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Institute
- Graduate School of Life Sciences (103)
- Theodor-Boveri-Institut für Biowissenschaften (82)
- Institut für Informatik (46)
- Institut für Psychologie (43)
- Neurologische Klinik und Poliklinik (31)
- Medizinische Klinik und Poliklinik II (30)
- Institut für Geographie und Geologie (27)
- Institut für Pharmazie und Lebensmittelchemie (26)
- Medizinische Klinik und Poliklinik I (25)
- Klinik und Poliklinik für Anästhesiologie (ab 2004) (24)
Schriftenreihe
Sonstige beteiligte Institutionen
- Helmholtz Institute for RNA-based Infection Research (HIRI) (2)
- Interdisziplinäres Zentrum für Klinische Forschung (IZKF) (2)
- Klinische Studienzentrale (Universitätsklinikum) (2)
- Rudolf Virchow Center for Integrative and Translational Bioimaging, University of Würzburg (2)
- Anthropology Department University of Tennessee, Knoxville (1)
- CIBSS Centre for Integrative Biological Signalling Studies, University of Freiburg (1)
- Carl-Ludwig-Institut für Physiologie, Universität Leipzig (1)
- Chair of Experimental Biomedicine I (1)
- Charles University, Faculty of Mathematics and Physics, Ke Karlovu 5, 121 16 Prague, Czech Republic (1)
- DATE Lab, KITE Research Insititute, University Health Network, Toronto, Canada (1)
Depressive disorders represent one of the main sources for the loss of healthy years of life. One of the reasons for this circumstance is the recurrent course of these disorders, which can be interrupted by current therapeutic approaches, especially in the shortterm, but seem to be maintained at least in part in the long-term. Subsequently, on one hand, this thesis deals with methodological measurement issues in the longitudinal prediction of depressive courses. On the other hand, it addresses two currently discussed neuroscience-based treatment approaches, which are investigated experimentally in a basic-psychological manner and reviewed in the light of their potential to translate results to the application in patient care. These two approaches each address potential mechanisms that may negatively impact long-term disease trajectories: First, stable endophenotypes for vulnerability factors that could regain control over the organism and reactivate maladaptive experiences, or behaviors with increasing temporal distance from therapeutic methods are focused on. In the studies presented, these were influenced by a recently rediscovered method of neuromodulation (transcranial low-intensity focused ultrasound) which is discussed in light of its unique capability to address even deepest, subcortical regions at a high spatial resolution. Lastly, as a second approach, an experimental design for the use of reconsolidation interference is presented, which could provide a first insight into the applicability of corresponding protocols in the field of depressive disorders and thus contribute to the modification, instead of inhibition, of already mentioned endophenotypes. In sum, methodological considerations for monitoring and predicting long-term courses of depression are deducted before two approaches are discussed that could potentially exert positive influences on the recurrent nature of depressive symptoms on their own, in combination with each other, or as augmentation for existing therapeutic procedures.
Ubiquitylation is a protein post translational modification, in which ubiquitin is covalently attached to target protein substrates resulting in diverse cellular outcomes. Besides ubiquitin, various ubiquitin-like proteins including FAT10 exist, which are also conjugated to target proteins. The underlying modification mechanisms are conserved. In the initial step, ubiquitin or a ubiquitin-like protein is thioester-linked to a catalytic cysteine in the E1activating enzyme in an ATP-dependent manner. The respective protein modifier is then transferred to an E2 conjugating enzyme in a transthioesterification reaction. Finally, an E3 ubiquitin ligase E3 catalyzes the covalent attachment of the protein modifier to a substrate. In the case of ubiquitin, multiple ubiquitin molecules can be attached to a substrate in the form of either linear or branched polyubiquitin chains but also as single ubiquitin modifications. Depending on the nature of the ubiquitin chain, the substrates are destined to various cellular processes such as their targeted destruction by the proteasome but also non-degradative outcomes may occur.
As stated above FAT10 is a ubiquitin-like protein modifier which typically targets proteins for proteasomal degradation. It consists of two ubiquitin-like domains and is mainly expressed in cells of the human immune system. The reported involvement of FAT10 modifications in cancers and other diseases has caught the attention of the scientific community as an inhibition of the FAT10ylation process may provide avenues for novel therapeutic approaches. UBA6 is the E1 activating enzyme that resides at the apex of the FAT10 proteasomal degradation pathway. UBA6 not only recognizes FAT10 but can also activate ubiquitin as efficiently as the ubiquitin specific E1 UBA1. The dual specificity of UBA6 may complicate the inhibition FAT10ylation since targeting the active site of UBA6 will also inhibit the UBA6-catalyzed ubiquitin activation. Therefore, it is important to understand the underlying principles for the dual specificity of UBA6 prior to the development of compounds interfering with FAT10ylation.
In this thesis important novel insights into the structure and function of UBA6 were derived by X-ray crystallography and biochemical methods. The first crystal structure of UBA6 reveals the multidomain architecture of this enzyme in atomic detail. The enzyme is composed of a rigid core including its active and inactive adenylation domains as well as a 4 helix bundle. Overall, the molecule adopts a “Y” shape architecture with the core at the base and the first and second catalytic half domains forming one arm of the “Y” and the ubiquitin fold domain constituting the other arm. While UBA6 shares the same domain architecture as UBA1, substantial differences were revealed by the crystal structure. In particular, the first catalytic half domain undergoes a significant shift to a position more distal from the core. This rigid body movement is assumed to generate room to accommodate the second ubiquitin-like domain of FAT10. Differences are also observed in a hydrophobic platform between the core and the first catalytic half domain and the adenylation active site in the core, which together from the binding sites for ubiquitin and FAT10. Site directed mutagenesis of key residues in these areas altered the UBA6-catalyzed activation of ubiquitin and FAT10. UBA6 variants were generated with the goal of trying to block the activation of FAT10 while still maintaining that of ubiquitin activation, in order to fully explain the dual specificity of UBA6. However, none of these mutations could block the activation of FAT10, while some of these UBA6 variants blocked ubiquitin activation. Preliminary inhibition assays with a group of E1 inhibitors belonging to the adenosyl sulfamate family demonstrated potent inhibition of FAT10ylation for two compounds. The dual specificity of UBA6 hence needs to be further examined by biochemical and structural methods. In particular, the structure of a complex between UBA6 and ubiquitin or FAT10 would provide key insights for further biochemical studies, ultimately allowing the targeted inhibition of the FAT10ylation machinery.
A cyclic alkyl(amino)carbene (CAAC)‐stabilized dicoordinate aminoborylene is synthesized by the twofold reduction of a [(CAAC)BCl\(_{2}\)(TMP)] (TMP=2,6‐tetramethylpiperidyl) precursor. NMR‐spectroscopic, X‐ray crystallographic and computational analyses confirm the cumulenic nature of the central C=B=N moiety. Irradiation of [(CAAC)B(TMP)] (2) resulted in an intramolecular C−C bond activation, leading to a doubly‐fused C\(_{10}\)BN heterocycle, while the reaction with acetonitrile resulted in an aryl migration from the CAAC to the acetonitrile nitrogen atom, concomitant with tautomerization of the latter to a boron‐bound allylamino ligand. One‐electron oxidation of 2 with CuX (X=Cl, Br) afforded the corresponding amino(halo)boryl radicals, which were characterized by EPR spectroscopy and DFT calculations. Placing 2 under an atmosphere of CO afforded the tricoordinate (CAAC,CO)‐stabilized aminoborylene. Finally, the twofold oxidation of 2 with chalcogens led, in the case of N\(_{2}\)O and sulfur, to the splitting of the B−C\(_{CAAC}\) bond and formation of the 2,4‐diamino‐1,3,2,4‐dichalcogenadiboretanes and CAAC‐chalcogen adducts, whereas with selenium a monomeric boraselenone was isolated, which showed some degree of B−Se multiple bonding.
The 2‐aryl‐3,4,5,6‐tetraphenyl‐1,2‐azaborinines 1‐EMe\(_{3}\) and 2‐EMe\(_{3}\) (E=Si, Sn; aryl=Ph (1), Mes (=2,4,6‐trimethylphenyl, 2)) were synthesized by ring‐expansion of borole precursors with N\(_{3}\)EMe\(_{3}\)‐derived nitrenes. Desilylative hydrolysis of 1‐ and 2‐SiMe\(_{3}\) yielded the corresponding N‐protonated azaborinines, which were deprotonated with nBuLi or MN(SiMe\(_{3}\))\(_{2}\) (M=Na, K) to the corresponding group 1 salts, 1‐M and 2‐M. While the lithium salts crystallized as monomeric Lewis base adducts, the potassium salts formed coordination polymers or oligomers via intramolecular K⋅⋅⋅aryl π interactions. The reaction of 1‐M or 2‐M with CO\(_{2}\) yielded N‐carboxylate salts, which were derivatized by salt metathesis to methyl and silyl esters. Salt metathesis of 1‐M or 2‐M with methyl triflate, [Cp*BeCl] (Cp*=C\(_{5}\)Me\(_{5}\)), BBr\(_{2}\)Ar (Ar=Ph, Mes, 2‐thienyl), ECl\(_{3}\) (E=B, Al, Ga) and PX\(_{3}\) (X=Cl, Br) afforded the respective group 2, 13 and 15 1,2‐azaborinin‐2‐yl complexes. Salt metathesis of 1‐K with BBr\(_{3}\) resulted not only in N‐borylation but also Ph‐Br exchange between the endocyclic and exocyclic boron atoms. Solution \(^{11}\)B NMR data suggest that the 1,2‐azaborinin‐2‐yl ligand is similarly electron‐withdrawing to a bromide. In the solid state the endocyclic bond length alternation and the twisting of the C\(_{4}\)BN ring increase with the sterics of the substituents at the boron and nitrogen atoms, respectively. Regression analyses revealed that the downfield shift of the endocyclic \(^{11}\)B NMR resonances is linearly correlated to both the degree of twisting of the C\(_{4}\)BN ring and the tilt angle of the N‐substituent. Calculations indicate that the 1,2‐azaborinin‐1‐yl ligand has no sizeable π‐donor ability and that the aromaticity of the ring can be subtly tuned by the electronics of the N‐substituent.
Deep learning enables enormous progress in many computer vision-related tasks. Artificial Intel- ligence (AI) steadily yields new state-of-the-art results in the field of detection and classification. Thereby AI performance equals or exceeds human performance. Those achievements impacted many domains, including medical applications.
One particular field of medical applications is gastroenterology. In gastroenterology, machine learning algorithms are used to assist examiners during interventions. One of the most critical concerns for gastroenterologists is the development of Colorectal Cancer (CRC), which is one of the leading causes of cancer-related deaths worldwide. Detecting polyps in screening colonoscopies is the essential procedure to prevent CRC. Thereby, the gastroenterologist uses an endoscope to screen the whole colon to find polyps during a colonoscopy. Polyps are mucosal growths that can vary in severity.
This thesis supports gastroenterologists in their examinations with automated detection and clas- sification systems for polyps. The main contribution is a real-time polyp detection system. This system is ready to be installed in any gastroenterology practice worldwide using open-source soft- ware. The system achieves state-of-the-art detection results and is currently evaluated in a clinical trial in four different centers in Germany.
The thesis presents two additional key contributions: One is a polyp detection system with ex- tended vision tested in an animal trial. Polyps often hide behind folds or in uninvestigated areas. Therefore, the polyp detection system with extended vision uses an endoscope assisted by two additional cameras to see behind those folds. If a polyp is detected, the endoscopist receives a vi- sual signal. While the detection system handles the additional two camera inputs, the endoscopist focuses on the main camera as usual.
The second one are two polyp classification models, one for the classification based on shape (Paris) and the other on surface and texture (NBI International Colorectal Endoscopic (NICE) classification). Both classifications help the endoscopist with the treatment of and the decisions about the detected polyp.
