The 10 most recently published documents
Quantitative Wood Anatomy (QWA) is defined as the analysis of the xylem anatomical features in trees, shrubs and herbaceous plants to investigate plants functioning, growth and environment. By combining the recognition of wood anatomical structures together with measurement techniques to quantify anatomical features like cell size, cell wall thickness, or vessel density, QWA provides comparable data among growth ring time series. The combination between QWA and dendrochronology allows for the establishment of wood anatomical trait time series which are particularly valuable in the frame of past climatic reconstructions and, in parallel, to predict plant functioning under future climate projections. Due to the intensification of the climate crisis, QWA is becoming an increasingly important tool for understanding the impacts on forest and shrub ecosystems and establish counteractive strategies. Current methodologies for quantitative wood anatomical analyses provide manual or semi-automated methods, therefore requiring significant user input in terms of settings adjustments and manual editing. These characteristics hinders these tools from being the ideal solution to tackle the current rising demand for wood anatomical data. The time spent for such analyses and the effort employed to gain meaningful results raise the interest in the implementation of AI in QWA.
Quantitative wood anatomical analyses may considerably improve in precision and efficiency following AI incorporation to the overall workflow, because of AI ability to identify complex patterns and relationships within wood structure. Furthermore, the automatization introduced by AI methods is supposed to improve the time-consuming task of manually editing traditional image analyses output. For these reasons this dissertation addresses two research topics: i) applying AI detection skills to improve quantitative wood anatomical analyses on thin-sections from wooden cores (Chapters I and II) and ii) introduce AI for the detection of concentric rings in shrub thin-sections and facilitate their measurements (Chapters III and IV).
The successful development of two distinct tools responding respectively to aim i) and ii) demonstrated that it is possible to improve the current state of the art by joining the two fields of AI and QWA for a variety of purposes. We introduced the development of CARROT (Cell And Ring RecOgnition Tool) in order to streamline quantitative wood anatomical analyses for a faster and automated workflow (Chapter I), and of INBD (Iterative Next Boundary Detection) to address the methodological gap of concentric ring automated detection and the relative computation (Chapter III). These tools showed not only the ability to provide meaningful results in the execution of the main tasks, but also to generally outperform manual or classic image analysis (Chapters I and IV). In view of the results obtained by both approaches, we promote the use of CARROT and INBD underscoring on one side the advantage of employing automatized methods to save time during analyses, and on the other side, the relevance of their broad applicability. Both tools operate several essential tasks with fairly high accuracy, handling
two growth structures (trees and shrubs), and in the case of CARROT four wood anatomical types (conifer, ring-porous, semi-ring-porous, and diffuse-porous). A great potential of application resides in the implementation of a user interface for both tools (Chapter II and IV), promoting wood anatomical analysis improvement through user-friendly interfaces in an open-source environment.
Practical applications of both tools were also performed. In Chapter II, CARROT was employed with the purpose of studying wood anatomical changes in surviving pedunculate oaks, after the flooding and the permanent rewetting of a formerly drained peatland. In this context, CARROT was found to be once again meeting the expectations in terms of high cell recognition performance, coping with the segmentation of both very wide earlywood vessels and very small latewood vessels. In Chapter IV, INBD cross-dating potential was tested to frame the realistic application of the tool. Results showed that cross-dating statistics were higher for INBD ring width measurements compared to those obtained manually, and that in most cases INBD was outperforming manual measurements even prior to any cross-dating attempt.
In general, we could observe that both methods would greatly benefit from the implementation of larger training datasets, which would enhance their accuracy across diverse wood anatomical dataset. For INBD specifically, future developments should focus on including functions that allow users to correct wrongly detected outputs and consequently recalculate the data.
Currently, recent attempts in merging AI and wood anatomy mainly take advantage of AI strengths to focus on species recognition or ring identification from cores, without effectively addressing quantitative wood anatomical research questions. For these reasons, CARROT and INBD can be regarded as cutting-edge techniques in quantitative wood anatomical analyses, for their innovative method and for their effective feasibility. Their employment would not only improve results in terms of accuracy and time, but also allow researchers to shift the focus towards the interpretation of the results and their discussion, rather than the current constraints of obtaining such results. Overall, the integration of CARROT and INBD and similar tools into quantitative wood anatomical research framework yield the possibility of expanding such studies, constituting a meaningful resource to broaden ecological investigations.
