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This article presents the development of an artificial olfactory bulb (OB) using an electronic nose with thermally modulated metal-oxide sensors. Inspired by animal OBs, our approach employs thermal modulation to replicate the spatial encoding patterns of glomeruli clusters and subclusters. This new approach enhances the classification capabilities of traditional electronic noses and offers new insights for biomimetic olfaction. Molecular receptive range (MRR) analysis confirms that our artificial OB effectively mimics the glomerular distribution of animal OBs. Additionally, the incorporation of a short axon cell (SAC) network, inspired by the animal olfactory system, significantly improves lifetime sparseness and qualitative ability of the artificial OB through extensive lateral inhibition, providing a theoretical framework for enhanced olfactory performance., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2024 The Authors. Published by Elsevier B.V. All rights reserved.)

Background: Non-invasive biomarkers may reduce post-colonoscopy colorectal cancer (CRC) rates and colonoscopy overuse in Lynch syndrome. Unlike faecal immunochemical test (FIT), faecal volatile organic compounds (VOCs) may accurately detect both advanced and non-advanced colorectal neoplasia., Aim: The aim of this study was to evaluate the potential of faecal VOCs-separately and with FIT-to guide optimal colonoscopy intervals in Lynch syndrome., Methods: Prospective longitudinal multicentre study in which individuals with Lynch syndrome collected faeces before and after high-quality surveillance colonoscopy. VOC-patterns were analysed using field asymmetric ion mobility spectrometry (FAIMS) and gas chromatography-ion mobility spectrometry (GC-IMS) followed by machine learning pipelines, and combined with FIT at 2.55 μg Hb/g faeces. Gas chromatography time-of-flight mass spectrometry analysed individual VOC abundance., Results: Among 200 included individuals (57% female, median 51 years), 62 had relevant neoplasia at colonoscopy: 3 CRC, 6 advanced adenoma (AA), 3 advanced serrated lesion (ASL), and 50 non-advanced adenoma (NAA). Respective sensitivity and negative predictive value for CRC and AA (and also ASL in case of FAIMS) were 100% and 100% using FAIMS (54% specificity), and 89% and 99% using GC-IMS (58% specificity). Respective sensitivity and specificity for any relevant neoplasia were 88% and 44% (FAIMS) and 84% and 28% (GC-IMS); accuracy did not significantly improve upon VOC-FIT. VOC-patterns differed before and after polypectomy (AUC 0.70). NAA showed decreased faecal abundance of butanal, 2-oxohexane, dimethyldisulphide and dimethyltrisulphide., Conclusions: In Lynch syndrome, faecal VOCs may be a promising strategy for postponing colonoscopy and for follow-up after polypectomy. Our results serve as a stepping stone for large validation studies., Trial Registration: NL8749., (© 2024 The Author(s). Alimentary Pharmacology & Therapeutics published by John Wiley & Sons Ltd.)

Diagnosis of respiratory tract infections (RTIs), especially in primary care, is typically made on clinical features and in the absence of quick and reliable diagnostic tests. Even in secondary care, where diagnostic microbiology facilities are available, these tests take 24-48 h to provide an indication of the etiology. This multicentre study used a portable gas chromatography-ion mobility spectrometer (GC-IMS) for the diagnosis of bacterial RTIs. Breath samples taken from 570 participants with 149 clinically validated bacterial and 421 non-bacterial RTIs were analyzed to distinguish bacterial from non-bacterial RTIs. Through the integration of a sparse logistic regression model, we identified a moderate diagnostic accuracy of 0.73 (95% CI 0 · 69, 0 · 77) alongside a sensitivity of 0 · 85 (95% CI 0 · 79, 0 · 91) and a specificity of 0 · 55 (95% CI 0 · 50, 0 · 60). The GC-IMS diagnostic device provides a promising outlook in distinguishing bacterial from non-bacterial RTIs and was also favorably viewed by participants., Competing Interests: The authors declare no competing interests., (© 2024 The Author(s).)

Background: Mosquitoes are carriers of tropical diseases, thus demanding a comprehensive understanding of their behaviour to devise effective disease control strategies. In this article we show that machine learning can provide a performance assessment of 2D and 3D machine vision techniques and thereby guide entomologists towards appropriate experimental approaches for behaviour assessment. Behaviours are best characterised via tracking-giving a full time series of information. However, tracking systems vary in complexity. Single-camera imaging yields two-component position data which generally are a function of all three orthogonal components due to perspective; however, a telecentric imaging setup gives constant magnification with respect to depth and thereby measures two orthogonal position components. Multi-camera or holographic techniques quantify all three components., Methods: In this study a 3D mosquito mating swarm dataset was used to generate equivalent 2D data via telecentric imaging and a single camera at various imaging distances. The performance of the tracking systems was assessed through an established machine learning classifier that differentiates male and non-male mosquito tracks. SHAPs analysis has been used to explore the trajectory feature values for each model., Results: The results reveal that both telecentric and single-camera models, when placed at large distances from the flying mosquitoes, can produce equivalent accuracy from a classifier as well as preserve characteristic features without resorting to more complex 3D tracking techniques., Conclusions: Caution should be exercised when employing a single camera at short distances as classifier balanced accuracy is reduced compared to that from 3D or telecentric imaging; the trajectory features also deviate compared to those from the other datasets. It is postulated that measurement of two orthogonal motion components is necessary to optimise the accuracy of machine learning classifiers based on trajectory data. The study increases the evidence base for using machine learning to determine behaviours from insect trajectory data., (© 2024. The Author(s).)

Objective: The fecal microbiota and metabolome are hypothesized to be altered before late-onset neonatal meningitis (LOM), in analogy to late-onset sepsis (LOS). The present study aimed to identify fecal microbiota composition and volatile metabolomics preceding LOM., Methods: Cases and gestational age-matched controls were selected from a prospective, longitudinal preterm cohort study (born <30 weeks' gestation) at nine neonatal intensive care units. The microbial composition (16S rRNA sequencing) and volatile metabolome (gas chromatography-ion mobility spectrometry (GC-IMS) and GC-time-of-flight-mass spectrometry (GC-TOF-MS)), were analyzed in fecal samples 1-10 days pre-LOM., Results: Of 1397 included infants, 21 were diagnosed with LOM (1.5%), and 19 with concomitant LOS (90%). Random Forest classification and MaAsLin2 analysis found similar microbiota features contribute to the discrimination of fecal pre-LOM samples versus controls. A Random Forest model based on six microbiota features accurately predicts LOM 1-3 days before diagnosis with an area under the curve (AUC) of 0.88 (n=147). Pattern recognition analysis by GC-IMS revealed an AUC of 0.70-0.76 (P<0.05) in the three days pre-LOM (n=92). No single discriminative metabolites were identified by GC-TOF-MS (n=66)., Conclusion: Infants with LOM could be accurately discriminated from controls based on preclinical microbiota composition, while alterations in the volatile metabolome were moderately associated with preclinical LOM., (© The Author(s) 2024. Published by Oxford University Press on behalf of Infectious Diseases Society of America.)

The gut microbiota and its related metabolites differ between inflammatory bowel disease (IBD) patients and healthy controls. In this study, we compared faecal volatile organic compound (VOC) patterns of paediatric IBD patients and controls with gastrointestinal symptoms (CGIs). Additionally, we aimed to assess if baseline VOC profiles could predict treatment response in paediatric IBD patients. We collected faecal samples from a cohort of de novo therapy-naïve paediatric IBD patients and CGIs. VOCs were analysed using gas chromatography-ion mobility spectrometry (GC-IMS). Response was defined as a combination of clinical response based on disease activity scores, without requiring treatment escalation. We included 109 paediatric IBD patients and 75 CGIs, aged 4 to 17 years. Faecal VOC profiles of paediatric IBD patients were distinguishable from those of CGIs (AUC ± 95% CI, p -values: 0.71 (0.64-0.79), <0.001). This discrimination was observed in both Crohn's disease (CD) (0.75 (0.67-0.84), <0.001) and ulcerative colitis (UC) (0.67 (0.56-0.78), 0.01) patients. VOC profiles between CD and UC patients were not distinguishable (0.57 (0.45-0.69), 0.87). Baseline VOC profiles of responders did not differ from non-responders (0.70 (0.58-0.83), 0.1). In conclusion, faecal VOC profiles of paediatric IBD patients differ significantly from those of CGIs.

