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Neuste Veröffentlichungen:

Silver-bismuth double perovskite semiconductors: variations on a theme
(2024) Schmitz, Fabian; Gatti, Teresa; Schlettwein, Derck
Lead-halide perovskites (LHPs) have experienced tremendous development within 15 years from their first report as light harvesters in solar cells until today, in which their power conversion efficiency has been gradually improved from 3.8% to 26.1%. These high efficiencies in combination with their easy and low-cost processability as thin films make them a potential alternative to conventional silicon-based solar cells. However, compared to the latter they possess a low environmental stability and pose an environmental and human health hazard due to their lead content. While the stability has been gradually improved by extensive chemical engineering and encapsulating techniques, the toxicity aspect can only be tackled by substituting lead. Cs2AgBiBr6 is such a material – which this dissertation revolves around - in which lead is substituted by equal amounts of silver and bismuth, thus named double perovskite, which is characterized by high environmental stability and low toxicity. This dissertation can be divided into two main topics: The tuning of absorption and emissive processes in Ag-Bi double perovskites via structural engineering and the investigation and improvement of hole transport material (HTM)-free Cs2AgBiBr6 solar cells. The first topic covers two different approaches to influence the emission of Ag-Bi double perovskites. On the one hand, Cs2AgBiBr6 was doped with the lanthanides Eu3+ and Yb3+, resulting in two new emission features: A weak emission from dopant-introduced trap states (Eu3+) and strong emission due to an efficient energy transfer towards the dopant (Yb3+), respectively. On the other hand, Cs2AgBiBr6 has been dimensionally reduced to create monolayered 2D perovskites which enlarges the material’s bandgap and introduces new characteristic emission. Regarding the second topic, HTM-free Cs2AgBiBr6 solar cells have been prepared using ultrasonic spray-coating to deposit electrodes that consist of carbon black, won from upcycled industry waste. Thus, this approach represents an end-of-waste strategy to fabricate “green” solar cells. To further improve these devices, the surface of the Cs2AgBiBr6 thin films has been modified to create 2D/3D mixed phases. The 2D/3D modification improves the perovskite’s band alignment towards the back electrode and theoretical calculations further suggest that it reduces the defect concentration close to the perovskite/electrode interface. Accordingly, the application of the 2D/3D modification represents a valuable alternative to HTMs for Cs2AgBiBr6 solar cells that utilize carbon-based electrodes.
Embryonale Stammzellen als Modellsystem für Infektion und Entzündung
(2024) Scharmacher, Jennifer; Sauer, Heinrich
In dieser Arbeit wurde der Einfluss von LPS auf inflammatorische Prozesse in Geweben aus ES der Maus untersucht. LPS sorgt innerhalb der EBs für eine signifikante Zunahme der Schlagfrequenz, ohne dabei die muskuläre Struktur der Kardiomyozyten zu verändern. Es konnte gezeigt werden, dass durch Inkubation mit LPS, Parameter wie ROS und NO in den EBs hochreguliert wurden. Anhand des NADPH-Oxidase Inhibitors Vas 2870 und Western-Blot Analyse konnte nachgewiesen werden, dass die ROS Quelle hauptsächlich die NOX 2 Isoform der NADPH-Oxidase ist. NOX 1 und NOX 4 wurden zwar auch verstärkt exprimiert, scheinen aber eine eher untergeordnete Rolle zu spielen. Durch den TLR 4 Inhibitor Tak-242 konnte gezeigt werden, dass NOX 2 in den LPS behandelten EBs signifikant zur Kontrolle herunterreguliert wird. Dies beweist eine Involvierung des TLR 4 Signalwegs in die LPS-induzierten Veränderungen des intrazellulären Redoxmilieus. Es ist bekannt, dass LPS über verschiedene Signalwege auch die NO-Synthasen stimuliert. In den EBs zeigte sich LPS-vermittelt eine erhöhte NO-Produktion. Eine gesteigerte Expression der p-eNOS und eNOS in den EBs wurde via Western-Blot nachgewiesen. Durch die Koinkubation mit Tak-242 wurde die NO-Generierung in den EBs nahezu gänzlich inhibiert. Weiterhin wurden durch die Koinkubation mit LPS, Makrophagen und andere aktivierte Immunzellen signifikant stärker differenziert. Es konnte zudem eine gesteigerte Expression des NLRP 3-Inflammasoms gezeigt werden, jedoch wurde hier kein signifikanter Unterschied zwischen kardialen und nicht kardialen Bereichen der EBs gefunden. Weiterhin kam es zu einer signifikant höheren Expression des proinflammatorischen Zytokins IL 1β. Tak-242 inhibierte die IL 1β-Expression in den LPS behandelten EBs, außerdem die LPS-induzierte Kontraktionsfrequenz der kardialen Zellen. Dies beweist die Involvierung des TLR 4 Signalwegs in die beobachteten inflammatorischen Vorgänge in EBs und die Veränderungen der Kardiomyozytenfunktion.
