Amsterdam, Netherlands
Amsterdam, Netherlands

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Szymanska E.,TI COAST | Szymanska E.,Radboud University Nijmegen | Brodrick E.,University of South Wales | Williams M.,University of South Wales | And 4 more authors.
Analytical Chemistry | Year: 2015

Ion mobility spectrometry combined with multicapillary column separation (MCC-IMS) is a well-known technology for detecting volatile organic compounds (VOCs) in gaseous samples. Due to their large data size, processing of MCC-IMS spectra is still the main bottleneck of data analysis, and there is an increasing need for data analysis strategies in which the size of MCC-IMS data is reduced to enable further analysis. In our study, the first untargeted chemometric strategy is developed and employed in the analysis of MCC-IMS spectra from 264 breath and ambient air samples. This strategy does not comprise identification of compounds as a primary step but includes several preprocessing steps and a discriminant analysis. Data size is significantly reduced in three steps. Wavelet transform, mask construction, and sparse-partial least squares-discriminant analysis (s-PLS-DA) allow data size reduction with down to 50 variables relevant to the goal of analysis. The influence and compatibility of the data reduction tools are studied by applying different settings of the developed strategy. Loss of information after preprocessing is evaluated, e.g., by comparing the performance of classification models for different classes of samples. Finally, the interpretability of the classification models is evaluated, and regions of spectra that are related to the identification of potential analytical biomarkers are successfully determined. This work will greatly enable the standardization of analytical procedures across different instrumentation types promoting the adoption of MCC-IMS technology in a wide range of diverse application fields. © 2014 American Chemical Society.


Brauckmann J.O.,TI COAST | Brauckmann J.O.,Radboud University Nijmegen | Zolfaghari P.,Radboud University Nijmegen | Verhoef R.,Teijin Aramid Research Institute | And 3 more authors.
Macromolecules | Year: 2016

Aramid fibers are of practical interest due to their high tensile strength, high elastic modulus, low elongation at breakage, and thermomechanical stability. Here we combine high-resolution solid-state NMR and density functional theory (DFT) calculations to gain insight into the details of the molecular packing of p-phenylene terephthalamides (PPTA). On the basis of the four models discussed thus far in the literature, we create a family of 16 possible structures. Calculations relate 1H and 13C chemical shifts obtained from experiments to structural aspects. Nucleus independent chemical shift (NICS) calculations show that ring currents and σ-π interactions as well as hydrogen bonding influence the chemical shifts on the rings. We obtain an unambiguous assignment, which differs from the literature data for carbon, for all resonances relating to the repeating unit of PPTA and obtain new insights into the possible packings of the PPTA units within the unit cell. © 2016 American Chemical Society.


Jansen J.J.,Radboud University Nijmegen | Hilvering B.,University Utrecht | van den Doel A.,Radboud University Nijmegen | Pickkers P.,Radboud University Nijmegen | And 3 more authors.
Chemometrics and Intelligent Laboratory Systems | Year: 2016

Multicolour Flow Cytometry (MFC) is widely used for single-cell analysis and employs a vastly increasing number of markers. It can be used for disease diagnosis, research of disease mechanisms and the identification and isolation of individual cells based on their surface marker profile. However, data analysis methods exploiting all these advantages are lacking. Our novel FLow cytometric Orthogonal Orientation for Diagnosis (FLOOD) method reveals disease specific marker patterns. The method constructs a benchmark from surface marker abundances that is used to highlight deviations of challenged from unchallenged individuals. We demonstrate its power in an in vivo study of the response of healthy humans to lipopolysaccharide (LPS) challenge. FLOOD reveals a reproducible pattern of challenge specific markers on blood neutrophils. The method both provides new mechanistic insights and confirms established knowledge on LPS-response, which demonstrates the high potential of FLOOD for both clinical and research application. © 2015 Elsevier B.V..


