Simulated Breathing Research Articles

An Individual Barrier Enclosure Actively Removing Aerosols for Airborne Isolation: A Vacuum Tent.

Aerosol barrier enclosure systems have been designed to prevent airborne contamination, but their safety has been questioned. A vacuum tent was designed with active continuous suctioning to minimize risks of aerosol dispersion. We tested its efficacy, risk of rebreathing, and usability on a bench, in healthy volunteers, and in an ergonomic clinical assessment study. First, a manikin with airway connected to a breathing simulator was placed inside the vacuum tent to generate active breathing, cough, and CO2 production; high-flow nasal cannula (HFNC) was applied in the manikin's nares. Negative pressure was applied in the vacuum tent's apex port using wall suction. Fluorescent microparticles were aerosolized in the vacuum tent for qualitative assessment. To quantify particles inside and around vacuum tent (aerosol retention), an airtight aerosol chamber with aerosolized latex microparticles was used. The vacuum tent was tested on healthy volunteers breathing with and without HFNC. Last, its usability was assessed in 5 subjects by 5 different anesthesiologists for delivery of full anesthesia, including intubation and extubation. The vacuum tent was adjusted until no leak was visualized using fluorescent particles. The efficacy in retaining microparticles was confirmed quantitatively. CO2 accumulation inside the vacuum tent showed an inverse correlation with the suction flow in all conditions (normal breathing and HFNC 30 or 60 L/min) in bench and healthy volunteers. Particle removal efficacy and safe breathing conditions (CO2, temperature) were reached when suctioning was at least 60 L/min or 20 L/min > HFNC flow. Five subjects were successfully intubated and anesthetized without ergonomic difficulties and with minimal interference with workflow and an excellent overall assessment by the anesthesiologists. The vacuum tent effectively minimized aerosol dispersion. Its continuous suction system set at a high suction flow was crucial to avoid the spread of aerosol particles and CO2 rebreathing.

UV-promoted NH3 sensor based on Ti3C2Tx/TiO2/ graphene sandwich structure with ultrasensitive RT sensing performances for human health detection

Gases produced by human respiration can effectively forewarn physiological health, and developing high-performance gas sensors for breath detection can help in the early diagnosis of many diseases. In this paper, Ti3C2Tx/TiO2/graphene composite with a unique sandwich structure was fabricated by hydrothermal method for resistive NH3 sensor, which is composed of the staggered interlayer of graphene, Ti3C2Tx, and in situ grown TiO2 nanosheets. The results indicate that the Ti3C2Tx/TiO2/graphene composite sensor has a response value of 35.8 at 50 ppm NH3 at room temperature and in a dark environment, which is 12.8 times higher than that of the single Ti3C2Tx and can detect dilute NH3 at ppb level with a calculated limit of 26 ppb. The sensor also possesses a fast response/recovery time of 19/29 s and excellent humidity resistance. Furthermore, with the assistance of UV illumination, the sensor response value for 50 ppm NH3 is increased to 45.18, the response/recovery time is accelerated to 18/25 s, and the calculated limit of detection is 22.23 ppb. Additionally, simulated breath detection demonstrates the potential application of the sensor for early respiratory warning in patients with renal failure. Finally, the NH3 gas sensing mechanism is discussed in terms of heterogeneous structure, morphology promotion, and energy band theory. It is believed that the sensing material with this structure has great potential for human health applications.

Mixed Potential Type Isoprene Sensor for the Application in Real-Time Monitoring of Biomarker Gases.

Monitoring of isoprene in exhaled breath is expected to provide a noninvasive and painless method for dynamic monitoring of physiological and metabolic states during exercise. However, for real-time and portable detection of isoprene, gas sensors have become the best choice for gas detection technology, which are crucial to achieving the goal of anytime, anywhere, human-centered healthcare in the future. Here, we first report a mixed potential type isoprene sensor based on a Gd2Zr2O7 solid electrolyte and a CdSb2O6 sensing electrode, which enables sensitive detection for isoprene with sensitivities of -21.2 mV/ppm and -65.8 mV/decade in the range of 0.05-1 and 1-100 ppm. The sensing behavior of the sensor follows the mixed potential sensing mechanism and was further verified by the electrochemical polarization curves. The significant differentiation between the sensor response to exhaled breath of healthy individuals and simulated breath containing different concentrations of isoprene demonstrates the potential of the sensor for the detection of isoprene in exhaled breath. Simultaneously, monitoring of isoprene during exercise signifies the feasibility of the sensor in dynamic monitoring of physiological indicators, which is not only of great significance for optimizing training and guiding therapeutic exercise intervention in sporting scenarios but also expected to help further reveal the interaction between exercise, muscle, and organ metabolism in medicine.