Gas chromatography ion-mobility spectrometry (GC-IMS) technology is drawing increasing attention due to its high sensitivity, low drift, and capability for the identification of compounds. The noninvasive detection of plant pests and pathogens is an application area well suited to this technology. In this work, we employed GC-IMS technology for early detection of Fusarium basal rot in brown onion, red onion, and shallot bulbs and for tracking disease progression during storage. The volatile profiles of the infected and healthy control bulbs were characterized using GC-IMS and gas chromatography-time-of-flight mass spectrometry (GC-TOF-MS). GC-IMS data combined with principal component analysis and supervised methods provided discrimination between infected and healthy control bulbs as early as 1 day after incubation with the pathogen, classification regarding the proportion of infected to healthy bulbs in a sample, and prediction of the infection's duration with an average R 2 = 0.92. Furthermore, GC-TOF-MS revealed several compounds, mostly sulfides and disulfides, that could be uniquely related to Fusarium basal rot infection.

Olfactory displays are digital devices designed to provide the controlled release of odours to users. In this paper, we report on the design and development of a simple vortex-based olfactory display for a single user. By employing a vortex approach, we are able to minimize the amount of required odour, whilst still producing a good user experience. The olfactory display designed here is based on a steel tube with 3D-printed apertures and solenoid valve operation. A number of different design parameters (such as aperture size) were investigated, and the best combination was combined into a functional olfactory display. User testing was undertaken with four volunteers who were presented with four different odours, at two concentrations. It was found that the time to identify an odour was not strongly related to concentration. However, the intensity of the odour was correlated. We also found that there was a wide variance in human panel results when considering the length of time for a subject to identify an odour to its perceived intensity. This is likely linked to the subject group receiving no odour training before the experiments. However, we were able to produce a working olfactory display, based on a scent project method, which could be applicable to a range of application scenarios.

Mosquito-borne diseases account for around one million deaths annually. There is a constant need for novel intervention mechanisms to mitigate transmission, especially as current insecticidal methods become less effective with the rise of insecticide resistance among mosquito populations. Previously, we used a near infra-red tracking system to describe the behaviour of mosquitoes at a human-occupied bed net, work that eventually led to an entirely novel bed net design. Advancing that approach, here we report on the use of trajectory analysis of a mosquito flight, using machine learning methods. This largely unexplored application has significant potential for providing useful insights into the behaviour of mosquitoes and other insects. In this work, a novel methodology applies anomaly detection to distinguish male mosquito tracks from females and couples. The proposed pipeline uses new feature engineering techniques and splits each track into segments such that detailed flight behaviour differences influence the classifier rather than the experimental constraints such as the field of view of the tracking system. Each segment is individually classified and the outcomes are combined to classify whole tracks. By interpreting the model using SHAP values, the features of flight that contribute to the differences between sexes are found and are explained by expert opinion. This methodology was tested using 3D tracks generated from mosquito mating swarms in the field and obtained a balanced accuracy of 64.5% and an ROC AUC score of 68.4%. Such a system can be used in a wide variety of trajectory domains to detect and analyse the behaviours of different classes, e.g., sex, strain, and species. The results of this study can support genetic mosquito control interventions for which mating represents a key event for their success.

This article outlines the design and implementation of an internet-of-things (IoT) platform for the monitoring of soil carbon dioxide (CO 2 ) concentrations. As atmospheric CO 2 continues to rise, accurate accounting of major carbon sources, such as soil, is essential to inform land management and government policy. Thus, a batch of IoT-connected CO 2 sensor probes were developed for soil measurement. These sensors were designed to capture spatial distribution of CO 2 concentrations across a site and communicate to a central gateway using LoRa. CO 2 concentration and other environmental parameters, including temperature, humidity and volatile organic compound concentration, were logged locally and communicated to the user through a mobile (GSM) connection to a hosted website. Following three field deployments in summer and autumn, we observed clear depth and diurnal variation of soil CO 2 concentration within woodland systems. We determined that the unit had the capacity to log data continuously for a maximum of 14 days. These low-cost systems have great potential for better accounting of soil CO 2 sources over temporal and spatial gradients and possibly flux estimations. Future testing will focus on divergent landscapes and soil conditions.

Early detection of late-onset sepsis (LOS) in preterm infants is crucial since timely treatment initiation is a key prognostic factor. We hypothesized that fecal volatile organic compounds (VOCs), reflecting microbiota composition and function, could serve as a non-invasive biomarker for preclinical pathogen-specific LOS detection. Fecal samples and clinical data of all preterm infants (≤30 weeks' gestation) admitted at nine neonatal intensive care units in the Netherlands and Belgium were collected daily. Samples from one to three days before LOS onset were analyzed by gas chromatography-ion mobility spectrometry (GC-IMS), a technique based on pattern recognition, and gas chromatography-time of flight-mass spectrometry (GC-TOF-MS), to identify unique metabolites. Fecal VOC profiles and metabolites from infants with LOS were compared with matched controls. Samples from 121 LOS infants and 121 matched controls were analyzed using GC-IMS, and from 34 LOS infants and 34 matched controls using GC-TOF-MS. Differences in fecal VOCs were most profound one and two days preceding Escherichia coli LOS (Area Under Curve; p -value: 0.73; p = 0.02, 0.83; p < 0.002, respectively) and two and three days before gram-negative LOS (0.81; p < 0.001, 0.85; p < 0.001, respectively). GC-TOF-MS identified pathogen-specific discriminative metabolites for LOS. This study underlines the potential for VOCs as a non-invasive preclinical diagnostic LOS biomarker.

Throughout the SARS-CoV-2 pandemic, diagnostic technology played a crucial role in managing outbreaks on a national and global level. One diagnostic modality that has shown promise is breath analysis, due to its non-invasive nature and ability to give a rapid result. In this study, a portable FTIR (Fourier Transform Infra-Red) spectrometer was used to detect chemical components in the breath from Covid positive symptomatic and asymptomatic patients versus a control cohort of Covid negative patients. Eighty-five patients who had a nasopharyngeal polymerase chain reaction (PCR) test for the detection of SARS-CoV-2 within the last 5 days were recruited to the study (36 symptomatic PCR positive, 23 asymptomatic PCR positive and 26 asymptomatic PCR negative). Data analysis indicated significant difference between the groups, with SARS-CoV-2 present on PCR versus the negative PCR control group producing an area under the curve (AUC) of 0.87. Similar results were obtained comparing symptomatic versus control and asymptomatic versus control. The asymptomatic results were higher than the symptomatic (0.88 vs. 0.80 AUC). When analysing individual chemicals, we found ethanol, methanol and acetaldehyde were the most important, with higher concentrations in the COVID-19 group, with symptomatic patients being higher than asymptomatic patients. This study has shown that breath analysis can provide significant results that distinguish patients with or without COVID-19 disease/carriage.

Accurate prediction of preterm birth is currently challenging, resulting in unnecessary maternal hospital admittance and fetal overexposure to antenatal corticosteroids. Novel biomarkers like volatile organic compounds (VOCs) hold potential for predictive, bed-side clinical applicability. In a proof of principle study, we aimed to assess the predictive potential of urinary volatile organic compounds in the identification of pregnant women at risk for preterm birth. Urine samples of women with a high risk for preterm birth (≧24 + 0 until 36 + 6 weeks) were collected prospectively and analyzed for VOCs using gas chromatography coupled with an ion mobility spectrometer (GS-IMS). Urinary VOCs of women delivering preterm were compared with urine samples of women with suspicion of preterm birth collected at the same gestation period but delivering at term. Additionally, the results were also interpreted in combination with patient characteristics, such as physical examination at admission, microbial cultures, and placental pathology. In our cohort, we found that urinary VOCs of women admitted for imminent preterm birth were not significantly different in the overall group of women delivering preterm vs. term. However, urinary VOCs of women admitted for imminent preterm birth and delivering between 28 + 0 until 36 + 6 weeks compared to women with a high risk for preterm birth during the same gestation period and eventually delivering at term (>37 + 0 weeks) differed significantly (area under the curve: 0.70). In addition, based on the same urinary VOCs, we could identify women with a confirmed chorioamnionitis (area under the curve: 0.72) and urinary tract infection (area under the curve: 0.97). In conclusion, urinary VOCs hold potential for non-invasive, bedside prediction of preterm birth and on the spot identification of intra-uterine infection and urinary tract infections. We suggest these observations are further explored in larger populations., Competing Interests: The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest., (© 2022 Ronde, Frerichs, Brantenaar, El Manouni El Hassani, Wicaksono, Covington, De Boer, De Meij, Hankemeier, Reiss and Schoenmakers.)

