7,534 research outputs found

    UMSL Bulletin 2023-2024

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    The 2023-2024 Bulletin and Course Catalog for the University of Missouri St. Louis.https://irl.umsl.edu/bulletin/1088/thumbnail.jp

    An investigation of entorhinal spatial representations in self-localisation behaviours

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    Spatial-modulated cells of the medial entorhinal cortex (MEC) and neighbouring cortices are thought to provide the neural substrate for self-localisation behaviours. These cells include grid cells of the MEC which are thought to compute path integration operations to update self-location estimates. In order to read this grid code, downstream cells are thought to reconstruct a positional estimate as a simple rate-coded representation of space. Here, I show the coding scheme of grid cell and putative readout cells recorded from mice performing a virtual reality (VR) linear location task which engaged mice in both beaconing and path integration behaviours. I found grid cells can encode two unique coding schemes on the linear track, namely a position code which reflects periodic grid fields anchored to salient features of the track and a distance code which reflects periodic grid fields without this anchoring. Grid cells were found to switch between these coding schemes within sessions. When grid cells were encoding position, mice performed better at trials that required path integration but not on trials that required beaconing. This result provides the first mechanistic evidence linking grid cell activity to path integration-dependent behaviour. Putative readout cells were found in the form of ramp cells which fire proportionally as a function of location in defined regions of the linear track. This ramping activity was found to be primarily explained by track position rather than other kinematic variables like speed and acceleration. These representations were found to be maintained across both trial types and outcomes indicating they likely result from recall of the track structure. Together, these results support the functional importance of grid and ramp cells for self-localisation behaviours. Future investigations will look into the coherence between these two neural populations, which may together form a complete neural system for coding and decoding self-location in the brain

    Using machine learning to predict pathogenicity of genomic variants throughout the human genome

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    Geschätzt mehr als 6.000 Erkrankungen werden durch Veränderungen im Genom verursacht. Ursachen gibt es viele: Eine genomische Variante kann die Translation eines Proteins stoppen, die Genregulation stören oder das Spleißen der mRNA in eine andere Isoform begünstigen. All diese Prozesse müssen überprüft werden, um die zum beschriebenen Phänotyp passende Variante zu ermitteln. Eine Automatisierung dieses Prozesses sind Varianteneffektmodelle. Mittels maschinellem Lernen und Annotationen aus verschiedenen Quellen bewerten diese Modelle genomische Varianten hinsichtlich ihrer Pathogenität. Die Entwicklung eines Varianteneffektmodells erfordert eine Reihe von Schritten: Annotation der Trainingsdaten, Auswahl von Features, Training verschiedener Modelle und Selektion eines Modells. Hier präsentiere ich ein allgemeines Workflow dieses Prozesses. Dieses ermöglicht es den Prozess zu konfigurieren, Modellmerkmale zu bearbeiten, und verschiedene Annotationen zu testen. Der Workflow umfasst außerdem die Optimierung von Hyperparametern, Validierung und letztlich die Anwendung des Modells durch genomweites Berechnen von Varianten-Scores. Der Workflow wird in der Entwicklung von Combined Annotation Dependent Depletion (CADD), einem Varianteneffektmodell zur genomweiten Bewertung von SNVs und InDels, verwendet. Durch Etablierung des ersten Varianteneffektmodells für das humane Referenzgenome GRCh38 demonstriere ich die gewonnenen Möglichkeiten Annotationen aufzugreifen und neue Modelle zu trainieren. Außerdem zeige ich, wie Deep-Learning-Scores als Feature in einem CADD-Modell die Vorhersage von RNA-Spleißing verbessern. Außerdem werden Varianteneffektmodelle aufgrund eines neuen, auf Allelhäufigkeit basierten, Trainingsdatensatz entwickelt. Diese Ergebnisse zeigen, dass der entwickelte Workflow eine skalierbare und flexible Möglichkeit ist, um Varianteneffektmodelle zu entwickeln. Alle entstandenen Scores sind unter cadd.gs.washington.edu und cadd.bihealth.org frei verfügbar.More than 6,000 diseases are estimated to be caused by genomic variants. This can happen in many possible ways: a variant may stop the translation of a protein, interfere with gene regulation, or alter splicing of the transcribed mRNA into an unwanted isoform. It is necessary to investigate all of these processes in order to evaluate which variant may be causal for the deleterious phenotype. A great help in this regard are variant effect scores. Implemented as machine learning classifiers, they integrate annotations from different resources to rank genomic variants in terms of pathogenicity. Developing a variant effect score requires multiple steps: annotation of the training data, feature selection, model training, benchmarking, and finally deployment for the model's application. Here, I present a generalized workflow of this process. It makes it simple to configure how information is converted into model features, enabling the rapid exploration of different annotations. The workflow further implements hyperparameter optimization, model validation and ultimately deployment of a selected model via genome-wide scoring of genomic variants. The workflow is applied to train Combined Annotation Dependent Depletion (CADD), a variant effect model that is scoring SNVs and InDels genome-wide. I show that the workflow can be quickly adapted to novel annotations by porting CADD to the genome reference GRCh38. Further, I demonstrate the integration of deep-neural network scores as features into a new CADD model, improving the annotation of RNA splicing events. Finally, I apply the workflow to train multiple variant effect models from training data that is based on variants selected by allele frequency. In conclusion, the developed workflow presents a flexible and scalable method to train variant effect scores. All software and developed scores are freely available from cadd.gs.washington.edu and cadd.bihealth.org

