Research aim:

To develop and demonstrate a novel instrument integrating thermal desorption (TD) with selected ion flow tube mass spectrometry (SIFT-MS) for analysing volatile organic compounds (VOCs) in human breath, particularly for large-scale multicentre clinical studies.

Main findings:

Integration of SIFT-MS and TD for practical use: The combination of SIFT-MS and TD enables rapid analysis of VOCs while also facilitating the collection of breath samples across multiple locations, making the instrument suitable for use in clinical practice.

Development of a targeted analytical method: A validated method was created to analyse 21 VOCs with diverse chemical classes, chosen for their clinical and biological relevance.

Successful validation across laboratories: The method was validated in two independent laboratories using both calibration standards and real breath samples from healthy volunteers.

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Research aim:

To develop an improved methodology for global volatolomic profiling using urinary samples for non-invasive disease detection and monitoring.

Main findings:

Reduction in required urine volume and clinical applicability: The required urine volume was reduced by five times (from 2 mL to 0.4 mL), and the methodology was successfully applied to a pancreatic ductal adenocarcinoma cohort, confirming previous findings and discovering additional VOCs with diagnostic potential.

Improved VOC extraction method: A multiphase sorbent was used for VOC extraction, achieving wide coverage and significantly increasing the number of monitored VOCs compared to the previously reported single-sorbent method.

Enhanced biomarker discovery: Multidimensional gas chromatography (GC×GC) further improved biomarker discovery, and data analysis was simplified using a tile-based approach.

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Research aim:

To develop and optimise a complete pipeline for untargeted urinary volatolomic profiling, addressing barriers to wider clinical adoption, and demonstrating its potential for non-invasive disease detection and biomarker discovery.

Main findings:

Clinical applicability and biomarker discovery: The pipeline was successfully applied to a clinical cohort of pancreatic ductal adenocarcinoma patients, identifying four urinary biomarkers (2-pentanone, hexanal, 3-hexanone, and p-cymene) that can distinguish pancreatic ductal adenocarcinoma from control subjects, demonstrating the pipeline’s clinical utility and potential for future biomarker studies.

Optimised extraction and analysis techniques: A novel HiSorb sorptive extraction method was developed, offering high analytical performance and throughput, combined with complementary chromatographic methods and time-of-flight mass spectrometry for broader VOC coverage.

Data pre-processing and quality control: A data pre-processing strategy was established, including internal standard normalisation, batch correction, and strict quality control measures to remove nonreproducible or contaminated features, ensuring high-quality data acquisition.

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Research aim:

To develop and evaluate a breath test based on detecting volatile organic compounds (VOCs) for detecting colorectal cancer, aimed at serving as a non-invasive triage tool for identifying patients at risk.

Main findings:

Multicentre feasibility and quality control: The study demonstrated the feasibility of multicentre breath collection and centralised analysis, with robust quality control measures and the selection of endogenous VOCs for model development, further supporting the potential for the breath test as a triage tool in colorectal cancer screening.

Diagnostic model for CRC detection: A breath test model based on 14 endogenous VOCs and body mass index successfully predicted colorectal cancer with an area under the ROC curve (AUC) of 0.87, achieving a sensitivity of 79%, specificity of 86%, and a negative predictive value (NPV) of 97%.

High performance in symptomatic patients: In a subset of symptomatic patients, the model showed even better performance, with an AUC of 0.91, sensitivity of 83%, specificity of 88%, and NPV of 96%, suggesting the breath test’s potential for accurately identifying colorectal cancer in those presenting with symptoms.

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Research aim:

To provide a standardised protocol for online and offline breath analysis using selected ion flow tube mass spectrometry (SIFT-MS) for non-invasive disease detection and monitoring.

Main findings:

Custom breath collection bags: A procedure for making custom breath collection bags was outlined, facilitating the standardised collection of breath samples, which is essential for reproducibility and broader application of breath analysis in clinical research.

Comprehensive workflow for breath analysis: A detailed protocol was developed for the analysis of 50 human breath samples in less than 3 hours, leveraging the advantages of SIFT-MS for real-time results and direct compound quantification without calibration curves.

