Refine
Year of publication
- 2022 (135) (remove)
Document Type
- Doctoral Thesis (135) (remove)
Language
- English (135) (remove)
Has Fulltext
- yes (135)
Is part of the Bibliography
- no (135) (remove)
Keywords
- CBM (2)
- HADES (2)
- Saccharomyces cerevisiae (2)
- ACKR (1)
- ADHD (1)
- ADHS (1)
- Accelerator (1)
- Actions in mathematical learning (1)
- Activation experiment (1)
- Acute Promyelocytic Leukemia (1)
Institute
- Biochemie, Chemie und Pharmazie (30)
- Biowissenschaften (26)
- Physik (20)
- Medizin (17)
- Informatik und Mathematik (15)
- Geowissenschaften / Geographie (8)
- Neuere Philologien (4)
- Biochemie und Chemie (3)
- Mathematik (2)
- Psychologie und Sportwissenschaften (2)
Atmospheric particles play an important role in the radiative balance of the Earth, as well as they affect human health and air quality. Hence, the chemical characterization constitutes a crucial task to determinate their properties, sources and fate. Particularly, the analysis of nanoparticles (d<100 nm) represents an analytical challenge, since these particles are abundant in number but have very little mass.
This accumulative thesis focuses on the chemical characterization of nanoparticles, performed in both laboratory and field studies. Here, I present four manuscripts, two of which are my main project as a lead author.
The first manuscript (Caudillo et al., 2021) focuses on the gas and the particle phase originated from biogenic precursor gases (α-pinene and isoprene). The experiments were performed in the CLOUD chamber at CERN to simulate pure biogenic new particle formation. Both gas and particle phases are measured with a nitrate CI-APi-TOF mass spectrometer, while the TD-DMA is coupled to it for particle-phase measurements, this setup allows a direct comparison as both measurements use the identical chemical ionization and detector. This study demonstrates the suitability of the TD-DMA for measuring newly formed nanoparticles and it confirms that isoprene suppresses new particle formation but contributes to the growth of newly formed particles.
The second manuscript (Caudillo et al., 2022) presents an intercomparison of four different techniques (including the TD-DMA) for measuring the chemical composition of SOA nanoparticles. The measurements were conducted in the CLOUD chamber. The intercomparison was done by contrasting the observed chemical composition, the calculated volatility, and the thermal desorption behavior (for the thermal desorption techniques). The methods generally agreed on the most important compounds that are found in the nanoparticles. However, they did see different parts of the organic spectrum. Potential explanations for these differences are suggested.
The third manuscript (Ungeheuer al., 2022) presents both laboratory and ambient measurements to investigate the ability of lubricant oil to form new particles. These new particles are an important source of ultrafine particles in the areas nearby large airports. The ambient measurements were performed downwind of Frankfurt International Airport, and it was found that the fraction of lubricant oil is largest in the smallest particles. In the laboratory, the main finding was that evaporated lubricant oil nucleates and forms new particles rapidly. The results suggest that nucleation of lubricant oil and subsequent particle growth can occur in the cooling exhaust plumes of aircraft-turbofans.
The fourth manuscript (Wang et al., 2022) is a new particle formation study in the CLOUD chamber at CERN. This study shows that nitric acid, sulfuric acid, and ammonia interact synergistically and rapidly form particles under upper free tropospheric conditions. These particles can grow by condensation (driven by the availability of ammonia) up to CCN sizes and INP particles. The ability of these particles to act as a CCN and INP was also investigated and it was found to be as efficient as for desert dust. This mechanism constitutes an important finding and it can account for previous observations of high concentrations of ammonia and ammonium nitrate over the Asia monsoon region.
