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Background: Multiple breath washout is a lung function test based on tidal breathing that assesses lung volume and ventilation distribution. The aim of this analysis was to use the Global Lung Function Initiative methodology to develop all-age reference equations for the multiple breath washout indices lung clearance index (LCI) and functional residual capacity (FRC)., Methods: Multiple breath washout data from healthy individuals were collated from sites. Data were re-analysed using the latest software versions. Reference equations were derived using the lambda-mu-sigma method using the generalised additive models of location shape and scale programme in R. The impact of equipment type, inert tracer gas and equipment dead space volume on the derived reference ranges were investigated., Results: Data from 23 sites (n=3647 test occasions) were submitted. Reference equations were derived from 1579 unique observations from participants between the ages of 2 and 81 years. Equipment type, inert tracer gas and equipment dead space volume did not significantly affect the prediction equations for either LCI or FRC. Reference equations for LCI include age as the only predictor, whereas sex-specific reference equations for FRC included height and age., Conclusions: Global Lung Function Initiative reference equations for multiple breath washout variables provide a standard for reporting and interpretation of LCI and FRC., Competing Interests: Conflict of interest: K.A. Ramsey reports support for the present study from ERS. S. Stanojevic reports grants from ATS, consultancy fees from Chiesi Farmaceuticals, payment or honoraria for lectures, presentations, manuscript writing or educational events from Vyaire Medical, participation on a data safety monitoring board or advisory board with Ndd Technologies, leadership roles with ATS (Pulmonary Function Testing Committee) and ERS (Global Lung Function Initiative), and the following financial (or non-financial) interests: Statistical Editor at Thorax, Editorial Board Member at European Respiratory Journal, and Junior Associate Editor at Canadian Journal of Respiratory, Critical Care and Sleep Medicine. C. Bowerman reports grants from Canadian Lung Association, support for attending meetings from Canadian Thoracic Society, and leadership role with Global Lung Function Initiative (Junior Executive). G.L. Hall reports support for the present study from ERS, as co-chair of the Global Lung Function Initiative. P. Latzin reports grants from Vertex and OM Pharma, payment or honoraria for lectures, presentations, manuscript writing or educational events from Vertex, Vifor and OM Pharma, and participation on a data safety monitoring board or advisory board with Polyphor, Santhera (DMC), Vertex, OM Pharma, Vifor, Allecra and Sanofi Aventis. M. Stahl reports support for the present study from German Research Foundation (Deutsche Forschungsgemeinschaft, DFG), grants, payment or honoraria for lectures, presentations, manuscript writing or educational events and participation on a data safety monitoring board or advisory board with Vertex Pharmaceuticals, and leadership roles with FGM (Chairman), ERS (Secretary Group CF), and GPP (Treasurer). D.J. Weiner reports consultancy fees from Cystic Fibrosis Foundation. A.M. Zwitserloot reports grants from Vertex Pharmaceuticals, and consultancy fees from Sanofi. A. Horsley reports support for the present study from ERS, grants from NIHR Manchester Biomedical Research Centre, consultancy fees, payment or honoraria for lectures, presentations, manuscript writing or educational events, and receipt of equipment, materials, drugs, medical writing, gifts or other services from Vertex Pharmaceuticals, a leadership role with NIHR Respiratory Translational Research Collaboration (Chair), and technical support provided to Innocor ApS. The remaining authors have no potential conflicts of interest to disclose., (Copyright ©The authors 2024. For reproduction rights and permissions contact permissions@ersnet.org.)

The diagnosis of paediatric pulmonary tuberculosis is difficult, especially in young infants who cannot expectorate sputum spontaneously. Breath testing has shown promise in diagnosing respiratory tract infections, but data on paediatric tuberculosis are limited. We performed a prospective cross-sectional study in Kenya in children younger than five years with symptoms of tuberculosis. We analysed exhaled breath with a hand-held battery-powered nose device. For data analysis, machine learning was applied using samples classified as positive (microbiologically confirmed) or negative (unlikely tuberculosis) to assess diagnostic accuracy. Breath analysis was performed in 118 children. The area under the curve of the optimal model was 0.73. At a sensitivity of 86 % (CI 62-96 %), this resulted in a specificity of 42 % (95 % CI 30-55 %). Exhaled breath analysis shows promise as a triage test for TB in young children, although the WHO target product characteristics were not met., (Copyright © 2024. Published by Elsevier Ltd.)

The biosensor, named "virusmeter" in this study, integrates quartz crystal microbalance technology with an immune-functionalized chip to distinguish between symptomatic patients with respiratory diseases and healthy individuals by analyzing exhaled air samples. Renowned for its compact design, rapidity, and noninvasive nature, this device yields results within a 5-min timeframe. Evaluated under controlled conditions with 54 hospitalized symptomatic COVID-19 patients and 128 control subjects, the biosensor demonstrated good overall sensitivity (98.15%, 95% CI 90.1-100.0) and specificity (96.87%, 95% CI 92.2-99.1). This proof-of-concept presents an innovative approach with significant potential for leveraging piezoelectric sensors to diagnose respiratory diseases., Competing Interests: Declarations. Ethics approval: All procedures strictly adhered to established guidelines and regulations. Ethical approvals were granted by the Biomedical Research Ethics Committee of the La Fe University and Polytechnic Hospital in Valencia, Spain, and the University General Hospital of Castellon, Spain. Additionally, the Health Centre at the Universitat Politècnica de València and the Fortuny nursing home in Valencia, Spain, permitted testing for their interns. Source of biological material: Exhaled air samples were monitored on-site at several locations, including La Fe University and Polytechnic Hospital in Valencia, University General Hospital of Castellon, Health Centre at the Universitat Politècnica de València, and Fortuny nursing home in Valencia. Sampling occurred from February 2nd, 2021, to November 24th, 2021. A total of 33 patients were analyzed at the University General Hospital of Castellon, and 21 patients were analyzed at La Fe University and Polytechnic Hospital in Valencia, totaling 54 patients. Control subjects included 84 individuals from the UPV Health Centre “Juana Portaceli,” 25 from the Fortuny nursing home, 12 from La Fe Hospital, and 7 from the Hospital of Castellon, totaling 128. Special measures were taken to prevent the spread of the virus during sampling. Competing interests: The authors declare no competing interests., (© 2024. The Author(s).)

Background: Breath testing for small intestinal bacterial overgrowth (SIBO) is typically performed using clinic-based equipment or single-use test kits., Aims: This study aimed to evaluate the utility of a portable, point-of-care breath analysis device (AIRE®, FoodMarble) in patients suspected to have SIBO. A technical assessment including a comparison to existing mail-in kits was first performed. Then, postprandial breath hydrogen levels of patients before and after antibiotic treatment were gathered and compared to levels seen in a healthy cohort., Methods: For the comparison, 50 patients suspected of having SIBO were provided with an AIRE device and performed concurrent LHBTs at-home with a mail-in breath test kit. For the postprandial analysis, twenty-four patients with chronic GI symptoms measured their postprandial hydrogen for 7 days prior to antibiotic treatment and for 7 days after treatment. 10 healthy controls also measured their postprandial hydrogen for 7 days., Results: Substantial agreement was demonstrated between AIRE and the mail-in kits for the performance of lactulose hydrogen breath tests (κ = 0.8). Prior to treatment, patients had significantly greater daily postprandial hydrogen than healthy controls (p < 0.001). The mean postprandial hydrogen of patients reduced significantly after treatment (p < 0.001)., Conclusions: Measuring postprandial hydrogen shows potential as a means of differentiating patients with chronic GI symptoms from healthy controls and may be useful in monitoring patients before, during, and after treatment. Future studies could help determine if pre-treatment breath gas levels are predictive of response to antibiotic treatment., Competing Interests: Declarations. Conflict of interest: Áine Moran, Barry Mc Bride, and Ricky Harrison are employees of FoodMarble Digestive Health. Pankaj Jay Pasricha is a member of the clinical advisory board of FoodMarble Digestive Health and a paid consultant. The authors declare no competing interests., (© 2024. The Author(s).)

