Search Results (196)

It has long been accepted that breathing gases that are physiologically inert include helium (He), neon (Ne), nitrogen (N₂), argon (Ar), krypton (Kr), xenon (Xe), and hydrogen (H₂). The term “inert gas” has been used to describe them due to their unusually high chemical stability. However, as investigations have advanced, many have shown that inert gas can have specific biological impacts when exposed to high pressure or atmospheric pressure. Additionally, different inert gases have different effects on intracellular signal transduction, ion channels, and cell membrane receptors, which are linked to their anesthetic and cell protection effects in normal or pathological processes. Through a selective analysis of the representative literature, this study offers a concise overview of the state of research on the biological impacts of inert gas and their molecular mechanisms. Full article

This article describes a new software architecture for the non-invasive detection of canine leishmaniasis disease. The proposed platform combines gas-sensing technologies, artificial intelligence (AI), and modular cloud-based software components to identify disease-specific volatile organic compounds (VOCs) found in dog breath and hair samples. The system, which has a multi-tier architecture that includes data collection, pre-processing, machine learning-based analysis, diagnosis-request processing, and user interfaces for veterinarians, faculty researchers, and dog owners, has been integrated into a Li-ion Power website plug-in. The primary goal of implementing the proposed platform is to detect parasites at any point they are infectious to a host. This includes detecting parasites at all stages of their life cycle, where they can infect a new host. In addition, this is crucial for accurate diagnosis, effective treatment, and preventing further transmission. Full article

Ketones, which are key biomarkers of fat oxidation, are relevant for metabolic health maintenance and disease development, making continuous monitoring essential. In this study, we introduce a novel colorimetric sensor designed for potential continuous acetone detection in biological fluids. The sensor features a polydimethylsiloxane (PDMS) shell that encapsulates a sensitive and specific liquid-core acetone-sensing probe. The microsphere sensors were characterized by evaluating their size, PDMS shell thickness, colorimetric response, and sensitivity under realistic conditions, including 100% relative humidity (RH) and CO₂ interference. The microsphere size and sensor sensitivity can be controlled by modifying the fabrication parameters. Critically, the sensor showed high selectivity for acetone detection, with negligible interference from CO₂ concentrations up to 4%. In addition, the sensor displayed good reproducibility (CV < 5%) and stability under realistic storage conditions (over two weeks at 4 °C). Finally, the accuracy of the microsphere sensor was validated against a gold standard gas chromatography-mass spectrometry (GC-MS) method using simulated and real breath samples from healthy individuals and type 1 diabetes patients. The correlation between the microsphere sensor and GC-MS produced a linear fit with a slope of 0.948 and an adjusted R-squared value of 0.954. Therefore, the liquid-core microsphere-based sensor is a promising platform for acetone body fluid analysis. Full article

Background/Objectives: The increasing prevalence of diabetes underscores the urgent need for non-invasive, rapid, and cost-effective diagnostic alternatives. This study presents a breath-based multiclass diabetes classification system leveraging only three gas sensors (CO, alcohol, and acetone) to analyze exhaled breath composition. Methods: Breath samples were collected from 58 participants (22 healthy, 7 prediabetic, and 29 diabetic), with blood glucose levels serving as the reference metric. To enhance classification performance, we introduced a novel biomarker, the alcohol-to-acetone ratio, through a feature engineering approach. Class imbalance was addressed using the Synthetic Minority Over-Sampling Technique (SMOTE), ensuring a balanced dataset for model training. A nested cross-validation framework with 3 outer and 3 inner folds was implemented. Multiple machine learning classifiers were evaluated, with Random Forest and Gradient Boosting emerging as the top-performing models. Results: An ensemble combining both yielded the highest overall performance, achieving an average accuracy of 98.86%, precision of 99.07%, recall of 98.81% and F1 score of 98.87%. These findings highlight the potential of gas sensor-based breath analysis as a highly accurate, scalable, and non-invasive method for diabetes screening. Conclusions: The proposed system offers a promising alternative to blood-based diagnostic approaches, paving the way for real-world applications in point-of-care diagnostics and continuous health monitoring. Full article