Computational models of rodent hippocampal nerve cells focusing on their morphology, excitability and function
(2023) Mittag, Martin; Heiliger, Christian; Jedlička, Peter
The nerve cells in the mammalian brain come in various shapes and sizes. They constitute a complex system emerging from a complicated interplay of biophysical principles. Functionally, they can be compared to a computing unit transferring input into useful output, leading ultimately to cognitive functions or behaviour. This processing of information is called the input-output (IO) function of a neuron. The focus of this dissertation is on the particular IO function of hippocampal neurons, their underlying structure (morphology) and their intrinsic mechanisms (ion channels). In order to study these nerve cells, computational models offer the advantage of disentangling the involved biophysical mechanisms and their functional effects in a controlled manner. Therefore, I implement biologically realistic computational models of hippocampal neurons to simulate their IO function in several major, complementary \textit{in silico} investigations.Initially, using detailed neuron models that include active ion channels and other dendritic non-linearities, I demonstrate that the neural IO function can be invariant even when the stimulated dendrites of the nerve cells show vastly different morphological structures and sizes. These results reveal a general principle called accordingly "dendritic constancy". Notably, the dendritic constancy principle can have important clinical implications for neurological diseases. For example, it has been suggested that morphological alterations lead to the concurrent increase in excitability of principal hippocampal nerve cells during Alzheimer’s disease (AD). However, in line with the dendritic constancy principle, I show that the dendritic remodeling in AD cells is likely a homeostatic mechanism to maintain the cell IO function and information flow. The simulations instead reveal, that other intrinsic (ion channels) and extrinsic mechanism modifications lead to the excitability increase observed in AD cells in a multi-causal manner. Finally, various expressions of underlying ion channels cannot only affect the altered, pathological behaviour but potentially result in an optimised IO function and information processing. For instance, hippocampal granule cells (GCs) are believed to convert similar inputs into dissimilar outputs (pattern separation) while using as little energy as possible. The findings in this thesis reveal that the experimentally validated GC model seems to be close to optimal among a population of random, but valid, GC models with different ion channel expressions for the simultaneous performance of pattern separation and economy. In summary, by applying computational models in this dissertation I uncover a relationship between the underlying structure and ion channels of various nerve cells and their IO function.
Maximizing information content of SNP arrays for genomic prediction
(2023) Weber, Sven Ernst; Snowdon, Rod; Frisch, Mathias
Genomic prediction is a promising tool for improving genetic gains in various crops, serving as a valuable tool for plant breeders. SNP arrays are the preferred genotyping tool for breeders of most major crops, however the limited predefined marker number associated with SNP arrays has the potential to impede achievable prediction accuracy in genomic prediction. The objective of this study was to evaluate cost-effective methods for maximizing the information content of SNP arrays. Three methods were explored and their information content was assessed using prediction accuracies from six genomic prediction models across diverse crops and agronomic traits. Independently of the method used to increase the information content of SNP arrays, the applied genomic prediction models consistently demonstrated similar performance in terms of prediction accuracy within traits, making them equally suitable for genomic prediction across a variety of crops and traits. The first method to maximize the information content of SNP arrays involved constructing haplotype blocks with various methods and parameters and utilizing their haplotypes for genomic prediction. Analyzing data from rapeseed, maize, wheat and soybean in genomic prediction models revealed only marginal improvements in genomic prediction accuracy across most traits. Notably, haplotype blocks demonstrated effectiveness in compensating for poorly performing models in scenarios with highly variable prediction accuracies across prediction models. Nevertheless, the absence of a consistent ideal method or parameter for constructing haplotype blocks makes them a hyperparameter requiring careful tuning. Furthermore, failed allele calls from SNP arrays were examined for their information content in genomic prediction of agronomic traits in maize and rapeseed. Two statistical pipelines were developed and tested to filter non-random failed allele calls from random technical errors. Surprisingly, failed allele calls, potentially originating from genome structural variants, exhibited prediction accuracies comparable to genome-wide SNP datasets. However, the combination of SNPs and failed allele calls did not enhance genomic prediction. As an alternative to whole-genome sequencing marker data, imputation of whole-genome sequencing marker data from SNP arrays was explored. While there was a considerable improvement in LD and marker density, no increase in prediction accuracy was observed. This can likely be attributed to erroneous haplotypes and marker calls resulting from imputation errors. A suitable hypothesis to explain this observation is that these errors are introduced by the high complexity and redundancy of crop plant genomes. Across all three methods, relationships emerged as an explanation for the lack of improvement in genomic prediction accuracy. Relationship estimates exhibited a high correlation between those obtained from SNP array data and methods to increase the information content of SNP arrays, contributing predominantly redundant information. Moreover, it can be assumed that markers on arrays generally exhibit sufficient LD with adjacent QTL. In conclusion, SNP arrays were proven to be a reliable genotyping technology, offering a representative sample of the genome for estimating relationships. Furthermore, this study reaffirms the potential of genomic prediction as a breeding tool to improve genetic gain in several crops.