Targeted analysis of disease-specific VOCs: The protocol includes methods for analysing key disease-specific volatile organic compounds, such as short-chain fatty acids, aldehydes, phenols, alcohols, and alkanes, providing insight into their potential for disease detection.

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Research aim:

To investigate the mechanisms behind the accumulation of volatile aldehydes in oesophageal adenocarcinoma (EAC) and explore their potential for improving early diagnosis and understanding their genotoxicity.

Main findings:

Therapeutic implications of aldehyde accumulation: Increased levels of decanal in EAC tissues were linked to reduced ALDH3A2 expression and TP53 deletion, while metformin, an aldehyde scavenger, was shown to reduce aldehyde-induced genotoxicity, suggesting a potential therapeutic approach.

Weak aldehyde detoxification in EAC: The study revealed that weak aldehyde detoxification in EAC leads to the accumulation of endogenous aldehydes, which contributes to the formation of genotoxic DNA-adducts.

Enrichment of aldehyde groups in EAC tissue: Two groups of aldehydes; short-chain alkanals and medium-chain alkanals, including decanal, were found to be significantly enriched in EAC biopsies and adjacent tissue, with decanal levels correlating with adverse clinical features.

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Research aim:

To develop a machine learning-based algorithm (MSHub) for auto-deconvolution of gas chromatography-mass spectrometry (GC-MS) data, facilitating reproducible, high-quality spectral analysis and molecular networking of GC-MS data within the GNPS platform.

Main findings:

Enhanced molecular networking and annotation: MSHub’s integration with GNPS enables global molecular networking and data co-analysis, allowing for better annotation at the molecular family level and providing a broader understanding of structural relationships in mass spectrometry data.

Automated spectral deconvolution with MSHub: MSHub utilises unsupervised non-negative matrix factorisation and Fourier transformation to automate GC-MS spectral deconvolution, significantly improving reproducibility and spectral quality without manual parameter setting.

Scalability and efficiency: MSHub scales efficiently with large datasets, processing files in an out-of-core manner to avoid memory overload, allowing for repository-scale operations and faster deconvolution as the number of files increases.

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Research aim:
To determine whether volatile organic compound (VOC) measurements could distinguish viral from bacterial infections in patients with chronic obstructive pulmonary disease (COPD) during acute exacerbations.

Main findings:

No induction by bacterial infections: The VOC signature was not induced by bacterial infections, highlighting its potential as a specific biomarker for viral infection and distinguishing viral from bacterial causes of exacerbations in COPD.

Viral infection VOC signature identified: A specific VOC signature, including decane and other long-chain alkanes, was induced during rhinovirus infection in airway epithelial cells. This signature was also observed in the exhaled breath of healthy subjects experimentally challenged with rhinovirus and COPD patients experiencing viral exacerbations.

Correlation with immune response and exacerbation severity: The VOC signature correlated with the magnitude of antiviral immune responses, viral burden and the severity of exacerbations, suggesting a link between these compounds and the viral infection process.

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Research aim:
To assess the relationship between two online mass spectrometry techniques, selected ion flow tube mass spectrometry (SIFT-MS) and proton-transfer-reaction time-of-flight mass spectrometry (PTR-ToF-MS), in the quantification of target breath metabolites.

Main findings:

Agreement in VOC detection and cross-platform compatibility: The majority of tested metabolites showed a high degree of agreement between the two MS techniques, with most compounds falling within 95% of the limits of agreement in Bland-Altman analysis, demonstrating strong linear regression and compatibility for data transfer between platforms.

Strong correlation between SIFT-MS and PTR-ToF-MS: The concentration of abundant breath metabolites, acetone and isoprene, showed a strong positive linear correlation between both mass spectrometry techniques (r = 0.97, r = 0.89, respectively; p < 0.001).

High correlation with thermal desorption tube method: Strong positive correlations were also observed between the direct injection and thermal desorption (TD) tube sampling methods for both acetone and isoprene (r = 0.97, r = 0.92, respectively; p < 0.001).

