Secondhand vaping exposure is an emerging public health concern that remains understudied. In this study, saliva and exhaled emissions from ENDS users (secondhand) and non-ENDS users (baseline) were collected, firsthand emissions were generated using an automated ENDS aerosol generation system programmed to simulate puffing topography profiles collected from ENDS users. Particulate concentrations and sizes along with volatile organic compounds were characterized. We revealed puffing topography metrics as potential mediators of firsthand and secondhand particle and chemical exposures, as well as metabolic and respiratory health outcomes. Particle deposition modeling revealed that while secondhand emissions displayed smaller deposited mass, total and pulmonary particle deposition fractions were higher than firsthand deposition levels, possibly due to smaller secondhand emission particle diameters. Lastly, untargeted metabolomic profiling of salivary biomarkers of lung injury due to firsthand ENDS exposures revealed potential early indicators of respiratory distress that may also be relevant in bystanders exposed to secondhand vaping scenarios. By leveraging system toxicology, we identified 10 metabolites, including leukotriene D4, that could potentially serve as biomarkers for ENDS use, exposure estimation, and the prediction of vaping-related disease. This study highlights characterization of vaping behavior is an important exposure component in advancing our understanding of potential health effects in ENDS users and bystanders.

[This corrects the article DOI: 10.3389/fpubh.2023.1195779.].

Conventional screening options for colorectal cancer (CRC) detection are mainly direct visualization and invasive methods including colonoscopy and flexible sigmoidoscopy, which must be performed in a clinical setting and may be linked to adverse effects for some patients. Non-invasive CRC diagnostic tests such as computed tomography colonography and stool tests are either too costly or less reliable than invasive ones. On the other hand, volatile organic compounds (VOCs) are potentially ideal non-invasive biomarkers for CRC detection and monitoring. The present review is a comprehensive presentation of the current state-of-the-art VOC-based CRC diagnostics, with a specific focus on recent advancements in biosensor design and application. Among them, breath-based chromatography pattern analysis and sampling techniques are overviewed, along with nanoparticle-based optical and electrochemical biosensor approaches. Limitations of the currently available technologies are also discussed with an outlook for improvement in combination with big data analytics and advanced instrumentation, as well as expanding the scope and specificity of CRC-related volatile biomarkers.

A promising pollution control technology is cold plasma driven chemical processing. The plasma is a pulsed electric gas discharge inside a near atmospheric-pressure-temperature reactor. The system is energized by a continuous stream of very short high-voltage pulses. The exhaust gas to be treated flows through the reactor. The methods applied involve the development of robust cold plasma systems, industrial applications and measuring technologies. Tests of the systems were performed at many industrial sites and involved control of airborne VOC (volatile organic compound) and odor. Electrical, chemical and odor measuring data were collected with state-of-the-art methods. To explain the test data an approximate solution of global reaction kinetics of pulsed plasma chemistry was developed. It involves the Lambert function and, for convenience, a simple approximation of it. The latter shows that the amount of removal, in good approximation, is a function of a single variable. This variable is electric plasma power divided by gas flow divided by input concentration. In the results sections we show that in some cases up to 99% of volatile pollution can be removed at an acceptable energy requirement. In the final sections we look into future efficiency enhancements by implementation of (sub)nanosecond pulsed plasma and solid state high-voltage technology and by integration with catalyst technology.

Plants emit a range of volatile organic compounds (VOCs) as a way of interacting with their biotic and abiotic surroundings. These VOCs can have various ecological functions, such as attracting pollinators, repelling herbivores, or may be emitted in response to abiotic stress. For the present dataset, we used gas chromatography coupled ion mobility spectrometry (GC-IMS) to analyse the VOCs emitted by different plant species under controlled conditions. GC-IMS is a rapid and sensitive technique for gas phase analysis, that separates VOCs based on their retention time and drift time, resulting in characteristic heatmaps where the xy-position of a signal corresponds to compound identity, while signal intensity reflects its abundance. In this dataset, rapid analysis by GC-IMS was used to record emission pattern of 140 plant species from different taxonomic groups. This includes both floral volatiles and emission from leaves after induced damage. The data was pre-evaluated and listed in one table, containing information on the plant material used, as well as information on the respective emission patterns (including already identified compounds). Thus, this dataset provides a broad overview over plant VOC emissions. These can be used to either check the distribution of knowns substances, or the specific emissions of plants for functional, ecological or physiological studies or as the starting point for chemotaxonomic studies. The extraordinary ease with which these data can be generated - with the suitable set-up - lends itself to larger scale systematic or ecological studies across plant (or animal) groups and even ecosystems.

