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[Background] Pathogenic variants in several genes have been linked to genetic forms of isolated or combined dystonia. The phenotypic and genetic spectrum and the frequency of pathogenic variants in these genes have not yet been fully elucidated, neither in patients with dystonia nor with other, sometimes co-occurring movement disorders such as Parkinson's disease (PD)., [Objectives] To screen >2000 patients with dystonia or PD for rare variants in known dystonia-causing genes., [Methods] We screened 1207 dystonia patients from Germany (DysTract consortium), Spain, and South Korea, and 1036 PD patients from Germany for pathogenic variants using a next-generation sequencing gene panel. The impact on DNA methylation of KMT2B variants was evaluated by analyzing the gene's characteristic episignature., [Results] We identified 171 carriers (109 with dystonia [9.0%]; 62 with PD [6.0%]) of 131 rare variants (minor allele frequency <0.005). A total of 52 patients (48 dystonia [4.0%]; four PD [0.4%, all with GCH1 variants]) carried 33 different (likely) pathogenic variants, of which 17 were not previously reported. Pathogenic biallelic variants in PRKRA were not found. Episignature analysis of 48 KMT2B variants revealed that only two of these should be considered (likely) pathogenic., [Conclusion] This study confirms pathogenic variants in GCH1, GNAL, KMT2B, SGCE, THAP1, and TOR1A as relevant causes in dystonia and expands the mutational spectrum. Of note, likely pathogenic variants only in GCH1 were also found among PD patients. For DYT-KMT2B, the recently described episignature served as a reliable readout to determine the functional effect of newly identified variants.

Coronavirus disease 2019 (COVID-19) can damage cerebral small vessels and cause neurological symptoms. Here we describe structural changes in cerebral small vessels of patients with COVID-19 and elucidate potential mechanisms underlying the vascular pathology. In brains of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2)-infected individuals and animal models, we found an increased number of empty basement membrane tubes, so-called string vessels representing remnants of lost capillaries. We obtained evidence that brain endothelial cells are infected and that the main protease of SARS-CoV-2 (M-pro) cleaves NEMO, the essential modulator of nuclear factor-kappa B. By ablating NEMO, M-pro induces the death of human brain endothelial cells and the occurrence of string vessels in mice. Deletion of receptor-interacting protein kinase (RIPK) 3, a mediator of regulated cell death, blocks the vessel rarefaction and disruption of the blood-brain barrier due to NEMO ablation. Importantly, a pharmacological inhibitor of RIPK signaling prevented the M-pro-induced microvascular pathology. Our data suggest RIPK as a potential therapeutic target to treat the neuropathology of COVID-19. A novel study led by scientists in Lubeck, Germany, shows that SARS-CoV-2-infected brain endothelial cells undergo cell death due to the cleavage of NEMO by the viral protease M-pro, potentially causing cerebral COVID-19 and 'long COVID' symptoms.

Coronavirus disease 2019 (COVID-19) can damage cerebral small vessels and cause neurological symptoms. Here we describe structural changes in cerebral small vessels of patients with COVID-19 and elucidate potential mechanisms underlying the vascular pathology. In brains of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2)-infected individuals and animal models, we found an increased number of empty basement membrane tubes, so-called string vessels representing remnants of lost capillaries. We obtained evidence that brain endothelial cells are infected and that the main protease of SARS-CoV-2 (M-pro) cleaves NEMO, the essential modulator of nuclear factor-kappa B. By ablating NEMO, M-pro induces the death of human brain endothelial cells and the occurrence of string vessels in mice. Deletion of receptor-interacting protein kinase (RIPK) 3, a mediator of regulated cell death, blocks the vessel rarefaction and disruption of the blood-brain barrier due to NEMO ablation. Importantly, a pharmacological inhibitor of RIPK signaling prevented the M-pro-induced microvascular pathology. Our data suggest RIPK as a potential therapeutic target to treat the neuropathology of COVID-19. A novel study led by scientists in Lubeck, Germany, shows that SARS-CoV-2-infected brain endothelial cells undergo cell death due to the cleavage of NEMO by the viral protease M-pro, potentially causing cerebral COVID-19 and 'long COVID' symptoms.