Background: Rapid diagnostic and prognostic tests for coronavirus disease (COVID-19) are urgently required. We aimed to evaluate the diagnostic and prognostic ability of breath analysis using gas chromatography-ion mobility spectrometry (GC-IMS) in hospitalized patients with COVID-19., Methods: Between February and May 2021, we took 1 breath sample for analysis using GC-IMS from participants who were admitted to the hospital for COVID-19, participants who were admitted to the hospital for other respiratory infections, and symptom-free controls, at the University Hospitals of Leicester NHS Trust, United Kingdom. Demographic, clinical, and radiological data, including requirement for continuous positive airway pressure (CPAP) ventilation as a marker for severe disease in the COVID-19 group, were collected., Results: A total of 113 participants were recruited into the study. Seventy-two (64%) were diagnosed with COVID-19, 20 (18%) were diagnosed with another respiratory infection, and 21 (19%) were healthy controls. Differentiation between participants with COVID-19 and those with other respiratory tract infections with GC-IMS was highly accurate (sensitivity/specificity, 0.80/0.88; area under the receiver operating characteristics curve [AUROC], 0.85; 95% CI, 0.74-0.96). GC-IMS was also moderately accurate at identifying those who subsequently required CPAP (sensitivity/specificity, 0.62/0.80; AUROC, 0.70; 95% CI, 0.53-0.87)., Conclusions: GC-IMS shows promise as both a diagnostic tool and a predictor of prognosis in hospitalized patients with COVID-19 and should be assessed further in larger studies., Competing Interests: Potential conflicts of interest. A.S. and E.B. report provision of materials, consumables, and training only, with no payment from IMSPEX Diagnostics Ltd, Abercynon, UK. All other authors report no potential conflicts. All authors have submitted the ICMJE Form for Disclosure of Potential Conflicts of Interest. Conflicts that the editors consider relevant to the content of the manuscript have been disclosed., (© The Author(s) 2022. Published by Oxford University Press on behalf of Infectious Diseases Society of America.)

The evaluation of crop health status and early disease detection are critical for implementing a fast response to a pathogen attack, managing crop infection, and minimizing the risk of disease spreading. Fusarium oxysporum f. sp. cepae , which causes fusarium basal rot disease, is considered one of the most harmful pathogens of onion and accounts for considerable crop losses annually. In this work, the capability of the PEN 3 electronic nose system to detect onion and shallot bulbs infected with F. oxysporum f. sp. cepae , to track the progression of fungal infection, and to discriminate between the varying proportions of infected onion bulbs was evaluated. To the best of our knowledge, this is a first report on successful application of an electronic nose to detect fungal infections in post-harvest onion and shallot bulbs. Sensor array responses combined with PCA provided a clear discrimination between non-infected and infected onion and shallot bulbs as well as differentiation between samples with varying proportions of infected bulbs. Classification models based on LDA, SVM, and k-NN algorithms successfully differentiate among various rates of infected bulbs in the samples with accuracy up to 96.9%. Therefore, the electronic nose was proved to be a potentially useful tool for rapid, non-destructive monitoring of the post-harvest crops.

Five potato varieties were studied using an electronic nose with nine MOS sensors. Parameters measured included carbohydrate content, sugar level, and the toughness of the potatoes. Routine tests were carried out while the signals for each potato were measured, simultaneously, using an electronic nose. The signals obtained indicated the concentration of various chemical components. In addition to support vector machines (SVMs that were used for the classification of the samples, chemometric methods, such as the partial least squares regression (PLSR) method, the principal component regression (PCR) method, and the multiple linear regression (MLR) method, were used to create separate regression models for sugar and carbohydrates. The predictive power of the regression models was characterized by a coefficient of determination (R 2 ), a root-mean-square error of prediction (RMSEP), and offsets. PLSR was able to accurately model the relationship between the smells of different types of potatoes, sugar, and carbohydrates. The highest and lowest accuracy of models for predicting sugar and carbohydrates was related to Marfona potatoes and Sprite cultivar potatoes. In general, in all cultivars, the accuracy in predicting the amount of carbohydrates was somewhat better than the accuracy in predicting the amount of sugar. Moreover, the linear function had 100% accuracy for training and validation in the C-SVM method for classification of five potato groups. The electronic nose could be used as a fast and non-destructive method for detecting different potato varieties. Researchers in the food industry will find this method extremely useful in selecting the desired product and samples.

Conductometric gas sensors (CGS) provide a reproducible gas response at a low cost but their operation mechanisms are still not fully understood. In this paper, we elucidate the nature of interactions between SnO 2 , a common gas-sensitive material, and O 2 , a ubiquitous gas central to the detection mechanisms of CGS. Using synchrotron radiation, we investigated a working SnO 2 sensor under operando conditions via near-ambient pressure (NAP) XPS with simultaneous resistance measurements, and created a depth profile of the variable near-surface stoichiometry of SnO 2- x as a function of O 2 pressure. Our results reveal a correlation between the dynamically changing surface oxygen vacancies and the resistance response in SnO 2 -based CGS. While oxygen adsorbates were observed in this study we conclude that these are an intermediary in oxygen transport between the gas phase and the lattice, and that surface oxygen vacancies, not the observed oxygen adsorbates, are central to response generation in SnO 2 -based gas sensors., Competing Interests: There are no conflicts to declare., (This journal is © The Royal Society of Chemistry.)

Colorectal symptoms are common but only infrequently represent serious pathology, including colorectal cancer (CRC). A large number of invasive tests are presently performed for reassurance. We investigated the feasibility of urinary volatile organic compound (VOC) testing as a potential triage tool in patients fast-tracked for assessment for possible CRC. A prospective, multi-center, observational feasibility study was performed across three sites. Patients referred to NHS fast-track pathways for potential CRC provided a urine sample that underwent Gas Chromatography-Mass Spectrometry (GC-MS), Field Asymmetric Ion Mobility Spectrometry (FAIMS), and Selected Ion Flow Tube Mass Spectrometry (SIFT-MS) analysis. Patients underwent colonoscopy and/or CT colonography and were grouped as either CRC, adenomatous polyp(s), or controls to explore the diagnostic accuracy of VOC output data supported by an artificial neural network (ANN) model. 558 patients participated with 23 (4%) CRC diagnosed. 59% of colonoscopies and 86% of CT colonographies showed no abnormalities. Urinary VOC testing was feasible, acceptable to patients, and applicable within the clinical fast track pathway. GC-MS showed the highest clinical utility for CRC and polyp detection vs. controls (sensitivity = 0.878, specificity = 0.882, AUROC = 0.896) but it is labour intensive. Urinary VOC testing and analysis are feasible within NHS fast-track CRC pathways. Clinically meaningful differences between patients with cancer, polyps, or no pathology were identified suggesting VOC analysis may have future utility as a triage tool.

The early prediction of changes in disease state allows timely treatment of patients with inflammatory bowel disease (IBD) to be performed, which improves disease outcome. The aim of this pilot study is to explore the potential of fecal volatile organic compound (VOC) profiles to predict disease course. In this prospective cohort, IBD patients were asked to collect two fecal samples and fill in a questionnaire at set intervals. Biochemically, active disease was defined by FCP ≥ 250 mg/g and remission was defined by FCP < 100 mg/g. Clinically, active disease was defined by a Harvey Bradshaw Index (HBI) ≥ 5 for Crohn’s disease or by a Simple Clinical Colitis Activity Index (SCCAI) ≥ 3 for ulcerative colitis. Clinical remission was defined by an HBI < 4 or SCCAI ≤ 2. Fecal VOC profiles were measured using gas chromatography-ion mobility spectrometry (GC-IMS). The fecal samples collected first were included for VOC analysis to predict disease state at the following collection. A total of 182 subsequently collected samples met the disease-state criteria. The fecal VOC profiles of samples displaying low FCP levels at the first measurements differed between patients preceding exacerbation versus those who remained in remission (AUC 0.75; p < 0.01). Samples with FCP levels at the first time point displayed different VOC profiles in patients preceding remission compared with those whose disease remained active (AUC 0.86; p < 0.01). Based on disease activity scores, there were no significant differences in any of the comparisons. Alterations in fecal VOC profiles preceding changes in FCP levels may be useful to detect disease-course alterations at an early stage. This could lead to earlier treatment, decreased numbers of complications, surgery and hospital admission.

