scholarly journals Automated Screening and Filtering Scripts for GC×GC-TOFMS Metabolomics Data

Separations ◽  
2021 ◽  
Vol 8 (6) ◽  
pp. 84
Author(s):  
Seo Lin Nam ◽  
A. Paulina de la Mata ◽  
James J. Harynuk
Keyword(s):  
High Speed ◽  
Methyl Esters ◽  
Gas Chromatography Mass Spectrometry ◽  
Retention Data ◽  
Metabolomics Data ◽  
Mass Spectrometers ◽  
Logical Operations ◽  
Unit Mass Resolution ◽  
Automated Screening ◽  
Resolution Mass

Comprehensive two-dimensional gas chromatography mass spectrometry (GC×GC-MS) is a powerful tool for the analysis of complex mixtures, and it is ideally suited to discovery studies where the entire sample is potentially of interest. Unfortunately, when unit mass resolution mass spectrometers are used, many detected compounds have spectra that do not match well with libraries. This could be due to the compound not being in the library, or the compound having a weak/nonexistent molecular ion cluster. While high-speed, high-resolution mass spectrometers, or ion sources with softer ionization than 70 eV electron impact (EI) may help with some of this, many GC×GC systems presently in use employ low-resolution mass spectrometers and 70 eV EI ionization. Scripting tools that apply filters to GC×GC-TOFMS data based on logical operations applied to spectral and/or retention data have been used previously for environmental and petroleum samples. This approach rapidly filters GC×GC-TOFMS peak tables (or raw data) and is available in software from multiple vendors. In this work, we present a series of scripts that have been developed to rapidly classify major groups of compounds that are of relevance to metabolomics studies including: fatty acid methyl esters, free fatty acids, aldehydes, alcohols, ketones, amino acids, and carbohydrates.

scholarly journals Evaluation of 3-Methylbutanoic Acid Methyl Ester as a Factor Influencing Flavor Cleanness in Arabica Specialty Coffee

2021 ◽  
Vol 11 (12) ◽  
pp. 5413
Author(s):  
Keiko Iwasa ◽  
Harumichi Seta ◽  
Yoshihide Matsuo ◽  
Koichi Nakahara
Keyword(s):  
Methyl Ester ◽  
Methyl Esters ◽  
Acid Methyl Ester ◽  
Chemical Compounds ◽  
Gas Chromatography Mass Spectrometry ◽  
Arabica Coffee ◽  
Acid Methyl ◽  
Coffee Brew ◽  
Coffee Beans ◽  
Specialty Coffee

This paper reports on the chemical compounds in arabica coffee beans with a high Specialty Coffee Association (SCA) cupping score, especially those in specialty coffee beans. We investigated the relationship between the chemical compounds and cupping scores by considering 16 types of Coffea arabica (arabica coffee) beans from Guatemala (SCA cupping score of 76.5–89.0 points). Non-targeted gas chromatography-mass spectrometry-based chemometric profiling indicated that specialty beans with a high cupping score contained considerable amounts of methyl-esterified compounds (MECs), including 3-methylbutanoic acid methyl ester (3-MBM), and other fatty acid methyl esters. The effect of MECs on flavor quality was verified by spiking the coffee brew with 3-MBM, which was the top-ranked component, as obtained through a regression model associated with cupping scores. Notably, 3-MBM was responsible for the fresh-fruity aroma and cleanness of the coffee brew. Although cleanness is a significant factor for specialty beans, the identification of compounds that contribute to cleanness has not been reported in previous research. The chemometric profiling approach coupled with spiking test validation will improve the identification and characterization of 3-MBM commonly found in arabica specialty beans. Therefore, 3-MBM, either alone or together with MECs, can be used as a marker in coffee production.

scholarly journals Ultra-High Performance Liquid Chromatography-High Resolution Mass Spectrometry and High-Sensitivity Gas Chromatography-Mass Spectrometry Screening of Classic Drugs and New Psychoactive Substances and Metabolites in Urine of Consumers

2021 ◽  
Vol 22 (8) ◽  
pp. 4000
Author(s):  
Emilia Marchei ◽  
Maria Alias Ferri ◽  
Marta Torrens ◽  
Magí Farré ◽  
Roberta Pacifici ◽  
...  
Keyword(s):  
Mass Spectrometry ◽  
Gas Chromatography ◽  
Mobile Phase ◽  
High Performance ◽  
High Resolution Mass Spectrometry ◽  
High Sensitivity ◽  
Gas Chromatography Mass Spectrometry ◽  
New Psychoactive Substances ◽  
Psychoactive Substances ◽  
Resolution Mass