Patients harboring mutations in the gene DEPDC5 often display variations of neurological diseases including epilepsy, autism spectrum disorders (ASD) and other neuro-architectural alterations. DEPDC5 protein has been identified as an amino acid sensor responsible for negatively regulating the mechanistic target of rapamycin (mTOR), a central regulator in cell growth and cell homeostasis. Often, mutations of the DEPDC5 protein result in mTOR hyperactivity leading to abnormal neuronal phenotypes and the generation of excitatory/inhibitory imbalances in animal models. Complete knockout (KO) of DEPDC5 results in death shortly after birth, while inhibition of mTOR activity recovers postnatal death (Marsan et al. 2016). However, heterozygous DEPDC5-KOs in animals have been variable in their disease phenotypes during adulthood indicating developmental differences between subspecies and early development mechanisms which could be impactful on the outcome of the diseases.
To understand the mechanisms underlying DEPDC5 mutations during early development, a novel primary human neural progenitor cell line extracted from fetal tissue was characterized during proliferation and differentiation. CRISPR-Cas9 induced mutations of the DEPDC5 gene resulted in hyperphosphorylation of mTOR signaling processes and rapid expansion of the neuronal population during differentiation. Analysis of transcriptome data identified deregulation amongst p53 signaling, ribosome biogenesis, nucleotide and lipid synthesis as well as protein degradation pathways due to loss of DEPDC5. Disease gene datasets identified a correlation between Tuberous Sclerosis mutations as being more closely associated with DEPDC5 mutations while also finding overlap with some ASD and epilepsy genes. By using the mTOR inhibitor rapamycin, a substantial amount of the deregulated gene network was recovered while also reversing rapid neuronal differentiation caused by loss of DEPDC5. Though we saw increased dendritic arborization and subsequent decreases in dendrite lengths and soma sizes, rapamycin failed to recover these effects suggesting mTOR independent processes produced by DEPDC5-KO. This study provides new insights on the relationship between mutations in DEPDC5 and the functional, genomic and deregulatory networks it intertwines in humans and highlights that the DEPDC5 associated pathomechanisms are not fully related to mTOR hyperactivation, but include independent processes. This also sheds light on the question why rapamycin treatment only partially restores DEPDC5 related phenotypes and gives insight on treatments for DEPDC5 patients.
Redox homeostasis must be kept in balance for an intact redox signaling, which is necessary to control neuronal pathways such as growth cone pathfinding, synaptic plasticity and transmission (Oswald, Garnham, Sweeney, & Landgraf, 2018).
Nucleoredoxin (NXN) is an oxidoreductase and thioredoxin-like protein holding two conserved cysteine residues in its structure (Funato & Miki, 2007), which are essential for its redox-regulating functionality. The function of NXN in neurons is still less well studied. But the expression of NXN in neurons, which was confirmed through analyzing adult NXN-LacZ reporter mice, suggested a dominant functional role in neuronal pathways. Initial experiments revealed calcium-calmodulin-dependent kinase 2 a (Camk2a) as a potential interaction partner through a Yeast-2-Hybrid screen (not shown) which is the major protein to induce synaptic plasticity during neuronal activity. Therefore, neuronal expression of NXN and the potential interaction with Camk2a prompted us to investigate deeper into the neuronal pathway. The goal of this work was to confirm the interaction of Camk2a and NXN with further experiments and to characterize behavior of mice carrying a neuronal NXN deletion. To achieve a pan-neuronal depletion of NXN expression in our mouse model, we used the Cre/loxP system with a NestinCre driver. We did not achieve the expected complete deletion of NXN due to unknown compensatory mechanisms. Nevertheless, the partial deletion of NXN in our transgenic mouse model prevented embryonic lethality as occurring in complete NXN knockout mice (Funato et al., 2010). The interaction of Camk2a and NXN was confirmed through proximity ligation assay (PLA) and immunofluorescence staining of primary cortical neurons.
Investigations of the functional interaction revealed a lower redox-sensitivity of Camk2a activity in NXN-deficient brain samples. Additionally, the respiratory activity was significantly reduced in mitochondria of NXN deficient mouse brain pointing to possible dysfunctional mitochondria which is also observed in various neurodegenerative diseases, e.g.: Alzheimer, Parkinson, and Huntington disease (Norat et al., 2020). Unexpectedly, behavioral studies revealed only a subtle effect of the pan-neuronal NXN-deficiency. Significant differences between genotypes were found at the reduction of exploratory behavior and a reduced motivation for the voluntary wheel running in NesNXN-/- mice, which is normally seen as a joyful and rewarding activity. The observed behavior of NesNXN-/- mice potentially results from interaction mechanisms of NXN with Camk2a, as well as decreased oxidation of
Camk2a and further unidentified target proteins of NXN.
