Search Results (24)

Electronic noses (E-Noses) equipped with metal-oxide semiconductor (MOS) sensors are promising tools for non-invasive medical diagnostics. Their adoption in clinical practice, however, is limited—among others—by sensor variability across devices, which makes individual calibration necessary. This study presents an approach for the development of a calibration transfer (CT) methodology for urine headspace analysis, involving the design and realization of a dedicated experimental setup and protocol. Partial least squares-discriminant analysis (PLS-DA) models were trained on human urine samples enriched with selected biomarkers to simulate pathological states. Models from a reference (“master”) device were transferred to other (“slave”) units in multiple master–slave configurations using Direct Standardization (DS). To overcome the variability of human urine, synthetic urine recipes were formulated to mimic sensor responses and serve as reproducible transfer samples. Several strategies for selecting transfer samples were evaluated, including the Kennard–Stone algorithm, a DBSCAN-based approach, and random selection. Without CT, classification accuracy on slave devices decreased markedly (37–55%) compared to the master’s performance (79%), whereas applying DS with synthetic standards restored accuracy to 75–80%. These results demonstrate that combining reproducible synthetic standards with DS enables effective model transfer across E-Noses, reducing calibration requirements and supporting their broader applicability in medical diagnostics. Full article

Volatile organic compounds (VOCs) in urine headspace are potential biomarkers for different medical conditions, as canines can detect human diseases simply by smelling VOCs. Because dogs can detect disease-specific VOCs, gas chromatography–mass spectrometry (GC–MS) systems may be able to differentiate medical conditions with enhanced accuracy and precision, given they have unprecedented efficiency in separating, quantifying, and identifying VOCs in urine. Advancements in instrumentation have permitted the development of portable GC–MS systems that analyze VOCs at the point of care, but these are designed for environmental monitoring, emergency response, and manufacturing/processing. The purpose of this study is to repurpose the HAPSITE^® ER portable GC–MS for identifying urinary VOC biomarkers. Method development focused on optimizing sample preparation, off-column conditions, and instrumental parameters that may affect performance. Once standardized, the method was used to analyze a urine standard (n = 10) to characterize intra-day reproducibility. To characterize inter-day performance, n = 3 samples each from three volunteers (and the standard) were analyzed each day for a total of four days (n = 48 samples). Results showed the method could detect VOC signals with adequate reproducibility and distinguish VOC profiles from different volunteers with 100% accuracy. Full article

Polychlorinated biphenyls (PCBs) are persistent organic pollutants that pose significant health risks, especially for neonates. Traditional urine analysis methods for PCBs are often complex and prone to contamination. This study introduces a novel, efficient, and contamination-free method for PCB analysis in neonatal urine using 3D-printed extraction devices. A headspace extraction method was developed, utilizing a 3D-printed device containing C18-modified silica particles. Urine samples were heated to 90 °C, and volatile PCBs were sorbed onto the particles. The method was optimized for maximum extraction efficiency and selectivity, demonstrating excellent linearity, precision, and accuracy. The optimized method was successfully applied to analyze neonatal urine samples, revealing detectable levels of PCBs. This innovative approach, leveraging 3D-printed devices, offers a promising solution for sample preparation, minimizing contamination risks and enabling the analysis of volatile compounds. The customizable nature of 3D-printed devices opens up possibilities for future advancements in environmental analysis. Full article

Alterations in metabolism caused by SARS-CoV-2 infection have been highlighted in various investigations and have been used to search for biomarkers in different biological matrices. However, the selected biomarkers vary greatly across studies. Our objective is to provide a robust selection of biomarkers, including results from different sample treatments in the analysis of volatile organic compounds (VOCs) present in urine samples from patients with COVID-19. Between September 2021 and May 2022, urine samples were collected from 35 hospitalized COVID-19 patients and 32 healthy controls. The samples were analyzed by headspace (HS) solid phase microextraction (SPME) coupled to gas chromatography–mass spectrometry (GC-MS). Analyses were conducted on untreated urine samples and on samples that underwent specific pretreatments: lyophilization and treatment with sulfuric acid. Partial Least Squares Linear Discriminant Analysis (PLS-LDA) and Subwindow Permutation Analysis (SPA) models were established to distinguish patterns between COVID-19 patients and healthy controls. The results identify compounds that are present in different proportions in urine samples from COVID-19 patients compared to those from healthy individuals. Analysis of urine samples using HS-SPME-GC-MS reveals differences between COVID-19 patients and healthy individuals. These differences are more pronounced when methods that enhance VOC formation are used. However, these pretreatments can cause reactions between sample components, creating additional products or removing compounds, so biomarker selection could be altered. Therefore, using a combination of methods may be more informative when evaluating metabolic alterations caused by viral infections and would allow for a better selection of biomarkers. Full article

