Pitfalls in the Detection of Volatiles Associated with Heated Tobacco and e-Vapor Products When Using PTR-TOF-MS.

We investigated the applicability of proton transfer reaction-time-of-flight mass spectrometry (PTR-TOF-MS) for quantitative analysis of mixtures comprising glycerin, acetol, glycidol, acetaldehyde, acetone, and propylene glycol. While PTR-TOF-MS offers real-time simultaneous determination, the method selectivity is limited when analyzing compounds with identical elemental compositions or when labile compounds present in the mixture produce fragments that generate overlapping ions with other matrix components. In this study, we observed significant fragmentation of glycerin, acetol, glycidol, and propylene glycol during protonation via hydronium ions (H3O+). Nevertheless, specific ions generated by glycerin (m/z 93.055) and propylene glycol (m/z 77.060) enabled their selective detection. To thoroughly investigate the selectivity of the method, various mixtures containing both isotope-labeled and unlabeled compounds were utilized. The experimental findings demonstrated that when samples contained high levels of glycerin, it was not feasible to perform time-resolved analysis in H3O+ mode for acetaldehyde, acetol, and glycidol. To overcome the observed selectivity limitations associated with the H3O+ reagent ions, alternative ionization modes were investigated. The ammonium ion mode proved appropriate for analyzing propylene glycol (m/z 94.086) and acetone (m/z 76.076) mixtures. Concerning the nitric oxide mode, specific m/z were identified for acetaldehyde (m/z 43.018), acetone (m/z 88.039), glycidol (m/z 73.028), and propylene glycol (m/z 75.044). It was concluded that considering the presence of multiple product ions and the potential influence of other compounds, it is crucial to conduct a thorough selectivity assessment when employing PTR-TOF-MS as the sole method for analyzing compounds in complex matrices of unknown composition.

The Classification of VOCs Based on Sensor Images Using a Lightweight Neural Network for Lung Cancer Diagnosis.

The application of artificial intelligence to point-of-care testing (POCT) disease detection has become a hot research field, in which breath detection, which detects the patient's exhaled VOCs, combined with sensor arrays of convolutional neural network (CNN) algorithms as a new lung cancer detection is attracting more researchers' attention. However, the low accuracy, high-complexity computation and large number of parameters make the CNN algorithms difficult to transplant to the embedded system of POCT devices. A lightweight neural network (LTNet) in this work is proposed to deal with this problem, and meanwhile, achieve high-precision classification of acetone and ethanol gases, which are respiratory markers for lung cancer patients. Compared to currently popular lightweight CNN models, such as EfficientNet, LTNet has fewer parameters (32 K) and its training weight size is only 0.155 MB. LTNet achieved an overall classification accuracy of 99.06% and 99.14% in the own mixed gas dataset and the University of California (UCI) dataset, which are both higher than the scores of the six existing models, and it also offers the shortest training (844.38 s and 584.67 s) and inference times (23 s and 14 s) in the same validation sets. Compared to the existing CNN models, LTNet is more suitable for resource-limited POCT devices.

Biomonitoring of volatile organic compounds and organophosphorus flame retardands in commercial aircrews after "fume and smell events".

Health risks to humans after "fume and smell events", short-term incidents on aircrafts that are accompanied by unpleasant odour or visible smoke, remain a subject of controversy. We assessed exposure to volatile organic compounds (VOC) and organophosphorus compounds (OPC) by biomonitoring in 375 aircrew members after self-reported "fume and smell events" and in 88 persons of the general population. A total of 20 parameters were analysed in blood and urine by gas chromatography and mass spectrometry. Median levels of acetone in blood and urine and 2-propanol in blood were elevated in aircrews compared to controls (p < 0.0001). Additionally, elevated peak exposures, best estimated by the 95th percentiles, were observed in aircrews for n-heptane and n-octane in blood, and acetone, 2,5-hexanedione and o-cresol in urine. Only the maximum observed levels of 2,5-hexandione in urine (768 µg/L) and toluene in blood (77 µg/L) in aircrew members were higher than the current biological exposure indices (BEI® levels) (500 and 20 µg/L, respectively) of the American Conference of Governmental Industrial Hygienists (US-ACGIH) for workers occupationally exposed to n-hexane and toluene, two well-accepted human neurotoxicants. Low-level exposures to n-hexane and toluene could be also observed in controls. The majority of OPC parameters in urine, including those of neurotoxic ortho-isomers of tricresylphosphate, were below the limit of quantitation in both aircrews and controls. Our comparative VOC and OPC analyses in biological samples of a large number of aircrew members and controls suggest that exposures are similar in both groups and generally low.