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Research aim:
To examine the feasibility and acceptability of breath research in primary care.

Main findings:

Effective collection and analysis of breath samples: 95% of breath samples collected across multiple sites met the quality criteria for mass spectrometry analysis, highlighting the effectiveness of the methodology for sample collection, handling, and analysis.

Feasibility of patient enrolment and breath testing: Both ‘single practice’ and ‘hub and spoke’ recruitment models were effective for patient enrolment, with an average of 5.3 and 4.3 patients enrolled per day, respectively. SMS messaging combined with the ‘hub and spoke’ model was the most efficient method of patient accrual.

High acceptability of the test: Both patients and general practitioners (GPs) demonstrated high acceptability of the breath test and the testing process, indicating that the approach is well-received in primary care settings.

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Research aim:
To evaluate the potential of combining faecal immunochemical tests (FIT) with volatile organic compounds (VOC) analysis as a triage tool for colorectal cancer detection in patients with lower gastrointestinal symptoms.

Main findings:

Need for further prospective studies and validation: The results of the meta-analyses should be viewed optimistically but cautiously, as they were based on unpaired FIT and VOC tests. There is a need for large-scale prospective clinical studies to validate the effectiveness of combined FIT and VOC tests, especially for detecting early-stage colorectal cancer in FIT-negative patients.

Combination of FIT and VOCs may reduce missed cancers: The meta-analyses concluded that combining FIT and VOC tests could potentially be a more effective triage tool for colorectal cancer detection compared to FIT alone. Testing FIT-negative patients for VOCs could reduce the number of missed cancer cases.

Challenges with sample collection and variability: Caution was advised due to significant variability in the VOC data, resulting from the inclusion of multiple sample matrices (breath, urine, faeces) analysed using different instruments. The lack of standardisation in sample collection, transport, and VOC analysis also contributed to this variability.

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Research aim:
To summarise the published literature on cancer-associated urinary volatile organic compounds (VOCs) and evaluate their potential as biomarkers for early cancer detection.

Main findings:

Study design limitations affecting consistency: The heterogeneity in study design, methodological approaches, and reporting quality led to inconsistencies between studies. These limitations need to be addressed to improve the reliability and reproducibility of urinary VOC analysis for cancer diagnosis in future research.

Distinct VOC profiles for cancer types: The review identified 48 urinary VOCs from 13 studies involving 1266 participants. These VOCs belonged to 11 chemical classes and exhibited high diagnostic performance. The VOC profiles were distinctive for each cancer subtype, with limited cross-over between them, suggesting the potential for specific biomarkers for different cancers.

Promising diagnostic performance for various cancers: The studies covered five cancer subtypes; prostate cancer, gastrointestinal cancer, leukaemia/lymphoma, lung cancer, and bladder cancer, demonstrating that urinary VOCs can offer a non-invasive diagnostic method with promising performance for cancer detection.

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Research aim:
To assess whether desorption electrospray ionisation mass spectrometry imaging (DESI-MSI) can objectively identify primary oesophageal adenocarcinoma and unveil mechanisms of phospholipidomic reprogramming in cancer development.

Main findings:

High discrimination for oesophageal adenocarcinoma using DESI-MSI: Multivariate models derived from phospholipid profiles of 117 patients were highly effective in discriminating oesophageal adenocarcinoma, achieving an area under the curve (AUC) of 0.97 in discovery and 1.0 in validation cohorts.

Enrichment of polyunsaturated phosphatidylglycerols in oesophageal adenocarcinoma: Oesophageal adenocarcinoma samples exhibited a marked enrichment of polyunsaturated phosphatidylglycerols with longer acyl chains, with a stepwise increase in premalignant tissues, indicating a link between lipid metabolism and cancer progression.

Link between de novo lipogenesis and phospholipidome reprogramming: Silencing the carbon switch enzyme ACLY in oesophageal adenocarcinoma cells shortened glycerophospholipid chains, demonstrating a mechanistic connection between fatty acid and glycerophospholipid synthesis pathways, influencing the phospholipidomic landscape in cancer.

