Search Results (1,385)

Clinical monitoring of chronic liver disease (CLD) is currently hindered by the invasiveness of conventional biopsies. While breath-borne volatile organic compound (VOC) analysis offers a promising non-invasive alternative, the metabolic profiles of sedentary populations often overlap significantly with those of healthy individuals, making latent pathologies difficult to identify. To overcome this high-resolution diagnostic challenge, this study developed an integrated framework that couples high-performance semiconductor sensing technology with a machine learning-based analytical baseline. During the biomarker screening phase, GC-MS was utilized to analyze over 2000 VOCs, identifying 20 markers associated with CLD. These were further optimized into a robust feature panel including ammonia, isoprene, dimethyl sulfide (DMS), and limonene. For several critical metabolic features exhibiting high diagnostic potential, preliminary identifications were conducted by referencing NIST database matches and relevant literature. To maintain analytical rigor and account for the inherent complexity of trace volatile metabolites in biological samples, these signals are treated as putative metabolic features and characterized by their retention times. Regarding hardware, an InN-based sensor with Pt-AlN surface modification was fabricated, achieving a limit of detection (LOD) for ammonia below 0.2 ppm. Crucially, while the InN sensor was validated for specific core markers such as ammonia, the current AI classification model is trained on a refined 7-VOC panel derived from the comprehensive GC-MS data. To resolve diagnostic overlaps, a three-state dynamic sampling protocol (resting, exercise, and recovery) was implemented to isolate biomarkers that remain physiologically stable. By integrating multi-dimensional VOC features (e.g., isoprene and DMS) with sensor-validated data through DBSCAN and Random Forest algorithms, the framework successfully captured non-linear metabolic fingerprints. Machine learning results confirm that the framework effectively distinguished sedentary controls from CLD patients, achieving a macro-average AUC of 0.96. This integration provides a high-precision technical pathway for early-stage liver disease screening. Full article

Background/Objectives: Two diagnostic approaches for sleep studies are commonly used worldwide: in-laboratory polysomnography [PSG] and home sleep apnea testing [HSAT]. Although HSAT has gained increasing acceptance due to its convenience and lower cost, clinical criteria for HSAT use remain complex and cannot be inferred directly from AHI/ODI severity indices alone. The aim of the present exploratory study was to examine associations between routinely collected demographic, clinical, and symptom-related variables and objective indices of disease severity, namely the apnea–hypopnea index [AHI] and oxygen desaturation index [ODI] as an initial, hypothesis-generating step toward future patient-level model development and validation. Methods: A retrospective observational analysis was conducted in 1100 individuals who previously underwent in lab-polysomnography [PSG] at the University Hospital of Thessaly, Greece, between 2006 and 2023. Specific demographic, clinical and symptom-related variables were included in this study [six continuous and fifteen categorical], which were analyzed in relation to AHI and ODI values. A three-step process was carried out: variable selection followed a screening and backward elimination process. Multivariable linear regression models were subsequently estimated within a Bayesian framework using Hamiltonian Monte Carlo methods. Results: Out of 1100 individuals, the mean age was 51.9 years with the predominant gender being male [76%]. Obesity [65.6%] and hypertension [40.5%] were the most common comorbidities. For AHI, male gender, body mass index [BMI], Epworth Sleepiness Scale [ESS] score, reported breathing interruptions during sleep, and chronic obstructive pulmonary disease [COPD] were significant predictors. For ODI, significant predictors included male gender, BMI, ESS score, breathing interruptions during sleep, daytime sleepiness, obesity, and COPD. COPD showed an inverse association with both indices. Conclusions: These findings support the feasibility of integrating routinely available clinical variables within a Bayesian probabilistic framework to estimate disease severity pre-test probability. The current analysis may not constitute a validated tool for HSAT versus PSG selection; however, it is an initial, hypothesis-generating step toward future model development. Full article