Background: Lung cancer (LC) is the leading cause of cancer-related deaths worldwide. Effective screening strategies for early diagnosis that could improve disease prognosis are lacking. Non-invasive breath analysis of volatile organic compounds (VOC) is a potential method for earlier LC detection. This study explores the association of VOC profiles with artificial intelligence (AI) to achieve a sensitive, specific, and fast method for LC detection. Patients and methods: Exhaled breath air samples were collected from 123 healthy individuals and 73 LC patients at two clinical sites. The enrolled patients had LC diagnosed with different stages. Breath samples were collected before undergoing any treatment, including surgery, and analyzed using gas chromatography coupled to ion-mobility spectrometry (GC-IMS). AI methods classified the overall chromatographic profiles. Results: GC-IMS is highly sensitive, yielding detailed chromatographic profiles. AI methods ranked the sets of exhaled breath profiles across both groups through training and validation steps, while qualitative information was deliberately not taking part nor influencing the results. The K-nearest neighbor (KNN) algorithm classified the groups with an accuracy of 90% (sensitivity = 87%, specificity = 92%). Narrowing the LC group to those only in early-stage IA, the accuracy was 90% (sensitivity = 90%, specificity = 93%). Conclusions: Evaluation of the global exhaled breath profiles using AI algorithms enabled LC detection and demonstrated that qualitative information may not be required, thus easing the frustration that many studies have experienced so far. The results show that this approach coupled with screening protocols may improve earlier detection of LC and hence its prognosis. Full article

Monitoring trace toluene exposure is critical for early-stage lung cancer screening via breath analysis, yet conventional chemiresistive sensors face fundamental limitations, including compromised selectivity in complex VOC matrices and humidity-induced signal drift, with prevailing p–n heterojunction architectures suffering from inherent charge recombination and environmental instability. Herein, we pioneer a 2D core–shell n–n heterojunction strategy through rational design of TiO₂@MoS₂ heterostructures, where vertically aligned MoS₂ nanosheets are epitaxially grown on 2D TiO₂ derived from graphene-templated synthesis, creating built-in electric fields at the heterojunction interface that dramatically enhance charge carrier separation efficiency. At 240 °C, the TiO₂@MoS₂ sensor exhibits a superior response (R_a/R_g = 9.8 to 10 ppm toluene), outperforming MoS₂ (R_a/R_g = 2.8). Additionally, the sensor demonstrates rapid response/recovery kinetics (9 s/16 s), a low detection limit (50 ppb), and excellent selectivity against interfering gases and moisture. The enhanced performance is attributed to unidirectional electron transfer (TiO₂ → MoS₂) without hole recombination losses, methyl-specific adsorption through TiO₂ oxygen vacancy alignment, and steric exclusion of non-target VOCs via size-selective MoS₂ interlayers. This work establishes a transformative paradigm in gas sensor design by leveraging n–n heterojunction physics and 2D core–shell synergy, overcoming long-standing limitations of conventional architectures. Full article

The detection of hydrogen gas is crucial for both industrial fields, as a green energy carrier, and biomedical applications, where it is a biomarker for diagnosis. TiO₂ nanomaterials are stable and sensitive to hydrogen gas, but their gas response can be negatively affected by external factors such as humidity. Therefore, a strategy is required to mitigate these influences. The utilization of organic–inorganic hybrid gas sensors, specifically metal oxide gas sensors coated with ultra-thin copolymer films, is a relatively novel approach in this field. In this study, we examined the performance and long-term stability of novel TiO₂-based sensors that were coated with poly(trivinyltrimethylcyclotrisiloxane-co-tetrafluoroethylene) (P(V3D3-co-TFE)) co-polymers. The P(V3D3-co-TFE)/TiO₂ hybrid sensors exhibit high reliability even for more than 427 days. They exhibit excellent hydrogen selectivity, particularly in environments with high humidity. An optimum operating temperature of 300 °C to 350 °C was determined. The highest recorded response to H₂ was approximately 153% during the initial set of measurements at a relative humidity of 10%. The developed organic–inorganic hybrid structures open wide opportunities for gas sensor tuning and customization, paving the way for innovative applications in industry and biomedical fields, such as exhaled breath analysis, etc. Full article

