Development of a Basic Biosensor System for Wood Degradation using Volatile Organic Compounds

This thesis describes the development of graphene-based sensor arrays, focusing on signal enhancement through innovative surface modification techniques, whilst leveraging graphene's unique properties. Awareness of the dangers posed by toxic gases has increased the demand for advanced gas sensors, which are critical for monitoring harmful gases. Gas sensor arrays, or "electronic noses," offer advantages over single sensors, including the ability to detect multiple analytes simultaneously with greater accuracy. Since its discovery in 2004, graphene has attracted significant interest due to its exceptional mechanical, chemical, and electrical properties, which make it ideal for miniaturized, low-cost sensors with high sensitivity and selectivity. However, graphene's high sensitivity poses a challenge, as it interacts with a wide range of molecules. Managing this sensitivity and selectivity through advanced surface modification techniques is crucial for enhancing the performance of graphene-based sensors. In this thesis, various surface modification techniques were explored to enhance the selectivity and sensitivity of graphene-based sensors, specifically targeting the detection of nitrogen dioxide, ammonia, nitric oxide, methane, and carbon dioxide. These modifications aimed to improve sensor selectivity while maintaining a strong response. One notable technique involved integrating metal phthalocyanines, known for their gas sensitivity, with graphene to create a hybrid sensor. For instance, a graphene sensor functionalized with tetra-tert-butyl copper phthalocyanine was developed for real-time detection of nitrogen dioxide (NO2), achieving a linear response and a detection limit of 31 ppb, showcasing its potential as a highly selective and effective NO2 detector. Polymers of intrinsic microporosity (PIMs), although well-established in gas separation, have not been extensively explored for gas sensing. This thesis presents a PIM-modified graphene sensor array that demonstrated high selectivity and sensitivity towards NO2, with a detection limit of 0.7 ppb, indicating its suitability for highly sensitive NO2 detection. The development of the graphene sensor array began with exploring electrochemical functionalization across different pixels, allowing each graphene element to respond to the same gas with different magnitudes. This proof-of-concept array demonstrated that these distinct responses could potentially be integrated with pattern recognition software to identify unknown gases. Beyond detecting environmental gases, the graphene sensors can also be adapted for the detection of volatile organic compounds (VOCs). To test the arrays, a gas sensing system was developed to enable simultaneous, real- time resistance measurements for each graphene pixel. The iterative development of this system is reported, highlighting challenges and limitations. A proof-of-concept bioelectronic nose based on a graphene resistor has been fabricated and evaluated. Functionalized with 1,5-diaminonaphthalene and immobilized with human olfactory receptor 2AG1, it selectively detected amyl butyrate at 0.5 pM, indicating the potential of bioelectronic noses using olfactory receptors, which can recognize multiple VOCs, thus reducing the required number of sensors in an array.

