Journal of breath research最新文献

Pulmonary function is usually assessed by measuring Vital Capacity (VC) using equipment such as a spirometer or ventilometer, but these are not always available to the population, as they are relatively expensive tests, difficult to transport and require trained professionals. However, the single breath counting technique (SBCT) appears as a possible alternative to respiratory function tests, to help in the pathophysiological understanding of lung diseases. The objective is to verify the applicability of the SBCT as a parameter for evaluating VC. This is a systematic review registered in the International Prospective Register of Systematic Reviews (CRD42023383706) and used for PubMed^®, Scientific Electronic Library Online, LILACS, EMBASE, and Web of Science databases of articles published until January 2023. Methodological quality regarding the risk of bias was assessed using Quality Assessment of Diagnostic Accuracy Studies-2 and National Institutes of Health tools. Eleven of a total of 574 studies were included, of these, nine showed a correlation between VC and SBCT (weak in healthy, moderate in neuromuscular and strong in hospitalized patients). One study of hospitalized patients accurately identified a count value of 21 for a VC of 20 ml kg^-1(Sensitivity = 94% and Specificity = 77%), and another estimated a count lower than 41 for a VC below 80% of predicted in patients with neuromuscular dystrophy (Sensitivity = 89% and Specificity = 62%), and another showed good intra and inter-examiner reproducibility in young, adult, and elderly populations. A meta-analysis of three studies showed a moderate correlation in subjects with neuromuscular diseases (r= 0.62, 95% CI = 0.52-0.71,p< 0.01). A high risk of bias was identified regarding the justification of the sample size and blinding of the evaluators. SBCT has been presented as an alternative to assess VC in the absence of specific equipment. There is a clear relationship between SBCT and VC, especially in neuromuscular and hospitalized individuals. New validation studies conducted with greater control of potential bias risks are necessary.

A 23-subject feasibility study is reported to assess how UV absorbance measurements on exhaled breath samples collected from silicon microreactors can be used to detect COVID-19. The silicon microreactor technology chemoselectively preconcentrates exhaled carbonyl volatile organic compounds and subsequent methanol elution provides samples for analysis. The underlying scientific rationale that viral infection will induce an increase in exhaled carbonyls appears to be supported by the results of the feasibility study. The data indicate statistically significant differences in measured UV absorbance values between healthy and symptomatic COVID-19 positive subjects in the wavelength range from 235 nm to 305 nm. Factors such as subject age were noted as potential confounding variables.

Exhaled breath contains numerous volatile organic compounds (VOCs) known to be related to lung disease like asthma. Its collection is non-invasive, simple to perform and therefore an attractive method for the use even in young children. We analysed breath in children of the multicenter All Age Asthma Cohort (ALLIANCE) to evaluate if 'breathomics' have the potential to phenotype patients with asthma and wheeze, and to identify extrinsic risk factors for underlying disease mechanisms. A breath sample was collected from 142 children (asthma: 51, pre-school wheezers: 55, healthy controls: 36) and analysed using gas chromatography-mass spectrometry (GC/MS). Children were diagnosed according to Global Initiative for Asthma guidelines and comprehensively examined each year over up to seven years. Forty children repeated the breath collection after 24 or 48 months. Most breath VOCs differing between groups reflect the exposome of the children. We observed lower levels of lifestyle-related VOCs and higher levels of the environmental pollutants, especially naphthalene, in children with asthma or wheeze. Naphthalene was also higher in symptomatic patients and in wheezers with recent inhaled corticosteroid use. No relationships with lung function or TH2 inflammation were detected. Increased levels of naphthalene in asthmatics and wheezers and the relationship to disease severity could indicate a role of environmental or indoor air pollution for the development or progress of asthma. Breath VOCs might help to elucidate the role of the exposome for the development of asthma. The study was registered at ClinicalTrials.gov (NCT02496468).

Human studies provide valuable information on components or analytes recovered from exhaled breath, but there are limitations due to inter-individual and intra-individual variation. Future development and implementation of breath tests based on aerosol analysis require a clear understanding of how human factors interact with device geometry to influence particle transport and deposition. The computational fluid and particle dynamics (CFPD) algorithm combines (i) the Eulerian approach to fluid dynamics and (ii) the Lagrangian approach to single particle transport and deposition to predict how particles are carried in fluids and deposited on surfaces. In this work, we developed a 3D multiscale CFPD model to provide insight into human factors that could be important to control or measure during sampling. We designed the model to characterize the local transport, spatial distribution, and deposition of polydisperse particles in a single impaction filter of a commercial aerosol collection device. We highlight the use of decoupling numerical strategies to simultaneously quantify the influence of filter geometry, fluid flowrate, and particle size. Our numerical models showed the remarkable effect of flowrate on aerosol dynamics. Specifically, aerosol mass deposition, spatial distribution, and deposition mechanisms inside the filter. This work as well as future studies on the effect of filter geometry and human factors on aerosol collection will guide the development, standardization, and validation of breath sampling protocols for current and emerging breath tests for forensic and clinical applications.

