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Neisseria meningitidis (the meningococcus) is one of the major causes of bacterial meningitis, a life-threatening inflammation of the meninges. Traversal of the meningeal blood-cerebrospinal fluid barrier (mBCSFB), which is composed of highly specialized brain endothelial cells (BECs), and subsequent interaction with leptomeningeal cells (LMCs) are critical for disease progression. Due to the human-exclusive tropism of N. meningitidis, research on this complex host-pathogen interaction is mostly limited to in vitro studies. Previous studies have primarily used peripheral or immortalized BECs alone, which do not retain relevant barrier phenotypes in culture. To study meningococcal interaction with the mBCSFB in a physiologically more accurate context, BEC-LMC co-culture models were developed in this project using BEC-like cells derived from induced pluripotent stem cells (iBECs) or hCMEC/D3 cells in combination with LMCs derived from tumor biopsies.
Distinct BEC and LMC layers as well as characteristic expression of cellular markers were observed using transmission electron microscopy (TEM) and immunofluorescence staining. Clear junctional expression of brain endothelial tight and adherens junction proteins was detected in the iBEC layer. LMC co-culture increased iBEC barrier tightness and stability over a period of seven days, as determined by sodium fluorescein (NaF) permeability and transendothelial electrical resistance (TEER). Infection experiments demonstrated comparable meningococcal adhesion and invasion of the BEC layer in all models tested, consistent with previously published data. While only few bacteria crossed the iBEC-LMC barrier initially, transmigration rates increased substantially over 24 hours, despite constant high TEER. After 24 hours of infection, deterioration of the barrier properties was observed including loss of TEER and altered expression of tight and adherens junction components. Reduced mRNA levels of ZO-1, claudin-5, and VE-cadherin were detected in BECs from all models. qPCR and siRNA knockdown data suggested that transcriptional downregulation of these genes was potentially but not solely mediated by Snail1. Immunofluorescence staining showed reduced junctional coverage of occludin, indicating N. meningitidis-induced post-transcriptional modulation of this protein, as previous studies have suggested. Together, these results suggest a potential combination of transcellular and paracellular meningococcal traversal of the mBCSFB, with the more accessible paracellular route becoming available upon barrier disruption after prolonged N. meningitidis infection. Finally, N. meningitidis induced cellular expression of pro-inflammatory cytokines and chemokines such as IL-8 in all mBCSFB models. Overall, the work described in this thesis highlights the usefulness of advanced in vitro models of the mBCSFB that mimic native physiology and exhibit relevant barrier properties to study infection with meningeal pathogens such as N. meningitidis.
Poor or variable oral bioavailability is of major concern regarding safety and efficacy for the treatment of patients with poorly water-soluble drugs (PWSDs). The problem statement of this work involves a pharmaceutical development perspective, the physicochemical basis of the absorption process and physiological / biopharmaceutical aspects. A methodology was developed aiming at closing the gap between drug liberation and dissolution on the one hand and the appearance of drug in the blood on the other. Considering what is out of control from a formulation development perspective, a clear differentiation between bioavailability and bioaccessibility was necessary. Focusing on the absorption process, bioaccessibility of a model compound, a poorly soluble but well permeable weak base, was characterized by means of flux across artificial biomimetic membranes. Such setups can be considered to reasonably mimic relevant oral absorption resistances in vitro in terms of diffusion through an unstirred water layer (UWL) and a lipidic barrier. Mechanistic understanding of the driving force for permeation was gained by differentiating drug species and subsequently linking them to the observed transfer rates using a bioaccessibility concept. The three key species that need to be differentiated are molecularly dissolved drug, drug associated in solution with other components (liquid reservoir) and undissolved drug (solid reservoir). An innovative approach to differentiate molecularly dissolved drug from the liquid reservoir using ultracentrifugation in combination with dynamic light scattering as control is presented. A guidance for rational formulation development of PWSDs is elaborated based on the employed model compound. It is structured into five guiding questions to help drug formulation scientists in selecting drug form, excipients and eventually the formulation principle. Overall, the relevance but also limitations of characterizing bioaccessibility were outlined with respect to practical application e.g. in early drug formulation development.
