Journal of breath research最新文献

Although pressurized metered dose inhaler (pMDI) education is a routine part of childhood asthma management and encouraging 'optimal breathing patterns' (i.e. slowly, deeply, completely, and with a mouth seal on the mouthpiece) is an integral part of recommended pMDI education, there is currently no quantifiable way to determine if a child is inhaling their medication correctly or optimally through a valved holding chamber (VHC). The TipsHaler™ (tVHC) is a prototype VHC device that measures inspiratory time, flow, and volume without changing the properties of the medication aerosol. The measurementsin vivorecorded by the tVHC can be downloaded and transferred to a spontaneous breathing lung model to simulate the inhalational patternsin vitroand also determine the deposition of inhaled aerosol mass with each pattern. We hypothesized that pediatric patients' inhalational patterns when using a pMDI would improve after active coaching via tVHC. This would increase the pulmonary deposition of inhaled aerosols in anin vitromodel. To test this hypothesis, we conducted a single-site, prospective, pilot, pre-and-post intervention study paired with a bedside-to-bench experiment. Healthy, inhaler-naïve subjects used a placebo inhaler in conjunction with the tVHC before and after coaching and recorded inspiratory parameters. These recordings were then implemented into a spontaneous breathing lung model during albuterol MDI delivery, and pulmonary deposition of albuterol was quantified. In this pilot study, active coaching resulted in a statistically significant increase in inspiratory time (n= 8,p= 0.0344, 95%CI: 0.082 to ∞). tVHC recorded inspiratory parameters obtained from patients were successfully implemented in thein vitromodel, which demonstrated that both inspiratory time (n= 8,r= 0.78,p <0.001, 95%CI: 0.47-0.92) and volume (n= 8,r= 0.58,p =0.0186, 95%CI: 0.15-0.85) strongly correlate with pulmonary deposition of inhaled drugs.

Rapid testing is essential to fighting pandemics such as coronavirus disease 2019 (COVID-19), the disease caused by the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). Exhaled human breath contains multiple volatile molecules providing powerful potential for non-invasive diagnosis of diverse medical conditions. We investigated breath detection of SARS-CoV-2 infection using cavity-enhanced direct frequency comb spectroscopy (CE-DFCS), a state-of-the-art laser spectroscopic technique capable of a real-time massive collection of broadband molecular absorption features at ro-vibrational quantum state resolution and at parts-per-trillion volume detection sensitivity. Using a total of 170 individual breath samples (83 positive and 87 negative with SARS-CoV-2 based on reverse transcription polymerase chain reaction tests), we report excellent discrimination capability for SARS-CoV-2 infection with an area under the receiver-operating-characteristics curve of 0.849(4). Our results support the development of CE-DFCS as an alternative, rapid, non-invasive test for COVID-19 and highlight its remarkable potential for optical diagnoses of diverse biological conditions and disease states.

Lung cancer is one of the common malignancies with high mortality rate and a poor prognosis. Most lung cancer cases are diagnosed at an advanced stage either due to limited resources of infrastructure, trained human resources, or delay in clinical suspicion. Low-dose computed tomography has emerged as a screening tool for lung cancer detection but this may not be a feasible option for most developing countries. Electronic nose is a unique non-invasive device that has been developed for lung cancer diagnosis and monitoring response by exhaled breath analysis of volatile organic compounds. The breath-print have been shown to differ not only among lung cancer and other respiratory diseases, but also between various types of lung cancer. Hence, we postulate that the breath-print analysis by electronic nose could be a potential biomarker for the early detection of lung cancer along with monitoring treatment response in a resource-limited setting. In this review, we have consolidated the current published literature suggesting the use of an electronic nose in the diagnosis and monitoring treatment response of lung cancer.

Early, rapid and non-invasive diagnosis of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection is needed for the prevention and control of coronavirus disease 2019 (COVID-19). COVID-19 mainly affects the respiratory tract and lungs. Therefore, analysis of exhaled breath could be an alternative scalable method for reliable SARS-CoV-2 screening. In the current study, an experimental protocol using an electronic-nose ('e-nose') for attempting to identify a specific respiratory imprint in COVID-19 patients was optimized. Thus the analytical performances of the Cyranose^®, a commercial e-nose device, were characterized under various controlled conditions. In addition, the effect of various experimental conditions on its sensor array response was assessed, including relative humidity, sampling time and flow rate, aiming to select the optimal parameters. A statistical data analysis was applied to e-nose sensor response using common statistical analysis algorithms in an attempt to demonstrate the possibility to detect the presence of low concentrations of spiked acetone and nonanal in the breath samples of a healthy volunteer. Cyranose^®reveals a possible detection of low concentrations of these two compounds, in particular of 25 ppm nonanal, a possible marker of SARS-CoV-2 in the breath.