Szymanska E.,TI COAST | Szymanska E.,Radboud University Nijmegen | Gerretzen J.,TI COAST | Gerretzen J.,Radboud University Nijmegen | And 4 more authors.
TrAC - Trends in Analytical Chemistry | Year: 2015

In analytical chemistry, qualitative analysis is often associated with compound identification, while chemometrics offers a wide spectrum of data-analysis methods that extend the application of qualitative analysis beyond compound identification. All chemical analyses that have a qualitative goal can or should be considered as qualitative chemical analysis. Thanks to chemometrics, both qualitative and quantitative data can be included in qualitative analysis and modeled towards a qualitative analysis goal. We provide an extensive overview on the vibrant relationship between chemometrics and qualitative analysis. It includes a description of chemometric methods, their real-life applications in qualitative analysis, challenges and possible solutions. Undoubtedly, the role of chemometrics will become pivotal in the future when more possibilities of qualitative analysis will be explored and new chemometric approaches will be developed for high-dimensional data. © 2015 Elsevier B.V.


Szymanska E.,TI COAST | Szymanska E.,Radboud University Nijmegen | Brown P.A.,TI COAST | Brown P.A.,Radboud University Nijmegen | And 5 more authors.
Analytical Chemistry | Year: 2015

Real-time measurements of many low-abundance volatile organic compounds (VOCs) in breath and air samples are already feasible due to progress in analytical technologies, such as proton transfer reaction mass spectrometry (PTR-MS). Nevertheless, the information content of real-time measurements is not fully exploited, due to the lack of suitable data handling methods. This study develops a data scientific procedure to enhance data analysis and interpretation of longitudinal, multivariate data sets from real-time, in vivo, aroma-release studies. The developed procedure includes an automated data preprocessing and a multivariate assessment of the test panel performance. A large multifactorial PTR-MS data set is investigated that includes four experimental protocols, two tested food products, four aroma compounds, and eight panelists. Real-time measurements are converted into standardized breath profiles by preprocessing, and 10 kinetic parameters are derived. Next to this, panel performance is evaluated per experimental protocol and food product. Comprehensive information about panel performance, individual panelists, studied products, aroma compounds, and kinetic parameters is extracted, demonstrating the great value of the developed approach. © 2015 American Chemical Society.


PubMed | Unilever, Radboud University Nijmegen and TI COAST
Type: Journal Article | Journal: Analytical chemistry | Year: 2015

Real-time measurements of many low-abundance volatile organic compounds (VOCs) in breath and air samples are already feasible due to progress in analytical technologies, such as proton transfer reaction mass spectrometry (PTR-MS). Nevertheless, the information content of real-time measurements is not fully exploited, due to the lack of suitable data handling methods. This study develops a data scientific procedure to enhance data analysis and interpretation of longitudinal, multivariate data sets from real-time, in vivo, aroma-release studies. The developed procedure includes an automated data preprocessing and a multivariate assessment of the test panel performance. A large multifactorial PTR-MS data set is investigated that includes four experimental protocols, two tested food products, four aroma compounds, and eight panelists. Real-time measurements are converted into standardized breath profiles by preprocessing, and 10 kinetic parameters are derived. Next to this, panel performance is evaluated per experimental protocol and food product. Comprehensive information about panel performance, individual panelists, studied products, aroma compounds, and kinetic parameters is extracted, demonstrating the great value of the developed approach.


Stationary-phase-assisted modulation is used to overcome one of the limitations of contemporary comprehensive two-dimensional liquid chromatography, which arises from the combination of a first-dimension column that is typically narrow and long and a second-dimension column that is wide and short. Shallow gradients at low flow rates are applied in the first dimension, whereas fast analyses (at high flow rates) are required in the second dimension. Limitations of this approach include a low sample capacity of the first-dimension column and a high dilution of the sample in the complete system. Moreover, the relatively high flow rates used for the second dimension make direct (splitless) hyphenation to mass spectrometry difficult. In the present study we demonstrate that stationary-phase-assisted modulation can be implemented in an online comprehensive two-dimensional LC (LC LC) setup to shift this paradigm. The proposed active modulation makes it possible to choose virtually any combination of first- and second-dimension column diameters without loss in system performance. In the current setup, a 0.30 mm internal diameter first-dimension column with a relatively high loadability is coupled to a 0.075 mm internal diameter second-dimension column. This actively modulated system is coupled to a nanoelectrospray high-resolution mass spectrometer and applied for the separation of the tryptic peptides of a six-protein mixture and for the proteome-wide analyses of yeast from Saccharomyces cerevisiae. In the latter application, about 20000 MS/MS spectra are generated within 24 h analysis time, resulting in the identification of 701 proteins.

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