Conclusively, function of NXN was revealed as a non-essential redox modulator of Camk2a in neurons. The behavioral phenotype of NesNXN-/- mice is probably compensated through unknown mechanisms. Redox signaling of Camk2a in neurons is regulated through various components such as TXN or GSH, which can backup each other (Branco et al., 2017; Ren et al., 2017). NXN is an additional but not essential regulator.
Post-translational modifications (PTMs) of cell fate regulating proteins determine their stability, localization and function and control the activation of cell protective signaling pathways. Particularly in aberrantly dividing cancer cells the surveillance of cell cycle progression is essential to control tumorigenicity. In a variety of carcinomas, lymphomas and leukemias, the tumor-suppressive functions of the apoptosis- and senescence-regulating promyelocytic leukemia protein (PML) is controlled by numerous PTMs. PML poly-ubiquitylation and polySUMOylation at several lysine (K) residues induce PML degradation that is correlated to a progressive and invasive cancer phenotype. Besides several known E3 ubiquitin protein ligases that are involved in PML degradation, less is known about PML-specific deubiquitylases (DUBs), the respective DUB-controlled ubiquitin conjugation sites and the functional consequences of PML (de)ubiquitylation. Here, we show that the pro-tumorigenic DUB USP22 critically regulates PML protein stability by modifying PML residue K394 in advanced colon carcinoma cells in vitro and that this modification also impacts the homeostasis and function of the leukemia-associated mutant variant PML-RARα. We found that ablation of USP22 decreases PML mono-ubiquitylation and correlates with a prolonged protein half-live in colon carcinoma and acute promyelocytic leukemia (APL) cell lines. Additionally, silencing of USP22 enhances interferon and interferon-stimulated gene (ISG) expression in APL cells in vitro, which together with prolonged PML-RARα stability increases the APL cell sensitivity towards differentiation treatment. In accordance with the novel roles of USP22 as suppressor of the interferon response in human intestinal epithelial cells (hIECs), our findings imply USP22-dependent surveillance of PML-RARα stability and interferon signaling in human leukemia cells, revealing USP22 as central regulator of leukemia pathogenesis.
In this thesis, the flow coefficients vn of the orders n = 1 − 6 are studied for protons and light nuclei in Au+Au collisions at Ebeam = 1.23 AGeV, equivalent to a center-of-mass energy in the nucleon-nucleon system of √sNN = 2.4 GeV. The detailed multi-differential measurement is performed with the HADES experiment at SIS18/GSI. HADES, with its large acceptance, covering almost full azimuth angle, combined with its high mass-resolution and good particle-identification capability, is well equipped to study the azimuthal flow pattern not only for protons, deuterons, and tritons but also for charged pions, kaons, the φ-mesons, electrons/positrons, as well as light nuclei like helions and alphas. The high statistics of more than seven billion Au-Au collisions recorded in April/May 2012 with HADES enables for the first time the measurement of higher order flow coefficients up to the 6th harmonic. Since the Fourier coefficient of 7th and 8th order are beyond the statistical significance only an upper bound is given. The Au+Au collision system is the largest reaction system with the highest particle multiplicities, which was measured so far with HADES. A dedicated correction method for the flow measurement had to be developed to cope with the reconstruction in-efficiencies due to occupancies of the detector system. The systematical bias of the flow measurement is studied and several sources of uncertainties identified, which mainly arise from the quality selection criteria applied to the analyzed tracks, the correction procedure for reconstruction inefficiencies, the procedures for particle identification (PID) and the effects of an azimuthally non-uniform detector acceptance. The systematic point-to-point uncertainties are determined separately for each particle type (proton, deuteron and triton), the order of the flow harmonics vn, and the centrality class. Further, the validity of the results is inspected in the range of their evaluated systematic uncertainties with several consistency checks. In order to enable meaningful comparisons between experimental observations and predictions of theoretical models, the classification of events should be well defined and in sufficiently narrow intervals of impact parameter. Part of this work included the implementation of the procedure to determine the centrality and orientation of the reaction.