Exhaled breath temperature (EBT) is a known biomarker of inflammation and airways blood flow. As opposed to previous studies, we were able to measure temperature of separate fractions of exhaled breath (fEBT) (those from the peripheral and central airways). The aim was to validate the fEBT measurement method to determine the reference values and the influence of endogenous and exogenous factors on fEBT in healthy subjects. This cross-sectional study included 55 healthy adults in whom fEBT was repeatedly measured, two days in a row, using a FractAir^®device. Also, basal metabolic rate, level of physical activity, distance from the main road, outdoor and ambient temperature, air pressure and humidity, haematology and inflammation markers, lung function, cumulative EBT and body temperature at characteristic points on the body were measured. The results showed that fEBT from central airways was lower compared to fEBT from the periphery and that fEBTs were not related to body temperature (p> 0.05 for all). We also showed repeatability of fEBT measurements for two consecutive days. All EBT fractions correlated significantly with ambient temperature (<0.01). No associations of fEBT with other personal and external factors were found using multivariate analysis. At room temperature of 22 °C, the physiological temperature values of the first fraction were 23.481 ± 3.150 °C, the second fraction 26.114 ± 4.024 °C and the third fraction 28.216 ± 3.321 °C. The proposed reference values represent the first part of validation of fEBT as the method for the use in clinical practice.

Children with cystic fibrosis (CF) suffer from chronic inflammation and recurrent pulmonary exacerbations (PEs). We aimed to test whether a specific miRNA could be associated with the occurrence of PE. We sequenced extracellular vesicle (EV)-derived miRNA in sputum (n= 20), exhaled breath condensate (EBC) (n= 11), and serum (n= 8) samples from pediatric patients during PE and the stable stage of CF. Four miRNAs: let-7c, miR-16, miR-25-3p and miR-146a, have been selected for validation in a larger group with reverse transcription quantitative real-time PCR (RT-qPCR) in sputum and serum, or droplet digital PCR (ddPCR) in EBC. Next-generation sequencing (NGS) differential expression analysis was done in Base Space, and the correlation between miRNAs expression and clinical data was calculated with Statistica. Functional annotation of selected miRNAs and their potential target genes was performed with miRDip and DAVID software. There were no differences in miRNA expression between stable and exacerbation in sputum and in serum. Validation of four selected miRNAs showed significant downregulation of miR-146a in serum. A panel of all four miRNAs (peripherally) was the best predictive model of exacerbation (p< 0.001, AUC = 0.96). Expression of airway miR-25-3p improved the diagnostic value of FEV1% pred and FVC% pred, while peripheral miR-146a improved the predictive model of C-reactive protein and neutrophilia.In silicoanalysis revealed a potential role for selected miRNAs in regulating processes associated with inflammation and tissue remodeling. We demonstrated that EVs contained in peripheral blood as well as local biomaterials can act as carriers for miRNAs with the diagnostic potential of predicting exacerbation in pediatric CF.

Early disease detection is often correlated with a reduction in mortality rate and improved prognosis. Currently, techniques like biopsy and imaging that are used to screen chronic diseases are invasive, costly or inaccessible to a large population. Thus, a non-invasive disease screening technology is the need of the hour. Existing non-invasive methods like gas chromatography-mass spectrometry, selected-ion flow-tube mass spectrometry, and proton transfer reaction-mass-spectrometry are expensive. These techniques necessitate experienced operators, making them unsuitable for a large population. Various non-invasive sources are available for disease detection, of which exhaled breath is preferred as it contains different volatile organic compounds (VOCs) that reflect the biochemical reactions in the human body. Disease screening by exhaled breath VOC analysis can revolutionize the healthcare industry. This review focuses on exhaled breath VOC biomarkers for screening various diseases with a particular emphasis on liver diseases and head and neck cancer as examples of diseases related to metabolic disorders and diseases unrelated to metabolic disorders, respectively. Single sensor and sensor array-based (Electronic Nose) approaches for exhaled breath VOC detection are briefly described, along with the machine learning techniques used for pattern recognition.

A small and lightweight optical sensor head prototype with a disposable airway adapter for continuous mainstream monitoring of oxygen at high sampling rate is designed and tested on an optical benchtop. In terms of its size and functionality, the sensor head design is similar to current capnography systems from leading medical equipment manufacturers, and it has been designed within constraints of potential applications in direct breath oxygen monitoring that require direct interaction with the gas inside a breathing tube. The measurement precision of 0.1% O₂with a 10 ms integration time are well within the performance required for breath O₂monitoring applications.