Falls among older adults are a major public health concern, yet collecting large-scale real fall data for radar-based detection is ethically and practically difficult. This study presents a controlled simulation-to-real feasibility study for trip-fall detection using continuous-wave (CW) Doppler radar. The method couples a physics-informed kinematic trip-fall model with a CW radar observation model to synthesize I/Q signals and Doppler spectrograms, while domain randomization varies body size, fall direction, initial velocity, sensor placement, aspect angle, amplitude, and noise. Synthetic walking and respiration data were also generated for controlled three-class classification among trip fall, walking, and seated quiet breathing. In Experiment I, the simulated spectrograms reproduced the dominant time–frequency characteristics of measured enacted trip-fall signals acquired with a 24 GHz CW radar; quantitative similarity analysis yielded a mean SSIM of 0.782 and a Doppler-ridge MAE of 24.6 Hz across five fall directions. In Experiment II, a ResNet-18 classifier trained only on simulated spectrograms achieved a macro-F1 score of 0.912 [95% CI: 0.883–0.936] on measured data from ten participants, three start locations, and eight directions. Under the present controlled evaluation, this exceeded the available real-data-trained baseline of 0.748 [95% CI: 0.691–0.805] (paired subject-level permutation test, $p=0.006$). These findings suggest that physics-informed simulation with domain randomization can reduce dependence on real trip-fall samples under limited-data conditions. The results do not establish robustness to other fall morphologies, fall-like activities of daily living, different environments, different radar devices, or embedded deployment. Full article

This exploratory study aimed to compare the determination of metabolic thresholds using muscle oxygen saturation (SmO₂) and gas exchange data during graded exercise testing in individuals with spinal cord injury. Nine participants (six males, three females) performed a graded exercise test on an arm-crank ergometer, with continuous measurements of breath-by-breath pulmonary gas exchange and SmO₂ from the biceps brachii and triceps brachii. Thresholds were identified as gas exchange threshold (GET) and respiratory compensation point (RCP), and their SmO₂ counterparts as MOT1 and MOT2. The results showed no differences between GET and MOT1 in either muscle (biceps: p = 0.14; triceps: p = 1.00), and similar results were observed between RCP and MOT2 for triceps brachii (p = 0.39) and biceps brachii (p = 0.12). Reliability analysis revealed good but non-significant agreement for the triceps brachii (ICC = 0.44–0.60), while the biceps brachii demonstrated very good agreement at GET (ICC = 0.78, p < 0.01) and excellent agreement at RCP (ICC = 0.81, p < 0.01), and Bland–Altman analyses confirmed no systematic bias between muscle sites. In conclusion, SmO₂ may be a valid and promising variable for detection in individuals with spinal cord injury during ramp exercise testing. Both muscles showed agreement with pulmonary gas exchange, but the biceps brachii provided more consistent and reliable estimates, particularly for the second threshold. These preliminary findings suggest the use of near-infrared spectroscopy as a non-invasive technology for metabolic threshold detection in spinal cord injury populations. Full article

Disinfection is essential to ensure safe drinking water and hygienic conditions in environmental, industrial, and clinical settings. However, conventional methods for monitoring free residual chlorine are often laboratory-based and not suited for decentralized analysis. Here, we report a novel paper-based colorimetric biosensing platform that translates the ISO 7393-2 standard, a method based on the reaction of chlorine with N,N-diethyl-p-phenylenediamine (DPD), into a portable and user-friendly format. The proposed device integrates the DPD chemistry within a paper architecture, enabling reagent-free operation at the point of need. The sensor provides a rapid visual readout that is detectable by the naked eye, while quantitative analysis is achieved within 3 min through smartphone-based image acquisition. This work constitutes the first implementation of the ISO standard in a portable paper-based format suitable for both environmental and clinical matrices. The sensor provided a detection limit of 12 μM for sodium hypochlorite and was successfully validated in real samples, including bottled water and exhaled breath condensate, with satisfactory recoveries. Furthermore, the stability of the paper-based sensor was assessed under storage conditions of 4 °C and room temperature (23 °C), demonstrating excellent performance over 30 days in both cases, indicating that refrigeration is not required for maintaining sensor performance. Full article