Orally administered medications are susceptible to different conditions, which can change the pharmacokinetics (PK), and directly influence the bioavailability of a drug. Because older adults are susceptible to drug adverse effects, changes in drug PK may be harmful to them, therefore, it is favourable to know how they take their medications in real life. The presented thesis combines theoretical and practical aspects of dosing conditions. First, by means of a questionnaire study, the real-life dosing conditions in older adults were investigated to identify the possible problems that can affect the safety and efficiency of orally administered medications from a biopharmaceutical perspective. The developed questionnaire was applied in Germany and Poland. Both study populations were similar regarding drug intake. Typical dosing conditions reported by older populations in Germany and Poland that were the most important for drug absorption were as follows: I. Drug intake was on average, with ~100 mL of fluid (in Germany, most often ~200 mL, in Poland ~50 mL). II. Non-carbonated water, tea, coffee, and carbonated water were commonly used for drug administration. III. Medications were mostly taken directly after meals; in Germany, also 30 minutes before breakfast. IV. Bread-based meals dominated breakfast and dinner. V. Solid dosage forms were preferred for their ease of use and swallowing.
Second, the data about the most common fluids co-administered with medications by older adults were used to investigate the influence of real-life fluids on the disintegration of gelatine and HPMC capsules in vitro and in vivo. For in vitro studies, the USP 2 apparatus and the biorelevant GastroDuo model were used. In a clinical study with 12 young, healthy volunteers and 6 study arms, the salivary tracer technique was used. In the clinical study, the gastric emptying of administered fluids was also investigated.
In vitro data demonstrated that co-administered fluids strongly affected capsules' behaviour. For gelatine capsules, temperature had the greatest influence. HPMC capsules were more consistent, however, black tea delayed their opening time and drug release in the USP 2 apparatus. In vivo, gelatine capsules were also highly affected by the temperature, with the fastest opening in warm water and significantly slower in cold water. However, warm black tea significantly delayed the opening time of gelatine capsules in comparison to warm water. HPMC capsules behaved consistently in all fluids, showing no effect of temperature or black tea ingredients. Overall, HPMC capsules were more robust under fasting conditions. Results also highlighted differences between in vitro models. USP 2 apparatus captured mainly temperature effects, while GastroDuo better reflected in vivo conditions by simulating gastric emptying, pH, volumes of media, secretion and pressure events and predicted well the behaviour of HPMC capsules in vivo.
No significant differences in gastric emptying of tested fluids were observed, which demonstrates that the indirectly detected capsule behaviour is the result of their properties and the influence of the co-administered fluid, not a matter of differences in gastric emptying.
Older adults in Poland and Germany interviewed within the presented thesis mostly administered their medications with non-carbonated water. However, the usage of black tea was also worth noting, since it was especially prevalent among the Polish population and in further studies it was demonstrated that it significantly delayed the opening time of gelatine capsules in vivo. The collected data gave an overview of capsules' behaviour in real-life fluids and demonstrated that dosing conditions are important. Investigating how patients take their medications is a way to ensure a more patient-centric approach in drug development.
Background: This PhD thesis is based on four comprehensive studies, all conducted to deepen understanding of various aspects of quality of life (QoL) among cancer patients. The assessment of QoL in this population has become increasingly significant, with patient reported outcomes (PROs) serving as indispensable tools for evaluation. QoL is a dynamic and multifaceted concept, encompassing all dimensions of life and reflecting individual needs and values. It is subjectively experienced and influenced by a multitude of factors. Within this context, the projects outlined in this thesis concentrate on various dimensions, all contributing to a deeper comprehension of QoL in cancer patients.