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Research aim:
To assess the impact of oral cleansing strategies on exhaled volatile organic compound (VOC) levels and provide standardised practices for breath sampling in disease detection.

Main findings:

Effect of water rinse on VOC levels: Oral cleansing with water significantly reduced the concentrations of volatile fatty acids and alcohols (e.g., butanoic acid, pentanoic acid, ethanol), suggesting that water rinsing is effective in minimising oral contamination of VOCs.

Impact of flavoured oral products on VOCs: Toothbrushing and alcohol-free mouthwash increased levels of aldehydes and phenols (e.g., acetaldehyde, menthone, p-cresol), likely caused by flavoured ingredients in these products, which may interfere with VOC measurements.

No effect on sulphur compounds: No significant reductions in sulphur compound concentrations were observed following any of the oral cleansing interventions, indicating that these compounds may be less affected by oral cleansing procedures.

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Research aim:
To investigate the potential of propanal as a breath biomarker for the diagnosis and recurrence detection of colorectal cancer by analysing exhaled volatile organic compounds (VOCs) in colorectal cancer patients and evaluating its performance in a prospective cohort.

Main findings:

Propanal as a biomarker for colorectal cancer diagnosis: Multivariate analysis identified elevated levels of propanal in the breath of colorectal cancer patients compared to controls. At a threshold of 28 ppbv, propanal showed a sensitivity of 96% and specificity of 76% for colorectal cancer diagnosis.

Validation in a prospective cohort: In a separate cohort, propanal at a threshold of 28 ppbv showed a sensitivity of 83.3% and specificity of 84.7% for distinguishing colorectal cancer patients from controls.

Propanal levels and colorectal cancer recurrence: After surgery, propanal levels returned to control levels in patients with no recurrence, while levels increased significantly in patients with colorectal cancer recurrence. At the same threshold of 28 ppbv, the sensitivity for detecting recurrence was 71.4%, with a specificity of 90.9%.

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Research aim:
To determine the diagnostic accuracy of volatile organic compound (VOC) breath tests for cancer detection and to evaluate sources of methodological variability in test performance.

Main findings:

High diagnostic accuracy for cancer detection: The pooled analysis of 63 studies with 3554 patients revealed a mean area under the receiver operating characteristic curve of 0.94, indicating strong diagnostic accuracy for VOC breath tests in cancer detection.

Effective sensitivity and specificity: VOC breath tests demonstrated a sensitivity of 79% (95% CI, 77%-81%) and specificity of 89% (95% CI, 88%-90%), highlighting their potential for accurate cancer diagnosis.

Methodological variability influencing results: Variability in VOC test results was found to be influenced by factors such as breath collection methods, patient physiological conditions, test environment, and analysis techniques, which may affect the consistency and reliability of the tests.

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Research aim:
To investigate the production of volatile fatty acids (VFAs) in oesophagogastric cancer through ex vivo and in vivo analysis of various anatomical compartments and assess their potential as biomarkers for earlier cancer detection.

Main findings:

Elevated VFA levels in ex vivo cancer tissues: In ex vivo experiments, VFAs (acetic, butyric, pentanoic, and hexanoic acids) and acetone were found to be elevated in the headspace above oesophagogastric cancer tissues compared to control tissues, suggesting a potential biomarker for cancer detection.

Diagnostic potential of specific VFAs in vivo: Receiver-operating-characteristic analysis showed that butyric acid and pentanoic acid in gastric-endoluminal air from 25 cancer patients demonstrated significant differences from controls, with an area under the curve of 0.80 (95% CI: 0.65–0.93), indicating potential for cancer-specific breath tests.

VFA levels highest in gastric-endoluminal air: VFA concentrations were highest in oesophagogastric-endoluminal air compared to mixed- and bronchial-breath samples, highlighting the importance of analysing gastric-endoluminal air for accurate detection of oesophagogastric cancer.

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Research aim:
To develop a workflow for method development in Proton Transfer Reaction Time of Flight Mass Spectrometry (PTR-ToF-MS) for targeted volatile organic compound (VOC) analysis, focusing on identifying product ions, optimising quantification accuracy, and addressing fragmentation patterns.

