Interactive exploration of population scale pharmacoepidemiology datasets

Population-scale drug prescription data linked with adverse drug reaction (ADR) data supports the fitting of models large enough to detect drug use and ADR patterns that are not detectable using traditional methods on smaller datasets. However, detecting ADR patterns in large datasets requires tools for scalable data processing, machine learning for data analysis, and interactive visualization. To our knowledge no existing pharmacoepidemiology tool supports all three requirements. We have therefore created a tool for interactive exploration of patterns in prescription datasets with millions of samples. We use Spark to preprocess the data for machine learning and for analyses using SQL queries. We have implemented models in Keras and the scikit-learn framework. The model results are visualized and interpreted using live Python coding in Jupyter. We apply our tool to explore a 384 million prescription data set from the Norwegian Prescription Database combined with a 62 million prescriptions for elders that were hospitalized. We preprocess the data in two minutes, train models in seconds, and plot the results in milliseconds. Our results show the power of combining computational power, short computation times, and ease of use for analysis of population scale pharmacoepidemiology datasets. The code is open source and available at: https://github.com/uit-hdl/norpd_prescription_analyse

MetaboLab - advanced NMR data processing and analysis for metabolomics

Background\ud Despite wide-spread use of Nuclear Magnetic Resonance (NMR) in metabolomics for the analysis of biological samples there is a lack of graphically driven, publicly available software to process large one and two-dimensional NMR data sets for statistical analysis.\ud \ud Results\ud Here we present MetaboLab, a MATLAB based software package that facilitates NMR data processing by providing automated algorithms for processing series of spectra in a reproducible fashion. A graphical user interface provides easy access to all steps of data processing via a script builder to generate MATLAB scripts, providing an option to alter code manually. The analysis of two-dimensional spectra (1H,13C-HSQC spectra) is facilitated by the use of a spectral library derived from publicly available databases which can be extended readily. The software allows to display specific metabolites in small regions of interest where signals can be picked. To facilitate the analysis of series of two-dimensional spectra, different spectra can be overlaid and assignments can be transferred between spectra. The software includes mechanisms to account for overlapping signals by highlighting neighboring and ambiguous assignments.\ud \ud Conclusions\ud The MetaboLab software is an integrated software package for NMR data processing and analysis, closely linked to the previously developed NMRLab software. It includes tools for batch processing and gives access to a wealth of algorithms available in the MATLAB framework. Algorithms within MetaboLab help to optimize the flow of metabolomics data preparation for statistical analysis. The combination of an intuitive graphical user interface along with advanced data processing algorithms facilitates the use of MetaboLab in a broader metabolomics context.\ud \u

Relationships of the early insulin secretory response and oral disposition index with gastric emptying in subjects with normal glucose tolerance

The oral disposition index, the product of the early insulin secretory response during an oral glucose tolerance test and insulin sensitivity, is used widely for both the prediction of, and evaluation of the response to interventions, in type 2 diabetes. Gastric emptying, which determines small intestinal exposure of nutrients, modulates postprandial glycemia. The aim of this study was to determine whether the insulin secretory response and the disposition index (DI) related to gastric emptying in subjects with normal glucose tolerance. Thirty-nine subjects consumed a 350 mL drink containing 75 g glucose labeled with 99mTc-sulfur colloid. Gastric emptying (by scintigraphy), blood glucose (G) and plasma insulin (I) were measured between t = 0-120 min. The rate of gastric emptying was derived from the time taken for 50% emptying (T50) and expressed as kcal/min. The early insulin secretory response was estimated by the ratio of the change in insulin (∆I0-30) to that of glucose at 30 min (∆G0-30) represented as ∆I0-30/∆G0-30 Insulin sensitivity was estimated as 1/fasting insulin and the DI was then calculated as ∆I0-30/∆G0-30 × 1/fasting insulin. There was a direct relationship between ∆G0-30 and gastric emptying (r = 0.47, P = 0.003). While there was no association of either ∆I0-30 (r = -0.16, P = 0.34) or fasting insulin (r = 0.21, P = 0.20), there were inverse relationships between the early insulin secretory response (r = -0.45, P = 0.004) and the DI (r = -0.33, P = 0.041), with gastric emptying. We conclude that gastric emptying is associated with both insulin secretion and the disposition index in subjects with normal glucose tolerance, such that when gastric emptying is relatively more rapid, both the early insulin secretory response and the disposition index are less. These findings should be interpreted as "hypothesis generating" and provide the rationale for longitudinal studies to examine the impact of baseline rate of gastric emptying on the prospective risk of type 2 diabetes.Chinmay S. Marathe, Christopher K. Rayner, Kylie Lange, Michelle Bound, Judith Wishart, Karen L. Jones, Steven E. Kahn and Michael Horowit

