Arterial Gas Embolism in Breath-Hold Diver.

An arterial gas embolism (AGE) is a potentially fatal complication of scuba diving that is related to insufficient exhalation during ascent. During breath-hold diving, an arterial gas embolism is unlikely because the volume of gas in the lungs generally cannot exceed the volume at the beginning of the dive. However, if a diver breathes from a gas source at any time during the dive, they are at risk for an AGE or other pulmonary overinflation syndromes (POIS). In this case report, a breath-hold diver suffered a suspected AGE due to rapidly ascending without exhalation following breathing from an air pocket at approximately 40 feet.

Unobtrusive Sensors for Synchronous Monitoring of Different Breathing Parameters in Care Environments.

Respiratory problems are common amongst older people. The rapid increase in the ageing population has led to a need for developing technologies that can monitor such conditions unobtrusively. This paper presents a novel study that investigates Wi-Fi and ultra-wideband (UWB) antenna sensors to simultaneously monitor two different breathing parameters: respiratory rate, and exhaled breath. Experiments were carried out with two subjects undergoing three breathing cases in breaths per minute (BPM): (1) slow breathing (12 BPM), (2) moderate breathing (20 BPM), and (3) fast breathing (28 BPM). Respiratory rates were captured by Wi-Fi sensors, and the data were processed to extract the respiration rates and compared with a metronome that controlled the subjects' breathing. On the other hand, exhaled breath data were captured by a UWB antenna using a vector network analyser (VNA). Corresponding reflection coefficient data (S11) were obtained from the subjects at the time of exhalation and compared with S11 in free space. The exhaled breath data from the UWB antenna were compared with relative humidity, which was measured with a digital psychrometer during the breathing exercises to determine whether a correlation existed between the exhaled breath's water vapour content and recorded S11 data. Finally, captured respiratory rate and exhaled breath data from the antenna sensors were compared to determine whether a correlation existed between the two parameters. The results showed that the antenna sensors were capable of capturing both parameters simultaneously. However, it was found that the two parameters were uncorrelated and independent of one another.

Flexible Chitosan-Based Capacitive Humidity Sensors for Respiratory Monitoring.

As one of the most important human health indicators, respiratory status is an important basis for the diagnosis of many diseases. However, the high cost of respiratory monitoring makes its use uncommon. This study introduces a low-cost, wearable, flexible humidity sensor for respiratory monitoring. Solution-processed chitosan (CS) placed on a polyethylene terephthalate substrate was used as the sensing layer. An Arduino circuit board was used to read humidity-sensitive voltage changes. The CS-based sensor demonstrated capacitive humidity sensitivity, whereby the capacitance instantly increased from 10-2 to 30 nF when the environmental humidity changed from 43% to 97%. The capacitance logarithm sensitivity and response voltage change was 35.9 pF/%RH and 0.8 V in the RH range from 56% to 97%. And the voltage variation between inhalation and exhalation was ~0.5 V during normal breathing. A rapid response time of ~0.7 s and a recovery time of ~2 s were achieved during respiration testing. Breathing modes (i.e., normal breathing, rest breathing, deep breathing, and fast breathing) and tonal changes during speech could be clearly distinguished. Therefore, such sensors provide a means for economical and convenient wearable respiratory monitoring, and they have the potential to be used for daily health examinations and professional medical diagnoses.

Quantifying exhaled acetone and isoprene through solid phase microextraction and gas chromatography-mass spectrometry.