The detection of acetone in human exhaled breath is crucial for the noninvasive diagnosis of diabetes. However, the direct and reliable detection of acetone in exhaled breath with high humidity at the parts per billion level remains a great challenge. Here, an ultrasensitive acetone gas sensor based on a K/Sn-Co 3 O 4 porous microsphere was reported. The sensor demonstrates a detection limit of up to 100 ppb, along with excellent repeatability and selectivity. Remarkably, without the removal of water vapor from exhaled breath, the sensor can accurately distinguish diabetic patients and healthy individuals according to the difference in acetone concentrations, demonstrating its great potential for diabetes diagnosis. The enhanced sensitivity of the sensor is attributed to the increased oxygen adsorption on the material surface due to K/Sn codoping and the stronger coadsorption of Sn-K atoms to acetone molecules. These findings shed light on the mechanisms underlying the sensor's improved performance.

Serious acute respiratory syndrome coronavirus-2 (SARS-CoV-2) poses a tremendous threat to global public health. Recently, the Food and Drug Administration approved the emergency use of volatile organic components as detection biomarkers for COVID-19, ushering in a new era of portable, simple, and rapid epidemiological screening based on breath diagnosis. Nitric oxide (NO) is an important biomarker indicating the degree of inflammation in the respiratory tract. In this study, a hollow multishelled structured WO 3 (HoMSs-WO 3 )-based waveguide microwave gas sensor (MGS) was fabricated to detect trace levels of NO in exhaled breath for the preliminary diagnosis of COVID-19. The sensor showed excellent reusability and selectivity and efficiently detected NO in the 10-100 ppb, with a sensitivity of 39.27 dB/ppm and a detection limit of 2.52 ppb. In addition, a sound correlation was observed in the measurement results between the MGS and the Sunvou detector for detecting NO from the exhaled breath of clinical COVID-19 patients. The difference between the two measurements was within 1.96 standard bias, and the consistency range was -12 to 17 ppb, thus fully demonstrating the significant potential of the sensor in COVID-19 screening.

Breath analysis enables rapid, noninvasive diagnosis of human health by identifying and quantifying exhaled biomarker. Here, we demonstrated an exhaled breath sensing method using the near-infrared laser spectroscopy, and sub parts-per-million (ppm) level ammonia detection inside the exhaled gas was achieved employing a distributed feedback laser centered at 1512 nm and Kalman filtering algorithm. Integration of the ammonia sensor was realized for exhaled breath analysis of kidney patients, and a dual operation mechanism with static and dynamic modes was proposed to make this method applicable for real-time and comprehensive pre-diagnosis of kidney disease., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2024 Elsevier B.V. All rights reserved.)

The measurement of trace breath gases is of growing interest for its potential to provide non-invasive physiological information in health and disease. While instrumental techniques such as selected-ion flow-tube mass spectrometry (SIFT-MS) can achieve this, these are less suitable for clinical application. Sensitive sensor-based systems for breath ammonia could be more widely deployed, but have proven challenging to develop. This work demonstrates the sequential analytical validation of an electrochemical impedance-based sensor system for the measurement of ammonia in breath using SIFT-MS. Qualitative and relative responses between the two methods were comparable, although there were consistent differences in absolute concentration. When tested in artificial breath ammonia, sensors had a relative impedance sensitivity of 3.43 × 10 -5 ppbv -1 for each breath in the range of 249-1653 ppbv ( r 2 = 0.87, p < 0.05). When correlated with SIFT-MS using human breath ( n = 14), ammonia was detected in the range of 100-700 ppbv ( r = 0.78, p < 0.001), demonstrating acceptable sensitivity, reproducibility and dynamic range for clinical application., (© 2024 IOP Publishing Ltd. All rights, including for text and data mining, AI training, and similar technologies, are reserved.)

Detecting volatile organic compounds (VOCs) is increasingly recognized as a pivotal tool in non-invasive disease diagnostics. VOCs are metabolic byproducts, mostly found in human breath, urine, feces, and sweat, whose profiles may shift significantly due to pathological conditions. This paper presents a thorough review of the latest advancements in sensor technologies for VOC detection, with a focus on their healthcare applications. It begins by introducing VOC detection principles, followed by a review of the rapidly evolving technologies in this area. Special emphasis is given to functionalized molecularly imprinted polymer-based biochemical sensors for detecting breath biomarkers, owing to their exceptional selectivity. The discussion examines SWaP-C considerations alongside the respective advantages and disadvantages of VOC sensing technologies. The paper also tackles the principal challenges facing the field and concludes by outlining the current status and proposing directions for future research.

In response to the growing demand for global health monitoring, we report a nonintrusive health detection method using a compact, conformal wearable ultraviolet (UV)-assisted gas-sensing system based on an intrinsically flexible porous polydimethylsiloxane (PDMS)-zinc oxide (ZnO) composite layer (PPZL) for the breath acetone (BrAce) detection and breath event analysis. The enhanced acetone response is attributed to the synergistic effect of UV irradiation and the high surface area of the porous structure, which also improves the mechanical robustness. The UV-assisted wearable sensor reliably detects acetone concentrations ranging from 1 to 100 ppm at room temperature under 4.05 mW/cm 2 UV intensity, even under mechanical strains such as a bending radius of 5 mm and 60% tensile strain. It accurately analyzes different breathing patterns (12-20 breaths per minute) and BrAce concentrations, maintaining a stable performance over 20 days with less than 5% signal degradation. The sensor exhibits response and recovery times of average 110-150 and 130-180 s, respectively, and maintains a consistent 3 ppm BrAce response under varying humidity levels up to 70% relative humidity, ensuring accurate detection of BrAce concentrations during real-world breath tests. Additionally, the sensor targets only specific gases, and the sensor's selectivity is not a key concern. This flexible acetone gas sensor offers a portable solution for health management and a fabrication method for designing flexible metal oxide materials.

Disease diagnosis of Helicobacter pylori (Hp) through human exhaled breath analysis has attracted considerable attention. However, conventional methods, such as carbon 13 ( 13 C) breath test and infrared spectrometers, are facing the challenge of achieving portability and reliability synchronously. Herein, we report a portable and hand-held Hp analyzer using a bimetallic PtRu@SnO 2 -based gas sensor for the prediagnosis of Hp infection, which is based on detecting ammonia (NH 3 ) as a potential biomarker in exhaled breath. Owing to the surface functionalization through highly catalytically active bimetallic PtRu nanoparticles (NPs) prepared by a photochemical reduction strategy, the PtRu@SnO 2 -based sensor exhibits high sensitivity and selectivity toward trace-level (200 ppb) NH 3 even at high-humidity surroundings (80% RH). Consequently, the designed portable and hand-held Hp analyzer makes the accurate determination of NH 3 at 800 ppb in exhaled breath. The tuning of energy band structure and electrical characteristics and the catalytic modulation of NH 3 oxidation by PtRu NPs are proposed to be the reasons behind the enhanced NH 3 gas-sensing performance, as confirmed by in situ analysis using an online MKS MultiGas 2030 FTIR gas analyzer. This work paves the way for the prediagnosis of Hp infection using a metal oxide gas sensor.