Main findings:

Optimised experimental conditions: Experiments conducted under breath-relevant conditions (100% humid air) and varying electric field values (E/N = 48–144 Td) demonstrated that lower electric fields (<90 Td) reduced fragmentation and improved sensitivity and identification, particularly for aldehydes using NO+ ions, resulting in up to a 4-fold increase in sensitivity.

Development of a novel calibration methodology: A new calibration approach utilising diffusion tubes as gravimetric standards was introduced. This method allowed for accurate quantification, achieving experimental errors of 8% or lower between gravimetric measurements and calculated concentrations for the tested compounds.

Fragmentation pattern analysis of target compounds: The fragmentation patterns of 13 selected compounds (including aldehydes, fatty acids, and phenols) were determined, providing insight into how different conditions and ion types (H3O+, NO+, O2+) affect the detection and quantification of VOCs in PTR-ToF-MS.

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Research aim:
To develop and evaluate a platform combining thermal desorption (TD) and proton transfer reaction time-of-flight mass spectrometry (PTR-ToF-MS) for large-scale breath analysis in clinical practice, focusing on its application for detecting biomarkers of colorectal and oesophagogastric adenocarcinoma.

Main findings:

High sensitivity and recovery for VOCs: The TD-PTR-ToF-MS platform demonstrated excellent sensitivity, with limits of detection ranging from 0.2 to 0.9 ppbV and limits of quantification between 0.3 and 1.5 ppbV. Analytical recoveries from TD tubes were consistently 80% or higher, ensuring reliable detection of target volatile organic compounds (VOCs).

Strong linear response and precision: The system exhibited a linear response in the low- to mid-ppbV range for the seven oxygenated VOCs tested, with high correlation (R² = 0.98–0.99). The coefficients of variation were below 20%, indicating high reproducibility and precision for VOC quantification.

Platform scalability for clinical use: The platform demonstrated the ability to process nearly 100 TD tubes within 24 hours, highlighting its suitability for large-scale clinical studies and real-time breath analysis. This capability supports the potential for breath-based biomarkers to be implemented in routine clinical practice.

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Research aim:
To determine the diagnostic accuracy of a breath test for the detection of oesophagogastric cancer in a multicentre validation study.

Main findings:

Diagnostic accuracy of the 5-VOCs model: The 5-VOCs model used for breath analysis demonstrated good diagnostic accuracy, with an area under the curve of 0.85, indicating reliable identification of oesophagogastric cancer.

High sensitivity and specificity: The breath test achieved a sensitivity of 80% and a specificity of 81% for diagnosing oesophagogastric cancer, making it a promising non-invasive diagnostic tool for clinical use.

Patient demographics and cancer stage: The oesophagogastric cancer group was older (median age 68 years) and had a higher proportion of men (82%) compared to the control group. The majority of patients with oesophagogastric cancer had advanced tumour stages (T3/4) and nodal metastasis, highlighting the potential of this breath test for detecting more advanced cancer stages.

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Research aim:
To quantify differences in exhaled breath volatile organic compounds (VOCs) between patients with pancreatic cancer and those without cancer.

Main findings:

Identification of significant VOCs: A total of 66 VOCs were identified, with 12 showing significant differences between cancer and non-cancer groups in the development cohort, suggesting potential biomarkers for pancreatic cancer detection.

Diagnostic performance in the validation cohort: Analysis of the significant VOCs in the validation cohort showed an area under the curve (AUC) of 0.736 (sensitivity 81%, specificity 58%) for differentiating cancer from no cancer, and 0.744 (sensitivity 70%, specificity 74%) for distinguishing adenocarcinoma from non-cancer patients.

Potential for breath VOCs in pancreatic cancer detection: The study indicates that breath VOCs can differentiate patients with pancreatic cancer from those without cancer, highlighting the potential of breath analysis as a non-invasive diagnostic tool.

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Research aim:
To determine the role of exhaled ketones as non-invasive markers of nutritional status in patients undergoing surgical treatment for obesity.

