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Featured researches published by Jörgen Jonsson.


Analytica Chimica Acta | 1993

DNA and peptide sequences and chemical processes multivariately modelled by principal component analysis and partial least-squares projections to latent structures

Svante Wold; Jörgen Jonsson; M. Sjörström; Maria Sandberg; Stefan Rännar

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 m ...


Mechanisms of Development | 1996

Pancreatic-duodenal homeobox 1 -role in gastric endocrine patterning

Lars-Inge Larsson; Ole D. Madsen; Palle Serup; Jörgen Jonsson; Helena Edlund

The gastrointestinal tract is subdivided into regions with different roles in digestion and absorption. How this patterning is established is unknown. We now report that the pancreatic-duodenal homeobox 1 gene (pdx1) is also expressed in cells of the distal stomach. Positive cells include subpopulations of the three main endocrine (gastrin, somatostatin and serotonin) cell types of this region. Pdx1 deficient mice were virtually devoid of gastrin cells, had normal numbers of somatostatin cells and increased numbers of serotonin cells. Pdx1 is thus important for development of the gastrin cells of the antropyloric mucosa of the stomach and probably acts by controlling the fate of gastrin/serotonin precursor cells.


Chemometrics and Intelligent Laboratory Systems | 1989

A strategy for ranking environmentally occurring chemicals

Jörgen Jonsson; Lennart Eriksson; Michael Sjöström; Svante Wold; Maria Livia Tosato

A systematic methodology for quantitative structure-activity relationship (QSAR) development in environmental toxicology is provided. The methodology is summarized in a strategy with six sequential ...


Archives of Environmental Contamination and Toxicology | 1992

Combined effects of tri-n-butyl tin (TBT) and diuron on marine periphyton communities detected as pollution-induced community tolerance

Sverker Molander; Björn Dahl; Hans Blanck; Jörgen Jonsson; Michael Sjöström

The effects of combined toxicity were studied, using marine periphyton communities exposed to mixtures of tri-n-butyl tin (TBT) and diuron (3-(3,4-dichlorophenyl)-1,1-dimethylurea, DCMU) in indoor aquaria during four weeks. The experimental design of the study followed a central composite design (CCD) and utilized dose-response surface methodology for evaluation of the results. The detection of pollution-induced community tolerance (PICT) was accomplished by short-term (1 h) tests on inhibition of photosynthesis. Both single-toxicant and two-toxicant short-term tests were used. Two tentative measures of tolerance are proposed to achieve convenient comparisons of the tolerances from the two-toxicant tests. With the detection of PICT, effects of the long-term exposure were recorded on diatom species richness, chlorophyll a accumulation and copepod abundance. The decrease of diatom species richness was accompanied by an increased tolerance (PICT), which was detectable by all tolerance measures used. Primary effects on microalgae were recorded as a decrease in chlorophyll a at higher toxicant concentrations. At lower concentrations, primary effects on copepods were found, which resulted in reduced grazing and increased chlorophyll a content.


Chemometrics and Intelligent Laboratory Systems | 1989

A strategy for ranking environmentally occurring chemicals: Part II. An illustration with two data sets of chlorinated aliphatics and aliphatic alcohols

Lennart Eriksson; Jörgen Jonsson; Michael Sjöström; Svante Wold

Abstract This paper demonstrates a recently proposed strategy for toxic hazard ranking of environmentally occurring chemicals on two data sets taken from the literature. The strategy is based on the assumption that a small set of representative chemicals can be identified within a structurally homogenous class, and that this small set, if properly chosen, indeed represents all the other compounds within the particular class. This subset is selected according to a statistical experimental design. Thereby it is especially suitable as a training set for quantitative structure—activity relationships (QSARs). These QSARs can subsequently be used to predict biological activity data for untested compounds in the class of interest. The predictions can, in turn, be used to identify the need for the biological testing of certain chemicals.


Water Research | 2002

Evaluation of different approaches to quantify strong organic acidity and acid-base buffering of organic-rich surface waters in Sweden

Stephan Köhler; Jakub Hruška; Jörgen Jonsson; Lars Lövgren; Stephen Lofts

The role of organic acids in buffering pH in surface waters has been studied using a small brownwater stream (26mg L(-1) TOC) draining a forested catchment in Northern Sweden. Under the conditions of elevated pressure of CO2 stream field pH was changed between 3.5 and 6.1 during the acidification and alkalinization experiment. Acid-base characteristics of the natural organic matter were also determined using a high precision potentiometric method for a concentrated sample from the same stream. We compared the predictions from the Windermere Humic Aqueous Model (WHAM Model V), a model derived from the potentiometric titration (diprotic/monoprotic acid model) and a previously derived triprotic acid model which only uses alkalinity and TOC as input variables. The predicted buffering characteristics of all three models are very similar in the pH range 4.5-7 which suggests that during routine analysis alkalinity and TOC are sufficient to give a good estimate of organic acid anion charge contribution in a large range of surface waters. A slightly adjusted version of WHAM V successfully describes the organic charge contribution in a large number of sampled surface water lakes, which were previously used to calibrate the triprotic model.