    Energy Supplies in the Countries from the Visegrad Group

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    The purpose of this Special Issue was to collect and present research results and experiences on energy supply in the Visegrad Group countries. This research considers both macroeconomic and microeconomic aspects. It was important to determine how the V4 countries deal with energy management, how they have undergone or are undergoing energy transformation and in what direction they are heading. The articles concerned aspects of the energy balance in the V4 countries compared to the EU, including the production of renewable energy, as well as changes in its individual sectors (transport and food production). The energy efficiency of low-emission vehicles in public transport and goods deliveries are also discussed, as well as the energy efficiency of farms and energy storage facilities and the impact of the energy sector on the quality of the environment

    The Impact of Heterogenous Cell Populations on Impedance-Based Cell Analysis

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    Many in vitro studies for drug development are based on population-averaging measurement techniques without giving information about cell-to-cell variability within the cell ensembles under study. However, such heterogeneities in cell cultures are omnipresent and can arise by several causes, like spontaneous genetic mutations, different metabolic situations or different cell cycle states of individual cells. Moreover, microenvironmental conditions, like cell crowding, might force cell ensembles to form subpopulations with distinct characteristics. Therefore, single phenotypically different subpopulations may be overseen or averaged responses across different subpopulations might not reflect the majority of the cells, leading to misinterpretations of data – one possible reason for the high failure rate in clinical trials. This thesis addressed the fundamental question of how cell-to-cell variability in populations influence the signal of population-based assays by using three different approaches. The first project addressed the impact of evenly distributed heterogeneities within cell populations, introduced by mixing a cell line expressing a certain G protein-coupled receptor (GPCR) with a cell line not expressing this receptor type, on the impedance-based cell analysis. The second project focused on the development of an impedance-based assay for the future purpose of spatiotemporally introducing heterogeneities in an isogenic cell population, expressing a certain GPCR, by switching an appropriate, photochromic ligand by illumination. The third project addressed the quantification of the impact of heterogeneities within cell populations on the impedance-based cell analysis in a theoretical manner. The first project focused on the impact of cell-to-cell variability on the population-based impedance signal by mixing cell lines in different ratios prior to the seeding onto the co-planar gold electrodes. The evenly distributed heterogeneities in the resulting cell populations were generated by co-culturing two cell lines with one of them expressing a GPCR predominantly coupled to one of the three main canonical G-protein pathways (Gq, Gs, Gi/o). A protocol was established to obtain co-cultures with distinct cell ratios resulting in well-defined areal receptor densities (ARD) as verified by supported microscopic staining studies. The stimulation of cell ensembles with varying ARD by the GPCR's endogenous ligands was analyzed in detail by wholistic impedance-based cell assays. Efficacies and potencies, which describe the maximal agonist effect and the activity of a drug, were compared to those of the pure and original cell lines. It was shown that both parameters were dependent on the ARD and the coupled signaling cascades in distinct ways: for the Gq pathway, efficacy decreased non-linearly with decreasing ARD, while the Gs- and Gi/o-pathways exhibited an almost linear dependency of efficacy on the ARD. The potencies observed for the Gq- and Gi/o-coupled signaling pathway decreased with decreasing ARD, while the potency of the Gs-pathway was almost independent of the ARD. Simple simulations indicated that underlying communication processes between stimulated and non-stimulated cells within the populations under study may be responsible for these trends. Additionally, two proximal assay techniques were used to assist the interpretation of impedance analysis and to assign the impact of the ARD on the signal to a certain part of the signaling cascade. The radioligand competition binding assay confirmed the correct co-culturing strategy for such heterogeneous cell populations and confirmed the corresponding potency to be independent of the population composition. Population-based Ca2+ imaging highlighted the impact of altering the ARD on second messenger mobilization. Again, the ARD did not affect the potency, but the analysis of the response on a single-cell level proposed cell communication as a potential mechanism explaining the dependency of impedance on ARD. Moreover, the stimulation of a co-culture, consisting of two GPCR-expressing cell lines, was analyzed impedimetrically. The outcomes indicated that the potency dependency on the ARD was caused by the simultaneous activation of two different signaling pathways. The obtained data confirmed that the impact of artificially introduced heterogeneities in the cell population under study on the obtained impedance signal was indeed significant. Nevertheless, it remains elusive, whether these results can be translated to other cell lines or other GPCRs. This project addressed the fundamental question of areal heterogeneities influencing the impedance signal. However, further studies on cell ensembles with different compositions and other measurement techniques have to be carried out to obtain a broader picture of such impacts on population-based measurements and its significance for the drug development process. In the second project of this thesis, an assay was developed for the future purpose of introducing cell-to-cell variability within isogenic cell populations by spatiotemporal illumination of photochromic GPCR-ligands, which can be toggled between their bioactive and -inactive isomer. Thus, it was required to establish a protocol to active in situ such a ligand by online irradiation with light and to monitor the cell responses in a time-resolved manner. The wholistic impedance-based cell assay was appropriate to monitor the in situ toggling of a model photoswitchable ligand for a Gq-coupled receptor. To accomplish the superordinate goal, it will be necessary to establish a measurement setup, which is capable of spatiotemporal illumination of the cell culture, so that a small subpopulation can be stimulated in a spatiotemporally well-defined manner after the systemic addition of the bioinactive species of a photoswitchable ligand. The third part of this thesis addressed the impact of heterogeneous cell populations on the impedance readout by theoretical means. For this purpose, a MATLAB-based algorithm was developed, capable of simulating different cell types following the electric cell-substrate impedance sensing (ECIS) model. In contrast to the conventional mode, which assumes global cell-related parameters (α for the cell-substrate contacts, Rb for the cell-cell contacts, Cm for the cell membrane capacitances) for the whole population, the new approach emulated cell populations by cell-related parameters, each showing a Gaussian distribution with a mean and a deviation value. After successful validation of the underlying algorithm, discrepancies from the ECIS model using global parameters were found for such populations with heterogeneous cell-related parameters for three distinct cell types, emulating leaky, moderately tight, and tight cells. Especially the deviation of the Gaussian-distributed parameters α and Rb had a big impact on the spectra. In direct comparison to the reference, which was a homogenous cell population with global parameter values being equal to the mean values of the Gaussian distribution, a systematical misestimation could be found for α (up to 110 % of the reference value) and underestimation for Rb (down to 78 % of the reference value) when the deviation values were set to 30 % of the mean values. In contrast, Cm was found to be very robust for deviations up to 30 % (100 % of the reference value). In summary, the thesis has demonstrated in an experimental and theoretical manner that cell-to-cell variability has indeed major impacts on the population-based impedance signal, having the potential to misdirect data interpretation. These can affect fundamental as well as pharmacological research. Thus, it is crucial to address such heterogeneities within cell populations in future studies using population- as well as single-cell-based assay techniques