Oxygen Vacancy-Rich Bimetallic Au@Pt Core-Shell Nanosphere-Functionalized Electrospun ZnFe2O4 Nanofibers for Chemiresistive Breath Acetone Detection.

Sensitive and selective acetone detection is of great significance in the fields of environmental protection, industrial production, and individual health monitoring from exhaled breath. To achieve this goal, bimetallic Au@Pt core-shell nanospheres (BNSs) functionalized-electrospun ZnFe2O4 nanofibers (ZFO NFs) are prepared in this work. Compared to pure NFs-650 analogue, the ZFO NFs/BNSs-2 sensor exhibits a stronger mean response (3.32 vs 1.84), quicker response/recovery speeds (33 s/28 s vs 54 s/42 s), and lower operating temperature (188 vs 273 °C) toward 0.5 ppm acetone. Note that an experimental detection limit of 30 ppb is achieved, which ranks among the best cases reported thus far. Besides the demonstrated excellent repeatability, humidity-enhanced response, and long-term stability, the selectivity toward acetone is remarkably improved after BNSs functionalization. Through material characterizations and DFT calculations, all these improvements could be attributed to the boosted oxygen vacancies and abundant Schottky junctions between ZFO NFs and BNSs, and the synergistic catalytic effect of BNSs. This work offers an alternative strategy to realize selective subppm acetone under high-humidity conditions catering for the future requirements of noninvasive breath diabetes diagnosis in the field of individual healthcare.

LC-MS/MS, GC-MS and molecular docking analysis for phytochemical fingerprint and bioactivity of Beta vulgaris L.

The plants that we consume in our daily diet and use as a risk preventer against many diseases have many biological and pharmacological activities. In this study, the phytochemical fingerprint and biological activities of Beta vulgaris L. leaf extract, which are widely consumed in the Black Sea region, were investigated. The leaf parts of the plant were dried in an oven at 35 °C and then ground into powder. The main constituents in B. vulgaris were identified by LC-MS/MS and GC-MS analyses. Phenolic content, betaxanthin and betacyanin levels were investigated in the extracts obtained using three different solvents. The biological activity of the extract was investigated by anti-microbial, anti-mutagenic, anti-proliferative and anti-diabetic activity tests. Anti-diabetic activity was investigated by in vitro enzyme inhibition and in-silico molecular docking was performed to confirm this activity. In the LC-MS analysis of B. vulgaris extract, a major proportion of p_coumaric acid, vannilin, protecatechuic aldehyde and sesamol were detected, while the major essential oils determined by GC-MS analysis were hexahydrofarnesyl acetone and phytol. Among the solvents used, the highest extraction efficiency of 2.4% was obtained in methanol extraction, and 36.2 mg of GAE/g phenolic substance, 5.1 mg/L betacyanin and 4.05 mg/L betaxanthin were determined in the methanol extract. Beta vulgaris, which exhibited broad-spectrum anti-microbial activity by forming a zone of inhibition against all tested bacteria, exhibited anti-mutagenic activity in the range of 35.9-61.8% against various chromosomal abnormalities. Beta vulgaris extract, which did not exhibit mutagenic, sub-lethal or lethal effects, exhibited anti-proliferative activity by reducing proliferation in Allium root tip cells by 21.7%. 50 mg/mL B. vulgaris extract caused 58.9% and 55.9% inhibition of α-amylase and α-glucosidase activity, respectively. The interactions of coumaric acid, vanniline, hexahydrofarnesyl acetone and phytol, which are major compounds in phytochemical content, with α-amylase and α-glucosidase were investigated by in silico molecular docking and interactions between molecules via various amino acids were determined. Binding energies between the tested compounds and α-amylase were obtained in the range of - 4.3 kcal/mol and - 6.1 kcal/mol, while for α-glucosidase it was obtained in the range of - 3.7 kcal/mol and - 5.7 kcal/mol. The biological activities of B. vulgaris are closely related to the active compounds it contains, and therefore studies investigating the phytochemical contents of plants are very important. Safe and non-toxic plant extracts can help reduce the risk of various diseases, such as diabetes, and serve as an alternative or complement to current pharmaceutical practices.