Study I: To evaluate whether external factors such as weather, sunshine, season, or lunar phase influence patient-reported outcomes in cancer patients: Results from the Prospective, Longitudinal, Observational Cohort ExPRO Study. Patients frequently report variations in their emotional and physical health in response to climatic conditions. Over the course of one year, patients were surveyed using the EORTC QLQ-C30, and daily weather data were documented to investigate the impact of weather factors on the QoL of cancer patients.
Study II: How do quality of life (QoL) and symptom burden evolve in inpatient palliative care (PC) patients following one week of care in a specialized palliative care unit (PCU)? A comparison of two groups, with one receiving specialized outpatient palliative care prior to admission. This investigation delves into the impact of PC on QoL among cancer patients. Alongside inpatient PC, specialized outpatient PC services extend care to patients in their homes. The study contrasts the QoL changes following one week of inpatient PC between two groups, one of which had prior support from an outpatient PC team. Another analysis within this project focuses on investigating the influence of dental care on QoL (Study III: Exploring the integration of dentistry within a multidisciplinary palliative care team: does dental care improve quality of life and symptom burden in palliative care patients?).
Study IV: Evaluation of electronic patient reported outcome assessment in inpatient cancer care: a feasibility study. PROs provide valuable insights into the subjective experiences and QoL. Despite their growing integration into clinical practice, PROs have predominantly been documented on paper. In this study, electronic PRO assessment was introduced into inpatient cancer care to evaluate its feasibility.
Results & Conclusion: The studies presented in this work provide insight into various facets of QoL experienced by cancer patients. The findings reveal an association between climatic conditions and patients’ health, with higher temperatures, increased sunshine duration, and summer month correlating with higher QoL scores and lower scores in symptom burden. Furthermore, improvement in QoL was demonstrated by patients staying in a palliative unit, regardless of whether they were accompanied by a specialised outpatient PC team prior to admission. Dental care also contributed to enhanced QoL among PC patients. The feasibility study for electronic PRO assessment demonstrated the potential to implement electronic PROs effectively in inpatient care, suggesting their potential to enhance clinical practice.
Die chronische Herzinsuffizienz (CHF) stellt eine der häufigsten Ursachen für Mortalität und Morbidität in Deutschland dar und führt mit Gesundheitskosten von knapp 7,5 Milliarden Euro pro Jahr zu einem wachsenden sozio-ökonomischen Problem. Dabei wird die CHF mit einer medikamentösen Standardtherapie nach Leitlinien der ESC behandelt, mit dem Ziel den Progress zu verlangsamen. Darüber hinaus werden Lebensstiländerungen empfohlen, wobei insbesondere körperliches Training Gegenstand intensiver Forschung ist. Tiermodell-basierte Studien konnten hierdurch eine signifikante Verbesserung der kardialen Funktion bei CHF hervorrufen. In diesen Zusammenhang wird auch der Brain-Derived Neurotrophic Factor (BDNF) gebracht: das Neurotrophin wird bei körperlicher Aktivität u.a. durch Neuronen der Skelettmuskulatur ausgeschüttet, aber auch kardial exprimiert. Es konnte nachgewiesen werden, dass ein niedriger BDNF-Serumspiegel bei CHF Patient:innen mit einer schlechteren Prognose assoziiert ist. Im Rahmen der vorliegenden Arbeit wurde deshalb untersucht, wie sich körperliches Training und die Applikation von BDNF auf kardiale Parameter und auf molekulare Mechanismen bei CHF auswirken. Als Herzinsuffizienzmodell wurden αMHC-Gαq-Mäuse genutzt. Im Alter von 5 Wochen wurde die kardiale Funktion mittels Echokardiographie evaluiert (Baseline-Untersuchung) und über 7 Wochen wöchentlich verlaufskontrolliert. Entsprechend der Gruppenzugehörigkeit erhielten die Tiere über den Versuchszeitraum entweder ein Laufrad zur freiwilligen körperlichen Aktivität oder eine wöchentliche intraperitoneale BDNF-Injektion oder eine Kombination beider Interventionen. Als Kontrolle dienten unbehandelte αMHC-Gαq-Mäuse. Nach 7 Wochen wurde den Mäusen Blut, das Herz sowie Skelettmuskulatur entnommen. Mittels ELISA, Nanostring®, einer Proteom-Analyse und Western-Blot wurden Herzinsuffizienzmarker im Serum, Expressionsänderungen im linksventrikulären Myokard, Unterschiede im kardialen Proteom und in der mitochondrialen Proteinexpression der Skelettmuskeln untersucht.