The growing demand for wearable healthcare devices has led to an urgent need for cost-effective, wireless and portable breath monitoring systems. However, it is essential to explore novel nanomaterials that combine state-of-the-art flexible sensors with high performance and sensing capabilities along with scalability and industrially acceptable processing. In this study, we demonstrate a highly efficient NiS 2 -based flexible capacitive sensor fabricated via a solution-processible route using a novel single-source precursor [Ni{S 2 P(OPr) 2 } 2 ]. The developed sensor could precisely detect the human respiration rate and exhibit rapid responsiveness, exceptional sensitivity and selectivity at ambient temperatures, with an ultra-fast response and recovery. The device effectively differentiates the exhaled breath patterns including slow, fast, oral and nasal breath, as well as post-exercise breath rates. Moreover, the sensor shows outstanding bending stability, repeatability, reliable and robust sensing performance and is capable of contactless sensing. The sensor was further employed with a user-friendly wireless interface to facilitate smartphone-enabled real-time breath monitoring systems. This work opens up numerous avenues for cost-effective, sustainable and versatile sensors with potential applications for Internet of Things-based flexible and wearable electronics.This article is part of the theme issue 'Celebrating the 15th anniversary of the Royal Society Newton International Fellowship'.

Non-invasive detection of tumors is of utmost importance to save lives. Nonetheless, identifying tumors through gas analysis is a challenging task. In this work, biosensors with remarkable gas-sensing characteristics were developed using a self-assembly method consisting of peptides and MXene. Based on these biosensors, a mimetic biosensor array (MBA) was fabricated and integrated into a real-time testing platform (RTP). In addition, machine learning (ML) algorithms were introduced to improve the RTP's detection and identification capabilities of exhaled gas signals. The synthesized biosensor, with the ability to specifically bind to targeted gas molecules, demonstrated higher performance than the pristine MXene, with a response up to 150% greater. Besides, the MBA successfully detected 15 odor molecules affiliated with five categories of alcohols, ketones, aldehydes, esters, and acids by pattern recognition algorithms. Furthermore, with the ML assistance, the RTP detected the breath odor samples from volunteers of four categories, including healthy populations, patients of lung cancer, upper digestive tract cancer, and lower digestive tract cancer, with accuracies of 100%, 94.1%, 90%, and 95.2%, respectively. In summary, we have developed a cost-effective and precise model for non-invasive tumor diagnosis. Furthermore, this prototype also offers a versatile solution for diagnosing other diseases like nephropathy, diabetes, etc., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2024 Elsevier B.V. All rights reserved.)

Objective: To predict exhaled air in patients undergoing mechanical ventilation during bedside diagnosis of ventilator-associated pneumonia., Methods: Air samples were collected through the expiratory branch of the mechanical ventilation circuit during the hospitalization of patients at the intensive care unit of Hospital São José in Criciúma (SC), Brazil. In this study, 83 participants were divided into two groups, namely, the group with and the group without ventilator-associated pneumonia., Results: The analysis of three air patterns revealed a predictive value for the diagnosis of ventilator-associated pneumonia. The analyses of samples from the first 12 hours of invasive mechanical ventilation were able to predict ventilator-associated pneumonia (p = 0.018). However, none of the other air samples collected during hospitalization were useful in identifying the severity or predicting early or late ventilator-associated pneumonia., Conclusion: The use of a gas analyzer may be helpful for the early identification of patients admitted to intensive care who will develop ventilator-associated pneumonia.

Kidney diseases are a group of conditions related to the functioning of kidneys, which are in turn unable to properly filter waste and excessive fluids from the blood, resulting in the presence of dangerous levels of electrolytes, fluids, and waste substances in the human body, possibly leading to significant health effects. At the same time, the toxins amassing in the organism can lead to significant changes in breath composition, resulting in halitosis with peculiar features like the popular ammonia breath. Starting from this evidence, scientists have started to work on systems that can detect the presence of kidney diseases using a minimally invasive approach, minimizing the burden to the individuals, albeit providing clinicians with useful information about the disease's presence or its main related features. The electronic nose (e-nose) is one of such tools, and its applications in this specific domain represent the core of the present review, performed on articles published in the last 20 years on humans to stay updated with the latest technological advancements, and conducted under the PRISMA guidelines. This review focuses not only on the chemical and physical principles of detection of such compounds (mainly ammonia), but also on the most popular data processing approaches adopted by the research community (mainly those relying on Machine Learning), to draw exhaustive conclusions about the state of the art and to figure out possible cues for future developments in the field.

For hazardous gas monitoring and non-invasive diagnosis of diabetes using breath analysis, porous foams assembled by Co 3 O 4 nanoparticles were designed as sensing electrode materials to fabricate efficient yttria-stabilized zirconia (YSZ)-based acetone sensors. The sensitivity of the sensors was improved by varying the sintering temperature to regulate the morphology. Compared to other materials sintered at different temperatures, the porous Co 3 O 4 nanofoams sintered at 800 °C exhibited the highest electrochemical catalytic activity during the electrochemical test. The response of the corresponding Co 3 O 4 -based sensor to 10 ppm acetone was -77.2 mV and it exhibited fast response and recovery times. Moreover, the fabricated sensor achieved a low detection limit of 0.05 ppm and a high sensitivity of -56 mV/decade in the acetone concentration range of 1-20 ppm. The sensor also exhibited excellent repeatability, acceptable selectivity, good O 2 /humidity resistance, and long-term stability during continuous measurements for over 30 days. Moreover, the fabricated sensor was used to determine the acetone concentration in the exhaled breaths of patients with diabetic ketosis. The results indicated that it could distinguish between healthy individuals and patients with diabetic ketosis, thereby proving its abilities to diagnose and monitor diabetic ketosis. Based on its excellent sensitivity and exhaled breath measurement results, the developed sensor has broad application prospects., Competing Interests: Declaration of Competing Interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2024 Elsevier B.V. All rights reserved.)

Human breath contains biomarkers (odorants) that can be targeted for early disease detection. It is well known that honeybees have a keen sense of smell and can detect a wide variety of odors at low concentrations. Here, we employ honeybee olfactory neuronal circuitry to classify human lung cancer volatile biomarkers at different concentrations and their mixtures at concentration ranges relevant to biomarkers in human breath from parts-per-billion to parts-per-trillion. We also validated this brain-based sensing technology by detecting human non-small cell lung cancer (NSCLC) and small cell lung cancer (SCLC) cell lines using the 'smell' of the cell cultures. Different lung cancer biomarkers evoked distinct spiking response dynamics in the honeybee antennal lobe neurons indicating that those neurons encoded biomarker-specific information. By investigating lung cancer biomarker-evoked population neuronal responses from the honeybee antennal lobe, we classified individual human lung cancer biomarkers successfully (88% success rate). When we mixed six lung cancer biomarkers at different concentrations to create 'synthetic lung cancer' vs. 'synthetic healthy' human breath, honeybee population neuronal responses were able to classify those complex breath mixtures reliably with exceedingly high accuracy (93-100% success rate with a leave-one-trial-out classification method). Finally, we employed this sensor to detect human NSCLC and SCLC cell lines and we demonstrated that honeybee brain olfactory neurons could distinguish between lung cancer vs. healthy cell lines and could differentiate between different NSCLC and SCLC cell lines successfully (82% classification success rate). These results indicate that the honeybee olfactory system can be used as a sensitive biological gas sensor to detect human lung cancer., Competing Interests: Declaration of competing interest We wish to confirm that there are no known conflicts of interest associated with this publication and there has been no significant financial support for this work that could have influenced its outcome., (Copyright © 2024 Elsevier B.V. All rights reserved.)

