Detection of axillary perspiration metabolites using ion mobility spectrometry coupled to rapid gas chromatography

Skin emitted volatiles analysis for noninvasive diagnosis: the current advances in sample preparation techniques for biomedical application

Human skin emits a series of volatile compounds from the skin due to various metabolic processes, microbial activity, and several external factors. Changes in the concentration of skin volatile metabolites indicate many diseases, including diabetes, cancer, and infectious diseases. Researchers focused on skin-emitted compounds to gain insight into the pathophysiology of various diseases. In the case of skin volatolomics research, it is noteworthy that sample preparation, sampling protocol, analytical techniques, and comprehensive validation are important for the successful integration of skin metabolic profiles into regular clinical settings. Solid-phase microextraction techniques and polymer-based active sorbent traps were developed to capture the skin-emitted volatile compounds. The primary advantage of these sample preparation techniques is the ability to efficiently and targetedly capture skin metabolites, thus improving the detection of the biomarkers associated with various diseases. In further research, polydimethyl-based patches were utilized for skin research due to their biocompatibility and thermal stability properties. The microextraction sampling tools coupled with high sensitive Gas Chromatography-Mass Spectrometer provided a potential platform for skin volatolomes, thus emerging as a state-of-the-art analytical technique. Later, technological advancements, including the design of wearable sensors, have enriched skin-based research as it can integrate the information from skin-emitted volatile profiles into a portable platform. However, individual-specific hydration, temperature, and skin conditions can influence variations in skin volatile concentration. Considering the subject-specific skin depth, sampling time standardization, and suitable techniques may improve the skin sampling techniques for the potential discovery of various skin-based marker compounds associated with diseases. Here, we have summarised the current research progress, limitations, and technological advances in skin-based sample preparation techniques for disease diagnosis, monitoring, and personalized healthcare applications.

Volatile-compound fingerprinting and discrimination of positional isomers in stamp-pad ink tracing using HS-GC-IMS combined with multivariate statistical analysis

The rising crime rate associated with document forgery has a significant impact on public safety and social stability. In document fraud cases, determining the origin of a particular stamp-pad ink is the most important objective. In this study, a comprehensive analysis of the volatile compounds in quick-drying stamp-pad inks from six commonly used brands were performed for the first time, utilizing a combination of headspace-gas chromatography-ion mobility spectrometry (HS-GC-IMS) and multivariate statistical analysis methods. Visual and comparative analysis of the differential volatile components among different stamp-pad ink samples was conducted using fingerprints and volcano plots. A total of 127 volatile compounds were accurately identified, with ketones, esters, alcohols, and aldehydes being the most abundant compounds in the stamp-pad inks. Hierarchical clustering analysis (HCA), including dendrograms and clustering heatmaps, was utilized to explore the correlations between these compounds and the samples. Additionally, the precise identification of positional isomers and functional group isomers of aliphatic compounds was achieved. To achieve accurate discrimination of various stamp-pad ink samples, a multivariate statistical analysis method was utilized to establish a classification model for them. Based on the results obtained from HS-GC-IMS, effective discrimination among different brands of stamp-pad ink samples was achieved through principal component analysis (PCA) and orthogonal partial least squares discriminant analysis (OPLS-DA). The model exhibited excellent performance, with the fit index of dependent variables (R2Y) and the predictive index of the model (Q2) values of 0.99 and 0.984, respectively. These results provided significant theoretical evidence for the application of HS-GC-IMS as an efficient technique in the analysis of volatile compounds, identification of positional isomers and functional group isomers, as well as tracing the origin of stamp-pad ink and analyzing the formation time of documents.

Investigation of 60Co Irradiation on the Volatile Organic Compounds from Finger Citron (Citri Sarcodactylis Fructus) Using GC-IMS

In recent years, as the desire for a healthy lifestyle has become more widespread, consumers are gaining an increasing appreciation for safe, high-quality food. Researchers are constantly seeking new ways to protect foods from insect pests and fungi. This study used GC-IMS to analyze the volatile organic compounds and flavor characteristics of Finger Citron in response to different doses of 60Co irradiation. The principal component analysis method was used to explore the overall differences in flavor spectra, and a total of 60 compounds were identified. The fingerprints of volatile organic compounds in the samples showed that the volatile organic compounds with doses of 60Co irradiation in about 0 kGy and 5 kGy are similar, while the 10 kGy samples are quite different. The PCA results showed that the similarity between 0 kGy and 5 kGy was slightly higher, and the difference between 10 kGy and other samples was greater. Therefore, it was determined that 60Co irradiation with a 10 kGy intensity has a significant influence on the content of volatile oils components, while 60Co irradiation with a 5 kGy intensity has little effect. Irradiation technology is demonstrated as a promising method of food sterilization, but the irradiation dose and chemical composition must be taken into consideration.