BACKGROUND: Acetone, isoprene, and other volatile organic compounds (VOCs) in exhaled breath have been shown to be biomarkers for many medical conditions. Researchers use different techniques for VOC detection, including solid phase microextraction (SPME), to preconcentrate volatile analytes prior to instrumental analysis by gas chromatography-mass spectrometry (GC-MS). These techniques include a previously developed method to detect VOCs in breath directly using SPME, but it is uncommon for studies to quantify exhaled volatiles because it can be time consuming due to the need of many external/internal standards, and there is no standardized or widely accepted method. The objective of this study was to develop an accessible method to quantify acetone and isoprene in breath by SPME GC-MS. RESULTS: A system was developed to mimic human exhalation and expose VOCs to a SPME fiber in the gas phase at known concentrations. VOCs were bubbled/diluted with dry air at a fixed flow rate, duration, and volume that was comparable to a previously developed breath sampling method. Identification of acetone and isoprene through GC-MS was verified using standards and observing overlaps in chromatographic retention/mass spectral fragmentation. Calibration curves were developed for these two analytes, which showed a high degree of linear correlation. Acetone and isoprene displayed limits of detection/quantification equal to 12 ppb/37 ppb and 73 ppb/222 ppb respectively. Quantification results in healthy breath samples (n = 15) showed acetone concentrations spanned between 71 ppb and 294 ppb, and isoprene varied between 170 ppb and 990 ppb. Both concentration ranges for acetone and isoprene in this study overlap with those reported in existing literature. SIGNIFICANCE: Results indicate the development of a system to quantify acetone and isoprene in breath that can be adapted to diverse sampling methods and instrumental analyses beyond SPME GC-MS.

Relationship Between Diaphragm Thickness, Thickening Fraction, Dome Excursion, and Respiratory Pressures in Healthy Subjects: An Ultrasound Study.

PURPOSE: Diaphragm ultrasonography is used to identify causes of diaphragm dysfunction. However, its correlation with pulmonary function tests, including maximal inspiratory (MIP) and expiratory pressures (MEP), remains unclear. This study investigated this relationship by measuring diaphragm thickness, thickening fraction (TF), and excursion (DE) using ultrasonography, and their relationship to MIP and MEP. It also examined the influence of age, sex, height, and BMI on these measures. METHODS: We recruited healthy Japanese volunteers and conducted pulmonary function tests and diaphragm ultrasonography in a seated position. Diaphragm ultrasonography was performed during quiet breathing (QB) and deep breathing (DB) to measure the diaphragm thickness, TF, and DE. A multivariate analysis was conducted, adjusting for age, sex, height, and BMI. RESULTS: Between March 2022 and January 2023, 109 individuals (56 males) were included from three facilities. The mean (standard deviation) MIP and MEP [cmH2O] were 72.2 (24.6) and 96.9 (35.8), respectively. Thickness [mm] at the end of expiration was 1.7 (0.4), TF [%] was 50.0 (25.9) during QB and 110.7 (44.3) during DB, and DE [cm] was 1.7 (0.6) during QB and 4.4 (1.4) during DB. Multivariate analysis revealed that only DE (DB) had a statistically significant relationship with MIP and MEP (p = 0.021, p = 0.008). Sex, age, and BMI had a statistically significant influence on relationships between DE (DB) and MIP (p = 0.008, 0.048, and < 0.001, respectively). CONCLUSION: In healthy adults, DE (DB) has a relationship with MIP and MEP. Sex, age, and BMI, but not height, are influencing factors on this relationship.

Review of the research status on the transmission and diffusion characteristics of indoor viral aerosol particles.

This study reviews the generation and diffusion characteristics of indoor viral aerosol particles, numerical simulation methods for the diffusion process of viral aerosols, and related research on the impact mechanism of different ventilation methods on the diffusion process of viral aerosols. Research has shown that the selection of initial conditions such as exhalation mode, initial airflow velocity, particle size, turbulence model, and calculation method for the generation of aerosol particles by the human body is of great significance for the numerical simulation of the diffusion process of viral aerosol particles. At the same time, on the basis of selecting appropriate ventilation methods, the reasonable setting of ventilation parameters (temperature, speed, height, etc.) can effectively suppress the spread of viral aerosols. This study can provide a theoretical basis for the study of related respiratory diseases, as well as technical and theoretical support for the selection of indoor ventilation methods to reduce the risk of human exposure caused by viral aerosols in the construction field. It also provides guidance and reference for aerosol transport and environmental protection in indoor atmospheric environments.

Analyzing key elements of breathing patterns, deriving remaining variables, and identifying cutoff values in individuals with chronic respiratory disease and healthy subjects.