Background: Severe acute asthma (SAA) in children can be life-threatening. There has been a significant rise in paediatric intensive care unit (PICU) admissions due to SAA over the past two decades. While asthma is a heterogeneous disease, its underlying pathophysiological pathways remain underexplored. This study aimed to assess the value of non-invasive targeted exhaled breath metabolomics analysis to better characterise SAA. Methods: Breath samples from 17 children admitted to the PICU with SAA (cases) and 27 children with controlled severe asthma (controls) were analysed using thermal desorption gas chromatography–mass spectrometry (TD-GC-MS). Results: A targeted volatile organic compound (VOC) analysis identified 25 compounds, of which 16 were shared between groups. Four VOCs were significantly more often present in SAA, and nine VOCs exhibited higher concentrations in SAA. Longitudinal analysis of VOCs from follow-up samples of 10 cases showed no significant temporal differences, reinforcing the reproducibility of identified biomarkers. Conclusions: This study exemplifies the potential of exhaled breath analysis to provide insights into the molecular background of SAA. Breath metabolomics may enable early recognition of severe asthma attacks and preventive therapeutic interventions in children with severe asthma. Full article

The rate of oxygen consumption, which is measured as the volume of oxygen consumed per mass per minute (VO₂) mL/kg/min, is a critical metric for evaluating cardiovascular health, metabolic status, and respiratory function. Specifically, VO₂ is a powerful prognostic predictor of survival in patients with heart failure (HF) because it provides an indirect assessment of a patient’s ability to increase cardiac output (CO). In addition, VO₂ measurements, particularly VO₂ max, are significant because they provide a reliable indicator of your cardiovascular fitness and aerobic endurance. However, traditional VO₂ assessment requires bulky, breath-by-breath gas analysis systems, limiting frequent and continuous monitoring to specialized settings. This study presents a novel wrist-worn multiwavelength photoplethysmography (PPG) device and machine learning algorithm designed to estimate VO₂ continuously. Unlike conventional wearables that rely on static formulas for VO₂ max estimation, our algorithm leverages the data from the PPG wearable and uses the Beer–Lambert Law with inputs from five wavelengths (670 nm, 770 nm, 810 nm, 850 nm, and 950 nm), incorporating the isosbestic point at 810 nm to differentiate oxy- and deoxy-hemoglobin. A validation study was conducted with eight subjects using a modified Bruce protocol, comparing the PPG-based estimates to the gold-standard Parvo Medics gas analysis system. The results demonstrated a mean absolute error of 1.66 mL/kg/min and an R² of 0.94. By providing precise, individualized VO₂ estimates using direct tissue oxygenation data, this wearable solution offers significant clinical and practical advantages over traditional methods, making continuous and accurate cardiovascular assessment readily available beyond clinical environments. Full article

We present an empirical model for the cross-section of low concentration acetone gas in the range of 1671.5–1675 nm that encompasses the absorption band of the methyl stretch overtone. This model is experimentally validated with cavity ring-down spectroscopy (CRDS) measurements performed with a calibration gas and its diluted mixtures with breath samples. Particular attention is paid to accurate wavelength measurements with an interferometric wavemeter. The theoretical framework for analysis of gas mixtures with several absorbing species is presented. We show that the proposed empirical model can be used to accurately determine the concentration of acetone vapor in human breath samples. The comparison of the acetone absorption cross-section with previous results is also presented. Full article

