570 Biowissenschaften; Biologie
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Interaction between species in a marine ecosy stem is described by expressions for food consumption and grazing mortality which are consistent with each other and with the Beverlon and Holt model of the population dynamics ofindividual species. A model of primary production is introduced in order to make possible an account of nutricnt circlliation (as examplified by phosphorus) within and nutrient flow through the system. It is demonstrated in an application to North Sea fishencs that recent changes in total yield can be described in some detail under the terms of the model as a function of fishing mortality alone. The composition of the North Sea fauna in the virgin state is discussed and also the conditions under which total yield could be increased above the 1970 level.
A multiple filter test for the detection of rate changes in renewal processes with varying variance
(2014)
The thesis provides novel procedures in the statistical field of change point detection in time series.
Motivated by a variety of neuronal spike train patterns, a broad stochastic point process model is introduced. This model features points in time (change points), where the associated event rate changes. For purposes of change point detection, filtered derivative processes (MOSUM) are studied. Functional limit theorems for the filtered derivative processes are derived. These results are used to support novel procedures for change point detection; in particular, multiple filters (bandwidths) are applied simultaneously in oder to detect change points in different time scales.
Variants resistant to compounds specifically targeting HCV are observed in clinical trials. A multi-variant viral dynamic model was developed to quantify the evolution and in vivo fitness of variants in subjects dosed with monotherapy of an HCV protease inhibitor, telaprevir. Variant fitness was estimated using a model in which variants were selected by competition for shared limited replication space. Fitness was represented in the absence of telaprevir by different variant production rate constants and in the presence of telaprevir by additional antiviral blockage by telaprevir. Model parameters, including rate constants for viral production, clearance, and effective telaprevir concentration, were estimated from 1) plasma HCV RNA levels of subjects before, during, and after dosing, 2) post-dosing prevalence of plasma variants from subjects, and 3) sensitivity of variants to telaprevir in the HCV replicon. The model provided a good fit to plasma HCV RNA levels observed both during and after telaprevir dosing, as well as to variant prevalence observed after telaprevir dosing. After an initial sharp decline in HCV RNA levels during dosing with telaprevir, HCV RNA levels increased in some subjects. The model predicted this increase to be caused by pre-existing variants with sufficient fitness to expand once available replication space increased due to rapid clearance of wild-type (WT) virus. The average replicative fitness estimates in the absence of telaprevir ranged from 1% to 68% of WT fitness. Compared to the relative fitness method, the in vivo estimates from the viral dynamic model corresponded more closely to in vitro replicon data, as well as to qualitative behaviors observed in both on-dosing and long-term post-dosing clinical data. The modeling fitness estimates were robust in sensitivity analyses in which the restoration dynamics of replication space and assumptions of HCV mutation rates were varied.
The calcareous substrate of spring-fed fens makes them unique islands of biodiversity, hosting endangered, vulnerable, and protected vascular plants. Hence, spring-fed fens ecosystems require special conservation attention because many of them are destroyed (e.g. drained, forested) and it is extremely difficult or even impossible to restore the unique hydrogeological and geochemical conditions enabling their function. The long-term perspective of paleoecological studies allows indication of former wetland ecosystem states and provides understanding of their development over millennia. To examine the late Holocene dynamics of a calcareous spring-fed fen (Raganu Mire) ecosystem on the Baltic Sea coast (Latvia) in relation to environmental changes, substrate and human activity, we have undertaken high-resolution analyses of plant macrofossils, pollen, mollusc, stable carbon (δ13C) and oxygen (δ18O) isotopes combined with radiocarbon dating (AMS) in three coring locations. Our study revealed that peat deposits began accumulating ca. 7000 cal. yr BP and calcareous deposits (tufa) from 1450 cal. yr BP, coinciding with regional hydrological changes. Several fire events occurred between 4000 and 1600 cal. yr BP, which appeared to have had a limited effect on local vegetation. The most significant changes in the forest and peatland ecosystems were at 3200 cal. yr BP associated with a dry climate stage and high fire activity, and then between 1400 and 500 cal. yr BP potentially associated with temperature changes during the Medieval Climate Anomaly (MCA) and Little Ice Age. Hydrological disturbances in the peatland catchment from 1400 cal. yr BP were most likely strengthened by human activity (deforestation) in this region. The relationship between the development of this peatland and changes in its catchment area, such as land cover changes or fluctuations in groundwater levels, suggest that protection and restoration of spring-fed fen ecosystems should also include the surrounding catchment. The presence of calcareous sediments, as well as appropriate temperature and local hydrological conditions appear to be the most crucial factors controlling Cladium marisus populations in our site - currently at the eastern limit of its distribution in Europe.