Coeliac disease (CD) patients are distinguishable from healthy individuals via urinary volatile organic compounds (VOCs) analysis. We exposed 20 stable CD patients on gluten-free diet (GFDs) to a 14-day, 3 g/day gluten challenge (GCh), and assessed urinary VOC changes. A control cohort of 20 patients continued on GFD. Urine samples from Days 0, 7, 14, 28 and 56 were analysed using Lonestar FAIMS and Markes Gas Chromatography-Time of Flight-Mass Spectrometer (GC-TOF-MS). VOC signatures on D (day) 7-56 were compared with D0. Statistical analysis was performed using R. In GCh patients, FAIMS revealed significant VOC differences for all time points compared to D0. GC-TOF-MS revealed significant changes at D7 and D14 only. In control samples, FAIMS revealed significant differences at D7 only. GC-TOF-MS detected no significant differences. Chemical analysis via GC-MS-TOF revealed 12 chemicals with significantly altered intensities at D7 vs. D0 for GCh patients. The alterations persisted for six chemicals at D14 and one (N-methyltaurine) remained altered after D14. This low-dose, short-duration challenge was well tolerated. FAIMS and GC-TOF-MS detected VOC signature changes in CD patients when undergoing a minimal GCh. These findings suggest urinary VOCs could have a role in monitoring dietary compliance in CD patients.

Bladder cancer (BCa) and prostate cancer (PCa) are some of the most common cancers in the world. In both BCa and PCa, the diagnosis is often confirmed with an invasive technique that carries a risk to the patient. Consequently, a non-invasive diagnostic approach would be medically desirable and beneficial to the patient. The use of volatile organic compounds (VOCs) for disease diagnosis, including cancer, is a promising research area that could support the diagnosis process. In this study, we investigated the urinary VOC profiles in BCa, PCa patients and non-cancerous controls by using gas chromatography-ion mobility spectrometry (GC-IMS) and gas chromatography time-of-flight mass spectrometry (GC-TOF-MS) to analyse patient samples. GC-IMS separated BCa from PCa (area under the curve: AUC: 0.97 (0.93-1.00)), BCa vs. non-cancerous (AUC: 0.95 (0.90-0.99)) and PCa vs. non-cancerous (AUC: 0.89 (0.83-0.94)) whereas GC-TOF-MS differentiated BCa from PCa (AUC: 0.84 (0.73-0.93)), BCa vs. non-cancerous (AUC: 0.81 (0.70-0.90)) and PCa vs. non-cancerous (AUC: 0.94 (0.90-0.97)). According to our study, a total of 34 biomarkers were found using GC-TOF-MS data, of which 13 VOCs were associated with BCa, seven were associated with PCa, and 14 VOCs were found in the comparison of BCa and PCa.

Electronic noses (e-nose) offer potential for the detection of cancer in its early stages. The ability to analyse samples in real time, at a low cost, applying easy-to-use and portable equipment, gives e-noses advantages over other technologies, such as Gas Chromatography-Mass Spectrometry (GC-MS). For diseases such as cancer with a high mortality, a technology that can provide fast results for use in routine clinical applications is important. Colorectal cancer (CRC) is among the highest occurring cancers and has high mortality rates, if diagnosed late. In our study, we investigated the use of portable electronic nose (PEN3), with further analysis using GC-TOF-MS, for the analysis of gases and volatile organic compounds (VOCs) to profile the urinary metabolome of colorectal cancer. We also compared the different cancer stages with non-cancers using the PEN3 and GC-TOF-MS. Results obtained from PEN3, and GC-TOF-MS demonstrated high accuracy for the separation of CRC and non-cancer. PEN3 separated CRC from non-cancerous group with 0.81 AUC (Area Under the Curve). We used data from GC-TOF-MS to obtain a VOC profile for CRC, which identified 23 potential biomarker VOCs for CRC. Thus, the PEN3 and GC-TOF-MS were found to successfully separate the cancer group from the non-cancer group.

Hepatocellular carcinoma (HCC) biomarkers are lacking in clinical practice. We therefore explored the pattern and composition of urinary volatile organic compounds (VOCs) in HCC patients. This was done in order to assess the feasibility of a potential non-invasive test for HCC, and to enhance our understanding of the disease. This pilot study recruited 58 participants, of whom 20 were HCC cases and 38 were non-HCC cases. The non-HCC cases included healthy individuals and patients with various stages of non-alcoholic fatty liver disease (NAFLD), including those with and without fibrosis. Urine was analysed using gas chromatography-ion mobility spectrometry (GC-IMS) and gas chromatography-time-of-flight mass spectrometry (GC-TOF-MS). GC-IMS was able to separate HCC from fibrotic cases with an area under the curve (AUC) of 0.97 (0.91-1.00), and from non-fibrotic cases with an AUC of 0.62 (0.48-0.76). For GC-TOF-MS, a subset of samples was analysed in which seven chemicals were identified and tentatively linked with HCC. These include 4-methyl-2,4- bis ( p -hydroxyphenyl)pent-1-ene (2TMS derivative), 2-butanone, 2-hexanone, benzene, 1-ethyl-2-methyl-, 3-butene-1,2-diol, 1-(2-furanyl)-, bicyclo(4.1.0)heptane, 3,7,7-trimethyl-, [1S-(1a,3β,6a)]-, and sulpiride. Urinary VOC analysis using both GC-IMS and GC-TOF-MS proved to be a feasible method of identifying HCC cases, and was also able to enhance our understanding of HCC pathogenesis.

Pancreatic ductal adenocarcinoma (PDAC) is a particularly challenging cancer, with very low 5-year survival rates. This low survival rate is linked to late stage diagnosis, associated with the lack of approved biomarkers. One approach that is receiving considerable attention is the use of volatile organic compounds (VOCs) that emanate from biological waste as biomarkers for disease. In this study, we used urine as our biological matrix and two VOC analysis platforms: gas chromatography - ion mobility spectrometry (GC-IMS) and GC time-of-flight mass spectrometry (GC-TOF-MS). We measured the urinary headspace of samples from patients with PDAC, chronic pancreatitis (CP) and healthy controls. In total, 123 samples were tested from these groups. Results indicate that both GC-IMS and GC-TOF-MS were able to discriminate PDAC from healthy controls with high confidence and an AUC (area under the curve) in excess of 0.85. However, both methods struggled to separate CP from PDAC, with the best result of AUC 0.58. This indicates that both conditions produce similar biomarkers in the urinary headspace. Chemical identification suggests that 2,6-dimethyl-octane, nonanal, 4-ethyl-1,2-dimethyl-benzene and 2-pentanone play an important role in separating these groups. Therefore, both techniques validate this approach in identifying subjects for further investigation in a clinical setting., (Copyright © 2020 Elsevier B.V. All rights reserved.)

Electronic nose (E-nose) technology provides an easy and inexpensive way to analyse chemical samples. In recent years, there has been increasing demand for E-noses in applications such as food safety, environmental monitoring and medical diagnostics. Currently, the majority of E-noses utilise an array of metal oxide (MOX) or conducting polymer (CP) gas sensors. However, these sensing technologies can suffer from sensor drift, poor repeatability and temperature and humidity effects. Optical gas sensors have the potential to overcome these issues. This paper reports on the development of an optical non-dispersive infrared (NDIR) E-nose, which consists of an array of four tuneable detectors, able to scan a range of wavelengths (3.1-10.5 μm). The functionality of the device was demonstrated in a series of experiments, involving gas rig tests for individual chemicals (CO 2 and CH 4 ), at different concentrations, and discriminating between chemical standards and complex mixtures. The optical gas sensor responses were shown to be linear to polynomial for different concentrations of CO 2 and CH 4 . Good discrimination was achieved between sample groups. Optical E-nose technology therefore demonstrates significant potential as a portable and low-cost solution for a number of E-nose applications.

