Journal of breath research最新文献

{"title":"Exploring exhaled breath volatile organic compounds in occupational asthma: A pilot cross-sectional study.","authors":"Hilde Heiro,Tonje Trulssen Hildre,Amy Craster,Liam Grimmett,Matteo Tardelli,Bato Hammarström","doi":"10.1088/1752-7163/ad7b6a","DOIUrl":"https://doi.org/10.1088/1752-7163/ad7b6a","url":null,"abstract":"Occupational asthma (OA) is divided into allergic asthma (AA) and irritant-induced asthma (IIA). IIA can be divided further into three different phenotypic subtypes. Volatile organic compounds (VOCs) in exhaled breath can reflect metabolic changes in the body, and a wide range of them have been associated with various diseases in the last two decades. This is the first known study to explore breath VOCs in subjects with OA, aimed to identify potential biomarkers to distinguish OA from healthy controls, as well as between different OA subgroups. In a cross-sectional investigation, exhaled breath from 40 patients with OA and 45 respiratory healthy healthcare workers were collected with ReCIVA® Breath Sampler. Samples were analyzed through an untargeted approach using thermal desorption-gas chromatography mass spectrometry (TD-GC-MS), and VOCs were identified according to tier classification. The data underwent analysis using both non-parametric and parametric statistical methods. 536 VOCs were identified. Significance (p<0.05) was observed in several emitted VOCs. Among these, compounds such as 1-hexadecanol, 2,3-butanediol, xylene, phenol, acetone, 3-methylhexane, methylcyclohexane, and isoprene have biological implications or are associated with exposures linked to OA. These VOCs may reflect metabolic changes in the body and the microbiome, as well as external exposures due to occupation.&#xD;In particular, 1-hexadecanol, 2,3-butanediol, xylene and phenol are associated with reduced nicotinamide adenine dinucleotide (NADH) and production of reactive oxygen species (ROS), mechanisms that can be linked to asthmatic diseases and therefore suggests its potential as biomarkers. This study demonstrates that VOCs detected in exhaled breath could serve as indicators of occupational exposure and enhance diagnostic accuracy for asthma.&#xD.","PeriodicalId":15306,"journal":{"name":"Journal of breath research","volume":"30 1","pages":""},"PeriodicalIF":3.8,"publicationDate":"2024-09-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142261936","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Exhaled breath condensate (EBC) in respiratory diseases: Recent advances, and future perspectives in the age of Omic sciences.","authors":"Mauro Maniscalco,Claudio Candia,Salvatore Fuschillo,Pasquale Ambrosino,Debora Paris,Andrea Motta","doi":"10.1088/1752-7163/ad7a9a","DOIUrl":"https://doi.org/10.1088/1752-7163/ad7a9a","url":null,"abstract":"Exhaled breath condensate (EBC) is used as a promising noninvasive diagnostic tool in the field of respiratory medicine. EBC is achieved by cooling exhaled air, which contains aerosolized particles and volatile compounds present in the breath. This method provides useful information on the biochemical and inflammatory state of the airways. In respiratory diseases such as asthma, chronic obstructive pulmonary disease (COPD) and cystic fibrosis, EBC analysis can reveal elevated levels of biomarkers such as hydrogen peroxide, nitric oxide and various cytokines, which correlate with oxidative stress and inflammation. &#xD;Furthermore, the presence of certain volatile organic compounds (VOCs) in EBC has been linked to specific respiratory conditions, potentially serving as disease-specific fingerprints. The noninvasive nature of EBC sampling makes it particularly useful for repeated measures and for use in vulnerable populations, including children and the elderly. Despite its potential, the standardization of collection methods, analytical techniques and interpretation of results currently limits its use in clinical practice. &#xD;Nonetheless, EBC holds significant promise for improving the diagnosis, monitoring and therapy of respiratory diseases.&#xD;In this tutorial we will present the latest advances in EBC research in airway diseases and future prospects for clinical applications of EBC analysis, including the application of the Omic sciences for its analysis.