N\(^6\)-methyladenosine (m\(^6\)A) is an important modified nucleoside in cellular RNA associated with multiple cellular processes and is implicated in diseases. The enzymes associated with the dynamic installation and removal of m\(^6\)A are heavily investigated targets for drug research, which requires detailed knowledge of the recognition modes of m\(^6\)A by proteins. Here, we use atomic mutagenesis of m\(^6\)A to systematically investigate the mechanisms of the two human m\(^6\)A demethylase enzymes FTO and ALKBH5 and the binding modes of YTH reader proteins YTHDF2/DC1/DC2. Atomic mutagenesis refers to atom-specific changes that are introduced by chemical synthesis, such as the replacement of nitrogen by carbon atoms. Synthetic RNA oligonucleotides containing site-specifically incorporated 1-deaza-, 3-deaza-, and 7-deaza-m\(^6\)A nucleosides were prepared by solid-phase synthesis and their RNA binding and demethylation by recombinant proteins were evaluated. We found distinct differences in substrate recognition and transformation and revealed structural preferences for the enzymatic activity. The deaza m\(^6\)A analogues introduced in this work will be useful probes for other proteins in m\(^6\)A research.
Background: That a differentiated treatment of subjects with low and high levels of disabling pain might be necessarily has only been suspected but not sufficiently confirmed so far. Furthermore, the effectiveness of extraoral therapy methods for TMD is still controversial in the literature. The present work could make an important contribution to this.
Objectives: Five systematic reviews with meta-analysis were conducted to investigate the efficacy of extraoral therapies (acupuncture, laser, medication, psychosocial interventions, and physiotherapy) in the treatment of TMD in relation to the degree of chronicity of pain.
Literature sources: With this objective, the databases Pubmed/MEDLINE, EMBASE, Cochrane Library, Livivo, OpenGrey, drks.de, Clinicaltrials.gov. were searched.
Criteria for the selection of suitable studies: Adults suffering from painful TMD and treated with either acupuncture, laser, medication, psychosocial interventions, or physiotherapy. The studies were then examined for evidence in the subjects' characteristics suggesting that they were suffering from chronic TMD in terms of pain dysfunction. These included a high score on the GCPS, resistance to undergone treatments, multilocular pain, depression, and regular use of pain medication. The effectiveness of the five interventions was then differentiated according to the suspected degree of chronicity. Effectiveness was assessed by the following outcomes: patient- related current pain intensity, MMO, pain on palpation, temporomandibular joint sounds, depression, and somatization.
Study evaluation: After the assessment of the studies, the quality assessment (Risk of Bias Tool of the Cochrane Institute) and the extraction of the data were conducted. After that five meta-analyses were carried out for each of the five interventions using the Review Manager of the Cochrane Institute (RevMan 5.3)
Results: Acupuncture and dry needling were statistically significantly more effective in providing short-term pain relief compared to the control group in patients with low disability pain (p=0.04) and (p=0.02), respectively. Acupuncture or dry needling did not show a significant result in the improvement of MMO in the short-term period. Laser therapy is more effective in relieving pain (p<0.0001) and functional outcomes (p=0.03) in the short term compared to placebo for low disability pain. Botulinum toxin (p=0.003) and NSAIDs (p=0.03) showed significantly better short-term improvement in pain intensity for high disability pain. Low disability pain is significantly better treated by psychosocial interventions than by other treatments in terms of long-term pain relief (more than 12 months) (p=0.02). Patients with high disability pain had significantly lower depression scores after psychosocial interventions than after other treatments (p=0.008). Physiotherapy showed a statistically significant short-term analgesic effect in patients with high disability pain compared to placebo (p=0.04). Manual Therapy (MT) showed a statistically significant short-term analgesic effect in high disability pain compared to the control group (p=0.01). Patients with low disability pain showed a statistically significant short-term pain-relieving effect with the single intervention of MT in combination with exercise compared to the control groups (p=0.003). A statistically significant result in the improvement of MMO was found in the short-term period in low disability pain for the single interventions of physiotherapy (p=0.008) and physiotherapy in combination with another treatment compared to other treatments (p=0.03), MT compared to the control group (p=0.03) and physiotherapy compared to splint therapy (p=0.03). Clinical conclusion: Individual interventions of the five extraoral therapies confirm the hypothesis that painful TMDs respond differently to established therapies depending on the degree of chronic pain-related disability and that the prognosis of therapy is significantly influenced by the degree of chronic pain- related disability of the condition, according to the GCPS.