Introduction Detection of VOCs (volatile organic compounds) has been required because it is detrimental to human health. In particular, in working environment with organic solvents, the need for VOC detectors has grown to reduce the damage to workers. For this purpose, we have developed SnO2 semiconductor sensors with hot-wire-type structures.The hot-wire-type semiconductor sensor can detect ppm concentration gas with a simple structure suitable for mass-production, resulting in practical use in various applications [1]. In this work, we have achieved high sensitivity and selectivity for VOCs by optimizing SnO2 loaded with several metal oxides. Moreover, the newly developed VOC sensor has excellent durability against the poisonous siloxane, leading to commercial products thanks to these advantageous characteristics.To improve convenience for portable use of VOC detectors, we have developed VOC sensors fabricated by micro electro mechanical systems (MEMS) technology to save power consumption [2]. The power consumption of the MEMS VOC sensor was greatly reduced in comparison with conventional hot-wire-type sensors, without sacrificing high sensitivity to VOCs. The low power consumption of the MEMS sensor makes it possible to extend the battery life, which would lead to further spread use of the VOC detectors. Experimental Figure 1 shows the structure of a hot wire semiconductor sensor, which consists of a platinum wire coil and a sintered SnO2 bead. A solution containing several metals was dropped and immersed in the sintered SnO2. Thereafter, metal oxides were supported on SnO2 by current heating to fabricate a hot-wire semiconductor VOC sensor. The coil served as both a heater and electrodes for the semiconductor bead; the total resistance of the sensor (Rs) was approximated by a parallel electric circuit consisting of the coil resistance and the semiconductor one (Fig.2). For the evaluation of the characteristics, the sensor output voltage (V s) was obtained by incorporating the sensor into a bridge circuit and applying a voltage. The operating temperature of the VOC sensor was controlled to be approximately 450 ℃. The sample gas sensitivity was calculated as difference between V s in mixture of air and sample gas (V s gas) and V s in clean air (V s air).Figure 3 shows a cross-sectional schematic of the MEMS VOC sensor. In the MEMS sensor, a Pt micro-heater/electrodes, patterned by using photolithography, was constructed on about 100 μm square insulating membrane cross-linked to the Si substrate. A sensitive layer of SnO2 with thickness of a few tens µm was deposited on the Pt micro-heater by thick film technology. After sintering the SnO2 thick film on the platinum pattern, several metal oxides were added. Results and Conclusions Figure 4 shows the typical gas sensitivity characteristics of the fabricated hot-wire-type semiconductor sensor to various VOCs. The sensor showed high sensitivity for vapors such as acetone, ethyl acetate, and toluene in a concentration range that affects human health. On the other hand, the sensor showed low sensitivity to interfering gases such as methane and hydrogen. These results demonstrate that the sensors have sufficient selectivity for practical use. Optimization of loaded metal oxides successfully controlled oxidation activity of SnO2 optimally, resulting in improved VOC sensitivity and further reduced interfering gas sensitivity. Furthermore, the sensor showed significantly better durability against toxic siloxane gas than the conventional one, resulting in long-life use in real field. The improved durability against siloxane poisoning is attributable to the controlled oxidation activity of SnO2 by loaded metal oxides. The developed sensor is useful for monitoring VOC as a practical detector that can measure in real time.Next, we investigated the MEMS VOC sensors. Quick thermal response owing to the miniaturized structure enabled us to achieve working temperatures (~500 °C) of the sensor only in 30 milliseconds. Thus, we could operate the MEMS sensor in a pulsed voltage mode, in which averaged power consumption was less than 1 mW. We confirmed that the MEMS sensors, even with the pulsed voltage operation, reproduced high sensitivity to VOCs obtained in the conventional sensor. In addition, the MEMS sensor exhibited long term stability for more than two years. The MEMS VOC sensor would contribute to the improvement of working environment with the spread use of VOC detectors.In conclusion, we have successfully developed hot-wire-type semiconductor VOC sensors ready for commercial use. We have also developed VOC sensors fabricated by MEMS technology to save power consumption.

Simple SummaryVolatile organic compounds (VOCs) in urine headspace have been previously shown to be potential biomarkers for prostate cancer. The aim of the current study is to further evaluate urinary VOCs as biomarkers in humans, assess their ability to stratify aggressive tumors, and compare them to the results of murine models of induced prostate cancer. Chemometric analyses were implemented and showed that VOCs in mouse urine were highly dysregulated by prostate cancer and could perfectly distinguish tumor-bearing mice. VOCs in human urine could not only classify any type of prostate cancer with moderate accuracy but could separate aggressive grades with higher sensitivity and specificity. Lastly, there was an overlap in VOC structure and functionality between the mouse and human urine analyses which shows the merit of utilizing murine models for identifying candidate VOC biomarkers for cancer.Canines can identify prostate cancer with high accuracy by smelling volatile organic compounds (VOCs) in urine. Previous studies have identified VOC biomarkers for prostate cancer utilizing solid phase microextraction (SPME) gas chromatography–mass spectrometry (GC-MS) but have not assessed the ability of VOCs to distinguish aggressive cancers. Additionally, previous investigations have utilized murine models to identify biomarkers but have not determined if the results are translatable to humans. To address these challenges, urine was collected from mice with prostate cancer and men undergoing prostate cancer biopsy and VOCs were analyzed by SPME GC-MS. Prior to analysis, SPME fibers/arrows were compared, and the fibers had enhanced sensitivity toward VOCs with a low molecular weight. The analysis of mouse urine demonstrated that VOCs could distinguish tumor-bearing mice with 100% accuracy. Linear discriminant analysis of six VOCs in human urine distinguished prostate cancer with sensitivity = 75% and specificity = 69%. Another panel of seven VOCs could classify aggressive cancer with sensitivity = 78% and specificity = 85%. These results show that VOCs have moderate accuracy in detecting prostate cancer and a superior ability to stratify aggressive tumors. Furthermore, the overlap in the structure of VOCs identified in humans and mice shows the merit of murine models for identifying biomarker candidates.

