5,343 research outputs found

    UMSL Bulletin 2023-2024

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

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

    Get PDF
    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

    Novel 129Xe Magnetic Resonance Imaging and Spectroscopy Measurements of Pulmonary Gas-Exchange

    Get PDF
    Gas-exchange is the primary function of the lungs and involves removing carbon dioxide from the body and exchanging it within the alveoli for inhaled oxygen. Several different pulmonary, cardiac and cardiovascular abnormalities have negative effects on pulmonary gas-exchange. Unfortunately, clinical tests do not always pinpoint the problem; sensitive and specific measurements are needed to probe the individual components participating in gas-exchange for a better understanding of pathophysiology, disease progression and response to therapy. In vivo Xenon-129 gas-exchange magnetic resonance imaging (129Xe gas-exchange MRI) has the potential to overcome these challenges. When participants inhale hyperpolarized 129Xe gas, it has different MR spectral properties as a gas, as it diffuses through the alveolar membrane and as it binds to red-blood-cells. 129Xe MR spectroscopy and imaging provides a way to tease out the different anatomic components of gas-exchange simultaneously and provides spatial information about where abnormalities may occur. In this thesis, I developed and applied 129Xe MR spectroscopy and imaging to measure gas-exchange in the lungs alongside other clinical and imaging measurements. I measured 129Xe gas-exchange in asymptomatic congenital heart disease and in prospective, controlled studies of long-COVID. I also developed mathematical tools to model 129Xe MR signals during acquisition and reconstruction. The insights gained from my work underscore the potential for 129Xe gas-exchange MRI biomarkers towards a better understanding of cardiopulmonary disease. My work also provides a way to generate a deeper imaging and physiologic understanding of gas-exchange in vivo in healthy participants and patients with chronic lung and heart disease

    Southern Adventist University Undergraduate Catalog 2022-2023

    Get PDF
    Southern Adventist University\u27s undergraduate catalog for the academic year 2022-2023.https://knowledge.e.southern.edu/undergrad_catalog/1121/thumbnail.jp

    Generalizable deep learning based medical image segmentation

    Get PDF
    Deep learning is revolutionizing medical image analysis and interpretation. However, its real-world deployment is often hindered by the poor generalization to unseen domains (new imaging modalities and protocols). This lack of generalization ability is further exacerbated by the scarcity of labeled datasets for training: Data collection and annotation can be prohibitively expensive in terms of labor and costs because label quality heavily dependents on the expertise of radiologists. Additionally, unreliable predictions caused by poor model generalization pose safety risks to clinical downstream applications. To mitigate labeling requirements, we investigate and develop a series of techniques to strengthen the generalization ability and the data efficiency of deep medical image computing models. We further improve model accountability and identify unreliable predictions made on out-of-domain data, by designing probability calibration techniques. In the first and the second part of thesis, we discuss two types of problems for handling unexpected domains: unsupervised domain adaptation and single-source domain generalization. For domain adaptation we present a data-efficient technique that adapts a segmentation model trained on a labeled source domain (e.g., MRI) to an unlabeled target domain (e.g., CT), using a small number of unlabeled training images from the target domain. For domain generalization, we focus on both image reconstruction and segmentation. For image reconstruction, we design a simple and effective domain generalization technique for cross-domain MRI reconstruction, by reusing image representations learned from natural image datasets. For image segmentation, we perform causal analysis of the challenging cross-domain image segmentation problem. Guided by this causal analysis we propose an effective data-augmentation-based generalization technique for single-source domains. The proposed method outperforms existing approaches on a large variety of cross-domain image segmentation scenarios. In the third part of the thesis, we present a novel self-supervised method for learning generic image representations that can be used to analyze unexpected objects of interest. The proposed method is designed together with a novel few-shot image segmentation framework that can segment unseen objects of interest by taking only a few labeled examples as references. Superior flexibility over conventional fully-supervised models is demonstrated by our few-shot framework: it does not require any fine-tuning on novel objects of interest. We further build a publicly available comprehensive evaluation environment for few-shot medical image segmentation. In the fourth part of the thesis, we present a novel probability calibration model. To ensure safety in clinical settings, a deep model is expected to be able to alert human radiologists if it has low confidence, especially when confronted with out-of-domain data. To this end we present a plug-and-play model to calibrate prediction probabilities on out-of-domain data. It aligns the prediction probability in line with the actual accuracy on the test data. We evaluate our method on both artifact-corrupted images and images from an unforeseen MRI scanning protocol. Our method demonstrates improved calibration accuracy compared with the state-of-the-art method. Finally, we summarize the major contributions and limitations of our works. We also suggest future research directions that will benefit from the works in this thesis.Open Acces

    Behavioural ecology of the greater bilby (Macrotis lagotis) and conservation tool development in a semi-wild sanctuary