The key algorithms of the thesis achieve state-of-the-art performance. Outstandingly, the polyp detection system tested on a highly demanding video data set shows an F1 score of 90.25 % while working in real-time. The results exceed all real-time systems in the literature. Furthermore, the first preliminary results of the clinical trial of the polyp detection system suggest a high Adenoma Detection Rate (ADR). In the preliminary study, all polyps were detected by the polyp detection system, and the system achieved a high usability score of 96.3 (max 100). The Paris classification model achieved an F1 score of 89.35 % which is state-of-the-art. The NICE classification model achieved an F1 score of 81.13 %.
Furthermore, a large data set for polyp detection and classification was created during this thesis. Therefore a fast and robust annotation system called Fast Colonoscopy Annotation Tool (FastCAT) was developed. The system simplifies the annotation process for gastroenterologists. Thereby the
i
gastroenterologists only annotate key parts of the endoscopic video. Afterward, those video parts are pre-labeled by a polyp detection AI to speed up the process. After the AI has pre-labeled the frames, non-experts correct and finish the annotation. This annotation process is fast and ensures high quality. FastCAT reduces the overall workload of the gastroenterologist on average by a factor of 20 compared to an open-source state-of-art annotation tool.
Among the parent borirane, benzoborirene and ortho‐dicarbadodecaborane‐fused borirane, the latter possesses the highest ring strain and the highest Lewis acidity according to our density functional theory (DFT) studies. The synthesis of this class of compounds is thus considerably challenging. The existing examples require either a strong π‐donating group or an extra ligand for B‐coordination, which nevertheless suppresses or completely turns off the Lewis acidity. The title compound, which possesses both features, not only allows the 1,2‐insertion of P=O, C=O or C≡N to proceed under milder conditions, but also enables the heretofore unknown dearomative 1,4‐insertion of Ar−(C=O)− into a B−C bond. The fusion of strained molecular systems to an o‐carborane cage shows great promise for boosting both the ring strain and acidity.
Isolated 2‐phenylallyl radicals (2‐PA), generated by pyrolysis from a nitrite precursor, have been investigated by IR/UV ion dip spectroscopy using free electron laser radiation. 2‐PA is a resonance‐stabilized radical that is considered to be involved in the formation of polycyclic aromatic hydrocarbons (PAH) in combustion, but also in interstellar space. The radical is identified based on its gas‐phase IR spectrum. Furthermore, a number of bimolecular reaction products are identified, showing that the self‐reaction as well as reactions with unimolecular decomposition products of 2‐PA form several PAH efficiently. Possible mechanisms are discussed and the chemistry of 2‐PA is compared with the one of the related 2‐methylallyl and phenylpropargyl radicals.
MDSCs are suppressive immune cells with a high relevance in various pathologies including cancer, autoimmunity, and chronic infections. Surface marker expression of MDSCs resembles monocytes and neutrophils which have immunostimulatory functions instead of suppressing T cells. Therefore, finding specific surface markers for MDSCs is important for MDSC research and therapeutic MDSC manipulation. In this study, we analyzed if the integrin VLA-1 has the potential as a novel MDSC marker. VLA-1 was expressed by M-MDSCs but not by G-MDSCs as well as by Teff cells. VLA-1 deficiency did not impact iNOS expression, the distribution of M-MDSC and G-MDSC subsets, and the suppressive capacity of MDSCs towards naïve and Teff cells in vitro. In mice, VLA-1 had no effect on the homing capability of MDSCs to the spleen, which is a major reservoir for MDSCs. Since the splenic red pulp contains collagen IV and VLA-1 binds collagen IV with a high affinity, we found MDSCs and Teff cells in this area as expected. We showed that T cell suppression in the spleen, indicated by reduced T cell recovery and proliferation as well as increased apoptosis and cell death, partially depended on VLA-1 expression by the MDSCs. In a mouse model of multiple sclerosis, MDSC injection prior to disease onset led to a decrease of the disease score, and this effect was significantly reduced when MDSCs were VLA-1 deficient. The expression of Sema7A by Teff cells, a ligand for VLA-1 which is implicated in negative T cell regulation, resulted in a slightly stronger Teff cell suppression by MDSCs compared to Sema7A deficient T cells. Live cell imaging and intravital 2-photon microscopy showed that the interaction time of MDSCs and Teff cells was shorter when MDSCs lacked VLA 1 expression, however VLA-1 expression had no impact on MDSC mobility. Therefore, the VLA-1-dependent interaction of MDSC and Teff cells on collagen IV in the splenic red pulp is implicated MDSC-mediated Teff cell suppression.
Activation of Ge−H and Sn−H Bonds with N‐Heterocyclic Carbenes and a Cyclic (Alkyl)(amino)carbene
(2023)
A study of the reactivity of several N‐heterocyclic carbenes (NHCs) and the cyclic (alkyl)(amino)carbene 1‐(2,6‐di‐iso‐propylphenyl)‐3,3,5,5‐tetramethyl‐pyrrolidin‐2‐ylidene (cAAC\(^{Me}\)) with the group 14 hydrides GeH2Mes2 and SnH2Me2 (Me=CH\(_{3}\), Mes=1,3,5‐(CH\(_{3}\))\(_{3}\)C\(_{6}\)H\(_{2}\)) is presented. The reaction of GeH\(_{2}\)Mes\(_{2}\) with cAAC\(^{Me}\) led to the insertion of cAAC\(^{Me}\) into one Ge−H bond to give cAAC\(^{Me}\)H−GeHMes\(_{2}\) (1). If 1,3,4,5‐tetramethyl‐imidazolin‐2‐ylidene (Me\(_{2}\)Im\(^{Me}\)) was used as the carbene, NHC‐mediated dehydrogenative coupling occurred, which led to the NHC‐stabilized germylene Me\(_{2}\)Im\(^{Me}\)⋅GeMes\(_{2}\) (2). The reaction of SnH\(_{2}\)Me\(_{2}\) with cAAC\(^{Me}\) also afforded the insertion product cAAC\(^{Me}\)H−SnHMe\(_{2}\) (3), and reaction of two equivalents Me\(_{2}\)Im\(^{Me}\) with SnH\(_{2}\)Me\(_{2}\) gave the NHC‐stabilized stannylene Me\(_{2}\)Im\(^{Me}\)⋅SnMe\(_{2}\) (4). If the sterically more demanding NHCs Me\(_{2}\)Im\(^{Me}\), 1,3‐di‐isopropyl‐4,5‐dimethyl‐imidazolin‐2‐ylidene (iPr\(_{2}\)Im\(^{Me}\)) and 1,3‐bis‐(2,6‐di‐isopropylphenyl)‐imidazolin‐2‐ylidene (Dipp\(_{2}\)Im) were employed, selective formation of cyclic oligomers (SnMe\(_{2}\))\(_{n}\) (5; n=5–8) in high yield was observed. These cyclic oligomers were also obtained from the controlled decomposition of cAAC\(^{Me}\)H−SnHMe\(_{2}\) (3).
Relativistic effects crucially influence the fundamental properties of many quantum materials. In the accelerated reference frame of an electron, the electric field of the nuclei is transformed into a magnetic field that couples to the electron spin. The resulting interaction between an electron spin and its orbital angular momentum, known as spin-orbit coupling (SOC), is hence fundamental to the physics of many condensed matter phenomena. It is particularly important quantitatively in low-dimensional quantum systems, where its coexistence with inversion symmetry breaking can lead to a splitting of spin degeneracy and spin momentum locking. Using the paradigm of Landau Fermi liquid theory, the physics of SOC can be adequately incorporated in an effective single particle picture. In a weak coupling approach, electronic correlation effects beyond single particle propagator renormalization can trigger Fermi surface instabilities such as itinerant magnetism, electron nematic phases, superconductivity, or other symmetry broken states of matter.
In this thesis, we use a weak coupling-based approach to study the effect of SOC on Fermi surface instabilities and, in particular, superconductivity. This encompasses a weak coupling renormalization group formulation of unconventional superconductivity as well as the random phase approximation. We propose a unified formulation for both of these two-particle Green’s function approaches based on the notion of a generalized susceptibility.
In the half-Heusler semimetal and superconductor LuPtBi, both SOC and electronic correlation
effects are prominent, and thus indispensable for any concise theoretical description. The metallic and weakly dispersive surface states of this material feature spin momentum locked Fermi surfaces, which we propose as a possible domain for the onset of unconventional surface superconductivity. Using our framework for the analysis of Fermi surface instability and combining it with ab-initio density functional theory calculations, we analyse the surface band structure of LuPtBi, and particularly its propensity towards Cooper pair formation. We study how the presence of strong SOC modifies the classification of two-electron wave functions as well as the screening of electron-electron interactions. Assuming an electronic mechanism, we identify a chiral superconducting condensate featuring Majorana edge modes to be energetically favoured over a wide range of model parameters.
Amber Light Control of Peptide Secondary Structure by a Perfluoroaromatic Azobenzene Photoswitch
(2023)
The incorporation of photoswitches into the molecular structure of peptides and proteins enables their dynamic photocontrol in complex biological systems. Here, a perfluorinated azobenzene derivative triggered by amber light was site‐specifically conjugated to cysteines in a helical peptide by perfluoroarylation chemistry. In response to the photoisomerization (trans→cis) of the conjugated azobenzene with amber light, the secondary structure of the peptide was modulated from a disorganized into an amphiphilic helical structure.
Azobenzene derivatives with activity against drug‐resistant Candida albicans and Candida auris
(2023)
Increasing resistance against antimycotic drugs challenges anti‐infective therapies today and contributes to the mortality of infections by drug‐resistant Candida species and strains. Therefore, novel antifungal agents are needed. A promising approach in developing new drugs is using naturally occurring molecules as lead structures. In this work, 4,4'‐dihydroxyazobenzene, a compound structurally related to antifungal stilbene derivatives and present in Agaricus xanthodermus (yellow stainer), served as a starting point for the synthesis of five azobenzene derivatives. These compounds prevented the growth of both fluconazole‐susceptible and fluconazole‐resistant Candida albicans and Candida auris strains. Further in vivo studies are required to confirm the potential therapeutic value of these compounds.
Proton‐coupled electron‐transfer (PCET) processes play a key role in biocatalytic energy conversion and storage, for example, photosynthesis or nitrogen fixation. Here, we report a series of bipyridine‐containing di‐ to tetranuclear Ru(bda) macrocycles 2 C–4 C (bda: 2,2′‐bipyridine‐6,6′‐dicarboxylate) to promote O−O bond formation. In photocatalytic water oxidation under neutral conditions, all complexes 2 C–4 C prevail in a folded conformation that support the water nucleophilic attack (WNA) pathway with remarkable turnover frequencies of up to 15.5 s\(^{−1}\) per Ru unit respectively. Single‐crystal X‐ray analysis revealed an increased tendency for intramolecular π‐π stacking and preorganization of the proximal bases close to the active centers for the larger macrocycles. H/D kinetic isotope effect studies and electrochemical data demonstrate the key role of the proximal bipyridines as proton acceptors in lowering the activation barrier for the crucial nucleophilic attack of H\(_{2}\)O in the WNA mechanism.
Carbene‐stabilized diborynes of the form LBBL (L=N‐heterocyclic carbene (NHC) or cyclic alkyl(amino)carbene (CAAC)) induce rapid, high yielding, intermolecular ortho‐C−H borylation at N‐heterocycles at room temperature. A simple pyridyldiborene is formed when an NHC‐stabilized diboryne is combined with pyridine, while a CAAC‐stabilized diboryne leads to activation of two pyridine molecules to give a tricyclic alkylideneborane, which can be forced to undergo a further H‐shift resulting in a zwitterionic, doubly benzo‐fused 1,3,2,5‐diazadiborinine by heating. Use of the extended N‐heteroaromatic quinoline leads to a borylmethyleneborane under mild conditions via an unprecedented boron‐carbon exchange process.
