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Life-threatening systemic infections often occur due to the translocation of pathogens across the gut barrier and into the bloodstream. While the microbial and host mechanisms permitting bacterial gut translocation are well characterized, these mechanisms are still unclear for fungal pathogens such as Candida albicans, a leading cause of nosocomial fungal bloodstream infections. In this study, we dissected the cellular mechanisms of translocation of C. albicans across intestinal epithelia in vitro and identified fungal genes associated with this process. We show that fungal translocation is a dynamic process initiated by invasion and followed by cellular damage and loss of epithelial integrity. A screen of >2,000 C. albicans deletion mutants identified genes required for cellular damage of and translocation across enterocytes. Correlation analysis suggests that hypha formation, barrier damage above a minimum threshold level, and a decreased epithelial integrity are required for efficient fungal translocation. Translocation occurs predominantly via a transcellular route, which is associated with fungus-induced necrotic epithelial damage, but not apoptotic cell death. The cytolytic peptide toxin of C. albicans, candidalysin, was found to be essential for damage of enterocytes and was a key factor in subsequent fungal translocation, suggesting that transcellular translocation of C. albicans through intestinal layers is mediated by candidalysin. However, fungal invasion and low-level translocation can also occur via non-transcellular routes in a candidalysin-independent manner. This is the first study showing translocation of a human-pathogenic fungus across the intestinal barrier being mediated by a peptide toxin. IMPORTANCE Candida albicans, usually a harmless fungus colonizing human mucosae, can cause lethal bloodstream infections when it manages to translocate across the intestinal epithelium. This can result from antibiotic treatment, immune dysfunction, or intestinal damage (e.g., during surgery). However, fungal processes may also contribute. In this study, we investigated the translocation process of C. albicans using in vitro cell culture models. Translocation occurs as a stepwise process starting with invasion, followed by epithelial damage and loss of epithelial integrity. The ability to secrete candidalysin, a peptide toxin deriving from the hyphal protein Ece1, is key: C. albicans hyphae, secreting candidalysin, take advantage of a necrotic weakened epithelium to translocate through the intestinal layer.
Understanding relationships between microstructure and electrical transport is an important goal for the materials science of organic semiconductors. Combining high-resolution surface potential mapping by scanning Kelvin probe microscopy (SKPM) with systematic field effect transport measurements, we show that step edges can trap electrons on the surfaces of single crystal organic semiconductors. n-type organic semiconductor crystals exhibiting positive step edge surface potentials display threshold voltages that increase and carrier mobilities that decrease with increasing step density, characteristic of trapping, whereas crystals that do not have positive step edge surface potentials do not have strongly step density dependent transport. A device model and microelectrostatics calculations suggest that trapping can be intrinsic to step edges for crystals of molecules with polar substituents. The results provide a unique example of a specific microstructure–charge trapping relationship and highlight the utility of surface potential imaging in combination with transport measurements as a productive strategy for uncovering microscopic structure–property relationships in organic semiconductors.
Controllable metal–insulator transitions (MIT), Rashba–Dresselhaus (RD) spin splitting, and Weyl semimetals are promising schemes for realizing processing devices. Complex oxides are a desirable materials platform for such devices, as they host delicate and tunable charge, spin, orbital, and lattice degrees of freedoms. Here, using first-principles calculations and symmetry analysis, we identify an electric-field tunable MIT, RD effect, and Weyl semimetal in a known, charge-ordered, and polar relativistic oxide Ag2BiO3 at room temperature. Remarkably, a centrosymmetric BiO6 octahedral-breathing distortion induces a sizable spontaneous ferroelectric polarization through Bi3+/Bi5+ charge disproportionation, which stabilizes simultaneously the insulating phase. The continuous attenuation of the Bi3+/Bi5+ disproportionation obtained by applying an external electric field reduces the band gap and RD spin splitting and drives the phase transition from a ferroelectric RD insulator to a paraelectric Dirac semimetal, through a topological Weyl semimetal intermediate state. These findings suggest that Ag2BiO3 is a promising material for spin-orbitonic applications.
Evolutionary conserved networks of human height identify multiple Mendelian causes of short stature
(2019)
Height is a heritable and highly heterogeneous trait. Short stature affects 3% of the population and in most cases is genetic in origin. After excluding known causes, 67% of affected individuals remain without diagnosis. To identify novel candidate genes for short stature, we performed exome sequencing in 254 unrelated families with short stature of unknown cause and identified variants in 63 candidate genes in 92 (36%) independent families. Based on systematic characterization of variants and functional analysis including expression in chondrocytes, we classified 13 genes as strong candidates. Whereas variants in at least two families were detected for all 13 candidates, two genes had variants in 6 (UBR4) and 8 (LAMA5) families, respectively. To facilitate their characterization, we established a clustered network of 1025 known growth and short stature genes, which yielded 29 significantly enriched clusters, including skeletal system development, appendage development, metabolic processes, and ciliopathy. Eleven of the candidate genes mapped to 21 of these clusters, including CPZ, EDEM3, FBRS, IFT81, KCND1, PLXNA3, RASA3, SLC7A8, UBR4, USP45, and ZFHX3. Fifty additional growth-related candidates we identified await confirmation in other affected families. Our study identifies Mendelian forms of growth retardation as an important component of idiopathic short stature.
Dishevelled (DVL) is the key component of the Wnt signaling pathway. Currently, DVL conformational dynamics under native conditions is unknown. To overcome this limitation, we develop the Fluorescein Arsenical Hairpin Binder- (FlAsH-) based FRET in vivo approach to study DVL conformation in living cells. Using this single-cell FRET approach, we demonstrate that (i) Wnt ligands induce open DVL conformation, (ii) DVL variants that are predominantly open, show more even subcellular localization and more efficient membrane recruitment by Frizzled (FZD) and (iii) Casein kinase 1 ɛ (CK1ɛ) has a key regulatory function in DVL conformational dynamics. In silico modeling and in vitro biophysical methods explain how CK1ɛ-specific phosphorylation events control DVL conformations via modulation of the PDZ domain and its interaction with DVL C-terminus. In summary, our study describes an experimental tool for DVL conformational sampling in living cells and elucidates the essential regulatory role of CK1ɛ in DVL conformational dynamics.
