Gas Chromatography‐Mass Spectrometry‐Basic Principles, Instrumentation and Selected Applications for Detection of Organic Compounds

Novel hollow-electrode glow discharge mass spectrometry for the quantitative analysis of protein content in food

Protein content in food is an important indicator of nutritional value and food safety. Therefore, it is of great significance to accurately detect protein content in food. In this work, a combustion furnace and novel hollow-electrode glow discharge ion source-quadrupole mass spectrometry (HGD-MS) were designed, which were used to construct a "combustion furnace + mass spectrometry" experimental platform to detect the protein content in food. Five food standard samples were selected for the analysis. The food samples were combusted in the combustion furnace at a high temperature (1300 °C) in an oxygen-rich environment. The gas products were passed into the novel hollow electrode glow discharge ion source-quadrupole mass spectrometer. A standard curve of y = 635.06x + 11 082, R2 = 0.9994 was plotted by detecting the NO+ ion intensity at a relative standard deviation (RSD) of 1.8% to 5.7%. Using the same method, food samples no. 6 and 7 were combusted and NO+ ion intensity was measured to verify the accuracy of the quantitation curve. Subsequently, the protein content was determined using a nitrogen-to-protein conversion factor of 6.25. This method provides a rapid, accurate, and environmentally friendly approach for determining protein content in food.

uafR: An R package that automates mass spectrometry data processing

Chemical information has become increasingly ubiquitous and has outstripped the pace of analysis and interpretation. We have developed an R package, uafR, that automates a grueling retrieval process for gas -chromatography coupled mass spectrometry (GC -MS) data and allows anyone interested in chemical comparisons to quickly perform advanced structural similarity matches. Our streamlined cheminformatics workflows allow anyone with basic experience in R to pull out component areas for tentative compound identifications using the best published understanding of molecules across samples (pubchem.gov). Interpretations can now be done at a fraction of the time, cost, and effort it would typically take using a standard chemical ecology data analysis pipeline. The package was tested in two experimental contexts: (1) A dataset of purified internal standards, which showed our algorithms correctly identified the known compounds with R2 values ranging from 0.827-0.999 along concentrations ranging from 1 × 10-5 to 1 × 103 ng/μl, (2) A large, previously published dataset, where the number and types of compounds identified were comparable (or identical) to those identified with the traditional manual peak annotation process, and NMDS analysis of the compounds produced the same pattern of significance as in the original study. Both the speed and accuracy of GC -MS data processing are drastically improved with uafR because it allows users to fluidly interact with their experiment following tentative library identifications [i.e. after the m/z spectra have been matched against an installed chemical fragmentation database (e.g. NIST)]. Use of uafR will allow larger datasets to be collected and systematically interpreted quickly. Furthermore, the functions of uafR could allow backlogs of previously collected and annotated data to be processed by new personnel or students as they are being trained. This is critical as we enter the era of exposomics, metabolomics, volatilomes, and landscape level, high-throughput chemotyping. This package was developed to advance collective understanding of chemical data and is applicable to any research that benefits from GC -MS analysis. It can be downloaded for free along with sample datasets from Github at github.org/castratton/uafR or installed directly from R or RStudio using the developer tools: 'devtools::install_github("castratton/uafR")'.

Revealing the Adverse Impact of Additive Carbon Material on Microorganisms and Its Implications for Biogas Yields: A Critical Review

Biochar could be a brilliant additive supporting the anaerobic fermentation process. However, it should be taken into account that in some cases it could also be harmful to microorganisms responsible for biogas production. The negative impact of carbon materials could be a result of an overdose of biochar, high biochar pH, increased arsenic mobility in the methane fermentation solution caused by the carbon material, and low porosity of some carbon materials for microorganisms. Moreover, when biochar is affected by an anaerobic digest solution, it could reduce the biodiversity of microorganisms. The purpose of the article is not to reject the idea of biochar additives to increase the efficiency of biogas production, but to draw attention to the properties and ways of adding these materials that could reduce biogas production. These findings have practical relevance for organizations seeking to implement such systems in industrial or local-scale biogas plants and provide valuable insights for future research. Needless to say, this study will also support the implementation of biogas technologies and waste management in implementing the idea of a circular economy, further emphasizing the significance of the research.

Recent Developments in the Detection of Organic Contaminants Using Molecularly Imprinted Polymers Combined with Various Analytical Techniques

Molecularly imprinted polymers (MIPs) encompass a diverse array of polymeric matrices that exhibit the unique capacity to selectively identify a designated template molecule through specific chemical moieties. Thanks to their pivotal attributes, including exceptional selectivity, extended shelf stability, and other distinct characteristics, this class of compounds has garnered interest in the development of highly responsive sensor systems. As a result, the incorporation of MIPs in crafting distinctive sensors and analytical procedures tailored for specific analytes across various domains has increasingly become a common practice within contemporary analytical chemistry. Furthermore, the range of polymers amenable to MIP formulation significantly influences the potential utilization of both conventional and innovative analytical methodologies. This versatility expands the array of possibilities in which MIP-based sensing can be employed in recognition systems. The following review summarizes the notable progress achieved within the preceding seven-year period in employing MIP-based sensing techniques for analyte determination.