Perylene bisimides (PBIs) are among the best fluorophores but have to be enwrapped for optoelectronic applications by large and heavy substituents to prevent their ππ‐stacking, which is known to accelerate non‐radiative decay processes in the solid state. Here, light‐weight di‐tert‐butylsilyl groups are introduced to bridge 1,12‐dihydroxy and 1,6,7,12‐tetrahydroxy PBIs to afford sublimable dyes for vacuum‐processed optoelectronic devices. For both new compounds, this substitution provides a twisted and shielded perylene π‐core whose, via OSiObridges, rigid structure affords well‐resolved absorption and emission spectra with strong fluorescence in solution, as well as in the solid state. The usefulness of these dyes for vacuum‐processed optoelectronic devices is demonstrated in organic light‐emitting diodes (OLEDs) that show monomer‐like emission spectra and high maximum external quantum efficiency (EQEmax) values of up to 3.1% for the doubly silicon‐bridged PBI.
The great progress in organic photovoltaics (OPV) over the past few years has been largely achieved by the development of non‐fullerene acceptors (NFAs), with power conversion efficiencies now approaching 20%. To further improve device performance, loss mechanisms must be identified and minimized. Triplet states are known to adversely affect device performance, since they can form energetically trapped excitons on low‐lying states that are responsible for non‐radiative losses or even device degradation. Halogenation of OPV materials has long been employed to tailor energy levels and to enhance open circuit voltage. Yet, the influence on recombination to triplet excitons has been largely unexplored. Using the complementary spin‐sensitive methods of photoluminescence detected magnetic resonance and transient electron paramagnetic resonance corroborated by transient absorption and quantum‐chemical calculations, exciton pathways in OPV blends are unravelled employing the polymer donors PBDB‐T, PM6, and PM7 together with NFAs Y6 and Y7. All blends reveal triplet excitons on the NFA populated via non‐geminate hole back transfer and, in blends with halogenated donors, also by spin‐orbit coupling driven intersystem crossing. Identifying these triplet formation pathways in all tested solar cell absorber films highlights the untapped potential for improved charge generation to further increase plateauing OPV efficiencies.
Insights;
(2023)
The cluster of texts assembled here were imagined, crafted, and brought together as a collaborative writing project that emerged from the seminar titled "Words Matter Worlds: Activist Scholarship and Literary Praxis," which convened over the course of the 2021/22 winter semester as an offering of the American Studies department of the Julius-Maximilians-Universität Würzburg. Like the seminar that nurtured the considerations that evolve here, these contributions engage with how scholarly writing practices in general, and literary and cultural studies in particular, can remake the world.
Mineral biocements are brittle materials, which usually results in catastrophic failure during mechanical loading. Here, previous works demonstrated the feasibility of reducing brittleness by a dual-setting approach, in which a silica sol was simultaneously gelled during the setting of a brushite forming cement. The current thesis aimed at further improving this concept by both using a novel silicate based cement matrix for an enhanced bonding between cement and silica matrix as well as multifunctional silica precursors to increase the network density of the gel. Due to its well-known biocompatibility and osteogenic regeneration capacity, baghdadite was chosen as mineral component of such composites. This required in a first approach the conversion of baghdadite ceramics into self-setting cement formulations. This was investigated initially by using baghdadite as reactive filler in a brushite forming cement (Chapter 4). Here, the ß-TCP component in a equimolar mixture of ß-TCP and acidic monocalcium phosphate anhydrous was subsequently replaced by baghdadite at various concentrations (0, 5, 10, 20, 30, 50, and 100 wt%) to study the influence on physicochemical cement properties such as mechanical performance, radiopacity, phase composition and microstructure. X-ray diffraction profiles demonstrated the dissolution of baghdadite during the cement reaction without affecting the crystal structure of the precipitated brushite phase. In addition, EDX analysis showed that calcium is homogeneously distributed in the cement matrix, while zirconium and silicon form cluster-like aggregates ranging in size from a few micrometers to more than 50 µm. X-ray images and µ-CT analyses indicate improved X-ray visibility with increased incorporation of baghdadite in brushite cement, with an aluminum equivalent thickness nearly doubling at a baghdadite content of 50 wt%. At the same time, the compressive strength of brushite cement increased from 12.9 ± 3.1 MPa to 21.1 ± 4.1 MPa at a baghdadite content of 10 wt%. Cell culture medium conditioned with powdered brushite cement approached physiological pH values when increasing amounts of baghdadite were added to the cement (pH = 6.47 for pure brushite, pH = 7.02 for brushite with 20 wt% baghdadite substitution). Baghdadite substitution also affected the ion content in the culture medium and thus the proliferation activity of primary human osteoblasts in vitro. The results demonstrated for the first time the suitability of baghdadite as a reactive cement additive for improving the radiopacity, mechanical performance, and cytocompatibility of brushite cements.
A second approach (Chapter 5) aimed to produce single component baghdadite cements by an increase of baghdadite solubility to initiate a self-setting cement reaction. For this, the material was mechanically activated by longer grinding times of up to 24h leading to both a decrease in particle and crystallite size as well as a partial amorphization of baghdadite. Baghdadite cements were formed by adding water at a powder to liquid ratio of 2.0 g/ml. Maximum compressive strengths were determined to be ~2 MPa after 3 days of setting for a 24-hour ground material. Inductively coupled plasma mass spectrometry (ICP-MS) measurements showed an incongruent dissolution profile of the set cements, with preferential dissolution of calcium and only minor release of zirconium ions. Cement formation occurs under alkaline conditions, with the unground raw powder resulting in a pH of 11.9 during setting, while prolonged grinding increases the pH to about 12.3.
Finally, mechanically activated baghdadite cements were combined with inorganic silica networks (Chapter 6) to create dual-setting cements with a further improvement of mechanical performance. While a modification of the cement pastes with a TEOS derived sol was already thought to improve strength, it was hypothesized that using multi-arm silica precursors can further enhance their mechanical performance due to a higher network density. In addition, this should also reduce pore size of both gels and cement and hence will be able to adjust the release kinetics of incorporated drugs. For this, multi-armed silica precursors were synthesized by the reaction of various multivalent alcohols (ethylene glycol, glycerine, pentaerythrit) with an isocyanate modified silica precursor. After hydrolysis under acidic conditions, the sols were mixed with baghdadite cement powders in order to allow a simultaneous gel formation and cement setting. Since the silica monomers have a high degree of linkage sites, this resulted in a branched network that interpenetrated with the growing cement crystals. In addition to minor changes in the crystalline phase composition as determined by X-ray diffraction, the novel composites exhibited improved mechanical properties with up to 20 times higher compressive strength and further benefit from an about 50% lower overall porosity than the reference pure baghdadite cement. In addition, the initial burst release of the model drug vancomycin was completely inhibited by the added silica matrix. This observation was verified by testing for the antimicrobial activity with Staphylococcus aureus by measuring the inhibition zones of selected samples after 24 h and 48 h, whereas the antimicrobial effectiveness of a constant vancomycin release could be demonstrated.
The current thesis clearly demonstrated the high potential of baghdadite as a cement formulation for medical application. The initially poor mechanical properties of such cements can be overcome by special processing techniques or by combination with silica networks. The achieved mechanical performance is > 10 MPa and hence suitable for bone replacement under non-load bearing conditions. The high intrinsic radiopacity as well as the alkaline pH during setting may open the way ahead to further dental applications, e.g. as root canal sealers or filler in dental composites. Here, the high pH is thought to lead to antimicrobial properties of such materials similar to commonly applied calcium hydroxide or calcium silicates, however combined with an intrinsic radiopacity for X-ray imaging. This would simplify such formulations to single component materials which are less susceptible to demixing processes during transport, storage or processing.
Onchocerciasis, the world's second-leading infectious cause of blindness in humans
–prevalent in Sub-Saharan Africa – is caused by Onchocerca volvulus (O. volvulus), an
obligatory human parasitic filarial worm. Commonly known as river blindness,
onchocerciasis is being targeted for elimination through ivermectin-based mass
drug administration programs. However, ivermectin does not kill adult parasites,
which can live and reproduce for more than 15 years within the human host. These
impediments heighten the need for a deeper understanding of parasite biology and
parasite-human host interactions, coupled with research into the development of
new tools – macrofilaricidal drugs, diagnostics, and vaccines. Humans are the only
definitive host for O. volvulus. Hence, no small-animal models exist for propagating
the full life cycle of O. volvulus, so the adult parasites must be obtained surgically
from subcutaneous nodules. A two-dimensional (2D) culture system allows that
O. volvulus larvae develop from the vector-derived infective stage larvae (L3) in vitro
to the early pre-adult L5 stages. As problematic, the in vitro development of
O. volvulus to adult worms has so far proved infeasible. We hypothesized that an
increased biological complexity of a three-dimensional (3D) culture system will
support the development of O. volvulus larvae in vitro. Thus, we aimed to translate
crucial factors of the in vivo environment of the developing worms into a culture
system based on human skin. The proposed tissue model should contain 1. skinspecific
extracellular matrix, 2. skin-specific cells, and 3. enable a direct contact of
larvae and tissue components. For the achievement, a novel adipose tissue model
was developed and integrated to a multilayered skin tissue comprised of epidermis,
dermis and subcutis. Challenges of the direct culture within a 3D tissue model
hindered the application of the three-layered skin tissue. However, the indirect coculture
of larvae and skin models supported the growth of fourth stage (L4) larvae in
vitro. The direct culture of L4 and adipose tissue strongly improved the larvae
survival. Furthermore, the results revealed important cues that might represent the
initial encapsulation of the developing worm within nodular tissue. These results
demonstrate that tissue engineered 3D tissues represent an appropriate in vitro
environment for the maintenance and examination of O. volvulus larvae.
For all animals the cold represents a dreadful danger. In the event of severe heat loss, animals
fall into a chill coma. If this state persists, it is inevitably followed by death. In poikilotherms
(e.g. insects), the optimal temperature range is narrow compared to homeotherms
(e.g. mammals), resulting in a critical core temperature being reached more quickly. As a
consequence, poikilotherms either had to develop survival strategies, migrate or die. Unlike
the majority of insects, the Western honeybee (Apis mellifera) is able to organize itself into
a superorganism. In this process, worker bees warm and cool the colony by coordinated
use of their flight muscles. This enables precise control of the core temperature in the hive,
analogous to the core body temperature in homeothermic animals. However, to survive the
harsh temperatures in the northern hemisphere, the thermogenic mechanism of honeybees
must be in constant readiness. This mechanism is called shivering thermogenesis, in which
honeybees generate heat using their flight muscles.
My thesis presents the molecular and neurochemical background underlying shivering thermogenesis
in worker honeybees. In this context, I investigated biogenic amine signaling.
I found that the depletion of vesicular monoamines impairs thermogenesis, resulting in
a decrease in thoracic temperature. Subsequent investigations involving various biogenic
amines showed that octopamine can reverse this effect. This clearly indicates the involvement
of the octopaminergic system. Proceeding from these results, the next step was to elucidate
the honeybee thoracic octopaminergic system. This required a multidisciplinary approach to
ultimately provide profound insights into the function and action of octopamine at the flight
muscles. This led to the identification of octopaminergic flight muscle controlling neurons,
which presumably transport octopamine to the flight muscle release sites. These neurons
most likely innervate octopamine β receptors and their activation may stimulate intracellular
glycolytic pathways, which ensure sufficient energy supply to the muscles.
Next, I examined the response of the thoracic octopaminergic system to cold stress conditions.
I found that the thoracic octopaminergic system tends towards an equilibrium,
even though the initial stress response leads to fluctuations of octopamine signaling. My
results indicate the importance of the neuro-muscular octopaminergic system and thus the need for its robustness. Moreover, cold sensitivity was observed for the expression of one
transcript of the octopamine receptor gene AmOARβ2. Furthermore, I found that honeybees
without colony context show a physiological disruption within the octopaminergic system.
