented and discussed.
Method
A 70-year-old woman sustained a closed posterior elbow dislocation with accompanying disruption of the brachial artery due to a fall in a domestic environment. Pulselessness of the radial artery led to a computed tomography angiography being performed, which confirmed the diagnosis. Direct operative vascular reconstruction with a vein insert was carried out. Due to strong swelling of the soft tissue, other examinations of the elbow could not be performed initially. A redislocation a few days later led to an operative stabilization of the elbow joint.
Results
The final consultation 4 months postoperatively showed a stable, centered elbow joint and a normal perfusion of the affected arm. The elbow function was good with a range of motion of 0/0/110° of extension/flexion.
Conclusion
An elbow dislocation is a complex injury. An accurate clinical examination of possible concomitant injuries is important and should be repeated in the first few days after the occurrence. Vascular reconstruction should be performed immediately. In the case of persistent joint instability, an operative stabilization is indicated and may be supported by a hinged external fixator.
Background
Research on the needs of people with disability is scarce, which promotes inadequate programs. Community Based Inclusive Development interventions aim to promote rights but demand a high level of community participation. This study aimed to identify prioritized needs as well as lessons learned for successful project implementation in different Latin American communities.
Methods
This study was based on a Community Based Inclusive Development project conducted from 2018 to 2021 led by a Columbian team in Columbia, Brazil and Bolivia. Within a sequential mixed methods design, we first retrospectively analyzed the project baseline data and then conducted Focus Group Discussions, together with ratings of community participation levels. Quantitative descriptive and between group analysis of the baseline survey were used to identify and compare sociodemographic characteristics and prioritized needs of participating communities. We conducted qualitative thematic analysis on Focus Group Discussions, using deductive main categories for triangulation: 1) prioritized needs and 2) lessons learned, with subcategories project impact, facilitators, barriers and community participation. Community participation was assessed via spidergrams. Key findings were compared with triangulation protocols.
Results
A total of 348 people with disability from 6 urban settings participated in the baseline survey, with a mean age of 37.6 years (SD 23.8). Out of these, 18 participated within the four Focus Group Discussions. Less than half of the survey participants were able to read and calculate (42.0%) and reported knowledge on health care routes (46.0%). Unemployment (87.9%) and inadequate housing (57.8%) were other prioritized needs across countries. Focus Group Discussions revealed needs within health, education, livelihood, social and empowerment domains.
Participants highlighted positive project impact in work inclusion, self-esteem and ability for self-advocacy. Facilitators included individual leadership, community networks and previous reputation of participating organizations. Barriers against successful project implementation were inadequate contextualization, lack of resources and on-site support, mostly due to the COVID-19 pandemic. The overall level of community participation was high (mean score 4.0/5) with lower levels in Brazil (3.8/5) and Bolivia (3.2/5).
Conclusion
People with disability still face significant needs. Community Based Inclusive Development can initiate positive changes, but adequate contextualization and on-site support should be assured.
Background
Colorectal cancer is a leading cause of cancer-related deaths worldwide. The best method to prevent CRC is a colonoscopy. However, not all colon polyps have the risk of becoming cancerous. Therefore, polyps are classified using different classification systems. After the classification, further treatment and procedures are based on the classification of the polyp. Nevertheless, classification is not easy. Therefore, we suggest two novel automated classifications system assisting gastroenterologists in classifying polyps based on the NICE and Paris classification.
Methods
We build two classification systems. One is classifying polyps based on their shape (Paris). The other classifies polyps based on their texture and surface patterns (NICE). A two-step process for the Paris classification is introduced: First, detecting and cropping the polyp on the image, and secondly, classifying the polyp based on the cropped area with a transformer network. For the NICE classification, we design a few-shot learning algorithm based on the Deep Metric Learning approach. The algorithm creates an embedding space for polyps, which allows classification from a few examples to account for the data scarcity of NICE annotated images in our database.
Results
For the Paris classification, we achieve an accuracy of 89.35 %, surpassing all papers in the literature and establishing a new state-of-the-art and baseline accuracy for other publications on a public data set. For the NICE classification, we achieve a competitive accuracy of 81.13 % and demonstrate thereby the viability of the few-shot learning paradigm in polyp classification in data-scarce environments. Additionally, we show different ablations of the algorithms. Finally, we further elaborate on the explainability of the system by showing heat maps of the neural network explaining neural activations.
Conclusion
Overall we introduce two polyp classification systems to assist gastroenterologists. We achieve state-of-the-art performance in the Paris classification and demonstrate the viability of the few-shot learning paradigm in the NICE classification, addressing the prevalent data scarcity issues faced in medical machine learning.