Gene mit gerigem Einfluss auf einen untersuchten Phänotyp können durch den Ein- schluss einer genetischen Variation im Tierversuch untersucht werden. Adulte Neuro- genese, der Prozess der Neubildung und Integration von funktionellen Neuronen in das existierende neurale Netzwerk, wird von vielen solchen Genen mit geringem Effekt beeinflusst. All diese Gene im lebenden Tier zu untersuchen wäre mit einem hohen Arbeitsaufwand verbunden, und würde hohe Tierzahlen erfordern. Bereits publizierte Ergebnisse zeigen, dass diese Gene auch in der Zellkultur unter Verwendung von Zelllinien genetisch rekombinanter Tiere untersucht werden können (Kannan et al., 2016). Die hier verwendeten, ingezüchteten Mausstämme des so genannten BXD Panels stellen die Nachkommen der Kreuzung der beiden Mausstämme C57BL/6J und DBA/2J dar (Peirce et al., 2004), die sich in der Ausprägung von unterschiedlichen Neurogenese bezogenen Phänotypen bereits deutlich unterscheiden (Kempermann et al., 2006). Durch die Verwendung der BXD Tiere wird hierbei die Aussagekraft der genetischen Variation mit dem Zellkultursystem verbunden. Die Aussagekraft dieser Studie ist jedoch darin limitiert, dass aufgrund des verwendeten Protokolls nur eine Zelllinie pro Mausstamm generiert werden konnte. Daher präsentiere ich hier ein neues Protokoll welches es erlaubt eine Zelllinie aus nur einem einzelnen Tier zu generieren. Diese Methode kombiniert zwei bestehende Zellkultursysteme, die Neurosphärenkultur und die Monolayerkultur. Es stellte sich heraus, dass die Überlebensrate der einzelnen Zelllinien vom biologischen Hintergrund der Zellen beeinflusst wird. So ist die Überlebensrate von Zellen der DBA/2J Mäuse deutlich schlechter als die der C57BL/6J oder die der F1 Generation aus der Verpaarung der beiden Stämme. Es zeigte sich allerdings, dass diese Überlebensrate nicht ausschließlich von der vorhandenen Anzahl proliferierender Zellen abhängt, da B6D2F1 (F1 Generation mit einem C57BL/6J Muttertier) signifikant weniger proliferierende (Ki67 positive) Zellen in vivo aufweisen, jedoch keine geringere Überlebensrate der Zelllinien haben. Eine hoch standardisierte, umfangreiche Analyse der Zelllinien aller vier Mausstämme (C57BL/6J, DBA/2J, und die zwei reziproken F1 Nachkommen BDF1 und DBF1) zeigte eine hohe Varianz innerhalb genetisch identischer Linien, was die Be- stimmung eines Effektes, der durch den genetischen Hintergrund der Linien verursacht wird, beeinträchtigte. Die Zelllinien werden signifikant von äußeren Faktoren beeinflusst, wie z.B. durch das Einfrieren der Zellen. Dies gibt Hinweise darauf, dass Untersuchungen in der Zellkultur genau geplant, kritisch hinterfragt, sowie möglichst alle potentiellen Einflussfaktoren gleich gehalten werden müssen. Nur so können valide, aussagekräftige Ergebnisse mit der Zellkultur gewonnen werden. Automatische Zellkultursysteme, neue Mikroskopieverfahren, sowie besser definierte Langzeitstudien werden unser Verständnis von Zellen in der Zellkultur deutlich verbessern und dabei ihren Wert, sowie bestehende Limitationen, endgültig klären.:List of Figures I List of Tables II List of Abbreviations III List of Publications V 1. Introduction 1 1.1 Genetic variation in animal research 2 Recombinant inbred strains 3 The BXD panel 4 The Gene Network 5 Genetic modifications 5 
 1.2 Adult hippocampal neurogenesis 6 History 7 Clinical relevance 8 The BXD panel and adult hippocampal neurogenesis 9 
 1.3 Developmental stages of neural precursor cells 9 
 1.4 Studying adult neurogenesis in vitro 11 Culturing hippocampal precursor cells 11 A mouse cell culture genetic reference panel 13 
 1.5 Tracking 13 
 1.6 Objectives 15 
 2. Materials and Methods 16 2.1 Components and equipment 16 
 2.2 Antibodies 20 
 2.3 Recipes 21 
 General buffers and solutions 21 Cell culture solutions 21 Immunocytochemistry solutions 23 Immunohistochemistry solutions 24 
 2.4 Experimental animals 25 
 2.5 Cell culture 25 Coating of cell culture vessels 25 Fire-polished pipettes 25 Dentate gyrus isolation 26 Neurosphere assay 26 Monolayer culture 27 
 2.6 Immunocytochemistry 29 BrdU staining preparations 29 Staining protocol 30 Imaging and counting 30 
 2.7 Immunohistochemistry 30 Sample preparation 30 Staining protocol 31 Cell counting 31 
 2.8 Tracking 32 Cell preparation and imaging setup 34 Image processing 35 Data analysis 35 
 2.9 Generation of CRISPR/Cas mediated knock-out lines 36 Construct design and cloning 36 E. coli Top10 transformation and plasmid isolation 37 Transfection of neural precursor cells and expansion of knock-out lines 38 Genotyping of the generated cell lines 39 Agarose gel electrophoresis 40 
