Search Results (33)

Exhaled breath analysis is emerging as one of the most promising non-invasive strategies for the early detection of life-threatening diseases, especially lung cancer, where rapid and reliable diagnosis remains a major clinical challenge. In this study, we designed and optimized an electronic nose (e-nose) platform composed of quantum resistive vapor sensors (vQRSs) engineered by polymer-carbon nanotube nanocomposites via spray layer-by-layer assembly. Each sensor was tailored through specific polymer functionalization to tune selectivity and enhance sensitivity toward volatile organic compounds (VOCs) of medical relevance. The sensor array, combined with linear discriminant analysis (LDA), demonstrated the ability to accurately discriminate between cancer-related biomarkers in synthetic blends, even when present at trace concentrations within complex volatile backgrounds. Beyond artificial mixtures, the system successfully distinguished real exhaled breath samples collected under challenging conditions, including before and after smoking and alcohol consumption. These results not only validate the robustness and reproducibility of the vQRS-based array but also highlight its potential as a versatile diagnostic tool. Overall, this work underscores the relevance of nanocomposite chemo-resistive arrays for breathomics and paves the way for their integration into future portable e-nose devices dedicated to telemedicine, continuous monitoring, and early-stage disease diagnosis. Full article

The detection of volatile organic compound (VOC) biomarkers from the volatolome for the anticipated diagnosis of severe diseases such as cancers is made difficult due to the presence of high quantities of H₂O in the collected samples. It has been shown that water molecules tend to compete or combine themselves with analytes, which requires either their removal or the development of more sensitive and discriminant sensors. In this later prospect, a positive effect of poly(hedral oligomeric silsesquioxanes) (POSS) is sought out to enhance the sensitivity of carbon nanotube-based quantum resistive vapour sensors (vQRS). POSS, once copolymerized with methyl methacrylate or styrene, can be used as nano-spacers amplifying the disconnection of the nano-junctions due to swelling of the polymer upon the diffusion of VOC. The amplitude of this phenomenon, which is at the origin of the chemo-resistive behaviour of vQRS, was compared with that of homologue transducers made of poly(styrene) (PS) and poly(methyl methacrylate) (PMMA)-coated carbon nanotube (CNT) random networks. The presence of POSS in PS-based sensors has enhanced their sensitivity by 213 times for toluene, by 268 times for acetone, by 4 times for ethanol, and by 187 times for cyclohexane. Similarly, the presence of POSS in PMMA chains increases the sensitivity of sensors to cyclohexane by 10 times, to ethanol by 45 times, to toluene by 244 times, and to acetone and butanone by 4 times. All transducers were made by spray layer by layer (sLbL) to obtain a hierarchically structured conducting architecture. The transducers’ surface was characterized by scanning electron microscopy (SEM) and atomic force microscopy (AFM) to observe the CNT coating and dispersion level in the matrix. All sensors were tested with twenty-one VOC part of lung and skin cancer biomarkers by using a dynamic vapour analysis (DVA). The vQRS based on POSS copolymers demonstrated much larger chemo-resistive responses (A_R) than the sensors based only on pure polymers and were found to be very selective towards cyclohexane and hexene-1. The PMMA-co-POSS/CNT sensor was able to detect down to 12 ppm of VOC with a very high signal-to-noise ratio (SNR) and to discriminate six VOC among them all with a PCA (principal component analysis) projection. Full article

The anticipated diagnosis of cancers and other fatal diseases from the simple analysis of the volatiles emitted by the body (volatolome) is getting closer and closer from becoming reality. The promises of vapour sensor arrays are to provide a rapid, reliable, non-invasive and ready-to-use method for clinical applications by making an olfactive fingerprint characteristic of people’s health state, to increase their chance of early recovery. However, the different steps of this complex and ambitious process are still paved with difficulties needing innovative answers. The purpose of this review is to provide a statement of the blocs composing the diagnostic chain to identify the improvements still needed. Nanocomposite chemo-resistive transducers have unique prospects to enhance both the selectivity and sensitivity to volatile biomarkers. The variety of their formulations offers multiple possibilities to chemical functionalization and conductive architectures that should provide solutions to discriminations and stability issues. A focus will be made on the protocols for the collection of organic volatile compounds (VOC) from the body, the choice of vapour sensors assembled into an array (e-nose), in particular, chemo-resistive vapour sensors, their principle, fabrication and characteristics, and the way to extract pertinent features and analyse them with suitable algorithms that are able to find and produce a health diagnosis. Full article

