Fast gas chromatography-mass spectrometry: A review of the last decade

Detection of Volatile Organic Compounds through Spectroscopic Signatures in Nanoporous Fabry-Pérot Optical Microcavities

Increasingly complex modern gas-monitoring scenarios necessitate advanced sensing capabilities to detect and identify a diverse range of gases under varying conditions. There is a rising demand for individual sensors with multiple responses capable of recognizing gases, identifying components in mixtures, and providing stable responses. Inspired by gas sensors employing multivariable response principles, we develop a nanoporous anodic alumina high-order microcavity (NAA-HOμCV) gas sensor with multiple optical outputs for discriminative gas detection. The NAA-HOμCV architecture, formed by a Fabry-Pérot microcavity with distributed Bragg reflector (DBR) mirrors and an extended-length microcavity layer supporting multiple resonant modes, serves as an effective solid-state fingerprint platform for distinguishing volatile organic compound (VOC) gases. Our research reveals that the coupling strength of light into resonant modes and their evolution depend on the thickness of the DBR mirrors and the dimension of the microcavity layer, which allows us to optimize the discriminative sensing capability of the NAA-HOμCV sensor through structural engineering of the microcavity and photonic crystal mirrors. Gas-sensing experiments conducted on the NAA-HOμCV sensor demonstrate real-time discrimination between physiosorbed VOC gases (isopropanol, ethanol, or acetone) in reversible gas sensing. It also achieves superior ppb-level sensing in irreversible gas sensing of model silane molecules. Our study presents promising avenues for designing compact, cost-effective, and highly efficient gas sensors with tailored properties for discriminative gas detection.

Protein Deceleration and Sequencing Using Si3N4-CNT Hybrid Nanopores

Protein sequencing is crucial for understanding the complex mechanisms driving biological functions and is of utmost importance in molecular diagnostics and medication development. Nanopores have become an effective tool for single molecule sensing, however, the weak charge and non-uniform charge distribution of protein make capturing and sensing very challenging, which poses a significant obstacle to the development of nanopore-based protein sequencing. In this study, to facilitate capturing of the unfolded protein, highly charged peptide was employed in our simulations, we found that the velocity of unfolded peptide translocating through a hybrid nanopore composed of silicon nitride membrane and carbon nanotube is much slower compared to bare silicon nitride nanopore, it is due to the significant interaction between amino acids and the surface of carbon nanotube. Moreover, by introducing variations in the charge states at the boundaries of carbon nanotube nanopores, the competition and combination of the electrophoretic and electroosmotic flows through the nanopores could be controlled, we then successfully regulated the translocation velocity of unfolded proteins through the hybrid nanopores. The proposed hybrid nanopore effectively retards the translocation velocity of protein through it, facilitates the acquisition of ample information for accurate amino acid identification.

Chromatographic speed classification for liquid chromatography using average theoretical peak time (ATPT)

BACKGROUND

The development of analytical techniques in the field of liquid chromatography has brought new frontiers in performance and analytical speed for the technique. The proper evaluation of the analytical boundaries achieved with those developments was not addressed in the literature, since different liquid chromatography (LC) techniques have not yet received any classification regarding their chromatographic speed. Defining chromatographic analysis speed based simply on analysis time is an outdated concept since it is sample and analyte-dependent. In this context, the application of the Average Theoretical Peak Time concept (ATPT) is proposed as a unified metric for chromatographic speed classification.

RESULTS

This metric was evaluated using PCA analysis in a group of more than 50 publications, which generated the classification of LC methods in normal, high, hyper, and ultra-high-speed separations using ATPT. Normal speed (ATPT values greater than 18000 ms/peak) was found in HPLC, nano-LC, SFC, and CEC methods. Therefore, high-speed methods (ATPT values between 4000 and 18000 ms/peak) were found in UHPLC techniques, while LC × LC methods presented higher ATPT values between 1000 and 4000 ms/peak being classified as hyper-speed separations. ATPT can also be used as an optimization parameter, since older methods show higher ATPT values, while recent published papers show lower values of this metric. This behavior is justified due to the improvement of the LC methods over the years.

SIGNIFICANCE

This work fulfills the gap in chromatographic definitions and metrics, regarding analytical speed in one-dimensional and multidimensional liquid chromatographic techniques and shows that ATPT metrics is a robust parameter that can be used to classify the separation speed as well as a metric to evaluate the LC Method optimization. It also corrects the historical application of separation time as a metric for chromatographic speed.