Non-invasive or minimally invasive disease diagnostics have revolutionized how various medical conditions are detected and monitored. Diseases like cancer cause changes in metabolic pathways and release unique metabolites. Some volatile metabolites are excreted through airways, making them measurable in exhaled breath. Identifying these volatile organic compounds (VOCs) is a promising approach for cancer diagnostics. The prevailing approach for identifying VOCs with high sensitivity and selectivity in exhaled breath involves gathering the sample using collection cartridges or containers, followed by laboratory-based analysis utilizing Gas Chromatography–Mass spectrometry (GC-MS). Nevertheless, this approach necessitates sample preparation, transportation, and the desorption of gases, all contributing to substantial turnaround times and augmenting the overall expenses of the procedure. Due to these, researchers have tried developing portable, low-cost sensors that detect multiple VOCs. The current research primarily relies on electronic noses based on metal oxide semiconductor (MOS) sensor arrays, which detect changes in conductivity in the presence of volatile organic compounds (VOCs). However, a major limitation of MOS sensors is their poor selectivity. In contrast, our electrochemical sensor utilizes ionic liquids (ILs) as the sensing medium, offering significantly improved selectivity. This enhancement is achieved by tailoring the ionic composition or selecting ILs with different gas solubilities. Moreover, our sensor integrates multiple electrochemical techniques—including electrochemical impedance spectroscopy (EIS), cyclic voltammetry, and amperometry—to measure parameters such as conductivity, charge transfer resistance, capacitance, and diffusion. These diverse measurements generate richer datasets, which can be leveraged by AI/ML algorithms to further boost both sensitivity and selectivity.To incorporate the ILs and perform in-situ detection, we developed a sensor architecture integrating microfluidics and microelectrode technology. This multi-layered design, essentially a membrane contactor on a microscale, consists of 5 layers. At the bottom is a glass substrate with planar interdigitated gold microelectrodes fabricated using photolithography and a physical vapor deposition process. The next layer is a double-sided tape with a microchannel (for confining the liquid) with a length of 65 mm, a width of 500 μm, and a thickness of 130 μm cut out using a Cricut machine. Next is the gas-permeable hydrophobic Polytetrafluoroethylene (PTFE) membrane with a pore size of 0.45 μm. The membrane confines the liquid within the microchannel while allowing the gas to pass through. The next layer is a double-sided tape with a microchannel for gas flow with the exact dimensions (65mm x 500 μm x 130 μm) of the liquid microchannel. Finally, the top glass slide has gas inlet and outlet ports. This multi-layered design enables interaction between the gas and the ionic liquid (IL) through the membrane and allows the detection of perturbations in the IL using microelectrodes connected to a potentiostat.Commercially available ionic liquids—1-ethyl-3-methylimidazolium bis(trifluoromethylsulfonyl)imide ([EMIM][TFSI]) and 1-butyl-3-methylimidazolium hexafluorophosphate ([BMIM][PF6])—were incorporated into this microfluidic platform for the selective detection of model VOCs, specifically acetone and toluene. Various electrochemical techniques, including EIS, cyclic voltammetry, differential pulse voltammetry, and amperometry, were employed to capture the perturbations induced by these VOCs in both ILs. The resulting multi-modal dataset was used to train a support vector machine (SVM) model, bypassing the need for a traditional electrochemical or equivalent circuit model. This approach enabled clear differentiation between acetone and toluene signals. Additionally, support vector regression (SVR) was applied to develop calibration curves for quantitative sensing.