Pan-cancer analyses that examine commonalities and differences among various cancer types have emerged as a powerful way to obtain novel insights into cancer biology. Here we present a comprehensive analysis of genetic alterations in a pan-cancer cohort including 961 tumours from children, adolescents, and young adults, comprising 24 distinct molecular types of cancer. Using a standardized workflow, we identified marked differences in terms of mutation frequency and significantly mutated genes in comparison to previously analysed adult cancers. Genetic alterations in 149 putative cancer driver genes separate the tumours into two classes: small mutation and structural/copy-number variant (correlating with germline variants). Structural variants, hyperdiploidy, and chromothripsis are linked to TP53 mutation status and mutational signatures. Our data suggest that 7–8% of the children in this cohort carry an unambiguous predisposing germline variant and that nearly 50% of paediatric neoplasms harbour a potentially druggable event, which is highly relevant for the design of future clinical trials.
Preclinical studies point to a pivotal role of the orexin 1 (OX1) receptor in arousal and fear learning and therefore suggest the HCRTR1 gene as a prime candidate in panic disorder (PD) with/without agoraphobia (AG), PD/AG treatment response, and PD/AG-related intermediate phenotypes. Here, a multilevel approach was applied to test the non-synonymous HCRTR1 C/T Ile408Val gene variant (rs2271933) for association with PD/AG in two independent case-control samples (total n = 613 cases, 1839 healthy subjects), as an outcome predictor of a six-weeks exposure-based cognitive behavioral therapy (CBT) in PD/AG patients (n = 189), as well as with respect to agoraphobic cognitions (ACQ) (n = 483 patients, n = 2382 healthy subjects), fMRI alerting network activation in healthy subjects (n = 94), and a behavioral avoidance task in PD/AG pre- and post-CBT (n = 271). The HCRTR1 rs2271933 T allele was associated with PD/AG in both samples independently, and in their meta-analysis (p = 4.2 × 10−7), particularly in the female subsample (p = 9.8 × 10−9). T allele carriers displayed a significantly poorer CBT outcome (e.g., Hamilton anxiety rating scale: p = 7.5 × 10−4). The T allele count was linked to higher ACQ sores in PD/AG and healthy subjects, decreased inferior frontal gyrus and increased locus coeruleus activation in the alerting network. Finally, the T allele count was associated with increased pre-CBT exposure avoidance and autonomic arousal as well as decreased post-CBT improvement. In sum, the present results provide converging evidence for an involvement of HCRTR1 gene variation in the etiology of PD/AG and PD/AG-related traits as well as treatment response to CBT, supporting future therapeutic approaches targeting the orexin-related arousal system.
Zinc (Zn2+) can modulate platelet and coagulation activation pathways, including fibrin formation. Here, we studied the (patho)physiological consequences of abnormal platelet Zn2+ storage and release. To visualize Zn2+ storage in human and mouse platelets, the Zn2+ specific fluorescent dye FluoZin3 was used. In resting platelets, the dye transiently accumulated into distinct cytosolic puncta, which were lost upon platelet activation. Platelets isolated from Unc13d−/− mice, characterized by combined defects of α/δ granular release, showed a markedly impaired Zn2+ release upon activation. Platelets from Nbeal2−/− mice mimicking Gray platelet syndrome (GPS), characterized by primarily loss of the α-granule content, had strongly reduced Zn2+ levels, which was also confirmed in primary megakaryocytes. In human platelets isolated from patients with GPS, Hermansky-Pudlak Syndrome (HPS) and Storage Pool Disease (SPD) altered Zn2+ homeostasis was detected. In turbidity and flow based assays, platelet-dependent fibrin formation was impaired in both Nbeal2−/− and Unc13d−/− mice, and the impairment could be partially restored by extracellular Zn2+. Altogether, we conclude that the release of ionic Zn2+ store from secretory granules upon platelet activation contributes to the procoagulant role of Zn2+ in platelet-dependent fibrin formation.
That the human brain contains magnetite is well established; however, its spatial distribution in the brain has remained unknown. We present room temperature, remanent magnetization measurements on 822 specimens from seven dissected whole human brains in order to systematically map concentrations of magnetic remanence carriers. Median saturation remanent magnetizations from the cerebellum were approximately twice as high as those from the cerebral cortex in all seven cases (statistically significantly distinct, p = 0.016). Brain stems were over two times higher in magnetization on average than the cerebral cortex. The ventral (lowermost) horizontal layer of the cerebral cortex was consistently more magnetic than the average cerebral cortex in each of the seven studied cases. Although exceptions existed, the reproducible magnetization patterns lead us to conclude that magnetite is preferentially partitioned in the human brain, specifically in the cerebellum and brain stem.
B cell development in bone marrow is a precisely regulated complex process. Through successive stages of differentiation, which are regulated by a multitude of signaling pathways and an array of lineage-specific transcription factors, the common lymphoid progenitors ultimately give rise to mature B cells. Similar to early thymocyte development in the thymus, early B cell development in bone marrow is critically dependent on IL-7 signaling. During this IL-7-dependent stage of differentiation, several transcription factors, such as E2A, EBF1, and Pax5, among others, play indispensable roles in B lineage specification and maintenance. Although recent studies have implicated several other transcription factors in B cell development, the role of NFATc1 in early B cell developmental stages is not known. Here, using multiple gene-manipulated mouse models and applying various experimental methods, we show that NFATc1 activity is vital for early B cell differentiation. Lack of NFATc1 activity in pro-B cells suppresses EBF1 expression, impairs immunoglobulin gene rearrangement, and thereby preBCR formation, resulting in defective B cell development. Overall, deficiency in NFATc1 activity arrested the pro-B cell transition to the pre-B cell stage, leading to severe B cell lymphopenia. Our findings suggest that, along with other transcription factors, NFATc1 is a critical component of the signaling mechanism that facilitates early B cell differentiation.