This disruption has profound effects on the honeybees protection against the cold.
I could show how important the neuro-muscular octopaminergic system is for thermogenesis
in honeybees. In this context, the previously unknown neurochemical modulation of the
honeybee thorax has now been revealed. I also provide a broad basis to conduct further
experiments regarding honeybee thermogenesis and muscle physiology.
Social contact is an integral part of daily life. Its health-enhancing effects include reduced negative affective experiences of fear and anxiety, a phenomenon called social buffering. This dissertation studied different forms of social contact and their anxiety-buffering effects with diverse methodologies.
The laboratory-based first study investigated minimal social contact in the context of pain relief learning. Results showed that the observed decreased autonomic and increased subjective fear responses following pain relief learning were independent of social influence. The minimalistic and controlled social setting may have prevented social buffering. Study 2 targeted social buffering in daily life using Ecological Momentary Assessment. We repeatedly assessed individuals’ state anxiety, related cardiovascular responses, and aspects of social interactions with smartphones and portable sensors on five days. Analyses of over 1,500 social contacts revealed gender-specific effects, e.g., heart rate-reducing effects of familiarity in women, but not men. Study 3 examined anxiety, loneliness, and related social factors in the absence of social contact due to social distancing. We constructed and validated a scale measuring state and trait loneliness and isolation, and analysed its link to mental health. Results include a social buffering-like relation of lower anxiety with more trait sociability and sense of belonging.
In sum, the studies showed no fear reduction by minimal social contact, but buffering effects relating to social and personal factors in more complex social situations. Anxiety responses during daily social contacts were lower with more familiar or opposite-gender interaction partners. During limited social contact, lower anxiety related to inter-individual differences in sociability, social belonging, and loneliness. By taking research from lab to life, this dissertation underlined the diverse nature of social contact and its relevance to mental health.
The mammalian central clock, located in the suprachiasmatic nucleus (SCN) of the anterior hypothalamus, controls circadian rhythms in behaviour such as the sleep-wake cycle. It is made up of approximately 20,000 heterogeneous neurons that can be classified by their expression of neuropeptides. There are three major populations: AVP neurons (arginine vasopressin), VIP neurons (vasoactive intestinal peptide), and GRP neurons (gastrin releasing peptide). How these neuronal clusters form functional units to govern various aspects of rhythmic behavior is poorly understood. At a molecular level, biological clocks are represented by transcriptional-posttranslational feedback loops that induce circadian oscillations in the electrical activity of the SCN and hence correlate with behavioral circadian rhythms. In mammals, the sleep wake cycle can be accurately predicted by measuring electrical muscle and brain activity. To investigate the link between the electrical activity of heterogeneous neurons of the SCN and the sleep wake cycle, we optogenetically manipulated AVP neurons in vivo with SSFO (stabilized step function opsin) and simultaneously recorded an electroencephalogram (EEG) and electromyogram (EMG) in freely moving mice. SSFO-mediated stimulation of AVP positive neurons in the anterior hypothalamus increased the total amount of wakefulness during the hour of stimulation. Interestingly, this effect led to a rebound in sleep in the hour after stimulation. Markov chain sleep-stage transition analysis showed that the depolarization of AVP neurons through SSFO promotes the transition from all states to wakefulness. After the end of stimulation, a compensatory increase in transitions to NREM sleep was observed. Ex vivo, SSFO activation in AVP neurons causes depolarization and modifies the activity of AVP neurons. Therefore, the results of this thesis project suggest an essential role of AVP neurons as mediators between circadian rhythmicity and sleep-wake behaviour.
The last years have witnessed an exciting scientific quest for intriguing topological phenomena in time-dependent quantum systems. A key to many manifestations of topology in dynamical systems relies on the effective dimensional extension by time-periodic drives. An archetypal example is provided by the Thouless pump in one spatial dimension, where a robust and quantized charge transport can be described in terms of an integer quantum Hall effect upon interpreting time as an extra dimension. Generalizing this fundamental concept to multifrequency driving, a variety of higher-dimensional topological models can be engineered in dynamical synthetic dimensions, where the underlying topological classification leads to quantized pumping effects in the associated lower-dimensional time-dependent systems.
In this Thesis, we explore how correlations profoundly impact the topological features of dynamical synthetic quantum materials. More precisely, we demonstrate that the interplay of interaction and dynamical synthetic dimension gives rise to striking topological phenomena that go beyond noninteracting implementations. As a starting point, we exploit the Floquet counterpart of an integer quantum Hall scenario, namely a two-level system driven by two incommensurate frequencies. In this model, the topologically quantized response translates into a process in which photons of different frequencies are exchanged between the external modes, referred to as topological frequency conversion. We extend this prototypical setup to an interacting version, focusing on the minimal case of two correlated spins equally exposed to the external drives. We show that the topological invariant determining the frequency conversion can be changed by odd integers, something explicitly forbidden in the noninteracting limit of two identical spins. This correlated topological feature may, in turn, result in an enhancement of the quantized response.
Robust response signals, such as those predicted for the topological frequency converter, are of fundamental interest for potential technological applications of topological quantum matter. Based on an open quantum system implementation of the frequency converter, we propose a novel mechanism of topological quantization coined ''topological burning glass effect''. Remarkably, this mechanism amplifies the local response of the driven two-level system by an integer that is proportional to the number of environmental degrees of freedom to which the system is strongly coupled. Specifically, our findings are illustrated by the extension of the frequency converter to a central spin model. There, the local energy transfer mediated exclusively by the central spin is significantly enhanced by the collective motion of the surrounding spins. In this sense, the central spin adopts the topological nature of the total system in its non-unitary dynamics, taking into account the correlations with the environment.
The life of an exciton: From ultrafast nonradiative relaxation to high quantum yield fluorescence
(2023)
This thesis focuses on understanding and predicting processes in chromophores after electronic state excitation, particularly the impact on luminescence - the spontaneous emission of light. It considers the effect of processes preceding luminescence on emission properties, which are challenging to predict, especially in complex aggregates.
For example, excitation energy transfer is a crucial process in understanding luminescence, as it allows the emission to occur from different molecular units than where the absorption occurs. This can lead to significant shifts in emission wavelength and fluorescence quantum yields. The thesis offers solutions to model this process effectively, understanding the impact of excitation energy and exciton coupling disorder on energy transfer rates and linking simulated energy transfer to experimental measurements.
The work further explores excimer formation - an undesired luminescence loss channel due to its significant stabilization of the electronic state. Usually, the molecules obey a stacked conformation with parallel orientation to maximize the orbital overlap. This energetic lowering of the excited state can often result in trapping of the dimer in this state due to a deep minimum on the potential energy surface. The excimer formation dynamics, structural rearrangement, and its influence on singlet-correlated triplet pair states formation, critical for the singlet-fission process, have been extensively studied.
The thesis also focuses on another luminescence loss channel triggered by conical intersections between the electronic ground and the first excited states. A new model is introduced to overcome limitations in current simulation methods, considering the solvent's electrostatic and frictional effects on the barriers. The model accurately describes merocyanine dyes' solvent-dependent photoluminescence quantum yields and characterizes all relaxation channels in different BODIPY oligomer series.
The Wuertual Reality XR Meeting 2023 was initiated to bring together researchers from many fields who use VR/AR/XR. There was a focus on applied XR and social VR.
In this conference band, you can find the abstracts of the two keynotes, the 34 posters and poster pitches, the 29 talks and the four workshops.
The fusion of methods from several disciplines is a crucial component of scientific development. Artificial Neural Networks, based on the principle of biological neuronal networks, demonstrate how nature provides the best templates for technological advancement. These innovations can then be employed to solve the remaining mysteries of biology, including, in particular, processes that take place on microscopic scales and can only be studied with sophisticated techniques. For instance, direct Stochastic Optical Reconstruction Microscopy combines tools from chemistry, physics, and computer science to visualize biological processes at the molecular level. One of the key components is the computer-aided reconstruction of super-resolved images. Improving the corresponding algorithms increases the quality of the generated data, providing further insights into our biology. It is important, however, to ensure that the heavily processed images are still a reflection of reality and do not originate in random artefacts.
Expansion microscopy is expanding the sample by embedding it in a swellable hydrogel. The method can be combined with other super-resolution techniques to gain additional resolution. We tested this approach on microtubules, a well-known filamentous reference structure, to evaluate the performance of different protocols and labelling techniques.
We developed LineProfiler an objective tool for data collection. Instead of collecting perpendicular profiles in small areas, the software gathers line profiles from filamentous structures of the entire image. This improves data quantity, quality and prevents a biased choice of the evaluated regions. On the basis of the collected data, we deployed theoretical models of the expected intensity distribution across the filaments. This led to the conclusion that post-expansion labelling significantly reduces the labelling error and thus, improves the data quality. The software was further used to determine the expansion factor and arrangement of synaptonemal complex data.
Automated Simple Elastix uses state-of-the-art image alignment to compare pre- and post-expansion images. It corrects linear distortions occurring under isotropic expansion, calculates a structural expansion factor and highlights structural mismatches in a distortion map. We used the software to evaluate expanded fungi and NK cells. We found that the expansion factor differs for the two structures and is lower than the overall expansion of the hydrogel.
Assessing the fluorescence lifetime of emitters used for direct Stochastic Optical Reconstruction Microscopy can reveal additional information about the molecular environment or distinguish dyes emitting with a similar wavelength. The corresponding measurements require a confocal scanning of the sample in combination with the fluorescent switching of the underlying emitters. This leads to non-linear, interrupted Point Spread Functions. The software ReCSAI targets this problem by combining the classical algorithm of compressed sensing with modern methods of artificial intelligence. We evaluated several different approaches to combine these components and found, that unrolling compressed sensing into the network architecture yields the best performance in terms of reconstruction speed and accuracy.
In addition to a deep insight into the functioning and learning of artificial intelligence in combination with classical algorithms, we were able to reconstruct the described non-linearities with significantly improved resolution, in comparison to other state-of-the-art architectures.
Mass spectrometry-based quantification of steroids for the diagnostic workup of adrenal tumors
(2023)
Tumors of the adrenal gland belong to the most frequent neoplasms in humans with a prevalence of 3–10 % in adults. The aim of the diagnostic workup is the identification of potentially hormone-secreting and / or malignant tumors, because most of these tumors will require surgical resection. Malignant adrenocortical carcinomas (ACC) are very rare and associated with a poor prognosis in advanced stages, therefore, an early and accurate diagnosis is crucial.
Within this thesis, two liquid chromatography tandem mass spectrometry (LC-MS/MS) methods for the quantification of steroids in different biomaterials were developed to improve the diagnostic workup of adrenal tumors.
First, an LC-MS/MS method for the simultaneous quantification of cortisol and dexamethasone in serum samples after dexamethasone suppression test (DST) was developed, validated, and applied to 400 clinical samples. Newly established method-specific threshold concentrations for cortisol and dexamethasone increased DST specificity from 67.5 % to 92.4 % while preserving 100 % sensitivity.
Second, an LC-MS/MS method for the quantification of eleven urinary steroids was developed and validated to improve the differentiation between ACC and adrenocortical adenomas (ACA). A decision tree requiring only two steroids was trained for classification and tested based on 24 h urine samples from 268 patients with adrenal tumor. Malignancy was excluded with a negative predictive value of 100 % in an independent validation cohort of 84 samples of 24-h urine. A newly proposed simplified diagnostic workflow with urinary steroid profiling as first tier test could obviate additional adrenal-specific imaging in 42 of 64 patients with ACA.
The new DST method is already in clinical use at the University Hospital Würzburg, whereas the classification model based on urinary steroid profiling will require prospective validation in a larger cohort.