Plant volatile organic compounds (VOCs) are organic chemicals that plants release as part of their natural biological processes. Various plant tissues produce VOCs, including leaves, stems, flowers, and roots. VOCs are essential in plant communication, defense against pests and pathogens, aroma and flavor, and attracting pollinators. The study of plant volatiles has become an increasingly important area of research in recent years, as scientists have recognized these compounds' important roles in plant physiology. As a result, there has been a growing interest in developing methods for collecting and analyzing plant VOCs. HS-SPME-GC-MS (headspace solid-phase microextraction-gas chromatography-mass spectrometry) is commonly used for plant volatile analysis due to its high sensitivity and selectivity. This chapter describes an efficient method for extracting and identifying volatile compounds by HS-SPME coupled with GC-MS in tomato fruits.

Mushrooms are part of the human diet since time immemorial, appreciated for their nutritional value and especially for their delicious flavors. Hundreds of volatile organic compounds (VOCs) have been identified in fungi contributing to the unique aroma of each species. Generally, studies on mushroom VOCs are carried out with chopped fruiting bodies of more or less one developmental stage. For determine fungal aromas for assessment of the food quality this procedure might be adequate. Nonetheless, for analysis of the biological role of fungal VOCs in context of inter alia VOC biosynthesis or fungal communication this approach can suffer from drawbacks. First of all, damaging fruiting bodies can lead to VOC artefacts due to cell disruption and the occurrence of unnatural enzymatic reactions. Furthermore, fungal VOC profiles are dynamic, changing with ongoing development. For better understanding of the biological function of fungal VOCs it is therefore helpful to know which volatile patterns are characteristic for a certain developmental stage.Against this background, an approach was developed enabling on one hand the cultivation of fungi during different developmental stages, including the growth of fruiting bodies, and on the other hand the non‐invasive analysis of VOCs in the headspace (HS) of fungal cultures. These requirements were complied with modified crystallizing dishes for culture purposes and a HS‐ SPME‐GC‐MS approach to analyze the VOCs. This method was applied to analyze the volatilomes of the dikaryotic strain C. aegerita AAE‐3 and four monokaryotic offspring siblings with different fruiting phenotypes throughout ten life stages. At early stages, in the HS of all tested strains alcohols and ketones, such as oct‐1‐en‐3‐ol, 2‐methylbutan‐1‐ol and cyclopentanone, were the most prominent VOCs. Particularly counting for the dikaryon, the volatilome altered with continued fruiting body development exhibiting remarkable changes during sporulation. Here, sesquiterpenes, especially Δ6‐protoilludene, α‐cubebene and δ‐cadinene, were the most abundant VOCs in the HS of C. aegerita AAE‐3. After sporulation, the amount of sesquiterpenes decreased along with the appearance of other VOCs including octan‐3‐one. In contrast, less VOCs were present in the HS of the monokaryotic strains of which all were as well detectable in the HS of the dikaryon. The changes of the volatilome were the fundament for a subsequent transcriptome analysis aiming to identify enzymes involved in fungal VOC biosynthesis, especially regarding C8 VOC formation, which is, despite the fact that these substances are ubiquitous found in fungi, still barely understood. The transcriptomic study was carried out with seven developmental stages of C. aegerita AAE‐3, which during the volatilome study exhibited interesting volatile patterns. Additionally, fruiting bodies (five stages) and mycelia (seven stages) samples were harvested separately to get further insights about the putative origin of the VOCs observed in the HS of C. aegerita. Combining transcriptome and volatilome data, enzymes putatively involved in the biosynthesis of C8 oxylipins in C. aegerita including lipoxygenases (LOXs), dioxygenases (DOXs), hydroperoxide lyases (HPLs), alcohol dehydrogenases (ADHs) and ene‐ reductases could be identified. Especially the putative DOX AAE3_13098, the putative HPLs AAE3_05330 and AAE3_09203, the putative ADHs AAE3_00054 and AAE3_06559 as well as the putative ene‐reductase AAE3_15349 exhibit remarkable transcriptomic patterns making these enzymes highly interesting for future characterization studies. Furthermore, the study showed that the mycelium is probably the main source for sesquiterpenes observed during sporulation in the HS of C. aegerita AAE‐3 cultures whereas changes in the Cs profile detected in late stages of development are probably due to the activity of enzymes located in the fruiting bodies.