Nitric oxide has different roles in asthma as both an endogenous modulator of airway function and a pro-inflammatory mediator. Fractional exhaled nitric oxide (FeNO) is a reliable, quantitative, non-invasive, simple, and safe biomarker for assessing airways inflammation in asthma. Previous genome-wide and genetic association studies have shown that different genes and single nucleotide polymorphisms (SNPs) are linked to FeNO. We aimed at identifying SNPs in candidate genes or gene regions that are associated with FeNO in asthma. We evaluated 264 asthma cases (median age 42.8 years, female 47.7%) who had been identified in the general adult population within the Gene Environment Interactions in Respiratory Diseases survey in Verona (Italy; 2008-2010). Two hundred and twenty-one tag-SNPs, which are representative of 50 candidate genes, were genotyped by a custom GoldenGate Genotyping Assay. A two-step association analysis was performed without assuming ana priorigenetic model: step (1) a machine learning technique [gradient boosting machine (GBM)] was used to select the 15 SNPs with the highest variable importance measure; step (2) the GBM-selected SNPs were jointly tested in a linear regression model with natural log-transformed FeNO as the normally distributed outcome and with age, sex, and the SNPs as covariates. We replicated our results within an independent sample of 296 patients from the European Community Respiratory Health Survey III. We found that SNP rs987314 in family with sequence similarity 13 member A (FAM13A) and SNP rs3218258 in interleukin 2 receptor subunit beta (IL2RB) gene regions are significantly associated with FeNO in adult subjects with asthma. These genes are involved in different mechanisms that affect smooth muscle constriction and endothelial barrier function responses (FAM13A), or in immune response processes (IL2RB). Our findings contribute to the current knowledge on FeNO in asthma by identifying two novel SNPs associated with this biomarker of airways inflammation.

It can be a clinical challenge to distinguish inflammation from infection in critically ill patients. Therefore, valid and conclusive surrogate markers for infections are desired. Nitric oxide (NO) might be that marker since concentrations of exhaled NO have shown to change in the presence of various diseases. This observational, prospective, single-center feasibility study aimed to investigate if fractional exhaled NO (FeNO) can be measured in intubated patients with or without infection, pneumonia and septic shock in a standardized, reliable setting. 20 intubated patients in the intensive care unit (ICU) were included for analysis. FeNO mean values were measured in the endotracheal tube via the suction channel using a chemiluminescence based analyzer. We developed a pragmatic method to measure FeNO repeatedly and reliably in intubated patients using a chemiluminescence based analyzer. We found a median of 0.98 (0.59-1.44) FeNO mean (ppb) in exhaled breath from all 20 intubated patient. Intubated patient with suspected infection had a significantly lower median FeNO mean compared with the intubated patients without suspected infection. Similarly did patients with septic shock demonstrate a significantly lower median FeNO mean than without septic shock. We found no statistical difference in median FeNO mean for intubated patients with pneumonia. It was feasible to measure FeNO in intubated patients in the ICU. Our results indicate decreased levels of FeNO in infected intubated patients in the ICU. The study was not powered to provide firm conclusions, so larger trials are needed to confirm the results and to prove FeNO as a useful biomarker for distinguishment between infection and inflammation in the ICU.

Pleural mesothelioma (PM) is an aggressive cancer of the serosal lining of the thoracic cavity, predominantly caused by asbestos exposure. Due to nonspecific symptoms, PM is characterized by an advanced-stage diagnosis, resulting in a dismal prognosis. However, early diagnosis improves patient outcome. Currently, no diagnostic biomarkers or screening tools are available. Therefore, exhaled breath was explored as this can easily be obtained and contains volatile organic compounds, which are considered biomarkers for multiple (patho)physiological processes. A breath test, which differentiates asbestos-exposed (AEx) individuals from PM patients with 87% accuracy, was developed. However, before being implemented as a screening tool, the clinical utility of the test must be determined. Occupational AEx individuals underwent annual breath tests using multicapillary column/ion mobility spectrometry. A baseline breath test was taken and their individual risk of PM was estimated. PM patients were included as controls. In total, 112 AEx individuals and six PM patients were included in the first of four screening rounds. All six PM patients were correctly classified as having mesothelioma (100% sensitivity) and out of 112 AEx individuals 78 were classified by the breath-based model as PM patients (30% specificity). Given the large false positive outcome, the breath test will be repeated annually for three more consecutive years to adhere to the 'test, re-test' principle and improve the false positivity rate. A low-dose computed tomography scan in those with two consecutive positive tests will correlate test positives with radiological findings and the possible growth of a pleural tumor. Finally, the evaluation of the clinical value of a breath-based prediction model may lead to the initiation of a screening program for early detection of PM in Aex individuals, which is currently lacking. This clinical study received approval from the Antwerp University Hospital Ethics Committee (B300201837007).