Tea is one of the most consumed beverages in the world and presents a great aromatic diversity depending on the origin of the production and the transformation process. Volatile organic compounds (VOCs) greatly contribute to the sensory perception of tea and are excellent markers for traceability and quality. In this work, we analyzed the volatile organic compounds (VOCs) emitted by twenty-six perfectly traced samples of tea with two analytical techniques and two data treatment strategies. First, we performed headspace solid-phase microextraction gas chromatography–mass spectrometry (HS-SPME-GC-MS) as the most widely used reference method for sanitary and quality controls of food. Next, we analyzed the samples with selected-ion flow-tube mass spectrometry (SIFT-MS), an emerging method for direct analysis of food products and aroma. We compared the performances of both techniques to trace the origin and the transformation processes. We selected the forty-eight most relevant markers with HS-SPME-GC-MS and evaluated their concentrations with a flame ionization detector (FID) on the same instrument. This set of markers permitted separation of the origins of samples but did not allow the samples to be differentiated based on the color. The same set of markers was measured with SIFT-MS instrument without success for either origin separation or color differentiation. Finally, a post-processing treatment of raw data signals with an untargeted approach was applied to the GC-MS and SIFT-MS dataset. This strategy allowed a good discrimination of origin and color with both instruments. Advantages and drawbacks of volatile profiles with both instruments were discussed for the traceability and quality assessment of food. Full article

This study investigates the volatolome in an individual with chromhidrosis, utilizing solid-phase microextraction (SPME) and pentane extraction, followed by gas chromatography–mass spectrometry (GC-MS), to identify key volatile organic compounds (VOCs). A total of 31 compounds were identified, including aldehydes, fatty acid esters, and benzoic acid derivatives. SPME was more effective in capturing highly volatile compounds, while pentane extraction primarily isolated lipophilic substances such as squalene and cholesterol. The findings suggest that lipid peroxidation and metabolic dysregulation contribute to the formation of lipofuscin, the pigment responsible for colored sweat. Additionally, the detection of 9-octadecenamide and benzoic acid derivatives highlights the role of oxidative processes in chromhidrosis. Full article

The “Stendesto” plumcot is the only successful Bulgarian plum–apricot hybrid having the “Modesto” apricot and the “Stanley” plum as parents. The current study reports on the metabolites and volatile organic compounds (VOCs) discovered in the three fruits. Forty-one metabolites in total, as represented by amino acids, organic acids, sugar acids and alcohols, phenolic acids, fatty acids, mono- and di-saccharides, and sterols, were identified in the samples. Additionally, sixty-five VOCs were profiled using the gas chromatography/mass spectrometry (GC/MS) analysis and HS-SPME technique. Among these VOCs, alcohols, aldehydes, esters, ketones, lactones, terpenoids, and benzene derivatives were the existing chemical classes. Not all metabolites were present in both apricot and plum, but the hybrid had managed to inherit all of the identified metabolites with the exception of γ-aminobutyric acid. This study is a first on the topic of plumcot fruit evaluation referencing its parental lines. Principal component (PCA) and hierarchical cluster (HCA) analyses further aided in revealing the differences and similarities between the “Stendesto” plum–apricot hybrid and its parents. Full article