Highly Selective and Reversible Detection of Simulated Breath Hydrogen Sulfide Using Fe-Doped CuO Hollow Spheres: Enhanced Surface Redox Reaction by Multi-Valent Catalysts.

The precise and reversible detection of hydrogen sulfide (H2S) at high humidity condition, a malodorous and harmful volatile sulfur compound, is essential for the self-assessment of oral diseases, halitosis, and asthma. However, the selective and reversible detection of trace concentrations of H2S (≈0.1ppm) in high humidity conditions (exhaled breath) is challenging because of irreversible H2S adsorption/desorption at the surface of chemiresistors. The study reports the synthesis of Fe-doped CuO hollow spheres as H2S gas-sensing materials via spray pyrolysis. 4 at.% of Fe-doped CuO hollow spheres exhibit high selectivity (response ratio ≥ 34.4) over interference gas (ethanol, 1ppm) and reversible sensing characteristics (100% recovery) to 0.1ppm of H2S under high humidity (relative humidity 80%) at 175 °C. The effect of multi-valent transition metal ion doping into CuO on sensor reversibility is confirmed through the enhancement of recovery kinetics by doping 4 at.% of Ti- or Nb ions into CuO sensors. Mechanistic detailsof these excellent H2S sensing characteristics are also investigated by analyzing the redox reactions and the catalytic activity change of the Fe-doped CuO sensing materials. The selective and reversible detection of H2S using the Fe-doped CuO sensor suggested in this work opens a new possibility for halitosis self-monitoring.

High-Flow and Low-Flow Oxygen Delivery by Nasal Cannula Evaluated in Infant and Adult Airway Replicas.

The nasal cannula is widely regarded as a safe and effective means of administering low- and high-flow oxygen to patients irrespective of their age. However, variability in delivered oxygen concentration (FDO2 FDO2 ) via nasal cannula has the potential to pose health risks. The present study aimed to evaluate predictive equations for FDO2 over a large parameter space, including variation in breathing, oxygen flow, and upper-airway geometry representative of both young children and adults. Realistic nasal airway geometries were previously collected from medical scans of adults, infants, and neonates. Nasal airway replicas based on these geometries were used to measure the FDO2 for low-flow oxygen delivery during simulated spontaneous breathing. The present study extends previously published data sets to include higher oxygen flows. The extended data sets included nasal cannula oxygen flows that ranged from 6 to 65 L/min for the adult replicas, and from 0.5 to 6 L/min for the infant replicas. For both age groups, FDO2 was measured over a range of breathing frequencies, inspiratory to expiratory time ratios, and tidal volumes. Measured FDO2 values were compared with values predicted by using a previously derived flow-weighted equation. For both age groups, FDO2 was observed to increase nonlinearly with the ratio between oxygen flow supplied to the nasal cannula and the average inhalation flow. The previously derived flow-weighted equation over-predicted FDO2 at higher oxygen flows. A new empirical equation, therefore, was proposed to predict FDO2 for either age group as a function of nasal cannula flow, tidal volume, and inspiratory time. Predicted FDO2 values matched measured values, with average relative errors of 2.4% for infants and 4.3% for adults. A new predictive equation for FDO2 was obtained that accurately matched measured data in both adult and infant airway replicas for low- and high-flow regimens.

Microfluidics produced ATRA-loaded PLGA NPs reduced tuberculosis burden in alveolar epithelial cells and enabled high delivered dose under simulated human breathing pattern in 3D printed head models