BACKGROUND: Pulmonary physiology encompasses intricate breathing patterns (BPs), characterized by breathing frequency (Bf), volumes, and flows. The complexities intensify in the presence of interstitial lung disease (ILD) and chronic obstructive pulmonary disease (COPD), especially during exercise. This study seeks to identify pivotal factors driving changes among these variables and establish cutoff values, comparing their efficacy in differentiating BPs to traditional methods, specifically a breathing reserve (BR) of 30% and a Bf of 50 bpm. METHODS: Screening 267 subjects revealed 23 with ILD, 126 with COPD, 33 healthy individuals, and the exclusion of 85 subjects. Lung function tests and ramp-pattern cardiopulmonary exercise testing (CPET) were conducted, identifying crucial BP elements. Changes were compared between groups at peak exercise. The area under the receiver operating characteristic curve (AUC) analysis determined cutoff values. RESULTS: Inspiratory time (TI) remained constant at peak exercise for all subjects (two-group comparisons, all p=NS). Given known differences in expiratory time (TE) and tidal volume (VT) among ILD, COPD, and healthy states, constant TI could infer patterns for Bf, total breathing cycle time (TTOT=60/Bf), I:E ratio, inspiratory duty cycle (IDC, TI/TTOT), rapid shallow breathing index (Bf/VT), tidal inspiratory and expiratory flows (VT/TI and VT/TE), and minute ventilation (V̇E=Bf×VT) across conditions. These inferences aligned with measurements, with potential type II errors causing inconsistencies. RSBI of 23 bpm/L and VT/TI of 104 L/min may differentiate ILD from control, while V̇E of 54 L/min, BR of 30%, and VT/TE of 108 may differentiate COPD from control. BR of 21%, TE of 0.99 s, and IDC of .45 may differentiate ILD from COPD. The algorithm outperformed traditional methods (AUC 0.84-0.91 versus 0.59-0.90). CONCLUSION: The quasi-fixed TI, in conjunction with TE and VT, proves effective in inferring time-related variables of BPs. The findings have the potential to significantly enhance medical education in interpreting cardiopulmonary exercise testing. Moreover, the study introduces a novel algorithm for distinguishing BPs among individuals with ILD, COPD, and those who are healthy.

Breath Measurement Method for Synchronized Reproduction of Biological Tones in an Augmented Reality Auscultation Training System.

An educational augmented reality auscultation system (EARS) is proposed to enhance the reality of auscultation training using a simulated patient. The conventional EARS cannot accurately reproduce breath sounds according to the breathing of a simulated patient because the system instructs the breathing rhythm. In this study, we propose breath measurement methods that can be integrated into the chest piece of a stethoscope. We investigate methods using the thoracic variations and frequency characteristics of breath sounds. An accelerometer, a magnetic sensor, a gyro sensor, a pressure sensor, and a microphone were selected as the sensors. For measurement with the magnetic sensor, we proposed a method by detecting the breathing waveform in terms of changes in the magnetic field accompanying the surface deformation of the stethoscope based on thoracic variations using a magnet. During breath sound measurement, the frequency spectra of the breath sounds acquired by the built-in microphone were calculated. The breathing waveforms were obtained from the difference in characteristics between the breath sounds during exhalation and inhalation. The result showed the average value of the correlation coefficient with the reference value reached 0.45, indicating the effectiveness of this method as a breath measurement method. And the evaluations suggest more accurate breathing waveforms can be obtained by selecting the measurement method according to breathing method and measurement point.

Exhaled nitric oxide levels in COPD patients who use electronic cigarettes.

