Novel computational approaches to research longitudinal microRNA-mRNA expression datasets

Ph. D. Thesis.microRNAs (miRNAs) regulate many biological processes and are used as biomarkers for the classification of diseases, conditions and developmental stages. miRNAs function by targeting and negatively regulating specific mRNAs. One limitation of utilising miRNAs in experimental work is the complex and often redundant behaviour of miRNA-mRNA interactions; as a single miRNA can regulate many mRNAs and one mRNA can be regulated by multiple miRNAs. This complexity stifles the potential of miRNAs. However, miRNAmRNA expression datasets are becoming generated more frequently and they can help to garner greater understanding of how miRNAs regulate biological systems. Furthermore, researchers are generating longitudinal datasets as these can elude to greater understanding of how biological conditions change over time. Thus there is a rise of longitudinal miRNA-mRNA expression datasets. However, extracting useful information from increasingly sophisticated datasets is a challenge in biological research. Exploration of such datasets using computational techniques, such as big data bioinformatics, kinetic modelling and machine learning could help in identifying interesting miRNA-mRNA interactions. During this PhD I asked if these methodologies can be used to gain insights from a range of longitudinal miRNA-mRNA expression datasets. Hence, I developed an R/Bioconductor tool called TimiRGeN to integrate, analyse and generate small networks from longitudinal miRNA-mRNA datasets. Datasets from kidney fibrosis, chondrogenesis dataset, breast cancer and Huntington’s disease (HD) were analysed with TimiRGeN. Results from the chondrogenesis dataset analysis were taken forward to generate a multimiRNA kinetic model. With help from my collaborators this model was validated and predictions were made. Using the HD dataset, machine learning (ML) techniques trained models to detect if samples have disease or wild type conditions. Overall, I have developed and used multiple computational techniques to increase knowledge gained from longitudinal miRNA-mRNA datasets, and I believe the results show these techniques can contribute to miRNA research

Photoacoustic ultrasound sources from diffusion-limited aggregates

Metallic diffusion-limited aggregate (DLA) films are well-known to exhibit near-perfect broadband optical absorption. We demonstrate that such films also manifest a substantial and relatively material-independent photoacoustic response, as a consequence of their random nanostructure. We theoretically and experimentally analyze photoacoustic phenomena in DLA films, and show that they can be used to create broadband air- coupled acoustic sources. These sources are inexpensive and simple to fabricate, and work into the ultrasonic regime. We illustrate the device possibilities by building and testing an optically-addressed acoustic phased array capable of producing virtually arbitrary acoustic intensity patterns in air.Comment: 5 pages, 5 figure

Xanthogranulomatous pyelonephritis: a case review of two cases

Xanthogranulomatous pyelonephirits is a chronic destructive granulomatous inflammation of the renal parenchyma. It was first described by Schlagenhaufer in 1916 and then Oberling named the disease as Xanthogranulomatous pyelonephritis in 1935. It represents 1% of all renal infections. In this report we present two cases of Xanthogranulomatous pyelonephritis along with radiological assessment

Evaluation of endometrial pathologies with high resolution transvaginal ultrasound

Background: The purpose of this study is to evaluate endometrial lesions on the basis of their appearances by high resolution trans-vaginal ultrasound. High resolution trans-vaginal sonography is useful for diagnosis of various endometrial lesions. Broad spectrum of endometrial lesions can be accurately imaged by various available modalities of which ultrasound is easily available, reliable, non-invasive and cost effective modality.Methods: In these study cases with complaints of abnormal uterine bleeding, suspected retained products, white discharge, dysmenorrhea and habitual abortions were evaluated with trans-vaginal ultrasound. Lesions were carefully studied and evaluated. Philips HD-11 and Accuson Siemens ultrasound machines with trans-vaginal probes were used.Results: In all 121 cases, trans-abdominal and trans-vaginal high resolution ultrasound was performed for different lesions in endometrium. Age group of females was between 18 to 65 years. Different uterine lesions were studied. Out of which most commonly encountered lesions were endometrial hyperplasia followed by polyps and least common lesion was AV malformation.Conclusions: High resolution trans-vaginal ultrasound helped in staging and management in cases of ca. endometrium. Hence trans-vaginal ultrasound should be 1st choice of investigation for diagnosis of endometrial lesions