Bile acid diarrhoea (BAD) is a common disorder resulting from increased loss of bile acids (BAs), overlapping irritable bowel syndrome with diarrhoea (IBS-D). The gut microbiota metabolises primary BAs to secondary BAs, with differing impacts on metabolism and homeostasis. The aim of this study was to profile the microbiome, metabolic products and bile acids in BAD. Patients with BAD diagnosed by SeHCAT testing, were compared with other IBS-D patients, and healthy controls. Faecal 16S ribosomal RNA gene analysis was undertaken. Faecal short chain fatty acid (SCFA) and urinary volatile organic compounds (VOCs) were measured. BAs were quantified in serum and faeces. Faecal bacterial diversity was significantly reduced in patients with BAD. Several taxa were enriched compared to IBS-D. SCFA amounts differed in BAD, controls and IBS-D, with significantly more propionate in BAD. Separation of VOC profiles was evident, but the greatest discrimination was between IBS-D and controls. Unconjugated and primary BA in serum and faeces were significantly higher in BAD. The faecal percentage primary BA was inversely related to SeHCAT. BAD produces dysbiosis, with metabolite differences, including VOC, SCFA and primary BAs when compared to IBS-D. These findings provide new mechanistic insights into the pathophysiology of BAD.

Children with severe acute malnutrition (SAM) display immature, altered gut microbiota and have a high mortality risk. Faecal volatile organic compounds (VOCs) reflect the microbiota composition and may provide insight into metabolic dysfunction that occurs in SAM. Here we determine whether analysis of faecal VOCs could identify children with SAM with increased risk of mortality. VOC profiles from children who died within six days following admission were compared to those who were discharged alive using machine learning algorithms. VOC profiles of children who died could be separated from those who were discharged with fair accuracy (AUC) = 0.71; 95% CI 0.59-0.87; P = 0.004). We present the first study showing differences in faecal VOC profiles between children with SAM who survived and those who died. VOC analysis holds potential to help discover metabolic pathways within the intestinal microbiome with causal association with mortality and target treatments in children with SAM.Trial Registration: The F75 study is registered at clinicaltrials.gov/ct2/show/NCT02246296.

Aim: Early detection and removal of colorectal cancer (CRC) and advanced adenomas (AAs) decreases the incidence of and mortality from the disease. We aimed to evaluate the potential of faecal volatile organic compounds (VOCs) for detection and follow-up of colorectal adenoma using advanced electronic nose technology., Method: This was a prospective multi-centre case-control cohort including two district hospitals and one tertiary referral hospital. Patients undergoing colonoscopy were instructed to collect a faecal sample prior to bowel cleansing and were included in the study when CRC, AAs, large adenomas (LAs; 0.5-1.0 cm), small adenomas (SAs; 0.1-0.5 cm) or no endoscopic abnormalities (controls) were observed. Patients undergoing polypectomy and controls were asked for a second sample after 3 months. Faecal VOCs were measured with gas chromatography-ion mobility spectrometry. Random forest, support vector machine, Gaussian process and neural net classification were used to evaluate accuracy., Results: In total, 14 patients with CRC, 64 with AAs, 69 with LAs, 127 with SAs and 227 controls were included. A second sample was collected from 32 polypectomy patients and 32 controls. Faecal VOCs discriminated CRC and adenomas from control [AUC (95% CI): CRC vs control 0.96 (0.89-1); AA vs control 0.96 (0.93-1); LA vs control 0.96 (0.92-0.99); SA vs control 0.96 (0.94-0.99)]. There were no significant differences between CRC and adenoma groups. Patients with adenomas and controls were discriminated prior to polypectomy, whereas 3 months after polypectomy VOC profiles were similar [T0 adenoma vs control 0.98 (0.95-1); T1 adenoma vs control 0.55 (0.40-0.69)]., Conclusions: Faecal VOC profiles may be useful for early detection of CRC and adenomas and the timing of polyp surveillance as polypectomy led to a normalization of the VOC profile., (© 2020 The Association of Coloproctology of Great Britain and Ireland.)

Current available methods for the clinical diagnosis of urinary tract infection (UTI) rely on a urine dipstick test or culturing of pathogens. The dipstick test is rapid (available in 1-2 min), but has a low positive predictive value, while culturing is time-consuming and delays diagnosis (24-72 h between sample collection and pathogen identification). Due to this delay, broad-spectrum antibiotics are often prescribed immediately. The over-prescription of antibiotics should be limited, in order to prevent the development of antimicrobial resistance. As a result, there is a growing need for alternative diagnostic tools. This paper reviews applications of chemical-analysis instruments, such as gas chromatography-mass spectrometry (GC-MS), selected ion flow tube mass spectrometry (SIFT-MS), ion mobility spectrometry (IMS), field asymmetric ion mobility spectrometry (FAIMS) and electronic noses (eNoses) used for the diagnosis of UTI. These methods analyse volatile organic compounds (VOCs) that emanate from the headspace of collected urine samples to identify the bacterial pathogen and even determine the causative agent's resistance to different antibiotics. There is great potential for these technologies to gain wide-spread and routine use in clinical settings, since the analysis can be automated, and test results can be available within minutes after sample collection. This could significantly reduce the necessity to prescribe broad-spectrum antibiotics and allow the faster and more effective use of narrow-spectrum antibiotics.

Preterm birth is the leading cause of death worldwide in children under five years. Due to its complex multifactorial nature, prediction is a challenge. Current research is aiming to develop accurate predictive models using patient history, ultrasound and biochemical markers. Volatile organic compound (VOC) analysis is an approach, which has good diagnostic potential to predict many disease states. Analysis of VOCs can reflect both the microbiome and host response to a condition. We aimed to ascertain if VOC analysis of vaginal swabs, taken throughout pregnancy, could predict which women go on to deliver preterm. Our prospective observational cohort study demonstrates that VOC analysis of vaginal swabs, taken in the midtrimester, is a fair test (AUC 0.79) for preterm prediction, with a sensitivity of 0.66 (95%CI 0.56-0.75) and specificity 0.89 (95%CI 0.82-0.94). Using vaginal swabs taken closest to delivery, VOC analysis is a good test (AUC 0.84) for the prediction of preterm birth with a sensitivity of 0.73 (95%CI 0.64-0.81) and specificity of 0.90 (95%CI 0.82-0.95). Consequently, VOC analysis of vaginal swabs has potential to be used as a predictive tool. With further work it could be considered as an additional component in models for predicting preterm birth.

Background: Inflammatory bowel disease (IBD) is diagnosed and monitored using endoscopic assessment, which is invasive and costly. In this study, potential of faecal volatile organic compounds (VOC) analysis for IBD detection and identification of disease activity was evaluated., Methods: IBD patients visiting outpatient clinics of participating tertiary hospitals were included. Active disease was defined as FCP ≥250 mg/g, remission as FCP <100 mg/g with Harvey Bradshaw Index <4 for Crohn's disease (CD) or Simple Clinical Colitis Activity Index <3 for ulcerative colitis (UC). Healthy controls (HC) were patients without mucosal abnormalities during colonoscopy. Faecal samples were measured using gas chromatography-ion mobility spectrometry., Results: A total of 280 IBD patients collected 107 CDa, 84 CDr, 80 UCa and 63 UCr samples. Additionally, 227 HC provided one faecal sample. UC and CD were discriminated from HC with high accuracy (AUC (95%CI): UCa vs HC 0.96(0.94-0.99); UCr vs HC 0.95(0.93-0.98); CDa vs HC 0.96(0.94-0.99); CDr vs HC 0.95(0.93-0.98)). There were small differences between UC and CD (0.55(0.50-0.6)) and no differences between active disease and remission (UCa vs UCr 0.63(0.44-0.82); CDa vs CDr 0.52(0.39-0.65))., Conclusion: Our study outcomes imply that faecal VOC analysis holds potential for identifying biomarkers for IBD detection but not for monitoring disease activity., Competing Interests: Declaration of Competing Interest The department of Gastroenterology and Hepatology of the Amsterdam UMC and Warwick University has no conflicts of interest to disclose., (Copyright © 2020 Editrice Gastroenterologica Italiana S.r.l. All rights reserved.)