Volatile organic compounds (VOCs), such as trichloroethene, toluene and xylenes have been reported to be detected from river water and sediment, because a part of VOCs charged into river can be distributed to river sediment. Fifty-three common VOCs in water have been simultaneously determined with good accuracy and precision by gas chromatography - mass spectrometry (GC/MS) with headspace method as well as purge-and-trap method. However, simultaneous determination methods for the VOCs in sediment have not been established. Several GC or GOMS methods have been reported to determine some VOCs in sediment, purge-and-trap, distillation, headspace and solvent extraction. Among them headspace GC/MS method appears to be the most appropriate method for screening the VOCs in sediments, because of its simplicity in analytical procedure. Hewitt et al. have reported that headspace method gave no statistically different results from purge-and-trap method for GC/MS determination of four VOCs in soil. Voice and Kolb have reported that headspace GC method gave better results to determine nine VOCs in soil than purge-and-trap method or solvent extraction method followed by headspace. However, headspace analysis of some VOCs in sediments could give insufficient recoveries. This is because VOCs adsorb to sediment. To improve their low recoveries from sediment,more » we have previously used a stable isotope-labeled compound as an internal standard to determine eight chlorinated VOCs. However, this method is not proper for determining simultaneously as many as 53 VOCs with various physical properties. Therefore, we investigate headspace GC/MS method with standard addition method for simultaneous screening of them in sediment. In this paper, we describe effects of a few headspace conditions on the VOC recoveries from sediment, and present screening results of the VOCs in sediments from mouths of rivers and a port in Niigata, Japan. 17 refs., 3 figs., 3 tabs.« less

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.

<div class="section abstract"><div class="htmlview paragraph">Vehicle interior air quality (VIAQ) measurements are currently conducted using the offline techniques GC/MS and HPLC. To improve throughput, speed of analysis, and enable online measurement, specialized instruments are being developed. These instruments promise to reduce testing cost and provide shortened analysis times at comparable accuracy to the current state of the art offline instruments and methods. This work compares GCMS/HPLC to the Voice200<i>ultra</i>, a specialized real-time instrument utilizing the technique selected ion flow tube mass spectrometry (SIFT-MS). The Voice200<i>ultra</i> is a real-time mass spectrometer that measures volatile organic compounds (VOCs) in air down to the parts-per-trillion level by volume (pptv). It provides instantaneous, quantifiable results with high selectivity and sensitivity using soft chemical ionization. The VOC measurement capabilities of the Voice200<i>ultra</i> is being compared to gas chromatography-mass spectrometry (GC/MS) and high-performance liquid chromatography (HPLC), which are the internationally accepted industry standard. In this study, we compare the analytical capabilities of SIFT-MS to the accepted standard measurement techniques by GCMS/HPLC by measuring the VOCs in new vehicle interiors. We quantify formaldehyde, acetaldehyde, benzene, toluene, ethylbenzene, xylene, styrene, and acrolein (the eight chemicals found in the GB list specified by the Chinese government) as well as many other compounds, including acetone and butanone. The comparability between SIFT-MS and GCMS/HPLC is excellent with an average R<sup>2</sup> values of at least 0.89 for all compounds excluding formaldehyde and acrolein. This excellent correlation demonstrates that the Voice200<i>ultra</i> is able to accurately measure these target species with excellent selectivity in the complex sample matrix of a new car cabin interior. Levels of acrolein and formaldehyde as measured by HPLC were extremely low and the lack of correlation for these two compounds is attributed to the intrinsic issues with the HPLC technique for the measurement of these compounds.</div></div>