Sleep apnea is a prevalent sleep-related breathing disorder characterized by recurrent cessations or reductions in airflow during sleep. It significantly impacts the quality of life, yet current diagnostic methods like polysomnography (PSG) are expensive and uncomfortable, limiting accessibility and ease of use. We developed a novel non-contact biosensing system using secondary laser speckle pattern analysis and dedicated image processing algorithms for apnea-like breathing cessations. The proposed method was tested on $14$ healthy subjects with diverse body characteristics, aged 22–50 years (mean $33.1 \pm 9.3$ years) and body mass index (BMI) ranging from $19.6$ to $28.7$ kg/m² (mean $24.6 \pm 3.0$ kg/m²) at different ‘simulated’ sleeping positions (back-lying, stomach-lying and side-lying), using voluntary breath-holding protocols to simulate apnea-like cessations lasting 10–20 s (short duration) and 20–30 s (long duration). To evaluate the performance of the system without selection bias, two complementary five-fold cross-validation procedures were applied: a participant-level and a class-level stratification. Using class-wise stratification, the system achieved an overall accuracy of $87.0 \pm 3.0\%$ (95% CI: [85.3%, 88.7%]), long-cessation sensitivity of $91 \pm 12.4\%$$(95\% \mathrm{C}\mathrm{I}:[83.8\%,98.2\%\left]\right)$ and a short-cessation sensitivity of $88.0 \pm 11\%$$\left(95\% \mathrm{C}\mathrm{I}:[81.6\%,94.4\%]\right)$. The two-class classification strategy confirm the robustness of the approach, supporting the potential of secondary laser speckle pattern analysis as a low-cost, non-contact alternative for home-based sleep apnea screening. Full article

Diagnostic latency limits time-sensitive care and early detection, and exhaled breath provides a rapid, repeatable window into metabolic and inflammatory chemistry. We review real-time breath sampling and analytical technologies and evaluate their readiness for clinical adoption, with emphasis on molecular pathways reflected in the breath volatilome and in exhaled breath condensate. Real-time mass spectrometry enables kinetic VOC profiling and targeted quantification, while humidity-aware sensors and wearable condensate platforms extend monitoring beyond the laboratory. Pathway-anchored interpretation links breath readouts to ketone handling, isoprenoid metabolism, nitric oxide signaling, lipid peroxidation, uremic nitrogen handling, and microbiome–host co-metabolism, but performance remains vulnerable to confounding, drift, and non-representative comparators. Translation requires standardized breath fraction control, traceable features, robust quality systems, and governed device algorithm stacks so that breath outputs inform decisions and outcomes. Full article

Background: Pectus excavatum (PE) is the most common anterior chest wall deformity in children and adolescents. It may lead to postural adaptations of the trunk and spine and can influence the distribution of the center of gravity. Methods: A total of 35 patients with PE, with a Haller index < 3.25, aged 5–17 years, followed a structured exercise program including postural correction exercises, thoracic mobility exercises, breathing retraining, and trunk extensor strengthening for three months after proper instruction by a specialist. Patients were assessed before and after the intervention. Postural alignment was evaluated laterally (right and left) using the GaitON Posture Analysis System, and static balance was assessed using the PoDATA 2.0 stabilometric platform (Chinesport, Italy), which analyzes plantar pressure distribution and center of pressure (COP) displacement during orthostatic stance. Statistical analysis was performed using paired t-tests and Pearson correlation coefficients. Results: Stabilometric analysis demonstrated a reduction in COP trajectory length, confidence ellipse area, and maximum velocity, indicating improved postural control and reduced sway. Postural analysis revealed statistically significant improvements in head and shoulder girdle alignment. Correlations suggest a potential relationship between segmental alignment and stabilometric parameters and a possible reduction in thoracic hyperkyphosis associated with PE. Conclusions: Postural and stabilometric assessment in PE highlights changes in the analyzed parameters and suggest that a structured exercise program may be associated with improvements in biomechanical function and neuromuscular control. These methods can be integrated into conservative management and therapeutic strategies. Full article