Unter dem Einfluss von körperlichem Training konnte echokardiographisch eine signifikant verschlechterte systolische sowie diastolische Funktion im Vergleich zur unbehandelten transgenen Kontrollgruppe festgestellt werden. Dies ging einher mit einer kardialen Expressionssteigerung von Remodeling-, Hypertrophie und Apoptose-assoziierten Gene. Im kardialen Proteom konnte darüber hinaus trotz körperlichem Training keine Änderung in der Abundanz von Proteinen der mitochondrialen Funktion festgestellt werden. Hinsichtlich des Energiemetabolismus zeigten sich hingegen Proteine der Glykolyse und der Fettsäureoxidation in ihrer Abundanz erhöht. Durch die Applikation von BDNF zusätzlich zu körperlichem Training zeigten sich die oben beschriebenen Effekte weniger stark ausgeprägt. Die alleinige Applikation von BDNF hingegen konnte keine signifikanten Veränderungen im Vergleich zur transgenen Kontrollgruppe hervorrufen.
Zusammenfassend lässt sich somit ein negativer Effekt von körperlichem Training auf den Krankheitsverlauf herzinsuffizienter αMHC-Gαq-Mäuse feststellen. Durch die Applikation von BDNF zusätzlich zu körperlichem Training konnten die negativen Effekte in αMHC-Gαq-Mäuse abgeschwächt werden, sodass BDNF hier möglicherweise kardioprotektive Mechanismen fördert. Über welchen Mechanismus körperliches Training zu einem Progress der Herzinsuffizienz in αMHC-Gαq-Mäuse beiträgt und inwieweit BDNF in diesen regulatorisch eingreift, muss mittels weiterer Untersuchungen geklärt werden.
Die ureterorenoskopische Harnsteintherapie stellt heutzutage in der Urologie ein etabliertes Verfahren dar. Angesichts einer steigenden Inzidenz und Prävalenz sind die neuesten Erkenntnisse über Therapiemöglichkeiten der Harnsteine sicherlich relevant.
Gegenstand der vorliegenden Untersuchung waren die epidemiologischen Aspekte, das prä-, peri- und postoperative Management sowie das postoperative Outcome der ureterorenoskopisch behandelten Steinpatienten in der Klinik und Poliklinik für Urologie des Universitätsklinikums Greifswald im Zeitraum von Januar 2010 bis einschließlich März 2015. Die Untersuchungsergebnisse wurden mit bereits veröffentlichten Studien verglichen, diskutiert und gewertet.
