Integrating biomedical research and electronic health records to create knowledge-based biologically meaningful machine-readable embeddings.

In order to advance precision medicine, detailed clinical features ought to be described in a way that leverages current knowledge. Although data collected from biomedical research is expanding at an almost exponential rate, our ability to transform that information into patient care has not kept at pace. A major barrier preventing this transformation is that multi-dimensional data collection and analysis is usually carried out without much understanding of the underlying knowledge structure. Here, in an effort to bridge this gap, Electronic Health Records (EHRs) of individual patients are connected to a heterogeneous knowledge network called Scalable Precision Medicine Oriented Knowledge Engine (SPOKE). Then an unsupervised machine-learning algorithm creates Propagated SPOKE Entry Vectors (PSEVs) that encode the importance of each SPOKE node for any code in the EHRs. We argue that these results, alongside the natural integration of PSEVs into any EHR machine-learning platform, provide a key step toward precision medicine

Estimating Worker Information Gaps From A Stochastic Wage Frontier: A Study Of Canadian Labour Markets

In the presence of imperfect information in labour markets, optimal job search entails accepting a wage offer if it exceeds a worker’s reservation wage.  However, this generally means that a worker with a given skill, will not earn the maximum wage on offer, and the gap between the maximum wager and the wage earned could be viewed as an indicator of labour market inefficiency arising from worker information gaps. The inefficiency arises because information is costly, so workers do not search long enough to discover the maximum wage, which would otherwise be sought and earned if information were costless. The aim of this paper is to empirically investigate the extent of labour market inefficiency within and across a number of population strata in Canada. These strata include individuals grouped according to various socio-economic and demographic characteristics such as gender, geographical location, education, and immigration status. The econometric model adopted is the stochastic frontier function used initially extensively in studies of production and cost efficiency of firms, and subsequently employed in studies of worker information gaps. The data we use are drawn from the 2001 Census of Canada

Coanalysis of GWAS with eQTLs reveals disease-tissue associations.

Expression quantitative trait loci (eQTL), or genetic variants associated with changes in gene expression, have the potential to assist in interpreting results of genome-wide association studies (GWAS). eQTLs also have varying degrees of tissue specificity. By correlating the statistical significance of eQTLs mapped in various tissue types to their odds ratios reported in a large GWAS by the Wellcome Trust Case Control Consortium (WTCCC), we discovered that there is a significant association between diseases studied genetically and their relevant tissues. This suggests that eQTL data sets can be used to determine tissues that play a role in the pathogenesis of a disease, thereby highlighting these tissue types for further post-GWAS functional studies

Predictors of Acute Liver Failure in Patients With Acute Hepatitis A: An Analysis of the 2016-2018 San Diego County Hepatitis A Outbreak.

Background:Between 2016 and 2018, San Diego County experienced a hepatitis A outbreak with a historically high mortality rate (3.4%) that highlighted the need for early recognition of those at risk of developing acute liver failure (ALF). Methods:A retrospective case series of adult hospitalized patients with acute hepatitis A. Results:One hundred six patients with hepatitis A were studied, of whom 11 (10.4%) developed ALF, of whom 7 (6.6%) died. A history of alcohol abuse, hyperbilirubinemia, hypoalbuminemia, hyponatremia, and anemia were associated with increased odds of developing ALF. Initial Maddrey's and Model of End-Stage Liver Disease Sodium (MELD-Na) scores were also associated with the development of ALF. Multivariable analysis showed that a higher initial MELD-Na score (odds ratio [OR], 1.205; 95% confidence interval [CI], 1.018-1.427) and a lower initial serum albumin concentration (OR, 9.35; 95% CI, 1.15-76.9) were associated with increased odds of developing ALF. Combining serum albumin and MELD-Na (SAM; C-statistic, 0.8878; 95% CI, 0.756-0.988) yielded a model that was not better than either serum albumin (C-statistic, 0.852; 95% CI, 0.675-0.976) or MELD-Na (C-statistic, 0.891; 95% CI, 0.784-0.968; P = .841). Finally, positive blood cultures were more common among patients with ALF compared with those without ALF (63.6% vs 4.3%; P < .00001). Conclusions:Hypoalbuminemia was associated with an increased risk of ALF in patients with acute hepatitis A. Positive blood cultures and septic shock as a cause of death were common among patients with ALF. Providers caring for patients with acute hepatitis A should monitor for early signs of sepsis and consider empiric antibiotics, especially in patients presenting with hypoalbuminemia

Government Size And The International Mobility Of Capital

This paper examines how government size impacts on the degree of capital mobility among 23 industrial countries by estimating saving-investment correlations using an error-correction model, with random coefficients, from data for the 1970-2006 period. The error-correction approach allows us to integrate both short-run and long-run behaviour within a single model. This is important if the model is to be given a capital mobility interpretation, because the saving-investment correlation relevant for assessing capital mobility is a long run one. Further, a model with random coefficients is a more general way of incorporating unmeasured differences between countries. Our sample is classified into five groups according to government size, which is measured by the ratio of government expenditures to GDP, and the model is estimated for each group separately using the random coefficients estimator.  Our results find some support for the view that countries with larger governments also have lower capital mobility

RECENT ADVANCES IN ANTIMICROBIAL ACTIVITY OF PYRIMIDINES: A REVIEW

Over the past era, development of small heterocycles as potential therapeutics has been a zone of major interest. A large number of pyrimidine derivatives are of considerable biological and chemical interest. Pyrimidine derivatives have shown numerous biological activities such as antimicrobial, antitubercular, anticancer, anticonvulsant, antidiabetic, antiviral, and anti-inflammatory. Being a heterocyclic compound, Pyrimidine finds its use for designing synthesis of newer biologically active structures, as its aromaticity makes it relatively stable, also reactive sites which allow for functionalization. Several amino derivatives of nitrogen-containing heterocycles such as pyrimidine, pyridine possess an antimicrobial activity. In this review, recent advancements in the antimicrobial activity of pyrimidine derivatives have been reported