Against the backdrop of advancements in modern multifunctional wearable electronics, there is a growing demand for simple, sustainable, and portable electronic skin (e-skin), posing significant challenges. This study aims to delineate the development of a straightforward, transparent, highly sensitive, and high power-density electronic skin based on a triboelectric nanogenerator(S-TENG), designed for harvesting human body energy and real-time monitoring of the physiological motion status. Our e-skin incorporates thermally treated polyvinylidene fluoride (PVDF) fiber membranes as the contact layer and a film of silver nanowires as the conductive electrodes. The resulting contact-separation type e-skin exhibits an impressive transparency of 80 %, along with a nice sensitivity value, capable of detecting a light touch from a 0.13 g sponge and demonstrating good working stability and breathability. Leveraging the triboelectric effect, our e-skin generates an open-circuit voltage of 301 V and a short-circuit current of 2.7 μA under an extrinsic force of 8 N over an interaction area of 4 × 4 cm 2 , achieving a power density up to 306 mW/m 2 . With its signal processing circuitry, the integrated S-TENG showcases nice energy harvesting and signal transmission capabilities. Accordingly, we contend that S-TENG has potential applications in energy capture and real-time human motion state monitoring. This research is anticipated to blaze a novel and practical trail for self-powered wearable devices and personalized health rehabilitation training regimens., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2024 Elsevier Inc. All rights reserved.)

The global demand for rapid and non-invasive diagnostic methods for respiratory diseases has significantly intensified due to the wide spread of respiratory infectious diseases. Recent advancements in respiratory disease diagnosis through the analysis of exhaled breath and saliva has attracted great attention all over the world. Among various analytical methods, biosensors can offer non-invasive, efficient, and cost-effective diagnostic capabilities, emerging as promising tools in this area. This review intends to provide a comprehensive overview of various biosensors for the detection of respiratory disease related biomarkers in exhaled breath and saliva. Firstly, the characteristics of exhaled breath and saliva, including their generation, composition, and relevant biomarkers are introduced. Subsequently, the design and application of various biosensors for detecting these biomarkers are presented, along with the innovative materials employed as sensitive components. Different types of biosensors are reviewed, including electrochemical, optical, piezoelectric, semiconductor, and other novel biosensors. At last, the challenges, limitations, and future trends of these biosensors are discussed. It is anticipated that biosensors will play a significant role in respiratory disease diagnosis in the future., Competing Interests: Declaration of competing interest All authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2024 Elsevier B.V. All rights reserved.)

The molecular composition of exhaled human breath can reflect various physiological and pathological conditions. Considerable progress has been achieved over the past decade in real-time analysis of exhaled human breath using direct mass spectrometry methods, including selected ion flow tube mass spectrometry, proton transfer reaction mass spectrometry, extractive electrospray ionization mass spectrometry, secondary electrospray ionization mass spectrometry, acetone-assisted negative photoionization mass spectrometry, atmospheric pressure photoionization mass spectrometry, and low-pressure photoionization mass spectrometry. Here, recent developments in direct mass spectrometry analysis of exhaled human breath are reviewed with regard to analytical performance (chemical sensitivity, selectivity, quantitative capabilities) and applications of the developed methods in disease diagnosis, targeted molecular detection, and real-time metabolic monitoring., (© 2023 John Wiley & Sons Ltd.)

Lung cancer remains a global health concern, demanding the development of noninvasive, prompt, selective, and point-of-care diagnostic tools. Correspondingly, breath analysis using nanobiosensors has emerged as a promising noninvasive nose-on-chip technique for the early detection of lung cancer through monitoring diversified biomarkers such as volatile organic compounds/gases in exhaled breath. This comprehensive review summarizes the state-of-the-art breath-based lung cancer diagnosis employing chemiresistive-module nanobiosensors supported by theoretical findings. It unveils the fundamental mechanisms and biological basis of breath biomarker generation associated with lung cancer, technological advancements, and clinical implementation of nanobiosensor-based breath analysis. It explores the merits, challenges, and potential alternate solutions in implementing these nanobiosensors in clinical settings, including standardization, biocompatibility/toxicity analysis, green and sustainable technologies, life-cycle assessment, and scheming regulatory modalities. It highlights nanobiosensors' role in facilitating precise, real-time, and on-site detection of lung cancer through breath analysis, leading to improved patient outcomes, enhanced clinical management, and remote personalized monitoring. Additionally, integrating these biosensors with artificial intelligence, machine learning, Internet-of-things, bioinformatics, and omics technologies is discussed, providing insights into the prospects of intelligent nose-on-chip lung cancer sniffing nanobiosensors. Overall, this review consolidates knowledge on breathomic biosensor-based lung cancer screening, shedding light on its significance and potential applications in advancing state-of-the-art medical diagnostics to reduce the burden on hospitals and save human lives.

Untargeted analysis of volatile organic compounds (VOCs) from exhaled breath and culture headspace are influenced by several confounding factors not represented in reference standards. In this study, we propose a method of generating pooled quality control (QC) samples for untargeted VOC studies using a split-recollection workflow with thermal desorption tubes. Sample tubes were desorbed and 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 multiple QC samples. We found pooled QC samples to be representative of complex mixtures using principal component analysis and may be useful in future longitudinal, multi-centre, and validation studies to assess data quality and adjust for batch effects., (Creative Commons Attribution license.)

Owing to the correlation between acetone in human's exhaled breath (EB) and blood glucose, the development of EB acetone gas-sensing devices is important for early diagnosis of diabetes diseases. In this article, a noninvasive blood glucose detection device through acetone sensing in EB, based on an α-Fe 2 O 3 -multiwalled carbon nanotube (MWCNT) nanocomposite, was successfully developed. Different amounts of α-Fe 2 O 3 were added to the MWCNTs by a simple solution method. The optimized acetone gas sensor showed a response of 5.15 to 10 ppm acetone gas at 200 °C. Also, the fabricated sensor showed very good sensing properties even in an atmosphere with high relative humidity. Since the EB has high humidity, the proposed sensor is a promising device to exactly detect the amount of acetone in EB with high humidity. The sensor was powered by a 3200 mAh battery with the possibility of charging using mains electricity. To increase the reliability and calibration of the sensing device, a practical test was taken to detect acetone EB from 50 volunteers, and a deep learning algorithm (DLA) was used to detect the effect of various factors on the amount of acetone in each person's acetone EB. The proposed device with ±15 errors had almost 85% correct responses. Also, the proposed device had excellent response, short response time, good selectivity, and good repeatability, leading it to be a suitable candidate for noninvasive blood glucose sensing.

A flexible wearable sensor based on the Fabry-Perot (FP) structure for human breath monitoring is proposed and demonstrated. This sensor is constructed by fusing a single-mode optical fiber to a small section of capillary and coating the end with agar film. In high relative humidity (RH) environments, the agar film absorbs moisture from the air, which leads to a change in the length of the FP cavity to cause a shift in the interference spectrum. The sensor has a sensitivity of 0.95 nm/%RH for testing RH in the range of 60%RH to 85%RH. The temperature sensitivity of the sensor varies nonlinearly from 30°C to 90°C, averaging 0.34 nm/°C over the range of 30°C to 55°C and 0.06 nm/°C over the range of 60°C to 90°C. The temperature and RH crosstalk problems can be solved by using cascaded fiber Bragg grating followed by matrix operations to monitor temperature and RH parameters simultaneously. In addition, the sensor has a fast response time of 0.88 s and a recovery time of 1.17 s for human breathing. The normal and deep breathing of nine subjects are monitored using the sensor, demonstrating that the sensor is able to recognize normal and deep breathing accurately. The success of this sensor proves that it is feasible to develop sensors with good resistance to vibration interference, good repeatability and high stability for human breath monitoring, which is of great significance for research on human breath monitoring.