 2.10 Statistical analysis 40 2.11 Data visualization 40 3. Results 41 3.1 Single animal monolayer cultures41 The three phenotypes of the neurosphere assay 44 Neurosphere assay phenotypes could not predict the survival of a cell line 45 The genetic background had an influence on all three phenotypes of the neurosphere assay 46 Significantly less proliferating cells in vivo but no difference in the neurosphere assay of BDF1 compared to BL6 animals 48 BDF1 cells could not be activated to form more spheres but sphere size could be increased using KCl 49 
 3.2 A new cell line phenotyping standard operation procedure and its application 50 Line generation data 52 Marker staining 54 Cell tracking 55 
 3.3 Cell culture – a system with limitations 59 Freezing effect 60 Cell culture data - technical variance hinders the analysis of small effects 62 3.4 Migration speed and GFAP 63 The strength of the BXD panel – cumulative data 65 
 3.5 Other applications of the tracking procedure 68 
 Tracking labeled cells in an embryonic zebrafish xenograft model 68 Cell tracking in mouse retina explants 68 4. Discussion 70 4.1 Single animal monolayer cultures – a new protocol 70 
 4.2 A new phenotyping pipeline 74 
 4.3 Semi-automated (user-supervised) cell tracking 77 
 4.4 A possible correlation between migration speed and differentiation 79 4.5 CRISPR/Cas knock-out lines - an ill-conceived system with high potential 82 4.6 The problem of the validity of cell culture experiments - a comment 83 4.7 Conclusion 84 
 Bibliography 88 A Single animal cell line generation protocol 106 
 B Cell line characterization SOP 112 
 C R Scripts 117 / Uncovering gene loci that assert only small effects onto a phenotype of interest, can be achieved by including genetic variation in animal research. Adult hippocampal neurogenesis, the process of the formation of new neurons and their functional integration into existing circuitry, is influenced by a broad range of such small effect genes. Analyzing all of these genes in vivo would be laborious and require a high number of animals. Previously published data merged the power of genetic variation with a cell culture system by using cell lines generated from the BXD recombinant inbred mouse strains (Kannan et al., 2016). These strains are inbred progeny of F2 crosses originating from the two mouse strains C57BL/6J and DBA/2J (Peirce et al., 2004), which already differ quite extensively in neurogenesis related phenotypes (Kempermann et al., 2006). As previous studies were limited by the number of strains that could be generated due to the demand for high numbers of animals, I developed a new method that allows the generation of a cell line from one single animal. For this new method, I combined the neurosphere culture with a subsequent monolayer culture. The survival of the resulting cell lines, is thereby greatly influenced by the genetic background. The survival rate of cell lines derived from DBA/2J animals is much lower as compared to C57BL/6J-derived lines or lines from the F1 generation of crossing the two strains. Whether or not a cell line survived did not seem to be solely influenced by the number of proliferating cells in vivo, as B6D2F1 (F1 progeny with a C57BL/6J mother) showed significantly less proliferative (Ki67 positive) cells in vivo while exhibiting a survival rate that exceeded both parental strains. An extensive study of the cell lines gained from all four mouse strains (C57BL/6J, DBA/2J, and the two reciprocal F1 progeny B6D2F1 and D2B6F1) in a highly standardized manner showed that the individual difference between single cell lines was rather high, hampering the successful detection of in-between strain differences. The standardized characterization of the generated cell lines, further allowed the identification of external factors, influencing the cells, as for example the freezing of the cells. This indicates that cell culture experiments need to be thoroughly planned and critically scrutinized, while all external factors should be kept as constant as possible to ensure the validity of the resulting data. Automated cell handling, new imaging technologies, as well as more defined long-term studies will greatly improve the understanding of cells in culture and thereby show their true values and limitations.:List of Figures I List of Tables II List of Abbreviations III List of Publications V 1. Introduction 1 1.1 Genetic variation in animal research 2 Recombinant inbred strains 3 The BXD panel 4 The Gene Network 5 Genetic modifications 5 