&#xD.","PeriodicalId":15306,"journal":{"name":"Journal of breath research","volume":"30 1","pages":""},"PeriodicalIF":3.8,"publicationDate":"2024-09-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142262032","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Rapid point-of-care breath test predicts breast cancer and abnormal mammograms in symptomatic women.","authors":"Michael Phillips,Therese Bevers,Linda Larsen,Nadine Pappas,Sonali Pathak","doi":"10.1088/1752-7163/ad7a20","DOIUrl":"https://doi.org/10.1088/1752-7163/ad7a20","url":null,"abstract":"Previous studies have reported volatile organic compounds (VOCs) in the breath as biomarkers of breast cancer. These biomarkers may be derived from cancer-associated fibroblasts, in which oxidative stress degrades polyunsaturated fatty acids to volatile alkanes and methylated alkane derivatives that are excreted in the breath. We evaluated a rapid point-of-care test for breath VOC biomarkers as predictors of breast cancer and abnormal mammograms.&#xD;Methods: We studied 593 women aged ≥ 18 yr referred to three sites for mammography for a symptomatic breast-related concern (e.g. breast mass, nipple discharge). A rapid point-of-care breath testing system collected and concentrated alveolar breath VOCs on a sorbent trap and analyzed them with gas chromatography and surface acoustic wave detection in < 6 min. Breath VOC chromatograms were randomly assigned to a training set or to a validation set. Monte Carlo analysis identified significant breath VOC biomarkers of breast cancer and abnormal mammograms in the training set, and these biomarkers were incorporated into a multivariate algorithm to predict disease in the validation set. &#xD;Results: Prediction of breast cancer: 50 women had biopsy-proven breast cancer (invasive cancer 41, ductal non-invasive cancer 9)&#xD;Unsplit data set: Breath VOCs identified breast cancer with 83% accuracy (area under curve of receiver operating characteristic), 82% sensitivity and 77.1% specificity.&#xD;Split data sets: Training set breath VOCs identified breast cancer with 80.3% accuracy, 84% sensitivity and 74.3% specificity. Corresponding values in the validation set were 68%% accuracy, 72.4% sensitivity and 61.5% specificity.&#xD;Prediction of BIRADS 4 and 5 mammograms (versus BIRADS 1, 2 and 3): &#xD;Unsplit data set: Breath VOCs identified abnormal mammograms with 76.2% accuracy.&#xD;Split data sets: Breath VOCs identified abnormal mammograms with 74.2% accuracy, 73.3% sensitivity and 60% specificity. Corresponding values in the validation set were 60.5% accuracy, 64.2% sensitivity and 51% specificity.&#xD;Conclusions: A rapid point-of-care test for breath VOC biomarkers predicted risk of breast cancer and abnormal mammograms in women with breast-related symptoms.&#xD;&#xD.","PeriodicalId":15306,"journal":{"name":"Journal of breath research","volume":"23 1","pages":""},"PeriodicalIF":3.8,"publicationDate":"2024-09-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142261935","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Volatile organic compound analysis of malignant pleural mesothelioma chorioallantoic membrane xenografts.","authors":"Liam D Little, Sarah E Barnett, Theo Issitt, Sam Bonsall, Vikki A Carolan, Elizabeth Allen, Laura M Cole, Neil A Cross, Judy M Coulson, Sarah L Haywood-Small","doi":"10.1088/1752-7163/ad7166","DOIUrl":"10.1088/1752-7163/ad7166","url":null,"abstract":"<p><p>Malignant pleural mesothelioma (MPM) is an aggressive cancer associated with asbestos exposure. MPM is often diagnosed late, at a point where limited treatment options are available, but early intervention could improve the chances of successful treatment for MPM patients. Biomarkers to detect MPM in at-risk individuals are needed to implement early diagnosis technologies. Volatile organic compounds (VOCs) have previously shown diagnostic potential as biomarkers when analysed in MPM patient breath. In this study, chorioallantoic membrane (CAM) xenografts of MPM cell lines were used as models of MPM tumour development for VOC biomarker discovery with the aim of generating targets for investigation in breath, biopsies or other complex matrices. VOC headspace analysis of biphasic or epithelioid MPM CAM xenografts was performed using solid-phase microextraction and gas chromatography-mass spectrometry. We successfully demonstrated the capture, analysis and separation of VOC signatures from CAM xenografts and controls. A panel of VOCs was identified that showed discrimination between MPM xenografts generated from biphasic and epithelioid cells and CAM controls. This is the first application of the CAM xenograft model for the discovery of VOC biomarkers associated with MPM histological subtypes. These findings support the potential utility of non-invasive VOC profiling from breath or headspace analysis of tissues for detection and monitoring of MPM.