Quantifying exhaled acetone and isoprene through solid phase microextraction and gas chromatography-mass spectrometry.

BACKGROUND: Acetone, isoprene, and other volatile organic compounds (VOCs) in exhaled breath have been shown to be biomarkers for many medical conditions. Researchers use different techniques for VOC detection, including solid phase microextraction (SPME), to preconcentrate volatile analytes prior to instrumental analysis by gas chromatography-mass spectrometry (GC-MS). These techniques include a previously developed method to detect VOCs in breath directly using SPME, but it is uncommon for studies to quantify exhaled volatiles because it can be time consuming due to the need of many external/internal standards, and there is no standardized or widely accepted method. The objective of this study was to develop an accessible method to quantify acetone and isoprene in breath by SPME GC-MS. RESULTS: A system was developed to mimic human exhalation and expose VOCs to a SPME fiber in the gas phase at known concentrations. VOCs were bubbled/diluted with dry air at a fixed flow rate, duration, and volume that was comparable to a previously developed breath sampling method. Identification of acetone and isoprene through GC-MS was verified using standards and observing overlaps in chromatographic retention/mass spectral fragmentation. Calibration curves were developed for these two analytes, which showed a high degree of linear correlation. Acetone and isoprene displayed limits of detection/quantification equal to 12 ppb/37 ppb and 73 ppb/222 ppb respectively. Quantification results in healthy breath samples (n = 15) showed acetone concentrations spanned between 71 ppb and 294 ppb, and isoprene varied between 170 ppb and 990 ppb. Both concentration ranges for acetone and isoprene in this study overlap with those reported in existing literature. SIGNIFICANCE: Results indicate the development of a system to quantify acetone and isoprene in breath that can be adapted to diverse sampling methods and instrumental analyses beyond SPME GC-MS.

Nanowire Array Breath Acetone Sensor for Diabetes Monitoring.

Diabetic ketoacidosis (DKA) is a life-threatening acute complication of diabetes characterized by the accumulation of ketone bodies in the blood. Breath acetone, a ketone, directly correlates with blood ketones. Therefore, monitoring breath acetone can significantly enhance the safety and efficacy of diabetes care. In this work, the design and fabrication of an InP/Pt/chitosan nanowire array-based chemiresistive acetone sensor is reported. By incorporation of chitosan as a surface-functional layer and a Pt Schottky contact for efficient charge transfer processes and photovoltaic effect, self-powered, highly selective acetone sensing is achieved. The sensor has exhibited an ultra-wide acetone detection range from sub-ppb to >100 000 ppm level at room temperature, covering those in the exhaled breath from healthy individuals (300-800 ppb) to people at high risk of DKA (>75 ppm). The nanowire sensor has also been successfully integrated into a handheld breath testing prototype, the Ketowhistle, which can successfully detect different ranges of acetone concentrations in simulated breath samples. The Ketowhistle demonstrates the immediate potential for non-invasive ketone monitoring for people living with diabetes, in particular for DKA prevention.

Volatile organic compounds for diagnosis of early hepatocellular carcinoma in at-risk patients.

