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  • 1.
    Ahmed, Trifa M.
    et al.
    Stockholms universitet, Naturvetenskapliga fakulteten, Institutionen för analytisk kemi.
    Bergvall, Christoffer
    Stockholms universitet, Naturvetenskapliga fakulteten, Institutionen för analytisk kemi.
    Åberg, Magnus
    Stockholms universitet, Naturvetenskapliga fakulteten, Institutionen för analytisk kemi.
    Westerholm, Roger
    Stockholms universitet, Naturvetenskapliga fakulteten, Institutionen för analytisk kemi.
    Determination of oxygenated and native polycyclic aromatic hydrocarbons in urban dust and diesel particulate matter standard reference materials using pressurized liquid extraction and LC-GC/MS2015Inngår i: Analytical and Bioanalytical Chemistry, ISSN 1618-2642, E-ISSN 1618-2650, Vol. 407, nr 2, s. 427-438Artikkel i tidsskrift (Fagfellevurdert)
    Abstract [en]

    The objective of this study was to develop a novel analytical chemistry method, comprised of a coupled high-performance liquid chromatography-gas chromatography/mass spectrometry system (LC-GC/MS) with low detection limits and high selectivity, for the identification and determination of oxygenated polycyclic aromatic hydrocarbons (OPAHs) and polycyclic aromatic hydrocarbons (PAHs) in urban air and diesel particulate matter. The linear range of the four OPAHs, which include 9,10-anthraquinone, 4H-cyclopenta[def]phenanthrene-4-one, benzanthrone, and 7,12-benz[a]anthraquinone, was 0.7 pg-43.3 ng with limits of detection (LODs) and limits of quantification (LOQs) on the order of 0.2-0.8 and 0.7-1.3 pg, respectively. The LODs in this study are generally lower than values reported in the literature, which can be explained by using large-volume injection. The recoveries of the OPAHs spiked onto glass fiber filters using two different pressurized liquid extraction (PLE) methods were in the ranges of 84-107 and 67-110 %, respectively. The analytical protocols were validated using the following National Institute of Standards and Technology standard reference materials: SRM 1649a (Urban Dust), SRM 1650b (Diesel Particulate Matter), and SRM 2975 (Diesel Particulate Matter, Industrial Forklift). The measured mass fractions of the OPAHs in the standard reference materials (SRMs) in this present study are higher than the values from the literature, except for benzanthrone in SRM 1649a (Urban Dust). In addition to the OPAHs, 44 PAHs could be detected and quantified from the same particulate extract used in this protocol. Using data from the literature and applying a two-sided t test at the 5 % level using Bonferroni correction, significant differences were found between the tested PLE methods for individual PAHs. However, the measured mass fractions of the PAHs were comparable, similar to, or higher than those previously reported in the literature.

  • 2.
    Alm, Erik
    et al.
    Stockholms universitet, Naturvetenskapliga fakulteten, Institutionen för analytisk kemi.
    Slagbrand, Tove
    Stockholms universitet, Naturvetenskapliga fakulteten, Institutionen för analytisk kemi.
    Åberg, K. Magnus
    Stockholms universitet, Naturvetenskapliga fakulteten, Institutionen för analytisk kemi.
    Wahlström, Erik
    Gustafsson, Ingela
    Lindberg, Johan
    Automated annotation and quantification of metabolites in (1)H NMR data of biological origin2012Inngår i: Analytical and Bioanalytical Chemistry, ISSN 1618-2642, E-ISSN 1618-2650, Vol. 403, nr 2, s. 443-455Artikkel i tidsskrift (Fagfellevurdert)
    Abstract [en]

    In 1H NMR metabolomic datasets, there are often over a thousand peaks per spectrum, many of which change position drastically between samples. Automatic alignment, annotation, and quantification of all the metabolites of interest in such datasets have not been feasible. In this work we propose a fully automated annotation and quantification procedure which requires annotation of metabolites only in a single spectrum. The reference database built from that single spectrum can be used for any number of 1H NMR datasets with a similar matrix. The procedure is based on the generalized fuzzy Hough transform (GFHT) for alignment and on Principal-components analysis (PCA) for peak selection and quantification. We show that we can establish quantities of 21 metabolites in several 1H NMR datasets and that the procedure is extendable to include any number of metabolites that can be identified in a single spectrum. The procedure speeds up the quantification of previously known metabolites and also returns a table containing the intensities and locations of all the peaks that were found and aligned but not assigned to a known metabolite. This enables both biopattern analysis of known metabolites and data mining for new potential biomarkers among the unknowns.

  • 3.
    Alm, Erik
    et al.
    Stockholms universitet, Naturvetenskapliga fakulteten, Institutionen för analytisk kemi.
    Torgrip, Ralf J. O.
    Åberg, K. Magnus
    Stockholms universitet, Naturvetenskapliga fakulteten, Institutionen för analytisk kemi.
    Schuppe-Koistinen, Ina
    Lindberg, Johan
    A solution to the 1D NMR alignment problem using an extended generalized fuzzy Hough transform and mode support2009Inngår i: Analytical and Bioanalytical Chemistry, ISSN 1618-2642, E-ISSN 1618-2650, Vol. 395, nr 1, s. 213-223Artikkel i tidsskrift (Fagfellevurdert)
    Abstract [en]