Tuberculosis, caused by Mycobacterium tuberculosis (Mtb), is second only to COVID-19 as the top infectious disease killer worldwide. Multi-drug resistant TB (MDR-TB) may arise because of poor patient adherence to medications due to lengthy treatment duration and side effects. Delivering novel host directed therapies (HDT), like all trans retinoic acid (ATRA) may help to improve drug regimens and reduce the incidence of MDR-TB. Local delivery of ATRA to the site of infection leads to higher bioavailability and reduced systemic side effects. ATRA is poorly soluble in water and has a short half-life in plasma. Therefore, it requires a formulation step before it can be administered in vivo. ATRA loaded PLGA nanoparticles suitable for nebulization were manufactured and optimized using a scalable nanomanufacturing microfluidics (MF) mixing approach (MF-ATRA-PLGA NPs). MF-ATRA-PLGA NPs demonstrated a dose dependent inhibition of Mtb growth in TB-infected A549 alveolar epithelial cell model while preserving cell viability. The MF-ATRA-PLGA NPs were nebulized with the Aerogen Solo vibrating mesh nebulizer, with aerosol droplet size characterized using laser diffraction and the estimated delivered dose was determined. The volume median diameter (VMD) of the MF-ATRA-PLGA NPs was 3.00 ± 0.18 μm. The inhaled dose delivered in adult and paediatric 3D printed head models under a simulated normal adult and paediatric breathing pattern was found to be 47.05 ± 3 % and 20.15 ± 3.46 % respectively. These aerosol characteristics of MF-ATRA-PLGA NPs supports its suitability for delivery to the lungs via inhalation. The data generated on the efficacy of an inhalable, scalable and regulatory friendly ATRA-PLGA NPs formulation provides a foundation on which further pre-clinical testing can be built. Overall, the results of this project are promising for future research into ATRA loaded NPs formulations as inhaled host directed therapies for TB.

SERS-Based Hydrogen Bonding Induction Strategy for Gaseous Acetic Acid Capture and Detection.

Surface-enhanced Raman scattering (SERS) can overcome the existing technological limitations, such as complex processes and harsh conditions in gaseous small-molecule detection, and advance the development of real-time gas sensing at room temperature. In this study, a SERS-based hydrogen bonding induction strategy for capturing and sensing gaseous acetic acid is proposed for the detection demands of gaseous acetic acid. This addresses the challenges of low adsorption of gaseous small molecules on SERS substrates and small Raman scattering cross sections and enables the first SERS-based detection of gaseous acetic acid by a portable Raman spectrometer. To provide abundant hydrogen bond donors and acceptors, 4-mercaptobenzoic acid (4-MBA) was used as a ligand molecule modified on the SERS substrate. Furthermore, a sensing chip with a low relative standard deviation (RSD) of 4.15% was constructed, ensuring highly sensitive and reliable detection. The hydrogen bond-induced acetic acid trapping was confirmed by experimental spectroscopy and density functional theory (DFT). In addition, to achieve superior accuracy compared to conventional methods, an innovative analytical method based on direct response hydrogen bond formation (IO-H/Iref) was proposed, enabling the detection of gaseous acetic acid at concentrations as low as 60 ppb. The strategy demonstrated a superior anti-interference capability in simulated breath and wine detection systems. Moreover, the high reusability of the chip highlights the significant potential for real-time sensing of gaseous acetic acid.

Introducing a free-breathing MRI method to assess peri-operative myocardial oxygenation and function: A volunteer cohort study.

Induction of general anaesthesia has many potential triggers for peri-operative myocardial ischaemia including the acute disturbance of blood gases that frequently follows alterations in breathing and ventilation patterns. Free-breathing oxygenation-sensitive cardiovascular magnetic resonance (OS-CMR) imaging may provide the opportunity to continuously quantify the impact of such triggers on myocardial oxygenation. To investigate the impact of breathing patterns that simulate induction of general anaesthesia on myocardial oxygenation in awake healthy adults using continuous OS-CMR imaging. Prospective observational study. Single-centre university hospital. Recruitment from August 2020 to January 2022. Thirty-two healthy volunteers younger than 45 years old were recruited. Data were analysed from n = 29 (69% male individuals). Participants performed a simulated induction breathing manoeuvre consisting of 2.5 min paced breathing with a respiration rate of 14 breaths per minute, followed by 5 deep breaths, then apnoea for up to 60s inside a magnetic resonance imaging scanner (MRI). Cardiac images were acquired with the traditional OS-CMR sequence (OS bh-cine ), which requires apnoea for acquisition and with two free-breathing OS-CMR sequences: a high-resolution single-shot sequence (OS fb-ss ) and a real-time cine sequence (OS fb-rtcine ). Myocardial oxygenation response at the end of the paced breathing period and at the 30 s timepoint during the subsequent apnoea, reflecting the time of successful intubation in a clinical setting. The paced breathing followed by five deep breaths significantly reduced myocardial oxygenation, which was observed with all three techniques (OS bh-cine -6.0 ± 2.6%, OS fb-ss -12.0 ± 5.9%, OS fb-rtcine -5.4 ± 7.0%, all P < 0.05). The subsequent vasodilating stimulus of apnoea then significantly increased myocardial oxygenation (OS bh-cine 6.8 ± 3.1%, OS fb-ss 8.4 ± 5.6%, OS fb-rtcine 15.7 ± 10.0%, all P < 0.01). The free-breathing sequences were reproducible and were not inferior to the original sequence for any stage. Breathing manoeuvres simulating induction of general anaesthesia cause dynamic alterations of myocardial oxygenation in young volunteers, which can be quantified continuously with free-breathing OS-CMR. Introducing these new imaging techniques into peri-operative studies may throw new light into the mechanisms of peri-operative perturbations of myocardial tissue oxygenation and ischaemia. http://links.lww.com/EJA/A922.