The remarkable diversity of sex determination mechanisms known in fish may be fuelled by exceptionally high rates of sex chromosome turnovers or transitions. However, the evolutionary causes and genomic mechanisms underlying this variation and instability are yet to be understood. Here we report on an over 30-year evolutionary experiment in which we tested the genomic consequences of hybridisation and selection between two Xiphophorus fish species with different sex chromosome systems. We find that introgression and imposing selection for pigmentation phenotypes results in the retention of an unexpectedly large maternally derived genomic region. During the hybridisation process, the sex-determining region of the X chromosome from one parental species was translocated to an autosome in the hybrids leading to the evolution of a new sex chromosome. Our results highlight the complexity of factors contributing to patterns observed in hybrid genomes, and we experimentally demonstrate that hybridisation can catalyze rapid evolution of a new sex chromosome.
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.
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.
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.
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.
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.
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.
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.
There is a great need for valuable ex vivo models that allow for assessment of cartilage repair strategies to reduce the high number of animal experiments. In this paper we present three studies with our novel ex vivo osteochondral culture platform. It consists of two separated media compartments for cartilage and bone, which better represents the in vivo situation and enables supply of factors pecific to the different needs of bone and cartilage. We investigated whether separation of the cartilage and bone compartments and/or culture media results in the maintenance of viability, structural and functional properties of cartilage tissue. Next, we valuated for how long we can preserve cartilage matrix stability of osteochondral explants during long-term culture over 84 days. Finally, we determined the optimal defect size that does not show spontaneous self-healing in this culture system. It was demonstrated that separated compartments for cartilage and bone in combination with tissue-specific medium allow for long-term culture of osteochondral explants while maintaining cartilage viability, atrix tissue content, structure and mechanical properties for at least 56 days. Furthermore, we could create critical size cartilage defects of different sizes in the model. The osteochondral model represents a valuable preclinical ex vivo tool for studying clinically relevant cartilage therapies, such as cartilage biomaterials, for their regenerative potential, for evaluation of drug and cell therapies, or to study mechanisms of cartilage regeneration. It will undoubtedly reduce the number of animals needed for in vivotesting.
SMART (Simple Modular Architecture Research Tool) is a web resource (https://smart.embl.de) for the identification and annotation of protein domains and the analysis of protein domain architectures. SMART version 9 contains manually curatedmodels formore than 1300 protein domains, with a topical set of 68 new models added since our last update article (1). All the new models are for diverse recombinase families and subfamilies and as a set they provide a comprehensive overview of mobile element recombinases namely transposase, integrase, relaxase, resolvase, cas1 casposase and Xer like cellular recombinase. Further updates include the synchronization of the underlying protein databases with UniProt (2), Ensembl (3) and STRING (4), greatly increasing the total number of annotated domains and other protein features available in architecture analysis mode. Furthermore, SMART's vector-based protein display engine has been extended and updated to use the latest web technologies and the domain architecture analysis components have been optimized to handle the increased number of protein features available.
Interpreting gaze behavior is essential in evaluating interaction partners, yet the ‘semantics of gaze’ in dynamic interactions are still poorly understood. We aimed to comprehensively investigate effects of gaze behavior patterns in different conversation contexts, using a two-step, qualitative-quantitative procedure. Participants watched video clips of single persons listening to autobiographic narrations by another (invisible) person. The listener’s gaze behavior was manipulated in terms of gaze direction, frequency and direction of gaze shifts, and blink frequency; emotional context was manipulated through the valence of the narration (neutral/negative). In Experiment 1 (qualitative-exploratory), participants freely described which states and traits they attributed to the listener in each condition, allowing us to identify relevant aspects of person perception and to construct distinct rating scales that were implemented in Experiment 2 (quantitative-confirmatory). Results revealed systematic and differential meanings ascribed to the listener’s gaze behavior. For example, rapid blinking and fast gaze shifts were rated more negatively (e.g., restless and unnatural) than slower gaze behavior; downward gaze was evaluated more favorably (e.g., empathetic) than other gaze aversion types, especially in the emotionally negative context. Overall, our study contributes to a more systematic understanding of flexible gaze semantics in social interaction.
Background
Deregulated expression of MYC is a driver of colorectal carcinogenesis, suggesting that decreasing MYC expression may have significant therapeutic value. CIP2A is an oncogenic factor that regulates MYC expression. CIP2A is overexpressed in colorectal cancer (CRC), and its expression levels are an independent marker for long-term outcome of CRC. Previous studies suggested that CIP2A controls MYC protein expression on a post-transcriptional level.
Methods
To determine the mechanism by which CIP2A regulates MYC in CRC, we dissected MYC translation and stability dependent on CIP2A in CRC cell lines.
Results
Knockdown of CIP2A reduced MYC protein levels without influencing MYC stability in CRC cell lines. Interfering with proteasomal degradation of MYC by usage of FBXW7-deficient cells or treatment with the proteasome inhibitor MG132 did not rescue the effect of CIP2A depletion on MYC protein levels. Whereas CIP2A knockdown had marginal influence on global protein synthesis, we could demonstrate that, by using different reporter constructs and cells expressing MYC mRNA with or without flanking UTR, CIP2A regulates MYC translation. This interaction is mainly conducted by the MYC 5′UTR.
Conclusions
Thus, instead of targeting MYC protein stability as reported for other tissue types before, CIP2A specifically regulates MYC mRNA translation in CRC but has only slight effects on global mRNA translation. In conclusion, we propose as novel mechanism that CIP2A regulates MYC on a translational level rather than affecting MYC protein stability in CRC.
