Bayesian analytical approaches for metabolomics : a novel method for molecular structure-informed metabolite interaction modeling, a novel diagnostic model for differentiating myocardial infarction type, and approaches for compound identification given mass spectrometry data.

Metabolomics, the study of small molecules in biological systems, has enjoyed great success in enabling researchers to examine disease-associated metabolic dysregulation and has been utilized for the discovery biomarkers of disease and phenotypic states. In spite of recent technological advances in the analytical platforms utilized in metabolomics and the proliferation of tools for the analysis of metabolomics data, significant challenges in metabolomics data analyses remain. In this dissertation, we present three of these challenges and Bayesian methodological solutions for each. In the first part we develop a new methodology to serve a basis for making higher order inferences in metabolomics, which we define as the testing of hypotheses that are more complex than single metabolite hypothesis tests. This methodology utilizes informative priors that are generated via the analysis of molecular structure similarity to enable the estimation of metabolite interactomes (or probabilistic models) which are organism-, sample media-, and condition-specific as well as comprehensive; and that can serve as reference models for studying perturbations in metabolic systems. After discussing the development of our methodology, we present an evaluation of its performance conducted using simulation studies, and we use the methodology for estimating a plasma metabolite interactome for stable heart disease. This interactome may serve as a reference model for evaluating systems-level changes that occur with acute disease events such as myocardial infarction (MI) or unstable angina. In the second part of this work, we present the challenge of developing diagnostic classification models which utilize metabolite abundances and that do not overfit relatively small sample sizes, especially given the high dimensionality of metabolite data acquired using platforms such as liquid chromatography-mass spectrometry. We use a Bayesian methodology for estimating a multinomial logistic regression classifier for the detection and discrimination of the subtype of acute myocardial infarction utilizing metabolite abundance data quantified from blood plasma. As heart disease is the leading cause of global mortality, a blood-based and non-invasive diagnostic test that could differentiate between MI types at the time of the event would have great utility. In the final part of this dissertation we review Bayesian approaches for compound identification in metabolomics experiments that utilize liquid chromatography-mass spectrometry which remains a challenging problem

Wisdom of artificial crowds feature selection in untargeted metabolomics: An application to the development of a blood-based diagnostic test for thrombotic myocardial infarction

Introduction: Heart disease remains a leading cause of global mortality. While acute myocardial infarction (colloquially: heart attack), has multiple proximate causes, proximate etiology cannot be determined by a blood-based diagnostic test. We enrolled a suitable patient cohort and conducted a non-targeted quantification of plasma metabolites by mass spectrometry for developing a test that can differentiate between thrombotic MI, non-thrombotic MI, and stable disease. A significant challenge in developing such a diagnostic test is solving the NP-hard problem of feature selection for constructing an optimal statistical classifier. Objective: We employed a Wisdom of Artificial Crowds (WoAC) strategy for solving the feature selection problem and evaluated the accuracy and parsimony of downstream classifiers in comparison with traditional feature selection techniques including the Lasso and selection using Random Forest variable importance criteria. Materials and methods: Artificial Crowd Wisdom was generated via aggregation of the best solutions from independent and diverse genetic algorithm populations that were initialized with bootstrapping and a random subspaces constraint. Results/Conclusions: Strong evidence was observed that a statistical classifier utilizing WoAC feature selection can discriminate between human subjects presenting with thrombotic MI, non-thrombotic MI, and stable Coronary Artery Disease given abundances of selected plasma metabolites. Utilizing the abundances of twenty selected metabolites, a leave-one-out cross-validation estimated misclassification rate of 2.6% was observed. However, the WoAC feature selection strategy did not perform better than the Lasso over the current study

Presence of multiple coronary angiographic characteristics for the diagnosis of acute coronary thrombus

Background: Coronary angiography is frequently employed to aid in the diagnosis of acute coronary thrombosis, but there is limited data to support its efficacy. The aim of the study was to evaluate sensitivity and specificity of five commonly used angiographic characteristics for diagnosis of acute coronary thrombosis: Ambrose complex lesion morphology; spherical, ovoid, or irregular filling defect; abrupt vessel cutoff; intraluminal staining; and any coronary filling defect. Methods: Coronary angiography of 80 acute myocardial infarction or stable coronary artery disease subjects were assessed in blinded fashion, for the presence or absence of five angiographic characteristics. Only lesions of ≥ 10% stenosis were included in the analysis. Presence or absence of each angiographic characteristic was compared between lesions with or without the following study defined outcomes: 1) histologically confirmed thrombus, 2) highly probable thrombus, and 3) highly unlikely thrombus. Results: A total of 323 lesions were evaluated. All studied angiographic characteristics were associated with histologically confirmed and highly probable thrombotic lesions vs. lesions not meeting criteria for these outcomes (p < 0.03), except for complex Ambrose morphology which was not associated with any of the study outcomes (p > 0.05). Specificity for identifying histologically confirmed or highly probable thrombotic lesion was high (92–100%), especially for spherical, ovoid, or irregular filling defect (99–100%) and intraluminal staining (99%). Sensitivity for identification of histologically confirmed or highly probable thrombotic lesions was low for all tested angiographic characteristics (17–60%). Conclusions: The presence of spherical, ovoid, or irregular filling defect or intraluminal staining was highly suggestive of coronary thrombus. However, none of the evaluated angiographic characteristics were useful for ruling out the presence of coronary thrombus. If confirmed in an independent cohort, these angiographic characteristic will be of significant value in confirming the diagnosis of acute coronary thrombosis.