Prostate cancer (PCa) continues to be the second most common malignant tumour and the main cause of oncological death in men. Investigating endogenous volatile organic metabolites (VOMs) produced by various metabolic pathways is emerging as a novel, effective, and non-invasive source of information to establish the volatilomic biosignature of PCa. In this study, headspace solid-phase microextraction combined with gas chromatography–mass spectrometry (HS-SPME/GC-MS) was used to establish the urine volatilomic profile of PCa and identify VOMs that can discriminate between the two investigated groups. This non-invasive approach was applied to oncological patients (PCa group, n = 26) and cancer-free individuals (control group, n = 30), retrieving a total of 147 VOMs from various chemical families. This included terpenes, norisoprenoid, sesquiterpenes, phenolic, sulphur and furanic compounds, ketones, alcohols, esters, aldehydes, carboxylic acid, benzene and naphthalene derivatives, hydrocarbons, and heterocyclic hydrocarbons. The data matrix was subjected to multivariate analysis, namely partial least-squares discriminant analysis (PLS-DA). Accordingly, this analysis showed that the group under study presented different volatomic profiles and suggested potential PCa biomarkers. Nevertheless, a larger cohort of samples is required to boost the predictability and accuracy of the statistical models developed. Full article

Objective: To evaluate the association between environmental exposure to the following chemical substances: cadmium (Cd), lead (Pb), nickel (Ni), manganese (Mn), benzene (BZN), and toluene (TLN), and Period Circadian Regulator 3 (PER3) gene variable number of tandem repeats (VNTR) polymorphisms, according to chronotype in a population living in a steel residue-contaminated area. Methods: This assessment comprises a study conducted from 2017 to 2019 with 159 participants who completed health, work, and Pittsburgh sleep scale questionnaires. Cd, Pb, Ni, Mn, BZN, and TLN concentrations in blood and urine were determined by Graphite Furnace Atomic Absorption Spectrometry (GFAAS) and Headspace Gas Chromatography (GC), and genotyping was carried out using Polymerase Chain Reaction (PCR). Results: A total of 47% of the participants were afternoon chronotype, 42% were indifferent, and 11% were morning chronotype. Insomnia and excessive sleepiness were associated with the indifferent chronotype, while higher urinary manganese levels were associated with the morning chronotype (Kruskal–Wallis chi-square = 9.16; p < 0.01). In turn, the evening chronotype was associated with poorer sleep quality, higher lead levels in blood, and BZN and TLN levels in urine (χ² = 11.20; p < 0.01) in non-occupationally exposed individuals (χ² = 6.98; p < 0.01) as well as the highest BZN (χ² = 9.66; p < 0.01) and TLN (χ² = 5.71; p < 0.01) levels detected in residents from the influence zone 2 (far from the slag). Conclusion: Mn, Pb, benzene, and toluene contaminants may have influenced the different chronotypes found in the steel residue-exposed population. Full article

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. Full article

Inflammatory bowel disease (IBD) is an immune-mediated disease characterized by chronic mucosal inflammation of the digestive tract. The IBD diagnosis is currently based on the results of imaging, clinical, and histopathological tests. The gold standard diagnostic method is endoscopy, an invasive imaging technique that requires patient sedation and prior bowel preparation and is expensive. In the present work, monitoring the volatile compound fingerprint of serum and urine by headspace gas chromatography-ion mobility spectrometry (HS-GC-IMS) is presented as a rapid and reliable diagnostic complementary test for patients with IBD. The analytical method was optimized and applied for the analysis of serum (118) and urine (123) samples from patients with IBD (in remission and active phase of the disease) and healthy volunteers without IBD. Orthogonal partial least square discriminant analysis was performed using all the integrated markers present in the topographic maps of each sample type, allowing the differentiation between healthy IBD volunteers and IBD patients and between IBD status (remission or active). The individual study of markers allowed the identification and quantification of twelve and six compounds in urine and serum samples, respectively. This information was further used to perform a one-way analysis of variance to compare the different categories. Full article