In the conclusion the experimental results are discussed, including various scaling properties of the flow harmonics. It is found that the ratio v4/v2 for protons and light nuclei (deuterons and tritons) at midrapidity for all centrality classes approaches values close to 0.5 at high transverse momenta, which was suggested to be indicative for an ideal hydrodynamic behaviour. A remarkable scaling is observed in the pt dependence of v2 (v4) at mid-rapidity of the three hydrogen isotopes, when dividing by their nuclear mass number A (A^2) and pt by A. This is consistent with naive expectations from nucleon coalescence, butraises the question whether this mass ordering can also be explained by a hydrodynamical-inspired approach, like the blast-wave model. The relation of v2 and v4 to the shape of the initial eccentricity of the collision system is studied. It is found that v2 is independent of centrality for all three particle species after dividing it by the averaged second order participant eccentricity v2/⟨ε2⟩. A similar scaling is shown for v4 after division by ⟨ε2⟩^2.
Simulations of conformational changes and enzyme-substrate interactions in protein drug targets
(2022)
Finding new drugs is a difficult, time-consuming, and costly challenge, with only a small success rate along the drug discovery pipeline of far less than 10%. The high failure rate of drug discovery projects motivates the integration of computational tools throughout the whole drug discovery pipeline, from target identification to clinical trials. Target identification is the first step in the process. A biological target, e.g., a protein that plays a role in disease, is identified and its molecular mechanism in the disease is studied. Further, a potential binding site on the target, where therapeutic molecules can bind and modulate the target’s activity, needs to be characterized. Computational tools can contribute to improving the initial molecular target elucidation and assessment.
In this thesis, I use computational, physics-based approaches to characterize binding sites of drug targets and to decipher enzyme-substrate interactions, which play a role in disease mechanisms. Molecular dynamics (MD) simulations were applied to study the dynamics of molecules in solution at high temporal and spatial resolution. The method generates time-resolved trajectories of the particles in a system of interest by integrating Newton’s equations of motion numerically, starting from a set of coordinates and velocities. In MD simulations, all atoms of a chosen system, including solvent, are represented explicitly. Atomistic simulations are especially well-suited to study detailed interactions that depend on intermolecular interactions, such as hydration effects, hydrogen bonding, hydrophobic interactions, or subtle chemical differences. System properties are inferred from the trajectories, provided that the force fields, describing the interactions between the particles in the system, have a high accuracy. The bonded and non-bonded interactions are parametrized on experimental and quantum chemical data. The purpose of MD simulations can be to gain insight into the behavior of complex biological systems at molecular level, which often cannot be observed in experiments at the same resolution. With recent advances in computer hardware and simulation software, molecular systems of increasing size and simulation length can be investigated.
In the first part of the thesis, I investigated the conformational ensemble of various protein drug targets. Proteins are dynamic biomacromolecules that can have diverse and nearly isoenergetic conformational states. Ligand binding can shift the equilibrium of this conformational ensemble and can uncover binding sites, called cryptic sites. Cryptic sites only emerge upon small molecule binding and are often flat and featureless, and thus not easily recognized in crystal structures without bound ligands. If new binding sites including cryptic sites are detected, they can potentially be exploited for binding to ligands and enable a druggable target. Druggability is the ability of a protein to bind small, drug-like molecules, which is the basis for rational drug design. In this thesis, I used state-of-the-art physics-based, computational approaches to investigate the conformational ensembles of binding sites. In all studied systems, it is known from experiment that a specific group of ligands can induce conformational changes. The aim is to sample the conformational space made accessible upon ligand binding, yet without using the specific ligand structures or details about their interactions. We are interested in sampling the
pocket conformational states and identifying the respective pocket opening mechanism. For some cases, I additionally assessed whether the observed flexibility is a feature of the protein family, or specific to the protein under consideration.