Background: The aim of this study was to assess in vitro nebulized drug delivery during invasive and non-invasive ventilation, comparing jet nebulizers (JN) and vibrating mesh nebulizers (VMN) across various pediatric ventilation models. Methods: Drug delivery performance was compared between a continuous output JN (Aquineb) and VMN (Aerogen Solo A-VMN). The non-invasive model simulated a spontaneously breathing 9-month-old child using an anatomically correct upper airway model and breathing simulator. The invasive model used a mechanical ventilator with heated humidifier in a pediatric breathing circuit with an endotracheal tube. Nebulizers were driven with supplemental oxygen at manufacturer-recommended rates and positioned at approved locations. Absolute inhaled dose, delivery rate and residual volume were assessed using face mask, mechanical ventilation, high-flow nasal therapy and blow-by delivery methods. Dose was quantified using spectrophotometric analysis. Results: During spontaneous breathing, A-VMN delivered almost double the dose of the evaluated JN (p < 0.001), with a significantly faster delivery rate (p < 0.001) and lower residual volume (p < 0.0001). During mechanical ventilation, A-VMN demonstrated a greater than 3-fold increase in delivered dose (p < 0.0001) and faster delivery (p < 0.0001), with reduced residual volume (p < 0.001). During high-flow nasal therapy, delivery via nasal cannula was affected by gas flow rate for both devices, with A-VMN consistently delivering greater doses. A-VMN delivered significantly greater salbutamol doses during blow-by delivery. Conclusions: VMN demonstrated significantly superior dose delivery, faster delivery rates and reduced residual volumes compared to the evaluated JN across all tested pediatric respiratory support modalities. These in vitro findings provide important performance data for evidence-based device selection and warrant clinical investigation to determine potential therapeutic benefits in pediatric populations requiring aerosol therapy during respiratory support. Full article

Background: Developmental and benign movement disorders (DBMD) are a common but often under-recognized cause of referral in children with suspected seizures, frequently leading to misdiagnosis and unnecessary treatment. Methods: This retrospective cohort study included 453 children evaluated for suspected seizures between January 2019 and January 2024. Patients with epilepsy, cerebral palsy, metabolic disorders, significant developmental delay, psychiatric conditions, or structural brain abnormalities were excluded. DBMD was diagnosed in 113 patients based on clinical evaluation by experienced pediatric neurologists and established diagnostic criteria. Demographic characteristics, diagnostic distribution, age at presentation, and electroencephalography (EEG) findings were analyzed. Prevalence was calculated with 95% confidence intervals (CIs). Group comparisons were performed using chi-square tests and one-way ANOVA with Tukey post hoc analysis. Results: The prevalence of DBMD was 24.9% (95% CI: 21.2–29.1), corresponding to nearly one in four children referred with suspected seizures. Breath-holding spells were the most common diagnosis (6.6% of the total cohort; 26.5% of DBMD cases), followed by Sandifer syndrome and non-epileptic staring episodes. Age at presentation differed significantly between diagnostic groups (p = 0.001), with breath-holding spells occurring at younger ages and staring episodes at older ages. EEG findings were normal in 80.5% of patients, and no diagnosis-specific epileptiform patterns were identified. No patients were observed to develop epilepsy during the follow-up period. Conclusions: DBMD accounts for a substantial proportion of children referred for suspected seizures. Recognition of age-specific clinical patterns and predominantly normal EEG findings may improve diagnostic accuracy and help avoid unnecessary investigations and antiepileptic treatment. Full article