Ultratrace eNose Sensing of VOCs toward Breath Analysis Applications Utilizing an eNose-Based Analyzer.

This proof-of-principle study presents the ability of the recently developed iLovEnose to measure ultratrace levels of volatile organic compounds (VOCs) in simulated human breath based on the combination of multiple gas sensors. The iLovEnose was developed by our research team as a test bed for gas sensors that can be hosted in three serially connected compact low-volume and temperature-controlled compartments. Herein, the eNose system was equipped with conventional semiconducting metal oxide (MOX) gas sensors using a variety of base technologies providing 11 different sensor signals that were evaluated to determine six VOCs of interest at eight low to ultralow concentration levels (i.e., ranging from 3 to 0.075 ppm) at humid conditions (90% rh at 22 °C). The measurements were randomized and performed four times over a period of 2 weeks. Partial least-squares regression analysis was applied to estimate the concentration of these six analytes. It was shown that the iLovEnose system is able to discriminate between these VOCs and provide reliable quantitative information relevant for future applications in exhaled breath analysis as a diagnostic disease detection or monitoring device.

Feasibility of a breath robot intervention to reduce sleep problems in posttraumatic stress disorder: protocol for a randomized controlled study

BackgroundMany patients with posttraumatic stress disorder (PTSD) suffer from sleep problems. Robot-based interventions might be an innovative approach to reduce sleep problems and hyperarousal in PTSD. However, the feasibility and effectiveness of a breath robot in patients with PTSD have never been empirically tested. The aim of this study is to investigate the feasibility of a breath robot to reduce sleep problems and hyperarousal in patients with PTSD.MethodsThis randomized controlled feasibility study will include N = 30 adult patients with at least subsyndromal PTSD (PTSD Symptom Scale – Interview-5 (PSSI-5)) according to the Diagnostic and Statistical Manual of Mental Disorders, 5th Edition (DSM-5) and impaired sleep quality (Pittsburgh Sleep Quality Index (PSQI) > 5). Patients with organic sleep disorders or currently in psychotherapeutic treatment are excluded. Study participants are randomized to receive either a 4-week Somnox 2 robot intervention including simulation of human breath or a 4-week Somnox 2 robot intervention without human breath simulation. The primary outcome will be the proportion of randomized participants providing outcome data at post-treatment. We consider a proportion of > 50% to indicate feasibility. Additional feasibility outcomes include eligibility rate, recruitment speed, uptake, retention, treatment adherence, and dropout. Potential outcomes of effectiveness (sleep quality, PSQI; severity of PTSD symptoms, PSSI-5) will be assessed at two time points, before (T0) and after (T1) the intervention. Sleep characteristics (Consensus Sleep Diary (CSD)) are measured daily.DiscussionThis study is the first to investigate the feasibility of a novel breath robot intervention for reducing sleep problems and hyperarousal in PTSD patients, with effectiveness considered as a secondary outcome. If feasible and effective, the use of a breath robot could be a nonintrusive and flexible intervention to supplement psychotherapy or to bridge treatment gaps.Trial registrationDRKS, DRKS00031063. Registered on 10/012023.

Deep Learning Enabled SERS Identification of Gaseous Molecules on Flexible Plasmonic MOF Nanowire Films.