Plum–apricot hybrids are the successful backcrosses of plums and apricots. Plums and apricots are well-known and preferred by consumers because of their distinct sensory and beneficial health properties. However, kernel consumption remains limited even though kernels are easily accessible. The “Stendesto” hybrid originates from the “Modesto” apricot and the “Stanley” plum. Kernal metabolites exhibited quantitative differences in terms of metabolites identified by gas chromatography–mass spectrometry (GC–MS) analysis and HS-SPME technique profiling. The results revealed a total of 55 different compounds. Phenolic acids, hydrocarbons, organic acids, fatty acids, sugar acids and alcohols, mono- and disaccharides, as well as amino acids were identified in the studied kernels. The hybrid kernel generally inherited all the metabolites present in the parental kernels. Volatile organic compounds were also investigated. Thirty-five compounds identified as aldehydes, alcohols, ketones, furans, acids, esters, and alkanes were present in the studied samples. Considering volatile organic compounds (VOCs), the hybrid kernel had more resemblance to the plum one, bearing that alkanes were only identified in the apricot kernel. The objective of this study was to investigate the volatile composition and metabolic profile of the first Bulgarian plum–apricot hybrid kernels, and to provide comparable data relevant to both parents. With the aid of principal component analysis (PCA) and hierarchical cluster analysis (HCA), differentiation and clustering of the results occurred in terms of the metabolites present in the plum–apricot hybrid kernels with reference to their parental lines. This study is the first providing information about the metabolic profile of variety-defined kernels. It is also a pioneering study on the comprehensive evaluation of fruit hybrids. Full article

X-ray irradiation is an emerging non-thermal technology that is used as a preservation and sanitization technique to inactivate pathogens and spoilage organisms, increasing the shelf life of products. In this work, two different types of surface-ripened cheeses, Brie and Camembert, produced with cow milk, were treated with X-rays at three dose levels, 2.0, 4.0 and 6.0 kGy, to evaluate the irradiation effects on the volatile profile using a volatolomic approach. The headspace solid-phase microextraction (HS-SPME) technique combined with gas chromatography–mass spectrometry (GC–MS) was used to extract and analyze the volatile fraction from these dairy matrices. The HS-SPME method was optimized by a central composite design in combination with a desirability optimization methodology. The Carboxen/PDMS fiber, 50 °C for extraction temperature and 60 min for time extraction were found to be the best parameter settings and were applied for this investigation. The obtained fingerprints demonstrated that the irradiation-induced changes are dose dependent. The X-ray irradiation produced many new volatiles not found in the non-irradiated samples, but it also varied the amount of some volatiles already present in the control. Specifically, aldehydes and hydrocarbons increased with the irradiation dose, whereas alcohols, carboxylic acids, esters, methyl esters, ketones, lactones and sulfur-containing compounds showed a non-linear dependence on the dose levels; indeed, they increased up to 4.0 kGy, and then decreased slightly at 6.0 kGy. This trend, more evident in the Camembert profile, is probably due to the fact that these compounds are involved in different oxidation mechanisms of lipids and proteins, which were induced by the radiation treatment. In these oxidative chemical changes, the production and degradation processes of the volatiles are competitive, but at higher doses, the decomposition reactions exceed those of formation. A principal component analysis and partial least square discriminant analysis were used to discriminate between the treated and untreated samples. Moreover, this study allowed for the identification of potential markers of X-ray treatment for the two cheeses, confirming this approach as a useful tool for the control of irradiated surface-ripened cheeses. Full article

Headspace solid-phase micro-extraction (HS-SPME) is a prevalent technique in metabolomics and volatolomics research. However, the performance of HS-SPME can vary considerably depending on the sample matrix. As a result, fine-tuning the parameters for each specific sample matrix is crucial to maximize extraction efficacy. In this context, we conducted comprehensive HS-SPME optimization for bronchoalveolar lavage fluid (BALF) samples using two-dimensional gas chromatography with time-of-flight mass spectrometry (GC×GC-ToFMS). Our exploration spanned several HS-SPME parameters, including vial size, dilution factor, extraction time, extraction temperature, and ionic strength. The 10 mL vial size, no sample dilution, extraction time of 50 min, extraction temperature of 45 °C, and 40% salt were identified as the optimized parameters. The optimized method was then evaluated by a pair-wise comparison of ten sets of samples. The results revealed that the optimized method yielded an increase of 340% in total peak area and an increase of 80% in total peak number. Moreover, enhancements were observed across nine major chemical classes in both peak area and number. Notably, the optimized method also doubled the number of volatile compounds consistently detected across BALF samples, from 52 to 108. Full article