The present study discusses money and conflicts and anxiety over money in late Ming vernacular stories and contextualizes these stories in the contemporary society of economic prosperity and rapid changes. The high monetization and extensive use of silver and copper cash as currency brought both wealth and conflicts in various aspects of society. Eleven vernacular stories from several collections are adopted as source materials for the close examination, including Jingshi tongyan (Stories to Caution the World, 1624) and Xingshi hengyan (Stories to Awaken the World, 1627) by Feng Menglong (1574-1646) and the two Pai’an jingqi (Slapping the Table in Amazement, 1628 and 1632) collections by Ling Mengchu (1580-1644), etc. The analysis then focuses on the relationship between money and four topics, the late Ming context, social relations, gender ideals, and religion. Multiple voices and various viewpoints in these narratives show human beings’ struggles in taming and dominating money, the increasingly familiar and essential object in everyday life. Generally, when people cannot control money properly, there is a fear of its detrimental power to humans and social relations within and beyond families. On the contrary, characters, who are able to control money, are praised.
Glioblastoma (GB) is the most aggressive malignant adult brain tumour with a median survival rate of only 15 months. GB tumours are characterized by necrotic and hypoxic core, which leads to nutrient deficient areas contributing to invasive, diffuseinfiltrative and angiogenic nature of these tumours. Cells exposed to nutrient deficient conditions and are known to reprogram their metabolism to produce or procure macro molecules from their environment. This makes cancer cells uniquely dependent on transcriptional regulators and a window of opportunity to target them. Sterol regulatory element binding protein 1 (SREBP1) is a transcriptional regulator of de-novo fatty acid synthesis in cells. The aim of this thesis was to investigate if SREBP1 was involved in restructuring the transcriptional regulation of genes involved in fatty acid biosynthesis upon low serum condition, in mediating interaction with other cell types in the tumour bulk such as endothelial cells, in regulating cancer stem like cells and finally to study its upstream regulation in GB. Global transcriptional analysis on GB cells exposed to low serum conditions revealed that SREBP1 regulated several fatty acid biosynthesis and phospholipid metabolic processes. PLA2G3 was identified as a novel target of SREBP1 in GB that was uniquely regulated in low serum condition. Analysis of total fatty acid and lipid species revealed that loss of SREBP1 in low serum condition changes the proportion of saturated, MUFAs and PUFAs. These changes were not specific to loss of PLA2G3 but as a result of downregulation of many genes regulated by SREBP1 in the fatty acid biosynthetic pathway. Next, treatment of HUVEC’s (endothelial cells) with condition medium from SREBP1-silenced U87 cells inhibited sprouting and tube formation capacity compared to the control condition, emphasizing the role of SREBP1 in angiogenesis and release of signalling mediators. Further, SREBP1 was shown to be important for proliferation of patient derived stem like cells and becomes indispensable for forming neurospheres in long term cultures, indicating its role in maintaining stemness. Also, inhibition of SREBP function by blocking the esterification of cholesterol using inhibitors targeting SOAT1 showed impairment in the viability of GB cells exposed to serum-depleted condition. Overall, SREBP1 plays an important role in maintaining tumour growth in nutrient deficient conditions and help in interaction with tumour microenvironment contributing to the aggressiveness of this tumour and poses itself as an attractive and unique target for GB treatment
Diabetes mellitus is an incurable, metabolic disease, which is associated with severe long-term complications. The in vitro generation of pancreatic β-cells from human induced pluripotent stem cells (hiPSCs) represent a promising strategy for a curative therapy of diabetes mellitus. However, current differentiation strategies largely fail to produce functional β-cells in vitro and require an additional in vivo transplantation to achieve terminal maturation. Previous studies demonstrated a beneficial effect of the extracellular matrix (ECM) on the survival and sustained function of adult, isolated islets of Langerhans. This raises the question whether organ-specific cell-ECM interactions might represent the missing link driving the final stage of β-cell development. In order to address this issue, this study investigated the impact of the pancreas ECM on in vitro β-cell differentiation and its use for the establishment of a pancreatic endocrine organ model.
To this purpose, a pancreas-specific ECM scaffolds (PanMa) was derived from porcine pancreata using whole organ decellularization with Sodium Deoxycholate. In a first step, the generated PanMa was thoroughly characterized using (immuno-) histological stainings, scanning electron microscopy and DNA quantification as well as perfusion and recellularization experiments with endothelial cells. Based on these data, a scoring system (PancScore) for a standardized PanMa generation was developed. Next, the generated PanMa was tested for the presence of tissue-specific ECM features. Therefore, the biophysical and physico-structural characteristics, such as rigidity, porosity and hygroscopy were analyzed using rheological measurements, particle diffusion analyses as well as a water evaporation assay and compared to the properties of ECM scaffolds derived from porcine small intestine (SISser) and lung (LungMa) to examine organ-specific scaffold cues. Following the thorough scaffold characterization, the impact of the PanMa on pluripotency and early development of hiPSC was studied. To this purpose, gene and protein expression of hiPSCs during maintenance culture and spontaneous differentiation on the PanMa were assessed. In a next step, the impact of the PanMa on the pancreatic endocrine differentiation of hiPSCs was tested. Therefore, the PanMa was used as a liquid media supplement or as a solid scaffold during the directed differentiation of hiPSC towards either pancreatic hormone-expressing cells (Rezania et al. 2012; Rezania et al. 2014) or maturing β-cells (Rezania et al. 2014). The impact of the PanMa on the generated cells was examined by gene expression analysis, immunohistochemical staining of important stage markers, as well as glucose stimulated insulin secretion assays. In a last part of this study, the potential of the PanMa for the prolonged culture of hiPSC derived endocrine cells for the establishment of an in vitro organ model of the endocrine pancreas was examined. Therefore, a PanMa-derived hydrogel was generated and used for the encapsulation and culture of hiPSC-derived hormone-expressing cells (HECs). The influence of the PanMa-hydrogel culture was analyzed on gene, protein and functional level by gene expression analysis, immunohistochemical stainings and glucose stimulated insulin secretion.
Whole organ decellularization resulted in the generation of an acellular PanMa scaffold, with low amounts of residual DNA and a preserved ECM micro- and ultrastructure, including important ECM components, such as collagen I, III and IV. Furthermore, the PanMa maintained an intact vessel system and was verified as cytocompatible as demonstrated by the successful recellularization of the arterial system with human endothelial cells. In comparison to SISser and LungMa, the PanMa was characterized as a relative soft, hygroscopic scaffold with a collagen-fiber based structure. Furthermore, the findings indicate that the ECM-specific properties have a relevant effect on the stem cell character and early multi-lineage decisions of hiPSCs. In this regard, maintenance of hiPSCs on the PanMa resulted in a slightly changed expression of pluripotency genes (OCT4, SOX2 and NANOG) and a weak immunohistochemical signal for NANOG protein, indicating a PanMa-dependent impact on hiPSC pluripotency. Strikingly, this presumption was corroborated by the finding that culture on the PanMa promoted an endodermal development of hiPSCs during spontaneous differentiation. In line with that, pancreatic differentiation of hiPSC on both the PanMa and SISser resulted in a significant decrease of glucagon and somatostatin gene expression as well as an unaltered insulin expression, suggesting an ECM-driven suppression of the development of non β-cell endocrine cells. However, this change did not result in an improved glucose stimulated insulin secretion of the generated HECs. Moreover, use of the PanMa as a hydrogel allowed prolonged culture of these cells in a defined culture system. HECs were viable after 21 days of culture, however already showed an altered islet morphology as well as a slightly decreased glucose stimulated insulin secretion.
Altogether, this study demonstrates a relevant biological effect of tissue specific ECM cues on the in vitro differentiation of hiPSCs. More specifically, the data indicate an involvement of the ECM in the endocrine commitment of hiPSC-derived pancreatic cells during directed differentiation highlighting the ECM as an important regulator of pancreatic development. Collectively, these findings emphasize the relevance of the ECM for the fabrication of functional hiPSC-derived cell types and suggest a much stronger consideration of organ specific ECM cues for tissue engineering approaches as well as clinical translation in regenerative medicine.
The Wuertual Reality XR Meeting 2023 was initiated to bring together researchers from many fields who use VR/AR/XR. There was a focus on applied XR and social VR.
In this conference band, you can find the abstracts of the two keynotes, the 34 posters and poster pitches, the 29 talks and the four workshops.
To reach their target site, systemic pesticides must enter the plant from a spray droplet applied in the field. The uptake of an active ingredient (AI) takes place via the barrier-forming cuticular membrane, which is the outermost layer of the plant, separating it from the surrounding environment. Formulations are usually used which, in addition to the AI, also contain stabilizers and adjuvants. Adjuvants can either have surface-active properties or they act directly as barrier-modifying agents. The latter are grouped in the class of accelerating adjuvants, whereby individual variants may also have surface-active properties. The uptake of a pesticide from a spray droplet depends essentially on its permeability through the cuticular barrier. Permeability defines a combined parameter, which is the product of AI mobility and AI solubility within the cuticle. In recent decades, several tools have been developed that allowed the determination of individual parameters of organic compound penetration across the cuticular membrane. Nevertheless, earlier studies showed that mainly cuticular waxes are the barrier-determining component of the cuticular membrane and additionally, it was shown that mainly the very-long-chain aliphatic compounds (VLCAs) are responsible for establishing an effective barrier. However, the barrier-determining role of the individual VLCAs, being classified according to their respective functional groups, is still unknown.
Therefore, the following objectives were pursued and achieved in this work: (1) A new ATR-FTIR-based approach was developed to measure the temperature-dependent real-time diffusion kinetics of organic models for active ingredients (AIs) in paraffin wax, exclusively consisting of very-long chain alkanes. (2) The developed ATR-FTIR approach was applied to determine the diffusion kinetics of self-accelerating adjuvants in cuticular model waxes of different VLCA composition. At the same time, wax-specific changes were recorded in the respective IR spectra, which provided information about the respective wax modification. (3) The ATR-FTIR method was used to characterize the diffusion kinetics, as well as to determine the wax-specific sorption capacities for an AI-modeling organic compound and water in cuticular model waxes after adjuvant treatment. Regarding the individual chemical compositions and structures, conclusions were drawn about the adjuvant-specific modes of action (MoA).
In the first chapter, the ATR-FTIR based approach to determine organic compound diffusion kinetics in paraffin wax was successfully established. The diffusion kinetics of the AI modelling organic compounds heptyl parabene (HPB) and 4-cyanophenol (CNP) were recorded, comprising different lipophilicities and molecular volumes typical for AIs used in pesticide formulations. Derived diffusion coefficients ranged within 10-15 m2 s-1, thus being thoroughly higher than those obtained from previous experiments using an approach solely investigating desorption kinetics in reconstituted cuticular waxes. An ln-linear dependence between the diffusion coefficients and the applied diffusion temperature was demonstrated for the first time in cuticular model wax, from which activation energies were derived. The determined activation energies were 66.2 ± 7.4 kJ mol-1 and 56.4 ± 9.8 kJ mol-1, being in the expected range of already well-founded activation energies required for organic compound diffusion across cuticular membranes, which again confirmed the significant contribution of waxes to the cuticular barrier. Deviations from the assumed Fickian diffusion were attributed to co-occurring water diffusion and apparatus-specific properties.