The first studied system is factor VIIa (FVIIa). FVIIa is an essential part of the coagulation cascade and hence a potential drug target for thrombotic diseases. In addition, I investigated various other trypsin-like serine proteases from the same protein family. The binding pocket of trypsin-like serine proteases is called S1 pocket. An X-ray crystal structure solved by our collaborators reveals that a b-sheet structure in the S1 pocket is distorted by a bound ligand. I resolved the conformational change with MD simulations, starting from the unbound protein structure solvated in water and ions. I observed multiple spontaneous transition events. In 7 out of 22 simulations with the b-sheet as starting structure, the S1 pocket eventually rearranged into a distorted loop structure. These transitions occurred spontaneously and were mediated by water molecules probing the backbone hydrogen bonds. The conformational change studied here controls the onset of substrate binding and catalysis. Furthermore, I used metadynamics simulation, an enhanced-sampling method, to estimate the free energy barrier of this conformational change..
Standard cancer therapy research targets tumor cells while not considering the damage on the tumor microenvironment (TME) and its associated implications in impairing therapy response. Employing patients-derived organoids (PDOs) and matched stroma cells or a novel murine preclinical rectal cancer model of local radiotherapy, it was demonstrated that tumor cells-derived IL-1α polarizes cancer-associated fibroblasts towards an inflammatory (iCAFs) phenotype. While numerous studies in different tumor entities highlighted the molecular heterogeneity of CAFs, so far there are no clear findings on their functional heterogeneity and relevance in therapy resistance and response. The present study molecularly characterized iCAFs subpopulation among RCA patients as well as the preclinical mouse model and importantly unraveled the detailed molecular mechanism underlying their contribution to impair therapy response. Mechanistically, iCAFs were demonstrated to be characterized by an upregulation of nitric oxide synthase (iNOS) which triggered accumulation of reactive nitrogen species (RNS) and subsequently an oxidative DNA damage response (DDR). Such a baseline IL-1α-driven DNA damage further sensitized iCAFs to a p53-mediated therapy induced senescence (TIS) causing extensive extracellular matrix (ECM) changes and induction of senescence associated secretory phenotype (SASP) that favored tumor progression and hindered tumor cell death. Moreover, iCAFs reversibility and repolarization into more quiescent like phenotype was demonstrated upon IL-1 signaling inhibition by anakinra, a recombinant IL-1 receptor antagonist (IL1RA). Accordingly, treating mice with anakinra or specific deletion of Il1r1 in CAFs sensitized stroma-rich resistant tumors to chemoradiotherapy (CRT). Similarly, targeting CAFs senescence by senotherapy (venetoclax chemical) or employing Trp53 deficient mice reverted therapy resistance among non-responsive tumors in vivo by reducing ECM deposition and consequently favoring CD8+ T cells intratumoral infiltration posttherapy. Importantly, rectal cancer patients that do not completely respond to neoadjuvant therapy displayed an iCAFs senescence program post-CRT. Moreover, these patients presented a baseline increased CAFs content, a dominant iCAFs signature that correlated with poorer disease-free survival (DFS) and a significantly reduced circulating IL1RA serum levels. While reduced pretherapeutic IL1RN gene expression predicted poor prognosis among RCA patients, IL1RA serum levels were associated with rs4251961 (T/C) single nucleotide polymorphism (SNP) in the IL1RN gene. Finally, functional validation assays revealed that conditioned media of PDOs drove inflammatory polarization of fibroblasts and consequently rendered them sensitive to RNS-mediated DNA damage and TIS. Collectively, the study highlighted a crucial and novel role of a CAFs subset, iCAFs, in therapy resistance among RCA patients, shedding light on their functional relevance by identifying IL-1 signaling as an appealing target for their repolarization and successful targeting. Therefore, it makes sense to combine the newly demonstrated and thoroughly proven therapeutic approach of targeting IL-1 signaling in combination with conventional CRT and possibly immunotherapy. This might have a major impact on RCA therapy and be of immense relevance for other stroma-rich tumors.