    This paper approaches the problem of intersample peak correspondence in the context of later applying statistical data analysis techniques to 1D 1H-nuclear magnetic resonance (NMR) data. Any data analysis methodology will fail to produce meaningful results if the analyzed data table is not synchronized, i.e., each analyzed variable frequency (Hz) does not originate from the same chemical source throughout the entire dataset. This is typically the case when dealing with NMR data from biological samples. In this paper, we present a new state of the art for solving this problem using the generalized fuzzy Hough transform (GFHT). This paper describes significant improvements since the method was introduced for NMR datasets of plasma in Csenki et al. (Anal Bioanal Chem 389:875-885, 15) and is now capable of synchronizing peaks from more complex datasets such as urine as well as plasma data. We present a novel way of globally modeling peak shifts using principal component analysis, a new algorithm for calculating the transform and an effective peak detection algorithm. The algorithm is applied to two real metabonomic 1H-NMR datasets and the properties of the method are compared to bucketing. We implicitly prove that GFHT establishes the objectively true correspondence. Desirable features of the GFHT are: (1) intersample peak correspondence even if peaks change order on the frequency axis and (2) the method is symmetric with respect to the samples.

  • 4.
    Alm, Erik
    et al.
    Stockholms universitet, Naturvetenskapliga fakulteten, Institutionen för analytisk kemi.
    Torgrip, Ralf J. O.
    Stockholms universitet, Naturvetenskapliga fakulteten, Institutionen för analytisk kemi.
    Åberg, K. Magnus
    Stockholms universitet, Naturvetenskapliga fakulteten, Institutionen för analytisk kemi.
    Schuppe-Koistinen, Ina
    Lindberg, Johan
    Time-resolved biomarker discovery inH-NMR data using generalized fuzzy Hough transform alignment and parallel factor analysis2010Inngår i: Analytical and Bioanalytical Chemistry, ISSN 1618-2642, E-ISSN 1618-2650, Vol. 396, nr 5, s. 1681-1689Artikkel i tidsskrift (Fagfellevurdert)
    Abstract [en]

    This work addresses the subject of time-series analysis of comprehensive 1H-NMR data of biological origin. One of the problems with toxicological and efficacy studies is the confounding of correlation between the administered drug, its metabolites and the systemic changes in molecular dynamics, i.e., the flux of drug-related molecules correlates with the molecules of system regulation. This correlation poses a problem for biomarker mining since this confounding must be untangled in order to separate true biomarker molecules from dose-related molecules. One way of achieving this goal is to perform pharmacokinetic analysis. The difference in pharmacokinetic time profiles of different molecules can aid in the elucidation of the origin of the dynamics, this can even be achieved regardless of whether the identity of the molecule is known or not. This mode of analysis is the basis for metabonomic studies of toxicology and efficacy. One major problem concerning the analysis of 1H-NMR data generated from metabonomic studies is that of the peak positional variation and of peak overlap. These phenomena induce variance in the data, obscuring the true information content and are hence unwanted but hard to avoid. Here, we show that by using the generalized fuzzy Hough transform spectral alignment, variable selection, and parallel factor analysis, we can solve both the alignment and the confounding problem stated above. Using the outlined method, several different temporal concentration profiles can be resolved and the majority of the studied molecules and their respective fluxes can be attributed to these resolved kinetic profiles. The resolved time profiles hereby simplifies finding true biomarkers and bio-patterns for early detection of biological conditions as well as providing more detailed information about the studied biological system. The presented method represents a significant step forward in time-series analysis of biological 1H-NMR data as it provides almost full automation of the whole data analysis process and is able to analyze over 800 unique features per sample. The method is demonstrated using a 1H-NMR rat urine dataset from a toxicology study and is compared with a classical approach: COW alignment followed by bucketing.

  • 5.
    Avagyan, Rozanna
    et al.
    Stockholms universitet, Naturvetenskapliga fakulteten, Institutionen för miljövetenskap och analytisk kemi.
    Åberg, Magnus
    Stockholms universitet, Naturvetenskapliga fakulteten, Institutionen för miljövetenskap och analytisk kemi.
    Westerholm, Roger
    Stockholms universitet, Naturvetenskapliga fakulteten, Institutionen för miljövetenskap och analytisk kemi.
    Suspect screening of OH-PAHs and non-target screening of other organic compounds in wood smoke particles using HR-Orbitrap-MS2016Inngår i: Chemosphere, ISSN 0045-6535, E-ISSN 1879-1298, Vol. 163, s. 313-321Artikkel i tidsskrift (Fagfellevurdert)
    Abstract [en]

    Wood combustion has been shown to contribute significantly to emissions of polycyclic aromatic hydrocarbons and hydroxylated polycyclic aromatic hydrocarbons, compounds with toxic and carcinogenic properties. However, only a small number of hydroxylated polycyclic aromatic hydrocarbons have been determined in particles from wood combustion, usually compounds with available reference standards. In this present study, suspect and non-target screening strategies were applied to characterize the wood smoke particles from four different wood types and two combustion conditions with respect to hydroxylated polycyclic aromatic hydrocarbons and other organic compounds. In the suspect screening, 32 peaks corresponding to 12 monohydroxylated masses were tentatively identified by elemental composition assignments and matching of isotopic pattern and fragments. More than one structure was suggested for most of the measured masses. Statistical analysis was performed on the non-target screening data in order to single out significant peaks having intensities that depend on the wood type and/or combustion condition. Significant peaks were found in both negative and positive ionization modes, with unique peaks for each wood type and combustion condition, as well as a combination of both factors. Furthermore, structural elucidation of some peaks was done by comparing the spectra in the samples with spectra found in the spectral databases. Six compounds were tentatively identified in positive ionization mode, and 19 in negative ionization mode. The results in this present study demonstrate that there are significant overall differences in the chemistry of wood smoke particles that depends on both the wood type and the combustion condition used.

