Stefan Rännar

Sartorius · Data Analytics

The zebrafish embryo is a popular model for drug screening, disease modelling and molecular genetics. In this study, samples were obtained from zebrafish at different developmental stages. The stages that were chosen were 3/4, 4/5, 24, 48, 72 and 96 hours post fertilization (hpf). Each sample included fifty embryos. The samples were analysed using...

In the present study, we performed a metabolomics analysis to evaluate a MODY5/RCAD mouse mutant line as a potential model for HNF1B-associated diseases. Gas chromatography time-of-flight mass spectrometry (GC-TOF-MS) of gut, kidney, liver, muscle, pancreas and plasma samples uncovered the tissue specific metabolite distribution. Orthogonal project...

IntroductionPost-collection handling, storage and transportation can affect the quality of blood samples. Pre-analytical biases can easily be introduced and can jeopardize accurate profiling of the plasma metabolome. Consequently, a mouse study must be carefully planned in order to avoid any kind of bias that can be introduced, in order not to comp...

Systemic lupus erythematosus (SLE) is a chronic inflammatory autoimmune disease which can affect most organ systems including skin, joints and the kidney. Clinically, SLE is a heterogeneous disease and shares features of several other rheumatic diseases, in particular primary Sjögrens syndrome (pSS) and systemic sclerosis (SSc), why it is difficult...

Supplementary information. (DOC)

Correct handling of samples is essential in metabolomic studies. Improper handling and prolonged storage of samples has unwanted effects on the metabolite levels. The aim of this study was to identify the effects that thawing has on different organ samples. Organ samples from gut, kidney, liver, muscle and pancreas were analyzed for a number of end...

Hierarchical modelling was applied in order to identify the organs that contribute to the levels of metabolites in plasma. Plasma and organ samples from gut, kidney, liver, muscle and pancreas were obtained from mice. The samples were analysed using gas chromatography time-of-flight mass spectrometry (GC TOF-MS) at the Swedish Metabolomics centre,...

Background Systemic Lupus Erythematosus (SLE) is a systemic autoimmune disease with symptoms ranging from skin related problems to more severe cardiovascular effects. The heterogenous representation of the disease might be the reason for the lack of efficient treatment. We hypothesize that subgroups of SLE can be characterized by different biochemi...

Background Systemic autoimmune diseases (SAIDs) affect about 2 % of the population in Western countries. Sufficient diagnostic criteria are lacking due to the heterogeneity within diagnostic categories and apparent overlap regarding symptoms and patterns of autoantibodies between different diagnoses. Systemic lupus erythematosus (SLE) is regarded a...

A strategy for optimizing LC-MS metabolomics data processing is proposed. We applied this strategy on the XCMS open source package written in R on both human and plant biology data. The strategy is a sequential design of experiments (DoE) based on a dilution series from a pooled sample and a measure of correlation between diluted concentrations and...

Systemic lupus erythematosus (SLE) is a systemic autoimmune disease with symptoms ranging from skin related problems to more severe cardiovascular effects. The heterogenous representation of the disease might be the reason for the lack of efficient treatment. The authors hypothesise that subgroups of SLE can be characterised by different biochemica...

A structural similarity tool was developed and aimed to search for environmentally persistent drugs. The basis for the tool was a selection of so-called anchor molecules and a multidimensional chemical map of drugs. The map was constructed using principal component analysis covering 899 drugs described by 67 diverse calculated chemical descriptors....

In metabolomics studies there is a clear increase of data. This indicates the necessity of both having a battery of suitable analysis methods and validation procedures able to handle large amounts of data. In this review, an overview of the metabolomics data processing pipeline is presented. A selection of recently developed and most cited data pro...

We propose a four-step strategy, based on principal component analysis and hierarchical clustering, for selecting structurally dissimilar organic substances from a list of commercial, high volume production chemicals. The selection strategy also presents alternative structures with similar characteristics, so that practical aspects of future testin...