 1.2 Adult hippocampal neurogenesis 6 History 7 Clinical relevance 8 The BXD panel and adult hippocampal neurogenesis 9 
 1.3 Developmental stages of neural precursor cells 9 
 1.4 Studying adult neurogenesis in vitro 11 Culturing hippocampal precursor cells 11 A mouse cell culture genetic reference panel 13 
 1.5 Tracking 13 
 1.6 Objectives 15 
 2. Materials and Methods 16 2.1 Components and equipment 16 
 2.2 Antibodies 20 
 2.3 Recipes 21 
 General buffers and solutions 21 Cell culture solutions 21 Immunocytochemistry solutions 23 Immunohistochemistry solutions 24 
 2.4 Experimental animals 25 
 2.5 Cell culture 25 Coating of cell culture vessels 25 Fire-polished pipettes 25 Dentate gyrus isolation 26 Neurosphere assay 26 Monolayer culture 27 
 2.6 Immunocytochemistry 29 BrdU staining preparations 29 Staining protocol 30 Imaging and counting 30 
 2.7 Immunohistochemistry 30 Sample preparation 30 Staining protocol 31 Cell counting 31 
 2.8 Tracking 32 Cell preparation and imaging setup 34 Image processing 35 Data analysis 35 
 2.9 Generation of CRISPR/Cas mediated knock-out lines 36 Construct design and cloning 36 E. coli Top10 transformation and plasmid isolation 37 Transfection of neural precursor cells and expansion of knock-out lines 38 Genotyping of the generated cell lines 39 Agarose gel electrophoresis 40 
 2.10 Statistical analysis 40 2.11 Data visualization 40 3. Results 41 3.1 Single animal monolayer cultures41 The three phenotypes of the neurosphere assay 44 Neurosphere assay phenotypes could not predict the survival of a cell line 45 The genetic background had an influence on all three phenotypes of the neurosphere assay 46 Significantly less proliferating cells in vivo but no difference in the neurosphere assay of BDF1 compared to BL6 animals 48 BDF1 cells could not be activated to form more spheres but sphere size could be increased using KCl 49 
 3.2 A new cell line phenotyping standard operation procedure and its application 50 Line generation data 52 Marker staining 54 Cell tracking 55 
 3.3 Cell culture – a system with limitations 59 Freezing effect 60 Cell culture data - technical variance hinders the analysis of small effects 62 3.4 Migration speed and GFAP 63 The strength of the BXD panel – cumulative data 65 
 3.5 Other applications of the tracking procedure 68 
 Tracking labeled cells in an embryonic zebrafish xenograft model 68 Cell tracking in mouse retina explants 68 4. Discussion 70 4.1 Single animal monolayer cultures – a new protocol 70 
 4.2 A new phenotyping pipeline 74 
 4.3 Semi-automated (user-supervised) cell tracking 77 
 4.4 A possible correlation between migration speed and differentiation 79 4.5 CRISPR/Cas knock-out lines - an ill-conceived system with high potential 82 4.6 The problem of the validity of cell culture experiments - a comment 83 4.7 Conclusion 84 
 Bibliography 88 A Single animal cell line generation protocol 106 
 B Cell line characterization SOP 112 
 C R Scripts 117

More efficient and reliable High-Throughput Field Phenotyping (HTFP) approaches are essential for the development of plant breeding and carbon storage studies, as well as the improvement of yield estimation in the food production sector. The use of ground-based platforms in combination with other data sources such as UAVs and satellites addresses constraints related to payload capacity restrictions and reduced below-canopy data collection. This study describes an early approach to the deployment of agile robots for HTFP that aims to estimate height, diameter at breast height (DBH), and volume for forty-three unique trees corresponding to two different species (E. variegata and F. altissima) occupying an urban-park. The data acquisition system consists of an agile robot from Boston Dynamics and a navigation enhancer LiDAR module from the same company. In order to obtain a point cloud using this system, it is necessary to overcome two challenges: a reduced vertical FoV of the LiDAR and limited management of the LiDAR module. A multiway registration approach is implemented to reconstruct a low-density digital twin of the experiment site, which is later georeferenced using points surveyed with a GNSS system. Subsequently, the point cloud is manually segmented using CloudCompare software to obtain individual tree point clouds. Three different algorithms are implemented to obtain height, DBH, and tree volume estimates from the individual point clouds. The results are statistically