Positive airway pressure (PAP) therapy is widely used to manage both acute and chronic respiratory failure and plays an increasingly important role in cardiology, particularly in treating patients with respiratory comorbidities. PAP, including continuous positive airway pressure and noninvasive ventilation, significantly impacts hemodynamics by altering intrathoracic pressure, affecting preload, afterload, and stroke volume. These changes are crucial in conditions such as acute cardiogenic pulmonary edema, where PAP can enhance gas exchange, reduce the work of breathing, and improve cardiac output. PAP reduces the left ventricular afterload, which in turn increases stroke volume and myocardial contractility in patients with left-sided heart failure. However, the role of PAP in right ventricular function and its effects on venous return and cardiac output are critical in the cardiac intensive care setting. While PAP provides respiratory benefits, it must be used cautiously in patients with right heart failure or preload-dependent conditions to avoid adverse outcomes. Additionally, in recent years, the use of PAP has expanded in the treatment of severe obstructive sleep apnea and obesity hypoventilation syndrome, both of which significantly influence cardiovascular events and heart failure. This review provides an in-depth analysis of the hemodynamic effects of PAP in cardiovascular disease, focusing on its impact on ventricular function in both acute and chronic conditions. Evaluating clinical studies, guidelines, and recent advancements offers practical insights into the physiological mechanisms and key clinical considerations. Furthermore, this review aims to serve as a helpful guide for clinicians, assisting in decision-making processes where PAP therapy is applied. Full article

Background/Objectives: Dyspnea, the subjective experience of breathing discomfort, accounts for approximately 5% of emergency department (ED) presentations, 10% of general ward admissions, and 20% of intensive care unit (ICU) admissions. Despite its prevalence, dyspnea remains a challenging clinical manifestation for physicians. To the best of our knowledge, there are no international guidelines for the assessment and management of patients with dyspnea coming to the ED. In this study, we aim to evaluate how dyspnea cases are assessed and managed at Cantonal Hospital Baselland in Liestal (KSBL) and to audit these practices. Methods: We conducted a retrospective, observational study of hospital records from KSBL, including all patients presenting to the ED with dyspnea as their primary symptom who were subsequently admitted to the internal medicine ward for at least one night between January and December 2022. Data on assessment and management practices were compared using the medStandards algorithm. Results: A total of 823 cases were included. The median age at admission was 76 years (with a range of 15–99), and 57% of the patients were male. Blood pressure and heart rate were documented in 93.8% of the cases, respiratory rate in 61.4%, oxygen saturation in 96.1%, and body temperature in 86.3%. The patient’s subjective dyspnea description was recorded in 14.8% of the cases, while the temporal onset (timing of symptoms) was documented in 98.8%, and the intensity of effort triggering dyspnea was noted in 36.2% of cases. A dyspnea index scale was used in 7.8% and smoking status was documented in 41.1% of the cases. Lung percussion was performed in 2.6% of the cases, while a lung auscultation was performed in 94.4% and a heart auscultation was performed in 85.3% of cases. A complete blood count with a basic metabolic panel and TSH test was collected in 86.9% of the cases, while a blood gas analysis was collected in 34.0% of the cases. An ECG was reported in 87.5% of the cases. From the 337 patients who should have received an emergency ultrasound, 10.1% received one. The three most frequent final diagnoses were decompensated heart failure (28.4%), pneumonia (26.4%), and COVID-19 (17.0%). None of the three patients with a known neuromuscular disease were admitted to the shock room. Conclusions: Our findings reveal that the medStandards algorithm was only partially followed at the ED in KSBL Liestal, highlighting gaps in detailed history taking, respiratory rate measurement, lung percussion, and emergency ultrasound use. Given the frequency of dyspnea-related presentations, systematic improvements in the adherence to assessment protocols are urgently needed to enhance patient outcomes. Full article