BACKGROUND: Volatile organic compounds (VOCs) have been shown as promising biomarkers for hepatocellular carcinoma (HCC) diagnosis. We aimed to investigate the performance of VOCs for diagnosing early-stage HCC in patients at-risk for HCC. METHODS: VOCs were identified in exhaled breath samples collected from 87 early-stage HCC patients, 90 cirrhotic patients, and 72 HBV-infected patients using thermal desorption-gas chromatography/field-asymmetric ion mobility spectrometry. The VOC levels were compared between the three groups. An association between VOCs and HCC was determined using logistic regression analysis. Diagnostic performance of VOCs was estimated using the AUROC and compared to serum alpha-fetoprotein (AFP). RESULTS: The levels of acetone monomer, dimethyl sulfide, 1,4-pentadiene, isopropyl alcohol, and acetone dimer were significantly different between the three groups. After adjusting for liver function test and AFP, acetone dimer was significantly associated with HCC. Acetone dimer significantly outperformed AFP with 86.2 % vs. 61.2 % sensitivity, 87.6 % vs. 66.2 % specificity, 86.9 % vs. 63.5 % for accuracy, and AUROC of 0.908 vs. 0.665, p = 0.007, <0.001, <0.001, and 0.001, respectively, for differentiating between HCC and cirrhosis. CONCLUSION: Acetone showed a better performance than AFP for diagnosing early HCC in at-risk patients. Further studies to validate the utility of VOCs as an HCC surveillance tool are needed.

Getting the phase consistent: The importance of phase description in balanced steady-state free precession MRI of multi-compartment systems.

PURPOSE: Determine the correct mathematical phase description for balanced steady-state free precession (bSSFP) signals in multi-compartment systems. THEORY AND METHODS: Based on published bSSFP signal models, different phase descriptions can be formulated: one predicting the presence and the other predicting the absence of destructive interference effects in multi-compartment systems. Numerical simulations of bSSFP signals of water and acetone were performed to evaluate the predictions of these different phase descriptions. For experimental validation, bSSFP profiles were measured at 3T using phase-cycled bSSFP acquisitions performed in a phantom containing mixtures of water and acetone, which replicates a system with two signal components. Localized single voxel MRS was performed at 7T to determine the relative chemical shift of the acetone-water mixtures. RESULTS: Based on the choice of phase description, the simulated bSSFP profiles of water-acetone mixtures varied significantly, either displaying or lacking destructive interference effects, as predicted theoretically. In phantom experiments, destructive interference was consistently observed in the measured bSSFP profiles of water-acetone mixtures, supporting the theoretical description that predicts such interference effects. The connection between the choice of phase description and predicted observation enables unambiguous experimental identification of the correct phase description for multi-compartment bSSFP profiles, which is consistent with the Bloch equations. CONCLUSION: The study emphasizes that consistent phase descriptions are crucial for accurately describing multi-compartment bSSFP signals, as incorrect phase descriptions result in erroneous predictions.

Breath-based biosensors and system development for noninvasive detection of diabetes: A review.

BACKGROUND AND AIMS: In recent years, noninvasive techniques are becoming conspicuous for diabetes detection. Sweat, tear, saliva, urine and breath-based methods showing prominent results in breath acetone detection which is considered as a biomarker of diabetes. A concrete relationship between breath acetone and BG helps in the development of devices for diabetes detection. METHODS: The primary source for this study includes scholarly publications that primarily focus on the development of biosensors and systems for diabetes detection using acetone present in breath. Articles were analysed to examine various types of biosensors with their sensing materials to provide acetone detection limits. Recent noninvasive systems and products have been investigated and determine the relationship between breath acetone and BG levels. RESULTS: Breath-based biosensor technologies are capable for diabetes detection. The acetone biosensor detection ranges from 100 ppb to 100 ppm, and it can applicable from room temperature to 400 °C. In healthy volunteers, acetone level ranges from 0.32 to 2.19 ppm, while patients with diabetes exhibit a wider range of 0.22-21 ppm depending on the biosensor, detection method, and clinical circumstances of patients and lab conditions. CONCLUSION: This manuscript presents an extensive analysis of breath-based biosensors and their potential for detection of diabetes. Acetone detection methods are promising but unable to provide concrete correlation between breath acetone and blood glucose levels. The present study motivates the continued research and development of biosensors, and electronic devices to provide linear relationship of breath acetone and BG for noninvasive diabetes detection applications.