Sensor development for multiple simultaneous classifications using genetically engineered M13 bacteriophages

Sensors for detecting infinitesimal amounts of chemicals in air have been widely developed because they can identify the origin of chemicals. These sensing technologies are also used to determine the variety and freshness of fresh food and detect explosives, hazardous chemicals, environmental hormones, and diseases using exhaled gases. However, there is still a need to rapidly develop portable and highly sensitive sensors that respond to complex environments. Here, we show an efficient method for optimising an M13 bacteriophage-based multi-array colourimetric sensor for multiple simultaneous classifications. Apples, which are difficult to classify due to many varieties in distribution, were selected for classifying targets. M13 was adopted to fabricate a multi-array colourimetric sensor using the self-templating process since a chemical property of major coat protein p8 consisting of the M13 body can be manipulated by genetic engineering to respond to various target substances. The twenty sensor units, which consisted of different types of manipulated M13, exhibited colour changes because of the change of photonic crystal-like nanostructure when they were exposed to target substances associated with apples. The classification success rate of the optimal sensor combinations was achieved with high accuracy for the apple variety (100%), four standard fragrances (100%), and aging (84.5%) simultaneously. We expect that this optimisation technique can be used for rapid sensor development capable of multiple simultaneous classifications in various fields, such as medical diagnosis, hazardous environment monitoring, and the food industry, where sensors need to be developed in response to complex environments consisting of various targets.

Simultaneous determination of low molecular weight nitrosamines in pharmaceutical products by fast gas chromatography mass spectrometry

Control of N-nitrosamines has been in the focus of health authorities in recent years because many of these compounds are probable human carcinogens. In July 2018 the U.S. Food and Drug Administration (FDA) announced a recall for valsartan-containing medicines due to contamination with the carcinogenic low molecular weight nitrosamine, N-nitrosodimethylamine (NDMA). It has become clear that the problem can not only exist in the case of sartans, but in any active pharmaceutical ingredient (API)/drug product in which secondary or tertiary amines are present (as API or as impurities) and a nitrosating agent is available. The decision was made by regulators, according to which manufacturers of pharmaceutical products are obliged to perform a risk assessment for the potential presence of nitrosamines in active pharmaceutical ingredients and drug products. This resulted in a high demand for validated analytical methods that are able to quantify N-nitrosamines at low ppb levels in pharmaceutical products. In this work we have developed and validated a generic fast GC-MS method suitable for the quantitative determination of a wide range of low molecular weight nitrosamines, which include N-nitrosodiethylamine (NDEA), N-nitrosodimethylamine (NDMA), N-nitroso-diphenylamine (NDPh), N-nitrosodipropylamine (NDPA), N-nitrosomethylethylamine (NMEA), N-nitrosomorpholine (NMOR), N-nitrosopiperidine (NPIP), N-nitroso-ethylisopropylamine (EIPNA), N-nitroso-diisopropylamine (DIPNA), N-nitroso-N-methylaniline (NMPA), 1-Methyl-4-nitrosopiperazine (MeNP) and N-nitroso-pyrrolidine (NPYR). The advantage of the method is that it is possible to screen low molecular weight nitrosamines in low concentrations with a short analysis time in a wide range of APIs and drug products.

A dilute-and-inject low-pressure gas chromatography-tandem mass spectrometry method for phthalate determination in extra virgin olive oil

The goal of this study was to develop a method for the determination of nine phthalic acid esters in extra virgin olive oils using low-pressure gas chromatography-triple-quadrupole mass spectrometry. Sample preparation was simple, environmental friendly, and rapid inasmuch that it involved only dilution (< 1 mL of hexane). The low-pressure gas chromatography analyses were performed by using a 5 m wide-bore column. The limit of quantification for the phthalates ranged from 0.06 to 1.14 mg kg-1 . Both intra- and interday precisions were measured, with coefficient of variation values ranging from 0.2% to 11.7%. The trueness of the method was measured by evaluating accuracy at the initial stage of the work and after 2 months, with values ranging between -8.7% and 12.1%. Moreover, blind accuracy was comprised between -11.6% and 14.2%. The method involves the use of simplified instrumentation and reduced analysis times (nearly two times faster) compared to a previously published comprehensive two-dimensional gas chromatography-triple-quadrupole mass spectrometry method, leading to a reduction of energy and helium consumption. The approaches were compared in analytical terms and for the environmental impact. In total, 23 olive oil samples were analyzed, with at least one phthalate detected in all but one sample.