analyzed by species in order to characterize sources of error. The height estimation method had a Median Percentage Error (MPE) of 1.4% for E. variegata and 1.2% for F. altissima. The DBH estimation had an MPE of 20.1% for E. variegata and 13% for F. altissima. The volume estimation model returned an R2 of 0.86 for E. variegata and 0.98 for F. altissima. Finally, all three feature estimations are mapped into a GEOJson file. These findings, combined with the numerous advantages of using agile robots as mobile platforms in HTFP, enable more efficient and reliable estimation of important parameters such as aboveground biomass and carbon storage sequestration, as well as delivery the potential for improvements in crop monitoring and yield estimation.

<p>    </p> <p>Meeting the nutritional requirements of an increasing population in a changing climate is the foremost concern of agricultural research in recent years. A solution to some of the many questions posed by this existential threat is breeding crops that more efficiently produce food with respect to land and water use. A key aspect to this optimization is geometric aspects of plant physiology such as canopy architecture that, while based in the actual 3D structure of the organism, does not necessarily require such a representation to measure. Although deep learning is a powerful tool to answer phenotyping questions that do not require an explicit intermediate 3D representation, training a network traditionally requires a large number of hand-segmented ground truth images. To bypass the enormous time and expense of hand- labeling datasets, we utilized a procedural sorghum image pipeline from another student in our group that produces images similar enough to the ground truth images from the phenotyping facility that the network can be directly used on real data while training only on automatically generated data. The synthetic data was used to train a deep segmentation network to identify which pixels correspond to which leaves. The segmentations were then processed to find the number of leaves identified in each image to use for the leaf-counting task in high-throughput phenotyping. Overall, our method performs comparably with human annotation accuracy by correctly predicting within a 90% confidence interval of the true leaf count in 97% of images while being faster and cheaper. This helps to add another expensive- to-collect phenotypic trait to the list of those that can be automatically collected. </p>

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<p>Plant phenotyping focuses on the measurement of plant characteristics throughout the growing season, typically with the goal of evaluating genotypes for plant breeding and management practices related to nutrient applications. Estimating plant characteristics is important for finding the relationship between the plant's genetic data and observable traits, which is also related to the environment and management practices. Recent machine learning approaches provide promising capabilities for high-throughput plant phenotyping using images. In this thesis, we focus on estimating plant traits for a field-based crop using images captured by Unmanned Aerial Vehicles (UAVs). We propose a method for estimating plant centers by transferring an existing model to a new scenario using limited ground truth data. We describe the use of transfer learning using a model fine-tuned for a single field or a single type of plant on a varied set of similar crops and fields. We introduce a method for rapidly counting panicles using images acquired by UAVs. We evaluate three different deep neural network structures for panicle counting and location. We propose a method for sorghum flowering time estimation using multi-temporal panicle counting. We present an approach that uses synthetic training images from generative adversarial networks for data augmentation to enhance the performance of sorghum panicle detection and counting. We reduce the amount of training data for sorghum panicle detection via semi-supervised learning. We create synthetic sorghum and maize images using diffusion models. We propose a method for tomato plant segmentation by color correction and color space conversion. We also introduce the methods for detecting and classifying bacterial tomato wilting from images.</p>