Mitochondrial 3-hydroxy-3-methylglutaryl-CoA synthase deficiency (HMGCS2D) is a rare metabolic disorder that impairs the body’s ability to produce ketone bodies and regulate energy metabolism. Diagnosing HMGCS2D is challenging because patients typically remain asymptomatic unless they experience fasting or illness. Due to the absence of reliable biochemical markers, genetic testing has become the definitive method for diagnosing HMGCS2D. This study included 19 patients from 14 unrelated families diagnosed with HMGCS2D in our department between October 2018 and October 2024. The clinical presentations, biochemical findings, molecular characteristics, and management strategies were systematically summarized and analyzed. Of the 19 cases studied, 16 were symptomatic, and 3 were asymptomatic. The onset of the first acute episode occurred between 10 days and 28 months of age. Triggers for the initial crisis in the symptomatic cases included poor feeding (93.8%), vomiting (56.3%), diarrhea (25.0%), and fever (18.8%). Clinical manifestations during the first episode were lethargy/coma (81.3%), rapid breathing (68.8%), hepatomegaly (56.3%), shock (37.5%), and seizures (18.8%). The biochemical abnormalities observed included elevated plasma transaminases (100%), metabolic acidosis (75%), hypoglycemia (56.3%), and elevated plasma ammonia levels (31.3%). Additionally, low free carnitine levels were found in seven cases, elevated C2 levels were found in one case, dicarboxylic aciduria was found in two cases, and ketonuria was found in two cases. Abnormal brain MRI findings were detected in three patients. Genetic analysis revealed seven HMGCS2 gene variants across the 19 cases. Notably, a novel variant, c.407A>T (p.D136V), was identified and has not been reported in any existing databases. Two common variants, c.559+1G>A and c.1090T>A (p.F364I), were present in 11 out of 19 cases (57.9%) and 10 out of 19 cases (55.5%), respectively. The implementation of a high glucose infusion and proactive management strategies—such as preventing prolonged fasting and providing enteral carbohydrate/glucose infusion during illness—effectively reduced the rate of acute relapses following accurate diagnosis. Currently, all 19 patients are alive, with ages ranging from 5 months to 14 years, and exhibit normal physical development. To the best of our knowledge, this study represents the first reported cases of HMGCS2D in Vietnamese patients. Our findings contribute to a broader understanding of the clinical phenotype and expand the known spectrum of HMGCS2 gene variants, enhancing current knowledge of this rare metabolic disorder. Full article

Chemiresistive ammonia gas sensors with a low limit of detection of 0.15 ppm and moisture-independent characteristics based on p-type copper iodide (CuI) semiconductor films have been developed. CuI films were deposited on glass and polyethylene terephthalate (PET) substrates using a Successive Ionic Layer Adsorption and Reaction method to fabricate CuI/glass and CuI/PET gas sensors, respectively. They have a nanoscale morphology, an excess iodine and sulfur impurity content, a zinc blende γ-CuI crystal structure with a grain size of ~34 nm and an optical band gap of about 2.95 eV. The high selective sensitivity of both sensors to NH₃ is explained by the formation of the [Cu(NH₃)₂]⁺ complex. At 5 °C, the responses to 3 ppm ammonia in air in terms of the relative resistance change were 24.5 for the CuI/glass gas sensor and 28 for the CuI/PET gas sensor, with short response times of 50 s to 210 s and recovery times of 10–70 s. The sensors have a fast response–recovery and their performance was well maintained after long-term stability testing for 45 days. After 1000 repeated bends of the flexible CuI/PET gas sensor in different directions, with bending angles up to 180° and curvature radii up to 0.25 cm, the response changes were only 3%. Full article

Timely ketone detection in patients with type 1 diabetes mellitus (T1DM) is critical for the effective management of diabetic ketoacidosis (DKA). This systematic review evaluates the current literature on breath-based analysis for ketone detection in T1DM, highlighting nanotechnology as a potential for a non-invasive alternative to blood-based ketone measurements. A comprehensive search across 5 databases identified 11 studies meeting inclusion criteria, showcasing various breath analysis techniques, such as semiconducting gas sensors, colorimetry, and nanoparticle-based chemo-resistive sensors. These studies report high sensitivity and correlation between breath acetone (BrAce) levels and blood ketones, with some demonstrating accuracies up to 94.7% and correlations reaching R² values as high as 0.98. However, significant heterogeneity in methodologies and cut-off values limits device comparability and precludes meta-analysis. Despite these challenges, the findings indicate that BrAce monitoring could offer significant clinical benefits by enabling the earlier detection of ketone buildup, reducing DKA-related hospitalisations and healthcare costs. Standardising BrAce measurement techniques and sensitivity thresholds is essential to broaden clinical adoption. This review underscores the promise of nanotechnology-based breath analysis as a transformative tool for DKA management, with potential utility across varied ketotic conditions. Full article