Von 574 Patienten waren 379 männlich (66,0%) und 195 weiblich (34,0%). Das durchschnittliche Patientenalter betrug 55,6 Jahre. Die Mehrheit der Harnsteine trat in der Altersgruppe der 51 bis 60-jährigen Patienten auf (23,3%). Der mittlere BMI lag bei 28,3 kg/m2. Die Mehrheit der Patienten war übergewichtig (39,3%). Im distalen Ureter waren die meisten Harnsteine lokalisiert (26,0%). Die durchschnittliche Harnsteingröße betrug 7,4 mm. Die mittlere stationäre Aufenthaltsdauer lag bei 2,5 Tagen. 72,3% aller Patienten hatten keine Voroperationen. Von den Voroperationen war die ESWL die häufigste Voroperation (15,7%). 558 Patienten (97,2%) bekamen präoperativ einen Stent eingelegt. Als präoperative Bildgebung wurde eine NLA (70,4%), gefolgt von der CT (29,1%) und der intravenösen Pyelographie (0,5%) durchgeführt. Die Kombination aus einem flexiblen und einem starren Ureterorenoskop wurde am häufigsten verwendet (39,9%). Die starren Ureterorenoskope wurden bei 35,0% der Patienten eingesetzt, die flexiblen Ureterorenoskope bei 25,1%. Die Harnsteine wurden mithilfe von Steinfangkörbchen (55,9%), der Kombination aus Ho:YAG-Laser und Steinfangkörbchen (20,9%) und der Steinfasszange (11,2%) therapiert. Die Steinfreiheitsrate betrug nach dem ersten ureterorenoskopischen Eingriff 90,5%. Bei Steinen, die mit einem flexiblen Ureterorenoskop therapiert worden sind, lag die Steinfreiheitsrate bei 84,0%; diejenigen, die ausschließlich mit einem starren Ureterorenoskop therapiert worden sind, bei 94,0%. 82,7% der Patienten hatten keine Komplikationen. Die Antibiotika Ampicillin/Sulbactam und Ciprofloxacin wurden prä-, peri- und postoperativ am häufigsten gegeben. Von 172 Patienten, die weder präoperativ, perioperativ noch postoperativ ein Antibiotikum erhielten, traten bei 166 dieser Patienten keine Komplikationen auf. Bei 88,5% der Patienten war kein Folgeeingriff notwendig.
Zusammenfassend lässt sich feststellen, dass die Ureterorenoskopie im Rahmen der Harnsteintherapie in der Klinik und Poliklinik für Urologie des Universitätsklinikums Greifswald eine komplikationsarme und effektive Methode zur Therapie von Harnsteinen im gesamten oberen Harntrakt ist. In wesentlichen Punkten stimmten die Ergebnisse dieser Untersuchung mit den Ergebnissen von internationalen Studien überein.
The human visual system is able to estimate distances, perceive fine details of a scene, and distinguish the reflectance of objects, even under varying illumination conditions. In contrast, machines vision systems face significant challenges in performing such tasks due to the complexity and ambiguity of scene interpretation. One way to enable artificial systems to perform these tasks is to utilize a computational approach called intrinsic image decomposition. This approach allows us to decompose an image into its low-level features such as reflectance, shading, illumination, surface normals, and depth. These intrinsics can improve the efficiency of tasks such as object classification, exposure correction, image segmentation, and object recoloring.
While intrinsic image decomposition offers several benefits, it also holds many challenges. The main challenge emerges from the nature of the problem itself. Intrinsic image decomposition is a severely under-constrained problem as it typically involves extracting low-level features from a single input image. This input image might be an RGB image or another intrinsic representation, from which further low-level features are computed. Another challenge in the field is the shortcomings of evaluation benchmarks. Existing datasets have limitations such as limited samples and/or intrinsics, and including simple scenes. A further challenge is the lack of error metrics demonstrating the actual performance of algorithms. The existing evaluation strategies in this field have shortcomings such as a bias toward favoring cases where large regions are decomposed correctly.
This thesis focuses on the challenges in intrinsic image decomposition by offering simple yet effective solutions and introducing new perspectives. Specifically, two datasets are created using computer graphics, ensuring accurate ground truth data while avoiding subjectivity and eliminating biases caused by camera specifications. The first dataset, namely IID-NORD, is a large-scale dataset including scenes and their ground truth reflectance, shading, surface normal vectors, depth map, and light direction vectors. The second dataset is called CC-NORD which addresses the illumination intrinsic image of the scenes. Furthermore, two error metrics, inspired by observations on the human visual system, are proposed for evaluating the reflectance and shading components. These metrics rely on operations in scale-space, and on the structural similarity index (SSIM), visual information fidelity (VIF), the feature similarity index (FSIM), and the $\Delta E$ (CIEDE$2000$) which are well-known evaluation methods in the field of image processing. Additionally, a learning-free algorithm utilizing scale-space computations is developed to calculate the surface normals from depth maps. Also, a traditional algorithm relying on the Retinex theory, scale-space operations, and superpixel segmentation is designed to estimate the reflectance and shading from input scenes. According to the experimental results both algorithms show competitive performance.