Portable chemical detection platform for on-site monitoring of odorant levels in natural gas

The adequate odorization of natural gas is critical to identify gas leaks and to reduce accidents. To ensure odorization, natural gas utility companies collect samples to be processed at core facilities or a trained human technician smells a diluted natural gas sample. In this work, we report a detection platform that addresses the lack of mobile solutions capable of providing quantitative analysis of mercaptans, a class of compounds used to odorize natural gas. Detailed description of the platform hardware and software components is provided. Designed to be portable, the platform hardware facilitates extraction of mercaptans from natural gas, separation of individual mercaptan species, and quantification of odorant concentration, with results reported at point-of-sampling. The software was developed to accommodate skilled users as well as minimally trained operators. Detection and quantification of six commonly used mercaptan compounds (ethyl mercaptan, dimethyl sulfide, n-propylmercaptan, isopropyl mercaptan, tert‑butyl mercaptan, and tetrahydrothiophene) at typical odorizing concentrations of 0.1-5 ppm was performed using the device. We demonstrate the potential of this technology to ensure natural gas odorizing concentrations throughout distribution systems.

Environmental Engineering Applications of Electronic Nose Systems Based on MOX Gas Sensors

Nowadays, the electronic nose (e-nose) has gained a huge amount of attention due to its ability to detect and differentiate mixtures of various gases and odors using a limited number of sensors. Its applications in the environmental fields include analysis of the parameters for environmental control, process control, and confirming the efficiency of the odor-control systems. The e-nose has been developed by mimicking the olfactory system of mammals. This paper investigates e-noses and their sensors for the detection of environmental contaminants. Among different types of gas chemical sensors, metal oxide semiconductor sensors (MOXs) can be used for the detection of volatile compounds in air at ppm and sub-ppm levels. In this regard, the advantages and disadvantages of MOX sensors and the solutions to solve the problems arising upon these sensors' applications are addressed, and the research works in the field of environmental contamination monitoring are overviewed. These studies have revealed the suitability of e-noses for most of the reported applications, especially when the tools were specifically developed for that application, e.g., in the facilities of water and wastewater management systems. As a general rule, the literature review discusses the aspects related to various applications as well as the development of effective solutions. However, the main limitation in the expansion of the use of e-noses as an environmental monitoring tool is their complexity and lack of specific standards, which can be corrected through appropriate data processing methods applications.

Analysis of Dibenzyltoluene Mixtures: From Fast Analysis to In-Depth Characterization of the Compounds

The so-called dibenzyltoluene (H0-DBT) heat transfer oil contains numerous isomers of dibenzyltoluene as well as (benzyl)benzyltoluene (methyl group on the central vs. the side aromatic ring). As it is used as a liquid organic hydrogen carrier (LOHC), a detailed analysis of its composition is crucial in assessing the kinetic rate of hydrogenation for each constituent and studying the mechanism of H0-DBT hydrogenation. To identify all of the compounds in the oil, an in-depth analysis of the GC-MS spectra was performed. To confirm peak attribution, we synthesized some DBTs and characterized the pure compounds using NMR and Raman spectroscopies. Moreover, a fast-GC analysis was developed to rapidly determine the degree of hydrogenation of the mixture.

Geographic Differentiation of Essential Oil from Rhizome of Cultivated Atractylodes lancea by Using GC-MS and Chemical Pattern Recognition Analysis

The rhizome of Atractylodes lancea (RAL) is a well-known Chinese herbal medicine (CHM) that has been applied in clinical settings for thousands of years. In the past two decades, cultivated RAL has gradually replaced wild RAL and become mainstream in clinical practice. The quality of CHM is significantly influenced by its geographical origin. To date, limited studies have compared the composition of cultivated RAL from different geographical origins. As essential oil is the primary active component of RAL, a strategy combining gas chromatography-mass spectrometry (GC-MS) and chemical pattern recognition was first applied to compare the essential oil of RAL (RALO) from different regions in China. Total ion chromatography (TIC) revealed that RALO from different origins had a similar composition; however, the relative content of the main compounds varied significantly. In addition, 26 samples obtained from various regions were divided into three categories by hierarchical cluster analysis (HCA) and principal component analysis (PCA). Combined with the geographical location and chemical composition analysis, the producing regions of RAL were classified into three areas. The main compounds of RALO vary depending on the production areas. Furthermore, a one-way analysis of variance (ANOVA) revealed that there were significant differences in six compounds, including modephene, caryophyllene, γ-elemene, atractylon, hinesol, and atractylodin, between the three areas. Hinesol, atractylon, and β-eudesmol were selected as the potential markers for distinguishing different areas by orthogonal partial least squares discriminant analysis (OPLS-DA). In conclusion, by combining GC-MS with chemical pattern recognition analysis, this research has identified the chemical variations across various producing areas and developed an effective method for geographic origin tracking of cultivated RAL based on essential oils.