    Creating and Implementing Strategies for NRHP Eligibility Assessment at the Fort Polk Military Reservation

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    Large U.S. military installations, such as Fort Polk military reservation in south-central Louisiana, have for decades been the sites of cultural resource management (CRM) investigations, primarily due to the corpus of federal legislation developed to protect archaeological resources. These projects have yielded massive amounts of material and geospatial data and allowed researchers to develop sophisticated methodologies for analyzing site distribution, lithic tool manufacture, and many other avenues of inquiry. However, the cultural chronology represented on Fort Polk is still not well understood, and as a result assignation of National Register of Historic Places (NRHP)significance to sites on Fort Polk has to date hinged on the presence of identifiable ‘cultural features’. Bigger sites do not necessarily yield higher artifact densities at Fort Polk; artifact diversity, however, is closely linked to assemblage size. One cannot extrapolate a site\u27s ‘true’ artifact density or diversity from a small sample size without fully testing the site. This is not only time consuming and expensive, but also detrimental to the preservationist ethic of CRM. My thesis will seek to address this two-fold issue by manipulating extant databases containing information about artifacts recovered from Fort Polk. By compiling data concerning any test unit from any site on Fort Polk that yielded two or more diagnostic artifacts, a searchable spreadsheet has been created that allows for an installation-wide statistical analysis of the frequencies of a given diagnostic artifact’s ‘relative stratigraphy’ in relation to one or more other diagnostics. If a meaningful spatial or matrical relationship between one or more diagnostic types that holds across the installation can be demonstrated, a more precise understanding of the cultural chronology of Fort Polk, as well as the character of a given cultural group’s exploitation of the Fort Polk area, could be better understood. Such an understanding would also ramify throughout all proceeding cultural resource management (CRM) projects on the installation, allowing for more accurate and efficient interpretations of a site and subsequent assignation of NRHP significance

    GAC-MAC-SGA 2023 Sudbury Meeting: Abstracts, Volume 46

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