In recent years, microbes and their metabolites are increasingly recognised as key players in the pathogenesis of a wide range of gastrointestinal disorders, such as inflammatory bowel disease (IBD), colorectal cancer, irritable bowel syndrome, and coeliac disease, but also diseases outside the gastrointestinal tract.1, 2 A relatively novel topic in the field of gut metabolomics is the study of faecal volatile organic compounds (VOCs). VOCs are carbon-based molecules and their chemical composition allows for vaporisation at room temperature. They are therefore released as gases from various matrices, such as blood, urine, or faeces, and are responsible for the odour of a substance. In the gut, these compounds primarily result from the metabolic activities of gut microbiota and the intestinal mucosa.3 Alterations in VOC profiles have been described as indicative of various intestinal diseases, including IBD, where specific changes in microbiota composition and diversity, reflected by changes in VOC-profiles, correlate with disease activity.4 Belnour et al. recently conducted a study in a population consisting of 132 case/control pairs of children with IBD and children with gastrointestinal symptoms without IBD.5 Their aim was to compare faecal VOC profiles between both groups, and to assess the relation of faecal VOCs with disease phenotype, localisation, severity, and response to treatment. VOCs were analysed through gas chromatography-mass spectrometry (GC-MS). They observed significantly decreased mean abundance of 43.6% of 62 measured faecal VOCs in IBD patients compared to controls, which is in accordance with the microbial dysbiosis linked with IBD in literature. Propan-1-ol, phenol, and oct-1-en-3-ol, all being alcohols, were the most distinctive VOCs in children with IBD compared to controls. The first two are products of amino acid degradation (threonine, and tyrosine and tryptophan, respectively) by Enterobacteriaceae and Clostridium species, which are often more abundant in IBD.6 The associated amino acids themselves are also linked to gut inflammation.7 The gut microbiome and metabolome have gained scientific interest due to the ongoing quest for new non-invasive biomarkers. Currently, the most used non-invasive biomarker for the detection and monitoring of IBD is faecal calprotectin (FCP), which is characterised by a high sensitivity for identifying disease activity and luminal inflammation, but suffers from low specificity. The reliance on FCP in clinical practice often leads to unnecessary endoscopies which are especially burdensome for children. Consequently, there is a need for novel more accurate non-invasive biomarkers. Belnour et al.'s finding that faecal VOCs could differentiate children with IBD from those with gastrointestinal symptoms without IBD, is significant and aligns with recent literature.8 However, as the authors note, these findings merely provide insights into the pathogenesis of paediatric IBD, and further research is warranted to develop a clinical biomarker. Another critical issue in managing IBD is predicting disease severity and response to therapy. In paediatric IBD, therapeutic guidelines regularly recommend a step-up approach. At baseline, predicting which patients will develop severe disease in the disease course and could benefit from early treatment escalation is challenging. The observation of Belnour et al. of differences in faecal VOC profiles between various states of disease severity and treatment responses is of importance. It highlights the complex pathogenesis of IBD and underscores the need for personalised medical approaches due to the disease's heterogeneity. Advantages of VOC analysis include its speed and relatively low costs. However, challenges include the influence of environmental factors, especially dietary intake, the lack of standardised sampling, storage and handling protocols, and the variety in used analytical techniques.9 GC-MS is considered the gold standard for VOC analysis,10 which separates complex compounds in a GC column, ionises and further separates in the MS column based on mass and transportation time. GC-MS is highly accurate and can identify specific VOCs on molecular level, but is the most expensive, high-maintenance and needs trained personnel to use. Electronic noses (eNoses) are more accessible in terms of costs and time. This technique is based on pattern-recognition of VOC mixtures, allowing for identification of disease-specific VOC patterns, but cannot measure individual VOCs. Though the clinical implementation of faecal VOC analysis is still distant, it holds promise as a potential novel non-invasive biomarker in (paediatric) IBD. Endoscopies will as yet remain necessary for diagnosing IBD to obtain information on disease phenotype, localisation and severity, but faecal VOCs could possibly support to select which patients presenting with gastrointestinal symptoms require endoscopy for suspected IBD diagnosis, given the limited specificity of FCP. Future research should focus on identifying specific VOCs and validating previous results in larger cohorts. The first step however is standardising and refining measurement methodologies to overcome variability in sampling and analysis. The authors have no conflicts of interest to declare. Data sharing is not applicable to this article as no new data were created or analyzed in this study.