In the second and third chapter, mainly the diffusion kinetics of accelerating adjuvants in the cuticular model waxes candelilla wax and carnauba wax were investigated, and simultaneously recorded changes in the wax-specific portion of the IR spectrum were interpreted as indications of plasticization. For this purpose, the oil derivative methyl oleate, as well as the organophosphate ester TEHP and three non-ionic monodisperse alcohol ethoxylates (AEs) C12E2, C12E4 and C12E6 were selected. Strong dependence of diffusion on the respective principal components of the mainly aliphatic waxes was demonstrated. The diffusion kinetics of the investigated adjuvants were faster in the n-alkane dominated candelilla wax than in the alkyl ester dominated carnauba wax. Furthermore, the equilibrium absorptions, indicating equilibrium concentrations, were also higher in candelilla wax than in carnauba wax. It was concluded that alkyl ester dominated waxes feature higher resistance to diffusion of accelerating adjuvants than alkane dominated waxes with shorter average chain lengths due to their structural integrity. This was also found either concerning candelilla/policosanol (n-alcohol) or candelilla/rice bran wax (alkyl-esters) blends: with increasing alcohol concentration, the barrier function was decreased, whereas it was increased with increasing alkyl ester concentration. However, due to the high variability of the individual diffusion curves, only a trend could be assumed here, but significant differences were not shown. The variability itself was described in terms of fluctuating crystalline arrangements and partial phase separation of the respective wax mixtures, which had inevitable effects on the adjuvant diffusion. However, diffusion kinetics also strongly depended on the studied adjuvants. Significantly slower methyl oleate diffusion accompanied by a less pronounced reduction in orthorhombic crystallinity was found in carnauba wax than in candelilla wax, whereas TEHP diffusion was significantly less dependent on the respective wax structure and therefore induced considerable plasticization in both waxes. Of particular interest was the AE diffusion into both waxes. Differences in diffusion kinetics were also found here between candelilla blends and carnauba wax. However, these depended equally on the degree of ethoxylation of the respective AEs. The lipophilic C12E2 showed approximately Fickian diffusion kinetics in both waxes, accompanied by a drastic reduction in orthorhombic crystallinity, especially in candelilla wax, whereas the more hydrophilic C12E6 showed significantly retarded diffusion kinetics associated with a smaller effect on orthorhombic crystallinity. The individual diffusion kinetics of the investigated adjuvants sometimes showed drastic deviations from the Fickian diffusion model, indicating a self-accelerating effect. Hence, adjuvant diffusion kinetics were accompanied by a distinct initial lag phase, indicating a critical concentration in the wax necessary for effective penetration, leading to sigmoidal rather than to exponential diffusion kinetics.
The last chapter dealt with the adjuvant-affected diffusion of the AI modelling CNP in candelilla and carnauba wax. Using ATR-FTIR, diffusion kinetics were recorded after adjuvant treatment, all of which were fully explicable based on the Fickian model, with high diffusion coefficients ranging from 10-14 to 10-13 m2 s-1. It is obvious that the diffusion coefficients presented in this work consistently demonstrated plasticization induced accelerated CNP mobilities. Furthermore, CNP equilibrium concentrations were derived, from which partition- and permeability coefficients could be determined. Significant differences between diffusion coefficients (mobility) and partition coefficients (solubility) were found on the one hand depending on the respective waxes, and on the other hand depending on treatment with respective adjuvants. Mobility was higher in candelilla wax than in carnauba wax only after methyl oleate treatment. Treatment with TEHP and AEs resulted in higher CNP mobility in the more polar alkyl ester dominated carnauba wax. The partition coefficients, on the other hand, were significantly lower after methyl oleate treatment in both candelilla and carnauba wax as followed by TEHP or AE treatment. Models were designed for the CNP penetration mode considering the respective adjuvants in both investigated waxes. Co-penetrating water, which is the main ingredient of spray formulations applied in the field, was likely the reason for the drastic differences in adjuvant efficacy. Especially the investigated AEs favored an enormous water uptake in both waxes with increasing ethoxylation level. Surprisingly, this effect was also found for the lipophilic TEHP in both waxes. This led to the assumption that the AI permeability is not exclusively determined by adjuvant induced plasticization, but also depends on a “secondary plasticization”, induced by adjuvant-attracted co-penetrating water, consequently leading to swelling and drastic destabilization of the crystalline wax structure.
The successful establishment of the presented ATR-FTIR method represents a milestone for the study of adjuvant and AI diffusion kinetics in cuticular waxes. In particular, the simultaneously detectable wax modification and, moreover, the determinable water uptake form a perfect basis to establish the ATR-FTIR system as a universal screening tool for wax-adjuvants-AI-water interaction in crop protection science.
“In Other News”: China’s International Media Strategy on Xinjiang — CGTN and New China TV on YouTube
(2023)
In the Western world China stands accused of severe human rights violations regarding its treatment of the Uyghurs and other predominantly Muslim minorities in its northwestern Xinjiang Uyghur Autonomous Region. This is the first article to systematically analyze the response of China’s international state media to these allegations. By studying the YouTube channels of two leading Chinese state media, China Global Television Network (CGTN) and New China TV (operated by Xinhua News Agency), it presents an indepth understanding of how China’s foreign-facing propaganda works in a crucial case. The quantitative content analysis highlights how China reacted to increasing international (mostly United States) pressure regarding its Xinjiang policies by producing higher volumes of videos and putting out new counternarratives. The qualitative analysis that follows provides in-depth treatment of the most important discourses that Chinese media engage in to salvage the nation’s international image, namely those on development, culture, nature, and terrorism. It finds several ways of countering criticism, ranging from presenting a positive image of China, in line with traditional propaganda guidelines and President Xi Jinping’s assignment to state media to “tell the China story well,” to more innovative approaches. Thus the development narrative becomes more personalized, the discourse on culture supports the “heritagization process” to incorporate minority cultures into a harmonized “Chinese civilization,” representations of nature firmly tie Xinjiang into the discourse of “beautiful China,” the “terror narrative” strategically employs shocking footage in an attempt to gain international “discourse power,” etc. The article provides an up-to-date picture of China’s state media strategy on a highly contentious international issue.
Magnetism is a phenomenon ubiquitously found in everyday life. Yet, together with superconductivity and superfluidity, it is among the few macroscopically realized quantum states. Although well-understood on a quasi-classical level, its microscopic description is still far from being solved. The interplay of strong interactions present in magnetic condensed-matter systems and the non-trivial commutator structure governing the underlying spin algebra prevents most conventional approaches in solid-state theory to be applied.
On the other hand, the quantum limit of magnetic systems is fertile land for the development of exotic phases of matter called spin-liquids. In these states, quantum fluctuations inhibit the formation of magnetic long-range order down to the lowest temperatures. From a theoretical point of view, spin-liquids open up the possibility to study their exotic properties, such as fractionalized excitations and emergent gauge fields. However, despite huge theoretical and experimental efforts, no material realizing spin-liquid properties has been unambiguously identified with a three-dimensional crystal structure. The search for such a realization is hindered by the inherent difficulty even for model calculations. As most numerical techniques are not applicable due to the interaction structure and dimensionality of these systems, a methodological gap has to be filled.
In this thesis, to fill this void, we employ the pseudo-fermion functional renormalization group (PFFRG), which provides a scheme to investigate ground state properties of quantum magnetic systems even in three spatial dimensions.
We report the status quo of this established method and extend it by alleviating some of its inherent approximations. To this end, we develop a multi-loop formulation of PFFRG, including hitherto neglected terms in the underlying flow equations consistently, rendering the outcome equivalent to a parquet approximation. As a necessary prerequisite, we also significantly improve the numerical accuracy of our implementation of the method by switching to a formulation respecting the asymptotic behavior of the vertex functions as well as employing state-of-the-art numerical algorithms tailored towards PFFRG. The resulting codebase was made publicly accessible in the open-source code PFFRGSolver.jl.
We subsequently apply the technique to both model systems and real materials. Augmented by a classical analysis of the respective models, we scan the phase diagram of the three-dimensional body-centered cubic lattice up to third-nearest neighbor coupling and the Pyrochlore lattice up to second-nearest neighbor. In both systems, we uncover in addition to the classically ordered phases, an extended parameter regime, where a quantum paramagnetic phase appears, giving rise to the possibility of a quantum spin liquid.
Additionally, we also use the nearest-neighbor antiferromagnet on the Pyrochlore lattice as well as the simple cubic lattice with first- and third-nearest neighbor couplings as a testbed for multi-loop PFFRG, demonstrating, that the inclusion of higher loop orders has quantitative effects in paramagnetic regimes and that the onset of order can be signaled by a lack of loop convergence.
Turning towards material realizations, we investigate the diamond lattice compound MnSc\(_2\)S\(_4\), explaining on grounds of ab initio couplings the emergence of a spiral spin liquid at low temperatures, but above the ordering transition.
In the Pyrochlore compound Lu\(_2\)Mo\(_2\)O\(_5\)N\(_2\), which is known to not magnetically order down to lowest temperatures, we predict a spin liquid state displaying a characteristic gearwheel pattern in the spin structure factor.
We introduce fluorescence-detected pump–probe microscopy by combining a wavelength-tunable ultrafast laser with a confocal scanning fluorescence microscope, enabling access to the femtosecond time scale on the micrometer spatial scale. In addition, we obtain spectral information from Fourier transformation over excitation pulse-pair time delays. We demonstrate this new approach on a model system of a terrylene bisimide (TBI) dye embedded in a PMMA matrix and acquire the linear excitation spectrum as well as time-dependent pump–probe spectra simultaneously. We then push the technique towards single TBI molecules and analyze the statistical distribution of their excitation spectra. Furthermore, we demonstrate the ultrafast transient evolution of several individual molecules, highlighting their different behavior in contrast to the ensemble due to their individual local environment. By correlating the linear and nonlinear spectra, we assess the effect of the molecular environment on the excited-state energy.
In this thesis, we are interested in numerically preserving stationary solutions of balance laws. We start by developing finite volume well-balanced schemes for the system of Euler equations and the system of MHD equations with gravitational source term. Since fluid models and kinetic models are related, this leads us to investigate AP schemes for kinetic equations and their ability to preserve stationary solutions. Kinetic models typically have a stiff term, thus AP schemes are needed to capture good solutions of the model. For such kinetic models, equilibrium solutions are reached after large time. Thus we need a new technique to numerically preserve stationary solutions for AP schemes. We find a criterion for SP schemes for kinetic equations which states, that AP schemes under a particular discretization are also SP. In an attempt to mimic our result for kinetic equations in the context of fluid models, for the isentropic Euler equations we developed an AP scheme in the limit of the Mach number going to zero. Our AP scheme is proven to have a SP property under the condition that the pressure is a function of the density and the latter is obtained as a solution of an elliptic equation. The properties of the schemes we developed and its criteria are validated numerically by various test cases from the literature.
Current therapeutic strategies efficiently improve survival in patients after myocardial infarction (MI). Nevertheless, long-term consequences such as heart failure development, are still one of the leading causes of death worldwide. Inflammation is critically involved in the cardiac healing process after MI and has a dual role, contributing to both tissue healing and tissue damage. In the last decade, a lot of attention was given to targeting inflammation as a potential therapeutic approach in MI, but the poor understanding of inflammatory cell heterogeneity and function is a limit to the development of immune modulatory strategies. The recent development of tools to profile immune cells with high resolution has provided a unique opportunity to better understand immune cell heterogeneity and dynamics in the ischemic heart.
In this thesis, we employed single-cell RNA-sequencing combined with detection of epitopes by sequencing (CITE-seq) to refine our understanding of neutrophils and monocytes/macrophages heterogeneity and dynamic after experimental myocardial infarction.
Neutrophils rapidly invade the infarcted heart shortly after ischemic damage and have previously been proposed to display time-dependent functional heterogeneity. At the single-cell level, we observed dynamic transcriptional heterogeneity in neutrophil populations during the acute post-MI phase and defined previously unknown cardiac neutrophil states. In particular, we identified a locally acquired SiglecFhi neutrophil state that displayed higher ROS production and phagocytic ability compared to newly recruited neutrophils, suggesting the acquisition of specific function in the infarcted heart. These findings highlight the importance of the tissue microenvironment in shaping neutrophil response.
From the macrophage perspective, we characterized MI-associated monocyte-derived macrophage subsets, two with a pro-inflammatory gene signature (MHCIIhiIl1βhi) and three Trem2hi macrophage populations with a lipid associated macrophage (LAM) signature, also expressing pro-fibrotic and tissue repair genes. Combined analysis of blood monocytes and cardiac monocyte/macrophages indicated that the Trem2hi LAM signature is acquired in the infarcted heart.