The development progress of multi-array colourimetric sensors based on the M13 bacteriophage

Techniques for detecting chemicals dispersed at low concentrations in air continue to evolve. These techniques can be applied not only to manage the quality of agricultural products using a post-ripening process but also to establish a safety prevention system by detecting harmful gases and diagnosing diseases. Recently, techniques for rapid response to various chemicals and detection in complex and noisy environments have been developed using M13 bacteriophage-based sensors. In this review, M13 bacteriophage-based multi-array colourimetric sensors for the development of an electronic nose is discussed. The self-templating process was adapted to fabricate a colour band structure consisting of an M13 bacteriophage. To detect diverse target chemicals, the colour band was utilised with wild and genetically engineered M13 bacteriophages to enhance their sensing abilities. Multi-array colourimetric sensors were optimised for application in complex and noisy environments based on simulation and deep learning analysis. The development of a multi-array colourimetric sensor platform based on the M13 bacteriophage is likely to result in significant advances in the detection of various harmful gases and the diagnosis of various diseases based on exhaled gas in the future.

Comprehensive Controller for Super Sonic Molecular Beam Gas Chromatograph Mass Spectrometer

This paper presents a new, comprehensive digital circuit used for the control of a novel gas chromatograph mass spectrometer (GC-MS) interface that is based on supersonic molecular beam (SMB). The circuit includes a Texas Instruments 150 MHz digital signal controller (DSC), high voltage amplifiers for 8 independent channels and 4 independent channels of high resolution pulse width modulation (PWM). The circuit, along with a sophisticated embedded program and a custom made personal computer (PC) application, control all aspects of the interface: smart filament emission-current stabilization, static and scanning mass-dependent ion-source voltages, transfer-line heater proportional integral differential (PID) controls with thermocouple feedbacks, on/off valves, relays and several peripheral device controls that enable the full operation of a turbo-molecular vacuum pump, and of gas flow and pressure controllers. All aspects of this comprehensive controller were successfully tested. The signal for the 450 Th ion (C32H66) for example increased by 123% which is a significant increase. It is obvious that correctly tuned dynamic voltages can guarantee the optimal signal for each mass.

Quantitative Analysis of Acetone in Transformer Oil Based on ZnO NPs@Ag NWs SERS Substrates Combined with a Stoichiometric Model

Acetone is an essential indicator for determining the aging of transformer insulation. Rapid, sensitive, and accurate quantification of acetone in transformer oil is highly significant in assessing the aging of oil-paper insulation systems. In this study, silver nanowires modified with small zinc oxide nanoparticles (ZnO NPs@Ag NWs) were excellent surface-enhanced Raman scattering (SERS) substrates and efficiently and sensitively detected acetone in transformer oil. Stoichiometric models such as multiple linear regression (MLR) models and partial least square regressions (PLS) were investigated to quantify acetone in transformer oil and compared with commonly used univariate linear regressions (ULR). PLS combined with a preprocessing algorithm provided the best prediction model, with a correlation coefficient of 0.998251 for the calibration set, 0.997678 for the predictive set, a root mean square error in the calibration set (RMSECV = 0.12596 mg/g), and a prediction set (RMSEP = 0.11408 mg/g). For an acetone solution of 0.003 mg/g, the mean absolute percentage error (MAPE) was the lowest among the three quantitative models. For a concentration of 7.29 mg/g, the MAPE was 1.60%. This method achieved limits of quantification and detections of 0.003 mg/g and 1 μg/g, respectively. In general, these results suggested that ZnO NPs@Ag NWs as SERS substrates coupled with PLS simply and accurately quantified trace acetone concentrations in transformer oil.

Computational design and molecular modeling of the interaction of nicotinic acid hydrazide nickel-based complexes with H2S gas

The application of nickel complexes of nicotinic acid hydrazide ligand as a potential gas-sensor and adsorbent material for H₂S gas was examined using appropriate density functional theory (DFT) calculations with the ωB97XD/Gen/6-311++G(d,p)/LanL2DZ method. The FT-IR spectrum of the synthesized ligand exhibited a medium band at 3178 cm^-1 attributed to ν(NH) stretching vibrations and strong bands at 1657 and 1600 cm^-1 corresponding to the presence of ν(C[double bond, length as m-dash]O) and ν(C[double bond, length as m-dash]N) vibration modes. In the spectrum of the nickel(ii) complex, the ν(C[double bond, length as m-dash]O) and ν(C[double bond, length as m-dash]N) vibration bands experience negative shifts to 1605 cm^-1 and 1580 cm^-1, respectively, compared to the ligand. This indicates the coordination of the carbonyl oxygen and the azomethine nitrogen atoms to the Ni²⁺ ion. Thus, the sensing mechanism of the complexes indicated a short recovery time and that the work function value increases for all complexes, necessitating an excellent H₂S gas sensor material. Thus, a profound assertion was given that the complex sensor surfaces exhibited very dense stability with regards to their relevant binding energies corresponding to various existing studies.