Recent respiratory outbreaks have garnered substantial attention, yet most respiratory monitoring remains confined to physical signals. Exhaled breath condensate (EBC) harbors rich molecular information that could unveil diverse insights into an individual's health. Unfortunately, challenges related to sample collection and the lack of on-site analytical tools impede the widespread adoption of EBC analysis. Here, we introduce EBCare, a mask-based device for real-time in situ monitoring of EBC biomarkers. Using a tandem cooling strategy, automated microfluidics, highly selective electrochemical biosensors, and a wireless reading circuit, EBCare enables continuous multimodal monitoring of EBC analytes across real-life indoor and outdoor activities. We validated EBCare's usability in assessing metabolic conditions and respiratory airway inflammation in healthy participants, patients with chronic obstructive pulmonary disease or asthma, and patients after COVID-19 infection.

Exhaled breath electrochemical sensing is a promising biomedical technology owing to its portability, painlessness, cost-effectiveness, and user-friendliness. Here, we present a novel approach for target analysis in exhaled breath by integrating a comfortable paper-based collector into an N95 face mask, providing a universal solution for analyzing several biomarkers. As a model analyte, we detected SARS-CoV-2 spike protein from the exhaled breath by sampling the target analyte into the collector, followed by its detection out of the N95 face mask using a magnetic bead-based electrochemical immunosensor. This approach was designed to avoid any contact between humans and the chemicals. To simulate human exhaled breath, untreated saliva samples were nebulized on the paper collector, revealing a detection limit of 1 ng/mL and a wide linear range of 3.7-10,000 ng/mL. Additionally, the developed immunosensor exhibited high selectivity toward the SARS-CoV-2 spike protein, compared to other airborne microorganisms, and the SARS-CoV-2 nucleocapsid protein. Accuracy assessments were conducted by analyzing the simulated breath samples spiked with varying concentrations of SARS-CoV-2 spike protein, resulting in satisfactory recovery values (ranging from 97 ± 4 to 118 ± 1%). Finally, the paper-based hybrid immunosensor was successfully applied for the detection of SARS-CoV-2 in real human exhaled breath samples. The position of the collector in the N95 mask was evaluated as well as the ability of this paper-based analytical tool to identify the positive patient.

Ammonia (NH 3 ) in exhaled breath (EB) has been a biomarker for kidney function, and accurate measurement of NH 3 is essential for early screening of kidney disease. In this work, we report an optical sensor that combines ultraviolet differential optical absorption spectroscopy (UV-DOAS) and spectral reconstruction fitting neural network (SRFNN) for detecting NH 3 in EB. UV-DOAS is introduced to eliminate interference from slow change absorption in the EB spectrum while spectral reconstruction fitting is proposed for the first time to map the original spectra onto the sine function spectra by the principle of least absolute deviations. The sine function spectra are then fitted by the least-squares method to eliminate noise signals and the interference of exhaled nitric oxide. Finally, the neural network is built to enable the detection of NH 3 in EB at parts per billion (ppb) level. The laboratory results show that the detection range is 9.50-12425.82 ppb, the mean absolute percentage error (MAPE) is 0.83%, and the detection accuracy is 0.42%. Experimental results prove that the sensor can detect breath NH 3 and identify EB in simulated patients and healthy people. Our sensor will serve as a new and effective system for detecting breath NH 3 with high accuracy and stability in the medical field.

Introduction: Volatile organic compounds (VOCs) in breath serve as a source of biomarkers for medical conditions relevant to warfighter health including Corona Virus Disease and other potential biological threats. Electronic noses are integrated arrays of gas sensors that are cost-effective and miniaturized devices that rapidly respond to VOCs in exhaled breath. The current study seeks to qualify healthy breath baselines of exhaled VOC profiles through analysis using a commercialized array of metal oxide (MOX) sensors., Materials and Methods: Subjects were recruited/consented through word of mouth and using posters. For each sample, breath was analyzed using an array of MOX sensors with parameters that were previously established. Data were also collected using a lifestyle questionnaire and from a blood test to assess markers of general health. Sensor data were processed using a feature extraction algorithm, which were analyzed through statistical approaches to identify correlations with confounding factors. Reproducibility was also assessed through relative standard deviation values of sensor features within a single subject and between different volunteers., Results: A total of 164 breath samples were collected from different individuals, and 10 of these volunteers provided an additional 9 samples over 6 months for the longitudinal study. First, data from different subjects were analyzed, and the trends of the 17 extracted features were elucidated. This revealed not only a high degree of correlation between sensors within the array but also between some of the features extracted within a single sensor. This helped guide the removal of multicollinear features for multivariate statistical analyses. No correlations were identified between sensor features and confounding factors of interest (age, body mass index, smoking, and sex) after P-value adjustment, indicating that these variables have an insignificant impact on the observed sensor signal. Finally, the longitudinal replicates were analyzed, and reproducibility assessment showed that the variability between subjects was significantly higher than within replicates of a single volunteer (P-value = .002). Multivariate analyses within the longitudinal data displayed that subjects could not be distinguished from one another, indicating that there may be a universal healthy breath baseline that is not specific to particular individuals., Conclusions: The current study sought to qualify healthy baselines of VOCs in exhaled breath using a MOX sensor array that can be leveraged in the future to detect medical conditions relevant to warfighter health. For example, the results of the study will be useful, as the healthy breath VOC data from the sensor array can be cross-referenced in future studies aiming to use the device to distinguish disease states. Ultimately, the sensors may be integrated into a portable breathalyzer or current military gear to increase warfighter readiness through rapid and noninvasive health monitoring., (© The Association of Military Surgeons of the United States 2024. All rights reserved. For commercial re-use, please contact reprints@oup.com for reprints and translation rights for reprints. All other permissions can be obtained through our RightsLink service via the Permissions link on the article page on our site–for further information please contact journals.permissions@oup.com.)

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 m / z 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., (Creative Commons Attribution license.)

Background: Theoretically, a rapid urease test (RUT) using a swab of the gastric wall (Swab-RUT) for Helicobacter pylori (H. pylori) is safe. However, the validity and utility of Swab-RUT remain unclear. Therefore, we assessed the validity and utility of Swab-RUT compared to RUT using mucosal forceps of the gastric wall (Forceps-RUT) and 13 C-urea breath test (UBT)., Methods: This study was a multicenter prospective observational study. When the examinees were suspected of H. pylori infection during esophagogastroduodenoscopy, we performed Swab-RUT and Forceps-RUT continuously. When the examinees were not suspected of H. pylori infection, we performed Swab-RUT alone. We validated the status of H. pylori infection using UBT., Results: Ninety-four examinees were enrolled from four institutions between May 2016 and December 2020 (median age [range], 56.5 [26-88] years). In this study, the sensitivity, specificity, and accuracy of Swab-RUT to UBT were 0.933 (95% confidence interval: 0.779-0.992), 0.922 (0.827-0.974), and 0.926 (0.853-0.970), respectively. The Kappa coefficient of Swab-RUT to UBT was 0.833, and that of Swab-RUT to forceps-RUT was 0.936. No complications were observed in this study., Conclusions: Swab-RUT is a valid examination for the status of H. pylori infection compared to the conventional Forceps-RUT., (© 2024. The Author(s).)