Emerging data from clinical studies have shown pro-inflammatory effects associated with e-cigarette use. Fractional exhaled nitric oxide (FeNO) is a biomarker of pulmonary type 2 (T2) inflammation. The effect of chronic e-cigarette use on FeNO is unclear. The aim of this study was to compare FeNO levels in COPD ex-smokers who use e-cigarettes (COPDE + e-cig) to COPDE ex-smokers (COPDE) and COPD current smokers (COPDS). FeNO levels were significantly higher in COPDE + e-cig (median 16.2 ppb) and COPDE (median 18.0 ppb) compared to COPDS (median 7.6 ppb) (p = 0.0003 and p < 0.0001 respectively). There was no difference in FeNO levels between COPDE + e-cig compared to COPDE (p > 0.9). The importance of our results is that electronic cigarette use does not alter the interpretation of FeNO results, and so does not interfere with the use of FeNO as a practical biomarker of T2 inflammation, unlike current cigarette smoking in COPD. Whilst the effect of electronic cigarette use on FeNO levels is not the same as cigarette smoke, this cannot be taken as evidence that electronic cigarettes are harmless. These differential pulmonary effects can be attributed to differences in the chemical composition of the two products.

Predicting parameters of airway dynamics generated from inspiratory and expiratory plethysmographic airway loops, differentiating subtypes of chronic obstructive diseases.

BACKGROUND: The plethysmographic shift volume-flow loop (sRaw-loop) measured during tidal breathing allows the determination of several lung function parameters such as the effective specific airway resistance (sReff), calculated from the ratio of the integral of the resistive aerodynamic specific work of breathing (sWOB) and the integral of the corresponding flow-volume loop. However, computing the inspiratory and expiratory areas of the sRaw-loop separately permits the determination of further parameters of airway dynamics. Therefore, we aimed to define the discriminating diagnostic power of the inspiratory and expiratory sWOB (sWOBin, sWOBex), as well as of the inspiratory and expiratory sReff (sReff IN and sReff EX), for discriminating different functional phenotypes of chronic obstructive lung diseases. METHODS: Reference equations were obtained from measurement of different databases, incorporating 194 healthy subjects (35 children and 159 adults), and applied to a collective of 294 patients with chronic lung diseases (16 children with asthma, aged 6-16 years, and 278 adults, aged 17-92 years). For all measurements, the same type of plethysmograph was used (Jaeger Würzburg, Germany). RESULTS: By multilinear modelling, reference equations of sWOBin, sWOBex, sReff IN and sReff EX were derived. Apart from anthropometric indices, additional parameters such as tidal volume (VT), the respiratory drive (P0.1), measured by means of a mouth occlusion pressure measurement 100 ms after inspiration and the mean inspiratory flow (VT/TI) were found to be informative. The statistical approach to define reference equations for parameters of airway dynamics reveals the interrelationship between covariants of the actual breathing pattern and the control of breathing. CONCLUSIONS: We discovered that sWOBin, sWOBex, sReff IN and sReff EX are new discriminating target parameters, that differentiate much better between chronic obstructive diseases and their subtypes, especially between chronic obstructive pulmonary disease (COPD) and asthma-COPD overlap (ACO), thus strengthening the concept of precision medicine.

New perspectives on 'Breathomics': metabolomic profiling of non-volatile organic compounds in exhaled breath using DI-FT-ICR-MS.

Breath analysis offers tremendous potential for diagnostic approaches, since it allows for easy and non-invasive sample collection. "Breathomics" as one major research field comprehensively analyses the metabolomic profile of exhaled breath providing insights into various (patho)physiological processes. Recent research, however, primarily focuses on volatile compounds. This is the first study that evaluates the non-volatile organic compounds (nVOCs) in breath following an untargeted metabolomic approach. Herein, we developed an innovative method utilizing a filter-based device for metabolite extraction. Breath samples of 101 healthy volunteers (female n = 50) were analysed using DI-FT-ICR-MS and biostatistically evaluated. The characterisation of the non-volatile core breathome identified more than 1100 metabolites including various amino acids, organic and fatty acids and conjugates thereof, carbohydrates as well as diverse hydrophilic and lipophilic nVOCs. The data shows gender-specific differences in metabolic patterns with 570 significant metabolites. Male and female metabolomic profiles of breath were distinguished by a random forest approach with an out-of-bag error of 0.0099. Additionally, the study examines how oral contraceptives and various lifestyle factors, like alcohol consumption, affect the non-volatile breathome. In conclusion, the successful application of a filter-based device combined with metabolomics-analyses delineate a non-volatile breathprint laying the foundation for discovering clinical biomarkers in exhaled breath.