Plants live is challenging. Live in the temperate zone requires high investment in adaptation to changing climatic conditions over the course of the year. Perennial plants enter a state of dormancy to survive the unfavourable time in winter. Dormancy also prevents them from leaving out to early. Research on plants dormancy and how its induction and release is impacted by environmental conditions has become relevant because in the recent decades, spring phenology has advanced substantially due to climate warming, which can have significant effects on the ecosystems.
The advancement of spring leaf-out is slowing down despite further warming, which demonstrates the complexity of temperatures effects on dormancy and phenology. This thesis aims to contribute to our understanding on the mechanism that enables the plants to synchronise with the meteorological seasons. I ask, in which way does winter warming impact or maybe even disturb this mechanism and what does it mean to the plants? Why is the advancement of spring phenology declining? How will the phenology be altered in an extreme warming scenario?
In a series of warming experiments with seedlings of European tree species I investigated, how temperature increase at different times of the year affects bud dormancy development and phenology. I tracked bud dormancy by quantifying dormancy depth and percentage of budburst from late summer to spring leaf-out. In addition, in an international collaboration, colleagues and I analysed how phenological states and characteristics of dormancy are related to each other across different tree species.
I found out that autumn temperature is of crucial importance, as it affects the timing of dormancy induction, which has a strong impact on the timing of next year’s spring leaf-out. Warm autumn temperatures delay leaf senescence and dormancy induction. This delay persists throughout the winter and the buds delay the timing of becoming sensitive to warm temperatures in spring, which is the reason for the decline in spring advancement. At the same time spring, spring temperature rise starts earlier, ultimately leading to increased accumulation of forcing temperatures prior to leaf unfolding. Thus, although spring phenology has substantially advanced over the last decades according to calendar dates, trees actually leaf-out later in relation to spring temperature rise. The temperature in actual winter has no significant effect on dormancy within the investigated range. In fact, from January onwards, winter warming has rather an advancing effect on leaf unfolding, which increases towards spring flushing.
Spring advancement is likely to continue under further climate warming, but its rate is likely to decline further. This means that will trees leaf-out in spring at a time when more warmth has already accumulated than in the past. This might be disadvantageous, as the trees will not be able to take full advantage of the season with optimal growing conditions, in particular in the face of increasing summer drought. It seems worth investigating whether provenances from warmer climate with lower chilling requirements might be better adapted to the climate of the future.
Obwohl die Aufnahme von Wirkstoffen aus dem Darm ein hochvariabler Prozess mit vielen Einflussfaktoren ist, ist die orale Arzneimittelgabe die bevorzugte Applikationsroute für Medikamente. Intestinale Metabolisierungsenzyme und Transportproteine stellen Faktoren dar, die die Absorption deutlich beeinflussen können. Obwohl bereits viel über ihre Funktion, Regulation und Lage im Darm bekannt ist, fehlen Daten über die interindividuelle Expression. Ziel dieser Arbeit war, diese im Hinblick auf die demographischen Faktoren biologisches Geschlecht, Alter und das Vorliegen der Volkskrankheit Diabetes mellitus Typ 2 hin zu charakterisieren und gegebenenfalls Schlüsse auf Implikationen für die Arzneimitteltherapie zu ziehen.
Dafür wurde intraoperativ gewonnenes kryokonserviertes Jejunumgewebe verwendet und Vergleichsgruppen (Geschlecht, Alter, Typ-2-Diabetiker) anhand der zugehörigen Datenbank gebildet. Die Expression relevanter Arzneimitteltransporter und Metabolisierungsenzyme wurde auf mRNA-Ebene bestimmt, die Expression ausgewählter Arzneimitteltransporter auch auf Protein-Ebene. Der relative mRNA-Gehalt wurde mittels reverser Transkription und quantitativer PCR bestimmt. Für die Protein-Messung wurde das gesamte Gewebeprotein filterbasiert extrahiert, mittels Trypsin gespalten und anschließend die erhaltenen transporterspezifischen Peptide mittels Flüssigchromatographie und Massenspektrometrie nach etablierter Methode quantifiziert (targeted proteomics). Die Ergebnisse bewegen sich in der Größenordnung anderer Arbeiten ähnlicher Methodik. mRNA und Protein korrelierten, wie in der Literatur beschrieben, kaum. Obwohl die Untersuchung bei relativ kleiner Probenzahl der Vergleichsgruppen underpowered ist, fanden sich einige signifikante Ergebnisse zwischen den Geschlechtern sowie den Typ-2-Diabetikern und der Kontrollgruppe. Hervorzuheben ist die deutlich niedrigere mRNA-Expression des Metformin-Transporters SLC29A4 bei Diabetikern. Auf Proteinebene zeigten Typ-2-Diabetiker eine ca. 20% niedrigere Expression von PEPT1 als Nicht-Diabetiker. Frauen exprimierten P-gp ca. 20% höher.