Helicobacter pylori ( H. pylori ) is a globally widespread bacterial infection. Early diagnosis of this infection is vital for public and individual health. Prevalent diagnosis methods like the isotope 13 C or 14 C labelled urea breath test (UBT) are not convenient and may do harm to the human body. The use of cross-response gas sensor arrays (GSAs) is an alternative way for label-free detection of metabolite changes in exhaled breath (EB). However, conventional GSAs are complex to prepare, lack reliability, and fail to discriminate subtle changes in EB due to the use of numerous sensing elements and single dimensional signal. This work presents a dual-element multimodal GSA empowered with multimodal sensing signals including conductance ( G ), capacitance ( C ), and dissipation factor ( DF ) to improve the ability for gas recognition and H. pylori -infection diagnosis. Sensitized by poly(diallyldimethylammonium chloride) (PDDA) and the metal-organic framework material NH 2 -UiO66, the dual-element graphene oxide (GO)-composite GSAs exhibited a high specific surface area and abundant adsorption sites, resulting in high sensitivity, repeatability, and fast response/recovery speed in all three signals. The multimodal sensing signals with rich sensing features allowed the GSA to detect various physicochemical properties of gas analytes, such as charge transfer and polarization ability, enhancing the sensing capabilities for gas discrimination. The dual-element GSA could differentiate different typical standard gases and non-dehumidified EB samples, demonstrating the advantages in EB analysis. In a case-control clinical study on 52 clinical EB samples, the diagnosis model based on the multimodal GSA achieved an accuracy of 94.1%, a sensitivity of 100%, and a specificity of 90.9% for diagnosing H. pylori infection, offering a promising strategy for developing an accurate, non-invasive and label-free method for disease diagnosis.

A novel Fe 2 Mo 3 O 8 /MoO 2 @MoS 2 nanocomposite is synthesized for extremely sensitive detection of NH 3 in the breath of kidney disease patients at room temperature. Compared to MoS 2 , α-Fe 2 O 3 /MoS 2 , and MoO 2 @MoS 2 , it shows the optimal gas-sensing performance by optimizing the formation of Fe 2 Mo 3 O 8 at 900 °C. The annealed Fe 2 Mo 3 O 8 /MoO 2 @MoS 2 nanocomposite (Fe 2 Mo 3 O 8 /MoO 2 @MoS 2 -900 °C) sensor demonstrates a remarkably high selectivity of NH 3 with a response of 875% to 30 ppm NH 3 and an ultralow detection limit of 3.7 ppb. This sensor demonstrates excellent linearity, repeatability, and long-term stability. Furthermore, it effectively differentiates between patients at varying stages of kidney disease through quantitative NH 3 measurements. The sensing mechanism is elucidated through the analysis of alterations in X-ray photoelectron spectroscopy (XPS) signals, which is supported by density functional theory (DFT) calculations illustrating the NH 3 adsorption and oxidation pathways and their effects on charge transfer, resulting in the conductivity change as the sensing signal. The excellent performance is mainly attributed to the heterojunction among MoS 2 , MoO 2 , and Fe 2 Mo 3 O 8 and the exceptional adsorption and catalytic activity of Fe 2 Mo 3 O 8 /MoO 2 @MoS 2 -900 °C for NH 3 . This research presents a promising new material optimized for detecting NH 3 in exhaled breath and a new strategy for the early diagnosis and management of kidney disease., (© 2024 The Author(s). Advanced Science published by Wiley‐VCH GmbH.)

Preservation of the breath sample integrity during storage and transport is one of the biggest challenges in off-line exhaled breath gas analysis. In this context, adsorbent tubes are frequently used as storage containers for use with analytical methods employing gas chromatography with mass spectrometric detection. The key objective of this short communication is to provide data on the recovery of selected breath volatiles from Tenax ® TA adsorbent tubes that were stored at -80 °C for up to 90 d. For this purpose, an Owlstone Medical's ReCIVA ® Breath Sampler was used for exhaled breath collection. The following fifteen compounds, selected to cover a range of chemical properties, were monitored for their stability: isoprene, n-heptane, n-nonane, toluene, p-cymene, allyl methyl sulfide, 1-(methylthio)-propane, 1-(methylthio)-1-propene, α -pinene, DL-limonene, β -pinene, γ -terpinene, 2-pentanone, acetoin and 2,3 butanedione. All compounds, but one (acetoin), were found to be stable during the first 4 weeks of storage (recovery within ± 2 × RSD). Furthermore, n-nonane was stable during the whole of the investigated period., (Creative Commons Attribution license.)

The Peppermint Initiative, established within the International Association of Breath Research, introduced the peppermint protocol, a breath analysis benchmarking effort designed to address the lack of inter-comparability of outcomes across different breath sampling techniques and analytical platforms. Benchmarking with gas chromatography-ion mobility spectrometry (GC-IMS) using peppermint has been previously reported however, coupling micro-thermal desorption ( µ TD) to GC-IMS has not yet, been benchmarked for breath analysis. To benchmark µ TD-GC-IMS for breath analysis using the peppermint protocol. Ten healthy participants (4 males and 6 females, aged 20-73 years), were enrolled to give six breath samples into Nalophan bags via a modified peppermint protocol. Breath sampling after peppermint ingestion occurred over 6 h at t = 60, 120, 200, 280, and 360 min. The breath samples (120 cm 3 ) were pre-concentrated in the µ TD before being transferred into the GC-IMS for detection. Data was processed using VOCal, including background subtractions, peak volume measurements, and room air assessment. During peppermint washout, eucalyptol showed the highest change in concentration levels, followed by α -pinene and β -pinene. The reproducibility of the technique for breath analysis was demonstrated by constructing logarithmic washout curves, with the average linearity coefficient of R 2 = 0.99. The time to baseline (benchmark) value for the eucalyptol washout was 1111 min (95% CI: 529-1693 min), obtained by extrapolating the average logarithmic washout curve. The study demonstrated that µ TD-GC-IMS is reproducible and suitable technique for breath analysis, with benchmark values for eucalyptol comparable to the gold standard GC-MS., (Creative Commons Attribution license.)

The analysis of exhaled breath condensate (EBC) demonstrates a promising avenue of minimally invasive biopsies for diagnostics. EBC is obtained by cooling exhaled air and collecting the condensation to be utilized for downstream analysis using various analytical methods. The aqueous phase of breath contains a large variety of miscible small compounds including polar electrolytes, amino acids, cytokines, chemokines, peptides, small proteins, metabolites, nucleic acids, and lipids/eicosanoids-however, these analytes are typically present at minuscule levels in EBC, posing a considerable technical challenge. Along with recent improvements in devices for breath collection, the sensitivity and resolution of liquid chromatography coupled to online mass spectrometry-based proteomics has attained subfemtomole sensitivity, vastly enhancing the quality of EBC sample analysis. As a result, proteomics analysis of EBC has been expanding the field of breath biomarker research. We present an au courant overview of the achievements in proteomics of EBC, the advancement of EBC collection devices, and the current and future applications for EBC biomarker analysis., (© 2023 John Wiley & Sons Ltd.)