When the gas sensor active layer film thickness is decreased, increased sensitivity to changes in the adsorbate concentration is expected when measuring the resistance of the layer, in particular when this thickness is on the order of the Debye length of the material (one-tens of nanometers); however, this is demonstrated only for a limited number of materials. Herein, ultrathin NiO films of different thicknesses (8-21 nm) have been deposited via chemical vapor deposition to fabricate gas sensor devices. Sensor performance for a range of NO 2 concentrations (800 part-per-billion to 7 part-per-million) was evaluated and an optimum operating temperature of 125 °C determined. The dependence of the potential relative changes with respect to the NO 2 concentration and of the sensor signal with respect to the geometrical parameters was qualitatively evaluated to derive a transduction model capable of fitting the experimental results. The selective sensitivity toward NO 2 was confirmed by the limited response for different reducing gases, CO, CH 4 , NH 3 , and SO 2 , under optimum operating conditions, and the sensor signal toward NO 2 increased with decreasing thickness, demonstrating that the concept of a Debye length dependence of sensitivity is applicable for the p-type semiconductor NiO. In addition, these NiO sensors were exposed to different relative levels of humidity over a wide range of operating temperatures and were found to display humidity tolerance far superior to those in previous reports on SnO 2 materials.

Background: Late onset sepsis (LOS) in preterm infants is preceded by fecal volatile organic compound (VOC) alterations, suggesting an etiologic role of gut microbiota in LOS rather than being primarily caused by central venous catheters (CVC). To increase our knowledge about the involvement of the gut microbiota in LOS, we analyzed fecal samples from septic infants without a CVC., Methods: In this prospective multicenter study, fecal samples were collected daily from all infants born at ≤30 weeks gestation. Fecal VOC profiles up to 3 days prior to sepsis onset from infants with non-catheter-related LOS were compared with profiles from non-septic controls by means of High-Field Asymmetric Waveform Ion Mobility Spectrometry., Results: In total, 104 fecal samples were analyzed. Fecal VOC profiles allowed for discrimination between non-catheter-related LOS cases (n = 24) and matched controls (n = 25). Discriminative accuracy increased after focusing on center of origin (area under the curve, sensitivity, specificity; 0.95, 100%, 83%) and after focusing on LOS cases caused by Staphylococcus epidermidis (0.95, 100%, 78%), the most cultured pathogen (n = 11)., Conclusions: Fecal VOC profiles of preterm LOS infants without a CVC differed from matched controls underlining the increasing notion that aberrations in gut microbiota composition and activity may play a role in LOS etiology.

Surgical site infection represents a large burden of care in the National Health Service. Current methods for diagnosis include a subjective clinical assessment and wound swab culture that may take several days to return a result. Both techniques are potentially unreliable and result in delays in using targeted antibiotics. Volatile organic compounds (VOCs) are produced by micro-organisms such as those present in an infected wound. This study describes the use of a device to differentiate VOCs produced by an infected wound vs. colonised wound. Malodourous wound dressings were collected from patients, these were a mix of post-operative wounds and vascular leg ulcers. Wound microbiology swabs were taken and antibiotics commenced as clinically appropriate. A control group of soiled, but not malodorous wound dressings were collected from patients who had a split skin graft (SSG) donor site. The analyser used was a G.A.S. GC-IMS. The results from the samples had a sensitivity of 100% and a specificity of 88%, with a positive predictive value of 90%. An area under the curve (AUC) of 91% demonstrates an excellent ability to discriminate those with an infected wound from those without. VOC detection using GC-IMS has the potential to serve as a diagnostic tool for the differentiation of infected and non-infected wounds and facilitate the treatment of wound infections that is cost effective, non-invasive, acceptable to patients, portable, and reliable., Competing Interests: The authors declare no conflict of interest.

Early detection of Alzheimer's disease (AD) will help researchers to better understand the disease and develop improved treatments. Recent developments have thus focused on identifying biomarkers for mild cognitive impairment due to AD (MCI) and AD during the preclinical phase. The aim of this pilot study is to determine whether exhaled volatile organic compounds (VOCs) can be used as a non-invasive method to distinguish controls from MCI, controls from AD and to determine whether there are differences between MCI and AD. The study used gas chromatography-ion mobility spectrometry (GC-IMS) techniques. Confounding factors, such as age, smoking habits, gender and alcohol consumption are investigated to demonstrate the efficacy of results. One hundred subjects were recruited including 50 controls, 25 AD and 25 MCI patients. The subject cohort was age- and gender-matched to minimise bias. Breath samples were analysed using a commercial GC-IMS instrument (G.A.S. BreathSpec, Dortmund, Germany). Data analysis indicates that the GC-IMS signal was consistently able to separate between diagnostic groups [AUC ± 95%, sensitivity, specificity], controls versus MCI: [0.77 (0.64-0.90), 0.68, 0.80], controls versus AD: [0.83 (0.72-0.94), 0.60, 0.96], and MCI versus AD: [0.70 (0.55-0.85), 0.60, 0.84]. VOC analysis indicates that six compounds play a crucial role in distinguishing between diagnostic groups. Analysis of possible confounding factors indicate that gender, age, smoking habits and alcohol consumption have insignificant influence on breath content. This pilot study confirms the utility of exhaled breath analysis to distinguish between AD, MCI and control subjects. Thus, GC-IMS offers great potential as a non-invasive, high-throughput, diagnostic technique for diagnosing and potentially monitoring AD in a clinical setting.

Our objective was to assess whether volatile organic compound (VOC) analysis of vaginal swabs can detect maternal Group B Streptococcus (GBS) during pregnancy in a prospective exploratory study. Around 243 women attending a high-risk antenatal clinic at one university teaching hospital in the UK consented to take part and provide vaginal swabs throughout pregnancy. VOC analysis of vaginal swabs was undertaken and compared with the reference standard of GBS detected using enrichment culture method. The chemical components that emanated from the vaginal swabs were measured by gas chromatograph ion mobility spectrometry. This platform has both high sensitivity and good specificity to a range of chemical compounds. Our main outcome was to determine the sensitivity and specificity of VOC analysis for the detection of maternal GBS in vaginal swabs during pregnancy. Our study has demonstrated that the sensitivity and specificity of the VOC analysis by GC-IMS for the detection of GBS from vaginal swabs was 0.81 (95% confidence interval [CI], 0.71-0.89) and 0.97 (95% CI, 0.91-1) respectively. We conclude that the use of VOCs as biomarkers for the detection of maternal GBS in the vagina is a novel tool. As this test produces results within minutes and is of low unit test cost, it has the potential to be used in clinical settings, where fast diagnosis is important, for example, a patient in early labour., (Copyright © 2019 Elsevier Inc. All rights reserved.)

Aim: Inflammatory markers such as serum C-reactive protein (CRP) are used as routine markers to detect anastomotic leakage following colorectal surgery. However, CRP is characterized by a relatively low predictive value, emphasizing the need for the development of novel diagnostic approaches. Volatile organic compounds (VOCs) are gaseous metabolic products deriving from all conceivable bodily excrements and reflect (alterations in) the patient's physical status. Therefore, VOCs are increasingly considered as potential non-invasive diagnostic biomarkers. The aim of this study was to assess the diagnostic accuracy of urinary VOCs for colorectal anastomotic leakage., Methods: In this explorative multicentre study, urinary VOC profiles of 22 patients with confirmed anastomotic leakage and 27 uneventful control patients following colorectal surgery were analysed by field asymmetric ion mobility spectrometry (FAIMS)., Results: Urinary VOCs of patients with anastomotic leakage could be distinguished from those of control patients with high accuracy: area under the receiver operating characteristics curve 0.91 (95% CI 0.81-1.00, P < 0.001), sensitivity 86% and specificity 93%. Serum CRP was significantly increased in patients with a confirmed anastomotic leak but with lower diagnostic accuracy compared to VOC analysis (area under the receiver operating characteristics curve 0.82, 95% CI 0.68-0.95, P < 0.001). Combining VOCs and CRP did not result in a significant improvement of the diagnostic performance compared to VOCs alone., Conclusion: Analysis by FAIMS allowed for discrimination between urinary VOC profiles of patients with a confirmed anastomotic leak and control patients following colorectal surgery. A superior accuracy compared to CRP and apparently high specificity was observed, underlining the potential as a non-invasive biomarker for the detection of colorectal anastomotic leakage., (Colorectal Disease © 2019 The Association of Coloproctology of Great Britain and Ireland.)

