Data correlation in on-line solid-phase extraction-gas chromatography-atomic emission/mass spectrometric detection of unknown microcontaminants

Hankemeier, Th.; Rozenbrand, Johan; Abhadur, M.; Vreuls, J. J.; Brinkman, U.A.Th.

doi:10.1007/bf02467683

Cited by 24 publications

(3 citation statements)

References 23 publications

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“…Methods based on both SPE-GC and LLE-GC have been developed for a variety of environmental determinations, and SPE-GC has also been used for the analysis of drugs in biological fluids [4,5,6,7,8,9,10,11,12,13,14,15,16,17,18,19,20,21,22,23,24,25,26,27,28,29,30,31,32,33,34,35,36,37,38,39,40,41,42,43,44,53,54,55,56,57,58,59,60,61,62,…”

Section: Liquid Samplesmentioning

confidence: 99%

Approaches for on-line coupling of extraction and chromatography

Hyötyläinen

Riekkola

2004

Analytical and Bioanalytical Chemistry

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This review provides an overview of the approaches available in order to perform on-line coupling of various extraction techniques with liquid and gas chromatography, for the analysis of semivolatile and nonvolatile analytes in liquid and solid samples. The main focus is on the instrumental set-up of these techniques. Selected real applications are described by way of illustration. The extraction methods suitable for on-line coupling covered in this review are: liquid-liquid extraction, solid-phase extraction, membrane-based techniques, pressurised liquid extraction, supercritical fluid extraction, and microwave- and sonication-assisted extractions. The following systems are not covered in this review: on-line coupled solid-phase extraction-liquid chromatography, purge-and-trap-GC, and membrane extraction with a sorbent interface-GC.

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Section: Liquid Samplesmentioning

confidence: 99%

Approaches for on-line coupling of extraction and chromatography

Hyötyläinen

Riekkola

2004

Analytical and Bioanalytical Chemistry

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“…The occurrence of prepeaks [16] was used to determine the flooded zone. This zone is defined as the length of retention gap that is occupied by the solvent film (in cmgL-1).…”

Section: Evaporation Profile For Large-volume Injectionsmentioning

confidence: 99%

Investigations on analyte losses in systems suited for large-volume on-column injections

et al. 2001

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Use o~ a large-volume injection system with a solvent vapour exit (SVE) requires optimisation. An appropriate strategy is to determine the evaporation rate by increasing the injection time at a fixed injection speed, injection temperature and head pressure. When measuring the flow rate in the carrier gas supply line to the on-column injector, optimisation can be very rapid: some five injections of pure solvent will be sufficient.When working under pa~ially concurrent solveni evaporation conditions, loss of volatiles is often observed if no retaining precolumn is used be~een the retention gap and the SVE. To investigate the requirements (length anct stationary phase) of the retaining precolumn, C8-C18 n-alkanes in n-hexane were used. The minimum length of the retaining precolumn (0.32 mm diameter) needed to prevent substantial losses of volatiles was 2 m. Experiments with retaining precolumns with ancl without stationary phase gave identical results. This shows that there is no need to coat the capillary as it only acts as a restrictor.

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“…Typical mining processes include peak detection [9], [17], [22], [25], spectrum alignment [31], data correlation [15], biomarker discovery [14], [20], among others. In this paper, we propose a new approach, called PeakID, for identifying peaks in liquid chromatographymass spectrometry (LC-MS) data.…”

mentioning

confidence: 99%

Fast Elastic Peak Detection for Mass Spectrometry Data Mining

Zhang

Shasha

Song

et al. 2012

IEEE Trans. Knowl. Data Eng.

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Abstract-We study a data mining problem concerning the elastic peak detection in 2D liquid chromatography-mass spectrometry (LC-MS) data. These data can be modeled as time series, in which the X-axis represents time points and the Y -axis represents intensity values. A peak occurs in a set of 2D LC-MS data when the sum of the intensity values in a sliding time window exceeds a user-determined threshold. The elastic peak detection problem is to locate all peaks across multiple window sizes of interest in the data set. We propose a new data structure, called a Shifted Aggregation Tree or AggTree for short, and use the data structure to find the different peaks. Our method, called PeakID, solves the elastic peak detection problem in 2D LC-MS data yielding neither false positives nor false negatives. The method works by first constructing an AggTree in a bottom-up manner from the given data set, and then searching the AggTree for the peaks in a top-down manner. We describe a state-space algorithm for finding the topology and structure of an efficient AggTree to be used by PeakID. Our experimental results demonstrate the superiority of the proposed method over other methods on both synthetic and real-world data.Index Terms-Knowledge discovery from LC-MS data, time series data mining, bioinformatics, computational proteomics, algorithms and data structures.

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Data correlation in on-line solid-phase extraction-gas chromatography-atomic emission/mass spectrometric detection of unknown microcontaminants

Cited by 24 publications

References 23 publications

Approaches for on-line coupling of extraction and chromatography

Approaches for on-line coupling of extraction and chromatography

Investigations on analyte losses in systems suited for large-volume on-column injections

Fast Elastic Peak Detection for Mass Spectrometry Data Mining

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