Registration number of the review at PROSPERO: CRD42020202558
Keywords: meta-analysis, systematic review, temporomandibular disorders, extra oral therapy, acupuncture, laser, medication, psychosocial interventions, physiotherapy, low disability, high disability, pain, chronification
π-Conjugated organic polymers have attracted tremendous attention in the last decades, and the interest in these materials is mainly driven by their applicability in next-generation electronic and optoelectronic devices (OLEDs, OFETs, photovoltaics). The partial or complete replacement of carbon atoms by main group elements in conjugated polymers can significantly change the characteristics and applications of these macromolecules. In this work, a class of inorganic polymers comprising a backbone of exclusively boron and nitrogen atoms (poly(iminoborane)s, PIBs) and their monodisperse oligomers is described. In addition, novel inorganic–organic hybrid polymers containing BN units in their polymer backbone were synthesized and characterized.
In chapter 2.1, the development of catalytic B–N coupling routes for the controlled synthesis of macromolecular materials is described. While the reaction of an N-silyl-B-chloro-aminoborane with the electrophilic reagent trimethylsilyl triflate led to effective B–N coupling, the reaction with a silver(I) salt resulted in an intramolecular Cl/Me exchange between the boron and silicon centers.
In chapter 2.2-2.4, the study of oligo- and poly(iminoborane)s is discussed. Monodisperse and cyclolinear oligo(iminoborane)s based on diazaborolidines with up to 7 boron and 8 nitrogen atoms were synthesized by successively extending the B-N main chain. However, the use of benzodiazaborolines only led to limited BN catenation. Furthermore, the redistribution processes resulting from the reaction of longer oligomers with non-stoichiometric amounts of (di)halogenated boranes is reported.
In chapter 2.5-2.6, the synthesis of 1,2,5-azadiborolanes as building blocks for the synthesis of poly(iminoborane)s and inorganic-organic hybrid polymers is described. While the attempt to apply an azadiborolane with sterically demanding groups on the boron-bridging ethylene unit for the construction of PIB was unfeasible, it was successfully incorporated in inorganic-organic hybrid polymers. Photophysical studies indicated π-conjugation along the polymer chain. A first attempt to synthesize PIBs based on azadiborolanes with unsubstituted ethylene units showed promising results.
In chapter 2.7-2.8, a comprehensive study of poly(arylene iminoborane)s, which are BN analogs of poly(arylene vinylene)s is described, and the properties of four polymers as well as twelve monodisperse oligomers were investigated. Photophysical investigations of the monomers, dimers and polymers showed a systematic bathochromic shift of the absorption maximum with increasing chain length and thiophene content. Based on TD-DFT calculations of the model oligomers, the lowest-energy absorption band could be assigned to HOMO to LUMO transitions with π-π* character. The oligo- and poly(arylene iminoborane)s showed only very weak to no emission in solution but they were emissive in the solid state. For four oligomers the aggregation induced emission (AIE) in a THF/water mixture was investigated and DLS studies confirmed the formation of nanoaggregates.
In chapter 2.9, oligo- and polymerizations of sulfur-containing building blocks and subsequent pH-triggered degradation of the products is described. While a sulfilimine-containing oligomer could not be isolated, the sulfone-, sulfoximine-, and sulfoxide-containing molecular oligomers and polymers could be successfully synthesized by B=N or B–O bond formation reactions. The sulfur-containing building blocks were successfully released under acidic or basic conditions, which was confirmed by NMR spectroscopy and mass spectrometry.
