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The ongoing and evolving usage of networks presents two critical challenges for current and future networks that require attention: (1) the task of effectively managing the vast and continually increasing data traffic and (2) the need to address the substantial number of end devices resulting from the rapid adoption of the Internet of Things. Besides these challenges, there is a mandatory need for energy consumption reduction, a more efficient resource usage, and streamlined processes without losing service quality. We comprehensively address these efforts, tackling the monitoring and quality assessment of streaming applications, a leading contributor to the total Internet traffic, as well as conducting an exhaustive analysis of the network performance within a Long Range Wide Area Network (LoRaWAN), one of the rapidly emerging LPWAN solutions.
The ongoing and evolving usage of networks presents two critical challenges for current and future networks that require attention: (1) the task of effectively managing the vast and continually increasing data traffic and (2) the need to address the substantial number of end devices resulting from the rapid adoption of the Internet of Things. Besides these challenges, there is a mandatory need for energy consumption reduction, a more efficient resource usage, and streamlined processes without losing service quality. We comprehensively address these efforts, tackling the monitoring and quality assessment of streaming applications, a leading contributor to the total Internet traffic, as well as conducting an exhaustive analysis of the network performance within a Long Range Wide Area Network (LoRaWAN), one of the rapidly emerging LPWAN solutions.
Western societies are steadily becoming older undergoing a clear trend of delayed parenthood. Children of older fathers have an undeniably higher risk for certain neurodevelopmental disorders and other medical conditions. Changes in the epigenetic landscape and especially in DNA methylation patterns are likely to account for a portion of this inherited disease susceptibility. DNA methylation changes during the ageing process are a well-known epigenetic feature. These so-called age-DMRs exist in developmentally important genes in the methylome of several mammalian species. However, there is only a minor overlap between the age-DMR datasets of different studies. We therefore replicated age-DMRs (which were obtained from a genome wide technique) by applying a different technical approach in a larger sample number. Here, this study confirmed 10 age-DMRs in the human and 4 in the bovine sperm epigenome from a preliminary candidate list based on RRBS. For this purpose, we used bisulphite Pyrosequencing in 94 human and 36 bovine sperm samples. These Pyrosequencing results confirm RRBS as an effective and reliable method to screen for age-DMRs in the vertebrate genome. To decipher whether paternal age effects are an evolutionary conserved feature of mammalian development, we compared methylation patterns between human and bovine sperm in orthologous regulatory regions. We discovered that the level of methylation and the age effect are both species-specific and speculate that these methylation marks reflect the lineage-specific development of each species to hit evolutionary requirements and adaptation processes. Different methylation levels between species in developmentally important genes also imply a differing mutational burden, representing a potential driver for point mutations and consequently deviations in the underlying DNA sequence of different species. Using the example of different haplotypes, this study showed the great effect of single base variations on the methylation of adjacent CpGs. Nonetheless, this study could not provide further evidence or a mechanism for the transfer of epigenetic marks to future generations. Therefore, further research in tissues from the progeny of old and young fathers is required to determine if the observed methylation changes are transmitted to the next generation and if they are associated with altered transcriptional activity of the respective genes. This could provide a direct link between the methylome of sperm from elderly fathers and the development potential of the next generation.
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
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.