[Subjective and objective comparative analysis of nasal ventilation function before and after nasal septoplasty].

Objective:To investigate the changes of nasal ventilation before and after septoplasty by using NOSE scoring scale and nasal function examination, and to explore the correlation between subjective nasal obstruction and nasal function examination and its clinical application value. Methods:A total of 129 cases of nasal septum deviation from December 2021 to April 2023 in our hospital were selected for study. All patients underwent septoplasty. Nasal obstruction symptom evaluation（NOSE） was performed in all patients before surgery and 3 months after surgery. nasal minimal cross-sectional area（MCA） and nasal cavity volume（NCV） were recorded by nasal acoustic reflex, nasal resistance meter and nasal respiration apparatus, nasal resistance（NR）, distance between the nostril to minimum cross-sectional area,（the distance between the nostril to minimum cross-sectional area, MD）, nasal inspiratory volume（IV）, nasal expiratory volume（EV）, the nasal partitioning ratio, NPR includes objective indicators such as inspiratory volume difference ratio（NPRi） and expiratory volume difference ratio（NPRe）. Paired test was used to compare and analyze the changes of various indicators before and after surgery, and the difference（P<0.05） was statistically significant, and Pearson correlation linear analysis was used to analyze the correlation between subjective and objective indicators. Results:There were statistically significant differences in NOSE score, NCV, NR, MD, EV, IV, NPRe and NPRi of 129 patients before and after surgery（P<0.05）, while there was no statistically significant difference between MCA before and after surgery（P>0.05）. Preoperative NOSE score was correlated with NR, NCV, EV, IV, NPRe and NPRi（P<0.05）, but not with MD and MCA（P>0.05）. There was correlation between NOSE score and NR, MCA, NCV, EV, IV, NPRe and NPRi（P<0.05）, but no correlation between nose score and MD（P>0.05）. Conclusion:The subjective NOSE scale combined with nasal function test has certain clinical reference value in evaluating the surgical effect of patients with deviated nasal septum.

Lung cancer detection in perioperative patients' exhaled breath with nanomechanical sensor array.

INTRODUCTION: Breath analysis using a chemical sensor array combined with machine learning algorithms may be applicable for detecting and screening lung cancer. In this study, we examined whether perioperative breath analysis can predict the presence of lung cancer using a Membrane-type Surface stress Sensor (MSS) array and machine learning. METHODS: Patients who underwent lung cancer surgery at an academic medical center, Japan, between November 2018 and November 2019 were included. Exhaled breaths were collected just before surgery and about one month after surgery, and analyzed using an MSS array. The array had 12 channels with various receptor materials and provided 12 waveforms from a single exhaled breath sample. Boxplots of the perioperative changes in the expiratory waveforms of each channel were generated and Mann-Whitney U test were performed. An optimal lung cancer prediction model was created and validated using machine learning. RESULTS: Sixty-six patients were enrolled of whom 57 were included in the analysis. Through the comprehensive analysis of the entire dataset, a prototype model for predicting lung cancer was created from the combination of array five channels. The optimal accuracy, sensitivity, specificity, positive predictive value, and negative predictive value were 0.809, 0.830, 0.807, 0.806, and 0.812, respectively. CONCLUSION: Breath analysis with MSS and machine learning with careful control of both samples and measurement conditions provided a lung cancer prediction model, demonstrating its capacity for non-invasive screening of lung cancer.

Influence of earthquake on radon exhalation law at the beach of the uranium tailing reservoir under high temperature environment.

In this paper, the influence of an earthquake on radon exhalation rate of uranium tailings reservoir beach under high temperature environment is studied by using a self-made integrated simulation test device for natural disasters, and a scale model test based on similarity and dimensional laws. The results show that, (1)When the peak acceleration reaches 0.6g, the radon exhalation rate increases sharply with the increase of peak acceleration, and tends to be gentle after 1.0g. (2)Under the action of high temperature, the radon exhalation rate increases rapidly with the increase of high temperature time, and gradually becomes flat after the 4th hour. (3)Compared with loading the earthquake condition only, the coupling effect of high temperatures and earthquakes causes a greater degree of damage to the beach surface of a uranium tailings reservoir under the same acceleration conditions, and the fissure rate and radon exhalation rate of the beach surface are substantially increased.