Ob Klimawandel oder Luftverschmutzung: Die chemischen und physikalischen Prozesse in der Atmosphäre haben wichtige Auswirkungen auf die menschliche Gesundheit und Ökosysteme. Dabei ist die Atmosphäre mehr als ein Gemisch aus Stickstoff, Sauerstoff, Wasserdampf, Helium und Kohlenstoffdioxid. Es gibt zahlreiche Spurengase, deren Gesamtanteil am Volumen weniger als 1 % ausmacht. In dieser Arbeit werden Stickstoffoxide, Schwefeldioxid, Kohlenstoffmonoxid und Schwefelsäure näher betrachtet, die im Rahmen der flugzeugbasierten Messkampagne Chemistry of the Atmosphere: field experiment in Europe (CAFE-EU)/BLUESKY gemessen wurden.
Die Stickstoffoxide NO und NO2, als NOx zusammengefasst, besitzen hauptsächlich anthropogene Quellen, allen voran fossile Verbrennung und industrielle Prozesse. Zwischen NO und NO2 besteht ein photochemisches Gleichgewicht, sodass in der Atmosphäre vor allem NO2 in relevanten Konzentrationen vorkommt; dies wirkt aufgrund der Bildung von Salpetersäure, HNO3, in wässriger Lösung beim Einatmen ätzend und ist entsprechend gesundheitsschädlich. Troposphärisches Ozon, O3, wesentlicher Bestandteil von Sommersmog, wird hauptsächlich durch die Reaktion von NO mit Peroxiden (HO2 und RO2) gebildet. In der Stratosphäre entstehen NOx hauptsächlich durch die Photodissoziation von Lachgas, N2O, das aufgrund seiner langen Lebenszeit von der Tropo- in die Stratosphäre transportiert werden kann und dort die wichtigste Stickstoffquelle darstellt. In der Stratosphäre tragen NOx zum katalytischen Abbaumechanismus des Ozons bei (Bliefert, 2002; Seinfeld and Pandis, 2016).
Schwefeldioxid, SO2, ist ein toxisches Gas, dessen atmosphärische Quellen hauptsächlich anthropogen sind, nämlich fossile Verbrennung und industrielle Prozesse; Senken sind trockene und feuchte Deposition, wobei letztere zu saurem Regen führen kann. Seit den 1980ern sinken die globalen SO2-Emissionen. SO2 kann in der Atmosphäre zu Sulfat und Schwefelsäure oxidiert werden, was Hauptbestandteil des Wintersmogs ist. Der wichtigste Mechanismus ist die Oxidation mit dem Hydroxylradikal, OH˙, unter Beteiligung von Wasserdampf. In der Stratosphäre ist Carbonylsulfid, OCS, die wichtigste Schwefelquelle, da es analog zum N2O dank seiner langen Lebenszeit von der Tropo- in die Stratosphäre transportiert werden kann (Bliefert, 2002; Seinfeld und Pandis, 2016). Typische Konzentrationen von Schwefelsäure sind 105 cm–3 nachts und 107 cm–3 tagsüber in der Troposphäre sowie 105 cm–3 tagsüber in der Stratosphäre (Clarke et al., 1999; Weber et al., 1999; Fiedler et al., 2005; Arnold, 2008; Kürten et al., 2016; Berresheim et al., 2000).
Kohlenstoffmonoxid, CO, ist ein toxisches Gas, das zu gleichen Teilen durch direkte Emissionen (v.a. Biomasseverbrennung und fossile Verbrennung) und In-situ-Oxidation (v.a. von Methan, Isopren und industriellen Kohlenwasserstoffen) in die Atmosphäre gelangt. Die Hauptsenke ist die Reaktion mit OH˙ in der Troposphäre. Seit 2000 sinkt die globale CO-Konzentration (Bliefert, 2002).