Integrative, three-dimensional \(in\) \(silico\) modeling of gas exchange in the human alveolus
(2024)
The lung plays a vital role by exchanging respiratory gases. At the core of this gas exchange is a simple yet crucial passive diffusion process occurring within the alveoli. These balloon-like structures, connected to the peripheral airways, are surrounded by a dense network
of small capillaries. Here, inhaled air comes into close proximity with deoxygenated blood coming from the heart, enabling the exchange of oxygen and carbon dioxide across their concentration gradients.
The efficiency of gas exchange can be measured through indicators such as the diffusion capacity of the lung for oxygen and the reaction half-time. A notable discrepancy exists in humans between physiological estimates of diffusion capacity and the theoretical maximum capacity under optimal structural conditions (morphological estimate). This discrepancy is influenced by a range of interrelated factors, including structural elements like the surface area and thickness of the diffusion barrier, as well as physiological factors such as blood flow dynamics. To unravel the different roles of these factors, we investigated how morphological and physiological properties of the human alveolar micro-environment collectively and individually influence the process of gas exchange. To this end, we developed an integrative in silico approach combining 3D morphological modeling and simulation of blood flow and of oxygen transport.
At the core of our approach lies the simulation software Alvin, serving as an interactive platform for the underlying mathematical model of oxygen transport within the alveolus. Developed by integrating and expanding existing mathematical models, our spatio-temporal model produces results in agreement with experimental data. Alvin allows for real-time parameter adjustments and the execution of multiple simultaneous simulation instances and provides detailed quantitative feedback, offering an immersive exploration of the simulated gas exchange process. The morphological and physiological parameters at play were further investigated with a focus on the microvasculature. By compiling a stereological database from the literature and 3D geometric modeling, we created a sheet-flow model as a realistic representation of the morphology of the human alveolar capillary network. Blood flow was simulated using computational fluid dynamics. Our findings were in line with previous estimations and highlighted the crucial role of viscosity models in predicting pressure drop across the microvasculature. Furthermore, we showcased how our approach can be harnessed to explore structural details, such as the connectivity of the alveolar capillary network with the vascular tree, using blood flow indices. It is important to emphasize that
so far we have relied on different data sources and that experimental validation is needed to move forward.
Integration of our findings into Alvin allowed quantification of the simulated gas exchange process through the diffusion capacity for oxygen and reaction half-time. In addition to evaluating the collective influences of the morphological and physiological properties, our interactive software facilitates the assessment of individual parameter value changes. Exploring blood volume and surface area available for gas exchange revealed linear correlations with diffusion capacity. The blood flow velocity had a positive, non-linear effect on diffusion capacity. The reaction half-time confirmed that under normal conditions, the gas exchange process is not diffusion-limited. Collectively, our alveolar model yielded a diffusion capacity value that fell in the middle of previous physiological and morphological estimates, implying that alveolar-level phenomena contribute to 50% of the diffusion capacity limitations that occur in vivo.
In summary, our integrative in silico approach disentangles various structural and functional influences on alveolar gas exchange, complementing traditional investigations in respiratory
research. We further showcase its utility in teaching and the interpretation of published data. To advance our understanding, future work should prioritize obtaining a cohesive experimental data set and identifying an appropriate viscosity model for blood flow simulations.
We analyze the mathematical models of two classes of physical phenomena. The first class of phenomena we consider is the interaction between one or more insulating rigid bodies and an electrically conducting fluid, inside of which the bodies are contained, as well as the electromagnetic fields trespassing both of the materials. We take into account both the cases of incompressible and compressible fluids. In both cases our main result yields the existence of weak solutions to the associated system of partial differential equations, respectively. The proofs of these results are built upon hybrid discrete-continuous approximation schemes: Parts of the systems are discretized with respect to time in order to deal with the solution-dependent test functions in the induction equation. The remaining parts are treated as continuous equations on the small intervals between consecutive discrete time points, allowing us to employ techniques which do not transfer to the discretized setting. Moreover, the solution-dependent test functions in the momentum equation are handled via the use of classical penalization methods.