Formation and treatment of biofilms present a great challenge for health care and industry. About 80% of human infections are associated with biofilms including biomaterial centered infections, like infections of prosthetic heart valves, central venous catheters, or urinary catheters. Additionally, biofilms can cause food and drinking water contamination. Biofilm research focusses on application of experimental biofilm models to study initial adherence processes, to optimize physico-chemical properties of medical materials for reducing interactions between materials and bacteria, and to investigate biofilm treatment under controlled conditions. Exploring new antimicrobial strategies plays a key role in a variety of scientific disciplines, like medical material research, anti-infectious research, plant engineering, or wastewater treatment. Although a variety of biofilm models exist, there is a lack of standardization for experimental protocols, and designing experimental setups remains a challenge. In this study, a number of experimental parameters critical for material research have been tested that influence formation and stability of an experimental biofilm using the non-pathogenic model strain of Pseudomonas fluorescens. These parameters include experimental time frame, nutrient supply, inoculum concentration, static and dynamic cultivation conditions, material properties, and sample treatment during staining for visualization of the biofilm. It was shown, that all tested parameters critically influence the experimental biofilm formation process. The results obtained in this study shall support material researchers in designing experimental biofilm setups.
In this work, we present a multimodal approach to three-dimensionally quantify and visualize fiber orientation and resin-rich areas in carbon-fiber-reinforced polymers manufactured by vacuum infusion. Three complementary image modalities were acquired by Talbot–Lau grating interferometer (TLGI) X-ray microcomputed tomography (XCT). Compared to absorption contrast (AC), TLGI-XCT provides enhanced contrast between polymer matrix and carbon fibers at lower spatial resolutions in the form of differential phase contrast (DPC) and dark-field contrast (DFC). Consequently, relatively thin layers of resin, effectively indiscernible from image noise in AC data, are distinguishable. In addition to the assessment of fiber orientation, the combination of DPC and DFC facilitates the quantification of resin-rich areas, e.g., in gaps between fiber layers or at binder yarn collimation sites. We found that resin-rich areas between fiber layers are predominantly developed in regions characterized by a pronounced curvature. In contrast, in-layer resin-rich areas are mainly caused by the collimation of fibers by binder yarn. Furthermore, void volume around two adjacent 90°-oriented fiber layers is increased by roughly 20% compared to a random distribution over the whole specimen.
The article deals with the pedagogical content knowledge of mathematical modelling as part of the professional competence of pre-service teachers. With the help of a test developed for this purpose from a conceptual model, we examine whether this pedagogical content knowledge can be promoted in its different facets—especially knowledge about modelling tasks and about interventions—by suitable university seminars. For this purpose, the test was administered to three groups in a seminar for the teaching of mathematical modelling: (1) to those respondents who created their own modelling tasks for use with students, (2) to those trained to intervene in mathematical modelling processes, and (3) participating students who are not required to address mathematical modelling. The findings of the study—based on variance analysis—indicate that certain facets (knowledge of modelling tasks, modelling processes, and interventions) have increased significantly in both experimental groups but to varying degrees. By contrast, pre-service teachers in the control group demonstrated no significant change to their level of pedagogical content knowledge.
In 2020, cancer was the leading cause of death worldwide, accounting for nearly 10 million deaths. Lung cancer was the most common cancer, with 2.21 million cases per year in both sexes. This non-homogeneous disease is further subdivided into small cell lung cancer (SCLC, 15%) and non-small cell lung cancer (NSCLC, 85%). By 2023, the American Cancer Society estimates that NSCLC will account for 13% of all new cancer cases and 21% of all estimated cancer deaths. In recent years, the treatment of patients with NSCLC has improved with the development of new therapeutic interventions and the advent of targeted and personalised therapies. However, these advances have only marginally improved the five-year survival rate, which remains alarmingly low for patients with NSCLC. This observation highlights the importance of having more appropriate experimental and preclinical models to recapitulate, identify and test novel susceptibilities in NSCLC. In recent years, the Trp53fl/fl KRaslsl-G12D/wt mouse model developed by Tuveson, Jacks and Berns has been the main in vivo model used to study NSCLC. This model mimics ADC and SCC to a certain extent. However, it is limited in its ability to reflect the genetic complexity of NSCLC. In this work, we use CRISPR/Cas9 genome editing with targeted mutagenesis and gene deletions to recapitulate the conditional model. By comparing the Trp53fl/fl KRaslsl- G12D/wt with the CRISPR-mediated Trp53mut KRasG12D, we demonstrated that both showed no differences in histopathological features, morphology, and marker expression. Furthermore, next-generation sequencing revealed a very high similarity in their transcriptional profile. Adeno-associated virus-mediated tumour induction and the modular design of the viral vector allow us to introduce additional mutations in a timely manner. CRISPR-mediated mutation of commonly mutated tumour suppressors in NSCLC reliably recapitulated the phenotypes described in patients in the animal model. Lastly, the dual viral approach could induce the formation of lung tumours not only in constitutive Cas9 expressing animals, but also in wildtype animals. Thus, the implementation of CRISPR genome editing can rapidly advance the repertoire of in vivo models for NSCLC research. Furthermore, it can reduce the necessity of extensive breeding.
Optimization problems with composite functions consist of an objective function which is the sum of a smooth and a (convex) nonsmooth term. This particular structure is exploited by the class of proximal gradient methods and some of their generalizations like proximal Newton and quasi-Newton methods. The current literature on these classes of methods almost exclusively considers the case where also the smooth term is convex. Here we present a globalized proximal Newton-type method which allows the smooth term to be nonconvex. The method is shown to have nice global and local convergence properties, and some numerical results indicate that this method is very promising also from a practical point of view.