Synaptic Protection in the Brain of WldS Mice Occurs Independently of Age but Is Sensitive to Gene-Dose

Disruption of synaptic connectivity is a significant early event in many neurodegenerative conditions affecting the aging CNS, including Alzheimer's disease and Parkinson's disease. Therapeutic approaches that protect synapses from degeneration in the aging brain offer the potential to slow or halt the progression of such conditions. A range of animal models expressing the slow Wallerian Degeneration (Wld(S)) gene show robust neuroprotection of synapses and axons from a wide variety of traumatic and genetic neurodegenerative stimuli in both the central and peripheral nervous systems, raising that possibility that Wld(S) may be useful as a neuroprotective agent in diseases with synaptic pathology. However, previous studies of neuromuscular junctions revealed significant negative effects of increasing age and positive effects of gene-dose on Wld(S)-mediated synaptic protection in the peripheral nervous system, raising doubts as to whether Wld(S) is capable of directly conferring synapse protection in the aging brain.We examined the influence of age and gene-dose on synaptic protection in the brain of mice expressing the Wld(S) gene using an established cortical lesion model to induce synaptic degeneration in the striatum. Synaptic protection was found to be sensitive to Wld(S) gene-dose, with heterozygous Wld(S) mice showing approximately half the level of protection observed in homozygous Wld(S) mice. Increasing age had no influence on levels of synaptic protection. In contrast to previous findings in the periphery, synapses in the brain of old Wld(S) mice were just as strongly protected as those in young mice.Our study demonstrates that Wld(S)-mediated synaptic protection in the CNS occurs independently of age, but is sensitive to gene dose. This suggests that the Wld(S) gene, and in particular its downstream endogenous effector pathways, may be potentially useful therapeutic agents for conferring synaptic protection in the aging brain

Provenance-Centered Dataset of Drug-Drug Interactions

Over the years several studies have demonstrated the ability to identify potential drug-drug interactions via data mining from the literature (MEDLINE), electronic health records, public databases (Drugbank), etc. While each one of these approaches is properly statistically validated, they do not take into consideration the overlap between them as one of their decision making variables. In this paper we present LInked Drug-Drug Interactions (LIDDI), a public nanopublication-based RDF dataset with trusty URIs that encompasses some of the most cited prediction methods and sources to provide researchers a resource for leveraging the work of others into their prediction methods. As one of the main issues to overcome the usage of external resources is their mappings between drug names and identifiers used, we also provide the set of mappings we curated to be able to compare the multiple sources we aggregate in our dataset.Comment: In Proceedings of the 14th International Semantic Web Conference (ISWC) 201

Site-specific perturbations of alpha-synuclein fibril structure by the Parkinson's disease associated mutations A53T and E46K.

PMCID: PMC3591419This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.Parkinson's disease (PD) is pathologically characterized by the presence of Lewy bodies (LBs) in dopaminergic neurons of the substantia nigra. These intracellular inclusions are largely composed of misfolded α-synuclein (AS), a neuronal protein that is abundant in the vertebrate brain. Point mutations in AS are associated with rare, early-onset forms of PD, although aggregation of the wild-type (WT) protein is observed in the more common sporadic forms of the disease. Here, we employed multidimensional solid-state NMR experiments to assess A53T and E46K mutant fibrils, in comparison to our recent description of WT AS fibrils. We made de novo chemical shift assignments for the mutants, and used these chemical shifts to empirically determine secondary structures. We observe significant perturbations in secondary structure throughout the fibril core for the E46K fibril, while the A53T fibril exhibits more localized perturbations near the mutation site. Overall, these results demonstrate that the secondary structure of A53T has some small differences from the WT and the secondary structure of E46K has significant differences, which may alter the overall structural arrangement of the fibrils

Compact smallest eigenvalue expressions in Wishart-Laguerre ensembles with or without fixed-trace