Instrumental Assessment of Aero-Resistive Expiratory Muscle Strength Rehabilitation Devices.

PURPOSE: Expiratory muscle strength training (EMST) is increasingly being used to treat voice, cough, and swallowing deficits in a wide range of conditions. However, a multitude of aero-resistive EMST models are commercially available, and the absence of side-by-side comparative data interferes with clinicians' ability to assess which model is best suited to a particular client's needs. The primary aim of this research was to test and compare the pressure and flow parameters of six currently available EMST models to help inform clinical decision making. METHOD: We identified and tested five devices of each of six different EMST models to generate benchmark data for minimum trigger pressures across settings. The reliability was tested within each device and between five devices of the same model across settings using coefficient of variation. RESULTS: All six models required higher pressures to initiate flow at the highest setting compared to the lowest setting, as expected. Detailed descriptive statistics for each model/setting combination include average flow-triggering pressure for each model/setting and the variability across trials within a device and across devices of the same model. From these, ranked order of the least to most stable EMST model was derived. CONCLUSIONS: Systematic testing of several commercially available expiratory resistance training devices yielded clinical benchmarks and reliability data to aid clinicians in selecting an appropriate therapy device and regimen for a client based on their available airflow and air pressure as well as reliability of the device. These findings allow clinicians to directly compare key parameters across EMST devices.

Isoproterenol modulates expiratory activities in the brainstem spinal cord preparation in neonatal mice in vitro.

Motor behaviors such as breathing required temporal coordination of different muscle groups to insured efficient ventilation and provide oxygen to the body. This action is the result of interactions between neural networks located within the brainstem. Inspiration and expiration depend at least in part on interactions between two separate oscillators: inspiration is driven by a neural network located in the preBötzinger complex (PreBötC) and active expiration is driven by a network in the parafacial respiratory group (pFRG). Neurons of the pFRG are silent at rest and become active when the respiratory drive increased. This study investigated the temporal coordination between the brainstem respiratory network and the lumbar spinal network that generates spontaneous activities that is different of the induced fictive locomotion. The remaining question is how these activities coordinate early during the development. Results of this study show that brainstem networks contribute to the temporal coordination of the lumbar spontaneous activity during inspiration since lumbar motor activity occurs exclusively during the expiratory time. This study also investigated the role of the ß-noradrenergic modulation on the respiratory activities. ß-noradrenergic receptors activation increased the frequency of the double bursts and increased expiratory activity at the lumbar level. These results suggest interactions between brainstem and spinal networks and reveal a descending drive that may contribute to the coordination of the respiratory and lumbar spontaneous activities.

A Clinical Breathomics Dataset.

This study entailed a comprehensive GC‒MS analysis conducted on 121 patient samples to generate a clinical breathomics dataset. Breath molecules, indicative of diverse conditions such as psychological and pathological states and the microbiome, were of particular interest due to their non-invasive nature. The highlighted noninvasive approach for detecting these breath molecules significantly enhances diagnostic and monitoring capacities. This dataset cataloged volatile organic compounds (VOCs) from the breath of individuals with asthma, bronchiectasis, and chronic obstructive pulmonary disease. Uniform and consistent sample collection protocols were strictly adhered to during the accumulation of this extensive dataset, ensuring its reliability. It encapsulates extensive human clinical breath molecule data pertinent to three specific diseases. This consequential clinical breathomics dataset is a crucial resource for researchers and clinicians in identifying and exploring important compounds within the patient's breath, thereby augmenting future diagnostic and therapeutic initiatives.

Potential exhaled breath biomarkers identified in chlorine-exposed mice.