<p>Improved phenotyping technologies and data analytic strategies have the potential to reduce the phenotyping bottleneck in breeding programs, increase the number of genotypes that can be evaluated, and improve genetic gain of maize. Ear photometry and remote sensing were evaluated in this dissertation for their integration into breeding programs to understand the development of grain yield in diverse germplasm and to better predict yield performance. Ear photometry was used in Chapter 2 to characterize the testcross performance of temperate and tropical inbred lines. The effect of heterosis among the temperate heterotic groups was more noticeable in the ear-related characteristics rather than kernel-size characteristics. Yield components were generally more heritable than grain yield per ear, so they were explored for their use in multi-trait genomic prediction for grain yield on a plot or ear basis in Chapter 3. Multi-trait genomic prediction of grain yield was improved where ear characteristics were known in the testing set compared with single-trait genomic prediction.  Additionally, single-trait genomic prediction was more accurate in the temperate germplasm compared to the tropical germplasm. Thus, ear photometry is an efficient method to quickly assess yield components in maize and improve yield prediction in certain circumstances. In Chapter 4, the effect of row selection, plot size, and plot trimming on remote sensing trait repeatability and prediction accuracy of biomass yield in sorghum or grain yield in maize was evaluated. Decreased plot size and configuration has been suggested to increase the number of genotypes that can be evaluated per unit area. In this study, larger plot sizes were favorable for increasing repeatability and excluding outer rows improved predictive modelling. Plot trimming was never shown to be significantly different from non-trimmed plots in this study. Genomic prediction is another way to minimize experimental size and phenotypic data collection and was evaluated in Chapter 5. A reaction norm was used to model the trajectory of hybrid yield performance across a gradient of 86 environments. The heritability and prediction accuracy of grain yield were both improved in the higher-yielding environments compared to the lower-yielding environments. Single nucleotide polymorphisms with the highest magnitude of effects were selected in each environment. Twenty-one SNPs were selected indicating many SNPs were selected in multiple environments. Candidate genes in linkage disequilibrium with many of these SNPs were previously reported as stress adaptions. Genomic prediction and remote sensing were integrated for prediction of grain yield in Chapter 6. Heritability of remote sensing traits generally improved throughout the growing season. Prediction accuracy of BLUPs were improved through an integrated phenomic and genomic prediction model for all scenarios tested. In summary, ear photometry and remote sensing are technologies to evaluate large populations for unique plant trait characteristics that can be used in combination with genomic prediction to improve understanding of grain yield development and grain yield prediction.</p>

The rapid digitalization of the healthcare domain in recent years highlighted the need for advanced predictive methods particularly based upon deep learning methods. Deep learning methods which are capable of dealing with time- series data have recently emerged in various fields such as natural language processing, machine translation, and the Intensive Care Unit (ICU). The recent applications of deep learning in ICU have increasingly received attention, and it has shown promising results for different clinical tasks; however, there is still a need for the benchmark models as far as a handful of public datasets are available in ICU. In this thesis, a novel benchmark model of four clinical tasks on a multi-center publicly available dataset is presented; we employed deep learning models to predict clinical studies. We believe this benchmark model can facilitate and accelerate the research in ICU by allowing other researchers to build on top of it. Moreover, we investigated the effectiveness of the proposed method to predict the risk of delirium in the varying observation and prediction windows, the variable ranking is provided to ease the implementation of a screening tool for helping caregivers at the bedside. Ultimately, an attention-based interpretable neural network is proposed to predict the outcome and rank the most influential variables in the model predictions’ outcome. Our experimental findings show the effectiveness of the proposed approaches in improving the application of deep learning models in daily ICU practice.