  • 6.
    Bergh, Caroline
    et al.
    Stockholms universitet, Naturvetenskapliga fakulteten, Institutionen för analytisk kemi.
    Åberg, K. Magnus
    Stockholms universitet, Naturvetenskapliga fakulteten, Institutionen för analytisk kemi.
    Svartengren, Magnus
    Emenius, Gunnel
    Östman, Conny
    Stockholms universitet, Naturvetenskapliga fakulteten, Institutionen för analytisk kemi.
    Organophosphate and phthalate esters in indoor air: a comparison between multi-storey buildings with high and low prevalence of sick building symptoms2011Inngår i: Journal of Environmental Monitoring, ISSN 1464-0325, E-ISSN 1464-0333, Vol. 13, nr 7, s. 2001-2009Artikkel i tidsskrift (Fagfellevurdert)
    Abstract [en]

    An extensive study has been conducted of the prevalence of organophosphorous flame retardants/plasticizers and phthalate ester plasticizers in indoor air. The targeted substances were measured in 45 multi-storey apartment buildings in Stockholm, Sweden. The apartment buildings were classified as high or low risk with regard to the reporting of sick building symptoms (SBS) within the project Healthy Sustainable Houses in Stockholm (3H). Air samples were taken from two to four apartments per building (in total 169 apartments) to facilitate comparison within and between buildings. Association with building characteristics have been examined as well as association with specific sources by combining chemical analysis and exploratory uni- and multivariate data analysis. The study contributes to the overall perspective of levels of organophosphate and phthalate ester in indoor air enabling comparison with other studies. The results indicated little or no difference in the concentrations of the target substances between the two risk classifications of the buildings. The differences between the apartments sampled within (inter) buildings were greater than the differences between (intra) buildings. The concentrations measured in air ranged up to 1,200 ng/m3 for organophosphate esters and up to 11,000 ng/m3 for phthalate esters. Results in terms of sources were discerned e.g. PVC flooring is a major source of benzylbutyl phthalate in indoor air.    

  • 7.
    Csenki, Leonard
    et al.
    Stockholms universitet, Naturvetenskapliga fakulteten, Institutionen för analytisk kemi.
    Alm, Erik
    Stockholms universitet, Naturvetenskapliga fakulteten, Institutionen för analytisk kemi.
    Torgrip, Ralf J. O.
    Stockholms universitet, Naturvetenskapliga fakulteten, Institutionen för analytisk kemi.
    Åberg, K. Magnus
    Stockholms universitet, Naturvetenskapliga fakulteten, Institutionen för analytisk kemi.
    Nord, Lars I.
    Schuppe-Koistinen, Ina
    Lindberg, Johan
    Proof of principle of a generalized fuzzy Hough transform approach to peak alignment of one-dimensional 1H NMR data2007Inngår i: Analytical and Bioanalytical Chemistry, ISSN 1618-2642, E-ISSN 1618-2650, Vol. 389, nr 3, s. 875-885Artikkel i tidsskrift (Fagfellevurdert)
    Abstract [en]

    In metabolic profiling, multivariate data analysis techniques are used to interpret one-dimensional (1D) 1H NMR data. Multivariate data analysis techniques require that peaks are characterised by the same variables in every spectrum. This location constraint is essential for correct comparison of the intensities of several NMR spectra. However, variations in physicochemical factors can cause the locations of the peaks to shift. The location prerequisite may thus not be met, and so, to solve this problem, alignment methods have been developed. However, current state-of-the-art algorithms for data alignment cannot resolve the inherent problems encountered when analysing NMR data of biological origin, because they are unable to align peaks when the spatial order of the peaks changes—a commonly occurring phenomenon. In this paper a new algorithm is proposed, based on the Hough transform operating on an image representation of the NMR dataset that is capable of correctly aligning peaks when existing methods fail. The proposed algorithm was compared with current state-of-the-art algorithms operating on a selected plasma dataset to demonstrate its potential. A urine dataset was also processed using the algorithm as a further demonstration. The method is capable of successfully aligning the plasma data but further development is needed to address more challenging applications, for example urine data.

  • 8.
    Hansson, Helena
    et al.
    Stockholms universitet, Naturvetenskapliga fakulteten, Institutionen för analytisk kemi.
    Lagerstroem, Malene
    Åberg, Magnus
    Stockholms universitet, Naturvetenskapliga fakulteten, Institutionen för analytisk kemi.
    Nilsson, Ulrika
    Stockholms universitet, Naturvetenskapliga fakulteten, Institutionen för analytisk kemi.
    Dynamic hollow-fibre liquid phase microextraction of dinitrophenols from human plasma: Optimization of an extraction flow system using experimental design methodology2009Inngår i: Talanta: The International Journal of Pure and Applied Analytical Chemistry, ISSN 0039-9140, E-ISSN 1873-3573, Vol. 79, nr 3, s. 633-638Artikkel i tidsskrift (Fagfellevurdert)
    Abstract [en]