</p>","PeriodicalId":15306,"journal":{"name":"Journal of breath research","volume":" ","pages":""},"PeriodicalIF":3.7,"publicationDate":"2024-09-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11388873/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142008804","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Generating pooled quality control samples of volatile organic compounds.","authors":"Waqar Ahmed,Max Wilkinson,Stephen J Fowler","doi":"10.1088/1752-7163/ad7977","DOIUrl":"https://doi.org/10.1088/1752-7163/ad7977","url":null,"abstract":"Untargeted analysis of volatile organic compounds (VOCs) from exhaled breath and culture headspace can be influenced by several confounding factors that are not reflected in reference standards. In this study, we propose a method to generating pooled quality control (QC) samples for untargeted VOC studies using a split-recollection workflow for thermal desorption tubes. Sample tubes were desorbed with a 10% split from each sample and recollected onto a single tube, generating a pooled QC sample. This QC sample was then repeatedly desorbed and recollected with a sequentially lower split ratio allowing injection of up to ten QC samples. We found pooled QC samples to be representative of complex mixtures using principal component analysis (PCA) and may be useful in future longitudinal, multi-centre, and validation studies to assess data quality and adjust for batch effects.","PeriodicalId":15306,"journal":{"name":"Journal of breath research","volume":"9 1","pages":""},"PeriodicalIF":3.8,"publicationDate":"2024-09-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142181552","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Discovery and Analysis of the Relationship between Organic Components in Exhaled Breath and Bronchiectasis.","authors":"Lichao Fan,Yan Chen,Yang Chen,Ling Wang,Shuo Liang,Kebin Cheng,Yue Pei,Yong Feng,Qingyun Li,Mengqi He,Ping Jiang,Haibin Chen,Jinfu Xu","doi":"10.1088/1752-7163/ad7978","DOIUrl":"https://doi.org/10.1088/1752-7163/ad7978","url":null,"abstract":"The prevalence of patients with bronchiectasis (BE) has been rising in recent years, which increases the substantial burden on the family and society. Exploring a convenient, effective, and low-cost screening tool for the diagnosis of BE is urgent. We expect to identify the accuracy of breath biomarkers(BBs) for the diagnosis of BE through breathomics testing and explore the association between BBs and clinical features of BE.&#xD;Method: Exhaled breath samples were collected and detected by high-pressure photon ionization time-of-flight mass spectrometry(HPPI-TOF MS) in a cross-sectional study. Exhaled breath samples were from 215 patients with BE and 295 control individuals. The potential BBs were selected via the machine learning method. The overall performance was assessed for the BBs-based BE detection model. The significant BBs between different subgroups such as the severity of BE, acute or stable stage, combined with hemoptysis or not, with or without Nontuberculous Mycobacterium (NTM), Pseudomonas aeruginosa (P.a) isolation or not, and the BBs related to the number of involved lung lobes and lung function were discovered and analyzed.&#xD;Results: The top 10 BBs based machine learning model achieved an area under the curve (AUC) of 0.940, sensitivity of 90.7%, specificity of 85%, and accuracy of 87.4% in BE diagnosis. Except for the top ten BBs, other BBs were found also related to the severity, acute/stable status, hemoptysis or not, NTM infection, P.a isolation, the number of involved lobes, and three lung functional paramters in BE patients.&#xD;Conclusions: BBs-based BE detection model showed good accuracy for diagnosis. BBs have a close relationship with the clinical features of BE. The breath test method may provide a new strategy for bronchiectasis screening and personalized management.