The development of a portable, low-cost sensor capable of accurately detecting H 2 S gas in exhaled human breath at room temperature is highly anticipated in the fields of human health assessment and food spoilage evaluation. However, achieving outstanding gas sensing performance and applicability for flexible room-temperature operation with parts per billion H 2 S gas sensors still poses technical challenges. To address this issue, this study involves the in situ growth of MoS 2 nanosheets on the surface of In 2 O 3 fibers to construct a p-n heterojunction. The In 2 O 3 @MoS 2 -2 sensor exhibits a high response of 460.61 to 50 ppm of H 2 S gas at room temperature, which is 19.5 times higher than that of the pure In 2 O 3 sensor and 322.1 times higher than that of pure MoS 2 . The In 2 O 3 @MoS 2 -2 also demonstrates a minimum detection limit of 3 ppb and maintains a stable response to H 2 S gas even after being bent 50 times at a 60° angle. These exceptional gas sensing properties are attributed to the increase in oxygen vacancies and chemisorbed oxygen on In 2 O 3 @MoS 2 -2 nanofibers as well as the formation of the p-n heterojunction, which modulates the heterojunction barrier. Furthermore, in this study, we successfully applied the In 2 O 3 @MoS 2 -2 sensor for oral disease and detection of food spoilage conditions, thereby providing new design insights for the development of portable exhaled gas sensors and gas sensors for evaluating food spoilage conditions at room temperature.

Analyzing exhaled volatile organic compounds (VOCs) with an electronic nose (e-nose) is emerging in medical diagnostics as a non-invasive, quick, and sensitive method for disease detection and monitoring. This study investigates if activities like spirometry or physical exercise affect exhaled VOCs measurements in asthmatics and healthy individuals, a crucial step for e-nose technology's validation for clinical use. The study analyzed exhaled VOCs using an e-nose in 27 healthy individuals and 27 patients with stable asthma, before and after performing spirometry and climbing five flights of stairs. Breath samples were collected using a validated technique and analyzed with a Cyranose 320 e-nose. In healthy controls, the exhaled VOCs spectrum remained unchanged after both lung function test and exercise. In asthmatics, principal component analysis and subsequent discriminant analysis revealed significant differences post-spirometry (vs. baseline 66.7% cross validated accuracy [CVA], p < 0.05) and exercise (vs. baseline 70.4% CVA, p < 0.05). E-nose measurements in healthy individuals are consistent, unaffected by spirometry or physical exercise. However, in asthma patients, significant changes in exhaled VOCs were detected post-activities, indicating airway responses likely due to constriction or inflammation, underscoring the e-nose's potential for respiratory condition diagnosis and monitoring., (© 2024 IOP Publishing Ltd.)

The authors report the fabrication of highly sensitive, rapidly responding flexible force sensors using ZnO/ZnMgO coaxial nanotubes grown on graphene layers and their applications in sleep apnea monitoring. Flexible force sensors are fabricated by forming Schottky contacts to the nanotube array, followed by the mechanical release of the entire structure from the host substrate. The electrical characteristics of ZnO and ZnO/ZnMgO nanotube-based sensors are thoroughly investigated and compared. Importantly, in force sensor applications, the ZnO/ZnMgO coaxial structure results in significantly higher sensitivity and a faster response time when compared to the bare ZnO nanotube. The origin of the improved performance is thoroughly discussed. Furthermore, wireless breath sensing is demonstrated using the ZnO/ZnMgO pressure sensors with custom electronics, demonstrating the feasibility of the sensor technology for health monitoring and the potential diagnosis of sleep apnea., (© 2024 Wiley‐VCH GmbH.)

The maximum oxygen uptake (VO 2max ) is a critical factor for endurance performance in soccer. Novel wearable technology may allow frequent assessment of V̇O 2max during non-fatiguing warm-up runs of soccer players with minimal interference to soccer practice. The aim of this study was to assess the validity of VO2max provided by a consumer grade smartwatch (Garmin Forerunner 245, Garmin, Olathe, USA, Software:13.00) and the YoYo Intermittent Recovery Run 2 (YYIR2) by comparing it with respiratory gas analysis. 24 trained male youth soccer players performed different tests to assess VO 2max : i) a treadmill test employing respiratory gas analysis, ii) YYIR2 and iii) during a non-fatiguing warm-up run of 10 min wearing a smartwatch as recommended by the device-manufacturer on 3 different days within 2 weeks. As the device-manufacturer indicates that validity of smartwatch-derived VO 2max may differ with an increase in runs, 16 players performed a second run with the smartwatch to test this claim. The main evidence revealed that the smartwatch showed an ICC of 0.37 [95% CI: -0.25; 0.71] a mean absolute percentage error (MAPE) of 5.58% after one run, as well as an ICC of 0.54 [95% CI: -0.3; 8.4] and a MAPE of 1.06% after the second run with the smartwatch. The YYIR2 showed an ICC of 0.17 [95% CI: -5.7; 0.6]; and MAPE of 4.2%. When using the smartwatch for VO 2max assessment in a non-fatiguing run as a warm-up, as suggested by the device manufacturer before soccer practice, the MAPE diminishes after two runs. Therefore, for more accurate VO 2max assessment with the smartwatch, we recommend to perform at least two runs to reduce the MAPE and enhance the validity of the findings., (© Journal of Sports Science and Medicine.)

The volatile particles and molecules in our dry exhaled breath can reveal enormous information about the health of any person, such as the person's respiratory and metabolic functioning. Beyond the carbon dioxide level is an indicator of life, it provides important health-related data like people's metabolic rate. This study considers periodic open and closed resonators for measuring carbon dioxide concentration in dry exhaled breath. Transfer matrix and green methods are used to simulate the interaction between acoustic waves and the proposed sensor. The band gaps using the green method coincide with the transmittance spectra by the transfer matrix. The suggested sensor recorded a sensitivity of 5.3 H z . m - 1 . s , a figure of merit of 10,254 m - 1 . s , a detection limit of 5 × 10 - 6 m . s - 1 , and a quality factor of 3 × 10 6 . Furthermore, the efficiency shows that the proposed design is appropriate as a diagnostic sensor for different diseases such as chronic obstructive pulmonary. Besides, cylindrical-adapted sensors are urgently needed in medicine, industry, and biology because they can simultaneously be used for fluid transport and detection., (© 2024. The Author(s).)

The analysis of volatile organic compounds (VOCs) in exhaled air has attracted the interest of the scientific community because it provides the possibility of monitoring physiological and metabolic processes and non-invasive diagnostics of various diseases. However, this method remains underused in clinical practice as well as in research because of the lack of standardized procedures for the collection, storage and transport of breath samples, which would guarantee good reproducibility and comparability of results. The method of sampling, as well as the storage time of the breath samples in the polymer bags used for sample storage and transport, affect the composition and concentration of VOCs present in the breath samples. The aim of our study was to compare breath samples obtained using two methods with fully disposable equipment: a Haldane sampling tube intended for direct breath collection and breath samples exhaled into a transparent Tedlar bag. The second task was to monitor the stability of selected compounds of real breath samples stored in a Tedlar bag for 6 h. Gas chromatography coupled with ion mobility spectrometry (GC-IMS) implemented in the BreathSpec ® device was used to analyse exhaled breath. Our results showed a significant difference in the signal intensity of some volatiles when taking a breath sample with a Haldane tube and a Tedlar bag. Due to its endogenous origin, acetone levels were significantly higher when the Haldane tube sampler was used while elevated levels of 2-propanol and unidentified VOC (designated as VOC 3) in the Tedlar bag samples likely originated from contamination of the Tedlar bags. The VOC stability study revealed compound-specific signal intensity changes of the selected VOCs with storage time in the Tedlar bags, with some volatiles showing increasing signal intensity during storage in Tedlar bags. This limits the use of Tedlar bags only for very limited time and carefully selected purpose. Our results highlight the importance of careful design and implementation of experiments and clinical protocols to obtain relevant and reliable results., (Creative Commons Attribution license.)

