scholarly journals Volatile organic compound breath signatures of children with cystic fibrosis by real-time SESI-HRMS

2020 ◽  
Vol 6 (1) ◽  
pp. 00171-2019 ◽  
Author(s):  
Ronja Weber ◽  
Naemi Haas ◽  
Astghik Baghdasaryan ◽  
Tobias Bruderer ◽  
Demet Inci ◽  
...  
Keyword(s):  
Cystic Fibrosis ◽  
High Resolution ◽  
Organic Compound ◽  
Real Time ◽  
Volatile Organic Compound ◽  
Lung Damage ◽  
Support Vector ◽  
P Value ◽  
Large Set ◽  
Volatile Organic

Early pulmonary infection and inflammation result in irreversible lung damage and are major contributors to cystic fibrosis (CF)-related morbidity. An easy to apply and noninvasive assessment for the timely detection of disease-associated complications would be of high value. We aimed to detect volatile organic compound (VOC) breath signatures of children with CF by real-time secondary electrospray ionisation high-resolution mass spectrometry (SESI-HRMS).A total of 101 children, aged 4–18 years (CF=52; healthy controls=49) and comparable for sex, body mass index and lung function were included in this prospective cross-sectional study. Exhaled air was analysed by a SESI-source linked to a high-resolution time-of-flight mass spectrometer. Mass spectra ranging from m/z 50 to 500 were recorded.Out of 3468 m/z features, 171 were significantly different in children with CF (false discovery rate adjusted p-value of 0.05). The predictive ability (CF versus healthy) was assessed by using a support-vector machine classifier and showed an average accuracy (repeated cross-validation) of 72.1% (sensitivity of 77.2% and specificity of 67.7%).This is the first study to assess entire breath profiles of children with SESI-HRMS and to extract sets of VOCs that are associated with CF. We have detected a large set of exhaled molecules that are potentially related to CF, indicating that the molecular breath of children with CF is diverse and informative.

Mid-Infrared Chalcogenide Waveguides for Real-Time and Nondestructive Volatile Organic Compound Detection

2018 ◽  
Vol 91 (1) ◽  
pp. 817-822 ◽  
Author(s):  
Tiening Jin ◽  
Junchao Zhou ◽  
Hao-Yu Greg Lin ◽  
Pao Tai Lin
Keyword(s):  
Organic Compound ◽  
Real Time ◽  
Volatile Organic Compound ◽  
Mid Infrared ◽  
Volatile Organic

scholarly journals P230 Exposure to cigarette smoke in a cystic fibrosis cohort - distinctive volatile organic compound profiles

2019 ◽  
Vol 18 ◽  
pp. S122
Author(s):  
T. Goddard ◽  
N. Darmawardana ◽  
R. Yazbek ◽  
J. Martin ◽  
J. Morton ◽  
...  
Keyword(s):  
Cystic Fibrosis ◽  
Organic Compound ◽  
Cigarette Smoke ◽  
Volatile Organic Compound ◽  
Volatile Organic

scholarly journals Detection of β-alanyl aminopeptidase as a biomarker for Pseudomonas aeruginosa in the sputum of patients with cystic fibrosis using exogenous volatile organic compound evolution

RSC Advances ◽  
2020 ◽  
Vol 10 (18) ◽  
pp. 10634-10645 ◽  
Author(s):  
Ryan Thompson ◽  
Dominic Stephenson ◽  
Hannah E. Sykes ◽  
John D. Perry ◽  
Stephen P. Stanforth ◽  
...  
Keyword(s):  
Cystic Fibrosis ◽  
Pseudomonas Aeruginosa ◽  
Organic Compound ◽  
Volatile Organic Compound ◽  
Analytical Method ◽  
Lung Transplant ◽  
Transplant Patients ◽  
Volatile Organic ◽  
Alanyl Aminopeptidase

A novel, rapid and sensitive analytical method has been developed and applied to 105 sputum samples from patients with cystic fibrosis, including 5 samples from post-lung transplant patients.

scholarly journals Determining the Geographical Origin of Crude Palm Oil with the Combined Use of GC-IMS Fingerprinting and Chemometrics