The use of the new psychoactive substances is continuously growing and the implementation of accurate and sensible analysis in biological matrices of users is relevant and fundamental for clinical and forensic purposes. Two different analytical technologies, high-sensitivity gas chromatography-mass spectrometry (GC-MS) and ultra-high-performance liquid chromatography-high-resolution mass spectrometry (UHPLC-HRMS) were used for a screening analysis of classic drugs and new psychoactive substances and their metabolites in urine of formed heroin addicts under methadone maintenance therapy. Sample preparation involved a liquid-liquid extraction. The UHPLC-HRMS method included Accucore™ phenyl Hexyl (100 × 2.1 mm, 2.6 μm, Thermo, USA) column with a gradient mobile phase consisting of mobile phase A (ammonium formate 2 mM in water, 0.1% formic acid) and mobile phase B (ammonium formate 2 mM in methanol/acetonitrile 50:50 (v/v), 0.1% formic acid) and a full-scan data-dependent MS2 (ddMS2) mode for substances identification (mass range 100–1000 m/z). The GC-MS method employed an ultra-Inert Intuvo GC column (HP-5MS UI, 30 m, 250 µm i.d, film thickness 0.25 µm; Agilent Technologies, Santa Clara, CA, USA) and electron-impact (EI) mass spectra were recorded in total ion monitoring mode (scan range 40–550 m/z). Urine samples from 296 patients with a history of opioid use disorder were examined. Around 80 different psychoactive substances and/or metabolites were identified, being methadone and metabolites the most prevalent ones. The possibility to screen for a huge number of psychotropic substances can be useful in suspected drug related fatalities or acute intoxication/exposure occurring in emergency departments and drug addiction services.

Nanodust detection with Cassini CDA - Implications for DESTINY+ and Interstellar Probe

2021 ◽  
Author(s):  
Ralf Srama ◽  
Jon K. Hillier ◽  
Sean Hsu ◽  
Sascha Kempf ◽  
Masanori Kobayashi ◽  
...  
Keyword(s):  
High Resolution ◽  
Impact Ionization ◽  
Cosmic Dust ◽  
Hypervelocity Impact ◽  
Dust Particles ◽  
Interstellar Space ◽  
Mass Spectrometers ◽  
High Resolution Mass ◽  
Resolution Mass

<p>The Cosmic Dust Analyzer (CDA) onboard Cassini characterized successfully the dust environment at Saturn from 2004 to 2017. Besides the study of Saturn’s E ring and its interaction with the embedded moons, CDA detected nanoparticles in the outer Saturn system moving on unbound orbits and originating primarily from Saturn’s E-ring. Although the instrument was built to detect micron and sub-micron sized particles, nano-sized grains were detected during the flyby at early Jupiter and in the outer environment at Saturn. Fast dust particles with sizes below 10 nm were measured by in-situ impact ionization and mass spectra were recorded. What are the limits of in-situ hypervelocity impact detection and what can be expected with current high-resolution mass spectrometers as flown onboard the missions DESTINY+ or EUROPA? Is the sensitivity of Dust Telescopes sufficient to detect nano-diamonds in interstellar space? This presentation summarizes the current experience of in-situ dust detectors and gives a prediction for future missions. In summary, current Dust Telescopes with integrated high-resolution mass spectrometers are more sensitive than the CASSINI Cosmic Dust Analyzer.</p>

The Thermal Volatilization of Petrodisel/Biodiesel from Waste Oil

2011 ◽  
Vol 347-353 ◽  
pp. 2656-2660
Author(s):  
Xiu Chen ◽  
Yin Nan Yuan ◽  
Yong Bin Lai
Keyword(s):  
Chemical Composition ◽  
Methyl Esters ◽  
Gas Chromatography Mass Spectrometry ◽  
Waste Oil ◽  
Compression Ignition Engine ◽  
Yield Information ◽  
Composition And Structure ◽  
Similar Chemical ◽  
Ignition Quality ◽  
Long Chain

Thermogravimetry (TG) has been employed to yield information on the thermal volatilization of the fuels since the volatility influences the ignition quality of the fuels in a compression ignition engine. The chemical composition of -10 petrodiesel (-10PD) and waste oil biodiesel (WME) was analyzed by gas chromatography-mass spectrometry. The thermal volatilization of biodiesel and its blends was investigated by TG and liquid volatile theory. Volatile index was put forward for describing biodiesel/petrodisel volatility. A good correlation model was proposed for calculate the biodiesel/petrodiesel volatility by biodiesel blending ratio. The study showed that -10PD and WME had similar chemical composition and structure. -10PD was mainly composed of long chain alkanes: C8–C26. WME was mainly composed of long chain fatty acid methyl esters: C14:0–C22:0, C16:1–C22:1, C18:2 and C18:3. The volatile indexes of WME and -10PD were 1.47E-04 and 3.64E-05, respectively. The biodiesel was considerably more volatile in comparison to the petrodiesel. The WME/-10PD volatility was better with increasing the biodiesel blending ratio.