Through the capture of a target molecule at the metal surface with a highly confined electromagnetic field induced by surface plasmon, surface enhanced Raman spectroscopy (SERS) emerges as a spectral analysis technology with high sensitivity. However, accurate SERS identification of a gaseous molecule with low density and high velocity is still a challenge due to its difficulty in capture. In this work, a flexible paper-based plasmonic metal-organic framework (MOF) film consisting of Ag nanowires@ZIF-8 (AgNWs@ZIF-8) is fabricated for SERS detection of gaseous molecules. Benefiting from its micronanopores generated by the nanowire network and ZIF-8 shell, the effective capture of the gaseous molecule is achieved, and its SERS spectrum is obtained in this paper-based flexible plasmonic MOF nanowire film. With optimal structure parameters, spectra of gaseous 4-aminothiophenol, 4-mercaptophenol, and dithiohydroquinone demonstrate that this film has good SERS performance, which could maintain obvious Raman signals within 30 days during reproducible detection. To realize SERS identification of gaseous molecules, deep learning is performed based on the SERS spectra of the mixed gaseous analyte obtained in this flexible porous film. The results point out that an artificial neural network algorithm could identify gaseous aldehydes (gaseous biomarker of colorectal cancer) in simulated exhaled breath with high accuracy at 93.7%. The integration of the flexible paper-based film sensors with deep learning offers a promising new approach for noninvasive colorectal cancer screening. Our work explores SERS applications in gaseous analyte detection and has broad potential in clinical medicine, food safety, environmental monitoring, etc.

Can physical parameters from radiation simulation scan with deep inspiratory breath hold predict magnitude of heart dose reduction?

ABSTRACT Introduction: Deep inspiratory breath hold is one of the techniques for reducing the heart doses for left breast cancers. This study was conducted to confirm use of physical parameters from DIBH simulation CT scan like DIBH amplitude alongside several novel parameters to predict the heart dose reduction. Materials and Methods: Segmentation and planning of radiation to the left breast on the free breathing (FB) and DIBH simulation scan was performed for 50 left-sided breast cancer patients treated with DIBH technique. Physical parameters, namely DIBH amplitude, anterior sternal displacement, diaphragmatic excursion, ratio of lung volume (cc) in DIBH scan to lung volume in FB scan (cc), and delta heart volume in field (DHVIF), were extracted and were compared with magnitude of heart dose reduction (mean heart dose, V30Gy, and D5%). Results: Forty-eight (96%) patients achieved reduction in the mean heart dose with DIBH technique, while all patients had reduction in V30Gy. The median reduction was 41%, 89.7%, and 63% in the mean dose, V30Gy, and D5%, respectively. While DIBH did not correlate with heart dose reduction, ratio of lung volumes and DHVIF showed a strong positive correlation with heart dose reduction (P &lt; 0.05). Sternal displacement correlated weakly with heart dose reduction but strongly with DHVIF, demonstrating to be an indirect predictor. Conclusions: Physical parameters like anterior sternal displacement, ratio of lung volumes of DIBH to FB, and possibly diaphragmatic movement can predict the dose reduction before the dose calculations by the physicist. These parameters can be used to construct a model to predict heart dose reduction.

Self-powered triboelectric nanogenerator sensor for detecting humidity level and monitoring ethanol variation in a simulated exhalation environment

Respiration stands as a vital process reflecting physiological and pathological human health status. Exhaled breath analysis offers a facile, non-invasive, swift, and cost-effective approach for diagnosing and monitoring diseases by detecting concentration changes of specific biomarkers. In this study, we employed Polyethylene oxide/copper (I) oxide composite nanofibers (PCNFs), synthesized via the electrospinning method as the sensing material to measure ethanol levels (1–200 ppm) in an exhaled breath simulator environment. The integrated contact-separation triboelectric nanogenerator was utilized to power the self-powered PCNFs exhaled breath sensor. The PCNFs-based gas sensor demonstrates promising results with values of 0.9 and 3.2 for detecting 5 ppm and 200 ppm ethanol, respectively, in the presence of interfering gas at 90% relative humidity (RH). Notably, the sensor displayed remarkable ethanol selectivity, with ratios of 10:1 to methanol and 25:1 to acetone. Response and recovery times for 200 ppm ethanol at 90 RH% were rapid, at 2.7 s and 5.8 s, respectively. The PCNFs-based exhaled breath sensor demonstrated consistent and stable performance in practical conditions, showcasing its potential for integration into wearable devices. This self-powered breath sensor enabling continuous monitoring of lung cancer symptoms and facilitating compliance checks with legal alcohol consumption limits.