    Full text link
    Conservation translocations are becoming an increasingly necessary tool to stem the decline of threatened species globally. The greater bilby (Macrotis lagotis) is a nationally threatened species in Australia. While bilby translocations are expected to contribute to the species’ persistence, the scarcity of information on their behaviour and ecology prevents informed-management. By intensively studying a population of bilbies both prior to, and following reintroduction, and subsequent reinforcements to a fenced sanctuary, I aimed to (1) advance knowledge of bilby behaviour and examine behaviours potentially relevant to fitness (i.e. survival and breeding success), (2) improve ecological knowledge of bilbies within understudied (temperate) climates, and (3) use this knowledge to suggest and develop effective tools for their conservation. Chapter 1 describes the current state of research in applied conservation research, and how increased behavioural data could help address some of the current knowledge gaps for bilby conservation. In Chapter 2, I examined patterns in bilby resource selection, finding that selection changed between seasons and years due to the environmental conditions and resources available. I also found that resource requirements are likely to be behavioural-state dependent and sex-specific. In Chapter 3, I constructed social networks to examine nocturnal proximity of bilbies and concurrent burrow sharing and found that associations were non-random. Expanding on this, in Chapter 4, I found that burrow sharing was likely to help describe breeding strategies, as males strongly avoided other males, and mixed-sex dyads exhibited kin-avoidance when mate choice was more limited. In Chapter 5, I developed a test to screen personality traits in bilbies, finding links between male response to handling and relative breeding success post-release. Lastly, in Chapter 6, I described a method to collect detailed movement data on the bilby, and discussed some of the practical and animal welfare constraints for its application. My thesis provides new insights into the behavioural ecology of the bilby with potential implications for future management of the species. With further translocations necessary for long-term persistence of the bilby, this research is highly relevant to current and future management of this ecologically important species, with potential applications to other similarly at-risk species

    Specificity of the innate immune responses to different classes of non-tuberculous mycobacteria

    Get PDF
    Mycobacterium avium is the most common nontuberculous mycobacterium (NTM) species causing infectious disease. Here, we characterized a M. avium infection model in zebrafish larvae, and compared it to M. marinum infection, a model of tuberculosis. M. avium bacteria are efficiently phagocytosed and frequently induce granuloma-like structures in zebrafish larvae. Although macrophages can respond to both mycobacterial infections, their migration speed is faster in infections caused by M. marinum. Tlr2 is conservatively involved in most aspects of the defense against both mycobacterial infections. However, Tlr2 has a function in the migration speed of macrophages and neutrophils to infection sites with M. marinum that is not observed with M. avium. Using RNAseq analysis, we found a distinct transcriptome response in cytokine-cytokine receptor interaction for M. avium and M. marinum infection. In addition, we found differences in gene expression in metabolic pathways, phagosome formation, matrix remodeling, and apoptosis in response to these mycobacterial infections. In conclusion, we characterized a new M. avium infection model in zebrafish that can be further used in studying pathological mechanisms for NTM-caused diseases

    The Perceived Availability and Usefulness of Academic Accommodations, Academic Supports, and Academic Self-Efficacy in Graduate Counseling Students with Invisible Disabilities: A Preliminary Study

    Get PDF
    Academic accommodations exist through Section 504 of The Rehabilitation Act of 1973, The Americans with Disabilities Act of 1990, and the Americans with Disabilities Act Amended Act of 2008. Graduate counseling students with invisible disabilities may be unaware of all available accommodations or find incomplete information on disability support services websites. Such lack of awareness creates academic and emotional barriers for students with an invisible disability. While these issues are not isolated to one university, this quantitative study analyzed responses to an anonymous survey that invited current graduate counseling students enrolled in a CACREP counseling program who identified as having ADHD, autism, dyslexia, traumatic brain injury, or other neurodivergent disorder to evaluate the effects of perceived availability and usefulness of academic accommodations, academic support, and academic self-efficacy. The study\u27s findings indicated that most students were unaware of available academic accommodations beyond more time to take exams and submit assignments. Furthermore, students indicated they would likely use other accommodations that may better suit their academic needs. The results also suggest that more awareness of available accommodations is needed beyond more time to take exams and submit assignments to provide students with clear information when deciding to disclose their disability and request accommodations. The scales used in the study provided suggestions for future qualitative research on how lack of awareness about academic accommodations creates barriers for students and educators who have or work with individuals with invisible disabilities