&#xD;&#xD;Clinical Trail Number: NCT05293314&#xD.","PeriodicalId":15306,"journal":{"name":"Journal of breath research","volume":"25 1","pages":""},"PeriodicalIF":3.8,"publicationDate":"2024-09-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142223804","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Performance of empirical and model-based classifiers for detecting sucrase-isomaltase inhibition using the¹³C-sucrose breath test.","authors":"Hannah Van Wyk, Gwenyth O Lee, Robert J Schillinger, Christine A Edwards, Douglas J Morrison, Andrew F Brouwer","doi":"10.1088/1752-7163/ad748d","DOIUrl":"10.1088/1752-7163/ad748d","url":null,"abstract":"<p><p>The¹³C-sucrose breath test (¹³C-SBT) has been proposed to estimate sucrase-isomaltase (SIM) activity and is a promising test for SIM deficiency, which can cause gastrointestinal symptoms, and for intestinal mucosal damage caused by gut dysfunction or chemotherapy. We previously showed how various summary measures of the¹³C-SBT breath curve reflect SIM inhibition. However, it is uncertain how the performance of these classifiers is affected by test duration. We leveraged¹³C-SBT data from a cross-over study in 16 adults who received 0, 100, and 750 mg of Reducose, an SIM inhibitor. We evaluated the performance of a pharmacokinetic-model-based classifier,ρ, and three empirical classifiers (cumulative percent dose recovered at 90 min (cPDR90), time to 50% dose recovered, and time to peak dose recovery rate), as a function of test duration using receiver operating characteristic (ROC) curves. We also assessed the sensitivity, specificity, and accuracy of consensus classifiers. Test durations of less than 2 h generally failed to accurately predict later breath curve dynamics. The cPDR90 classifier had the highest ROC area-under-the-curve and, by design, was robust to shorter test durations. For detecting mild SIM inhibition,ρhad a higher sensitivity. We recommend¹³C-SBT tests run for at least a 2 h duration. Although cPDR90 was the classifier with highest accuracy and robustness to test duration in this application, concerns remain about its sensitivity to misspecification of the CO₂production rate. More research is needed to assess these classifiers in target populations.</p>","PeriodicalId":15306,"journal":{"name":"Journal of breath research","volume":" ","pages":""},"PeriodicalIF":3.7,"publicationDate":"2024-09-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11385691/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142093212","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Systematic study of polymer gas sampling bags for offline analysis of exhaled breath.","authors":"Mateusz Fido, Simone Hersberger, Andreas T Güntner, Renato Zenobi, Stamatios Giannoukos","doi":"10.1088/1752-7163/ad6a31","DOIUrl":"10.1088/1752-7163/ad6a31","url":null,"abstract":"<p><p>Polymeric bags are a widely applied, simple, and cost-effective method for the storage and offline analysis of gaseous samples. Various materials have been used as sampling bags, all known to contain impurities and differing in their cost, durability, and storage capabilities. Herein, we present a comparative study of several well-known bag materials, Tedlar (PVF), Kynar (PVDF), Teflon (PTFE), and Nalophan (PET), as well as a new material, ethylene vinyl copolymer (EVOH), commonly used for storing food. We investigated the influences of storage conditions, humidity, bag cleaning, and light exposure on volatile organic compound concentration (acetone, acetic acid, isoprene, benzene, limonene, among others) in samples of exhaled human breath stored in bags for up to 48 h. Specifically, we show high losses of short-chain fatty acids (SCFAs) in bags of all materials (for most SCFAs, less than 50% after 8 h of storage). We found that samples in Tedlar, Nalophan, and EVOH bags undergo changes in composition when exposed to UV radiation over a period of 48 h. We report high initial impurity levels in all the bags and their doubling after a period of 48 h. We compare secondary electrospray ionization and proton transfer reaction mass spectrometry in the context of offline analysis after storage in sampling bags. We provide an analytical perspective on the temporal evolution of bag contents by presenting the intensity changes of all significant<i>m</i>/<i>z</i>features. We also present a simple, automated, and cost-effective offline sample introduction system, which enables controlled delivery of collected gaseous samples from polymeric bags into the mass spectrometer. Overall, our findings suggest that sampling bags exhibit high levels of impurities, are sensitive to several environmental factors (e.g. light exposure), and provide low recoveries for some classes of compounds, e.g. SCFAs.