In der im Rahmen dieser Arbeit durchgeführten Untersuchung zeigte sich kein signifikanter Einfluss des Alters und lediglich ein limitierter Einfluss der Faktoren Geschlecht und Typ-2-Diabetes auf das Expressionsprofil der untersuchten Arzneimitteltransporter und -enzyme, vor allem auf Protein-Ebene. Eine pharmakokinetische Relevanz dieser Faktoren durch Beeinflussung der Expression von Transportproteinen und Metabolisierungsenzymen für die orale Arzneimitteltherapie bleibt somit fraglich.
Earlier studies regarded mainly membrane cholesterol as the cellular receptor for cholesterol dependent cytolysins (CDCs) like pneumolysin but growing evidence suggests a crucial role for glycans as possible receptors or mediators. However, their precise role remains unclear. This doctoral thesis aimed to examine the interactions of pneumolysin from S. pneumoniae with human platelets. Especially the role of the two neuraminidases NanH from C. perfringens and NanA from S. pneumoniae in the toxin’s pathogenesis was investigated. Moreover, the inhibitory effects of intravenous immunoglobulin (IVIG) and the neuraminidase inhibitor Oseltamivir Carboxylate (OC) on NanA were studied. My findings demonstrated that treatment with NanA (S. pneumoniae) or NanH (C. perfringens) leads to desialylation of platelet glycoproteins. This concentration dependent increase in desialylation enhances the binding of pneumolysin to platelets as well as the toxin’s effects – namely pore formation and lysis. NanA and NanH also enhance the binding of pneumolysin in low concentrations, while NanA is further able to enhance the destructive effects of such low concentrations. On the one hand, IVIG is able to inhibit NanA dependent desialylation of platelet glycoproteins and hence, the toxin’s pore forming effects. On the other hand, OC is able to partially inhibit NanA. Desialylation of platelet glycoproteins is inhibited by OC but apparently not sufficiently. As a result, the destructive effects of pneumolysin are unhindered. Very little information is known about the cellular receptor for pneumolysin. My findings thus shed a light on this topic, but further in vivo research with different S. pneumoniae strains is necessary. Moreover, the role of other exoglycosidases like β-galactosidase A in the pathogenesis of pneumolysin should be investigated in the future.
The Explainable Modular Neural Network (XModNN) enables the identification of biomarkers, facilitating the classification of diseases and clinical parameters in transcriptomic datasets. The modules within XModNN represent specific pathways or genes of a functional hierarchy. The incorporation of biological insights into the architectural design reduced the number of parameters. This is further reinforced by the weighted multi-loss progressive training, which enables successful classification with a reduced number of replicates. The combination of this workflow with layer-wise relevance propagation ensures a robust post hoc explanation of the individual module contribution. Two use cases were employed to predict sex and neuroblastoma cell states, demonstrating that XModNN, in contrast to standard statistical approaches, results in a reduced number of candidate biomarkers. Moreover, the architecture enables the training on a limited number of examples, attaining the same performance and robustness as support vector machine and random forests. The integrated pathway relevance analysis improves a standard gene set overrepresentation analysis, which relies solely on gene assignment. Two crucial genes and three pathways were identified for sex classification, while 26 genes and six pathways are highly important to discriminate adrenergic–mesenchymal cell states in neuroblastoma cancer.