scholarly journals Detecting Pulmonary Oxygen Toxicity Using eNose Technology and Associations between Electronic Nose and Gas Chromatography–Mass Spectrometry Data

Metabolites ◽  
2019 ◽  
Vol 9 (12) ◽  
pp. 286
Author(s):  
Thijs T. Wingelaar ◽  
Paul Brinkman ◽  
Rianne de Vries ◽  
Pieter-Jan A.M. van Ooij ◽  
Rigo Hoencamp ◽  
...  
Keyword(s):  
Mass Spectrometry ◽  
Gas Chromatography ◽  
Electronic Nose ◽  
Oxygen Toxicity ◽  
Partial Least Square ◽  
Least Square ◽  
Sensor Data ◽  
Gas Chromatography Mass Spectrometry ◽  
Exhaled Breath ◽  
Chromatography Mass Spectrometry

Exposure to oxygen under increased atmospheric pressures can induce pulmonary oxygen toxicity (POT). Exhaled breath analysis using gas chromatography–mass spectrometry (GC–MS) has revealed that volatile organic compounds (VOCs) are associated with inflammation and lipoperoxidation after hyperbaric–hyperoxic exposure. Electronic nose (eNose) technology would be more suited for the detection of POT, since it is less time and resource consuming. However, it is unknown whether eNose technology can detect POT and whether eNose sensor data can be associated with VOCs of interest. In this randomized cross-over trial, the exhaled breath from divers who had made two dives of 1 h to 192.5 kPa (a depth of 9 m) with either 100% oxygen or compressed air was analyzed, at several time points, using GC–MS and eNose. We used a partial least square discriminant analysis, eNose discriminated oxygen and air dives at 30 min post dive with an area under the receiver operating characteristics curve of 79.9% (95%CI: 61.1–98.6; p = 0.003). A two-way orthogonal partial least square regression (O2PLS) model analysis revealed an R² of 0.50 between targeted VOCs obtained by GC–MS and eNose sensor data. The contribution of each sensor to the detection of targeted VOCs was also assessed using O2PLS. When all GC–MS fragments were included in the O2PLS model, this resulted in an R² of 0.08. Thus, eNose could detect POT 30 min post dive, and the correlation between targeted VOCs and eNose data could be assessed using O2PLS.

scholarly journals Gas Chromatography-Mass Spectrometry Coupled with Multivariate Statistical Analysis to Identify the Alpha Glucosidase Inhibitors from Flesh of Salacca zalacca Fruits and Their Molecular Docking Studies

2021 ◽  
Vol 2021 ◽  
pp. 1-10
Author(s):  
Mohammed S. M. Saleh ◽  
Mohammad Jamshed Siddiqui ◽  
Nabil Ali Al-Mekhlafi ◽  
Hussah Abdullah Alshwyeh ◽  
Ahmed Mediani ◽  
...  
Keyword(s):  
Mass Spectrometry ◽  
Gas Chromatography ◽  
Molecular Docking ◽  
Palmitic Acid ◽  
Partial Least Square ◽  
Least Square ◽  
Gas Chromatography Mass Spectrometry ◽  
Bioactive Metabolites ◽  
Inhibition Activity ◽  
Chromatography Mass Spectrometry

Fruit of salak (Salaaca zalacca) is traditionally used and commercialized as an antidiabetic agent. However, scientific evidence to prove this folk claim is quite lacking. Therefore, this research was aimed to evaluate the α-glucosidase inhibition activity of S. zalacca fruit and identify the bioactive compounds. The fruits were extracted by different ratios of ethanol and water (0, 20, 40, 60, 80, 100%, v/v) to get E0 (100% water), E20 (20% ethanol), E40 (40% ethanol), E60 (60% ethanol), E80 (80% ethanol), and E100 (100% ethanol) extracts. The extracts obtained were subjected to the α-glucosidase inhibitory assay. Gas chromatography-mass spectrometry- (GC-MS-) based metabolomics approach was used in profiling the bioactive metabolites present in the extracts. Orthogonal partial least square (OPLS) was used to correlate GC-MS data and α-glucosidase assay results to identify the possible chemical markers. All active compounds identified were subjected to molecular docking. The extracts from the S. zalacca fruit showed potent inhibition activity against α-glucosidase. The IC50 values from the α-glucosidase inhibitory assay ranged between 16 and 275 µg/ml. Overall, E60 displayed significantly higher α-glucosidase inhibition activity, while E0 showed the lowest α-glucosidase inhibition activity. Major compounds detected in S. zalacca fruits were sugars, fatty acids, and sterols, including myo-inositol, palmitic acid, stearic acid, and β-sitosterol. Moreover, the results obtained from molecular docking indicated that palmitic acid and β-sitosterol were close to the active side of the enzyme. Some of the residues that interacted include HID295, ASN259, LEU313, LYS125, PHE159, VAL216, PHE178, TYR72, TYR158, HIE315, ARG315, and PHE303. The bioassay result strongly suggests that E60 extract from S. zalacca fruits has potential α-glucosidase inhibitory activity. The hydrophobic compounds, including palmitic acid and β-sitosterol, were found to induce the α-glucosidase inhibition activity.

scholarly journals Comprehensive Two-Dimensional Gas Chromatography–Mass Spectrometry Analysis of Exhaled Breath Compounds after Whole Grain Diets