Main findings:

Increase in exhaled acetone after dietary and surgical interventions: Exhaled acetone concentrations significantly increased following a pre-operative low carbohydrate diet (1396 ppb) and bariatric surgery (1693 ppb), compared to baseline concentrations (410 ppb, P < 0.0001), indicating its potential as a marker of metabolic changes.

Decrease in other ketones post-treatment: Concentrations of heptanone (6.5 vs. 4.1 vs. 1.4 ppb, P = 0.021) and octanone (3.0 vs. 1.4 vs. 0.7 ppb, P = 0.021) decreased significantly after the low carbohydrate diet and surgical interventions, highlighting changes in ketone profiles during treatment.

Correlation with body weight and metabolic markers: Exhaled acetone and octanone concentrations were correlated with excess body weight (ρ -0.264, P = 0.005), as well as with neutrophil and triglyceride levels (P < 0.05), suggesting their potential use in monitoring nutritional status and metabolic health in obese patients.

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Research aim:
To develop a rapid and sensitive ultra-performance liquid chromatography (UPLC) method for the analysis and quantification of nucleoside-adducts in DNA samples, addressing challenges in DNA damage quantification and providing a method for high-throughput analysis.

Main findings:

Development of a rapid, sensitive UPLC method: A six-minute UPLC method was developed, effectively separating seven candidate nucleoside-adducts from four unmodified nucleosides, with sensitivity to 1 adduct per 10^8 normal bases using 20 µg DNA input for most targets.

High accuracy and precision: The method demonstrated accuracy ranging from 81% to 119% across five tissue types and a relative standard deviation of 4–13%, confirming reliable quantification of nucleoside-adducts.

Fast and high-throughput processing: The method allowed for an analytical processing time of less than 8 hours, enabling the preparation and analysis of up to 96 samples per day. This throughput capability facilitates large-scale genotoxicity studies.

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Research aim:
To investigate the impact of different breath sampling parameters (fraction of exhaled breath, sample volume, and flow rate) on the detection of volatile organic compounds (VOCs) for the identification of biomarkers for oesophagogastric cancer.

Main findings:

Influence of sample volume on VOC detection: Increasing the breath sample volume improved the detection of VOCs, with larger volumes enhancing the levels of acetone and potential biomarkers for oesophagogastric cancer.

Effect of breath fraction and flow rate on VOCs: The fraction of exhaled breath (whole vs. lower airway) did not significantly impact the concentration of potential biomarkers for oesophagogastric cancer. However, the flow rate affected the recovery of certain VOCs, with higher flow rates reducing the recovery of phenols and acetone.

Optimisation of sampling parameters for clinical studies: The study concluded that for clinical studies targeting oesophagogastric cancer biomarkers, the optimal breath sampling parameters are a 500 ml sample volume of whole breath with a flow rate of 200 ml/min, along with a clean air supply to minimise contamination from ambient air.

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Research aim:
To investigate the variation in exhaled nitric oxide (NO) levels during oesophagectomy, with a focus on the response to one-lung ventilation (OLV) and the correlation with physiological variables and clinical outcomes.

Main findings:

Exhaled NO levels during two-lung ventilation: Baseline exhaled NO levels (2.9 ppb) increased after lung re-inflation (3.5 ppb) but decreased postoperatively at 2 hours (2.1 ppb) and 12 hours (2.2 ppb), indicating fluctuations in NO levels throughout the perioperative period.

Impact of OLV on exhaled NO: A significant reduction in exhaled NO levels was observed in the ventilated lung during OLV (1.6 ppb vs 3.1 ppb), whereas re-inflation of the collapsed lung resulted in higher NO levels (3.4 ppb vs 2.7 ppb), suggesting ventilation status influences NO concentrations.

Correlation with clinical variables: Exhaled NO levels showed significant correlation with systolic blood pressure and lactate (P < 0.007). Additionally, higher NO levels were observed in patients who developed postoperative respiratory complications, suggesting a potential link between NO and postoperative lung injury.

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