The second class of phenomena we consider is the evolution of a magnetoelastic material. Here too, our main result proves the existence of weak solutions to the corresponding system of partial differential equations. Its proof is based on De Giorgi's minimizing movements method, in which the system is discretized in time and, at each discrete time point, a minimization problem is solved, the associated Euler-Lagrange equations of which constitute a suitable approximation of the original equation of motion and magnetic force balance. The construction of such a minimization problem is made possible by the realization that, already on the continuous level, both of these equations can be written in terms of the same energy and dissipation potentials. The functional for the discrete minimization problem can then be constructed on the basis of these potentials.
Introduction.
Mobile health (mHealth) integrates mobile devices into healthcare, enabling remote monitoring, data collection, and personalized interventions. Machine Learning (ML), a subfield of Artificial Intelligence (AI), can use mHealth data to confirm or extend domain knowledge by finding associations within the data, i.e., with the goal of improving healthcare decisions. In this work, two data collection techniques were used for mHealth data fed into ML systems: Mobile Crowdsensing (MCS), which is a collaborative data gathering approach, and Ecological Momentary Assessments (EMA), which capture real-time individual experiences within the individual’s common environments using questionnaires and sensors. We collected EMA and MCS data on tinnitus and COVID-19. About 15 % of the world’s population suffers from tinnitus.
Materials & Methods.
This thesis investigates the challenges of ML systems when using MCS and EMA data. It asks: How can ML confirm or broad domain knowledge? Domain knowledge refers to expertise and understanding in a specific field, gained through experience and education. Are ML systems always superior to simple heuristics and if yes, how can one reach explainable AI (XAI) in the presence of mHealth data? An XAI method enables a human to understand why a model makes certain predictions. Finally, which guidelines can be beneficial for the use of ML within the mHealth domain? In tinnitus research, ML discerns gender, temperature, and season-related variations among patients. In the realm of COVID-19, we collaboratively designed a COVID-19 check app for public education, incorporating EMA data to offer informative feedback on COVID-19-related matters. This thesis uses seven EMA datasets with more than 250,000 assessments. Our analyses revealed a set of challenges: App user over-representation, time gaps, identity ambiguity, and operating system specific rounding errors, among others. Our systematic review of 450 medical studies assessed prior utilization of XAI methods.
Results.
ML models predict gender and tinnitus perception, validating gender-linked tinnitus disparities. Using season and temperature to predict tinnitus shows the association of these variables with tinnitus. Multiple assessments of one app user can constitute a group. Neglecting these groups in data sets leads to model overfitting. In select instances, heuristics outperform ML models, highlighting the need for domain expert consultation to unveil hidden groups or find simple heuristics.
Conclusion.
This thesis suggests guidelines for mHealth related data analyses and improves estimates for ML performance. Close communication with medical domain experts to identify latent user subsets and incremental benefits of ML is essential.
The demand for LIB with enhanced energy densities leads to increased utilization of the space within the confinements of the battery housing or to the use of electrode material with increased intrinsic specific energy densities. Both requirements result in more stress on the battery electrodes and separator during cycling or aging. However, the effect of mechanical strain on the cell’s electrochemistry and thus the performance of batteries is rather unexplored compared to the impact of current or temperature, for example. The objective of this thesis was to give a better understanding of the electrochemical and mechanical interplay in current- and next-generation lithium based battery cells. Therefore, the thesis was structured into the investigations on SoA and next-generation LIBs. For SoA LIBs, the investigations of the interplay started at laboratory scale. Here, the expansion of various electrodes and also the impact of mechanical pressure and its distribution on the performance of the cells were
studied. The investigations at laboratory scale was followed by an examination of the electrochemical and mechanical interactions on large format commercial LIBs which are used in BEVs. Accordingly, the effect of bracing and its effect on the performance was studied in an aging and post-mortem study. To gain a deeper understanding of the mechanical changes in LIBs, an ultrasonic study was performed for pouch cells. Here, the mechanical changes were further investigated in dependence of SoC and SoH. The effects of the mechanical stress on the performance for next-generation batteries were studied at laboratory scale. In the beginning, the expansion of next-generation anode materials such as silicon and lithium was compared with today’s anode materials. Furthermore, the effect of mechanical pressure and electrolyte on the irreversible dilation and performance was investigated for lithium metal cells. Overall, it was shown that pressure has a significant effect on the performance of today’s and also future LIBs. The interplay of the electrochemical and mechanical effects inside a LIB has a considerable impact on the lifetime, capacity fading and impedance increase of the batteries.