Biochimica et Biophysica Acta | 1994

Similar regulatory mechanisms despite differences in membrane lipid composition in Acholeplasma laidlawii strains A-EF22 and B-PG9. A multivariate data analysis

Åke Wieslander; Leif Rilfors; Anders Dahlqvist; Jörgen Jonsson; Sven Hellberg; Stefan Rännar; Michael Sjöström; Göran Lindblom

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 consistently observed in the B-PG9 strain. A comparison has been performed between the membrane lipid composition for strains A-EF22 and B-PG9, simultaneously changing eight experimental conditions known to affect the regulation and packing properties of the A-EF22 lipids. Multiple regression and partial least-square discriminant analyses of many variables showed: (i) quantitative differences in membrane lipid and protein composition, and in membrane protein molecular masses of the two strains; (ii) different molar fractions of the major polar lipids monoglucosyldiacylglycerol (nonlamellar) and diglucosyldiacylglycerol (lamellar), which were caused by differences in lipid acyl chain length and unsaturation inherent in the strains and by the type of growth medium used; and (iii) similar regulatory mechanisms for changes in the lipid composition under most conditions, responding to the experimentally varied bilayer and nonbilayer properties of the lipid matrix. These regulatory principles are probably valid in other bacteria as well.


Science of The Total Environment | 1991

Multivariate modelling of the rate constant of the gas-phase reaction of haloalkanes with the hydroxyl radical

Maria Livia Tosato; Claudio Chiorboli; Lennart Eriksson; Jörgen Jonsson

Abstract A QSAR strategy for screening toxic substances and identifying priorities for testing has been applied to haloalkanes with the objective of modelling their reaction rate constant with the hydroxyl radical in the gas phase, k(OH). A model has been calibrated using a training set of nine haloalkanes selected from a series of 58 by means of a statistical design. The model correlating the rate constant with 12 structural descriptors was obtained using partial least squares (PLS), and found to explain almost 90% of the variation in k(OH). Its predictive capability was tested using 16 validation compounds not included in the model calibration. The analysis indicated that several structural variables simultaneously contribute to the variation in k(OH). A simplified multivariate model based on qualitative and indicator variables has also been developed for estimating the rate constant of haloalkanes, aliphatic alcohols, ketones and aldehydes. The multi-class model was developed under the assumption of a similar mechanism of reaction with the hydroxyl radical.


Journal of Chemometrics | 1996

A multivariate characterization of tRNA nucleosides

Maria Sandberg; Michael Sjöström; Jörgen Jonsson

Twenty nucleosides occurring in transfer ribonucleic acid (tRNA) have been characterized using 21 experimentally determined (HPLC, TLC, NMR, etc.) and calculated (log P, van der Waals surface area, ionization potential, etc.) variables. Principal component analysis (PCA) was performed on the data set and four statistically significant components or principal properties (PPs) were extracted. The PPs described 68·4% of the variance in the data. The PP values are discussed in terms of similarity and dissimilarity among the nucleosides. The loading vectors from the PCA are used for an interpretation of the nature of the PP vectors. Application of the PPs in sequence‐activity modelling is demonstrated with 25 DNA‐promoter sequences originating from E. coli.


Journal of the American College of Toxicology | 1990

Quantitative Structure—Activity Relationships (QSARs): An Integrated Multivariate Approach for Risk Assessment Studies

Maria Livia Tosato; Claudio Chiorboli; Lennart Eriksson; Jörgen Jonsson; Silvia Marchini; Laura Passerini; Anna Pino; Luigi Viganó

The conditions and methods for constructing reliable QSARs are revised in relation to each component of a QSAR study: the selection of a training set out of a QSAR compatible series, the collection of data pertinent to the descriptors matrix (X) and to the effects matrix (Y), the analysis of data to connect X to Y by a regression model, and the validation of the model. In discussing these conditions, attention is given to the constraints that arise from the theoretical foundation of QSARs as analogy models of local validity and to the complexity and limited knowledge about the mechanisms of action. Hence, emphasis is placed on the need and importance to adopt multivariate methods for dealing with (1) the characterization of the structures, (2) the selection of a representative set of training compounds, and (3) analysis of the data. It is finally shown that the same integrated multivariate approach applies to the modeling of biological activities and other properties—chemical and biological—as well as to the modeling of correlations between batteries of data. The role of QSAR in risk assessment is addressed in the second part of the article. The framework of a strategy for an efficient screening assessment of toxic substances through the modeling of their exposure and toxicity-related properties is outlined. Applications of the strategy are reported that deal with two series of compounds. Examples of toxicity and persistency models are illustrated.

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Maria Livia Tosato

Istituto Superiore di Sanità

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