Artificial Intelligence for chemical risk assessment.

As the basis for managing the risks of chemical exposure, the Chemical Risk Assessment (CRA) process can impact a substantial part of the economy, the health of hundreds of millions of people, and the condition of the environment. However, the number of properly assessed chemicals falls short of societal needs due to a lack of experts for evaluation, interference of third party interests, and the sheer volume of potentially relevant information on the chemicals from disparate sources. In order to explore ways in which computational methods may help overcome this discrepancy between the number of chemical risk assessments required on the one hand and the number and adequateness of assessments actually being conducted on the other, the European Commission's Joint Research Centre organised a workshop on Artificial Intelligence for Chemical Risk Assessment (AI4CRA).

Resolving outbreak dynamics using approximate Bayesian computation for stochastic birth-death models.

Earlier research has suggested that approximate Bayesian computation (ABC) makes it possible to fit simulator-based intractable birth-death models to investigate communicable disease outbreak dynamics with accuracy comparable to that of exact Bayesian methods. However, recent findings have indicated that key parameters, such as the reproductive number , may remain poorly identifiable with these models. Here we show that this identifiability issue can be resolved by taking into account disease-specific characteristics of the transmission process in closer detail.

Modelling-based experiment retrieval: a case study with gene expression clustering.

Motivation: Public and private repositories of experimental data are growing to sizes that require dedicated methods for finding relevant data. To improve on the state of the art of keyword searches from annotations, methods for content-based retrieval have been proposed. In the context of gene expression experiments, most methods retrieve gene expression profiles, requiring each experiment to be expressed as a single profile, typically of case versus control.

A Bayesian Predictive Model for Clustering Data of Mixed Discrete and Continuous Type.

Advantages of model-based clustering methods over heuristic alternatives have been widely demonstrated in the literature. Most model-based clustering algorithms assume that the data are either discrete or continuous, possibly allowing both types to be present in separate features. In this paper, we introduce a model-based approach for clustering feature vectors of mixed type, allowing each feature to simultaneously take on both categorical and real values.

A central role for GRB10 in regulation of islet function in man.

Variants in the growth factor receptor-bound protein 10 (GRB10) gene were in a GWAS meta-analysis associated with reduced glucose-stimulated insulin secretion and increased risk of type 2 diabetes (T2D) if inherited from the father, but inexplicably reduced fasting glucose when inherited from the mother. GRB10 is a negative regulator of insulin signaling and imprinted in a parent-of-origin fashion in different tissues. GRB10 knock-down in human pancreatic islets showed reduced insulin and glucagon secretion, which together with changes in insulin sensitivity may explain the paradoxical reduction of glucose despite a decrease in insulin secretion.

Personality and dietary intake - findings in the Helsinki birth cohort study.

Background: Personality traits are associated with health outcomes including non-communicable diseases. This could be partly explained by lifestyle related factors including diet. The personality traits neuroticism, extraversion, openness, agreeableness, and conscientiousness are linked with resilience, meaning adaptability in challenging situations.

Early growth and non-alcoholic fatty liver disease in adulthood-the NAFLD liver fat score and equation applied on the Helsinki Birth Cohort Study.

Introduction: Prenatal and childhood growth influence the risk of developing the metabolic syndrome and type 2 diabetes. Both conditions are associated with non-alcoholic fatty liver disease (NAFLD). Our aim was to explore the associations between early growth and adult NAFLD.

Association between type 2 diabetes and exposure to persistent organic pollutants.

Objective: The prevalence of type 2 diabetes is increasing alarmingly in both developed and developing countries. Recently, exposure to persistent organic pollutants (POPs) has been associated with the prevalence of type 2 diabetes. The purpose of this cross-sectional study is to examine the association between type 2 diabetes and POP exposure in the Helsinki Birth Cohort Study.

Birth-weight and resting metabolic rate in adulthood - sex-specific differences.

Introduction: Low birth-weight is associated with an increased risk of cardiovascular disease, hypertension, and the metabolic syndrome (MetS) in adulthood. Resting metabolic rate (RMR) has been suggested to be associated with the development of obesity as well as MetS and might be an indirect indicator of sympathetic activity. This study's aim was to examine the association between birth-weight and adult RMR.

Prenatal exposure to wartime stress: long-term effect on coronary heart disease in later life.

Background. Increased rates of coronary heart disease (CHD) and cerebrovascular disease in later life have been repeatedly observed in subjects with low birth-weight. One possible reason for low birth-weight is prenatal stress.

Statistical modelling of measurement errors in gas chromatographic analyses of blood alcohol content.

Headspace gas chromatographic measurements of ethanol content in blood specimens from suspect drunk drivers are routinely carried out in forensic laboratories. In the widely established standard statistical framework, measurement errors in such data are represented by Gaussian distributions for the population of blood specimens at any given level of ethanol content. It is known that the variance of measurement errors increases as a function of the level of ethanol content and the standard statistical approach addresses this issue by replacing the unknown population variances by estimates derived from large sample using a linear regression model.

Perinatal risk factors in young adult-onset type 1 and type 2 diabetes - a population-based case-control study.

Objective: To examine the effects of the size of the mother and the newborn, including placental weight and gestational age at delivery, on the risk for young adult-onset type 1 diabetes (T1DM) and type 2 diabetes (T2DM).

Design: Case-control study.

Setting: Finland.