In clinical practice, caregivers of children with phenylketonuria (PKU) report that their children have breath malodour. This might be linked to the regular consumption of low phenylalanine (Phe)/Phe-free protein substitutes (PS), which are an essential component of a low-Phe diet. Oral malodour can negatively affect interpersonal communication, lead to bullying, low self-esteem and social isolation. In this longitudinal cross-over study, exhaled volatile organic compounds (VOCs) were measured using gas chromatography-ion mobility spectrometry. 40 children (20 PKU, 20 controls) were recruited. Subjects with PKU took either L-Amino Acid (L-AA) or Casein Glycomacropeptide (CGMP-AA) exclusively for 1 week, in a randomised order. On the seventh day, seven exhaled breath samples were collected over a 10 h period. Subjects then transferred to the other PS for a week and on day seven, provided seven further breath samples. All subjects had a standardised menu using low-Phe food alternatives and all food intake was measured and recorded. In the PKU group, the aim was to collect samples 30 min after consuming PS. In 3 subjects, breath was collected 5 min post-PS consumption. Fasted L-AA and CGMP-AA breath samples contained a similar number of VOC peaks (10-12) as controls. Longitudinal breath testing results demonstrate that there was no significant difference in the number of exhaled VOCs, comparing L-AA or CGMP-AA with controls, or between PS (12-18 VOC peaks). Breath analysed immediately after consumption of PS (n = 3) showed an immediate increase in the number of VOC peaks (25-30), but these were no longer detectable at 30 min post-consumption. This suggests PS have a transient effect on exhaled breath. Measurements taken 30 min after consuming L-AA or CGMP-AA were not significantly different to controls. This indicates that timing food and drinks with PS consumption may be a potential solution for carers to reduce or eliminate unpleasant PS-related breath odours.

Endoscopic evaluation is mandatory in establishing the diagnosis of pediatric inflammatory bowel disease (IBD), but unfortunately carries a high burden on patients. Volatile organic compounds (VOC) have been proposed as alternative, noninvasive diagnostic biomarkers for IBD. The current study aimed to assess and compare the potential of fecal and urinary VOC as diagnostic biomarkers for pediatric IBD in an intention-to-diagnose cohort. In this cohort study, patients aged 4-17 years, referred to the outpatient clinic of a tertiary referral center under suspicion of IBD, were eligible to participate. The diagnosis was established by endoscopic and histopathologic assessment, participants who did not meet the criteria of IBD were allocated to the control group. Participants were instructed to concurrently collect a fecal and urinary sample prior to bowel lavage. Samples were analyzed by means of gas chromatography-ion mobility spectrometry. In total, five ulcerative colitis patients, five Crohn's disease patients, and ten age and gender matched controls were included. A significant difference was demonstrated for both fecal ( p -value, area under the curve; 0.038, 0.73) and urinary (0.028, 0.78) VOC profiles between IBD and controls. Analysis of both fecal and urinary VOC behold equal potential as noninvasive biomarkers for pediatric IBD diagnosis.

Currently, the gold standard for diagnosis of coeliac disease (CD) is based on serology and gastroduodenoscopy with histology of duodenal mucosal biopsies. The aim of this study was to evaluate the potential of faecal volatile organic compounds (VOCs) analysis as a novel, non-invasive tool to discriminate between CD in remission in patients on a gluten-free diet (GFD), refractory coeliac disease (RCD) and controls without CD. Patients with an established diagnosis of CD on a GFD, RCD and healthy controls (HC) were instructed to collect a faecal sample. All subjects completed questionnaires on clinical symptoms, lifestyle and dietary information. Faecal VOCs were measured using gas chromatography-ion mobility spectrometry. A total of 13 CD, 7 RCD and 10 HC were included. A significant difference in VOC profiles between CD and RCD patients (area under the curve (AUC) ± 95% CI: 0.91 (0.79-1) p = 0.000) and between CD and HC (AUC ± 95% CI: 0.71 (0.51-0.91) p = 0.0254) was observed. We found no significant differences between faecal VOC patterns of HC and RCD. Based on faecal VOCs, CD could be discriminated from RCD and HC. This implies that faecal VOC analysis may hold potential as a novel non-invasive biomarker for RCD. Future studies should encompass a larger cohort to further investigate and validate this prior to application in clinical practice.

Early diagnosis of inflammatory bowel disease (IBD), including Crohn's disease (CD) and ulcerative colitis (UC), remains a clinical challenge with current tests being invasive and costly. The analysis of volatile organic compounds (VOCs) in exhaled breath and biomarkers in stool (faecal calprotectin (FCP)) show increasing potential as non-invasive diagnostic tools. The aim of this pilot study is to evaluate the efficacy of breath analysis and determine if FCP can be used as an additional non-invasive parameter to supplement breath results, for the diagnosis of IBD. Thirty-nine subjects were recruited (14 CD, 16 UC, 9 controls). Breath samples were analysed using an in-house built electronic nose (Wolf eNose) and commercial gas chromatograph-ion mobility spectrometer (G.A.S. BreathSpec GC-IMS). Both technologies could consistently separate IBD and controls [AUC ± 95%, sensitivity, specificity], eNose: [0.81, 0.67, 0.89]; GC-IMS: [0.93, 0.87, 0.89]. Furthermore, we could separate CD from UC, eNose: [0.88, 0.71, 0.88]; GC-IMS: [0.71, 0.86, 0.62]. Including FCP did not improve distinction between CD vs UC; eNose: [0.74, 1.00, 0.56], but rather, improved separation of CD vs controls and UC vs controls; eNose: [0.77, 0.55, 1.00] and [0.72, 0.89, 0.67] without FCP, [0.81, 0.73, 0.78] and [0.90, 1.00, 0.78] with FCP, respectively. These results confirm the utility of breath analysis to distinguish between IBD-related diagnostic groups. FCP does not add significant diagnostic value to breath analysis within this study., Competing Interests: The authors declare no conflict of interest.

Background: The United Kingdom (UK) bowel cancer screening programme has reduced mortality from colorectal cancer (CRC), but poor uptake with stool-based tests and lack of specificity of faecal occult blood testing (FOBT), has prompted investigation for a more suitable screening test. The aim of this study was to investigate the feasibility of a urinary volatile organic compounds (VOC)-based screening tool for CRC., Methods: The urine from FOBT-positive patients was analysed using field asymmetric ion mobility spectrometry (FAIMS) and gas chromatography coupled with ion mobility spectrometry (GC-IMS). Data were analysed using a machine learning algorithm to calculate the test accuracy for correct classification of CRC against adenomas and other gastrointestinal pathology., Results: One hundred and sixty-three patients were enrolled in the study. Test accuracy was high for differentiating CRC from control: area under the curve (AUC) 0.98 (95% CI 0.93-1) and 0.82 (95% CI 0.67-0.97) using FAIMS and GC-IMS respectively. Correct classification of CRC from adenoma was high with AUC range 0.83-0.92 (95% CI 0.43-1.0). Classification of adenoma from control was poor with AUC range 0.54-0.61 (95% CI 0.47-0.75) using both analytical modalities., Conclusions: CRC was correctly distinguished from adenomas or no bowel pathology using urinary VOC markers, within the bowel screening population. This pilot study demonstrates the potential of this method for CRC detection, with higher test uptake and superior sensitivity than FOBT. In addition, this is the first application of GC-IMS in CRC detection which has shown high test accuracy and usability.

