High-Resolution Asymmetrical Flow Field-Flow Fractionation Data Evaluation via Richardson-Lucy-Based Fractogram Correction.

Asymmetrical flow field-flow fractionation (AF4) is a chromatographic separation technique that can be used for a broad range of particles or macromolecules. As an orthogonal method to size exclusion chromatography (SEC) with a much broader separation size range (1-800 nm) AF4 is gaining importance. However, the data evaluation capacities are far behind in comparison to other techniques like analytical ultracentrifugation (AUC). A program for evaluation of data from AF4 with a coupled multiangle laser light scattering (MALLS) detector was developed that allows the determination of the distributions of diffusion coefficients ( D), hydrodynamic radii ( Rh), molecular weights ( Mw), and relative concentrations (RC) of the obtained species. In addition, two algorithms to remove broadening effects via deconvolution were implemented and tested for their validity. The first is an extension of the known diffusion broadening correction applying the entire diffusion coefficient distribution instead of a single diffusion coefficient. The second applies the Richardson-Lucy algorithm for the deconvolution of overlapping signals from stars in astronomy. This program allows a reproducible strong enhancement of the fractogram resolution allowing for entire baseline separations of proteins. The comparison of the values for Mw determined by a partial Zimm plot from each data point of the original fractogram and the deconvolved results shows that especially the Richardson-Lucy algorithm maintains a high degree of data robustness.

MARK-AGE data management: Cleaning, exploration and visualization of data.

Databases are an organized collection of data and necessary to investigate a wide spectrum of research questions. For data evaluation analyzers should be aware of possible data quality problems that can compromise results validity. Therefore data cleaning is an essential part of the data management process, which deals with the identification and correction of errors in order to improve data quality. In our cross-sectional study, biomarkers of ageing, analytical, anthropometric and demographic data from about 3000 volunteers have been collected in the MARK-AGE database. Although several preventive strategies were applied before data entry, errors like miscoding, missing values, batch problems etc., could not be avoided completely. Such errors can result in misleading information and affect the validity of the performed data analysis. Here we present an overview of the methods we applied for dealing with errors in the MARK-AGE database. We especially describe our strategies for the detection of missing values, outliers and batch effects and explain how they can be handled to improve data quality. Finally we report about the tools used for data exploration and data sharing between MARK-AGE collaborators.

Mathematical modelling of the automated FADU assay for the quantification of DNA strand breaks and their repair in human peripheral mononuclear blood cells.

BACKGROUND: Cells continuously undergo DNA damage from exogenous agents like irradiation or genotoxic chemicals or from endogenous radicals produced by normal cellular metabolic activities. DNA strand breaks are one of the most common genotoxic lesions and they can also arise as intermediates of DNA repair activity. Unrepaired DNA damage can lead to genomic instability, which can massively compromise the health status of organisms. Therefore it is important to measure and quantify DNA damage and its repair. RESULTS: We have previously published an automated method for measuring DNA strand breaks based on fluorimetric detection of alkaline DNA unwinding [1], and here we present a mathematical model of the FADU assay, which enables to an analytic expression for the relation between measured fluorescence and the number of strand breaks. CONCLUSIONS: Assessment of the formation and also the repair of DNA strand breaks is a crucial functional parameter to investigate genotoxicity in living cells. A reliable and convenient method to quantify DNA strand breakage is therefore of significant importance for a wide variety of scientific fields, e.g. toxicology, pharmacology, epidemiology and medical sciences.

One-point boundary condition for the lattice Boltzmann method.

We propose a correction to the bounce back boundary condition for lattice Boltzmann algorithms which improves the accuracy of pressure from zero to first order and the accuracy of velocity from first to second order. Compared to interpolation based corrections, our method has the advantage of being completely local. In fact, methods using interpolation face difficulties at boundary points where not enough neighboring nodes are available. We show that a combination with our method offers a natural solution to this problem.