The increasing use of silver nanoparticles (AgNPs) in various products leads to their presence in the aquatic environment. The dissolution of AgNPs is an important property that has a direct impact on human health and the natural environment. Understanding the dissolution behaviour of nanoparticles in liquid suspensions is essential for predicting their potential toxic effect in organisms, ranging from viruses and bacteria to humans. Moreover, the dissolution rate of nanoparticles can explain some of their disinfecting properties, which are important for sanitation. The objective of this study is to determine the dissolution behaviour of AgNPs in pure water and to improve our understanding of its most fundamental principles. Dissolution constants of AgNPs found in literature span over a wide range, indicating that improvement of the measuring method is needed. AgNPs in this study were produced in a principally impurity-free way, from the gas phase, after which they were transferred into liquid solutions. The purity of the particles produced in this study is in principle higher compared to those used until now, which allows for higher precision in determining the dissolution constant. Measuring the silver ion concentration in the resulting liquid solutions (i.e., after introducing the AgNPs in the solution) with an ICP-MS at specific time intervals gave direct information on the dissolution kinetics. The experiments were repeated with particles having diameters from 7 to 12 nm and, as expected, dissolution kinetics were found to be highly dependent on particle size. The determined dissolution constants are in the same order of magnitude as the values reported in literature. To further improve the reliability of the measurements, the experiment needs to be repeated using different methods for transferring the particles into the liquid, given that the used bubbling method showed deficiencies., Civil Engineering | Environmental Engineering

The increasing use of silver nanoparticles (AgNPs) in various products leads to their presence in the aquatic environment. The dissolution of AgNPs is an important property that has a direct impact on human health and the natural environment. Understanding the dissolution behaviour of nanoparticles in liquid suspensions is essential for predicting their potential toxic effect in organisms, ranging from viruses and bacteria to humans. Moreover, the dissolution rate of nanoparticles can explain some of their disinfecting properties, which are important for sanitation. The objective of this study is to determine the dissolution behaviour of AgNPs in pure water and to improve our understanding of its most fundamental principles. Dissolution constants of AgNPs found in literature span over a wide range, indicating that improvement of the measuring method is needed. AgNPs in this study were produced in a principally impurity-free way, from the gas phase, after which they were transferred into liquid solutions. The purity of the particles produced in this study is in principle higher compared to those used until now, which allows for higher precision in determining the dissolution constant. Measuring the silver ion concentration in the resulting liquid solutions (i.e., after introducing the AgNPs in the solution) with an ICP-MS at specific time intervals gave direct information on the dissolution kinetics. The experiments were repeated with particles having diameters from 7 to 12 nm and, as expected, dissolution kinetics were found to be highly dependent on particle size. The determined dissolution constants are in the same order of magnitude as the values reported in literature. To further improve the reliability of the measurements, the experiment needs to be repeated using different methods for transferring the particles into the liquid, given that the used bubbling method showed deficiencies., Civil Engineering | Environmental Engineering

In the present research, the activation parameterization method introduced by Nenes and Seinfeld (2003) was compared and evaluated to a remote sensing-based method by Rusli, Donovan & Russchenberg (2017) for determining the cloud drop number concentration. Both methods have fundamentally different approaches for indirectly determining the cloud droplet number concentration. The parameterization method is based on the Köhler Theory, in which the activation process of particles contained in a rising parcel is modelled for predicting the number concentrations of cloud droplets. The remote sensing method, on the other hand, applies theories about particle-light interactions. Since the remote sensing method determines the cloud droplet concentrations in a more direct manner than the parameterization method, it is regarded here as the reference. An agreement was found between the two models, with a relative error of cloud droplet number concentrations between 41.1% and 78.0%, which lead to errors of the cloud’s scattering intensity in the range of 13% and 26%. Despite some discrepancies between the obtained droplet concentrations, the parameterization model shows similar trends to the remote sensing observations. It was found that the updraft velocity that is needed as input variable for the parameterization model has the largest influence on the model’s prediction of droplets concentrations, and that it is likely to be an important cause for the seen discrepancies. Furthermore, the present research shows how assumptions were made on the size distribution input variable used in the parameterization model, which were not available from observations., Additional Master Thesis

In the present research, the activation parameterization method introduced by Nenes and Seinfeld (2003) was compared and evaluated to a remote sensing-based method by Rusli, Donovan & Russchenberg (2017) for determining the cloud drop number concentration. Both methods have fundamentally different approaches for indirectly determining the cloud droplet number concentration. The parameterization method is based on the Köhler Theory, in which the activation process of particles contained in a rising parcel is modelled for predicting the number concentrations of cloud droplets. The remote sensing method, on the other hand, applies theories about particle-light interactions. Since the remote sensing method determines the cloud droplet concentrations in a more direct manner than the parameterization method, it is regarded here as the reference. An agreement was found between the two models, with a relative error of cloud droplet number concentrations between 41.1% and 78.0%, which lead to errors of the cloud’s scattering intensity in the range of 13% and 26%. Despite some discrepancies between the obtained droplet concentrations, the parameterization model shows similar trends to the remote sensing observations. It was found that the updraft velocity that is needed as input variable for the parameterization model has the largest influence on the model’s prediction of droplets concentrations, and that it is likely to be an important cause for the seen discrepancies. Furthermore, the present research shows how assumptions were made on the size distribution input variable used in the parameterization model, which were not available from observations., Additional Master Thesis