Therapeutic drug monitoring (TDM) of medications with a narrow therapeutic window is a common clinical practice to minimize toxic effects and maximize clinical outcomes. Routine analyses rely on the quantification of systemic blood concentrations of drugs. Alternative matrices such as exhaled breath are appealing because of their inherent non-invasive nature. This is especially the case for pediatric patients. We have recently showcased the possibility of predicting systemic concentrations of valproic acid (VPA), an anti-seizure medication by real-time breath analysis in two real clinical settings. This approach, however, comes with the limitation of the patients having to physically exhale into the mass spectrometer. This restricts the possibility of sampling from patients not capable or available to exhale into the mass spectrometer located on the hospital premises. In this work, we developed an alternative method to overcome this limitation by collecting the breath samples in customized bags and subsequently analyzing them by secondary electrospray ionization coupled to high-resolution mass spectrometry (SESI-HRMS). A total ofn= 40 patients (mean ± SD, 11.5 ± 3.5 y.o.) diagnosed with epilepsy and taking VPA were included in this study. The patients underwent three measurements: (i) serum concentrations of total and free VPA, (ii) real-time breath analysis and (iii) off-line analysis of exhaled breath collected in bags. The agreement between the real-time and the off-line breath analysis methods was evaluated using Lin's concordance correlation coefficient (CCC). CCC was computed for ten mass spectral predictors of VPA concentrations. Lin's CCC was >0.6 for all VPA-associated features, except for two low-signal intensity isotopic peaks. Finally, free and total serum VPA concentrations were predicted by cross validating the off-line data set. Support vector machine algorithms provided the most accurate predictions with a root mean square error of cross validation of 29.0 ± 7.4 mg l^-1and 3.9 ± 1.4 mg l^-1for total and free VPA (mean ± SD), respectively. As a secondary analysis, we explored whether exhaled metabolites previously associated with side-effects and response to medication could be rendered by the off-line analysis method. We found that five features associated with side effects showed a CCC > 0.6, whereas none of the drug response-associated peaks reached this cut-off. We conclude that the clinically relevant free fraction of VPA can be predicted by this combination of off-line breath collection with rapid SESI-HRMS analysis. This opens new possibilities for breath based TDM in clinical settings.

The nasal dominance (ND) determination is crucial for nasal synchronized ventilator, optimum nasal drug delivery, identifying brain hemispheric dominance, nasal airway obstruction surgery, mindfulness breathing, and for possible markers of a conscious state. Given these wider applications of ND, it is interesting to understand the patterns of ND with varying temperature and respiration rates. In this paper, we propose a method which measures peak-to-peak temperature oscillations (difference between end-expiratory and end-inspiratory temperature) for the left and right nostrils during nasal breathing. These nostril-specific temperature oscillations are further used to calculate the nasal dominance index (NDI), nasal laterality ratio (NLR), inter-nostril correlation, and mean of peak-to-peak temperature oscillation for inspiratory and expiratory phase at (1) different ambient temperatures of 18 °C, 28 °C, and 38 °C and (2) at three different respiration rate of 6 bpm, 12 bpm, and 18 bpm. The peak-to-peak temperature (T_pp) oscillation range (averaged across participants;n= 8) for the left and right nostril were 3.80 ± 0.57 °C and 2.34 ± 0.61 °C, 2.03 ± 0.20 °C and 1.40 ± 0.26 °C, and 0.20 ± 0.02 °C and 0.29 ± 0.03 °C at the ambient temperature of 18 °C, 28 °C, and 38 °C respectively (averaged across participants and respiration rates). The NDI and NLR averaged across participants and three different respiration rates were 35.67 ± 5.53 and 2.03 ± 1.12; 8.36 ± 10.61 and 2.49 ± 3.69; and -25.04 ± 14.50 and 0.82 ± 0.54 at the ambient temperature of 18 °C, 28 °C, and 38 °C respectively. The Shapiro-Wilk test, and non-parametric Friedman test showed a significant effect of ambient temperature conditions on both NDI and NLR. No significant effect of respiration rate condition was observed on both NDI and NLR. The findings of the proposed study indicate the importance of ambient temperature while determining ND during the diagnosis of breathing disorders such as septum deviation, nasal polyps, nosebleeds, rhinitis, and nasal fractions, and in the intensive care unit for nasal synchronized ventilator.