We furthermore characterized the role of TREM2, a surface protein expressed mainly in macrophages and involved in macrophage survival and function, in the post-MI macrophage response and cardiac repair. Using TREM2 deficient mice, we demonstrate that acquisition of the LAM signature in cardiac macrophages after MI is partially dependent on TREM2. While their cardiac function was not affected, TREM2 deficient mice showed reduced collagen deposition in the heart after MI. Thus, our data in Trem2-deficient mice highlight the role of TREM2 in promoting a macrophage pro-fibrotic phenotype, in line with the pro-fibrotic/tissue repair gene signature of the Trem2hi LAM-signature genes.
Overall, our data provide a high-resolution characterization of neutrophils and macrophage heterogeneity and dynamics in the ischemic heart and can be used as a valuable resource to investigate how these cells modulate the healing processes after MI. Furthermore, our work identified TREM2 as a regulator of macrophage phenotype in the infarcted heart
The universal two-child policy was introduced by the central government of China in 2016 to respond to the country’s deteriorating population problems, but it was soon replaced by a three-child policy in 2021 given that it failed to continuously boost fertility in Chinese society. This dissertation empirically investigates the implementation of universal two-child policy in three Chinese major cities. Based on the data collected through semi-structured interviews with leaders of local family planning agencies, it finds that local officials are primarily devoted to coping with the discontent of the bereaved single-child parents (shidu families), which is an unexpected consequence of the historical one-child policy, rather than working on the tasks regarding birth encouragement. The dissertation suggests understanding the implementation of China’s population policy within the framework of both historical and rational choice institutionalism. The target responsibility system as an effective tool of the central authority drives local agents to fix their attention at tasks that have larger impact on their career. The shifted focus in the implementation of the universal two-child policy is a result of local officials’ emphasis on the task of maintaining social stability. Shidu families are deemed as a salient threat to social order because their discontent with the state support has incurred continuous petitions at both the national and local level, which would severely undermine local officials’ career advancement. However, in the meantime, stability maintenance is found to have become alienated as reflected by the rising costs and that it replaced birth support to be the focus of local family planning agents in the universal two-child policy era. Since the conflict between the shidu group and the state is unlikely to be resolved, the future population policy design and enforcement will continue to be constrained by the shidu problem.
The nervous system relies on an orchestrated assembly of complex cellular entities called neurons, which are specifically committed to information management and transmission. Inter-neuronal communication takes place via synapses, membrane-membrane junctions which ensure efficient signal transfer. Synaptic neurotransmission involves release of presynaptic neurotransmitters and their reception by cognate receptors at postsynaptic terminals. Inhibitory neurotransmission is primarily mediated by the release of neurotransmitters GABA (γ-Aminobutyric acid) and glycine, which are precisely sensed by GABA type-A receptors (GABAARs) and glycine receptors (GlyRs), respectively. GABAAR assembly and maintenance is coordinated by various postsynaptic neuronal factors including the scaffolding protein gephyrin, the neuronal adaptor collybistin (CB) and cell adhesion proteins of the neuroligin (NL) family, specifically NL2 and NL4.
At inhibitory postsynaptic specializations, gephyrin has been hypothesized to form extended structures underneath the plasma membrane, where its interaction with the receptors leads to their stabilization and impedes their lateral movement. Gephyrin mutations have been associated with various brain disorders, including autism, schizophrenia, Alzheimer’s disease, and epilepsy. Furthermore, gephyrin loss is lethal and causes mice to die within the first post-natal day. Gephyrin recruitment from intracellular deposits to postsynaptic membranes primarily relies on the adaptor protein CB.
As a moonlighting protein, CB, a guanine nucleotide exchange factor (GEF), also catalyzes a nucleotide exchange reaction, thereby regenerating the GTP-bound state of the small GTPase Cdc42 from its GDP-bound form. The CB gene undergoes alternative splicing with the majority of CB splice variants featuring an N-terminal SH3 domain followed by tandem Dbl-homology (DH) and pleckstrin-homology (PH) domains. Previous studies demonstrated that the most widely expressed, SH3-domain containing splice variant (CB2SH3+) preferentially adopts a closed conformation, in which the N-terminally located SH3 domain forms intra-molecular interaction with the DH-PH domain tandem. Previous cell-based studies indicated that SH3 domain-encoding CB variants remain untargeted and colocalize with intracellular gephyrin deposits and hence require additional factors which interact with the SH3 domain, thus inducing an open or active conformation. The SH3 domain-deficient CB isoform (CB2SH3-), on the contrary, adopts an open conformation, which possess enhanced postsynaptic gephyrin-clustering and also effectively replenishes the GTP-bound small GTPase-Cdc42 from its GDP-bound state.
Despite the fundamental role of CB as a neuronal adaptor protein maintaining the proper function of inhibitory GABAergic synapses, its interactions with the neuronal scaffolding protein gephyrin and other post synaptic neuronal factors remain poorly understood. Moreover, CB interaction studies with the small GTPase Cdc42 and TC10, a closely related member of Cdc42 subfamily, remains poorly characterized. Most importantly, the roles of the neuronal factors and small GTPases in CB conformational activation have not been elucidated.
This PhD dissertation primarily focuses on delineating the molecular basis of the interactions between CB and postsynaptic neuronal factors. During the course of my PhD dissertation, I engineered a series of CB FRET (Förster Resonance Energy Transfer) sensors to characterize the CB interaction with its binding partners along with outlining their role in CB conformational activation. Through the aid of these CB FRET sensors, I analyzed the gephyrin-CB interaction, which, due to technical limitations remained unaddressed for more than two decades (refer Chapter 2 for more details). Subsequently, I also unraveled the molecular basis of the interactions between CB and the neuronal cell adhesion factor neuroligin 2 (refer chapter 2) and the small GTPases Cdc42 and TC10 (refer chapter 3) and describe how these binding partners induce a conformational activation of CB.
In summary, this PhD dissertation provides strong evidence of a closely knit CB communication network with gephyrin, neuroligin and the small GTPase TC10, wherein CB activation from closed/inactive to open/active states is effectively triggered by these ligands.
As part of the parasympathetic nervous system, muscarinic receptors are involved in the regulation of numerous functions in the human body. However, targeting a specific subtype of muscarinic receptors is challenging due to the high degree of similarity within the binding site of the endogenous neurotransmitter acetylcholine. Therefore, this study focused on the investigation of dualsteric ligands. Such hybrid ligands target the orthosteric acetylcholine binding site and, simultaneously, a distinct allosteric binding site. Since allosteric binding regions show significant structural differences throughout muscarinic receptor subtypes, it was aimed to produce selective ligands by means of combination of two pharmacophores in one molecule. Herein, the thienopyridine derivatives LY2033298 and LY2119620 were chosen as allosteric moieties. Based on literature studies, the investigated allosteric modulators were analyzed in terms of adequate attachment points for the combination with an orthosteric agonist. As orthosteric units, muscarinic superagonist iperoxo, xanomeline, and TMA were applied in this work. Since the distance between orthosteric and allosteric moieties plays a crucial role for dualsteric ligand binding, the linker chain length was also varied. Pharmacological investigations of the synthesized hybrid ligands were perfomed via FRET- and BRET-assay measurements.
Environmental issues have emerged especially since humans burned fossil fuels, which led to air pollution and climate change that harm the environment. These issues’ substantial consequences evoked strong efforts towards assessing the state of our environment.
Various environmental machine learning (ML) tasks aid these efforts. These tasks concern environmental data but are common ML tasks otherwise, i.e., datasets are split (training, validatition, test), hyperparameters are optimized on validation data, and test set metrics measure a model’s generalizability. This work focuses on the following environmental ML tasks: Regarding air pollution, land use regression (LUR) estimates air pollutant concentrations at locations where no measurements are available based on measured locations and each location’s land use (e.g., industry, streets). For LUR, this work uses data from London (modeled) and Zurich (measured). Concerning climate change, a common ML task is model output statistics (MOS), where a climate model’s output for a study area is altered to better fit Earth observations and provide more accurate climate data. This work uses the regional climate model (RCM) REMO and Earth observations from the E-OBS dataset for MOS. Another task regarding climate is grain size distribution interpolation where soil properties at locations without measurements are estimated based on the few measured locations. This can provide climate models with soil information, that is important for hydrology. For this task, data from Lower Franconia is used.
Such environmental ML tasks commonly have a number of properties: (i) geospatiality, i.e., their data refers to locations relative to the Earth’s surface. (ii) The environmental variables to estimate or predict are usually continuous. (iii) Data can be imbalanced due to relatively rare extreme events (e.g., extreme precipitation). (iv) Multiple related potential target variables can be available per location, since measurement devices often contain different sensors. (v) Labels are spatially often only sparsely available since conducting measurements at all locations of interest is usually infeasible. These properties present challenges but also opportunities when designing ML methods for such tasks.
In the past, environmental ML tasks have been tackled with conventional ML methods, such as linear regression or random forests (RFs). However, the field of ML has made tremendous leaps beyond these classic models through deep learning (DL). In DL, models use multiple layers of neurons, producing increasingly higher-level feature representations with growing layer depth. DL has made previously infeasible ML tasks feasible, improved the performance for many tasks in comparison to existing ML models significantly, and eliminated the need for manual feature engineering in some domains due to its ability to learn features from raw data. To harness these advantages for environmental domains it is promising to develop novel DL methods for environmental ML tasks.
This thesis presents methods for dealing with special challenges and exploiting opportunities inherent to environmental ML tasks in conjunction with DL. To this end, the proposed methods explore the following techniques: (i) Convolutions as in convolutional neural networks (CNNs) to exploit reoccurring spatial patterns in geospatial data. (ii) Posing the problems as regression tasks to estimate the continuous variables. (iii) Density-based weighting to improve estimation performance for rare and extreme events. (iv) Multi-task learning to make use of multiple related target variables. (v) Semi–supervised learning to cope with label sparsity. Using these techniques, this thesis considers four research questions: (i) Can air pollution be estimated without manual feature engineering? This is answered positively by the introduction of the CNN-based LUR model MapLUR as well as the off-the-shelf LUR solution OpenLUR. (ii) Can colocated pollution data improve spatial air pollution models? Multi-task learning for LUR is developed for this, showing potential for improvements with colocated data. (iii) Can DL models improve the quality of climate model outputs? The proposed DL climate MOS architecture ConvMOS demonstrates this. Additionally, semi-supervised training of multilayer perceptrons (MLPs) for grain size distribution interpolation is presented, which can provide improved input data. (iv) Can DL models be taught to better estimate climate extremes? To this end, density-based weighting for imbalanced regression (DenseLoss) is proposed and applied to the DL architecture ConvMOS, improving climate extremes estimation. These methods show how especially DL techniques can be developed for environmental ML tasks with their special characteristics in mind. This allows for better models than previously possible with conventional ML, leading to more accurate assessment and better understanding of the state of our environment.
The use of digital media by children and young people offers opportunities for communication, collaboration, and participation. However, to prepare them for the risks and challenges of media usage, promoting digital competencies of students and teachers is an indispensable goal for educational institutions. To meet this requirement, teacher education must be opened to innovative pedagogical concepts for initial teacher education that considers new technologies in a reflective, action-oriented way to promote competencies. Therefore, this work aims to promote the technological pedagogical content knowledge (TPACK) of prospective teachers that enables the purposeful integration of social virtual reality (social VR) into the classroom. Consequently, a pedagogical concept is developed and evaluated in an iterative research and development process following the design- based research approach (DBR) through four consecutive studies. The first study involved an analysis of the requirements of teachers and students for the effective use of social VR in the classroom. The second study examined how prospective teachers perceive teaching and learning activities within two theory-driven scenarios in social VR. The third study investigated the development of Technological Pedagogical Content Knowledge (TPACK) among students in social VR compared to video-based communication. Finally, the fourth study measured the development of TPACK in social VR using epistemic network analysis, finding that social VR can be an effective tool for teacher education, emphasizing the importance of authentic contexts and practical experiences for effective teaching in social VR. In the concluding chapter, appropriate implications for teacher education research and practice are derived from findings. For example, that a deeper understanding of TPACK as metacognitive awareness could enhance teacher education for media integration. It also highlights the need for digital literacy in seminars that address new technologies, emphasizing the importance of considering moral values and sustainability when using VR.