Exhaled breath (EB) contains various volatile organic compounds (VOCs) that can indicate specific biological or pathological processes in the body. Analytical techniques like gas chromatography-mass spectrometry (GC-MS) can be used to detect and measure these exhaled biomarkers. In this study, the objective was to develop a non-invasive method of EB sampling in animals that were awake, as well as to analyze EB for volatile biomarkers specific for chlorine exposure and/or diagnostic biomarkers for chlorine-induced acute lung injury (ALI). To achieve this, a custom-made sampling device was used to collect EB samples from 19 female Balb/c mice. EB was sampled both pre-exposure (serving as internal control) and 30 min after exposure to chlorine. EB was collected on thermal desorption tubes and subsequently analyzed for VOCs by GC-MS. The following day, the extent of airway injury was assessed in the animals by examining neutrophils in the bronchoalveolar lavage fluid. VOC analysis revealed alterations in the EB biomarker pattern post-chlorine exposure, with eight biomarkers displaying increased levels and six exhibiting decreased levels following exposure. Four chlorinated compounds: trichloromethane, chloroacetone, 1,1-dichloroacetone and dichloroacetonitrile, were increased in chlorine-exposed mice, suggesting their specificity as chlorine EB biomarkers. Furthermore, chlorine-exposed mice displayed a neutrophilic inflammatory response and body weight loss 24 h following exposure. In conclusion, all animals developed an airway inflammation characterized by neutrophil infiltration and a specific EB pattern that could be extracted after chlorine exposure. Monitoring EB samples can readily and non-invasively provide valuable information on biomarkers for diagnosis of chlorine-induced ALI, confirming chlorine exposures.

Ultrasensitive Online NO Sensor Based on a Distributed Parallel Self-Regulating Neural Network and Ultraviolet Differential Optical Absorption Spectroscopy for Exhaled Breath Diagnosis.

The concentration of fractional exhaled nitric oxide (FeNO) is closely related to human respiratory inflammation, and the detection of its concentration plays a key role in aiding diagnosing inflammatory airway diseases. In this paper, we report a gas sensor system based on a distributed parallel self-regulating neural network (DPSRNN) model combined with ultraviolet differential optical absorption spectroscopy for detecting ppb-level FeNO concentrations. The noise signals in the spectrum are eliminated by discrete wavelet transform. The DPSRNN model is then built based on the separated multipeak characteristic absorption structure of the UV absorption spectrum of NO. Furthermore, a distributed parallel network structure is built based on each absorption feature region, which is given self-regulating weights and finally trained by a unified model structure. The final self-regulating weights obtained by the model indicate that each absorption feature region contributes a different weight to the concentration prediction. Compared with the regular convolutional neural network model structure, the proposed model has better performance by considering the effect of separated characteristic absorptions in the spectrum on the concentration and breaking the habit of bringing the spectrum as a whole into the model training in previous related studies. Lab-based results show that the sensor system can stably achieve high-precision detection of NO (2.59-750.66 ppb) with a mean absolute error of 0.17 ppb and a measurement accuracy of 0.84%, which is the best result to date. More interestingly, the proposed sensor system is capable of achieving high-precision online detection of FeNO, as confirmed by the exhaled breath analysis.

On the relation between tidal and forced spirometry.

Spirometry is a lung function test involving deep inhalation and forceful deep exhalation. It is widely used to obtain objective information about airflow limitation and to diagnose lung diseases. In contrast, tidal spirometry is based on normal breathing and therefore much more convenient, but it is hardly used in medical care and its relation with conventional (forced) spirometry is largely unknown. Therefore, the objective of this work is to reveal the relation between tidal and forced spirometry. Employing the strong correspondence between the forced flow-volume curves and the Tiffeneau-Pinelli (TP) index, we present a method to obtain (a) the expected tidal flow-volume curve for a given TP-index, and (b) the expected TP-index for a given tidal curve. For patients with similar values of the TP-index, the tidal curves show a larger spread than the forced curves, but their average shape varies in a characteristic way with varying index. Therefore, just as with forced curves, the TP-index provides a useful objective ranking of the average of tidal curves: upon decreasing TP-index the expiratory flow rate changes in that its peak shifts towards smaller expiratory volumes, and its post-peak part becomes dented.