Background. Multiple sclerosis (MS) is a chronic autoimmune inflammatory disease of the central nervous system. It is the most common neurological disease in young adults, affecting mostly women at the peak of their productive age. The most frequent disease phenotype is the relapsing remitting MS, where patients present relapses with a total or partial recovery of their symptoms. A group of these patients develops a secondary progressive course (SPMS), with an accumulation of MS-related disability independent of the relapse activity. As the identification of SPMS represents a significant diagnostic challenge, the identification of disease disability plays an important role in the monitoring of these patients. Gait and balance problems stand out among the most important symptoms of disability in MS patients. Due to the heterogeneity of the demyelinating lesions and their burden, several anatomic structures with a consequence in postural control may be affected by the MS. Recent advances in technology make possible a reliable evaluation of balance through objective measures. The implementation of static posturography could complement the classical neurological evaluation through the Expanded Disability Status Scale (EDSS) in the detection and characterization of balance impairment. Additionally, in the recent years, several new disease modifying treatment (DMTs) options have been developed for the treatment of MS. Fingolimod is a modulator of the S1P receptor that alters the trafficking of lymphocytes, decreasing the absolute count in blood. Several adverse effects have been described for this drug through its mechanism of action, such as cardiac or vascular alterations. Animal models have demonstrated a reduction of the fecal secretory immunoglobulin A (sIgA) levels through an impairment of the local immune response in the colon and a reduction of plasma cell precursors controlled by the S1P receptor. Human studies for this effect have not been so far. A similar effect in MS patients could lead to an impairment in the gut function and alter the commensal bacteria in the gut microbiome. Considering the limitations of the classic neurological evaluation and the still incomplete but growing understanding of MS, the investigation of clinical and paraclinical characteristics of MS patients and the effects of DMTs gains a remarkable importance. The main objective of this dissertation was to characterize people with MS through clinical outcome measures, as well as through the evaluation of fecal immunity after long-term treatment with fingolimod. Additionally, an assessment of balance parameters generated through static posturography was performed as well as physiological characteristics and alterations of postural control in this group. Methods. A cross-sectional evaluation of MS patients and healthy controls was performed. Patients with confirmed diagnosis of MS according to the 2010’s McDonald’s criteria and healthy controls were evaluated. An EDSS score was calculated for each patient according to the neurostatus scoring guidelines. Static posturography measures were performed with patients standing on a force platform in a standardized position equivalent to the Romberg test. The following balance outcomes were generated through an automatized software fur further evaluation: delineated area, average sway and average speed of sway. Both were obtained in the open and closed eyes conditions. The difference between the conditions was calculated. Fecal and salivary samples of a group of 25 patients with MS diagnosis and treatment with fingolimod or glatirameracetat for over twelve months were analyzed after a proper standardization. Through ELISA immunoasays free sIgA levels were calculated in the supernant. Required statistical analysis were performed. Results. 