Mixed Potential Type Acetone Sensor with Ultralow Detection Limit for Diabetic Ketosis Breath Analysis.

Breath analysis using gas sensors is an emerging method for disease screening and diagnosis. Since it is closely related to the lipid metabolism and blood ketone concentration of the body, the detection of acetone content in exhaled breath is helpful for the screening and monitoring of diabetes and ketosis. The development of an acetone sensor with high selectivity, stability, and low detection limit has been the research focus for this purpose. Here, we developed a mixed potential type acetone sensor based on Gd2Zr2O7 solid electrolyte and CoSb2O6 sensing electrode. The developed sensor exhibits an extremely low detection limit of 10 ppb, enabling linear detection for acetone in an extremely wide range of 10 ppb-100 ppm. The good results of systematic evaluation on selectivity, repeatability, and stability prove the superior reliability of the sensor, which is a prerequisite for the application in actual breath detection. The ability of the sensor to distinguish healthy people from diabetic ketosis patients was confirmed by using the sensor to detect the breath of healthy people and diabetic patients, proving the feasibility of the sensor in the diagnosis and monitoring of diabetic ketosis.

A novel coupling technique based on thermal desorption gas chromatography with mass spectrometry and ion mobility spectrometry for breath analysis.

Exhaled breath analysis is evolving into an increasingly important non-invasive diagnostic tool. Volatile organic compounds (VOCs) in breath contain information about health status and are promising biomarkers for several diseases, including respiratory infections caused by bacteria. To monitor the composition of VOCs in breath or the emission of VOCs from bacteria, sensitive analytical techniques are required. Next to mass spectrometry, ion mobility spectrometry (IMS) is considered a promising analytical tool for detecting gaseous analytes in the parts per billion by volume to parts per trillion by volume range. This work presents a new, dual coupling of thermal desorption gas chromatography to a quadrupole mass spectrometer (MS) and an IMS by operating a simple splitter. Nearly identical retention times can be reached in the range of up to 30 min with slight deviations of 0.06 min-0.24 min. This enables the identification of unknown compounds in the IMS chromatogram using unambiguous mass spectral identification, as there are still no commercially available databases for IMS. It is also possible to discriminate one of the detectors using the splitter to improve detection limits. Using a test liquid mixture of seven ketones, namely 2-butanone, 2-pentanone, 2-hexanone, 2-heptanone, 2-octanone, 2-nonanone, and 2-decanone with a concentration of 0.01 g l-1reproducibilities ranging from 3.0% to 7.6% for MS and 2.2%-5.3%, for IMS were obtained, respectively. In order to test the system optimized here for the field of breath analysis, characteristic VOCs such as ethanol, isoprene, acetone, 2-propanol, and 1-propanol were successfully identified in exhaled air using the dual detector system due to the match of the corresponding IMS, and MS spectra. The presented results may be considered to be a starting point for the greater use of IMS in combination with MS within the medical field.

Acetone Detection and Classification as Biomarker of Diabetes Mellitus Using a Quartz Crystal Microbalance Gas Sensor Array.

A gas sensor array was developed and evaluated using four high-frequency quartz crystal microbalance devices (with a 30 MHz resonant frequency in fundamental mode). The QCM devices were coated with ethyl cellulose (EC), polymethylmethacrylate (PMMA), Apiezon L (ApL), and Apiezon T (ApT) sensing films, and deposited by the ultrasonic atomization method. The objective of this research was to propose a non-invasive technique for acetone biomarker detection, which is associated with diabetes mellitus disease. The gas sensor array was exposed to methanol, ethanol, isopropanol, and acetone biomarkers in four different concentrations, corresponding to 1, 5, 10, and 15 µL, at temperature of 22 °C and relative humidity of 20%. These samples were used because human breath contains them and they are used for disease detection. Moreover, the gas sensor responses were analyzed using principal component analysis and discriminant analysis, achieving the classification of the acetone biomarker with a 100% membership percentage when its concentration varies from 327 to 4908 ppm, and its identification from methanol, ethanol, and isopropanol.