In order to valorize Moroccan aromatic and medicinal plants, this study focused on both the chemical characterization and the study of the antifungal activity of Pelargonium graveolens essential oil and its fractions against four fungi that are responsible for wood decay (Coniophora puteana, Coriolus versicolor, Poria placenta and Gloeophyllum trabeum). The essential oils were analyzed by Gas chromatography/Mass spectrometry (GC/MS) and evaluated for antifungal activity, using the macrodilution method for the determination of EC50. The GC/MS essential oil analysis has led to the identification of 54 components. Citronellol (25.24 %), geraniol (23.36 %), citronellyl formate (8.35 %), linalool (7.11 %), β-eudesmol (6.13 %), geranyl formate (4.26 %) and iso-menthone (3.37 %), were identified as the major components. Fractions 1, 2 and 3 essential oils have displayed qualitative similarities with the EO sample, and quantitative differences among the relative percentages of major compounds were observed. A significant difference (p < 0.0001) was shown in main compounds of fraction 3 obtained by fractional distillation. P. graveolens essential oil has inhibited all fungi with a value of EC50 between 0.255 to 1.022 mg/mL. The EC50 values of fractions 1 and 2 are ranging from 0.292 to 1.022 mg/mL. The fraction 3 exhibited a great antifungal activity against all tested fungi. These results support the potential use of P. graveolens essential oils and its fractions for wood protection against wood decay fungi.

Volatile organic compounds (VOCs), which are generated from adhesives, resins and paints of new building materials and furniture, cause sick house syndrome such as headache, dizziness and nausea, and thus portable VOC-detecting devices with high sensitivity and selectivity were required as an alternative to large and expensive VOC-analyzing systems. Among various types of VOC sensors, adsorption/combustion-type micro gas sensors, which were developed by our group, are quite promising to detect a low concentration of VOCs, because the VOCs, which are firstly adsorbed on the sensing materials at lower temperatures and then the adsorbed ones, are catalytically oxidized at pulsed heating to elevated temperatures leading to a large response to the VOCs. For example, the sensors using Pd-loaded mesoporous (mp-) alumina (Al2O3) exhibited excellent performance in detecting VOCs1), and co-loading of Au with Pd onto mp-Al2O3 by impregnation improved the sensing property to ethanol2). In addition, the ethanol-sensing property was further enhanced by highly dispersing Au(core)/Pd(shell) nanoparticles, which were prepared by ultrasonic-assisted reduction of Au and Pd chlorides with polyethylene glycol monostearate, on the mp-Al2O3 3). Recently, we have demonstrated that the loading of Pt nanoparticles on the mp-Al2O3 by utilizing the ultrasonic-assisted reduction is also effective in improving several VOCs such as ethanol, acetone, and ethyl acetate4). Therefore, VOC-sensing properties of adsorption/combustion-type micro gas sensors using mp-Al2O3 co-loaded with 1 wt% Pt and 10 wt% metal oxide (1Pt/10MO/mp-Al2O3 sensor, MO: metal oxide (Bi2O3, CeO2, Fe2O3, NiO, RuO2 or ZrO2)) have been investigated in this study. The mp-Al2O3 powder (specific surface area: ca. 250 m2 g-1) was prepared by microwave-assisted solvothermal treatment of Al(sec-OC4H9)3 in 1-propanol solution4). The 10 wt% MO-loaded mp-Al2O3 (10MO/mp-Al2O3) powders were prepared by impregnation with the constituent metal salt to the mp-Al2O3 powder, followed by firing at 700ºC for 1 h in air. Thereafter, the mp-Al2O3 and 10MO/mp-Al2O3 powders were loaded with 1.0 wt% Pt nanoparticles, which were synthesized by utilizing the ultrasonic-assisted reduction of H2PtCl6 (10 mM) in deionized water containing an appropriate amount of polyethylene glycol monostearate (MW: 4000). The obtained Pt-loaded powders (1 wt% Pt-loaded mp-Al2O3 (1Pt/mp-Al2O3) or 1 wt% Pt-loaded 10MO/mp-Al2O3 (1Pt/10MO/mp-Al2O3)) and mp-Al2O3 powder were set on the sensing and reference regions of a MEMS platform, respectively, and VOC-sensing properties of the adsorption/combustion-type micro gas sensors were measured with a mode of pulse-driven heating (high temperature (450°C) for 0.4 s after low temperature (150°C) for 9.6 s within a cycle of 10 s). In this operation mode, the target VOCs and/or the partially-decomposed products are adsorbed on the sensing materials at 150°C, and subsequently all the adsorbates abruptly burn upon the pulse heating up to 450°C. Thus, a sensor-signal profile typically consists of one large dynamic response and subsequent static response, which originate from the flash catalytic combustion of these adsorbates and general catalytic combustion, respectively, during the pulse heating at 450°C. The 1Pt/10CeO2-mp-Al2O3 sensor showed the largest static response to all target VOCs (ethanol, ethyl acetate, acetone, benzene, and toluene) among all the sensors tested, probably because Pt/10CeO2-mp-Al2O3 showed the largest specific surface area (ca. 187 m2 g-1). In addition, the magnitude of the static response was little dependent on the kinds of VOCs. On the other hand, all 1Pt/10MO/mp-Al2O3 sensors showed larger dynamic response to ethanol than other VOCs (ethyl acetate, acetone, benzene, and toluene). These sensors also showed relatively large dynamic responses to acetone and ethyl acetate, and the magnitude of dynamic responses to benzene and toluene was much smaller than that to acetone and ethyl acetate. Among them, the 1Pt/10CeO2-mp-Al2O3 sensor showed the largest dynamic response to most of target VOCs, while 1Pt/10Bi2O3-mp-Al2O3 showed the largest dynamic response to only toluene, even though the specific surface area of 1Pt/10Bi2O3-mp-Al2O3 (ca. 142 m2 g-1) is smaller than that of 1Pt/10CeO2-mp-Al2O3. Moreover, the dynamic response speed of the 1Pt/10Bi2O3-mp-Al2O3 sensor to toluene was faster than that of the 1Pt/10CeO2-mp-Al2O3 sensor. These toluene-sensing properties probably result from higher catalytic combustion behavior of toluene over 1Pt/10Bi2O3-mp-Al2O3 than 1Pt/10CeO2-mp-Al2O3. In addition, the adsorption property of toluene on 1Pt/10Bi2O3-mp-Al2O3 may also influence the dynamic response. 1. T. Sasahara, A. Kido, T. Sunayama, S. Uematsu, and M. Egashira, Sens. Actuators, 99, 532-538 (2004). 2. Y. Yuzuriha, T. Hyodo, T. Sasahara, Y. Shimizu, and M. Egashira, Sens. Lett, 9, 409-413 (2011) 3. T. Hyodo, Y. Yuzuriha, O. Nakagoe, T. Sasahara, S. Tanabe, and Y. Shimizu, Sens. Actuators, 202, 748-757 (2014). 4. T. Hyodo, T. Hashimoto, T. Ueda, O. Nakagoe, K. Kamada, T. Sasahara, S. Tanabe, and Y. Shimizy, Sens. Actuators, 220, 1091-1104 (2005).