99 people with MS and 30 healthy controls participated in the static posturography evaluation. The MS had a worse performance than healthy controls in the three static posturography outcomes. Both groups had a worse performance in the closed eyes condition. However, the magnitude of the effect of vision was more significant in the MS patients as a significant interaction between vision and MS diagnosis was seen in the delineated area (p < 0.001) and average speed of sway (p = 0.001). There were moderate and significant correlations between most of the evaluated parameters and the EDSS and MSFC (r’s ranging from 0.207 to 0.537, p < 0.05). The highest correlations were seen for the delineated area and average speed in the closed eyes condition and their difference between the open and closed eyes evaluations. Especially these two parameters could differentiate between disability groups and healthy controls. Additionally, patients without postural instability documented through the Romberg test score of the EDSS assessment showed significantly worse outcomes in the delineated area [+1.97 cm2, 95%-CI (0.61–3.34); p = 0.002] than healthy controls. A similar trend was observed for the comparison between MS patients with normal cerebellar function EDSS-systems and healthy subjects. On the other hand, 15 patients with fingolimod and 10 with glatirameracetat participated in the measure of fecal sIgA. There was no significant difference between both groups at the evaluated time point. A similar pattern was seen in the salivary sIgA and serum immunoglobulins. In our studie, we evaluated the static posturography as a complement of the neurological assessment through the EDSS, which could characterize disease disability already at early stages of the diseases. The MS patients were more dependent of the visual feedback than HC to maintain postural control. In contrast, we could not confirm a decrease of fecal sIgA after a long-term treatment with fingolimod, although further longitudinal studies are needed for further analysis. / Hintergrund. Die Multiple Sklerose (MS) ist eine chronisch entzündliche Autoimmunerkrankung des Zentralnervensystems. Sie ist die häufigste neurologische Erkrankung bei jungen Erwachsenen und betrifft vor allem Frauen auf dem Höhepunkt ihres produktiven Alters. Der häufigste Krankheitsverlauf ist die schubförmig remittierende MS (RRMS), bei der die Patienten Schübe mit einer vollständigen oder teilweisen Erholung ihrer Symptome aufweisen. Eine Gruppe dieser Patienten entwickelt einen sekundär progredienten Verlauf (SPMS), wobei eine schleichende MS-bedingte Behinderungsprogression unabhängig von der Schubsaktivität beschrieben wird. Da die Diagnose von SPMS eine bedeutende diagnostische Herausforderung darstellt, spielt die frühzeitige Erkennung der krankheitsbedingten Einschränkungen eine wichtige Rolle beim Monitoring von MS-Patienten. Gang- und Gleichgewichtsstörungen gehören zu den wichtigsten Beschwerden bei MS-Patienten. Aufgrund einer breiten Heterogenität der demyelinisierenden Läsionen können mehrere anatomische Strukturen mit Auswirkungen in der Haltungskontrolle betroffen sein. Jüngste technologische Fortschritte ermöglichen eine zuverlässige Bewertung des Gleichgewichts durch objektive Messungen. Die Anwendung der statischen Posturographie könnte die klassische neurologische Untersuchung durch die Expanded Disability Status Scale (EDSS) hinsichtlich einer Erkennung und Charakterisierung von Gleichgewichtsstörungen ergänzen. Darüber hinaus wurden in den letzten Jahren mehrere neue krankheitsmodifizierende therapeutische Optionen (DMTs) für die Behandlung von MS-Patienten entwickelt. Fingolimod ist ein Modulator des S1P-Rezeptors, der die Lymphozytendistribution modifiziert mit einer absoluten Verminderung der Anzahl im Blut. Für dieses Medikament wurden mehrere unerwünschte Wirkungen durch seinen Wirkmechanismus beschrieben, wie z.B. kardiale oder vaskuläre Veränderungen. In Tiermodellen wurde eine Verringerung der fäkalen sekretorischen Immunglobulin-A-Spiegel (sIgA) durch eine Beeinträchtigung der lokalen Immunantwort im Dickdarm und eine Verringerung der durch den S1P-Rezeptor kontrollierten Plasmazellvorläufer nachgewiesen. Humanuntersuchungen bezüglich dieses Effekts sind zu diesem Zeitpunkt noch nicht durchgeführt worden. Ein ähnlicher Effekt bei MS-Patienten könnte zu einer Beeinträchtigung der Darmfunktion führen und die kommensalen Bakterien der Darmflora verändern. In Anbetracht der Einschränkungen der klassischen neurologischen Unteruschung und des noch unvollständigen, jedoch wachsenden Verständnisses der MS gewinnt die klinische und