The holy grail of structural biology is to study a protein in situ, and this goal has been fast approaching since the resolution revolution and the achievement of atomic resolution. A cell's interior is not a dilute environment, and proteins have evolved to fold and function as needed in that environment; as such, an investigation of a cellular component should ideally include the full complexity of the cellular environment. Imaging whole cells in three dimensions using electron cryotomography is the best method to accomplish this goal, but it comes with a limitation on sample thickness and produces noisy data unamenable to direct analysis. This thesis establishes a novel workflow to systematically analyse whole-cell electron cryotomography data in three dimensions and to find and identify instances of protein complexes in the data to set up a determination of their structure and identity for success. Mycoplasma pneumoniae is a very small parasitic bacterium with fewer than 700 protein-coding genes, is thin enough and small enough to be imaged in large quantities by electron cryotomography, and can grow directly on the grids used for imaging, making it ideal for exploratory studies in structural proteomics. As part of the workflow, a methodology for training deep-learning-based particle-picking models is established.
As a proof of principle, a dataset of whole-cell Mycoplasma pneumoniae tomograms is used with this workflow to characterize a novel membrane-associated complex observed in the data. Ultimately, 25431 such particles are picked from 353 tomograms and refined to a density map with a resolution of 11 Å. Making good use of orthogonal datasets to filter search space and verify results, structures were predicted for candidate proteins and checked for suitable fit in the density map. In the end, with this approach, nine proteins were found to be part of the complex, which appears to be associated with chaperone activity and interact with translocon machinery.
Visual proteomics refers to the ultimate potential of in situ electron cryotomography: the comprehensive interpretation of tomograms. The workflow presented here is demonstrated to help in reaching that potential.
Small bacterial regulatory RNAs (sRNAs) have been implicated in the regulation of numerous metabolic pathways. In most of these studies, sRNA-dependent regulation of mRNAs or proteins of enzymes in metabolic pathways has been predicted to affect the metabolism of these bacteria. However, only in a very few cases has the role in metabolism been demonstrated. Here, we performed a combined transcriptome and metabolome analysis to define the regulon of the sibling sRNAs NgncR_162 and NgncR_163 (NgncR_162/163) and their impact on the metabolism of Neisseria gonorrhoeae. These sRNAs have been reported to control genes of the citric acid and methylcitric acid cycles by posttranscriptional negative regulation. By transcriptome analysis, we now expand the NgncR_162/163 regulon by several new members and provide evidence that the sibling sRNAs act as both negative and positive regulators of target gene expression. Newly identified NgncR_162/163 targets are mostly involved in transport processes, especially in the uptake of glycine, phenylalanine, and branched-chain amino acids. NgncR_162/163 also play key roles in the control of serine-glycine metabolism and, hence, probably affect biosyntheses of nucleotides, vitamins, and other amino acids via the supply of one-carbon (C\(_1\)) units. Indeed, these roles were confirmed by metabolomics and metabolic flux analysis, which revealed a bipartite metabolic network with glucose degradation for the supply of anabolic pathways and the usage of amino acids via the citric acid cycle for energy metabolism. Thus, by combined deep RNA sequencing (RNA-seq) and metabolomics, we significantly extended the regulon of NgncR_162/163 and demonstrated the role of NgncR_162/163 in the regulation of central metabolic pathways of the gonococcus.
The signal modelling framework JimenaE simulates dynamically Boolean networks. In contrast to SQUAD, there is systematic and not just heuristic calculation of all system states. These specific features are not present in CellNetAnalyzer and BoolNet. JimenaE is an expert extension of Jimena, with new optimized code, network conversion into different formats, rapid convergence both for system state calculation as well as for all three network centralities. It allows higher accuracy in determining network states and allows to dissect networks and identification of network control type and amount for each protein with high accuracy. Biological examples demonstrate this: (i) High plasticity of mesenchymal stromal cells for differentiation into chondrocytes, osteoblasts and adipocytes and differentiation-specific network control focusses on wnt-, TGF-beta and PPAR-gamma signaling. JimenaE allows to study individual proteins, removal or adding interactions (or autocrine loops) and accurately quantifies effects as well as number of system states. (ii) Dynamical modelling of cell–cell interactions of plant Arapidopsis thaliana against Pseudomonas syringae DC3000: We analyze for the first time the pathogen perspective and its interaction with the host. We next provide a detailed analysis on how plant hormonal regulation stimulates specific proteins and who and which protein has which type and amount of network control including a detailed heatmap of the A.thaliana response distinguishing between two states of the immune response. (iii) In an immune response network of dendritic cells confronted with Aspergillus fumigatus, JimenaE calculates now accurately the specific values for centralities and protein-specific network control including chemokine and pattern recognition receptors.
Enterococcus faecalis and Enterococcus faecium are major nosocomial pathogens. Despite their relevance to public health and their role in the development of bacterial antibiotic resistance, relatively little is known about gene regulation in these species. RNA–protein complexes serve crucial functions in all cellular processes associated with gene expression, including post-transcriptional control mediated by small regulatory RNAs (sRNAs). Here, we present a new resource for the study of enterococcal RNA biology, employing the Grad-seq technique to comprehensively predict complexes formed by RNA and proteins in E. faecalis V583 and E. faecium AUS0004. Analysis of the generated global RNA and protein sedimentation profiles led to the identification of RNA–protein complexes and putative novel sRNAs. Validating our data sets, we observe well-established cellular RNA–protein complexes such as the 6S RNA–RNA polymerase complex, suggesting that 6S RNA-mediated global control of transcription is conserved in enterococci. Focusing on the largely uncharacterized RNA-binding protein KhpB, we use the RIP-seq technique to predict that KhpB interacts with sRNAs, tRNAs, and untranslated regions of mRNAs, and might be involved in the processing of specific tRNAs. Collectively, these datasets provide departure points for in-depth studies of the cellular interactome of enterococci that should facilitate functional discovery in these and related Gram-positive species. Our data are available to the community through a user-friendly Grad-seq browser that allows interactive searches of the sedimentation profiles (https://resources.helmholtz-hiri.de/gradseqef/).
The present cumulative dissertation summarizes three clinical studies, which examine
subgroups of patients within the fibromyalgia syndrome (FMS). FMS entails chronic pain and
associated symptoms, and its pathophysiology is incompletely understood (1). Previous studies
show that there is a subgroup of patients with FMS with objective histological pathology of the
small nerve fibers of the peripheral nervous system (PNS). Another subgroup of FMS patients
does not show any signs of pathological changes of the small nerve fibers. The aim of this
dissertation was to compare FMS patients with healthy controls, and these two FMS subgroups
for differences in the central nervous system (CNS) in order to explore possible interactions
between PNS and the CNS. Regarding the CNS, differences of FMS patients with healthy
controls have already been found in studies with small sample sizes, but no subgroups have yet
been identified. Another aim of this thesis was to test whether the subgroups show a different
response to different classes of pain medication. The methods used in this thesis are structural
and functional magnetic resonance imaging (MRI), magnetic resonance diffusion imaging and
magnetic resonance spectroscopy. For the evaluation of clinical symptoms, we used
standardized questionnaires. The subgroups with and without pathologies of the PNS were
determined by skin biopsies of the right thigh and lower leg based on the intraepidermal nerve
fiber density (IENFD) of the small nerve fibers.
1) In the first MRI study, 43 female patients with the diagnosis of FMS and 40 healthy
control subjects, matched in age and body mass index, were examined with different MRI
sequences. Cortical thickness was investigated by structural T1 imaging, white matter integrity
by diffusion tensor imaging and functional connectivity within neuronal networks by functional
resting state MRI. Compared to the controls, FMS patients had a lower cortical volume in
bilateral frontotemporoparietal regions and the left insula, but a higher cortical volume in the
left pericalcarine cortex. Compared to the subgroup without PNS pathology, the subgroup with
PNS pathology had lower cortical volume in both pericalcarine cortices. Diffusion tensor
imaging revealed an increased fractional anisotropy (FA) of FMS patients in corticospinal
pathways such as the corona radiata, but also in regions of the limbic systems such as the fornix
and cingulum. Subgroup comparison again revealed lower mean FA values of the posterior
thalamic radiation and the posterior limb of the left internal capsule in the subgroup with PNS
pathology. In the functional connectivity analysis FMS patients, compared to controls, showed
a hypoconnectivity between the right median frontal gyrus and the posterior cerebellum and
the right crus cerebellum, respectively. In the subgroup comparisons, the subgroup with PNS
pathology showed a hyperconnectivity between both inferior frontal gyri, the right posterior
parietal cortex and the right angular gyrus. In summary, these results show that differences in
brain morphology and functional connectivity exist between FMS patients with and without
PNS pathology. These differences were not associated with symptom duration or severity and,
in some cases, have not yet been described in the context of FMS. The differences in brain
morphology and connectivity between subgroups could also lead to a differential response to
treatment with centrally acting drugs. Further imaging studies with FMS patients should take
into account this heterogeneity of FMS patient cohorts.
2) Following the results from the first MRI study, drug therapies of FMS patients and
their treatment response were compared between PNS subgroups. As there is no licensed drug
for FMS in Europe, the German S3 guideline recommends amitriptyline, duloxetine and
pregabalin for temporary use. In order to examine the current drug use in FMS patients in
Germany on a cross-sectional basis, 156 patients with FMS were systematically interviewed.
The drugs most frequently used to treat pain in FMS were non-steroidal anti-inflammatory
drugs (NSAIDs) (28.9%), metamizole (15.4%) and amitriptyline (8.8%). Pain relief assessed by
patients on a numerical rating scale from 0-10 averaged 2.2 points for NSAIDs, 2.0 for
metamizole and 1.5 for amitriptyline. Drugs that were discontinued for lack of efficacy and not
for side effects were acetaminophen (100%), flupirtine (91.7%), selective serotonin reuptake
inhibitors (81.8%), NSAIDs (83.7%) and weak opioids (74.1%). Patients were divided into
subgroups with and without PNS pathology as determined by skin biopsies. We found no
differences in drug use and effect between the subgroups. Taken together, these results show
that many FMS patients take medication that is not in accordance with the guidelines. The
reduction of symptoms was best achieved with metamizole and NSAIDs. Further longitudinal
studies on medication in FMS are necessary to obtain clearer treatment recommendations.
3) Derived from previous pharmacological and imaging studies (with smaller case
numbers), there is a hypothesis in the FMS literature that hyperreactivity of the insular cortex
may have an impact on FMS. The hyperreactivity seems to be due to an increased concentration
of the excitatory neurotransmitter glutamate in the insular cortex of FMS patients. The
hypothesis is supported by magnetic resonance spectroscopy studies with small number of
cases, as well as results from pharmacological studies with glutamate-inhibiting medication.
Studies from animal models have also shown that an artificially induced increase in glutamate
in the insular cortex can lead to reduced skin innervation. Therefore, the aim of this study was
to compare glutamate and GABA concentrations in the insular cortex of FMS patients with
those of healthy controls using magnetic resonance imaging. There was no significant
difference of both neurotransmitters between the groups. In addition, there was no correlation
between the neurotransmitter concentrations and the severity of clinical symptoms. There
were also no differences in neurotransmitter concentrations between the subgroups with and
without PNS pathology. In conclusion, our study could not show any evidence of a correlation
of glutamate and GABA concentrations with the symptoms of FMS or the pathogenesis of
subgroups with PNS pathologies.