    The utility of a dynamic hollow-fibre liquid phase microextraction method (optimized using a four-variable experimental design and response surface modelling) for extracting dinitrophenolic compounds from human plasma samples was evaluated. The investigated variables were donor phase salt concentration (10–400 mM), donor phase pH (2–6), acceptor phase pH (7–12), and donor/acceptor phase flow rates (30/7.5 to 70/17.5 μL min−1). Four dinitrophenol pesticides were used as model substances at concentrations of 0.1 μg mL−1 in spiked human plasma samples. Extraction efficiencies ranging from 42 to 77% with RSDs below 9 were achieved with the optimized method. The flow rate and acceptor pH were shown to strongly affect the extraction efficiency for all compounds, while the donor phase pH and salt concentration had minor effects. With a well-defined acceptor phase pH and flow rate the system exhibited high robustness. The limits of quantification for the investigated compounds, using the presented extraction method followed by liquid chromatography/electrospray ionization mass spectrometry in selected ion monitoring mode, ranged from 0.05 to 0.1 μg mL−1 plasma.

  • 9.
    Jiang, Liying
    et al.
    Stockholms universitet, Naturvetenskapliga fakulteten, Institutionen för analytisk kemi.
    Johnston, Eric
    Stockholms universitet, Naturvetenskapliga fakulteten, Institutionen för organisk kemi.
    Åberg, K. Magnus
    Stockholms universitet, Naturvetenskapliga fakulteten, Institutionen för analytisk kemi.
    Nilsson, Ulrika
    Stockholms universitet, Naturvetenskapliga fakulteten, Institutionen för analytisk kemi.
    Ilag, Leopold L.
    Stockholms universitet, Naturvetenskapliga fakulteten, Institutionen för analytisk kemi.
    Strategy for quantifying trace levels of BMAA in cyanobacteria by LC/MS/MS2013Inngår i: Analytical and Bioanalytical Chemistry, ISSN 1618-2642, E-ISSN 1618-2650, Vol. 405, nr 4, s. 1283-1292Artikkel i tidsskrift (Fagfellevurdert)
    Abstract [en]

    The cyanobacterial neurotoxin β-N-methylamino--alanine (BMAA) is an amino acid that is putatively associated with the pathology of amyotrophic lateral sclerosis/Parkinsonism –dementia complex (ALS-PDC) disease. It raises serious health risk concerns since cyanobacteria are ubiquitous thus making human exposure almost inevitable. The identification and quantification of BMAA in cyanobacteria is challenging because it is present only in trace amounts and occurs alongside structurally similar compounds such as BMAA isomers. This work describes an enhanced liquid chromatography/tandem mass spectrometry platform that can distinguish BMAA from its isomers β-amino-N-methyl-alanine, N-(2-oethyl) glycine (AEG), and 2,4-diaminobutyric acid, thus ensuring confident identification of BMAA. The method's sensitivity was improved fourfold by a post-column addition of acetonitrile. The instrument and method limits of detection were shown to be 4.2 fmol/injection (or 0.5 g/one column) and 0.1 μg/g dry weight of cyanobacteria, respectively. The quantification method uses synthesized deuterated BMAA as an internal standard and exhibits good linearity, accuracy, and precision. Matrix effects were also investigated, revealing an ion enhancement of around 18 %. A lab-cultured cyanobacterial sample (Leptolyngbya PCC73110) was analyzed and shown to contain about 0.73 μg/g dry weight BMAA. The isomer AEG, whose chromatographic properties closely resemble those of BMAA, was also detected. These results highlight the importance of distinguishing BMAA from its isomers for reliable identification as well as providing a sensitive and accurate quantification method for measuring trace levels of BMAA in cyanobacterial samples.

  • 10.
    Kolmert, J.
    et al.
    Stockholms universitet, Naturvetenskapliga fakulteten, Institutionen för analytisk kemi.
    Forngren, B.
    Lindberg, J.
    Ohd, J.
    Åberg, Magnus
    Stockholms universitet, Naturvetenskapliga fakulteten, Institutionen för analytisk kemi.
    Nilsson, G.
    Moritz, T.
    Nordström, A.
    A quantitative LC/MS method targeting urinary 1-methyl-4-imidazoleacetic acid for safety monitoring of the global histamine turnover in clinical studies2014Inngår i: Analytical and Bioanalytical Chemistry, ISSN 1618-2642, E-ISSN 1618-2650, Vol. 406, nr 6, s. 1751-1762Artikkel i tidsskrift (Fagfellevurdert)
    Abstract [en]

    Anaphylaxis is a potentially life-threatening condition triggered mainly by the release of inflammatory mediators, notably histamine. In pharmaceutical research, drug discovery, and clinical evaluation, it may be necessary to accurately assess the potential of a compound, event, or disorder to promote the release of histamine. In contrast to the measurement of plasma histamine, determination of the stable metabolite 1-methyl-4-imidazoleacetic acid (tele-MIAA) in urine provides a noninvasive and more reliable methodology to monitor histamine release. This study presents a repeatable high-performance liquid chromatography coupled to electrospray mass spectrometry (LC-ESI-MS) method where tele-MIAA is baseline separated from its structural isomer 1-methyl-5-imidazoleacetic acid (pi-MIAA) and an unknown in human urine. The ion-pairing chromatography method, in reversed-phase mode, based on 0.5 mM tridecafluoroheptanoic acid demonstrated high repeatability and was applied in a clinical development program that comprised a large number of clinical samples from different cohorts. The inter- and intra-run precision of the method for tele-MIAA were 8.4 and 4.3 %, respectively, at the mean urinary concentration level, while method accuracy was between -16.2 and 8.0 % across the linear concentration range of 22-1,111 ng mL(-1). Overall, method precision was greater than that reported in previously published methods and enabled the identification of gender differences that were independent of age or demography. The median concentration measured in female subjects was 3.0 mu mol mmol(-1) of creatinine, and for male subjects, it was 2.1 mu mol mmol(-1) of creatinine. The results demonstrate that the method provides unprecedented accuracy, precision, and practicality for the measurement of tele-MIAA in large clinical settings.