Molecules ◽  
2021 ◽  
Vol 26 (9) ◽  
pp. 2667
Author(s):  
Kaisa Raninen ◽  
Ringa Nenonen ◽  
Elina Järvelä-Reijonen ◽  
Kaisa Poutanen ◽  
Hannu Mykkänen ◽  
...  
Keyword(s):  
Mass Spectrometry ◽  
Gas Chromatography ◽  
Metabolic Effects ◽  
Mass Spectrometry Analysis ◽  
Gas Chromatography Mass Spectrometry ◽  
Wheat Bread ◽  
Exhaled Breath ◽  
Two Dimensional ◽  
Whole Grain ◽  
Chromatography Mass Spectrometry

Exhaled breath is a potential noninvasive matrix to give new information about metabolic effects of diets. In this pilot study, non-targeted analysis of exhaled breath volatile organic compounds (VOCs) was made by comprehensive two-dimensional gas chromatography–mass spectrometry (GCxGC-MS) to explore compounds relating to whole grain (WG) diets. Nine healthy subjects participated in the dietary intervention with parallel crossover design, consisting of two high-fiber diets containing whole grain rye bread (WGR) or whole grain wheat bread (WGW) and 1-week control diets with refined wheat bread (WW) before both diet periods. Large interindividual differences were detected in the VOC composition. About 260 VOCs were detected from exhaled breath samples, in which 40 of the compounds were present in more than half of the samples. Various derivatives of benzoic acid and phenolic compounds, as well as some furanones existed in exhaled breath samples only after the WG diets, making them interesting compounds to study further.

scholarly journals Characterization of α-Glucosidase Inhibitors from Clinacanthus nutans Lindau Leaves by Gas Chromatography-Mass Spectrometry-Based Metabolomics and Molecular Docking Simulation

Molecules ◽  
2018 ◽  
Vol 23 (9) ◽  
pp. 2402 ◽  
Author(s):  
Suganya Murugesu ◽  
Zalikha Ibrahim ◽  
Qamar-Uddin Ahmed ◽  
Nik-Idris Nik Yusoff ◽  
Bisha-Fathamah Uzir ◽  
...  
Keyword(s):  
Mass Spectrometry ◽  
Gas Chromatography ◽  
Molecular Docking ◽  
Acid Methyl Ester ◽  
Docking Simulation ◽  
Partial Least Square ◽  
Least Square ◽  
Gas Chromatography Mass Spectrometry ◽  
Glucosidase Inhibitors ◽  
Clinacanthus Nutans

Background: Clinacanthus nutans (C. nutans) is an Acanthaceae herbal shrub traditionally consumed to treat various diseases including diabetes in Malaysia. This study was designed to evaluate the α-glucosidase inhibitory activity of C. nutans leaves extracts, and to identify the metabolites responsible for the bioactivity. Methods: Crude extract obtained from the dried leaves using 80% methanolic solution was further partitioned using different polarity solvents. The resultant extracts were investigated for their α-glucosidase inhibitory potential followed by metabolites profiling using the gas chromatography tandem with mass spectrometry (GC-MS). Results: Multivariate data analysis was developed by correlating the bioactivity, and GC-MS data generated a suitable partial least square (PLS) model resulting in 11 bioactive compounds, namely, palmitic acid, phytol, hexadecanoic acid (methyl ester), 1-monopalmitin, stigmast-5-ene, pentadecanoic acid, heptadecanoic acid, 1-linolenoylglycerol, glycerol monostearate, alpha-tocospiro B, and stigmasterol. In-silico study via molecular docking was carried out using the crystal structure Saccharomyces cerevisiae isomaltase (PDB code: 3A4A). Interactions between the inhibitors and the protein were predicted involving residues, namely LYS156, THR310, PRO312, LEU313, GLU411, and ASN415 with hydrogen bond, while PHE314 and ARG315 with hydrophobic bonding. Conclusion: The study provides informative data on the potential α-glucosidase inhibitors identified in C. nutans leaves, indicating the plant’s therapeutic effect to manage hyperglycemia.

scholarly journals Rapid Non-Destructive Quantification of Eugenol in Curdlan Biofilms by Electronic Nose Combined with Gas Chromatography-Mass Spectrometry

Sensors ◽  
2020 ◽  
Vol 20 (16) ◽  
pp. 4441
Author(s):  
Lu Han ◽  
Jingyi Zhu ◽  
Xia Fan ◽  
Chong Zhang ◽  
Kang Tu ◽  
...  
Keyword(s):  
Mass Spectrometry ◽  
Gas Chromatography ◽  
Prediction Model ◽  
Electronic Nose ◽  
Quantitative Method ◽  
Gas Chromatography Mass Spectrometry ◽  
Support Vector ◽  
Linear Discriminant ◽  
Chromatography Mass Spectrometry ◽  
Non Destructive

Eugenol is hepatotoxic and potentially hazardous to human health. This paper reports on a rapid non-destructive quantitative method for the determination of eugenol concentration in curdlan (CD) biofilms by electronic nose (E-nose) combined with gas chromatography-mass spectrometry (GC-MS). Different concentrations of eugenol were added to the film-forming solution to form a series of biofilms by casting method, and the actual eugenol concentration in the biofilm was determined. Analysis of the odor collected on the biofilms was carried out by GC-MS and an E-nose. The E-nose data was subjected to principal component analysis (PCA) and linear discriminant analysis (LDA) in order to establish a discriminant model for determining eugenol concentrations in the biofilms. Further analyses involving the application of all sensors and featured sensors, the prediction model-based partial least squares (PLS) and support vector machines (SVM) were carried out to determine eugenol concentration in the CD biofilms. The results showed that the optimal prediction model for eugenol concentration was obtained by PLS at R2p of 0.952 using 10 sensors. The study described a rapid, non-destructive detection and quantitative method for determining eugenol concentration in bio-based packaging materials.

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