Doch neben Gasen sind auch Aerosolpartikel fester Bestandteil des Gemisches Luft, welche luftgetragene feste oder flüssige Teilchen sind. Primäre Aerosolpartikel werden direkt als solche in die Atmosphäre emittiert, während sekundäre Aerosolpartikel in der Atmosphäre gebildet werden, indem gasförmige Vorläufersubstanzen mit geringer Flüchtigkeit auf primären Partikeln kondensieren oder durch Zusammenclustern und Anwachsen komplett neue Partikel bilden. Aerosolpartikel ermöglichen als Wolkenkondensationskeime erst die Bildung von Wolken und wirken somit – neben ihrem direkten reflektierenden Effekt – durch Änderung der Wolkenbedeckung und -eigenschaften insgesamt kühlend aufs Klima und beeinflussen die lokalen und globalen Wasserkreisläufe. Doch sie haben auch negative Auswirkungen auf die menschliche Gesundheit und sind für eine Verkürzung der durchschnittlichen Lebensdauer in Regionen mit hohen Feinstaubbelastungen verantwortlich (Seinfeld und Pandis, 2016; Bellouin et al., 2020; World Health Organization, 2016).
Neben den bisher betrachteten neutralen, also ungeladenen Gasen und Partikeln sind Ionen in der Gasphase sowie geladene Partikel ebenfalls Bestandteil der Atmosphäre. Sie spielen bei vielen atmosphärischen Prozessen eine wichtige Rolle, wie etwa bei Gewittern, Radiowellenübertragung und ionen-induzierter Nukleation von Aerosolpartikeln. Die Hauptquellen für Ionisation in der Tropo- und Stratosphäre ist die galaktische kosmische Strahlung, die entgegen ihrem Namen hauptsächlich aus Protonen und α-Partikeln (primäre Partikel genannt) besteht und in der Erdatmosphäre durch Kollision mit Luftmolekülen Teilchenschauer von sekundären Partikeln (u.a. Myonen, Pionen und Neutrinos) hervorruft. Die primären und sekundären Partikel können die Luftmoleküle ionisieren unter Entstehung von N+, N2+, O+, O2+ und Elektronen. Sauerstoff reagiert rasch mit letzteren zu O– und O2–. Diese Kationen und Anionen reagieren weiter, bis Ionenclustern der Summenformeln (HNO3)n(H2O)mNO3– und H+(H2O)n(B)m gebildet werden, wobei B Basen wie Methanol, Aceton, Ammoniak oder Pyridin sind. Weitere Ionisationsquellen sind der Zerfall des Radioisotops 222Rn in Bodennähe und ionisierende Solarstrahlung oberhalb der Stratosphäre. Atmosphärische Ionen haben zwei wichtige Senken: die Wiedervereinigung, auch Rekombination genannt, bei der sich ein Kation und ein Anion gegenseitig neutralisieren sowie das Anhaften an Aerosolpartikeln. Letztere Senke ist vor allem in der Troposphäre aufgrund der relativ hohen Konzentration an Aerosolpartikeln relevant (Arnold, 2008; Viggiano und Arnold, 1995; Bazilevskaya et al., 2008; Hirsikko et al., 2011).
This thesis presents a first-of-its-kind phenomenological framework that formally describes the development of acquired epilepsy and the role of the neuro-immune axis in this development. Formulated as a system of nonlinear differential equations, the model describes the interaction of processes such as neuroinflammation, blood- brain barrier disruption, neuronal death, circuit remodeling, and epileptic seizures. The model allows for the simulation of epilepsy development courses caused by a variety of neurological injuries. The simulation results are in agreement with ex- perimental findings from three distinct animal models of epileptogenesis. Simula- tions capture injury-specific temporal patterns of seizure occurrence, neuroinflam- mation, blood-brain barrier leakage, and progression of neuronal death. In addition, the model provides insights into phenomena related to epileptogenesis such as the emergence of paradoxically long time scales of disease development after injury, the dose-dependence of epileptogenesis features on injury severity, and the variability of clinical outcomes in subjects exposed to identical injury. Moreover, the developed framework allows for the simulation of therapeutic interventions, which provides insights into the injury-specificity of prominent intervention strategies. Thus, the model can be used as an in silico tool for the generation of testable predictions, which may aid pre-clinical research for the development of epilepsy treatments.