The role and function of IκKα/β in monocyte impairment

Following major trauma, sepsis or surgery, some patients exhibit an impaired monocyte inflammatory response that is characterized by a decreased response to a subsequent bacterial challenge. To investigate this poorly understood phenomenon, we adopted an in-vitro model of endotoxin tolerance utilising primary human CD14 + monocytes to focus on the effect of impairment on IκKα/β, a critical part of the NFκB pathway. Impaired monocytes had decreased IκKα mRNA and protein expression and decreased phosphorylation of the IκKα/β complex. The impaired monocyte secretome demonstrated a distinct cytokine/chemokine footprint from the naïve monocyte, and that TNF-α was the most sensitive cytokine or chemokine in this setting of impairment. Inhibition of IκKα/β with a novel selective inhibitor reproduced the impaired monocyte phenotype with decreased production of TNF-α, IL-6, IL-12p70, IL-10, GM-CSF, VEGF, MIP-1β, TNF-β, IFN-α2 and IL-7 in response to an LPS challenge. Surgical patients with infection also exhibited an impaired monocyte phenotype and had decreased SITPEC, TAK1 and MEKK gene expression, which are important for IκKα/β activation. Our results emphasize that impaired monocyte function is, at least in part, related to dysregulated IκKα/β activation, and that IκKα/β is likely involved in mounting a sufficient monocyte inflammatory response. Future studies may wish to focus on adjuvant therapies that augment IκKα/β function to restore monocyte function in this clinically important problem

Multi-Filament Inflows Fueling Young Star Forming Galaxies

Theory suggests that there are two primary modes of accretion through which dark matter halos acquire the gas to form and fuel galaxies, hot and cold mode accretion. In cold mode accretion, gas streams along cosmic web filaments to the center of the halo, allowing for the efficient delivery of star-forming fuel. Recently, two QSO-illuminated HI Lyman alpha (Ly{\alpha}) emitting objects were reported to have properties of cold, rotating structures (Martin et al. 2015, Martin et al. 2016). However, the spatial and spectral resolution available was insufficient to constrain radial flows associated with connecting filaments. With the Keck Cosmic Web Imager (KCWI) we now have eight times the spatial resolution, permitting the detection of these in-spiraling flows. In order to detect these inflows, we introduce a suite of models which incorporate zonal radial flows, demonstrate their performance on a numerical simulation that exhibits coldflow accretion, and show that they are an excellent match to KCWI velocity maps of two Ly{\alpha} emitters observed around high-redshift quasars. These Multi-Filament Inflow models kinematically isolate zones of radial inflow that correspond to extended filamentary emission. The derived gas flux and inflow path is sufficient to fuel the inferred central galaxy star formation rate and angular momentum. Thus, our kinematic emission maps provide strong evidence for the inflow of gas from the cosmic web building galaxies at the peak of star formation

Exercise-Induced Changes in Glucose Metabolism Promote Physiological Cardiac Growth

Background: Exercise promotes metabolic remodeling in the heart, which is associated with physiological cardiac growth; however, it is not known whether or how physical activity–induced changes in cardiac metabolism cause myocardial remodeling. In this study, we tested whether exercise-mediated changes in cardiomyocyte glucose metabolism are important for physiological cardiac growth. Methods: We used radiometric, immunologic, metabolomic, and biochemical assays to measure changes in myocardial glucose metabolism in mice subjected to acute and chronic treadmill exercise. To assess the relevance of changes in glycolytic activity, we determined how cardiac-specific expression of mutant forms of 6-phosphofructo-2-kinase/fructose-2,6-bisphosphatase affect cardiac structure, function, metabolism, and gene programs relevant to cardiac remodeling. Metabolomic and transcriptomic screenings were used to identify metabolic pathways and gene sets regulated by glycolytic activity in the heart. Results: Exercise acutely decreased glucose utilization via glycolysis by modulating circulating substrates and reducing phosphofructokinase activity; however, in the recovered state following exercise adaptation, there was an increase in myocardial phosphofructokinase activity and glycolysis. In mice, cardiac-specific expression of a kinase-deficient 6-phosphofructo-2-kinase/fructose-2,6-bisphosphatase transgene (GlycoLo mice) lowered glycolytic rate and regulated the expression of genes known to promote cardiac growth. Hearts of GlycoLo mice had larger myocytes, enhanced cardiac function, and higher capillary-to-myocyte ratios. Expression of phosphatase-deficient 6-phosphofructo-2-kinase/fructose-2,6-bisphosphatase in the heart (GlycoHi mice) increased glucose utilization and promoted a more pathological form of hypertrophy devoid of transcriptional activation of the physiological cardiac growth program. Modulation of phosphofructokinase activity was sufficient to regulate the glucose–fatty acid cycle in the heart; however, metabolic inflexibility caused by invariantly low or high phosphofructokinase activity caused modest mitochondrial damage. Transcriptomic analyses showed that glycolysis regulates the expression of key genes involved in cardiac metabolism and remodeling. Conclusions: Exercise-induced decreases in glycolytic activity stimulate physiological cardiac remodeling, and metabolic flexibility is important for maintaining mitochondrial health in the heart