Biodiesel Purification by Solvent-Aided Crystallization Using 2-Methyltetrahydrofuran

The previous biodiesel purification by Solvent-Aided Crystallization (SAC) using 1-butanol as assisting agent and parameters for SAC were optimized such as coolant temperature, cooling time and stirring speed. Meanwhile, 2-Methyltetrahydrofuran (2-MeTHF) was selected as an alternative to previous organic solvents for this study. In this context, it is used to replace solvent 1-butanol from a conducted previous study. This study also focuses on the technological improvements in the purification of biodiesel via SAC as well as to produce an even higher purity of biodiesel. Experimental works on the transesterification process to produce crude biodiesel were performed and SAC was carried out to purify the crude biodiesel. The crude biodiesel content was analyzed by using Gas Chromatography-Mass Spectrometry (GC-MS) and Differential Scanning Calorimetry (DSC) to measure the composition of Fatty Acid Methyl Esters (FAME) present. The optimum value to yield the highest purity of FAME for parameters coolant temperature, cooling time, and stirring speed is -4 °C, 10 min and 210 rpm, respectively. It can be concluded that the assisting solvent 2-MeTHF has a significant effect on the process parameters to produce purified biodiesel according to the standard requirement.

Volatilomics as an Emerging Strategy to Determine Potential Biomarkers of Female Infertility: A Pilot Study

Due to its high prevalence, infertility has become a prominent public health issue, posing a significant challenge to modern reproductive medicine. Some clinical conditions that lead to female infertility include polycystic ovary syndrome (PCOS), endometriosis, and premature ovarian failure (POF). Follicular fluid (FF) is the biological matrix that has the most contact with the oocyte and can, therefore, be used as a predictor of its quality. Volatilomics has emerged as a non-invasive, straightforward, affordable, and simple method for characterizing various diseases and determining the effectiveness of their current therapies. In order to find potential biomarkers of infertility, this study set out to determine the volatomic pattern of the follicular fluid from patients with PCOS, endometriosis, and POF. The chromatographic data integration was performed through solid-phase microextraction (SPME), followed by gas chromatography–mass spectrometry (GC-MS). The findings pointed to specific metabolite patterns as potential biomarkers for the studied diseases. These open the door for further research into the relevant metabolomic pathways to enhance infertility knowledge and diagnostic tools. An extended investigation may, however, produce a new mechanistic understanding of the pathophysiology of the diseases.

Organic waste conversion through anaerobic digestion: A critical insight into the metabolic pathways and microbial interactions

Anaerobic digestion is a promising method for energy recovery through conversion of organic waste to biogas and other industrial valuables. However, to tap the full potential of anaerobic digestion, deciphering the microbial metabolic pathway activities and their underlying bioenergetics is required. In addition, the behavior of organisms in consortia along with the analytical abilities to kinetically measure their metabolic interactions will allow rational optimization of the process. This review aims to explore the metabolic bottlenecks of the microbial communities adopting latest advances of profiling and ¹³C tracer-based analysis using state of the art analytical platforms (GC, GC-MS, LC-MS, NMR). The review summarizes the phases of anaerobic digestion, the role of microbial communities, key process parameters of significance, syntrophic microbial interactions and the bottlenecks that are critical for optimal bioenergetics and enhanced production of valuables. Considerations into the designing of efficient synthetic microbial communities as well as the latest advances in capturing their metabolic cross talk will be highlighted. The review further explores how the presence of additives and inhibiting factors affect the metabolic pathways. The critical insight into the reaction mechanism covered in this review may be helpful to optimize and upgrade the anaerobic digestion system.

Determination of fipronil and bixafen pesticides residues using gas chromatography mass spectroscopy with matrix matching calibration strategy after binary dispersive liquid-liquid microextraction

The objective of this study was to determine bixafen and fipronil residues in domestic and industrial wastewater, soil and mint samples by binary dispersive liquid-liquid microextraction method (BDLLME) prior to gas chromatography-mass spectrometry (GC-MS). Extraction efficiency for the selected analytes was improved by optimizing the parameters such as solvent type, ratio and volume, dispersive solvent type/volume, mixing type and duration to increase overall analytical performance. Under the optimum chromatographic and extraction conditions, limits of detection values for bixafen and fipronil were determined as 7.3 and 6.1 µg L^-1, respectively. Spiking experiments were performed for domestic and industrial wastewater, soil and mint samples to evaluate applicability and accuracy of the proposed method. Recovery results for the samples were calculated in the range of 89.4%-112.6% via matrix matching calibration strategy. It was determined that the detection power of GC-MS system was improved 7.8 times for bixafen and 119 times for fipronil over LOD comparisons of conventional GC-MS and B-DLLME-GC-MS systems.