Past, Present, and Future of Human Chemical Communication Research

Although chemical signaling is an essential mode of communication in most vertebrates, it has long been viewed as having negligible effects in humans. However, a growing body of evidence shows that the sense of smell affects human behavior in social contexts ranging from affiliation and parenting to disease avoidance and social threat. This article aims to (a) introduce research on human chemical communication in the historical context of the behavioral sciences; (b) provide a balanced overview of recent advances that describe individual differences in the emission of semiochemicals and the neural mechanisms underpinning their perception, that together demonstrate communicative function; and (c) propose directions for future research toward unraveling the molecular principles involved and understanding the variability in the generation, transmission, and reception of chemical signals in increasingly ecologically valid conditions. Achieving these goals will enable us to address some important societal challenges but are within reach only with the aid of genuinely interdisciplinary approaches.

Exploring the interrelationship between the skin microbiome and skin volatiles: A pilot study

Unravelling the interplay between a human’s microbiome and physiology is a relevant task for understanding the principles underlying human health and disease. With regard to human chemical communication, it is of interest to elucidate the role of the microbiome in shaping or generating volatiles emitted from the human body. In this study, we characterized the microbiome and volatile organic compounds (VOCs) sampled from the neck and axilla of ten participants (five male, five female) on two sampling days, by applying different methodological approaches. Volatiles emitted from the respective skin site were collected for 20 min using textile sampling material and analyzed on two analytical columns with varying polarity of the stationary phase. Microbiome samples were analyzed by a culture approach coupled with MALDI-TOF-MS analysis and a 16S ribosomal RNA gene (16S RNA) sequencing approach. Statistical and advanced data analysis methods revealed that classification of body sites was possible by using VOC and microbiome data sets. Higher classification accuracy was achieved by combination of both data pools. Cutibacterium, Staphylococcus, Micrococcus, Streptococcus, Lawsonella, Anaerococcus, and Corynebacterium species were found to contribute to classification of the body sites by the microbiome. Alkanes, esters, ethers, ketones, aldehydes and cyclic structures were used by the classifier when VOC data were considered. The interdisciplinary methodological platform developed here will enable further investigations of skin microbiome and skin VOCs alterations in physiological and pathological conditions.

Electrochemical multi-analyte point-of-care perspiration sensors using on-chip three-dimensional graphene electrodes

Multi-analyte sensing using exclusively laser-induced graphene (LIG)-based planar electrode systems was developed for sweat analysis. LIG provides 3D structures of graphene, can be manufactured easier than any other carbon electrode also on large scale, and in form of electrodes: hence, it is predestinated for affordable, wearable point-of-care sensors. Here, it is demonstrated that LIG facilitates all three electrochemical sensing strategies (voltammetry, potentiometry, impedance) in a multi-analyte system for sweat analysis. A potentiometric potassium-ion-selective electrode in combination with an electrodeposited Ag/AgCl reference electrode (RE) enabled the detection of potassium ions in the entire physiologically relevant range (1 to 500 mM) with a fast response time, unaffected by the presence of main interfering ions and sweat-collecting materials. A kidney-shaped interdigitated LIG electrode enabled the determination of the overall electrolyte concentration by electrochemical impedance spectroscopy at a fixed frequency. Enzyme-based strategies with amperometric detection share a common RE and were realized with Prussian blue as electron mediator and biocompatible chitosan for enzyme immobilization and protection of the electrode. Using glucose and lactate oxidases, lower limits of detection of 13.7 ± 0.5 μM for glucose and 28 ± 3 μM for lactate were obtained, respectively. The sensor showed a good performance at different pH, with sweat-collecting tissues, on a model skin system and furthermore in synthetic sweat as well as in artificial tear fluid. Response time for each analytical cycle totals 75 s, and hence allows a quasi-continuous and simultaneous monitoring of all analytes. This multi-analyte all-LIG system is therefore a practical, versatile, and most simple strategy for point-of-care applications and has the potential to outcompete standard screen-printed electrodes.