Exhaled breath analysis offers a non-invasive route for metabolic monitoring and disease screening, but its practical implementation requires sensing platforms that combine high sensitivity, robustness, and simplicity. Here, we report an evanescent wave-excited fiber-optic surface-enhanced Raman scattering (SERS) sensor based on silver nanocubes (Ag NCs) assembled onto a fiber taper waist (FTW), and the design is further extended to an Ag/graphene oxide (GO) hybrid interface for enhanced gas detection. Finite element and finite-difference time-domain simulations were employed to optimize the FTW geometry and Ag NC dimensions for efficient evanescent-field excitation and plasmonic enhancement. The fabricated FTW-SERS probe achieved a minimum detectable concentration of 10⁻⁹ M for crystal violet, together with good linearity and a relative standard deviation below 5%. For gas sensing, ethanol and acetone vapors were detected down to 50 ppm using the Ag NC-based FTW-SERS probe. After introducing a 0.3 mg/mL GO functional layer, the minimum detectable concentrations of both analytes were further reduced to 25 ppm. In addition, proof-of-concept monitoring of exhaled ethanol after alcohol consumption revealed dynamic spectral changes consistent with ethanol metabolism. These results demonstrate the potential of evanescent wave-excited FTW-SERS probes for compact and sensitive breath-analysis applications. Full article

Background: Small intestinal bacterial overgrowth (SIBO) has been implicated in the pathogenesis of MASLD; however, large-scale clinical data characterizing prevalence patterns, phenotypic subtypes, and disease-specific associations remain limited. Methods: This cross-sectional study enrolled 2549 MASLD patients with gastrointestinal symptoms undergoing lactulose methane–hydrogen breath testing and transient elastography. Univariate and multivariable analysis identified independent risk factors for SIBO. We also explore the distribution of SIBO subtypes and their associations with comorbidity profiles across the MASLD spectrum. Results: The overall prevalence of SIBO was 66.3%, escalating from 65.9% in MASL to 72.8% in at-risk MASH and 78.9% in cirrhosis, alongside a notable enrichment of the intestinal methanogen overgrowth (IMO) phenotype. Multivariable analysis identified advanced fibrosis (stage F4; OR = 1.75, 95% CI: 1.03–2.96), gastroesophageal reflux disease (GERD; OR = 1.66, 95% CI: 1.22–2.28), and coronary artery disease (CAD; OR = 1.80, 95% CI: 1.06–3.06) as independent predictors of SIBO. Additionally, elevated ALT (OR = 1.01, 95% CI: 1.01–1.13) showed a modest association with SIBO. Subtype analysis revealed that IMO was associated with GERD, alcohol consumption, CAD, and obesity, while a history of cholecystectomy and elevated triglycerides were linked to early-phase hydrogen peaks. Conclusions: SIBO is highly prevalent among patients with MASLD, with its prevalence and phenotypic subtype distribution being closely associated with disease severity. The identification of fibrosis-specific risk factors and subtype–clinical associations suggest consideration of SIBO assessment in advanced MASLD, particularly in patients with cardiometabolic or gastrointestinal comorbidities. Full article

Limited data are available regarding the physiological profile of youth triathletes. The aim of this study was to characterize the physiological and body composition profile of Hungarian youth triathletes and to examine the relationships between anthropometric characteristics and aerobic performance indicators. Forty-one youth triathletes (20 females and 21 males; age: 15.8 ± 1.7 years), members of the Hungarian national development squad, participated in the study. Anthropometric and body composition parameters were assessed using standardized procedures and multi-frequency bioelectrical impedance analysis. Aerobic performance was evaluated using a graded cardiopulmonary exercise test on a treadmill with breath-by-breath gas analysis. Male athletes demonstrated higher body height, body mass, fat-free mass, and skeletal muscle mass compared with females (p < 0.05). Cardiopulmonary exercise testing revealed high aerobic capacity, with mean VO₂max values of 73.2 ± 5.4 mL·kg⁻¹·min⁻¹ in males and 63.1 ± 5.0 mL·kg⁻¹·min⁻¹ in females. The second ventilatory threshold occurred at approximately 82–86% of VO₂max. Strong positive correlations were observed between anthropometric parameters and absolute oxygen uptake (mL·min⁻¹), particularly for fat-free mass, skeletal muscle mass, and body surface area (r = 0.83–0.95). However, these relationships are influenced by body size and were weaker or inverse when relative oxygen uptake (mL·kg⁻¹·min⁻¹) was considered. Regression analyses further indicated that body composition variables, especially fat-free mass and skeletal muscle mass, were positively associated with aerobic performance, while body fat percentage was not a significant predictor when body size and sex were controlled. These findings are based on cross-sectional associations and should be interpreted as descriptive reference data for this population rather than predictive criteria. The results contribute to the characterization of physiological and anthropometric profiles in youth triathletes and may support future research and athlete monitoring. Full article