Predicting when a patient with advanced cancer is dying is a challenge and currently no prognostic test is available. We hypothesised that a dying process from cancer is associated with metabolic changes and specifically with changes in volatile organic compounds (VOCs). We analysed urine from patients with lung cancer in the last weeks of life by headspace gas chromatography mass spectrometry. Urine was acidified or alkalinised before analysis. VOC changes in the last weeks of life were identified using univariate, multivariate and linear regression analysis; 12 VOCs increased (11 from the acid dataset, 2 from the alkali dataset) and 25 VOCs decreased (23 from the acid dataset and 3 from the alkali dataset). A Cox Lasso prediction model using 8 VOCs predicted dying with an AUC of 0.77, 0.78 and 0.85 at 30, 20 and 10 days and stratified patients into a low (median 10 days), medium (median 50 days) or high risk of survival. Our data supports the hypothesis there are specific metabolic changes associated with the dying. The VOCs identified are potential biomarkers of dying in lung cancer and could be used as a tool to provide additional prognostic information to inform expert clinician judgement and subsequent decision making. Full article

Volatile organic compounds (VOCs) are a differentiated class of molecules, continuously generated in the human body and released as products of metabolic pathways. Their concentrations vary depending on pathophysiological conditions. They are detectable in a wide variety of biological samples, such as exhaled breath, faeces, and urine. In particular, urine represents an easily accessible specimen widely used in clinics. The most used techniques for VOCs detections are expensive and time-consuming, thus not allowing for rapid clinical analysis. In this perspective, the aim of this study is a comprehensive characterisation of the urine volatilome by the development of an alternative rapid analytical method. Briefly, 115 urine samples are collected; sample treatment is not needed. VOCs are detected in the urine headspace using gas chromatography coupled to ion mobility spectrometry (GC–IMS) by an extremely fast analysis (10 min). The method is analytically validated; the analysis is sensitive and robust with results comparable to those reported with other techniques. Twenty-three molecules are identified, including ketones, aldehydes, alcohols, and sulphur compounds, whose concentration is altered in several pathological states such as cancer and metabolic disorders. Therefore, it opens new perspectives for fast diagnosis and screening, showing great potential for clinical applications. Full article

Ethanol is the most commonly used recreational drug worldwide. This study describes the development and validation of a headspace gas chromatography flame ionisation detection (HS-GC-FID) method using dual columns and detectors for simultaneous separation and quantitation. The use of a dual-column, dual-detector HS-GC-FID to quantitate ethanol is a common analytical technique in forensic toxicology; however, most analytical systems utilise pressure-balance injection rather than a simplified gas-tight syringe, as per this technique. This study is the first to develop and validate a technique that meets the specifications of the United Kingdom’s requirements for road traffic toxicology testing using a Shimadzu GC-2014 gas-tight syringe. The calibration ranged from 10 to 400 mg/100 mL, with a target minimum linearity of r2 > 0.999, using tertiary butanol as the internal standard marker. The method has an expanded uncertainty at 99.73% confidence of 3.64% at 80 mg/100 mL, which is the blood alcohol limit for drink driving in England and Wales. In addition, at 200 mg%—the limit at which a custodial sentence may be imposed on the defendant—the expanded uncertainty was 1.95%. For both the 80 mg% and 200 mg% concentrations, no bias was present in the analytical method. This method displays sufficient separation for other alcohols, such as methanol, isopropanol, acetaldehyde, and acetone. The validation of this technique complies with the recommended laboratory guidelines set out by United Kingdom and Ireland Association of Forensic Toxicologists (UKIAFT), the recently issued Laboratory 51 guidelines by the United Kingdom Accreditation Service (UKAS), and the criteria set out by the California Code of Regulations (CCR), 17 CCR § 1220.1. Full article