Background: Esophagectomy or pancreaticoduodenectomy is the standard surgical approach for patients with tumors of the esophagus or pancreatic head. Postoperative mortality is strongly correlated with the occurrence of anastomotic leakage (AL). Delay in diagnosis leads to delay in treatment, which ratifies the need for development of novel and accurate non-invasive diagnostic tests for detection of AL. Urinary volatile organic compounds (VOCs) reflect the metabolic status of an individual, which is associated with a systemic immunological response. The aim of this study was to determine the diagnostic accuracy of urinary VOCs to detect AL after esophagectomy or pancreaticoduodenectomy., Methods: In the present study, urinary VOCs of 63 patients after esophagectomy (n = 31) or pancreaticoduodenectomy (n = 32) were analyzed by means of field asymmetric ion mobility spectrometry. AL was defined according to international study groups., Results: AL was observed in 15 patients (24%). Urinary VOCs of patients with AL after pancreaticoduodenectomy could be distinguished from uncomplicated controls, area under the curve 0.85 (95% CI 0.76-0.93), sensitivity 76%, and specificity 77%. However, this was not observed following esophagectomy, area under the curve 0.51 (95% CI 0.37-0.65)., Conclusion: In our study population AL following pancreaticoduodenectomy could be discriminated from uncomplicated controls by means of urinary VOC analysis, NTC03203434., (© 2018 The Author(s) Published by S. Karger AG, Basel.)

Background: The intestinal microbiota has increasingly been considered to play a role in the etiology of late-onset sepsis (LOS). We hypothesize that early alterations in fecal volatile organic compounds (VOCs), reflecting intestinal microbiota composition and function, allow for discrimination between infants developing LOS and controls in a preclinical stage., Methods: In 9 neonatal intensive care units in the Netherlands and Belgium, fecal samples of preterm infants born at a gestational age ≤30 weeks were collected daily, up to the postnatal age of 28 days. Fecal VOC were measured by high-field asymmetric waveform ion mobility spectrometry (FAIMS). VOC profiles of LOS infants, up to 3 days prior to clinical LOS onset, were compared with profiles from matched controls., Results: In total, 843 preterm born infants (gestational age ≤30 weeks) were included. From 127 LOS cases and 127 matched controls, fecal samples were analyzed by means of FAIMS. Fecal VOCs allowed for preclinical discrimination between LOS and control infants. Focusing on individual pathogens, fecal VOCs differed significantly between LOS cases and controls at all predefined time points. Highest accuracy rates were obtained for sepsis caused by Escherichia coli, followed by sepsis caused by Staphylococcus aureus and Staphylococcus epidermidis., Conclusions: Fecal VOC analysis allowed for preclinical discrimination between infants developing LOS and matched controls. Early detection of LOS may provide clinicians a window of opportunity for timely initiation of individualized therapeutic strategies aimed at prevention of sepsis, possibly improving LOS-related morbidity and mortality.

The electronic nose (eNose) is an instrument designed to mimic the human olfactory system. Usage of eNose in medical applications is more popular than ever, due to its low costs and non-invasive nature. The eNose sniffs the gases and vapours that emanate from human waste (urine, breath, and stool) for the diagnosis of variety of diseases. Diabetes mellitus type 2 (DM2) affects 8.3% of adults in the world, with 43% being underdiagnosed, resulting in 4.9 million deaths per year. In this study, we investigated the potential of urinary volatile organic compounds (VOCs) as novel non-invasive diagnostic biomarker for diabetes. In addition, we investigated the influence of sample age on the diagnostic accuracy of urinary VOCs. We analysed 140 urine samples (73 DM2, 67 healthy) with Field-Asymmetric Ion Mobility Spectrometry (FAIMS); a type of eNose; and FOX 4000 (AlphaM.O.S, Toulouse, France). Urine samples were collected at UHCW NHS Trust clinics over 4 years and stored at -80 °C within two hours of collection. Four different classifiers were used for classification, specifically Sparse Logistic Regression, Random Forest, Gaussian Process, and Support Vector on both FAIMS and FOX4000. Both eNoses showed their capability of diagnosing DM2 from controls and the effect of sample age on the discrimination. FAIMS samples were analysed for all samples aged 0⁻4 years (AUC: 88%, sensitivity: 87%, specificity: 82%) and then sub group samples aged less than a year (AUC (Area Under the Curve): 94%, Sensitivity: 92%, specificity: 100%). FOX4000 samples were analysed for all samples aged 0⁻4 years (AUC: 85%, sensitivity: 77%, specificity: 85%) and a sub group samples aged less than 18 months: (AUC: 94%, sensitivity: 90%, specificity: 89%). We demonstrated that FAIMS and FOX 4000 eNoses can discriminate DM2 from controls using urinary VOCs. In addition, we showed that urine sample age affects discriminative accuracy., Competing Interests: The authors declare no conflict of interest.

Aim: Faecal markers, such as the faecal immunochemical test for haemoglobin (FIT) and faecal calprotectin (FCP), have been increasingly used to exclude colorectal cancer (CRC) and colonic inflammation. However, in those with lower gastrointestinal symptoms there are considerable numbers who have cancer but have a negative FIT test (i.e. false negative), which has impeded its use in clinical practice. We undertook a study of diagnostic accuracy CRC using FIT, FCP and urinary volatile organic compounds (VOCs) in patients with lower gastrointestinal symptoms., Method: One thousand and sixteen symptomatic patients with suspected CRC referred by family physicians were recruited prospectively in accordance with national referring protocol. A total of 562 patients who completed colonic investigations, in addition to providing stool for FIT and FCP as well as urine samples for urinary VOC measurements, were included in the final outcome measures., Results: The sensitivity and specificity for CRC using FIT was 0.80 [95% confidence interval (CI) 0.66-0.93] and 0.93 (CI 0.91-0.95), respectively. For urinary VOCs, the sensitivity and specificity for CRC was 0.63 (CI 0.46-0.79) and 0.63 (CI 0.59-0.67), respectively. However, for those who were FIT-negative CRC (i.e. false negatives), the addition of urinary VOCs resulted in a sensitivity of 0.97 (CI 0.90-1.0) and specificity of 0.72 (CI 0.68-0.76)., Conclusions: When applied to the FIT-negative group, urinary VOCs improve CRC detection (sensitivity rises from 0.80 to 0.97), thus showing promise as a second-stage test to complement FIT in the detection of CRC., (© 2018 The Authors. Colorectal Disease published by John Wiley & Sons Ltd on behalf of Association of Coloproctology of Great Britain and Ireland.)

Background: The diagnostic work-up of pediatric irritable bowel syndrome (IBS) and functional abdominal pain-not otherwise specified (FAP-NOS) commonly includes invasive tests for discrimination from inflammatory bowel disease (IBD). As this carries a high burden on patients, an ongoing need exists for development of noninvasive diagnostic biomarkers for IBS and FAP-NOS. Several studies have shown microbiota alterations in IBS/FAP, which are considered to be reflected by fecal volatile organic compounds (VOCs). The object of the study was to evaluate whether pediatric IBS/FAP-NOS could be discriminated from IBD and healthy controls by fecal VOC analysis., Methods: IBS/FAP-NOS was diagnosed according to the ROME IV criteria, and de novo IBD patients and healthy controls (HCs) aged 4 to 17 years were matched on age and sex. Fecal VOCs were analyzed by means of field asymmetric ion mobility spectrometry., Results: Fecal VOCs of 15 IBS/FAP-NOS, 30 IBD (15 ulcerative colitis, 15 Crohn's disease) patients and 30 HCs were analyzed and compared. Differentiation between IBS/FAP-NOS and IBD was feasible with high accuracy (area under the curve [AUC], 0.94; 95% confidence interval [CI], 0.88-1; P < 0.00001). IBS/FAP-NOS profiles could not be differentiated from HCs (AUC, 0.59; 95% CI, 0.41-0.77; P = 0.167), whereas IBD profiles could with high accuracy (AUC, 0.96; 95% CI, 0.93-1; P < 0.00001)., Conclusion: Pediatric IBS/FAP-NOS could be differentiated from IBD by fecal VOC analysis with high accuracy, but not from healthy controls. The latter finding limits the potential of fecal VOCs to serve as a diagnostic biomarker for IBS/FAP-NOS. However, VOC could possibly serve as additional noninvasive biomarker to differentiate IBS/FAP-NOS from IBD. 10.1093/ibd/izy151&#95;video1izy151.video15786446046001.