  • 11. Kunzelmann, Marco
    et al.
    Winter, Martin
    Åberg, Magnus
    Stockholms universitet, Naturvetenskapliga fakulteten, Institutionen för miljövetenskap och analytisk kemi.
    Hellenäs, Karl-Erik
    Rosén, Johan
    Non-targeted analysis of unexpected food contaminants using LC-HRMS2018Inngår i: Analytical and Bioanalytical Chemistry, ISSN 1618-2642, E-ISSN 1618-2650, Vol. 410, nr 22, s. 5593-5602Artikkel i tidsskrift (Fagfellevurdert)
    Abstract [en]

    A non-target analysis method for unexpected contaminants in food is described. Many current methods referred to as non-target are capable of detecting hundreds or even thousands of contaminants. However, they will typically still miss all other possible contaminants. Instead, a metabolomics approach might be used to obtain true non-target analysis. In the present work, such a method was optimized for improved detection capability at low concentrations. The method was evaluated using 19 chemically diverse model compounds spiked into milk samples to mimic unknown contamination. Other milk samples were used as reference samples. All samples were analyzed with UHPLC-TOF-MS (ultra-high-performance liquid chromatography time-of-flight mass spectrometry), using reversed-phase chromatography and electrospray ionization in positive mode. Data evaluation was performed by the software TracMass 2. No target lists of specific compounds were used to search for the contaminants. Instead, the software was used to sort out all features only occurring in the spiked sample data, i.e., the workflow resembled a metabolomics approach. Procedures for chemical identification of peaks were outside the scope of the study. Method, study design, and settings in the software were optimized to minimize manual evaluation and faulty or irrelevant hits and to maximize hit rate of the spiked compounds. A practical detection limit was established at 25 mu g/kg. At this concentration, most compounds (17 out of 19) were detected as intact precursor ions, as fragments or as adducts. Only 2 irrelevant hits, probably natural compounds, were obtained. Limitations and possible practical use of the approach are discussed.

  • 12.
    Plassmann, Merle M.
    et al.
    Stockholms universitet, Naturvetenskapliga fakulteten, Institutionen för miljövetenskap och analytisk kemi.
    Tengstrand, Erik
    Stockholms universitet, Naturvetenskapliga fakulteten, Institutionen för miljövetenskap och analytisk kemi.
    Åberg, K. Magnus
    Stockholms universitet, Naturvetenskapliga fakulteten, Institutionen för miljövetenskap och analytisk kemi.
    Benskin, Jonathan P.
    Stockholms universitet, Naturvetenskapliga fakulteten, Institutionen för miljövetenskap och analytisk kemi.
    Non-target time trend screening: a data reduction strategy for detecting emerging contaminants in biological samples2016Inngår i: Analusis, ISSN 1618-2642, E-ISSN 1618-2650, Vol. 408, nr 16, s. 4203-4208Artikkel i tidsskrift (Fagfellevurdert)
    Abstract [en]

    Non-targeted mass spectrometry-based approaches for detecting novel xenobiotics in biological samples are hampered by the occurrence of naturally fluctuating endogenous substances, which are difficult to distinguish from environmental contaminants. Here, we investigate a data reduction strategy for datasets derived from a biological time series. The objective is to flag reoccurring peaks in the time series based on increasing peak intensities, thereby reducing peak lists to only those which may be associated with emerging bioaccumulative contaminants. As a result, compounds with increasing concentrations are flagged while compounds displaying random, decreasing, or steady-state time trends are removed. As an initial proof of concept, we created artificial time trends by fortifying human whole blood samples with isotopically labelled standards. Different scenarios were investigated: eight model compounds had a continuously increasing trend in the last two to nine time points, and four model compounds had a trend that reached steady state after an initial increase. Each time series was investigated at three fortification levels and one unfortified series. Following extraction, analysis by ultra performance liquid chromatography high-resolution mass spectrometry, and data processing, a total of 21,700 aligned peaks were obtained. Peaks displaying an increasing trend were filtered from randomly fluctuating peaks using time trend ratios and Spearman's rank correlation coefficients. The first approach was successful in flagging model compounds spiked at only two to three time points, while the latter approach resulted in all model compounds ranking in the top 11 % of the peak lists. Compared to initial peak lists, a combination of both approaches reduced the size of datasets by 80-85 %. Overall, non-target time trend screening represents a promising data reduction strategy for identifying emerging bioaccumulative contaminants in biological samples.