Design of experiment techniques for the optimization of chromatographic analysis conditions: A review

Design of experiment (DoE) techniques have been widely used in the field of chromatographic parameters optimization as a valuable tool. A systematic literature review of the available DoE techniques applied to the development of a chromatographic analysis method is presented in this paper. First, the most common available designs and the implementation steps of DoE are comprehensively introduced. Then the studies in recent 10 years for the application of DoE techniques in various chromatographic techniques are discussed, such as capillary electrophoresis, liquid chromatography, gas chromatography, thin-layer chromatography, and high-speed countercurrent chromatography. Current problems and future outlooks are finally given to provide a certain inspiration of research in the application of DoE techniques to the different chromatographic techniques field. This review contributes to a better understanding of the DoE techniques for the efficient optimization of chromatographic analysis conditions, especially for the analysis of complex systems, such as multicomponent drugs and natural products.

Study on the identification and evaluation of growth years for Paris polyphylla var. yunnanensis using deep learning combined with 2DCOS

Paris polyphylla var. yunnanensis, as perennial plants, its quality is closely related to growth period. Different harvest years determine the dry matter accumulation of its medicinal parts and the dynamic accumulation of active ingredients, as well as its economic value and medicinal value. Therefore, it is necessary to establish a systematic evaluation method for the identification and evaluation of P. polyphylla var. yunnanensis with different growth years. Deep learning has a powerful ability in recognition. This study extends it to the identification analysis of medicinal plants from the perspective of spectrum. For the first time, two-dimensional correlation spectroscopy (2DCOS) based on the attenuated total reflection Fourier transformed infrared spectroscopy (ATR-FTIR) combined with residual neural network (Resnet) was used to identify growth years. 525 samples were collected, 4725 2DCOS images were drawn, and the dry matter accumulation in rhizomes of different growth years and different sampling sites were briefly analyzed. The results show that the eight-year-old P. polyphylla var. yunnanensis in Dali has higher economic value and medicinal value. The synchronous 2DCOS models based on ATR-FTIR can realize the identification of growth years with accuracy of 100%. Synchronous 2DCOS are more suitable for the identification of medicinal plants with complex systems. 2DCOS images with different colors and second derivative processing cannot optimize the modeling results. In summary, the method we established is innovative and feasible. It not only solved the identification of growth years, expanded the application field of deep learning, but could also be extended to further research on other medicinal plants.

Conductive Polymer Composites for Hydrogen Sulphide Sensors Working at Sub-PPM Level and Room Temperature

Hybrid composites based on tin chloride and the conductive polymers, polyaniline (PAni) and poly(3,4-ethylenedioxythiophene) polystyrene sulfonate (PEDOT:PSS), were integrated into high-performance hydrogen sulphide (H2S) gas sensors working at room temperature. The morphology and chemical properties were studied by scanning and transmission electron microscopy (SEM, TEM), energy dispersive spectroscopy (EDS) and Fourier-transform infrared (FTIR). The composites demonstrated a slightly porous nanostructure and strong interactions between the polymers and the metal salt, which slightly dopes PAni. The hybrid sensors exhibited a very low detection limit (<85 ppb), fast response, repeatability, reproducibility and stability over one month. Moreover, this work presents how calibration based on the derivative of the signal can give hybrid sensors the ability to quantify the concentration of targeted gas, even during continuous variation of the analyte concentration. Finally, the effect of interfering species, such as water and ammonia, is discussed.