</p>","PeriodicalId":15306,"journal":{"name":"Journal of breath research","volume":" ","pages":""},"PeriodicalIF":3.7,"publicationDate":"2024-08-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141874893","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Evaluation of tetrachloroethylene (PCE) and its degradation products in human exhaled breath and indoor air in a community setting.","authors":"Jung Hyun Lee, Alaina K Bryant, Marwan Alajlouni, Brandon E Boor, Antonios Tasoglou, Sa Liu","doi":"10.1088/1752-7163/ad67fd","DOIUrl":"10.1088/1752-7163/ad67fd","url":null,"abstract":"<p><p>Tetrachloroethylene (PCE) is a widely utilized volatile chemical in industrial applications, including dry cleaning and metal degreasing. Exposure to PCE potentially presents a significant health risk to workers as well as communities near contamination sites. Adverse health effects arise not only from PCE, but also from PCE degradation products, such as trichloroethylene (TCE) and vinyl chloride (VC). PCE, TCE, and VC can contaminate water, soil, and air, leading to exposure through multiple pathways, including inhalation, ingestion, and dermal contact. This study focused on a community setting in Martinsville, Indiana, a working-class Midwestern community in the United States, where extensive PCE contamination has occurred due to multiple contamination sites (referring to 'plumes'), including a Superfund site. Utilizing proton transfer reaction time-of-flight mass spectrometry (PTR-TOF-MS), PCE, TCE, and VC concentrations were measured in the exhaled breath of 73 residents from both within and outside the plume areas. PCE was detected in 66 samples, TCE in 26 samples, and VC in 68 samples. Our results revealed a significant positive correlation between the concentrations of these compounds in exhaled breath and indoor air (Pearson correlation coefficients: PCE = 0.75, TCE = 0.71, and VC = 0.89). This study confirms the presence of PCE and its degradation products in exhaled breath in a community exposure investigation, demonstrating the potential of using exhaled breath analysis in monitoring exposure to environmental contaminants. This study showed the feasibility of utilizing PTR-TOF-MS in community investigations to assess exposure to PCE and its degradation products by measuring these compounds in exhaled breath and indoor air.</p>","PeriodicalId":15306,"journal":{"name":"Journal of breath research","volume":" ","pages":""},"PeriodicalIF":3.7,"publicationDate":"2024-08-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141766134","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Volatile organic compounds in exhaled breath: a promising approach for accurate differentiation of lung adenocarcinoma and squamous cell carcinoma.","authors":"Xian Li, Lin Shi, Yijing Long, Chunyan Wang, Cheng Qian, Wenwen Li, Yonghui Tian, Yixiang Duan","doi":"10.1088/1752-7163/ad6474","DOIUrl":"10.1088/1752-7163/ad6474","url":null,"abstract":"<p><p>Lung cancer subtyping, particularly differentiating adenocarcinoma (ADC) from squamous cell carcinoma (SCC), is paramount for clinicians to develop effective treatment strategies. In this study, we aimed: (i) to discover volatile organic compound (VOC) biomarkers for precise diagnosis of ADC and SCC, (ii) to investigated the impact of risk factors on ADC and SCC prediction, and (iii) to explore the metabolic pathways of VOC biomarkers. Exhaled breath samples from patients with ADC (<i>n</i>= 149) and SCC (<i>n</i>= 94) were analyzed by gas chromatography-mass spectrometry. Both multivariate and univariate statistical analysis method were employed to identify VOC biomarkers. Support vector machine (SVM) prediction models were developed and validated based on these VOC biomarkers. The impact of risk factors on ADC and SCC prediction was investigated. A panel of 13 VOCs was found to differ significantly between ADC and SCC. Utilizing the SVM algorithm, the VOC biomarkers achieved a specificity of 90.48%, a sensitivity of 83.50%, and an area under the curve (AUC) value of 0.958 on the training set. On the validation set, these VOC biomarkers attained a predictive power of 85.71% for sensitivity and 73.08% for specificity, along with an AUC value of 0.875. Clinical risk factors exhibit certain predictive power on ADC and SCC prediction. Integrating these risk factors into the prediction model based on VOC biomarkers can enhance its predictive accuracy. This work indicates that exhaled breath holds the potential to precisely detect ADCs and SCCs. Considering clinical risk factors is essential when differentiating between these two subtypes.</p>","PeriodicalId":15306,"journal":{"name":"Journal of breath research","volume":" ","pages":""},"PeriodicalIF":3.7,"publicationDate":"2024-08-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141633647","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}