  • 13. Savolainen, Johannes
    et al.
    Mascialino, Barbara
    Pensamo, Elina
    Åberg, K. Magnus
    Stockholms universitet, Naturvetenskapliga fakulteten, Institutionen för miljövetenskap och analytisk kemi. Thermo Fisher Scientific, Sweden.
    Silvan, Maija
    Borres, Magnus P.
    Korhonen, Krista
    Structured intervention plan including component-resolved diagnostics helps reducing the burden of food allergy among school-aged children2019Inngår i: Pediatric Allergy and Immunology, ISSN 0905-6157, E-ISSN 1399-3038, Vol. 30, nr 1, s. 99-106Artikkel i tidsskrift (Fagfellevurdert)
    Abstract [en]

    Background: Food allergies can substantially burden patients and families by negatively affecting finances, social relationships, and personal perceptions of health. This study was performed under the Finnish Allergy Programme aimed at reducing avoidance diets to foods in schoolchildren by 50%. The main goal of this study was to investigate how many children could be freed from diet restrictions in a Finnish school district through a diagnostic algorithm including component-resolved diagnostics and food challenge. The secondary aim was to provide a crude estimate of the burden of the elimination food diets in the region, and the savings associated with the proposed intervention.

    Methods: A total of 205 children on a food avoidance diet according to the school register because of food allergy were invited into the study. One hundred and fifty-seven children were interviewed, tested for IgE to extracts and allergen components and food challenged in respective order.

    Results: After two years, 12 children still had an avoidance diet and three of them were treated successfully with sOTI; the rest suspended their avoidance diet (n = 134) or dropped out of the study (n = 11). The cost of the elimination diets was estimated in 172 700euro per year at start and 13 200euro per year at the end of the study; total savings were 128 400euro yearly.

    Conclusions: The results demonstrate a 65% reduction of avoidance diets to foods in school-aged children, exceeding the 50% aim of the Finnish Allergy Programme. Therefore, it is possible to actively reduce the number of food allergy diagnoses that remain unmonitored in the society through a tailored diagnostic work-up.

  • 14.
    Sousa, Pedro F. M.
    et al.
    Stockholms universitet, Naturvetenskapliga fakulteten, Institutionen för miljövetenskap och analytisk kemi.
    de Waard, Angela
    Stockholms universitet, Naturvetenskapliga fakulteten, Institutionen för miljövetenskap och analytisk kemi.
    Åberg, K. Magnus
    Stockholms universitet, Naturvetenskapliga fakulteten, Institutionen för miljövetenskap och analytisk kemi.
    Elucidation of chromatographic peak shifts in complex samples using a chemometrical approach2018Inngår i: Analytical and Bioanalytical Chemistry, ISSN 1618-2642, E-ISSN 1618-2650, Vol. 410, nr 21, s. 5229-5235Artikkel i tidsskrift (Fagfellevurdert)
    Abstract [en]

    Chromatographic retention time peak shifts between consecutive analyses is a well-known fact yet not fully understood. Algorithms have been developed to align peaks between runs, but with no specific studies considering the causes of peak shifts. Here, designed experiments reveal chromatographic shift patterns for a complex peptide mixture that are attributable to the temperature and pH of the mobile phase. These results demonstrate that peak shifts are highly structured and are to a high degree explained by underlying differences in physico-chemical parameters of the chromatographic system and also provide experimental support for the alignment algorithm called the generalized fuzzy Hough transform which exploits this fact. It can be expected that the development of alignment algorithms enters a new phase resulting in increasingly accurate alignment by considering the latent structure of the peak shifts.

  • 15.
    Sousa, Pedro F. M.
    et al.
    Stockholms universitet, Naturvetenskapliga fakulteten, Institutionen för miljövetenskap och analytisk kemi.
    Åberg, K. Magnus
    Stockholms universitet, Naturvetenskapliga fakulteten, Institutionen för miljövetenskap och analytisk kemi.
    Can we beat overfitting?-A closer look at Cloarec's PLS algorithm2018Inngår i: Journal of Chemometrics, ISSN 0886-9383, E-ISSN 1099-128X, Vol. 32, nr 6, artikkel-id e3002Artikkel i tidsskrift (Fagfellevurdert)
    Abstract [en]

    Random noise has been addressed as a cause of overfitting in partial least squares regression. A previous study pinpointed that one of the sources of overfitting resides in the calculation of scores due to the accumulation of noise in the diagonal of the variance-covariance matrix, and a modified partial least squares regression was proposed with the removal of this diagonal prior to the score calculation. Here, a further modification of the NIPALS algorithm is proposed, with the same ability to overcome overfitting due to noise, but algebraically more similar to the original NIPALS. The results indicate that it is possible to get more reliable auto-prediction R-2 with a cross-validation performance close to that of the original NIPALS algorithm.

  • 16.
    Tengstrand, Erik
    et al.
    Stockholms universitet, Naturvetenskapliga fakulteten, Institutionen för analytisk kemi.
    Lindberg, Johan
    Åberg, K. Magnus
    Stockholms universitet, Naturvetenskapliga fakulteten, Institutionen för analytisk kemi.
    TracMass 2-A Modular Suite of Tools for Processing Chromatography-Full Scan Mass Spectrometry Data2014Inngår i: Analytical Chemistry, ISSN 0003-2700, E-ISSN 1520-6882, Vol. 86, nr 7, s. 3435-3442Artikkel i tidsskrift (Fagfellevurdert)
    Abstract [en]

    In untargeted proteomics and metabolomics, raw data obtained with an LC/MS instrument are processed into a format that can be used for statistical analysis. Full scan MS data from chromatographic separation of biological samples are complex and analyte concentrations need to be extracted and aligned so that they can be compared across the samples. Several computer programs and methods have been developed for this purpose. There is still a need to improve the ease of use and feedback to the user because of the advanced multi-parametric algorithms used. Here, we present and make publicly available, TracMass 2, a suite of computer programs that gives immediate graphical feedback to the data analyst on parameter settings and processing results, as well as producing state-of-the-art results. The main advantage of TracMass 2 is that the feedback and transparency of the processing steps generate confidence in the end result, which is a table of peak intensities. The data analyst can easily validate every step of the processing pipeline. Because the user receives feedback on how all parameter values affect the result before starting a lengthy computation, the user's learning curve is enhanced and the total time used for data processing can be reduced. TracMass 2 has been released as open source and is included in the Supporting Information. We anticipate that TracMass 2 will set a new standard for how chemometrical algorithms are implemented in computer programs.