Abstract
To compare intravenous contrast material (CM) injection protocols for dual-energy CT pulmonary angiography (CTPA) in patients with suspected acute pulmonary embolism with regard to image quality and pulmonary perfused blood volume (PBV) values. A total of 198 studies performed with four CM injection protocols varying in CM volume and iodine delivery rates (IDR) were retrospectively included: (A) 60 ml at 5 ml/s (IDR = 1.75gI/s), (B) 50 ml at 5 ml/s (IDR = 1.75gI/s), (C) 50 ml at 4 ml/s (IDR = 1.40gI/s), (D) 40 ml at 3 ml/s (IDR = 1.05gI/s). Image quality and PBV values at different resolution settings were compared. Pulmonary arterial tract attenuation was highest for protocol A (397 ± 110 HU; p vs. B = 0.13; vs. C = 0.02; vs. D < 0.001). CTPA image quality of protocol A was rated superior compared to protocols B and D by reader 1 (p = 0.01; < 0.001), and superior to protocols B, C and D by reader 2 (p < 0.001; 0.02; < 0.001). Otherwise, there were no significant differences in CTPA quality ratings. Subjective iodine map ratings did not vary significantly between protocols A, B, and C. Both readers rated protocol D inferior to all other protocols (p < 0.05). PBV values did not vary significantly between protocols A and B at resolution settings of 1, 4 and 10 (p = 0.10; 0.10; 0.09), while otherwise PBV values displayed a decreasing trend from protocol A to D (p < 0.05). Higher CM volume and IDR are associated with superior CTPA and iodine map quality and higher absolute PBV values.
Purpose
Radiotherapy (RT) was identified as a risk factor for long-term cardiac effects in breast cancer patients treated until the 1990s. However, modern techniques reduce radiation exposure of the heart, but some exposure remains unavoidable. In a retrospective cohort study, we investigated cardiac mortality and morbidity of breast cancer survivors treated with recent RT in Germany.
Methods
A total of 11,982 breast cancer patients treated between 1998 and 2008 were included. A mortality follow-up was conducted until 06/2018. In order to assess cardiac morbidity occurring after breast cancer treatment, a questionnaire was sent out in 2014 and 2019. The effect of breast cancer laterality on cardiac mortality and morbidity was investigated as a proxy for radiation exposure. We used Cox Proportional Hazards regression analysis, taking potential confounders into account.
Results
After a median follow-up time of 11.1 years, there was no significant association of tumor laterality with cardiac mortality in irradiated patients (hazard ratio (HR) for left-sided versus right-sided tumor 1.09; 95% confidence interval (CI) 0.85–1.41). Furthermore, tumor laterality was not identified as a significant risk factor for cardiac morbidity (HR = 1.05; 95%CI 0.88–1.25).
Conclusions
Even though RT for left-sided breast cancer on average incurs higher radiation dose to the heart than RT for right-sided tumors, we found no evidence that laterality is a strong risk factor for cardiac disease after contemporary RT. However, larger sample sizes, longer follow-up, detailed information on individual risk factors and heart dose are needed to assess clinically manifest late effects of current cancer therapy.
Across Europe, calcareous grasslands become increasingly fragmented and their quality deteriorates through abandonment and land use intensification, both affecting biodiversity. Here, we investigated local and landscape effects on diversity patterns of several taxonomic groups in a landscape of highly fragmented calcareous grassland remnants. We surveyed 31 grassland fragments near Göttingen, Germany, in spring and summer 2017 for vascular plants, butterflies and birds, with sampling effort adapted to fragment area. Through regression modelling, we tested relationships between species richness and fragment size (from 314 to 51,395 m\(^2\)), successional stage, habitat connectivity and the per cent cover of arable land in the landscape at several radii. We detected 283 plant species, 53 butterfly species and 70 bird species. Of these, 59 plant species, 19 butterfly species and 9 bird species were grassland specialists. Larger fragments supported twice the species richness of plants than small ones, and hosted more species of butterflies, but not of birds. Larger grassland fragments contained more grassland specialist plants, but not butterfly or bird specialists. Increasing amounts of arable land in the landscape from 20 to 90% was related to the loss of a third of species of plants, and less so, of butterflies, but not of birds. Per cent cover of arable land negatively correlated to richness of grassland specialist plants and butterflies, but positively to grassland specialist birds. We found no effect by successional stages and habitat connectivity. Our multi-taxa approach highlights the need for conservation management at the local scale, complemented by measures at the landscape scale.
Physical regimes characterized by low Mach numbers and steep stratifications pose severe challenges to standard finite volume methods. We present three new methods specifically designed to navigate these challenges by being both low Mach compliant and well-balanced. These properties are crucial for numerical methods to efficiently and accurately compute solutions in the regimes considered.
First, we concentrate on the construction of an approximate Riemann solver within Godunov-type finite volume methods. A new relaxation system gives rise to a two-speed relaxation solver for the Euler equations with gravity. Derived from fundamental mathematical principles, this solver reduces the artificial dissipation in the subsonic regime and preserves hydrostatic equilibria. The solver is particularly stable as it satisfies a discrete entropy inequality, preserves positivity of density and internal energy, and suppresses checkerboard modes.
The second scheme is designed to solve the equations of ideal MHD and combines different approaches. In order to deal with low Mach numbers, it makes use of a low-dissipation version of the HLLD solver and a partially implicit time discretization to relax the CFL time step constraint. A Deviation Well-Balancing method is employed to preserve a priori known magnetohydrostatic equilibria and thereby reduces the magnitude of spatial discretization errors in strongly stratified setups.
The third scheme relies on an IMEX approach based on a splitting of the MHD equations. The slow scale part of the system is discretized by a time-explicit Godunov-type method, whereas the fast scale part is discretized implicitly by central finite differences. Numerical dissipation terms and CFL time step restriction of the method depend solely on the slow waves of the explicit part, making the method particularly suited for subsonic regimes. Deviation Well-Balancing ensures the preservation of a priori known magnetohydrostatic equilibria.
The three schemes are applied to various numerical experiments for the compressible Euler and ideal MHD equations, demonstrating their ability to accurately simulate flows in regimes with low Mach numbers and strong stratification even on coarse grids.