A Portable Micro-Gas Chromatography with Integrated Photonic Crystal Slab Sensors on Chip

The miniaturization of gas chromatography (GC) systems has made it possible to utilize the analytical technique in various on-site applications to rapidly analyze complex gas samples. Various types of miniaturized sensors have been developed for micro-gas chromatography (µGC). However, the integration of an appropriate detector in µGC systems still faces a significant challenge. We present a solution to the problem through integration of µGC with photonic crystal slab (PCS) sensors using transfer printing technology. This integration offers an opportunity to utilize the advantages of optical sensors, such as high sensitivity and rapid response time, and at the same time, compensate for the lack of detection specificity from which label-free optical sensors suffer. We transfer printed a 2D defect free PCS on a borofloat glass, bonded it to a silicon microfluidic gas cell or directly to a microfabricated GC column, and then coated it with a gas responsive polymer. Realtime spectral shift in Fano resonance of the PCS sensor was used to quantitatively detect analytes over a mass range of three orders. The integrated µGC–PCS system was used to demonstrate separation and detection of a complex mixture of 10 chemicals. Fast separation and detection (4 min) and a low detection limit (ng) was demonstrated.

Quantification and mapping of DNA modifications

Apart from the four canonical nucleobases, DNA molecules carry a number of natural modifications. Substantial evidence shows that DNA modifications can regulate diverse biological processes. Dynamic and reversible modifications of DNA are critical for cell differentiation and development. Dysregulation of DNA modifications is closely related to many human diseases. The research of DNA modifications is a rapidly expanding area and has been significantly stimulated by the innovations of analytical methods. With the recent advances in methods and techniques, a series of new DNA modifications have been discovered in the genomes of prokaryotes and eukaryotes. Deciphering the biological roles of DNA modifications depends on the sensitive detection, accurate quantification, and genome-wide mapping of modifications in genomic DNA. This review provides an overview of the recent advances in analytical methods and techniques for both the quantification and genome-wide mapping of natural DNA modifications. We discuss the principles, advantages, and limitations of these developed methods. It is anticipated that new methods and techniques will resolve the current challenges in this burgeoning research field and expedite the elucidation of the functions of DNA modifications.

Packing a punch: understanding how flavours are produced in lager fermentations

Beer is one of the most popular beverages in the world and it has an irreplaceable place in culture. Although invented later than ale, lager beers dominate the current market. Many factors relating to the appearance (colour, clarity and foam stability) and sensory characters (flavour, taste and aroma) of beer, and other psychological determinants affect consumers' perception of the product and defines its drinkability. This review takes a wholistic approach to scrutinise flavour generation in the brewing process, focusing particularly on the contribution of the raw ingredients and the yeasts to the final flavour profiles of lager beers. In addition, we examine current developments to improve lager beer flavour profiles for the modern consumers.

Advances in high resolution GC-MS technology: a focus on the application of GC-Orbitrap-MS in metabolomics and exposomics for FAIR practices

Gas chromatography-mass spectrometry (GC-MS) provides a complementary analytical platform for capturing volatiles, non-polar and (derivatized) polar metabolites and exposures from a diverse array of matrixes. High resolution (HR) GC-MS as a data generation platform can capture data on analytes that are usually not detectable/quantifiable in liquid chromatography mass-spectrometry-based solutions. With the rise of high-resolution accurate mass (HRAM) GC-MS systems such as GC-Orbitrap-MS in the last decade after the time-of-flight (ToF) renaissance, numerous applications have been found in the fields of metabolomics and exposomics. In a short span of time, a multitude of studies have used GC-Orbitrap-MS to generate exciting new high throughput data spanning from diverse basic to applied research areas. The GC-Orbitrap-MS has found application in both targeted and untargeted efforts for capturing metabolomes and exposomes across diverse studies. In this review, I capture and summarize all the reported studies to date, and provide a snapshot of the milieu of commercial and open-source software solutions, spectral libraries, and informatics solutions available to a GC-Orbitrap-MS system instrument user or a data analyst dealing with these datasets. Lastly, but importantly, I provide an account on data sharing and meta-data capturing solutions that are available to make HRAM GC-MS based metabolomics and exposomics studies findable, accessible, interoperable, and reproducible (FAIR). These FAIR practices would allow data generators and users of GC-HRMS instruments to help the community of GC-MS researchers to collaborate and co-develop exciting tools and algorithms in the future.

Hyper-fast gas chromatography and single-photon ionisation time-of-flight mass spectrometry with integrated electrical modulator-based sampling for headspace and online VOC analyses

We developed a novel fast gas chromatography (fastGC) instrument with integrated sampling of volatile organic compounds (VOCs) and detection by single-photon ionisation (SPI) time-of-flight mass spectrometry (TOFMS). A consumable-free electrical modulator rapidly cools down to -55 °C to trap VOCs and inject them on a short chromatographic column by prompt heating to 300 °C, followed by carrier gas exchange from air to helium. Due to the low thermal mass and optical heating, the fastGC is operated within total runtimes including cooling for 30 s and 15 s, referring to hyper-fast GC, and at a constantly increasing temperature ramp from 30 °C to 280 °C. The application of soft SPI-TOFMS allows the detection of co-eluting VOCs of different molecular compositions, which cannot be resolved by conventional GC (cGC) with electron ionisation (EI). Among other analytical figures of merit, we achieved limits of detection for toluene and p-xylene of 2 ppb and 0.5 ppb, respectively, at a signal-to-noise ratio of 3 and a linear response over a range of more than five orders of magnitude. Furthermore, we demonstrate the performance of the instrument on samples from the fields of environmental research and food science by headspace analysis of roasted coffee beans and needles from coniferous trees as well as by quasi-real-time analysis of biomass burning emissions and coffee roast gas.