The degree of entanglement of random pure states in bipartite quantum systems can be estimated from the distribution of the extreme Schmidt eigenvalues. For a bipartition of size M\geq N, these are distributed according to a Wishart-Laguerre ensemble (WL) of random matrices of size N x M, with a fixed-trace constraint. We first compute the distribution and moments of the smallest eigenvalue in the fixed trace orthogonal WL ensemble for arbitrary M\geq N. Our method is based on a Laplace inversion of the recursive results for the corresponding orthogonal WL ensemble by Edelman. Explicit examples are given for fixed N and M, generalizing and simplifying earlier results. In the microscopic large-N limit with M-N fixed, the orthogonal and unitary WL distributions exhibit universality after a suitable rescaling and are therefore independent of the constraint. We prove that very recent results given in terms of hypergeometric functions of matrix argument are equivalent to more explicit expressions in terms of a Pfaffian or determinant of Bessel functions. While the latter were mostly known from the random matrix literature on the QCD Dirac operator spectrum, we also derive some new results in the orthogonal symmetry class.Comment: 25 pag., 4 fig - minor changes, typos fixed. To appear in JSTA

KPZ equation in one dimension and line ensembles

For suitably discretized versions of the Kardar-Parisi-Zhang equation in one space dimension exact scaling functions are available, amongst them the stationary two-point function. We explain one central piece from the technology through which such results are obtained, namely the method of line ensembles with purely entropic repulsion.Comment: Proceedings STATPHYS22, Bangalore, 200

Simulation of primordial object formation

We have included the chemical rate network responsible for the formation of molecular Hydrogen in the N-body hydrodynamic code, Hydra, in order to study the formation of the first cosmological at redshifts between 10 and 50. We have tested our implementation of the chemical and cooling processes by comparing N-body top hat simulations with theoretical predictions from a semi-analytic model and found them to be in good agreement. We find that post-virialization properties are insensitive to the initial abundance of molecular hydrogen. Our main objective was to determine the minimum mass ($M_{SG}(z)$) of perturbations that could become self gravitating (a prerequisite for star formation), and the redshift at which this occurred. We have developed a robust indicator for detecting the presence of a self-gravitating cloud in our simulations and find that we can do so with a baryonic particle mass-resolution of 40 solar masses. We have performed cosmological simulations of primordial objects and find that the object's mass and redshift at which they become self gravitating agree well with the $M_{SG}(z)$ results from the top hat simulations. Once a critical molecular hydrogen fractional abundance of about 0.0005 has formed in an object, the cooling time drops below the dynamical time at the centre of the cloud and the gas free falls in the dark matter potential wells, becoming self gravitating a dynamical time later.Comment: 45 pages, 17 figures, submitted to Ap

Fasting and nutrient-stimulated plasma peptide-YY levels are elevated in critical illness and associated with feed intolerance: an observational, controlled study

INTRODUCTION: Delayed gastric emptying and feed intolerance occur frequently in the critically ill. In these patients, gastric motor responses to nutrients are disturbed. Peptide YY (PYY) slows gastric emptying. The aim of this study was to determine fasting and nutrient-stimulated plasma PYY concentrations and their relationship to cholecystokinin (CCK) in critically ill patients. METHODS: Studies were performed in 19 unselected mechanically ventilated critically ill patients (12 males; 48 ± 7 years old) in a randomised, single-blind fashion. Subjects received a 60-minute duodenal infusion of Ensure(® )at either 1 or 2 kcal/minute. Blood samples were collected at baseline and at 20, 40, 60, and 180 minutes following commencement of the nutrient infusion for the measurement of plasma PYY and CCK concentrations (using radioimmunoassay). Patient data were compared to 24 healthy subjects (17 males; 43 ± 2 years old). RESULTS: Fasting PYY concentration was higher in patients (P < 0.05), particularly in those with feed intolerance (P < 0.05). Plasma PYY concentrations were higher in patients during nutrient infusion (area under the curve [AUC] at 1 kcal/minute: 2,265 ± 718 versus 1,125 ± 138 pmol/l.min, P < 0.05; at 2 kcal/minute: 2,276 ± 303 versus 1,378 ± 210 pmol/l.min, P = 0.01) compared to healthy subjects. The magnitude of PYY elevation was greater in patients during the 1 kcal/minute infusion (AUC: 441 ± 153 versus 186 ± 58 pmol/l.min, P < 0.05), but not the 2 kcal/minute infusion. Fasting and nutrient-stimulated plasma CCK concentrations were higher in patients (P < 0.05). There was a relationship between plasma PYY and CCK concentrations during fasting (r = 0.52, P < 0.05) and nutrient infusion (r = 0.98, P < 0.0001). CONCLUSION: In critical illness, both fasting and nutrient-stimulated plasma PYY concentrations are elevated, particularly in patients with feed intolerance, in conjunction with increased CCK concentrations