Development Of A Human iPSC-Derived Cortical Neuron Model Of Adaptor- Protein-Complex-4-Deficiency
(2024)
Adaptor-protein-4-deficiency (AP-4-deficiency) is an autosomal-recessive childhood- onset form of complicated hereditary spastic paraplegia (HSP) caused by bi-allelic loss- of-function mutations in one of the four subunits of the AP-4-complex. These four conditions are named SPG47 (AP4B1, OMIM #614066), SPG50 (AP4M1, OMIM #612936), SPG51 (AP4E1, OMIM #613744) and SPG52 (AP4S1, OMIM #614067), respectively and all present with global developmental delay, progressive spasticity and seizures. Imaging features include a thinning of the corpus callosum, ventriculomegaly and white matter changes. AP-4 is a highly conserved heterotetrameric complex, which is responsible for polarized sorting of transmembrane cargo including the autophagy- related protein 9 A (ATG9A). Loss of any of the four subunits leads to an instable complex and defective sorting of AP-4-cargo. ATG9A is implicated in autophagosome formation and neurite outgrowth. It is missorted in AP-4-deficient cells and CNS-specific knockout of Atg9a in mice results in a phenotype reminiscent of AP-4-deficiency. However, the AP-4-related cellular phenotypes including ATG9A missorting have not been investigated in human neurons.
Thus, the aim of this study is to provide the first human induced pluripotent stem cell- derived (iPSC) cortical neuron model of AP-4-deficiency to explore AP-4-related phenotypes in preparation for a high-content screening. Under the hypothesis that AP-4- deficiency leads to ATG9A missorting, elevated ATG9A levels, impaired autophagy and neurite outgrowth in human iPSC-derived cortical neurons, in vitro biochemical and imaging assays including automated high-content imaging and analysis were applied. First, these phenotypes were investigated in fibroblasts from three patients with compound heterozygous mutations in the AP4B1 gene and their sex-matched parental controls. The same cell lines were used to generate iPSCs and differentiate them into human excitatory cortical neurons.
This work shows that ATG9A is accumulating in the trans-Golgi-network in AP-4- deficient human fibroblasts and that ATG9A levels are increased compared to parental controls and wild type cells suggesting a compensatory mechanism. Protein levels of the AP4E1-subunit were used as a surrogate marker for the AP-4-complex and were decreased in AP-4-deficient fibroblasts with co-immunoprecipitation confirming the instability of the complex. Lentiviral re-expression of the AP4B1-subunit rescues this corroborating the fact that a stable AP-4-complex is needed for ATG9A trafficking. Surprisingly, autophagic flux was present in AP-4-deficient fibroblasts under nutrient- rich and starvation conditions. These phenotypic markers were evaluated in iPSC-derived cortical neurons and here, a robust accumulation of ATG9A in the juxtanuclear area was seen together with elevated ATG9A protein levels. Strikingly, assessment of autophagy markers under nutrient-rich conditions showed alterations in AP-4-deficient iPSC- derived cortical neurons indicating dysfunctional autophagosome formation. These findings point towards a neuron-specific impairment of autophagy and need further investigation. Adding to the range of AP-4-related phenotypes, neurite outgrowth and branching are impaired in AP-4-deficient iPSC-derived cortical neurons as early as 24h after plating and together with recent studies point towards a distinct role of ATG9A in neurodevelopment independent of autophagy.
Together, this work provides the first patient-derived neuron model of AP-4-deficiency and shows that ATG9A is sorted in an AP-4-dependent manner. It establishes ATG9A- related phenotypes and impaired neurite outgrowth as robust markers for a high-content screening. This disease model holds the promise of providing a platform to further study AP-4-deficiency and to search for novel therapeutic targets.