Mass Specthoscope: A Hand-held Extendable Probe for Localized Noninvasive Sampling of Skin Volatome for Online Analysis.

Human skin emits a unique set of volatile organic compounds (VOCs). These VOCs can be probed in order to obtain physiological information about the individuals. However, extracting the VOCs that emanate from human skin for analysis is troublesome and time-consuming. Therefore, we have developed "Mass Specthoscope"─a convenient tool for rapid sampling and detecting VOCs emitted by human skin. The hand-held probe with a pressurized tip and wireless button enables sampling VOCs from surfaces and their transfer to the atmospheric pressure chemical ionization source of quadrupole time-of-flight mass spectrometer. The system was characterized using chemical standards (acetone, benzaldehyde, sulcatone, α-pinene, and decanal). The limits of detection are in the range from 2.25 × 10-5 to 3.79 × 10-5 mol m-2. The system was initially tested by detecting VOCs emanating from porcine skin spiked with VOCs as well as unspiked fresh and spoiled ham. In the main test, the skin of nine healthy participants was probed with the Mass Specthoscope. The sampling regions included the armpit, forearm, and forehead. Numerous skin-related VOC signals were detected. In the final test, one participant ingested a fenugreek drink, and the participant's skin surface was probed using the Mass Specthoscope hourly during the 8 h period. The result revealed a gradual release of fenugreek-related VOCs from the skin. We believe that this analytical approach has the potential to be used in metabolomic studies and following further identification of disease biomarkers─also in noninvasive diagnostics.

Association between hyperketolactia and production in early-lactating dairy cows.

Study aims were to investigate associations of hyperketolactia (HYKL) status of Holstein dairy cows between 6 and 60 d in milk (DIM), defined by milk acetone (mACE) and ß-hydroxybutyrate (mBHB) content, with daily milk yield and composition. Milk samples (∼5.0 million) were collected over a 5-yr period (2014-2019) within the milk recording system in Poland. Concentrations of mACE and mBHB determined by Fourier-transform infrared spectroscopy were used to categorize samples into 4 ketolactia groups. Based on threshold values of ≥0.15 mmol/L mACE and ≥0.10 mmol/L mBHB, ketolactia groups were normoketolactia (NKL; mACE <0.15 mmol/L and mBHB <0.10 mmol/L), BHB hyperketolactia (HYKLBHB; mACE <0.15 mmol/L and mBHB ≥0.10 mmol/L), ACE hyperketolactia (HYKLACE; mACE ≥0.15 mmol/L and mBHB <0.10 mmol/L), and ACE and BHB hyperketolactia (HYKLACEBHB; mACE ≥0.15 mmol/L and mBHB ≥0.10 mmol/L). To investigate ketolactia association with production outcomes, a linear model was developed, including ketolactia group, DIM, parity, their interactions, year-season as fixed effects, and random effects of herd and cow. Among all milk samples, 31.2% were classified as HYKL, and of these, 52.6%, 39.6%, and 7.8% were HYKLACEBHB, HYKLBHB, and HYKLACE, respectively. Ketolactia groups differed for all traits studied in all parities and DIM. Among HYKL groups, lowest milk yield was found in HYKLACEBHB cows, except for 6 to 30 DIM in first- and second-lactation cows. Milk yield of HYKLBHB cows was higher than that of NKL cows until 20 to 30 DIM, and then it was lower than NKL cows. Milk yield of HYKLACE cows was mostly lower than NKL cows. Energy-corrected milk (ECM) yield of HYKLACEBHB cows was higher than that of NKL cows until 30 to 35 DIM for second lactation and third lactation or greater, and in the whole study period for first lactation. The yield of ECM for HYKLBHB cows was mostly higher than that of NKL cows, whereas HYKLACE cows had higher ECM than NKL cows until 15 to 25 DIM and then was lower for the HYKLACE group. Milk composition differed among HYKL groups. Highest milk fat (MF) and lowest milk lactose (ML) contents were observed in HYKLACEBHB cows. Cows in HYKLACEBHB and HYKLBHB groups had higher MF and lower milk protein (MP; except in 6-8 DIM in first lactation) and ML content than NKL cows. Milk fat content was higher in HYKLACE than NKL cows in first lactation and during the first 30 to 40 DIM in older cows. Lactose content was lower in HYKLACE than in NKL cows within 30 to 40 DIM; afterward it was higher in NKL cows. Lower MP content was found in HYKLACE than in NKL cows, except during 6 to 9 DIM for cows in first lactation and third lactation or greater. In conclusion, HYKL is associated with altered milk production in all parities, but a range of these negative relations depends on ketone status addressing both ACE and BHB contents. Further research is needed to ascertain underpinning biochemical defects of HYKL from elevated ACE, alone or in combination with BHB, during early lactation.

