Analysis of volatile organic compounds in human urine by headspace gas chromatography–mass spectrometry with a multipurpose sampler

Wahl, Hans Günther; Hoffmann, Andreas; Luft, D; Liebich, H.M.

doi:10.1016/s0021-9673(99)00017-5

Cited by 84 publications

(60 citation statements)

References 33 publications

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“…Volatile organic compounds in urine result from food, drinks, air pollutants, drugs, bacterial interaction within the body, and metabolic processes 70,71 . Studies on the profiles of volatile metabolites in urine have demonstrated the presence of compounds of wide range of functional groups including alcohols, aldehydes, ketones, oxygen-and nitrogencontaining compounds, sulfur-containing compounds, and other heterocyclic compounds [70][71][72][73] .…”

Section: Figure 24 Schematic Of Urine Productionmentioning

confidence: 99%

“…Studies on the profiles of volatile metabolites in urine have demonstrated the presence of compounds of wide range of functional groups including alcohols, aldehydes, ketones, oxygen-and nitrogencontaining compounds, sulfur-containing compounds, and other heterocyclic compounds [70][71][72][73] . The VOCs in the headspace of urine have been studied in a variety of fields including toxicology (drug detection and recovery) [74][75][76] , occupational and environmental exposures [77][78][79][80] , and metabolic investigations 70,71,81 . Early studies on the urinary VOC profiles showed that there was a significant variance between different individuals, but intra-person urinary VOC profiles remained constant over time even with variation factors such as diet, exercise, circadian and seasonal changes 73 .…”

Section: Figure 24 Schematic Of Urine Productionmentioning

confidence: 99%

“…Early studies on the urinary VOC profiles showed that there was a significant variance between different individuals, but intra-person urinary VOC profiles remained constant over time even with variation factors such as diet, exercise, circadian and seasonal changes 73 . Disturbances of volatile compounds found in urine have been associated with physiological disorders including diabetes mellitus, liver and kidney disease, and trimethylaminuria 71,82,83 . Divinylbenzene/Carboxen/Polydimethylsiloxane (DVB/CAR/PDMS) (50/30 μm film thickness) SPME fibers and SPME fiber holders were obtained from SUPELCO (Bellefonte, PA, USA).…”

Section: Figure 24 Schematic Of Urine Productionmentioning

confidence: 99%

“…While many of the reported VOCs are also present in healthy individuals, studies have reported an elevation in the levels of these compounds in patients with asthma [91][92][93] , diabetes 56,94 , liver and kidney disease/impairment 70,71,83 , gastrointestinal diseases 95 , and oxidative stress 56,96 . This disease is an autosomal recessively inherited disorder in which branched-chain Table 13.…”

Section: Scent Biomarkers For Diseasesmentioning

confidence: 99%

“…Common names for some of the compounds are given in parentheses and italicized. Many of the presented compounds have been previously reported to be volatile emanation compounds of human skin 5,14,28,29,123 , saliva 127 , breath 44,48,97,128 , volatile constituents of human blood 18,62,66,67 , and urine [70][71][72] . Compounds denoted by "en" are possibly endogenous compounds, while compounds denoted by "ex" are possibly of exogenous origin.…”

Section: Equationmentioning

confidence: 99%

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Comparison of Medical and Forensic Profiling Potential of Volatile Biomarkers from Different Biological Specimens from Individuals and Across Populations

Kusano¹

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Section: Figure 24 Schematic Of Urine Productionmentioning

confidence: 99%

Section: Figure 24 Schematic Of Urine Productionmentioning

confidence: 99%

Section: Figure 24 Schematic Of Urine Productionmentioning

confidence: 99%

Section: Scent Biomarkers For Diseasesmentioning

confidence: 99%

Section: Equationmentioning

confidence: 99%

See 3 more Smart Citations

Comparison of Medical and Forensic Profiling Potential of Volatile Biomarkers from Different Biological Specimens from Individuals and Across Populations

Kusano¹

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Urinary biomarker and treatment mechanism of Rhizoma Alismatis on hyperlipidemia

Miao

Zhang

Chen

et al. 2016

Biomedical Chromatography

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Rhizoma Alismatis (RA), a diuretic in Asia and Europe, was found to possess anti-hyperlipidemic activity. Since the biomarkers and mechanisms of RA in the treatment of hyperlipidemia are inadequate, ultra-performance liquid chromatography coupled with quadrupole time-of-flight synapt high-definition mass spectrometry and multivariate data analysis were employed to investigate the urinary metabolomics of RA on hyperlipidemic rats induced by high-fat diet. The metabolic profile of RA-treated hyperlipidemic group located between control and diet-induced hyperlipidemic groups. Nineteen metabolites with significant fluctuations were identified as potential biomarkers related to the hyperlipidemia and anti-hyperlipidemia of RA using partial least-squares-discriminate analysis, heatmap analysis and correlation coefficient analysis. The fluctuations of these biomarkers represented disturbances in amino acid metabolism, purine metabolism, pyrimidine metabolism and energy metabolism. After RA treatment, these perturbed metabolites were restored to normal or nearly normal levels. RA can alleviate high-fat diet-induced dysfunctions in these metabolic pathways.

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Support vector machine classification of volatile organic compounds based on narrow‐band spectroscopic data

Argyris

Filippi

Syvridis

2014

Journal of Chemometrics

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In this work, a list of volatile organic compounds (VOCs) that are associated with targets susceptible to versatile security issues – such as drug trafficking, explosives carrying, or human presence in forbidden areas – are monitored and discriminated through algorithmic processing of their midinfrared (MIR) spectroscopic properties. Usually, such tasks are relatively straightforward by identifying the absorption peaks of the investigated compounds in extended spectral recordings, from a few hundred up to many thousands of wavenumbers (cm−1). Nevertheless, the physical mechanisms and instrumentation for obtaining so broad spectral profiles may prove to be complex, especially in field measurements, while data acquisition and processing may also prove to be time‐consuming. In the proposed approach, support vector machine algorithmic training is applied in order to evaluate the potential of exploiting very narrow spectral MIR absorption bands that are optimal for reliable prediction analysis and training. The probabilistic classification performance of these bands is evaluated and compared with the prediction performance when using wider MIR absorption spectra. Depending on the data set and the list of the associated VOCs, spectral data recording within a span up to several tens of wavenumbers – at regions where absorption is detectable – prove to be enough for efficient VOC classification. Copyright © 2014 John Wiley & Sons, Ltd.

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Analysis of volatile organic compounds in human urine by headspace gas chromatography–mass spectrometry with a multipurpose sampler

Cited by 84 publications

References 33 publications

Comparison of Medical and Forensic Profiling Potential of Volatile Biomarkers from Different Biological Specimens from Individuals and Across Populations

Comparison of Medical and Forensic Profiling Potential of Volatile Biomarkers from Different Biological Specimens from Individuals and Across Populations

Urinary biomarker and treatment mechanism of Rhizoma Alismatis on hyperlipidemia

Support vector machine classification of volatile organic compounds based on narrow‐band spectroscopic data

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