Fusarium bulb rot, caused by Fusarium proliferatum, is a worldwide disease of garlic, both in the open field and during storage. Early diagnosis of the disease during storage is difficult due to the morphology of the bulbs and cloves. Volatile organic compounds (VOCs) are secondary metabolites produced by several microorganisms, including phytopathogenic fungi and bacteria. In recent years, the development of several techniques for the detection and characterization of VOCs has prompted their use, among others, as a diagnostic tool for the early and non-destructive analysis of many diseases of species of agricultural interest. In this paper, proton-transfer-reaction time-of-flight mass spectrometry (PTR-ToF-MS) and solid-phase microextraction gas chromatography/mass spectrometry (SPME-GC/MS) were successfully utilized to characterize the volatolome of commercial garlic cloves, artificially and naturally infected with F. proliferatum, for the early discrimination between diseased and healthy ones. A partial least squares discriminant analysis (PLSDA) and a principal component analysis (PCA) allowed for the separation of infected and healthy cloves and the identification of specific VOCs produced by the fungus during the infection. The results obtained in this work could be utilized for the development of simpler, more economical, and more portable devices for the early detection of infected garlic bulbs during storage. Full article

Roses are popular ornamental plants all over the world. Rosa damascena Mill., also known as the damask rose, is a well-known scented rose species cultivated to produce essential oil. The essential oils obtained are high in volatile organic compounds (VOCs), which are in demand across the pharmaceutical, food, perfume, and cosmetic industries. Citronellol, nonadecane, heneicosane, caryophyllene, geraniol, nerol, linalool, and phenyl ethyl acetate are the most important components of the rose essential oil. Abiotic factors, including as environmental stress and stress generated by agricultural practises, frequently exert a selective impact on particular floral characteristics, hence influencing the overall quality and quantity of rose products. Additionally, it has been observed that the existence of stress exerts a notable impact on the chemical composition and abundance of aromatic compounds present in roses. Therefore, understanding the factors that affect the biosynthesis of VOCs, especially those representing the aroma and scent of rose, as a response to abiotic stress is important. This review provides comprehensive information on plant taxonomy, an overview of the volatolomics involving aromatic profiles, and describes the influence of abiotic stresses on the biosynthesis of the VOCs in damask rose. Full article

Microbiota and the metabolites they produce within the large intestine interact with the host epithelia under the influence of a range of host-derived metabolic, immune, and homeostatic factors. This complex host–microbe interaction affects intestinal tumorigenesis, but established microbial or metabolite profiles predicting colorectal cancer (CRC) risk are missing. Here, we aimed to identify fecal bacteria, volatile organic compounds (VOC), and their associations that distinguish healthy (non-adenoma, NA) from CRC prone (high-risk adenoma, HRA) individuals. Analyzing fecal samples obtained from 117 participants ≥15 days past routine colonoscopy, we highlight the higher abundance of Proteobacteria and Parabacteroides distasonis, and the lower abundance of Lachnospiraceae species, Roseburia faecis, Blautia luti, Fusicatenibacter saccharivorans, Eubacterium rectale, and Phascolarctobacterium faecium in the samples of HRA individuals. Volatolomic analysis of samples from 28 participants revealed a higher concentration of five compounds in the feces of HRA individuals, isobutyric acid, methyl butyrate, methyl propionate, 2-hexanone, and 2-pentanone. We used binomial logistic regression modeling, revealing 68 and 96 fecal bacteria-VOC associations at the family and genus level, respectively, that distinguish NA from HRA endpoints. For example, isobutyric acid associations with Lachnospiraceae incertae sedis and Bacteroides genera exhibit positive and negative regression lines for NA and HRA endpoints, respectively. However, the same chemical associates with Coprococcus and Colinsella genera exhibit the reverse regression line trends. Thus, fecal microbiota and VOC profiles and their associations in NA versus HRA individuals indicate the significance of multiple levels of analysis towards the identification of testable CRC risk biomarkers. Full article