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

LeishVet update and recommendations on feline leishmaniosis

Limited data is available on feline leishmaniosis (FeL) caused by Leishmania infantum worldwide. The LeishVet group presents in this report a review of the current knowledge on FeL, the epidemiological role of the cat in L. infantum infection, clinical manifestations, and recommendations on diagnosis, treatment and monitoring, prognosis and prevention of infection, in order to standardize the management of this disease in cats. The consensus of opinions and recommendations was formulated by combining a comprehensive review of evidence-based studies and case reports, clinical experience and critical consensus discussions. While subclinical feline infections are common in areas endemic for canine leishmaniosis, clinical illness due to L. infantum in cats is rare. The prevalence rates of feline infection with L. infantum in serological or molecular-based surveys range from 0 % to more than 60 %. Cats are able to infect sand flies and, therefore, they may act as a secondary reservoir, with dogs being the primary natural reservoir. The most common clinical signs and clinicopathological abnormalities compatible with FeL include lymph node enlargement and skin lesions such as ulcerative, exfoliative, crusting or nodular dermatitis (mainly on the head or distal limbs), ocular lesions (mainly uveitis), feline chronic gingivostomatitis syndrome, mucocutaneous ulcerative or nodular lesions, hypergammaglobulinaemia and mild normocytic normochromic anaemia. Clinical illness is frequently associated with impaired immunocompetence, as in case of retroviral coinfections or immunosuppressive therapy. Diagnosis is based on serology, polymerase chain reaction (PCR), cytology, histology, immunohistochemistry (IHC) or culture. If serological testing is negative or low positive in a cat with clinical signs compatible with FeL, the diagnosis of leishmaniosis should not be excluded and additional diagnostic methods (cytology, histology with IHC, PCR, culture) should be employed. The most common treatment used is allopurinol. Meglumine antimoniate has been administered in very few reported cases. Both drugs are administered alone and most cats recover clinically after therapy. Follow-up of treated cats with routine laboratory tests, serology and PCR is essential for prevention of clinical relapses. Specific preventative measures for this infection in cats are currently not available

The Labor Management Relationship of the Typographical Unions and the Newspapers Publishers: A Case Study of the Conflict of Law and Custom

Abstract not availabl

Atherothrombotic factors and atherosclerotic cardiovascular events: the multi-ethnic study of atherosclerosis.

AimsTraditional atherosclerotic cardiovascular disease (ASCVD) risk factors fail to address the full spectrum of the complex interplay of atherosclerotic and atherothrombotic factors integral to ASCVD events. This study sought to examine the association between atherothrombotic biomarkers and ASCVD events.Methods and resultsThe association between atherothrombotic biomarkers and 877 ASCVD events with and without adjustment for traditional risk factors was evaluated via Cox proportional hazards models and factor analysis in 5789 Multi-Ethnic Study of Atherosclerosis participants over a median follow-up of 14.7 years. Factor analysis accounted for multidimensional relationship and shared variance among study biomarkers, which identified two new variables: a thrombotic factor (Factor 1), principally defined by shared variance in fibrinogen, plasmin-antiplasmin complex, factor VIII, D-dimer, and lipoprotein(a), and a fibrinolytic factor (Factor 2), principally defined by shared variance of plasminogen and oxidized phospholipids on plasminogen. In a model including both factors, the thrombotic factor was associated with the higher risk of ASCVD events [hazard ratio (HR) 1.57, 95% confidence interval (CI) 1.45, 1.70], while the fibrinolytic factor was associated with the lower risk of ASCVD events (HR 0.76, 95% CI 0.70, 0.82), with estimated ASCVD free survival highest for low atherothrombotic Factor 1 and high atherothrombotic Factor 2.ConclusionTwo atherothrombotic factors, one representative of thrombotic propensity and the other representative of fibrinolytic propensity, were significantly and complementarily associated with incident ASCVD events, remained significantly associated with incident ASCVD after controlling for traditional risk factors, and have promise for identifying patients at high ASCVD event risk specifically due to their atherothrombotic profile