scholarly journals Upon the opportunity to apply ART2 Neural Network for clusterization of biodiesel fuels

2016 ◽  
Vol 3 (1) ◽  
pp. 19-25
Author(s):  
T. Petkov ◽  
Z. Mustafa ◽  
S. Sotirov ◽  
R. Milina ◽  
M. Moskovkina
Keyword(s):  
Neural Network ◽  
Mass Spectrometry ◽  
Artificial Neural Network ◽  
Gas Chromatography ◽  
Fatty Acid Methyl Esters ◽  
Methyl Esters ◽  
Gas Chromatography Mass Spectrometry ◽  
Acid Methyl ◽  
Chemometric Approach ◽  
Biodiesel Fuels

Abstract A chemometric approach using artificial neural network for clusterization of biodiesels was developed. It is based on artificial ART2 neural network. Gas chromatography (GC) and Gas Chromatography - mass spectrometry (GC-MS) were used for quantitative and qualitative analysis of biodiesels, produced from different feedstocks, and FAME (fatty acid methyl esters) profiles were determined. Totally 96 analytical results for 7 different classes of biofuel plants: sunflower, rapeseed, corn, soybean, palm, peanut, “unknown” were used as objects. The analysis of biodiesels showed the content of five major FAME (C16:0, C18:0, C18:1, C18:2, C18:3) and those components were used like inputs in the model. After training with 6 samples, for which the origin was known, ANN was verified and tested with ninety “unknown” samples. The present research demonstrated the successful application of neural network for recognition of biodiesels according to their feedstock which give information upon their properties and handling.

Web Server for Peak Detection, Baseline Correction, and Alignment in Two-Dimensional Gas Chromatography Mass Spectrometry-Based Metabolomics Data

2016 ◽  
Vol 88 (21) ◽  
pp. 10395-10403 ◽  
Author(s):  
Tze-Feng Tian ◽  
San-Yuan Wang ◽  
Tien-Chueh Kuo ◽  
Cheng-En Tan ◽  
Guan-Yuan Chen ◽  
...  
Keyword(s):  
Mass Spectrometry ◽  
Gas Chromatography ◽  
Web Server ◽  
Peak Detection ◽  
Gas Chromatography Mass Spectrometry ◽  
Baseline Correction ◽  
Two Dimensional ◽  
Metabolomics Data ◽  
Chromatography Mass Spectrometry

scholarly journals Molecular Distributions of Soluble Oxidation Products from Coals Characterized by Mass Spectrometers

2018 ◽  
Vol 2018 ◽  
pp. 1-7
Author(s):  
Xing Fan ◽  
Fei Wang
Keyword(s):  
Mass Spectrometry ◽  
Direct Analysis ◽  
Water Soluble ◽  
Oxidation Products ◽  
Gas Chromatography Mass Spectrometry ◽  
Mass Spectrometers ◽  
Polycarboxylic Acids ◽  
Alkanoic Acids ◽  
Carboxylic Groups ◽  
Soluble Species

Oxidation of three coals with rank from lignite to anthracite in NaOCl aqueous solution was investigated in this study. The oxidation products were characterized by using gas chromatography/mass spectrometry and direct analysis in real-time mass spectrometry. The results showed that most of organic compounds in coals were converted into water-soluble species under mild conditions, even the anthracite. Benzene polycarboxylic acids (BPCAs) and chloro-substituted alkanoic acids (CSAAs) were major products from the reactions. The products from lower rank coals consist of considerable CSAAs and most products from high rank coals are BPCAs. As coal rank increases, the yield of BPCAs with more carboxylic groups increases.

Simulation and Analysis of different CMOS Full Adders for Delay Optimisation

2021 ◽  
Vol 9 (9) ◽  
pp. 66-70
Author(s):  
Nakul C. Kubsad
Keyword(s):  
Power Dissipation ◽  
High Speed ◽  
Digital Signal ◽  
Full Adder ◽  
Digital Signal Processors ◽  
Transmission Gate ◽  
Logical Operations ◽  
Recent Advancement ◽  
Voltage Swing ◽  
Signal Processors

Abstract: Full adder circuit is one among the fundamental and necessary digital part. The full adder is be a part of microprocessors, digital signal processors etc. It's needed for the arithmetic and logical operations. Full adder design enhancements are necessary for recent advancement. The requirement of an adder cell is to provide high speed, consume low power and provide high voltage swing. This paper analyses and compares 3 adders with completely different logic designs (Conventional, transmission gate & pseudo NMOS) for transistor count, power dissipation and delay. The simulation is performed in Cadence virtuoso tool with accessible GPDK – 180nm kit. Transmission gate full adder has sheer advantage of high speed, fewer space and also it shows higher performance in terms of delay. Keywords: Delay, power dissipation, voltage, transistor sizing.

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