Techniques that measure the force acting on a lifter bar, when it hits the charge inside a tumbling mill, have got an increased interest because of its direct physical relation to the behavior of the grinding charge. The possibility to combine it with discrete element modeling (DEM), which gives an opportunity to visualize the charge motion, opens...

Multivariate process monitoring was applied to understand the influence of numerous production parameters on the release of organic matter into the effluent of a newsprint mill. The release was characterized by measuring the chemical oxygen demand (COD). The relationships between over 50 process variables and the COD load were investigated using PL...

Multivariate statistical process control (MSPC) is applied to an electrolysis process. The process produces extremely pure copper, and to monitor its quality the levels of eight metal impurities were recorded twice a day. These quality data are analysed adopting an (1) `intuitive' univariate approach, and (2) with multivariate techniques. It is dem...

Multivariate time series analysis is applied to understand and model the dynamics of an electrolytic process manufacturing copper. Here, eight metal impurities were measured, twice daily, over a period of one year, to characterize the quality of the copper. In the data analysis, these eight variables were summarized by means of principal component...

A new approach to monitoring batch processes using the process variable trajectories is presented. It was developed to overcome the need in the approach of Nomikos and MacGregor [P. Nomikos, J.F. MacGregor, Monitoring of batch processes using multi-way principal components analysis, Am. Inst. Chem. Eng. J. 40 (1994) 1361–1375; P. Nomikos, J.F. MacG...

Mathematical treatments and modelling of large data structures have always created problems. From the infancy of computers to the late 1980s, the limiting factor when modelling large data structures was often the size of the computer memory. Due to the strong evolution in the field of computer technology, this problem is steadily decreasing. Conseq...

This is Part II of a series concerning the PLS kernel algorithm for data sets with many variables and few objects. Here the issues of cross-validation and missing data are investigated. Both partial and full crossvalidation are evaluated in terms of predictive residuals and speed and are illustrated on real examples. Two related approaches to the s...

For multivariate classification and quantitative structure activity studies of proteins, which involve amino acid sequences of different length, preprocessing methods are needed which make it possible to translate the sequence into a quantitative measure with the same number of variables.Here three different preprocessing methods are investigated....

A modified PLS algorithm is introduced with the goal of achieving improved prediction ability. The method, denoted IVS-PLS, is based on dimension-wise selective reweighting of single elements in the PLS weight vector w. Cross-validation, a criterion for the estimation of predictive quality, is used for guiding the selection procedure in the modelli...

Mycoplasmas are small, cell wall-deficient bacteria. The metabolic regulation of the lipid composition in the membrane of the species Acholeplasma laidlawii, strains A-EF22 and B-JU, is governed mainly by the balance between the potential formation of lamellar and nonlamellar phase structures. However, the regulatory features have not been consiste...

Multivariate quantitative structure–activity relationships (QSARs) are applied to model the atmospheric persistence of halogenated aliphatic hydrocarbons. The objective is to forecast the rate of reaction between the haloalkanes and the hydroxyl radical in the gas phase. The QSARs are developed in the light of a recently proposed strategy for risk...

A fast PLS regression algorithm dealing with large data matrices with many variables (K) and fewer objects (N) is presented For such data matrices the classical algorithm is computer-intensive and memory-demanding. Recently, Lindgren et al. (J. Chemometrics, 7, 45–49 (1993)) developed a quick and efficient kernel algorithm for the case with many ob...

Biopolymer sequences (e.g., DNA, RNA, proteins and polysaccharides) and chemical processes (e.g., a batch or continuous polymer synthesis run in a chemical plant) have close similarities from the modelling point of view. When a set of sequences or processes is characterized by multivariate data, a three-way data matrix is obtained. With sequences t...

Factorial experimental design was used to study the protective effects of Zn and Cu on cadmium-metallothionein(CdMT)-induced nephrotoxicity in male Wistar rats. In the factorial design two levels of Zn (0 and 25 mg/kg body weight), two levels of Cu (0 and 12.5 mg/kg), and two levels of CdMT (0.1 and 0.4 mg of Cd/kg) were used as varied factors. The...