2020 ◽  
Author(s):  
Kirstie Goggin ◽  
Emma Brodrick ◽  
Alfian Nur Wicaksono ◽  
James Covington ◽  
Antony N Davies ◽  
...  
Keyword(s):  
Logistic Regression ◽  
Organic Compound ◽  
Palm Oil ◽  
Volatile Organic Compound ◽  
Geographical Origin ◽  
Peninsular Malaysia ◽  
Support Vector ◽  
Crude Palm Oil ◽  
Sparse Logistic Regression ◽  
Volatile Organic

<p>Current administrative controls used to verify geographical provenance within palm oil supply chains require enhancement and strengthening by more robust analytical methods. In this study, the application of volatile organic compound fingerprinting, in combination with five different analytical classification models, has been used to verify the regional geographical provenance of crude palm oil samples. For this purpose, 108 crude palm oil samples were collected from two regions within Malaysia, namely Peninsular Malaysia (32) and Sabah (76). Samples were analysed by gas chromatography-ion mobility spectrometry (GC-IMS) and the five predictive models (Sparse Logistic Regression, Random Forests, Gaussian Processes, Support Vector Machines, and Artificial Neural Networks) were built and applied. Models were validated using 10-fold cross-validation. The Area Under Curve (AUC) measure was used as a summary indicator of the performance of each classifier. All models performed well (AUC 0.96) with the Sparse Logistic Regression model giving best performance (AUC = 0.98). This demonstrates that the verification of the geographical origin of crude palm oil is feasible by volatile organic compound fingerprinting, using GC-IMS supported by chemometric analysis. </p>

scholarly journals Exploring new dimensions in cadaveric decomposition odour analysis

2015 ◽  
Vol 7 (6) ◽  
pp. 2287-2294 ◽  
Author(s):  
P.-H. Stefanuto ◽  
K. A. Perrault ◽  
R. M. Lloyd ◽  
B. Stuart ◽  
T. Rai ◽  
...  
Keyword(s):  
Mass Spectrometry ◽  
Gas Chromatography ◽  
High Resolution ◽  
Organic Compound ◽  
Volatile Organic Compound ◽  
Forensic Sciences ◽  
Two Dimensional ◽  
Resolution Time ◽  
Flight Mass Spectrometry ◽  
Volatile Organic

This study demonstrates the first documented use of comprehensive two-dimensional gas chromatography – high-resolution time-of-flight mass spectrometry (GC×GC-HRTOFMS) for volatile organic compound analysis in the forensic sciences.

Tracing ecosystem scale interactions of volatile organic compound (VOC) and CO2 emissions by position-specific and whole ecosystem isotope labelling

2020 ◽  
Author(s):  
Christiane Werner ◽  
Nemiah S. Ladd ◽  
Laura Meredith ◽  
Keyword(s):  
Organic Compound ◽  
Secondary Metabolism ◽  
Real Time ◽  
Volatile Organic Compound ◽  
Carbon Allocation ◽  
Ecosystem Processes ◽  
Scale Interactions ◽  
Biosphere 2 ◽  
Primary And Secondary Metabolism ◽  
Volatile Organic