Based on an embodied account of language comprehension, this study investigated the dynamic characteristics of children and adults’ perceptual simulations during sentence comprehension, using a novel paradigm to assess the perceptual simulation of objects moving up and down a vertical axis. The participants comprised adults (N = 40) and 6-, 8-, and 10-year-old children (N = 116). After listening in experimental trials to sentences implying that objects moved upward or downward, the participants were shown pictures and had to decide as quickly as possible whether the objects depicted had been mentioned in the sentences. The target pictures moved either up or down and then stopped in the middle of the screen. All age groups’ reaction times were found to be shorter when the objects moved in the directions that the sentences implied. Age exerted no developmental effect on reaction times. The findings suggest that dynamic perceptual simulations are fundamental to language comprehension in text recipients aged 6 and older.
Coisotropic algebras consist of triples of algebras for which a reduction can be defined and unify in a very algebraic fashion coisotropic reduction in several settings. In this paper, we study the theory of (formal) deformation of coisotropic algebras showing that deformations are governed by suitable coisotropic DGLAs. We define a deformation functor and prove that it commutes with reduction. Finally, we study the obstructions to existence and uniqueness of coisotropic algebras and present some geometric examples.
Quantitative information is omnipresent in the world and a wide range of species has been shown to use quantities to optimize their decisions. While most studies have focused on vertebrates, a growing body of research demonstrates that also insects such as honeybees possess basic quantitative abilities that might aid them in finding profitable flower patches. However, it remains unclear if for insects, quantity is a salient feature relative to other stimulus dimensions, or if it is only used as a “last resort” strategy in case other stimulus dimensions are inconclusive. Here, we tested the stingless bee Trigona fuscipennis, a species representative of a vastly understudied group of tropical pollinators, in a quantity discrimination task. In four experiments, we trained wild, free-flying bees on stimuli that depicted either one or four elements. Subsequently, bees were confronted with a choice between stimuli that matched the training stimulus either in terms of quantity or another stimulus dimension. We found that bees were able to discriminate between the two quantities, but performance differed depending on which quantity was rewarded. Furthermore, quantity was more salient than was shape. However, quantity did not measurably influence the bees' decisions when contrasted with color or surface area. Our results demonstrate that just as honeybees, small-brained stingless bees also possess basic quantitative abilities. Moreover, invertebrate pollinators seem to utilize quantity not only as "last resort" but as a salient stimulus dimension. Our study contributes to the growing body of knowledge on quantitative cognition in invertebrate species and adds to our understanding of the evolution of numerical cognition.
Objectives
To determine sleep bruxism (SB) behavior during five consecutive nights and to identify correlations between SB episodes per hour (SB index) and sleep-time masseter-muscle activity (sMMA).
Material and methods
Thirty-one participants were included in the study. Of these, 10 were classified as sleep bruxers (group SB-1) and nine as non-sleep bruxers (group non-SB). The bruxism status of these 19 patients was identified by means of questionnaires, an assessment of clinical symptoms, and electromyographic/electrocardiographic data (Bruxoff® device). The remaining 12 participants were also identified as bruxers, but based exclusively on data from the Bruxoff device (group SB-2). Data analysis included descriptive statistics and Spearman’s correlation to assess the relationship between the SB index and sMMA.
Results
Participants in group SB-1 showed an overall mean SB index of 3.1 ± 1.6 and a mean total sMMA per night of 62.9 ± 38.3. Participants in group SB-2 had an overall mean SB index of 2.7 ± 1.5 and a mean total sMMA of 56.0 ± 29.3. In the non-SB group, participants showed an overall mean SB index of 0.8 ± 0.5 and a mean total sMMA of 56.8 ± 30.3. Spearman’s correlation yielded values of − 0.27 to 0.71 for the correlation between sMMA and SB index.
Conclusions
The data revealed variable SB activity and the absence of a reliable correlation between sMMA and the SB index.
Clinical relevance
The high variation in SB activity and lack of correlation between sMMA and the SB index should be considered when diagnosing SB.
Trial registration
Clinical Trials [NIH], clinical trial no. NCT03039985.
Objectives
Micro-computed tomography (μ-CT) and histology, the current gold standard methods for assessing the formation of new bone and blood vessels, are invasive and/or destructive. With that in mind, a more conservative tool, dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI), was tested for its accuracy and reproducibility in monitoring neovascularization during bone regeneration. Additionally, the suitability of blood perfusion as a surrogate of the efficacy of osteoplastic materials was evaluated.
Materials and methods
Sixteen rabbits were used and equally divided into four groups, according to the time of euthanasia (2, 3, 4, and 6 weeks after surgery). The animals were submitted to two 8-mm craniotomies that were filled with blood or autogenous bone. Neovascularization was assessed in vivo through DCE-MRI, and bone regeneration, ex vivo, through μ-CT and histology.
Results
The defects could be consistently identified, and their blood perfusion measured through DCE-MRI, there being statistically significant differences within the blood clot group between 3 and 6 weeks (p = 0.029), and between the former and autogenous bone at six weeks (p = 0.017). Nonetheless, no significant correlations between DCE-MRI findings on neovascularization and μ-CT (r =−0.101, 95% CI [−0.445; 0.268]) or histology (r = 0.305, 95% CI [−0.133; 0.644]) findings on bone regeneration were observed.
Conclusions
These results support the hypothesis that DCE-MRI can be used to monitor neovascularization but contradict the premise that it could predict bone regeneration as well.
Objectives
To investigate plaque inhibition of 0.1% octenidine mouthwash (OCT) vs. placebo over 5 days in the absence of mechanical plaque control.