Preliminary observations on the use of a novel low duty cycle flow modulator for comprehensive two-dimensional gas chromatography

The present research is focused on the preliminary evaluation, in particular in relation to the advisable operational conditions, of a novel low duty cycle flow modulator. In such a respect, a fast comprehensive two-dimensional gas chromatography-mass spectrometry method is herein proposed. Applications on a C₇-C₃₀ series of alkanes, 64 fragrance allergens (plus 2 internal standards), and 5 perfumes, were carried out by using two different column sets, low-polarity + medium-polarity and low-polarity + low-polarity. In both cases, the first column was of dimensions 10 m × 0.25 mm ID × 0.25 µm d_f, while the second one was of dimensions 1 m × 0.10 mm ID × 0.10 µm d_f. A modulation period of 700 ms, with a re-injection period of 80 ms, was used in order to obtain a higher duty cycle (measured to be approx. 0.04). Absolute quantification of the allergens was carried out by using two internal standards, namely 1,4-dibromobenzene and 4,4'-dibromobiphenyl. In terms of limits of quantification the instrumental response was characterized by a wide variability, ranging between 9 ppb and 5.4 ppm for both column sets. A total number of 97 fragrance allergens were identified and quantified in five commercial perfumes.

Techniques and application in comprehensive multidimensional gas chromatography - mass spectrometry

In contrast to the well-known comprehensive two-dimensional gas chromatography (GC×GC) method, it is possible to define comprehensive multidimensional gas chromatography. 'Comprehensiveness' relates to analysis of the whole sample. Two-dimensional and multidimensional here refer to the use of at least two separation stages for analysis, however comprehensive 2DGC now appears to be reserved for the GC×GC method. This may be differentiated from comprehensive MDGC (CMDGC) simply by the analysis time assigned to the second (²D) column, although there does not appear to be a specific definition that relates to this analysis time parameter. A number of different implementation protocols for comprehensive MDGC are described here, that may involve either a single, or multiple, injection(s). In all cases, independent retention must be achieved on each dimension to ensure the probability of enhanced separation. An original application of a crude oil sample is presented to illustrate development of the MDGC approach that incorporates two Deans switches (DS) and a cryogenic trapping approach, performed using a sequential heart-cut (H/C) event method incremented by 0.5 min for each injection; a total of 40 injections is used to analyse the total sample. The higher peak capacity and consequently greater resolution on the long ²D column is illustrated, compared with that expected for conventional GC×GC, with tentative identification in order to classify chemical classes. Incorporating an approach to acquiring retention indices may be implemented, although its utility for petroleum hydrocarbons is limited. Structured groupings of different chemical classes, as exemplified by mono and diaromatics for the crude oil sample, were noted.

A rapid GC method coupled with quadrupole or time of flight mass spectrometry for metabolomics analysis

Gas chromatography-mass spectrometry (GC-MS) is an ideal tool for analyzing the intermediates of tricarboxylic acid cycle and glycolysis, sugars, organic acids and amino acids, etc. High-throughput metabolomics methods are required by large-scale clinical researches, and time of flight mass spectrometry (TOF MS) having fast scanning rate is preferable for rapid GC. Quadrupole MS (qMS) instruments have 95% market share, and their potential in rapid metabolomics is worth being studied. In this work, a within 15-min GC program was established and matched by qMS scanning for plasma metabolome analysis after N-methyl-N-(trimethylsilyl)-trifluoroacetamide derivatization. Compared to the longer-time program GC-qMS method, the rapid GC-qMS method had nearly no metabolome information loss, and it had excellent profile performance in repeatability, intra-day and inter-day precision, sampling range, linearity and extraction recovery. Compared to TOF MS, qMS achieved similar results in investigating lung cancer serum metabolic disruptions. Partial least squares-discriminant analysis revealed that the two datasets acquired by qMS and TOF MS had very similar model parameters, and most of top ranked differential metabolites were the same. This study provides a rapid and economical GC-qMS metabolomics method for researchers. Still, MS having faster scanning rate and higher sensitivity are recommended, if possible, to detect more small peaks and some co-eluted peaks.