A review of breath analysis techniques in head and neck cancer

Cancers of the head and neck region are a severely disabling group of diseases with no method for early detection. Analysis of exhaled breath volatile organic compounds shows promise as biomarkers for early detection and disease monitoring. This article reviews breath analysis in the setting of head and neck cancer, with a practical focus on breath sampling techniques, detection technologies and valid data analysis methods. Title and abstract keyword searches were conducted on PubMed and Embase databases to identify English language studies without a time-period limitation. The main inclusion criteria were human studies comparing head and neck cancer patients to healthy controls using exhaled breath analysis. Multiple breath collection techniques, three major detection technologies and multiple data analysis methods were identified. However, the variability in techniques and lack of methodological standardization does not allow for adequate study replication or data pooling. Twenty-two volatile organic compounds identified in five studies have been reported to discriminate head and neck cancer patients from healthy controls. Breath analysis for detection of head and neck cancer shows promise as a non-invasive detection tool. However, methodological standardization is paramount for future research study design to provide the potential for translating these techniques into routine clinical use.

Aroma Profile Characterization of Mahi-Mahi and Tuna for Determining Spoilage Using Purge and Trap Gas Chromatography-Mass Spectrometry

Alcohols, aldehydes, ketones, amines, and sulfur compounds are essential aroma compounds related to fish flavor and spoilage. Gas chromatography-mass spectrometry (GC-MS) is an instrument that is widely used to identify and quantify volatile and semi-volatile compounds in fish products. In this research, a simple and accurate GC-MS method was developed to determine the aroma profile of mahi-mahi and tuna for chemical indicators of spoilage. In the developed GC-MS method, trichloroacetic acid (TCA) solution was used to extract analytes from homogenized fish samples. The purge and trap system was used for sample introduction, and the GC-MS with an RTX-Volatile Amine column was able to separate compounds without a derivatization procedure. The created purge and trap gas chromatography-mass spectrometry (PT-GC-MS) method could identify and quantify twenty aroma compounds in mahi-mahi (Coryphaena hippurus) and 16 volatile compounds in yellowfin tuna (Thunnus albacares) associated with fish spoilage. The amines (dimethylamine, trimethylamine, isobutylamine, 3-methylbutylamine, and 2-methylbutanamine), alcohols (2-ethylhexanol, 1-penten-3-ol and isoamyl alcohol, ethanol), aldehydes (2-methylbutanal, 3-methylbutanal, benzaldehyde), ketones (acetone, 2,3-butanedione, 2-butanone, acetoin), and dimethyl disulfide strongly statistically correlated with poorer quality tuna and mahi-mahi and were considered as the key spoilage indicators. PRACTICAL APPLICATION: A simplified and rapid purge and trap gas chromatography-mass spectrometry (PT-GC-MS) method developed in this research was able to identify and quantify important spoilage compounds in mahi-mahi and yellowfin tuna. This method is an efficient analytical method for determining volatile profiles of fish samples for industry analytical labs or the government. The identified analytical quality markers can be used to monitor the spoilage level of tuna and mahi-mahi.

Development of a Dual MOS Electronic Nose/Camera System for Improving Fruit Ripeness Classification

Electronic nose (E-nose) systems have become popular in food and fruit quality evaluation because of their rapid and repeatable availability and robustness. In this paper, we propose an E-nose system that has potential as a non-destructive system for monitoring variation in the volatile organic compounds produced by fruit during the maturing process. In addition to the E-nose system, we also propose a camera system to monitor the peel color of fruit as another feature for identification. By incorporating E-nose and camera systems together, we propose a non-destructive solution for fruit maturity monitoring. The dual E-nose/camera system presents the best Fisher class separability measure and shows a perfect classification of the four maturity stages of a banana: Unripe, half-ripe, fully ripe, and overripe.

Volatile organic compounds and the potential for a lung cancer breath test

SUMMARY Detecting exhaled volatile organic compounds (VOCs) that are associated with lung cancer (LC) has realistic potential for becoming an integral part of population-based LC screening and monitoring in the near future. Here, we review the main three approaches for profiling VOCs in LC patients and their advantages and pitfalls: first, mass spectrometry techniques for the identification and/or quantification of a wide variety of separate breath VOCs; second, canines that are trained to sniff out LC; and third, cross-reactive chemical sensors in combination with statistical methods for identifying disease-specific patterns. We estimate that the latter would be most suitable for clinical practice. In the short run, breath testing could provide a critically needed adjunct method for detecting nodule malignancy with high specificity during low-dose computed tomography screening. In the long run, breath testing holds potential for entirely revolutionizing LC screening, diagnosis and management.