  • 17.
    Tengstrand, Erik
    et al.
    Stockholms universitet, Naturvetenskapliga fakulteten, Institutionen för analytisk kemi.
    Rosén, Johan
    Hellenäs, Karl-Erik
    Åberg, K. Magnus
    Stockholms universitet, Naturvetenskapliga fakulteten, Institutionen för analytisk kemi.
    A concept study on non-targeted screening for chemical contaminants in food using liquid chromatography–mass spectrometry in combination with a metabolomics approach2013Inngår i: Analytical and Bioanalytical Chemistry, ISSN 1618-2642, E-ISSN 1618-2650, Vol. 405, nr 4, s. 1237-1243Artikkel i tidsskrift (Fagfellevurdert)
    Abstract [en]

    A generic method to screen for new or unexpected contaminants at ppm levels in food has been developed. The method comprises an acidic acetonitrile extraction, detection with ultra-high-pressure liquid chromatography coupled to electrospray ionisation time-of-flight mass spectrometry and statistical evaluation using a metabolomics approach comparing suspected contaminated food with uncontaminated foods. The method was tested for 26 model contaminants from 100 μg/g down to 0.4 μg/g in three brands of fresh orange juice. Blinded statistical evaluation revealed signals from all added contaminants detectable by liquid chromatography –electrospray ionisation using positive ionisation mode, while only two false-positive signals were reported. The method is primarily intended to be used  for investigation of food samples suspected to be contaminated with unknown substances. Additionally it could be used to continuously monitor for appearance of new food contaminants as a complement to the specific targeted analysis that is today’s foundation of food safety analysis.

  • 18.
    Tengstrand, Erik
    et al.
    Stockholms universitet, Naturvetenskapliga fakulteten, Institutionen för miljövetenskap och analytisk kemi.
    Åberg, K. Magnus
    Stockholms universitet, Naturvetenskapliga fakulteten, Institutionen för miljövetenskap och analytisk kemi.
    Exploiting the sample dimension to resolve ambiguities in chromatographic peak alignmentInngår i: Journal of Chemometrics, ISSN 0886-9383, E-ISSN 1099-128XArtikkel i tidsskrift (Fagfellevurdert)
  • 19.
    Thuy, Tran Thi
    et al.
    Stockholms universitet, Naturvetenskapliga fakulteten, Institutionen för analytisk kemi.
    Tengstrand, Erik
    Stockholms universitet, Naturvetenskapliga fakulteten, Institutionen för analytisk kemi.
    Åberg, Magnus
    Stockholms universitet, Naturvetenskapliga fakulteten, Institutionen för analytisk kemi.
    Thorsen, Gunnar
    Stockholms universitet, Naturvetenskapliga fakulteten, Institutionen för analytisk kemi.
    Discrimination between glycosylation patterns of therapeutic antibodies using a microfluidic platform, MALDI-MS and multivariate statistics2012Inngår i: Journal of Pharmaceutical and Biomedical Analysis, ISSN 0731-7085, E-ISSN 1873-264X, Vol. 70, s. 47-52Artikkel i tidsskrift (Fagfellevurdert)
    Abstract [en]

    Optimal glycosylation with respect to the efficacy, serum half-life time, and immunogenic properties is essential in the generation of therapeutic antibodies. The glycosylation pattern can be affected by several different parameters during the manufacture of antibodies and may change significantly over cultivation time. Fast and robust methods for determination of the glycosylation patterns of therapeutic antibodies are therefore needed. We have recently presented an efficient method for the determination of glycans on therapeutic antibodies using a microfluidic CD platform for sample preparation prior to matrix-assisted laser-desorption mass spectrometry analysis. In the present work, this method is applied to analyse the glycosylation patterns of three commercially available therapeutic antibodies and one intended for therapeutic use. Two of the antibodies produced in mouse myeloma cell line (SP2/0) and one produced in Chinese hamster ovary (CHO) cells exhibited similar glycosylation patterns but could still be readily differentiated from each other using multivariate statistical methods. The two antibodies with most similar glycosylation patterns were also studied in an assessment of the method's applicability for quality control of therapeutic antibodies. The method presented in this paper is highly automated and rapid. It can therefore efficiently generate data that helps to keep a production process within the desired design space or assess that an identical product is being produced after changes to the process.