Background: Bladder cancer (BCa) emits specific volatile organic compounds (VOCs) in the urine headspace that can be detected by an electronic nose. The diagnostic performance of an electronic nose in detecting BCa was investigated in a pilot study. Methods: A prospective, single-center, controlled, non-randomized, phase 2 study was carried out on 198 consecutive subjects (102 with proven BCa, 96 controls). Urine samples were evaluated with an electronic nose provided with 32 volatile gas analyzer sensors. The tests were repeated at least two times per sample. Accuracy, sensitivity, specificity, and variability were evaluated using mainly the non-parametric combination method, permutation tests, and discriminant analysis classification. Results: Statistically significant differences between BCa patients and controls were reported by 28 (87.5%) of the 32 sensors. The overall discriminatory power, sensitivity, and specificity were 78.8%, 74.1%, and 76%, respectively; 13/96 (13.5%) controls and 29/102 (28.4%) BCa patients were misclassified as false positive and false negative, respectively. Where the most efficient sensors were selected, the sensitivity and specificity increased up to 91.1% (72.5–100) and 89.1% (81–95.8), respectively. None of the tumor characteristics represented independent predictors of device responsiveness. Conclusions: The electronic nose might represent a potentially reliable, quick, accurate, and cost-effective tool for non-invasive BCa diagnosis. Full article

Renal cell carcinoma (RCC) represents around 3% of all cancers, within which clear cell RCC (ccRCC) are the most common type (70–75%). The RCC disease regularly progresses asymptomatically and upon presentation is recurrently metastatic, therefore, an early method of detection is necessary. The identification of one or more specific biomarkers measurable in biofluids (i.e., urine) by combined approaches could surely be appropriate for this kind of cancer, especially due to easy obtainability by noninvasive method. OLR1 is a metabolic gene that encodes for the Lectin-like oxidized low-density lipoprotein receptor-1 (LOX-1), implicated in inflammation, atherosclerosis, ROS, and metabolic disorder-associated carcinogenesis. Specifically, LOX-1 is clearly involved in tumor insurgence and progression of different human cancers. This work reports for the first time the presence of LOX-1 protein in ccRCC urine and its peculiar distribution in tumoral tissues. The urine samples headspace has also been analyzed for the presence of the volatile compounds (VOCs) by SPME-GC/MS and gas sensor array. In particular, it was found by GC/MS analysis that 2-Cyclohexen-1-one,3-methyl-6-(1-methylethyl)- correlates with LOX-1 concentration in urine. The combined approach of VOCs analysis and protein quantification could lead to promising results in terms of diagnostic and prognostic potential for ccRCC tumors. Full article

Timely diagnosis is crucial to improve the long-term survival of bladder cancer (BC) patients. The discovery of new BC biomarkers based in urine analysis is very attractive because this biofluid is in direct contact with the inner bladder layer, in which most of the neoplasms develop, and is non-invasively collected. Hence, this work aimed to unveil alterations in the urinary volatile profile of patients diagnosed with BC compared with cancer-free individuals, as well as differences among patients diagnosed at different tumor stages, to identify candidate biomarkers for non-invasive BC diagnosis and staging. Urine analysis was performed by headspace solid-phase microextraction coupled with gas chromatography-mass spectrometry (HS-SPME-GC-MS). The results unveiled that BC patients have a distinct urinary volatile profile characterized by higher levels of several alkanes and aromatic compounds, and lower levels of aldehydes, ketones and monoterpenes. Seventeen significantly altered volatiles were used to evaluate the performance for overall BC detection, disclosing 70% sensitivity, 89% specificity and 80% accuracy. Moreover, distinct urinary volatile profiles were found among patients diagnosed at different tumor stages (Ta/Tis, T1 and ≥T2). This work identified distinct urinary volatile signatures of BC patients with potential for non-invasive detection and staging of bladder cancer. Full article

Volatile organic compounds (VOCs) exiting in urine are potential biomarkers of chronic kidney diseases. Headspace solid phase microextraction (HS-SPME) was applied for extraction VOCs over the urine samples. Volatile metabolites were separated and identified by means of two-dimensional gas chromatography and time of flight mass spectrometry (GC × GC TOF MS). Patients with glomerular diseases (n = 27) and healthy controls (n = 20) were recruited in the study. Different VOCs profiles were obtained from patients and control. Developed methodology offers the opportunity to examine the metabolic profile associated with glomerulopathy. Four compounds found in elevated amounts in the patients group, i.e., methyl hexadecanoate; 9-hexadecen-1-ol; 6,10-dimethyl-5,9-undecadien-2-one and 2-pentanone were proposed as markers of glomerular diseases. Full article