Materials and methods
For this randomized, placebo-controlled, double-blind, parallel group, multi-center phase 3 study, 201 healthy adults were recruited. After baseline recording of plaque index (PI) and gingival index (GI), collection of salivary samples, and dental prophylaxis, subjects were randomly assigned to OCT or placebo mouthwash in a 3:1 ratio. Rinsing was performed twice daily for 30 s. Colony forming units in saliva were determined before and after the first rinse. At day 5, PI, GI, and tooth discoloration index (DI) were assessed. Non-parametric van Elteren tests were applied with a significance level of p < 0.05.
Results
Treatment with OCT inhibited plaque formation more than treatment with placebo (PI: 0.36 vs. 1.29; p < 0.0001). OCT reduced GI (0.04 vs. placebo 0.00; p = 0.003) and salivary bacterial counts (2.73 vs. placebo 0.24 lgCFU/ml; p < 0.0001). Tooth discoloration was slightly higher under OCT (DI: 0.25 vs. placebo 0.00; p = 0.0011). Mild tongue staining and dysgeusia occurred.
Conclusions
OCT 0.1% mouthwash inhibits plaque formation over 5 days. It therefore can be recommended when regular oral hygiene is temporarily compromised.
Clinical relevance
When individual plaque control is compromised, rinsing with octenidine mouthwash is recommended to maintain healthy oral conditions while side effects are limited.
The WHO-designated neglected-disease pathogen Chlamydia trachomatis (CT) is a gram-negative bacterium responsible for the most frequently diagnosed sexually transmitted infection worldwide. CT infections can lead to infertility, blindness and reactive arthritis, among others. CT acts as an infectious agent by its ability to evade the immune response of its host, which includes the impairment of the NF-κB mediated inflammatory response and the Mcl1 pro-apoptotic pathway through its deubiquitylating, deneddylating and transacetylating enzyme ChlaDUB1 (Cdu1). Expression of Cdu1 is also connected to host cell Golgi apparatus fragmentation, a key process in CT infections.
Cdu1 may this be an attractive drug target for the treatment of CT infections. However, a lead molecule for the development of novel potent inhibitors has been unknown so far. Sequence alignments and phylogenetic searches allocate Cdu1 in the CE clan of cysteine proteases. The adenovirus protease (adenain) also belongs to this clan and shares a high degree of structural similarity with Cdu1. Taking advantage of topological similarities between the active sites of Cdu1 and adenain, a target-hopping approach on a focused set of adenain inhibitors, developed at Novartis, has been pursued. The thereby identified cyano-pyrimidines represent the first active-site directed covalent reversible inhibitors for Cdu1. High-resolution crystal structures of Cdu1 in complex with the covalently bound cyano-pyrimidines as well as with its substrate ubiquitin have been elucidated. The structural data of this thesis, combined with enzymatic assays and covalent docking studies, provide valuable insights into Cdu1s activity, substrate recognition, active site pocket flexibility and potential hotspots for ligand interaction. Structure-informed drug design permitted the optimization of this cyano-pyrimidine based scaffold towards HJR108, the first molecule of its kind specifically designed to disrupt the function of Cdu1. The structures of potentially more potent and selective Cdu1 inhibitors are herein proposed.
This thesis provides important insights towards our understanding of the structural basis of ubiquitin recognition by Cdu1, and the basis to design highly specific Cdu1 covalent inhibitors.
This dissertation explores the development and assessment of inhibitory control – a crucial component of executive functions – in young children. Inhibitory control, defined as the ability to suppress inappropriate responses (Verbruggen & Logan, 2008), is essential for adaptable and goal-oriented behavior. The rapid and non-linear development of this cognitive function in early childhood presents unique challenges for accurate assessment. As children age, they often exhibit a ceiling effect in terms of response accuracy (Petersen et al., 2016), underscoring the need to consider response latency as well. Ideally, combining response latency with accuracy could yield a more precise measure of inhibitory control (e.g., Magnus et al., 2019), facilitating a detailed tracking of developmental changes in inhibitory control across a wider age spectrum. The three studies of this dissertation collectively aim to clarify the relationship between response accuracy, response latency, and inhibitory control across different stages of child development. Each study utilizes a computerized Pointing Stroop Task (Berger et al., 2000) to measure inhibitory control, examining the task's validity and the integration of dual metrics for a more comprehensive evaluation.
The first study focuses on establishing the validity of using both response accuracy and latency as indicators of inhibitory control. Utilizing the framework of explanatory item-response modeling (De Boeck & Wilson, 2004), the study revealed how the task characteristics congruency and item position influence both the difficulty level and timing aspects in young children’s responses in the computerized Pointing Stroop task. Further, this study found that integrating response accuracy with latency, even in a basic manner, provides additional insights. Building upon these findings, the second study investigates the nuances of integrating response accuracy and latency, examining whether this approach can account for age-related differences in inhibitory control. It also explores whether response latencies may contain different information depending on the age and proficiency of the children. The study leverages novel and established methodological perspectives to integrate response accuracy and latency into a single metric, showing the potential applicability of different approaches for assessing inhibitory control development. The third study extends the investigation to a longitudinal perspective, exploring the dynamic relationship between response accuracy, latency, and inhibitory control over time. It assesses whether children who achieve high accuracy at an earlier age show faster improvement in response latency, suggesting a non-linear maturation pathway of inhibitory control. The study also examines if the predictive value of early response latency for later fluid intelligence is dependent on the response accuracy level.
Together, these empirical studies contribute to a more robust understanding of the complex interaction between inhibitory control, response accuracy, and response latency, facilitating valid evaluations of cognitive capabilities in children. Moreover, the findings may have practical implications for designing educational strategies and clinical interventions that address the developmental trajectory of inhibitory control. The nuanced approach advocated in this dissertation suggests prioritizing accuracy in assessment and interventions during the early stages of children's cognitive development, gradually shifting the focus to response latency as children mature and secure their inhibitory control abilities.