Diabetic ketoacidosis (DKA) is a life-threatening acute complication of diabetes characterized by the accumulation of ketone bodies in the blood. Breath acetone, a ketone, directly correlates with blood ketones. Therefore, monitoring breath acetone can significantly enhance the safety and efficacy of diabetes care. In this work, the design and fabrication of an InP/Pt/chitosan nanowire array-based chemiresistive acetone sensor is reported. By incorporation of chitosan as a surface-functional layer and a Pt Schottky contact for efficient charge transfer processes and photovoltaic effect, self-powered, highly selective acetone sensing is achieved. The sensor has exhibited an ultra-wide acetone detection range from sub-ppb to >100 000 ppm level at room temperature, covering those in the exhaled breath from healthy individuals (300-800 ppb) to people at high risk of DKA (>75 ppm). The nanowire sensor has also been successfully integrated into a handheld breath testing prototype, the Ketowhistle, which can successfully detect different ranges of acetone concentrations in simulated breath samples. The Ketowhistle demonstrates the immediate potential for non-invasive ketone monitoring for people living with diabetes, in particular for DKA prevention., (© 2024 The Authors. Advanced Science published by Wiley‐VCH GmbH.)

Prolonged air leakage (AL) following pulmonary resections leads to prolonged hospital stay and post-operative complications. Intra- and postoperative quantification of AL might be useful for improving treatment decisions, but these measurements have not been characterised. AL calculations based on inspiratory and expiratory tidal volumes were investigated in an Intensive Care Unit mechanical ventilator circuit (Servo-I). AL was also measured by a digital chest drainage system. This study shows that AL measurements increase in accuracy when corrected for baseline deviations (R: 0.904 > 0.997, p  < 0.001). Bland-Altman analysis revealed a funnel-shape, indicative of a detection threshhold. Corrected measurements were most accurate when averaged over five breaths and AL was >500 mL/min, with an estimated mean systemic bias of 7.4% (95%-limits of agreement [LoA]: 1.1%-13.7%) at 500 mL/min air leak. Breath-by-breath analysis showed most accurate results at AL >20 mL/breath (R: 0.989-0.991, p  < 0.001) at tidal volumes between 350-600 mL. The digital drain had a mean systemic bias of -11.1% (95%-LoA: -18.9% to -3.3%) with homogenous scatter in Bland-Altman analysis and a strong correlation to the control measurement over a large range (0-2000mL/min, R: 0.999, p  < 0.001). This study indicates that the Servo-I can be used for air leak quantification in clinically relevant ranges (>500 mL/min), but is unsuited for small leak detection due to a detection threshold. Researchers and clinicians should be aware of varying accuracy and interoperability characteristics between AL measurement devices.

Breathomics is the future of non-invasive point-of-care devices. The field of breathomics can be split into the isolation of disease-specific volatile organic compounds (VOCs) and their detection. In the present work, an array of five quartz tuning fork (QTF)-based sensors modified by polymer with nanomaterial additive has been utilized. The array has been used to detect samples of human breath spiked with ∼0.5 ppm of known VOCs namely, acetone, acetaldehyde, octane, decane, ethanol, methanol, styrene, propylbenzene, cyclohexanone, butanediol, and isopropyl alcohol which are bio-markers for certain diseases. Polystyrene was used as the base polymer and it was functionalized with 4 different fillers namely, silver nanoparticles-reduced graphene oxide composite, titanium dioxide nanoparticles, zinc ferrite nanoparticles-reduced graphene oxide composite, and cellulose acetate. Each of these fillers enhanced the selectivity of a particular sensor towards a certain VOC compared to the pristine polystyrene-modified sensor. Their interaction with the VOCs in changing the mechanical properties of polymer giving rise to change in the resonant frequency of QTF is used as sensor response for detection. The interaction of functionalized polymers with VOCs was analyzed by FTIR and UV-vis spectroscopy. The collective sensor response of five sensors is used to identify VOCs using an ensemble classifier with 92.8% accuracy of prediction. The accuracy of prediction improved to 96% when isopropyl alcohol, ethanol, and methanol were considered as one class., (© 2022 IOP Publishing Ltd.)

The high moisture level of exhaled gases unavoidably limits the sensitivity of breath analysis via wearable bioelectronics. Inspired by pulmonary lobe expansion/contraction observed during respiration, a respiration-driven triboelectric sensor (RTS) was devised for simultaneous respiratory biomechanical monitoring and exhaled acetone concentration analysis. A tin oxide-doped polyethyleneimine membrane was devised to play a dual role as both a triboelectric layer and an acetone sensing material. The prepared RTS exhibited excellent ability in measuring respiratory flow rate (2-8 L/min) and breath frequency (0.33-0.8 Hz). Furthermore, the RTS presented good performance in biochemical acetone sensing (2-10 ppm range at high moisture levels), which was validated via finite element analysis. This work has led to the development of a novel real-time active respiratory monitoring system and strengthened triboelectric-chemisorption coupling sensing mechanism.

A surface-plasmon-resonance-based fiber device is proposed for highly sensitive relative humidity (RH) sensing and human breath monitoring. The device is fabricated by using a polyvinyl alcohol (PVA) film and gold coating on the flat surface of a side-polished polymer optical fiber. The thickness and refractive index of the PVA coating are sensitive to environmental humidity, and thus the resonant wavelength of the proposed device exhibits a redshift as the RH increases. Experimental results demonstrate an average sensitivity of 4.98 nm/RH% across an ambient RH ranging from 40% to 90%. In particular, the sensor exhibits a linear response between 75% and 90% RH, with a sensitivity of 10.15 nm/RH%. The device is suitable for human breath tests and shows an average wavelength shift of up to 228.20 nm, which is 10 times larger than that of a silica-fiber-based humidity sensor. The corresponding response and recovery times are determined to be 0.44 s and 0.86 s, respectively. The proposed sensor has significant potential for a variety of practical applications, such as intensive care and human health analysis., Competing Interests: The authors declare no conflict of interest.

Objective: To assess the accuracy of a breath ketone analyzer to detect ketosis in adults and children with type 1 diabetes., Research Design and Methods: This is a proof-of-concept, prospective study comparing breath ketone analyzer and blood ketone meter to detect ketosis., Results: A total of 500 measurements from 19 adults and children with type 1 diabetes were analyzed. There was a significant association between the breath ketone analyzer and blood ketone meter results in non-fasting adults (p = 0.0066), but not in children (p = 0.4579). In adults, a cut-off of 3.9 PPM on the breath ketone analyzer maximized the Youden Index with an AUC of 0.73. This cut-off for the breath ketone analyzer had 94.7% sensitivity and 54.2% specificity to detect ketosis (≥0.6 mmol/L in blood ketone meter)., Conclusions: The breath ketone analyzer may be considered as a non-invasive screening tool to rule out ketosis in adults with type 1 diabetes., (Copyright © 2021 Elsevier Inc. All rights reserved.)

Airborne transmission of exhaled virus can rapidly spread, thereby increasing disease progression from local incidents to pandemics. Due to the COVID-19 pandemic, states and local governments have enforced the use of protective masks in public and work areas to minimize the disease spread. Here, we have leveraged the function of protective face coverings toward COVID-19 diagnosis. We developed a user-friendly, affordable, and wearable collector. This noninvasive platform is integrated into protective masks toward collecting airborne virus in the exhaled breath over the wearing period. A viral sample was sprayed into the collector to model airborne dispersion, and then the enriched pathogen was extracted from the collector for further analytical evaluation. To validate this design, qualitative colorimetric loop-mediated isothermal amplification, quantitative reverse transcription polymerase chain reaction, and antibody-based dot blot assays were performed to detect the presence of SARS-CoV-2. We envision that this platform will facilitate sampling of current SARS-CoV-2 and is potentially broadly applicable to other airborne diseases for future emerging pandemics.