  • 20. Torgrip, Ralf
    et al.
    Åberg, Magnus
    Stockholms universitet, Naturvetenskapliga fakulteten, Institutionen för analytisk kemi.
    Alm, Erik
    Stockholms universitet, Naturvetenskapliga fakulteten, Institutionen för analytisk kemi.
    An improved data processing pipe-line for comprehensive H-NMR and X/MS -omics data2009Konferansepaper (Annet vitenskapelig)
  • 21. Zamani, Leila
    et al.
    Lundqvist, Magnus
    Zhang, Ye
    Åberg, Magnus
    Stockholms universitet, Naturvetenskapliga fakulteten, Institutionen för miljövetenskap och analytisk kemi.
    Edfors, Fredrik
    Bidkhori, Gholamreza
    Lindahl, Anna
    Mie, Axel
    Mardinoglu, Adil
    Field, Raymond
    Turner, Richard
    Rockberg, Johan
    Chotteau, Veronique
    High Cell Density Perfusion Culture has a Maintained Exoproteome and Metabolome2018Inngår i: Biotechnology Journal, ISSN 1860-6768, E-ISSN 1860-7314, Vol. 13, nr 10, artikkel-id 1800036Artikkel i tidsskrift (Fagfellevurdert)
    Abstract [en]

    The optimization of bioprocesses for biopharmaceutical manufacturing by Chinese hamster ovary (CHO) cells can be a challenging endeavor and, today, heavily relies on empirical methods treating the bioreactor process and the cells as black boxes. Multi-omics approaches have the potential to reveal otherwise unknown characteristics of these systems and identify culture parameters to more rationally optimize the cultivation process. Here, the authors have applied both metabolomic and proteomic profiling to a perfusion process, using CHO cells for antibody production, to explore how cell biology and reactor environment change as the cell density reaches 200x10(6)cellsmL(-1). The extracellular metabolic composition obtained in perfusion mode shows a markedly more stable profile in comparison to fed-batch, despite a far larger range of viable cell densities in perfusion. This stable profile is confirmed in the extracellular proteosome. Furthermore, the proteomics data shows an increase of structural proteins as cell density increases, which could be due to a higher shear stress and explain the decrease in cell diameter at very high cell densities. Both proteomic and metabolic results shows signs of oxidative stress and changes in glutathione metabolism at very high cell densities. The authors suggest the methodology presented herein to be a powerful tool for optimizing processes of recombinant protein production.

  • 22.
    Åberg, K. Magnus
    et al.
    Stockholms universitet, Naturvetenskapliga fakulteten, Institutionen för analytisk kemi.
    Torgrip, Ralf J. O.
    Jacobsson, Sven P.
    Stockholms universitet, Naturvetenskapliga fakulteten, Institutionen för analytisk kemi.
    Extensions to peak alignment using reduced set mapping and classification of LC-UV data from peptide mapping2005Inngår i: Journal of Chemometrics, ISSN 0886-9383, E-ISSN 1099-128X, Vol. 18, nr 10, s. 465-473Artikkel i tidsskrift (Fagfellevurdert)
    Abstract [en]

    Peak alignment using reduced set mapping (PARS) is extended with a new baseline approximation

    and a new dendrogram alignment scheme, which is designed to avoid the issue of selecting a target

    chromatogram for the alignment. Two data sets with LC/UV data are studied and it is shown that

    peak alignment with PARS increases the class separation substantially in the principal component

    score space. The results indicate that it is possible to use PARS for calibration transfer of multivariate

    models of chromatographic data.

  • 23.
    Åberg, Magnus
    Stockholms universitet, Naturvetenskapliga fakulteten, Institutionen för analytisk kemi.
    A Comparison of Algorithms for Warping and Peak Alignment2009Inngår i: 11 th Scandinavian Symposium on Chemometrics SSC11, 2009Konferansepaper (Annet vitenskapelig)
  • 24.
    Åberg, Magnus
    et al.
    Stockholms universitet, Naturvetenskapliga fakulteten, Institutionen för analytisk kemi.
    Alm, Erik
    Stockholms universitet, Naturvetenskapliga fakulteten, Institutionen för analytisk kemi.
    Torgrip, R
    The correspondence problem for metabonomics datasets K2009Inngår i: Analytical and Bioanalytical Chemistry, ISSN 1618-2642, E-ISSN 1618-2650, Vol. 394, s. 151-162Artikkel i tidsskrift (Fagfellevurdert)
    Abstract [en]

    In metabonomics it is difficult to tell which peak is which in datasets with many samples. This is known as the correspondence problem. Data from different samples are not synchronised, i.e., the peak from one metabolite does not appear in exactly the same place in all samples. For datasets with many samples, this problem is nontrivial, because each sample contains hundreds to thousands of peaks that shift and are identified ambiguously. Statistical analysis of the data assumes that peaks from one metabolite are found in one column of a data table. For every error in the data table, the statistical analysis loses power and the risk of missing a biomarker increases. It is therefore important to solve the correspondence problem by synchronising samples and there is no method that solves it once and for all. In this review, we analyse the correspondence problem, discuss current state-of-the-art methods for synchronising samples, and predict the properties of future methods.

  • 25.
    Östman, C
    et al.
    Stockholms universitet, Naturvetenskapliga fakulteten, Institutionen för analytisk kemi.
    Bergh, C
    Stockholms universitet, Naturvetenskapliga fakulteten, Institutionen för analytisk kemi.
    Åberg, M
    Stockholms universitet, Naturvetenskapliga fakulteten, Institutionen för analytisk kemi.
    Identifiering av ”sjuka hus” med kemisk analys kombinerat med multivariat statistisk dataanalys: Rapport till Miljöförvaltningen, Stockholms Stad2008Rapport (Annet vitenskapelig)
1 - 25 of 25
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