Increasing the Catalytic Activity of Co3O4 via Boron Doping and Chemical Reduction for Enhanced Acetone Detection

AbstractOptimally increasing the catalytic activity of Co3O4‐based materials is crucial for promoting their practical applications for acetone detection; however, this still remains challenging. Herein, a strategy is proposed in this work to increase the catalytic activity of Co3O4 toward the oxidation of acetone through the synergistic effect of boron doping and chemical reduction, which can substantially improve the sensing performance for acetone detection. The characterization results confirm that the present strategy facilitates the formation of more oxygen vacancies and increases the content of Co2+ ions serving as active sites. As expected, the optimal sensor yields a higher response . To extend the practical application to the auxiliary diagnosis of diabetes through exhaled breath, the optimal sensors distinguished between acetone concentrations in the breath of healthy individuals and in the simulated breath of patients with diabetes. Detailed gas‐sensing measurements reveal that the enhanced acetone sensing performance is attributed to the increased catalytic activity of materials for oxidation of acetone by the Mars–van Krevelen, Langmuir–Hinshelwood, and Eley–Rideal mechanisms. This study provides new insights into the fabrication of high‐performance metal oxide‐based gas sensors by improving the catalytic activity of sensing materials.

Breathing mode assessment with thermography: a pilot study.

To present a method for analyzing breathing modes with infrared thermography. This exploratory cross-sectional study used 38 thermal images of inspiration and expiration with nasal breathing and simulated mouth breathing in four nasal breathers without respiratory complaints. Three different data selection forms (line, rectangle, and ellipse) were used to extract the minimum, mean, and maximum temperatures of the regions of interest (nose and mouth) using the FLIR Tools® software. Among the three selection forms, there was greater temperature variability obtained with the line, revealing limitations in this measurement. There were no differences between the rectangle and ellipse values, showing that both selection forms present similar temperature extraction results. The comparison results between nose and mouth temperatures during inspiration and expiration indicated a statistically significant difference between all measurements, except for mean inspiration temperatures with the rectangle and ellipse. The breathing mode can be distinguished in both inspiration and expiration when using mean mouth temperatures with the rectangle and ellipse. Breathing modes should be assessed based on mean mouth temperatures during inspiration, using the ellipse.

Detection of severe acute respiratory syndrome coronavirus 2 in bioaerosols using digital droplet polymerase chain reaction and loop-mediated isothermal amplification

In the present study, we simulated human passive breathing, sampled severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) bioaerosols, and compared the detection ability of quantitative polymerase chain reaction (qPCR), digital...

Avaliação do modo respiratório por meio da termografia: um estudo piloto

ABSTRACT Purpose To present a method for analyzing breathing modes with infrared thermography. Methods This exploratory cross-sectional study used 38 thermal images of inspiration and expiration with nasal breathing and simulated mouth breathing in four nasal breathers without respiratory complaints. Three different data selection forms (line, rectangle, and ellipse) were used to extract the minimum, mean, and maximum temperatures of the regions of interest (nose and mouth) using the FLIR Tools® software. Results Among the three selection forms, there was greater temperature variability obtained with the line, revealing limitations in this measurement. There were no differences between the rectangle and ellipse values, showing that both selection forms present similar temperature extraction results. The comparison results between nose and mouth temperatures during inspiration and expiration indicated a statistically significant difference between all measurements, except for mean inspiration temperatures with the rectangle and ellipse. The breathing mode can be distinguished in both inspiration and expiration when using mean mouth temperatures with the rectangle and ellipse. Conclusion Breathing modes should be assessed based on mean mouth temperatures during inspiration, using the ellipse.

Graphene and metal-organic framework hybrids for high-performance sensors for lung cancer biomarker detection supported by machine learning augmentation.