&lt;p&gt;Ecosystem processes present a complex interplay between different components, such as vegetation, soil, and the rhizosphere. All these different components can emit (or even uptake) a plethora of volatile organic compound (BVOC) with highly dynamic response to environmental changes. However, processes controlling carbon allocation into primary and secondary metabolism such as VOC synthesis or respiratory CO&lt;sub&gt;2&lt;/sub&gt; emission remain unclear. De novo synthesis of BVOC depends on the availability of carbon, as well as energy provided by primary metabolism. Thus, carbon allocation may compete between primary and secondary metabolism, which are linked via a number of interfaces including the central metabolite pyruvate. It is the main substrate fulling respiration, but also a substrate for a large array of secondary pathways leading to the biosynthesis of many volatile organic compounds, such as volatile isoprenoids, oxygenated VOCs. Within the European Research Council (ERC) Project VOCO we developed a novel technological basis to couple CO&lt;sub&gt;2&lt;/sub&gt; fluxes with VOC emissions based on simultaneous real-time measurements of stable carbon isotope composition of branch, root, and soil respired CO&lt;sub&gt;2&lt;/sub&gt; and VOC fluxes (Fasbender et al. 2018). Position specific &lt;sup&gt;13&lt;/sup&gt;C-labeled pyruvate feeding experiments are used to trace partitioning within the metabolic branching points into VOCs versus CO&lt;sub&gt;2&lt;/sub&gt; emissions, bridging scales from sub-molecular to whole-plant and ecosystem processes. Positional 13C-labelling will trace real-time sub-molecular carbon investment into VOCs and CO&lt;sub&gt;2&lt;/sub&gt;, enabling mechanistic descriptions of the underlying biochemical pathways coupling anabolic and catabolic processes.&lt;/p&gt;&lt;p&gt;To trace ecosystem scale interactions, we implemented a whole-ecosystem labelling approach in the world&amp;#8217;s largest controlled growth facility: the Biosphere 2 Tropical Rainforest. In the Biosphere 2 Water, Atmosphere, and Life Dynamics (B2-WALD) experiment, we applied an ecosystem scale drought and tracing carbon allocation and dynamics of VOC, CO&lt;sub&gt;2&lt;/sub&gt; and H&lt;sub&gt;2&lt;/sub&gt;O fluxes from leaf, root, soil and atmospheric scales. The overarching goal of B2-WALD is to track, biological mechanisms controlling the fate of CO&lt;sub&gt;2&lt;/sub&gt;, VOC and water cycling in an ecosystem under change in an interdisciplinary approach. This comprehensive data set will be used for carbon and water partitioning from the metabolic to ecosystem scale&lt;/p&gt;&lt;p&gt;Fasbender L., et al. (&lt;strong&gt;2018&lt;/strong&gt;). A novel approach combining PTR-TOF-MS, &lt;sup&gt;13&lt;/sup&gt;CO&lt;sub&gt;2&lt;/sub&gt; laser spectroscopy and &lt;sup&gt;13&lt;/sup&gt;C-metabolite labelling to trace real-time carbon allocation into BVOCs and respiratory CO&lt;sub&gt;2&lt;/sub&gt;. PLOS One,13: e0204398&lt;/p&gt;&lt;p&gt;&amp;#160;&lt;/p&gt;

scholarly journals Determining the Geographical Origin of Crude Palm Oil with the Combined Use of GC-IMS Fingerprinting and Chemometrics

2020 ◽  
Author(s):  
Kirstie Goggin ◽  
Emma Brodrick ◽  
Alfian Nur Wicaksono ◽  
James Covington ◽  
Antony N Davies ◽  
...  
Keyword(s):  
Logistic Regression ◽  
Organic Compound ◽  
Palm Oil ◽  
Volatile Organic Compound ◽  
Geographical Origin ◽  
Peninsular Malaysia ◽  
Support Vector ◽  
Crude Palm Oil ◽  
Sparse Logistic Regression ◽  
Volatile Organic

<p>Current administrative controls used to verify geographical provenance within palm oil supply chains require enhancement and strengthening by more robust analytical methods. In this study, the application of volatile organic compound fingerprinting, in combination with five different analytical classification models, has been used to verify the regional geographical provenance of crude palm oil samples. For this purpose, 108 crude palm oil samples were collected from two regions within Malaysia, namely Peninsular Malaysia (32) and Sabah (76). Samples were analysed by gas chromatography-ion mobility spectrometry (GC-IMS) and the five predictive models (Sparse Logistic Regression, Random Forests, Gaussian Processes, Support Vector Machines, and Artificial Neural Networks) were built and applied. Models were validated using 10-fold cross-validation. The Area Under Curve (AUC) measure was used as a summary indicator of the performance of each classifier. All models performed well (AUC 0.96) with the Sparse Logistic Regression model giving best performance (AUC = 0.98). This demonstrates that the verification of the geographical origin of crude palm oil is feasible by volatile organic compound fingerprinting, using GC-IMS supported by chemometric analysis. </p>

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