Linkage between the Danish National Health Service Prescription Database, the Danish Fetal Medicine Database, and other Danish registries as a tool for the study of drug safety in pregnancy

A linked population-based database is being created in Denmark for research on drug safety during pregnancy. It combines information from the Danish National Health Service Prescription Database (with information on all prescriptions reimbursed in Denmark since 2004), the Danish Fetal Medicine Database, the Danish National Registry of Patients, and the Medical Birth Registry. The new linked database will provide validated information on malformations diagnosed both prenatally and postnatally. The cohort from 2008 to 2014 will comprise 589,000 pregnancies with information on 424,000 pregnancies resulting in live-born children, ∼420,000 pregnancies undergoing prenatal ultrasound scans, 65,000 miscarriages, and 92,000 terminations. It will be updated yearly with information on ∼80,000 pregnancies. The cohort will enable identification of drug exposures associated with severe malformations, not only based on malformations diagnosed after birth but also including those having led to termination of pregnancy or miscarriage. Such combined data will provide a unique source of information for research on the safety of medications used during pregnancy

Diabetes is an independent predictor of survival 17 years after myocardial infarction: follow-up of the TRACE registry

<p>Abstract</p> <p>Background</p> <p>In patients hospitalized for myocardial infarction, there are limited data examining the long-term prognostic effect of diabetes.</p> <p>The aim of this study was to systematically evaluate the development of diabetes as an independent long-term prognostic factor after myocardial infarction.</p> <p>Methods</p> <p>Prospective follow-up of 6676 consecutive MI patients screened for entry in the Trandolapril Cardiac Evaluation (TRACE) study. The patients were analysed by Kaplan-Meier survival analysis, landmark analysis and Cox proportional hazard models and outcome measure was all-cause mortality.</p> <p>Results</p> <p>The mortality in patients with diabetes was 82,7% at 10 years of follow-up and 91,1% at 15 years of follow-up, while patients without diabetes had a mortality of 60,2% at 10 years of follow-up and 72,9% at 15 years of follow-up (p < 0.0001). Landmark analysis continued to show prognostic significance of diabetes throughout the duration of follow-up. Multivariable Cox proportional-hazards model showed that the hazard ratio for death in patients with diabetes overall was 1.47 (95% confidence intervals (CI) 1.35-1.61) and varied between 1.19 (CI 1.04-1.37) and 2.13 (CI 1.33-3.42) in the 2-year periods of follow-up.</p> <p>Conclusions</p> <p>Diabetes is an important independent long-term prognostic factor after MI and continues to predict mortality even 17 years after index MI.</p> <p>This underscores the importance of aggressive diagnostic and therapeutic approach in diabetes patients with MI.</p

Selective Serial Multi-Antibody Biosensing with TOPAS Microstructured Polymer Optical Fibers

We have developed a fluorescence-based fiber-optical biosensor, which can selectively detect different antibodies in serial at preselected positions inside a single piece of fiber. The fiber is a microstructured polymer optical fiber fabricated from TOPAS cyclic olefin copolymer, which allows for UV activation of localized sensor layers inside the holes of the fiber. Serial fluorescence-based selective sensing of Cy3-labelled α-streptavidin and Cy5-labelled α-CRP antibodies is demonstrated

A recursive kinematic random forest and alpha beta filter classifier for 2D radar tracks

In this work, we show that by using a recursive random forest together with an alpha beta filter classifier it is possible to classify radar tracks from the tracks’ kinematic data. The kinematic data is from a 2D scanning radar without Doppler or height information. We use random forest as this classifier implicit handles the uncertainty in the position measurements. As stationary targets can have an apparently high speed because of the measurement uncertainty, we use an alpha beta filter classifier to classify stationary targets from moving targets. We show an overall classification rate from simulated data at 82.6 % and from real world data 79.7 %. Additional to the confusion matrix we also show recordings of real world data

Within-day repeatability for absolute quantification of Lawsonia intracellularis bacteria in feces from growing pigs

Absolute quantification of Lawsonia intracellularis by real-time polymerase chain reaction (PCR) is now possible on a routine basis. Poor repeatability of quantification can result in disease status misclassification of individual pigs when a single fecal sample is obtained. The objective of the current study was to investigate overall variation within a day for fecal numbers of L. intracellularis bacteria determined by real-time PCR in growing pigs. From each of 30 pigs with an infection of L. intracellularis, 5 fecal samples were collected within 1 day. A total of 150 fecal samples were obtained and subjected to quantitative PCR (qPCR) testing. Mean fecal dry matter content was 14.3% (standard deviation = 4.5%). Two pigs (6.7%) alternated between being L. intracellularis qPCR positive and negative. For 28 pigs, the excreting levels of L. intracellularis were within the dynamic range of the qPCR assay at all sampling points. For these 28 pigs, the mean excretion level of L. intracellularis was 6.1 log10 bacteria/g feces (standard deviation = 1.2 log10 bacteria/g feces). The maximum observed difference between 2 fecal samples from the same pig was 1.1 log10 bacteria/g feces. The average standard deviation for individual pigs was 0.27 log10 bacteria/g feces. The average coefficient of variation within pigs was 0.04, ranging from 0.006 to 0.08. The results imply that absolute quantification of L. intracellularis by qPCR has acceptable repeatability within 1 day. However, a population-specific proportion of pigs alternating between positive and negative test results must be expected. </jats:p

Hydrodynamic guiding for addressing subsets of immobilized cells and molecules in microfluidic systems

BACKGROUND: The interest in microfluidics and surface patterning is increasing as the use of these technologies in diverse biomedical applications is substantiated. Controlled molecular and cellular surface patterning is a costly and time-consuming process. Methods for keeping multiple separate experimental conditions on a patterned area are, therefore, needed to amplify the amount of biological information that can be retrieved from a patterned surface area. We describe, in three examples of biomedical applications, how this can be achieved in an open microfluidic system, by hydrodynamically guiding sample fluid over biological molecules and living cells immobilized on a surface. RESULTS: A microfluidic format of a standard assay for cell-membrane integrity showed a fast and dose-dependent toxicity of saponin on mammalian cells. A model of the interactions of human mononuclear leukocytes and endothelial cells was established. By contrast to static adhesion assays, cell-cell adhesion in this dynamic model depended on cytokine-mediated activation of both endothelial and blood cells. The microfluidic system allowed the use of unprocessed blood as sample material, and a specific and fast immunoassay for measuring the concentration of C-reactive protein in whole blood was demonstrated. CONCLUSION: The use of hydrodynamic guiding made multiple and dynamic experimental conditions on a small surface area possible. The ability to change the direction of flow and produce two-dimensional grids can increase the number of reactions per surface area even further. The described microfluidic system is widely applicable, and can take advantage of surfaces produced by current and future techniques for patterning in the micro- and nanometer scale