One of the methods to inactivate viruses is to denature viral proteins using released ions. However, there have been no reports detailing the effects of changes in humidity or contamination with body fluids on the inactivation of viruses. This study investigated the effects of humidity changes and saliva contamination on the efficacy of SARS-CoV-2 inactivation with ions using multiple viral strains. Virus solutions with different infectious titers were dropped onto a circular nitrocellulose membrane and irradiated with ions from 10 cm above the membrane. After the irradiation of ions for 60, 90, and 120 min, changes in viral infectious titers were measured. The effect of ions on virus inactivation under different humidity conditions was also examined using virus solutions containing 90% mixtures of saliva collected from 10 people. A decrease in viral infectivity was observed over time for all strains, but ion irradiation further accelerated the decrease in viral infectivity. Ion irradiation can inactivate all viral strains, but at 80% humidity, the effect did not appear until 90 min after irradiation. The presence of saliva protected the virus from drying and maintained infectiousness for a longer period compared with no saliva. In particular, the Omicron strain retained its infectivity titer longer than the other strains. Ion irradiation demonstrated a consistent reduction in the number of infectious viruses when compared to the control across varying levels of humidity and irradiation periods. This underscores the notable effectiveness of irradiation, even when the reduction effect is as modest as 50%, thereby emphasizing its crucial role in mitigating the rapid dissemination of SARS-CoV-2.

Significant progress has been made in two-dimensional material-based sensing devices over the past decade. Organic vapor sensors, particularly those using graphene and transition metal dichalcogenides as key components, have demonstrated excellent sensitivity. These sensors are highly active because all the atoms in the ultra-thin layers are exposed to volatile compounds. However, their selectivity needs improvement. We propose a novel gas-sensing device that addresses this challenge. It consists of two side-by-side sensors fabricated from the same active material, few-layer molybdenum disulfide (MoS₂), for detecting volatile organic compounds like alcohol, acetone, and toluene. To create a dual-channel sensor, we introduce a simple step into the conventional 2D material sensor fabrication process. This step involves treating one-half of the few-layer MoS₂ using ultraviolet-ozone (UV-O3) treatment. The responses of pristine few-layer MoS₂ sensors to 3000 ppm of ethanol, acetone, and toluene gases are 18%, 3.5%, and 49%, respectively. The UV-O3-treated few-layer MoS₂-based sensors show responses of 13.4%, 3.1%, and 6.7%, respectively. This dual-channel sensing device demonstrates a 7-fold improvement in selectivity for toluene gas against ethanol and acetone. Our work sheds light on understanding surface processes and interaction mechanisms at the interface between transition metal dichalcogenides and volatile organic compounds, leading to enhanced sensitivity and selectivity.