Review: Detection and quantification of proteins in human urine

Extensive medical research showed that patients, with high protein concentration in urine, have various kinds of kidney diseases, referred to as proteinuria. Urinary protein biomarkers are useful for diagnosis of many health conditions – kidney and cardio vascular diseases, cancers, diabetes, infections. This review focuses on the instrumental quantification (electrophoresis, chromatography, immunoassays, mass spectrometry, fluorescence spectroscopy, the infrared spectroscopy, and Raman spectroscopy) of proteins (the most of all albumin) in human urine matrix. Different techniques provide unique information on what constituents of the urine are. Due to complex nature of urine, a separation step by electrophoresis or chromatography are often used for proteomics study of urine. Mass spectrometry is a powerful tool for the discovery and the analysis of biomarkers in urine, however, costs of the analysis are high, especially for quantitative analysis. Immunoassays, which often come with fluorescence detection, are major qualitative and quantitative tools in clinical analysis. While Infrared and Raman spectroscopies do not give extensive information about urine, they could become important tools for the routine clinical diagnostics of kidney problems, due to rapidness and low-cost. Thus, it is important to review all the applicable techniques and methods related to urine analysis. In this review, a brief overview of each technique's principle is introduced. Where applicable, research papers about protein determination in urine are summarized with the main figures of merits, such as the limit of detection, the detectable range, recovery and accuracy, when available.

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Urinary protein biomarkers are useful for diagnosis of many conditions: kidney and cardio vascular diseases, cancers.

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Liquid chromatography – mass spectroscopy is a powerful tool for urine proteomics, but used mostly in science.

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Immunoassays are widely used in both clinical and bio-analytical laboratories.

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IR and Raman spectroscopies are promising tools for diagnostics of urine due to low-cost and rapidness.

Comparative antidandruff efficacy of plant extracts prepared from conventional and supercritical fluid extraction method and chemical profiling using GCMS

BACKGROUND

To combat dandruff associated pathogens, supercritical fluid extraction (SFE) can be used as an alternative eco-friendly technique to obtain antimicrobial plant extracts over conventional methods.

OBJECTIVES

The purpose of the study was to compare the yield and antimicrobial potential of extracts obtained by different extraction methods.

METHODS

Extraction was carried out by cold percolation method using ethyl acetate (EA) and SFE using CO₂. Antimicrobial activity was studied against dandruff causing microbes; Malassezia furfur, Propionibacterium acne, and Staphylococcus epidermidis by agar well diffusion and micro broth dilution method. Statistical evaluation was done by principal component analysis (PCA).

RESULTS

The yield was found higher in the ethyl acetate extracts. PCA indicated that among the sixteen extracts, SFE extract of Azadirachta indica leaves was the most influential with the highest F1 score and maximum antimicrobial activity. Cinnamomum zeylanicum SFE extract demonstrated the lowest MIC against P. acne and M. furfur. GC-MS analysis of A. indica extract inferred that ganoderic acid, 13,14-epoxyoleanan-3-ol acetate, henicosanal, 2-heptadecycloxirane were the major phytoconstituents whereas cinnamaldehyde, α- muurolene and caffeic acid were primarily found in cinnamon.

CONCLUSION

Bioactive compounds identified in the extracts of A. indica and C. zeylanicum can be used in natural antidandruff products.

An Affordable Fabrication of a Zeolite-Based Capacitor for Gas Sensing

The development of even more compact, inexpensive, and highly sensitive gas sensors is widespread, even though their performances are still limited and technological improvements are in continuous evolution. Zeolite is a class of material which has received particular attention in different applications due to its interesting adsorption/desorption capabilities. The behavior of a zeolite 4A modified capacitor has been investigated for the adsorption of nitrogen (N₂), nitric oxide (NO) and 1,1-Difluoroethane (C₂H₄F₂), which are of interest in the field of chemical, biological, radiological, and nuclear threats. Sample measurements were carried out in different environmental conditions, and the variation of the sensor electric capacitance was investigated. The dielectric properties were influenced by the type and concentration of gas species in the environment. Higher changes in capacitance were shown during the adsorption of dry air (+4.2%) and fluorinated gas (+7.3%), while lower dielectric variations were found upon exposure to N₂ (-0.4%) and NO (-0.5%). The proposed approach pointed-out that a simple fabrication process may provide a convenient and affordable fabrication of reusable capacitive gas sensor.