Peer review of research articles is a core part of our scholarly communication system. In spite of its importance, the status and purpose of peer review is often contested. What is its role in our modern digital research and communications infrastructure? Does it perform to the high standards with which it is generally regarded? Studies of peer review have shown that it is prone to bias and abuse in numerous dimensions, frequently unreliable, and can fail to detect even fraudulent research. With the advent of Web technologies, we are now witnessing a phase of innovation and experimentation in our approaches to peer review. These developments prompted us to examine emerging models of peer review from a range of disciplines and venues, and to ask how they might address some of the issues with our current systems of peer review. We examine the functionality of a range of social Web platforms, and compare these with the traits underlying a viable peer review system: quality control, quantified performance metrics as engagement incentives, and certification and reputation. Ideally, any new systems will demonstrate that they out-perform current models while avoiding as many of the biases of existing systems as possible. We conclude that there is considerable scope for new peer review initiatives to be developed, each with their own potential issues and advantages. We also propose a novel hybrid platform model that, at least partially, resolves many of the technical and social issues associated with peer review, and can potentially disrupt the entire scholarly communication system. Success for any such development relies on reaching a critical threshold of research community engagement with both the process and the platform, and therefore cannot be achieved without a significant change of incentives in research environments.
DEAD-box proteins are enzymes endowed with nucleic acid-dependent ATPase, RNA translocase and unwinding activities. The human DEAD-box protein DDX3 has been shown to play important roles in tumor proliferation and viral infections. In particular, DDX3 has been identified as an essential cofactor for HIV-1 replication. Here we characterized a set of DDX3 mutants biochemically with respect to nucleic acid binding, ATPase and helicase activity. In particular, we addressed the functional role of a unique insertion between motifs I and Ia of DDX3 and provide evidence for its implication in nucleic acid binding and HIV-1 replication. We show that human DDX3 lacking this domain binds HIV-1 RNA with lower affinity. Furthermore, a specific peptide ligand for this insertion selected by phage display interferes with HIV-1 replication after transduction into HelaP4 cells. Besides broadening our understanding of the structure-function relationships of this important protein, our results identify a specific domain of DDX3 which may be suited as target for antiviral drugs designed to inhibit cellular cofactors for HIV-1 replication.
How the brain evolved remains a mystery. The goal of this thesis is to understand the fundamental processes that are behind the evolutionary history of the brain. Amniotes appeared 320 million years ago with the transition from water to land. This early group bifurcated into sauropsids (reptiles and birds) and synapsids (mammals). Amniote brains evolved separately and display obvious structural and functional differences. Although those differences reflect brain diversification, all amniote brains share a common ancestor and their brains show multiple derived similarities: equivalent structures, networks, circuits and cell types have been preserved during millions of years. Finding these differences and similarities will help us understand brain historical evolution and function. Studying brain evolution can be approached from various levels, including brain structure, circuits, cell types, and genes. We propose a focus on cell types for a more comprehensive understanding of brain evolution. Neurons are the basic building blocks and the most diverse cell types in the brain. Their evolution reflects changes in the developmental processes that produce them, which in turn may shape the neural circuits they belong to. However, there is currently a lack of a unified criteria for studying the homology of connectivity and development between neurons. A neuron’s transcriptome is a molecular representation of its identity, connectivity, and developmental/evolutionary history. Hence the comparison of neuronal transcriptomes within and across species is a new and transformative development in the study of brain evolution. As an alternative, comparing neuronal transcriptomes across different species can provide insights into the evolution of the brain. We propose that comparing transcriptomes can be a way to fill this gap and unify these criteria. In previous studies, published in Science (Tosches et al., 2018) and Nature (Norimoto et al., 2020), we leveraged scRNAseq in reptiles to re-evaluate the origins and evolution of the mammalian cerebral cortex and claustrum. Motivated by the success of this approach, in this thesis we have now expanded single-cell profiling to the entire brain of a lizard species, the Australian dragon Pogona vitticeps, with a special focus in thalamus and prethalamus of. This approach allowed us to study the evolution of neuron types in amniotes. Therefore, we aimed to build a multilevel atlas of the lizard brain based on histology and transcriptomic and compare it to an equal mouse dataset (Zeisel et al., 2018).