Low level detection of acetone vapor by improvised design of high "Q" tunable frequency Helmholtz photoacoustic cell using UV, mid- IR and THz sources.

The paper reports the designing and fabrication aspects of a high "Q = 492.3" Helmholtz photoacoustic (PA) cell employed for the trace level detection of acetone, a biomarker by using 266 nm- UV, Mid-IR (5.4-10.6 micron) and 0.11 Terahertz (THz) sources. The designed Helmholtz PA cell is made of Aluminum and possesses a natural frequency tunable between 1.4 to 4.4 kHz range using a movable piston arrangement of the microphone sensor. Numerous types of disorders, including diabetes, asthma, lung cancer, etc., can be diagnosed using the acetone concentration obtained through breath analysis. The comparative study is related to the response of different types of excitation mechanisms contributed by electronics, vibrational and rotational modes of acetone. The low-level detection (LoD) limit for acetone is of the order of 5.06 & 7.92 ppbV, and 15.3 pptV, respectively, in UV, Mid-IR, and THz region. This study contributes to the development of a highly sensitive, non-invasive acetone detection and quantification modality.

Phytochemical Profiling, Antimicrobial, Antiproliferative and Apoptotic Effects of Stemodia viscosa Roxb. of Western Ghats Region, India.

The present study shows the chemical profile, antimicrobial, antiproliferative, and apoptotic effects of Stemodia viscosa extracts. Thirteen bioactive compounds were identified in the 80 % ethanolic extract by GC/MS analysis. The acetone extract exhibited a higher content of flavonoids and phenols of 805.10 µg QE/mg DW and 89.31 µg GAE/mg DW extracts, respectively. Furthermore, the acetone extract possessed the highest antioxidant activity (IC50 =9.96 µg/mL). The 80 % ethanolic extract exhibited significant antimicrobial activity; the highest activity was observed against Staphylococcus aureus with a zone of inhibition of 25±0.51 mm, MIC value of 4 mg/mL, and MBC value of 8 mg/mL. The antiproliferative results revealed the presence of anticancer activity with an IC50 =91.562 and 74.362 µg/mL against the B16F10 skin and COLO205 colon cancer cells, respectively. The flow cytometric analysis shows that the plant extracts cause cancer cell death through the induction of apoptosis. Our findings confirmed that Stemodia viscosa is a potential source of biologically active compounds.

Influence of ventilatory parameters on the concentration of exhaled volatile organic compounds in mechanically ventilated patients.