WARNING : The light-emitting molecular structures responsible for the chemiluminescence and fluorescence phenomena are not necessarily the same!

Real-time monitoring of volatile organic compounds (VOCs) is crucial for both industrial production and daily life. However, the non-reactive nature of VOCs and their low concentrations pose a significant challenge for developing sensors. In this study, we investigated the adsorption behaviors of typical VOCs (C2H4, C2H6, and C6H6), on pristine and Pt-decorated SnS monolayers using density functional theory (DFT) calculations. Pristine SnS monolayers have limited charge transfer and long adsorption distances to VOC molecules, resulting in VOC insensitivity. The introduction of Pt atoms promotes charge transfer, creates new energy levels, and increases the overlap of the density of states, thereby enhancing electron excitation and improving gas sensitivity. Pt-decorated SnS monolayers exhibited high sensitivities of 241,921.7%, 35.7%, and 74.3% towards C2H4, C2H6, and C6H6, respectively. These values are 142,306.9, 23.8, and 82.6 times higher than those of pristine SnS monolayers, respectively. Moreover, the moderate adsorption energies of adsorbing C2H6 and C6H6 molecules ensure that Pt-decorated SnS monolayers possess good reversibility with a short recovery time at 298 K. When heated to 498 K, C2H4 molecules desorbs from the surface of Pt-decorated SnS monolayer in 162.33 s. Our results indicate that Pt-decorated SnS monolayers could be superior candidates for sensing VOCs with high selectivity, sensitivity, and reversibility.

A controllable selective cataluminescence sensor for diethyl ether using mesoporous TiO2 nanoparticles