Our atlas reveals a general structure that is consistent with that for other amniote brains, allowing us to make a direct comparison between lizard and mouse, despite their evolutionary divergence 320 million years ago. Through our analysis of the transcriptomes present in various neuron types, we have uncovered a core of conserved classes and discovered a fascinating dichotomy of new and conserved neuron types throughout the brain. This research challenges the traditional notion that certain brain regions are more conserved than others.
Our research also has uncovered the evolutionary history of the lizard thalamus and prethalamus by comparing them to homologous brain regions of the mouse. This pioneering research sheds new light on our understanding of the evolutionary history of the lizard brain. We propose a new classification of the lizard thalamic nuclei based on
transcriptomics. Our research revealed that the thalamic neuron types in lizards can be grouped into two large, conserved categories from the medial to lateral thalamus. These categories are encoded by a common set of effector genes, linking theories based on connectivity and molecular studies of these areas. In our data we have seen that there is a conservation of the medial-lateral transcriptomic axis in mouse and lizard, this conservation was most likely already present in the common ancestor. Although there is a shared medial-lateral axis, a deeper study of the thalamic cell types has allowed us to see the existence of a partial diversification of the thalamic population, specifically in the sensory-related lateral thalamus; in opposition, the medial thalamic nuclei neuron-types have been preserved.
On the other hand, the comparison with the mammalian prethalamus allowed us to confirm that the lizard ventromedial thalamic neuron types are homologous to mouse reticular thalamic neuron types (Díaz et al., 1994), even if they do not express the classical Reticular thalamic nucleus (RTn) marker PV/pvalb. We also discovered that there has been a simplification in the mammalian prethalamic neuron types in favor of an increase in the number of Interneurons (IN) types within their thalamus. We suggest that the loss of GABAergic neuronal types in the mammalian prethalamus is linked to the need for a more efficient control of the thalamo-pallial communication in mammals, while in lizards, where thalamo-pallial communication is probably simpler, the diversity prethalamus presents a higher diversity.
The ability to learn sequential behaviors is a fundamental property of our brains. Yet a long stream of studies including recent experiments investigating motor sequence learning in adult human subjects have produced a number of puzzling and seemingly contradictory results. In particular, when subjects have to learn multiple action sequences, learning is sometimes impaired by proactive and retroactive interference effects. In other situations, however, learning is accelerated as reflected in facilitation and transfer effects. At present it is unclear what the underlying neural mechanism are that give rise to these diverse findings. Here we show that a recently developed recurrent neural network model readily reproduces this diverse set of findings. The self-organizing recurrent neural network (SORN) model is a network of recurrently connected threshold units that combines a simplified form of spike-timing dependent plasticity (STDP) with homeostatic plasticity mechanisms ensuring network stability, namely intrinsic plasticity (IP) and synaptic normalization (SN). When trained on sequence learning tasks modeled after recent experiments we find that it reproduces the full range of interference, facilitation, and transfer effects. We show how these effects are rooted in the network’s changing internal representation of the different sequences across learning and how they depend on an interaction of training schedule and task similarity. Furthermore, since learning in the model is based on fundamental neuronal plasticity mechanisms, the model reveals how these plasticity mechanisms are ultimately responsible for the network’s sequence learning abilities. In particular, we find that all three plasticity mechanisms are essential for the network to learn effective internal models of the different training sequences. This ability to form effective internal models is also the basis for the observed interference and facilitation effects. This suggests that STDP, IP, and SN may be the driving forces behind our ability to learn complex action sequences.