The focus of this thesis is on analysing a linear stochastic partial differential equation (SPDE) with a bounded domain. The first part of the thesis commences with an examination of a one-dimensional SPDE. In this context, we construct estimators for the parameters of a parabolic SPDE based on discrete observations of a solution in time and space on a bounded domain. We establish central limit theorems for a high-frequency asymptotic regime, showing substantially smaller asymptotic variances compared to existing estimation methods. Moreover, asymptotic confidence intervals are directly feasible. Our approach builds upon realized volatilities and their asymptotic illustration as the response of a log-linear model with a spatial explanatory variable. This yields efficient estimators based on realized volatilities with optimal rates of convergence and minimal variances. We demonstrate our results by Monte Carlo simulations.
Extending this framework, we analyse a second-order SPDE model in multiple space dimensions in the second part of this thesis and develop estimators for the parameters of this model based on discrete observations in time and space on a bounded domain. While parameter estimation for one and two spatial dimensions was established in recent literature, this is the first work that generalizes the theory to a general, multi-dimensional framework. Our methodology enables the construction of an oracle estimator for volatility within the underlying model. For proving central limit theorems, we use a high-frequency observation scheme. To showcase our results, we conduct a Monte Carlo simulation, highlighting the advantages of our novel approach in a multi-dimensional context.
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.
In this thesis, a variety of Fokker--Planck (FP) optimal control problems are investigated. Main emphasis is put on a first-- and second--order analysis of different optimal control problems, characterizing optimal controls, establishing regularity results for optimal controls, and providing a numerical analysis for a Galerkin--based numerical scheme.
The Fokker--Planck equation is a partial differential equation (PDE) of linear parabolic type deeply connected to the theory of stochastic processes and stochastic differential equations. In essence, it describes the evolution over time of the probability distribution of the state of an object or system of objects under the influence of both deterministic and stochastic forces.
The FP equation is a cornerstone in understanding and modeling phenomena ranging from the diffusion and motion of molecules in a fluid to the fluctuations in financial markets.
Two different types of optimal control problems are analyzed in this thesis. On the one hand, Fokker--Planck ensemble optimal control problems are considered that have a wide range of applications in controlling a system of multiple non--interacting objects. In this framework, the goal is to collectively drive each object into a desired state.
On the other hand, tracking--type control problems are investigated, commonly used in parameter identification problems or stemming from the field of inverse problems.
In this framework, the aim is to determine certain parameters or functions of the FP equation, such that the resulting probability distribution function takes a desired form, possibly observed by measurements.
In both cases, we consider FP models where the control functions are part of the drift, arising only from the deterministic forces of the system. Therefore, the FP optimal control problem has a bilinear control structure.
Box constraints on the controls may be present, and the focus is on time--space dependent controls for ensemble--type problems and on only time--dependent controls for tracking--type optimal control problems.
In the first chapter of the thesis, a proof of the connection between the FP equation and stochastic differential equations is provided. Additionally, stochastic optimal control problems, aiming to minimize an expected cost value, are introduced, and the corresponding formulation within a deterministic FP control framework is established.
For the analysis of this PDE--constrained optimal control problem, the existence, and regularity of solutions to the FP problem are investigated. New $L^\infty$--estimates for solutions are established for low space dimensions under mild assumptions on the drift. Furthermore, based on the theory of Bessel potential spaces, new smoothness properties are derived for solutions to the FP problem in the case of only time--dependent controls. Due to these properties, the control--to--state map, which associates the control functions with the corresponding solution of the FP problem, is well--defined, Fréchet differentiable and compact for suitable Lebesgue spaces or Sobolev spaces.
The existence of optimal controls is proven under various assumptions on the space of admissible controls and objective functionals. First--order optimality conditions are derived using the adjoint system. The resulting characterization of optimal controls is exploited to achieve higher regularity of optimal controls, as well as their state and co--state functions.
Since the FP optimal control problem is non--convex due to its bilinear structure, a first--order analysis should be complemented by a second--order analysis.
Therefore, a second--order analysis for the ensemble--type control problem in the case of $H^1$--controls in time and space is performed, and sufficient second--order conditions are provided. Analogous results are obtained for the tracking--type problem for only time--dependent controls.
The developed theory on the control problem and the first-- and second--order optimality conditions is applied to perform a numerical analysis for a Galerkin discretization of the FP optimal control problem. The main focus is on tracking-type problems with only time--dependent controls. The idea of the presented Galerkin scheme is to first approximate the PDE--constrained optimization problem by a system of ODE--constrained optimization problems. Then, conditions on the problem are presented such that the convergence of optimal controls from one problem to the other can be guaranteed.
For this purpose, a class of bilinear ODE--constrained optimal control problems arising from the Galerkin discretization of the FP problem is analyzed. First-- and second--order optimality conditions are established, and a numerical analysis is performed. A discretization with linear finite elements for the state and co--state problem is investigated, while the control functions are approximated by piecewise constant or piecewise quadratic continuous polynomials. The latter choice is motivated by the bilinear structure of the optimal control problem, allowing to overcome the discrepancies between a discretize--then--optimize and optimize--then--discretize approach. Moreover, second--order accuracy results are shown using the space of continuous, piecewise quadratic polynomials as the discrete space of controls. Lastly, the theoretical results and the second--order convergence rates are numerically verified.
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.
This paper is devoted to a theoretical and numerical investigation of Nash equilibria and Nash bargaining problems governed by bilinear (input-affine) differential models. These systems with a bilinear state-control structure arise in many applications in, e.g., biology, economics, physics, where competition between different species, agents, and forces needs to be modelled. For this purpose, the concept of Nash equilibria (NE) appears appropriate, and the building blocks of the resulting differential Nash games are different control functions associated with different players that pursue different non-cooperative objectives. In this framework, existence of Nash equilibria is proved and computed with a semi-smooth Newton scheme combined with a relaxation method. Further, a related Nash bargaining (NB) problem is discussed. This aims at determining an improvement of all players’ objectives with respect to the Nash equilibria. Results of numerical experiments successfully demonstrate the effectiveness of the proposed NE and NB computational framework.