paraklinische Phenotypisierung von MS-Patienten und der Wirkungen von DMTs eine bemerkenswerte Bedeutung. Das Hauptziel dieser Dissertation war die Phenotypisierung von Menschen mit MS durch klinische Ergebnismessungen sowie durch die Bewertung der fäkalen Immunität nach Langzeitbehandlung mit Fingolimod. Zusätzlich wurde eine Bemessung von Gleichgewichtsparametern, die durch statische Posturographie erzeugt wurden, sowie physiologische Merkmale und Veränderungen der posturalen Kontrolle in dieser Gruppe durchgeführt. Methoden. Es wurde eine Querschnittanalyse von MS-Patienten und gesunden Kontrollen durchgeführt. Patienten mit einer bestätigten MS-Diagnose nach den Revisionen der McDonald's-Kriterien von 2010 und gesunde Kontrollpersonen wurden untersucht. Für jeden Patienten wurde ein EDSS-Score nach den Neurostatus-Scoring-Leitlinien erhoben. Statische posturographische Messungen wurden durchgeführt, wobei die Patienten auf einer Kraftplattform in einer standardisierten Position standen, die dem Romberg-Test entsprach. Die folgenden Gleichgewichtsparameter wurden durch eine automatisierte Software zur weiteren Auswertung generiert: „delineated area“ (abgegrenzter Bereich), „average sway“ (durchschnittliches Schwanken) und „average speed of sway“ (durchschnittliche Schwenkgeschwindigkeit). Diese wurden mit dem Patienten mit offenen und geschlossenen Augen erhoben. Die Differenz zwischen beiden Bedingungen wurde dazu berechnet. Stuhl- und Speichelproben einer Gruppe von 25 Patienten mit MS-Diagnose nach Behandlung mit Fingolimod oder Glatirameracetat für über zwölf Monate wurden nach einer angemessenen Standardisierung analysiert. Mittels ELISA-Immunassays wurden die freien sIgA-Konzentrationen im Supernant berechnet. Die erforderliche statistische Analyse wurde durchgeführt. Ergebnisse. 99 Personen mit MS und 30 gesunde Kontrollen nahmen an der statischen posturographischen Auswertung teil. Die MS-Gruppe hatte in den drei statischen Posturographie-Ergebnissen eine schlechtere Leistung als gesunde Kontrollen. Beide Gruppen hatten eine schlechtere Leistung im Zustand mit geschlossenen Augen. Das Ausmaß der Auswirkung des Sehens war jedoch bei den MS-Patienten bedeutsamer, da eine signifikante Interaktion zwischen Sehen und MS-Diagnose im abgegrenzten Bereich (p < 0,001) und der durchschnittlichen Schwankungsgeschwindigkeit (p = 0,001) in einer ANCOVA-Analyse zu beobachten war. Es gab mäßige und signifikante Korrelationen zwischen den meisten der evaluierten Parameter und der EDSS und dem MSFC (die r-Werte lagen zwischen 0,207 und 0,537, p < 0,05). Die höchsten Korrelationen wurden für die „delineated area“ und die „average speed of sway“ im Zustand mit geschlossenen Augen und deren Differenz zwischen dem Zustand mit offenen und geschlossenen Augen festgestellt. Insbesondere diese beiden Parameter konnten zwischen (leicht) Behindertengruppen und gesunden Kontrollen unterscheiden. Zusätzlich zeigten Patienten ohne klinisch sichtbare Gleichgewichtsstörungen, die durch den Romberg-Testscore der EDSS-Bewertung dokumentiert wurden, signifikant schlechtere Ergebnisse der „delineated area“ [+1,97 cm2, 95%-CI (0,61-3,34); p = 0,002] als gesunde Kontrollen. Ein ähnliches Muster wurde für den Vergleich zwischen MS Patienten mit normaler Kleinhirnfunktion und gesunden Probanden beobachtet. Auf der anderen Seite nahmen 15 Patienten mit Fingolimod und 10 mit Glatirameracetat an der Messung der fäkalen sIgA teil. Zum ausgewerteten Zeitpunkt gab es keinen signifikanten Unterschied zwischen beiden Gruppen. Ein ähnliches Muster zeigte sich bei der Speichel-sIgA und den Serum-Immunglobulinen. In unseren Studien evaluierten wir die statische Posturographie als Ergänzung der neurologischen Beurteilung durch die EDSS, die die Krankheitsinvalidität bereits in frühen Krankheitsstadien charakterisieren könnte. Die MS-Patienten waren zur Aufrechterhaltung der posturalen Kontrolle stärker vom visuellen Feedback abhängig als von der HC. Im Gegensatz dazu konnten wir eine Abnahme der fäkalen sIgA Konzentration nach einer Langzeitbehandlung mit Fingolimod nicht bestätigen, wobei zur weiteren Analyse Längsschnittstudien erforderlich sind.

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