This study aimed to assess the redox status and trace metal levels in 49 shoe industry workers (11 men and 38 women) occupationally exposed to a mixture of volatile organic compounds (VOCs), which includes aliphatic hydrocarbons, aromatic hydrocarbons, ketones, esters, ethers, and carboxylic acids. All measured VOCs were below the permitted occupational exposure limits. The control group included 50 unexposed participants (25 men and 25 women). The following plasma parameters were analysed: superoxide anion (O2 •-), advanced oxidation protein products (AOPP), total oxidative status (TOS), prooxidant-antioxidant balance (PAB), oxidative stress index (OSI), superoxide dismutase (SOD) and paraoxonase-1 (PON1) enzyme activity, total SH group content (SHG), and total antioxidant status (TAS). Trace metal levels (copper, zinc, iron, magnesium, and manganese) were analysed in whole blood. All oxidative stress and antioxidative defence parameters were higher in the exposed workers than controls, except for PON1 activity. Higher Fe, Mg, and Zn, and lower Cu were observed in the exposed vs control men, while the exposed women had higher Fe and lower Mg, Zn, and Cu than their controls. Our findings confirm that combined exposure to a mixture of VOCs, even at permitted levels, may result in additive or synergistic adverse health effects and related disorders. This raises concern about current risk assessments, which mainly rely on the effects of individual chemicals, and calls for risk assessment approaches that can explain combined exposure to multiple chemicals.
Cilj istraživanja bio je procijeniti redoks status i koncentracije metala u tragovima kod 49 radnika (11 muškaraca i 38 žena) zaposlenih u industriji obuće, izloženih mješavini hlapljivih organskih spojeva (engl. volatile organic compounds, krat. VOC) koju su činili alifatski i aromatični ugljikovodici, ketoni, esteri, eteri i karboksilne kiseline. Sve izmjerene razine VOC bile su ispod dozvoljenih granica profesionalne izloženosti. U kontrolnoj je skupini bilo 50 neizloženih ispitanika (25 muškaraca i 25 žena). U plazmi obućarskih radnika analizirani su sljedeći parametri: superoksid anion radikal (O2 •−), uznapredovali produkti oksidacije proteina (AOPP), totalni oksidacijski status (TOS), prooksidacijskoantioksidacijski balans (PAB), indeks oksidacijskoga stresa (OSI), aktivnost superoksid-dismutaze (SOD), aktivnost enzima paraoksonaze-1 (PON1), ukupni sadržaj sulfhidrilnih grupa (SHG) i totalni antioksidacijski status (TAS). Koncentracije metala u tragovima (bakar, cink, željezo, magnezij i mangan) analizirane su u punoj krvi. U usporedbi s kontrolnom skupinom, svi parametri oksidacijskoga stresa i antioksidacijske obrane u izloženih radnika bili su povišeni, osim aktivnosti PON1. Povećana koncentracija Fe, Mg i Zn te smanjena koncentracija Cu uočene su u izloženih muškaraca u usporedbi s kontrolnima, a u žena je primijećena povišena koncentracija Fe, a niža koncentracija Mg, Zn i Cu u odnosu na kontrolnu skupinu. Naši nalazi potvrđuju da kombinirano izlaganje mješavini VOC, čak i pri dozvoljenim koncentracijama, može dovesti do aditivnih ili sinergističkih štetnih učinaka na zdravlje i popratnih poremećaja. Trenutna procjena rizika, koja se uglavnom oslanja na učinke pojedinačnih kemikalija, izaziva zabrinutost i upućuje na potrebu za novim pristupima koji će objasniti kombiniranu izloženost većem broju kemikalija.

RNA viruses of the genera Ambivirus, Mitovirus, Sclerotimonavirus, and Partitivirus were found in a single isolate of Fusarium graminearum. The genomes of the mitovirus, sclerotimonavirus, and partitivirus were assigned to previously described viruses, whereas the ambivirus genome putatively represents a new species, named Fusarium graminearum ambivirus 1 (FgAV1). To investigate the effect of mycoviruses on the fungal phenotype, the spontaneous loss of mycoviruses during meiosis and the transmission of mycoviruses into a new strain via anastomosis were used to obtain isogenic F. graminearum strains both with and without mycoviruses. Notable effects observed in mycovirus-harboring strains were (i) the suppression of the synthesis of trichothecene mycotoxins and their precursor trichodiene, (ii) the suppression of the synthesis of the defense compound aurofusarin, (iii) the stimulation of the emission of 2-methyl-1-butanol and 3-methyl-1-butanol, and (iv) the increased attractiveness of fungal mycelia for fungivorous collembolans. The increased attractiveness of mycovirus-infected filamentous fungi to animal predators opens new perspectives on the ecological implications of the infection of fungi with viruses.

Human exposure to toxic chemicals presents a huge health burden. Key to understanding chemical toxicity is knowledge of the molecular target(s) of the chemicals. Because a comprehensive safety assessment for all chemicals is infeasible due to limited resources, a robust computational method for discovering targets of environmental exposures is a promising direction for public health research. In this study, we implemented a novel matrix completion algorithm named coupled matrix-matrix completion (CMMC) for predicting direct and indirect exposome-target interactions, which exploits the vast amount of accumulated data regarding chemical exposures and their molecular targets. Our approach achieved an AUC of 0.89 on a benchmark data set generated using data from the Comparative Toxicogenomics Database. Our case studies with bisphenol A and its analogues, PFAS, dioxins, PCBs, and VOCs show that CMMC can be used to accurately predict molecular targets of novel chemicals without any prior bioactivity knowledge. Our results demonstrate the feasibility and promise of computationally predicting environmental chemical-target interactions to efficiently prioritize chemicals in hazard identification and risk assessment.