    Understanding the Code of Life: Holistic Conceptual Modeling of the Genome

    Full text link
    [ES] En las últimas décadas, los avances en la tecnología de secuenciación han producido cantidades significativas de datos genómicos, hecho que ha revolucionado nuestra comprensión de la biología. Sin embargo, la cantidad de datos generados ha superado con creces nuestra capacidad para interpretarlos. Descifrar el código de la vida es un gran reto. A pesar de los numerosos avances realizados, nuestra comprensión del mismo sigue siendo mínima, y apenas estamos empezando a descubrir todo su potencial, por ejemplo, en áreas como la medicina de precisión o la farmacogenómica. El objetivo principal de esta tesis es avanzar en nuestra comprensión de la vida proponiendo una aproximación holística mediante un enfoque basado en modelos que consta de tres artefactos: i) un esquema conceptual del genoma, ii) un método para su aplicación en el mundo real, y iii) el uso de ontologías fundacionales para representar el conocimiento del dominio de una forma más precisa y explícita. Las dos primeras contribuciones se han validado mediante la implementación de sistemas de información genómicos basados en modelos conceptuales. La tercera contribución se ha validado mediante experimentos empíricos que han evaluado si el uso de ontologías fundacionales conduce a una mejor comprensión del dominio genómico. Los artefactos generados ofrecen importantes beneficios. En primer lugar, se han generado procesos de gestión de datos más eficientes, lo que ha permitido mejorar los procesos de extracción de conocimientos. En segundo lugar, se ha logrado una mejor comprensión y comunicación del dominio.[CA] En les últimes dècades, els avanços en la tecnologia de seqüenciació han produït quantitats significatives de dades genòmiques, fet que ha revolucionat la nostra comprensió de la biologia. No obstant això, la quantitat de dades generades ha superat amb escreix la nostra capacitat per a interpretar-los. Desxifrar el codi de la vida és un gran repte. Malgrat els nombrosos avanços realitzats, la nostra comprensió del mateix continua sent mínima, i a penes estem començant a descobrir tot el seu potencial, per exemple, en àrees com la medicina de precisió o la farmacogenómica. L'objectiu principal d'aquesta tesi és avançar en la nostra comprensió de la vida proposant una aproximació holística mitjançant un enfocament basat en models que consta de tres artefactes: i) un esquema conceptual del genoma, ii) un mètode per a la seua aplicació en el món real, i iii) l'ús d'ontologies fundacionals per a representar el coneixement del domini d'una forma més precisa i explícita. Les dues primeres contribucions s'han validat mitjançant la implementació de sistemes d'informació genòmics basats en models conceptuals. La tercera contribució s'ha validat mitjançant experiments empírics que han avaluat si l'ús d'ontologies fundacionals condueix a una millor comprensió del domini genòmic. Els artefactes generats ofereixen importants beneficis. En primer lloc, s'han generat processos de gestió de dades més eficients, la qual cosa ha permés millorar els processos d'extracció de coneixements. En segon lloc, s'ha aconseguit una millor comprensió i comunicació del domini.[EN] Over the last few decades, advances in sequencing technology have produced significant amounts of genomic data, which has revolutionised our understanding of biology. However, the amount of data generated has far exceeded our ability to interpret it. Deciphering the code of life is a grand challenge. Despite our progress, our understanding of it remains minimal, and we are just beginning to uncover its full potential, for instance, in areas such as precision medicine or pharmacogenomics. The main objective of this thesis is to advance our understanding of life by proposing a holistic approach, using a model-based approach, consisting of three artifacts: i) a conceptual schema of the genome, ii) a method for its application in the real-world, and iii) the use of foundational ontologies to represent domain knowledge in a more unambiguous and explicit way. The first two contributions have been validated by implementing genome information systems based on conceptual models. The third contribution has been validated by empirical experiments assessing whether using foundational ontologies leads to a better understanding of the genomic domain. The artifacts generated offer significant benefits. First, more efficient data management processes were produced, leading to better knowledge extraction processes. Second, a better understanding and communication of the domain was achieved.Las fructíferas discusiones y los resultados derivados de los proyectos INNEST2021 /57, MICIN/AEI/10.13039/501100011033, PID2021-123824OB-I00, CIPROM/2021/023 y PDC2021- 121243-I00 han contribuido en gran medida a la calidad final de este tesis.García Simón, A. (2022). Understanding the Code of Life: Holistic Conceptual Modeling of the Genome [Tesis doctoral]. Universitat Politècnica de València. https://doi.org/10.4995/Thesis/10251/19143

    Perceptions of Organizational Politics and Interpersonal Relationships in Black Women\u27s Organizations and Sororities

    Get PDF
    Although much research has addressed the relationships between leaders and followers, none has focused on these relationships between Black women—specifically, in the context of Black women’s social service organizations and sororities—and the impact the leader’s chosen style of leadership has on the followers’ use of voice. Self silencing is a prominent response to the power dynamic in many leader–follower relationships. The purpose of this study was to describe the interactions between leaders and followers in Black women’s social service organizations and sororities and identify the influence leadership style has on follower engagement. This study extends the application of silencing the self theory to leader–follower dynamics in Black women’s organizations and sororities. This qualitative study employed a narrative design and semistructured interviews to ascertain the experiences of and gain insight from 15 members of Black women’s organizations and sororities on their interactions with leaders in their organization and the impact on their use of voice and their commitment to the organization. The multiple themes identified suggest that the leader–follower relationship—specifically the leader’s actions and leadership style—and the culture and interpersonal dynamics of the organization are critical to followers’ decision to moderate their voice and their commitment to the organization
    • …
    corecore