Conventional diagnostic methods for lung cancer, based on breath analysis using gas chromatography and mass spectrometry, have limitations for fast screening due to their limited availability, operational complexity, and high cost. As potential replacement, among several low-cost and portable methods, chemoresistive sensors for the detection of volatile organic compounds (VOCs) that represent biomarkers of lung cancer were explored as promising solutions, which unfortunately still face challenges. To address the key problems of these sensors, such as low sensitivity, high response time, and poor selectivity, this study presents the design of new chemoresistive sensors based on hybridised porous zeolitic imidazolate (ZIF-8) based metal-organic frameworks (MOFs) and laser-scribed graphene (LSG) structures, inspired by the architecture of the human lung. The sensing performance of the fabricated ZIF-8@LSG hybrid sensors was characterised using four dominant VOC biomarkers, including acetone, ethanol, methanol, and formaldehyde, which are identified as metabolomic signatures in lung cancer patients' exhaled breath. The results using simulated breath samples showed that the sensors exhibited excellent performance for a set of these biomarkers, including fast response (2-3 seconds), a wide detection range (0.8 ppm to 50 ppm), a low detection limit (0.8 ppm), and high selectivity, all obtained at room temperature. Intelligent machine learning (ML) recognition using the multilayer perceptron (MLP)-based classification algorithm was further employed to enhance the capability of these sensors, achieving an exceptional accuracy (approximately 96.5%) for the four targeted VOCs over the tested range (0.8-10 ppm). The developed hybridised nanomaterials, combined with the ML methodology, showcase robust identification of lung cancer biomarkers in simulated breath samples containing multiple biomarkers and a promising solution for their further improvements toward practical applications.

Self-Healing, Laminated, and Low Resistance NH3 Sensor Based on 6,6',6″-(Nitrilotris(benzene-4,1-diyl))tris(5-phenylpyrazine-2,3-dicarbonitrile) Sensing Material Operating at Room Temperature.

With the rapid development of the concept of the Internet of Things (IoT), gas sensors with the function of simulating the human sense of smell became irreplaceable as a key element. Among them, ammonia (NH3) sensors played an important role in respiration tests, environmental monitoring, safety, and other fields. However, the fabrication of the high-performance device with high stability and resistance to mechanical damages was still a challenge. In this work, polyurethane (PU) with excellent self-healing ability was applied as the substrate, and the sensor was designed from new sensitive material design and device structure optimization, through applying the organic molecule with groups which could absorb NH3 and the laminated structure to shorten the electronic transmission path to achieve a low resistance state and favorable sensing properties. Accordingly, a room temperature flexible NH3 sensor based on 6,6',6″-(nitrilotris(benzene-4,1-diyl))tris(5-phenylpyrazine-2,3-dicarbonitrile) (TPA-3DCNPZ) was successfully developed. The device could self-heal by means of a thermal evaporation assisted method. It exhibited a detection limit of 1 ppm at 98% relative humidity (RH), as well as great stability, selectivity, bending flexibility, and self-healing properties. The improved NH3 sensing performance under high RH was further investigated by complex impedance plots (CIPs) and density functional theory (DFT), attributing to the enhanced adsorption of NH3. The TPA-3DCNPZ based NH3 sensors proved to have great potential for application on simulated exhaled breath to determine the severity of kidney diseases and the progress of treatment. This work also provided new ideas for the construction of high-performance room temperature NH3 sensors.

Aerosol and surface contamination assessment of a novel ventilated infectious aerosol containment device.

Healthcare personnels (HCPs) are at risk of respiratory infectious diseases during patient care activities. HCPs rely primarily on personal protective equipment to prevent pathogen exposures, but there is a need to develop alternative, or complementary control strategies, including engineering controls. The objective of this study was to evaluate the ability of the 3 designs (denoted D1A, D1B, and D2) of the University of Utah Containment Ventilation for Exposure Reduction (U-COVER), a protective barrier enclosure device to contain respirable aerosols when placed over a simulated patient. The 2 primary performance metrics were the percent reduction in: (i) the concentration of respirable aerosols in the simulated breathing zone of an HCP, and (ii) surface contamination outside the device, which were tested using salt aerosols and fluorescein aerosols, respectively. Briefly, salt or fluorescein aerosols were generated as though expelled by a prone patient under 3 conditions: (i) no device (control), (ii) with the device but without exhaust ventilation, and (iii) with the device with exhaust ventilation. Device D2 was also tested under simulated use conditions, in which cardboard "arms" were placed inside the device ports. All 3 device designs showed the ability to reduce particle concentrations in the simulated HCP breathing zone and on surfaces by >99% with exhaust ventilation compared to the control condition. Without exhaust ventilation, device performance was lower and highly variable. Under simulated use conditions, device D2 reduced particle concentrations in the simulated HCP breathing zone by ≥91% and on surfaces by >99% relative to control for all combinations of "arms" tested. The U-COVER device demonstrates excellent aerosol containment and warrants further testing with dynamic simulated or actual use conditions.