TimiRGeN: R/Bioconductor package for time series microRNA-mRNA integration and analysis

Motivation: The analysis of longitudinal datasets and construction of gene regulatory networks (GRNs) provide a valuable means to disentangle the complexity of microRNA (miRNA)-mRNA interactions. However, there are no computational tools that can integrate, conduct functional analysis and generate detailed networks from longitudinal miRNA-mRNA datasets. Results: We present TimiRGeN, an R package that uses time point-based differential expression results to identify miRNA-mRNA interactions influencing signaling pathways of interest. miRNA-mRNA interactions can be visualized in R or exported to PathVisio or Cytoscape. The output can be used for hypothesis generation and directing in vitro or further in silico work such as GRN construction

Neuromuscular disease genetics in under-represented populations: increasing data diversity

Neuromuscular diseases (NMDs) affect ∼15 million people globally. In high income settings DNA-based diagnosis has transformed care pathways and led to gene-specific therapies. However, most affected families are in low-to-middle income countries (LMICs) with limited access to DNA-based diagnosis. Most (86%) published genetic data is derived from European ancestry. This marked genetic data inequality hampers understanding of genetic diversity and hinders accurate genetic diagnosis in all income settings. We developed a cloud-based transcontinental partnership to build diverse, deeply-phenotyped and genetically characterized cohorts to improve genetic architecture knowledge, and potentially advance diagnosis and clinical management. We connected 18 centres in Brazil, India, South Africa, Turkey, Zambia, Netherlands and the UK. We co-developed a cloud-based data solution and trained 17 international neurology fellows in clinical genomic data interpretation. Single gene and whole exome data were analysed via a bespoke bioinformatics pipeline and reviewed alongside clinical and phenotypic data in global webinars to inform genetic outcome decisions. We recruited 6001 participants in the first 43 months. Initial genetic analyses ‘solved’ or ‘possibly solved’ ∼56% probands overall. In-depth genetic data review of the four commonest clinical categories (limb girdle muscular dystrophy, inherited peripheral neuropathies, congenital myopathy/muscular dystrophies and Duchenne/Becker muscular dystrophy) delivered a ∼59% ‘solved’ and ∼13% ‘possibly solved’ outcome. Almost 29% of disease causing variants were novel, increasing diverse pathogenic variant knowledge. Unsolved participants represent a new discovery cohort. The dataset provides a large resource from under-represented populations for genetic and translational research. In conclusion, we established a remote transcontinental partnership to assess genetic architecture of NMDs across diverse populations. It supported DNA-based diagnosis, potentially enabling genetic counselling, care pathways and eligibility for gene-specific trials. Similar virtual partnerships could be adopted by other areas of global genomic neurological practice to reduce genetic data inequality and benefit patients globally

Interactions and Excitations in Quantum Degenerate 133^{133}Cs-6^6Li Bose-Fermi Mixtures

The study of quantum many-body systems remains a topic at the forefront of both theoretical and experimental physics research. These systems can exhibit a wealth of interesting phenomena and phases, and their understanding is important for progress towards new quantum technologies. Ultracold atomic gases are a powerful experimental platform for studying quantum many-body physics due to the flexibility and control that they afford. From the perspective of quantum simulation, mixtures of bosonic and fermionic neutral atoms offer a unique experimental system which permits tunable interactions between both types of fundamental particles. In solid-state materials, the interplay between the bosonic and fermionic components can be very important, with the most famous example being phonon-induced electron pairing in conventional superconductors. This thesis describes experiments on quantum degenerate mixtures of bosonic $^{133}$Cs and fermionic $^6$Li with tunable interspecies interactions. We have created the first degenerate mixtures of Li and Cs atoms and performed several experiments studying the role of interactions in their ground state and dynamics. The central question investigated is this: ``What happens to a Bose-Einstein condensate when it is immersed in a degenerate Fermi gas?" Throughout the work presented in this thesis, we have discovered several answers: the fermionic environment changes the effective confinement, the effective 2- and 3- body interactions, the phase diagram, and the excitations of the condensate. Our work represents significant progress in understanding the quantum behavior of Bose-Fermi mixtures, establishing the Li-Cs system as a valuable experimental platform in this direction. We lay groundwork for future studies of strongly interacting bosons and fermions, for which there are numerous fascinating theoretical proposals suggesting new quantum phases and phenomena