Analysis of volatile organic compounds (VOC) within exhaled breath is subject to numerous sources of methodological and physiological variability. Whilst breathing pattern is expected to influence the concentrations of selected exhaled VOCs, it remains challenging to investigate respiratory rate and depth accurately in awake subjects. Online breath sampling was performed in 20 mechanically ventilated patients using proton transfer reaction time-of-flight mass spectrometry (PTR-ToF-MS). The effect of variation in respiratory rate (RR) and tidal volume (TV) on the VOC release profiles was examined. A panel of nineteen VOCs were selected, including isoprene, acetone, propofol, volatile aldehydes, acids and phenols. Variation in RR had the greatest influence on exhaled isoprene levels, with maximum and average concentrations being inversely correlated with RR. Variations in RR had a statistically significant impact on acetone, C3-C7 linear aldehydes and acetic acid. In comparison, phenols (including propofol), C8-C10 aldehydes and C3-C6 carboxylic acids were not influenced by RR. Isoprene was the only compound to be influenced by variation in TV. These findings, obtained under controlled conditions, provide useful guidelines for the optimisation of breath sampling protocols to be applied on awake patients.

Dynamic Breath Limonene Sensing at High Selectivity.

Liver diseases (e.g., cirrhosis, cancer) cause more than two million deaths per year worldwide. This is partly attributed to late diagnosis and insufficient screening techniques. A promising biomarker for noninvasive and inexpensive liver disease screening is breath limonene that can indicate a deficiency of the cytochrome P450 liver enzymes. Here, we introduce a compact and low-cost detector for dynamic and selective breath limonene sensing. It comprises a chemoresistive sensor based on Si/WO3 nanoparticles pre-screened by a packed bed Tenax separation column at room temperature. We demonstrate selective limonene detection down to 20 parts per billion over up to three orders of magnitude higher concentrated acetone, ethanol, hydrogen, methanol, and 2-propanol in gas mixtures, as well as robustness to 10-90% relative humidity. Most importantly, this detector recognizes the individual breath limonene dynamics of four healthy volunteers following the ingestion (swallowing or chewing) of a limonene capsule. Limonene release and subsequent metabolization are monitored from breath measurements in real time and in excellent agreement (R2 = 0.98) with high-resolution proton transfer reaction mass spectrometry. This study demonstrates the potential of the detector as a simple-to-use and noninvasive device for the routine monitoring of limonene levels in exhaled breath to facilitate early diagnosis of liver dysfunction.

Methods to Detect Volatile Organic Compounds for Breath Biopsy Using Solid-Phase Microextraction and Gas Chromatography-Mass Spectrometry.

Volatile organic compounds (VOCs) are byproducts from metabolic pathways that can be detected in exhaled breath and have been reported as biomarkers for different diseases. The gold standard for analysis is gas chromatography-mass spectrometry (GC-MS), which can be coupled with various sampling methods. The current study aims to develop and compare different methods for sampling and preconcentrating VOCs using solid-phase microextraction (SPME). An in-house sampling method, direct-breath SPME (DB-SPME), was developed to directly extract VOCs from breath using a SPME fiber. The method was optimized by exploring different SPME types, the overall exhalation volume, and breath fractionation. DB-SPME was quantitatively compared to two alternative methods involving the collection of breath in a Tedlar bag. In one method, VOCs were directly extracted from the Tedlar bag (Tedlar-SPME) and in the other, the VOCs were cryothermally transferred from the Tedlar bag to a headspace vial (cryotransfer). The methods were verified and quantitatively compared using breath samples (n = 15 for each method respectively) analyzed by GC-MS quadrupole time-of-flight (QTOF) for compounds including but not limited to acetone, isoprene, toluene, limonene, and pinene. The cryotransfer method was the most sensitive, demonstrating the strongest signal for the majority of the VOCs detected in the exhaled breath samples. However, VOCs with low molecular weights, including acetone and isoprene, were detected with the highest sensitivity using the Tedlar-SPME. On the other hand, the DB-SPME was less sensitive, although it was rapid and had the lowest background GC-MS signal. Overall, the three breath-sampling methods can detect a wide variety of VOCs in breath. The cryotransfer method may be optimal when collecting a large number of samples using Tedlar bags, as it allows the long-term storage of VOCs at low temperatures (-80 °C), while Tedlar-SPME may be more effective when targeting relatively small VOCs. The DB-SPME method may be the most efficient when more immediate analyses and results are required.