Food quality control is an important area to address, as it directly impacts the health of the whole population. To evaluate the food authenticity and quality, the organoleptic feature of the food aroma is very important, such that the composition of volatile organic compounds (VOC) is unique in each aroma, providing a basis to predict the food quality. Different types of analytical approaches have been used to assess the VOC biomarkers and other parameters in the food. The conventional approaches are based on targeted analyses using chromatography and spectroscopies coupled with chemometrics, which are highly sensitive, selective, and accurate to predict food authenticity, ageing, and geographical origin. However, these methods require passive sampling, are expensive, time-consuming, and lack real-time measurements. Alternately, gas sensor-based devices, such as the electronic nose (e-nose), bring a potential solution for the existing limitations of conventional methods, offering a real-time and cheaper point-of-care analysis of food quality assessment. Currently, research advancement in this field involves mainly metal oxide semiconductor-based chemiresistive gas sensors, which are highly sensitive, partially selective, have a short response time, and utilize diverse pattern recognition methods for the classification and identification of biomarkers. Further research interests are emerging in the use of organic nanomaterials in e-noses, which are cheaper and operable at room temperature. Full article

There is a lot of discussion on how viruses (such as influenza and SARS-CoV-2) are transmitted in air, potentially from aerosols and respiratory droplets, and thus it is important to monitor the environment for the presence of an active pathogen. Currently, the presence of viruses is being determined using primarily nucleic acid-based detection methods, such as reverse transcription- polymerase chain reaction (RT-PCR) tests. Antigen tests have also been developed for this purpose. However, most nucleic acid and antigen methods fail to discriminate between a viable and a non-viable virus. Therefore, we present an alternative, innovative, and disruptive approach involving a live-cell sensor microdevice that captures the viruses (and bacteria) from the air, becomes infected by them, and emits signals for an early warning of the presence of pathogens. This perspective outlines the processes and components required for living sensors to monitor the presence of pathogens in built environments and highlights the opportunity to use immune sentinels in the cells of normal human skin to produce monitors for indoor air pollutants. Full article

(1) Background: lung cancer is the world’s deadliest cancer, but early diagnosis helps to improve the cure rate and thus reduce the mortality rate. Annual low-dose computed tomography (LD-CT) screening is an efficient lung cancer-screening program for a high-risk population. However, LD-CT has often been characterized by a higher degree of false-positive results. To meet these challenges, a volatolomic approach, in particular, the breath volatile organic compounds (VOCs) fingerprint analysis, has recently received increased attention for its application in early lung cancer screening thanks to its convenience, non-invasiveness, and being well tolerated by patients. (2) Methods: a LC-MS/MS-based volatolomics analysis was carried out according to P/N 5046800 standard based breath analysis of VOC as novel cancer biomarkers for distinguishing early-stage lung cancer from the healthy control group. The discriminatory accuracy of identified VOCs was assessed using subject work characterization and a random forest risk prediction model. (3) Results: the proposed technique has good performance compared with existing approaches, the differences between the exhaled VOCs of the early lung cancer patients before operation, three to seven days after the operation, as well as four to six weeks after operation under fasting and 1 h after the meal were compared with the healthy controls. The results showed that only 1 h after a meal, the concentration of seven VOCs, including 3-hydroxy-2-butanone (TG-4), glycolaldehyde (TG-7), 2-pentanone (TG-8), acrolein (TG-11), nonaldehyde (TG-19), decanal (TG-20), and crotonaldehyde (TG-22), differ significantly between lung cancer patients and control, with the invasive adenocarcinoma of the lung (IAC) having the most significant difference. (4) Conclusions: this novel, non-invasive approach can improve the detection rate of early lung cancer, and LC-MS/MS-based breath analysis could be a promising method for clinical application. Full article