Background: Gastroesophageal reflux disease (GERD) is a highly prevalent gastrointestinal disorder worldwide. Management strategies include lifestyle modification, pharmacologic therapy, and surgical interventions. Diaphragmatic breathing exercises have been proposed as a non-pharmacological treatment aimed at improving lower esophageal sphincter function and reducing reflux episodes. Methods: A systematic search of PubMed/MEDLINE, Scopus, ScienceDirect, Google Scholar, and ClinicalTrials.gov was conducted from database inception to 10 March 2026 to identify randomized controlled trials evaluating diaphragmatic breathing in patients with GERD. Two reviewers independently screened studies, extracted data, and assessed risk of bias using the Cochrane Risk of Bias 2.0 tool. Random-effects meta-analyses were performed to estimate pooled mean differences for symptom scores and quality-of-life outcomes. Results: Ten randomized controlled trials including 476 patients were analyzed (mean age: 39.9 ± 11.3 years). Diaphragmatic breathing interventions were performed in 229 participants, with an average duration of 20.36 min per session over approximately 5.1 weeks. Meta-analysis demonstrated a modest improvement in GERD symptom scores favoring diaphragmatic breathing (SMD −0.74; 95% CI −1.36 to −0.12; p = 0.019), with substantial heterogeneity (I² = 79.7%). Subgroup analyses comparing breathing with medication and sham breathing controls produced similar trends. Quality-of-life outcomes did not demonstrate statistically significant improvement (MD −2.35; 95% CI −6.35 to 1.65; p = 0.25) and showed considerable heterogeneity (I² = 85.3%). Risk-of-bias assessment revealed “some concerns” in several studies, primarily related to randomization procedures and outcome reporting. Conclusions: Although pooled results demonstrated a statistically significant reduction in GERD symptom scores favoring diaphragmatic breathing, this finding must be interpreted with considerable caution given the substantial heterogeneity observed. The current evidence remains limited by methodological heterogeneity, and inconsistent outcome assessment is insufficient to support definitive clinical recommendations, and the observed benefit may not be generalizable across patient populations or clinical settings. Larger standardized randomized trials are required to determine the clinical role of diaphragmatic breathing in GERD management. Full article

Background/Objectives: Sleep-disordered breathing (SDB), including obstructive sleep apnea, is common in children and is associated with mouth breathing, snoring, and neurobehavioral disturbances. In pediatric orthodontic patients, oral habits and craniofacial imbalances may contribute to airway dysfunction, making orthodontic evaluation a potential setting for early identification of SDB. This study aimed to estimate the prevalence of SDB and to evaluate its associations with parent-reported behavioral symptom profiles in a cohort of pediatric orthodontic patients. Methods: A multicenter cross-sectional study was conducted in 186 children aged 7–13 years attending orthodontic clinics in Oradea and Târgu Mureș, Romania. Parents completed a structured questionnaire on oral habits, the 22-item Pediatric Sleep Questionnaire (PSQ), with SDB defined as 8 or more positive responses, and a parent-reported behavioral screening form assessing ADHD symptom subtypes, oppositional-defiant disorder (ODD), conduct disorder, and anxiety/depression. These behavioral outcomes were based on screening measures and were not intended as clinical psychiatric diagnoses. Associations were analyzed using chi-square or Fisher’s exact tests, and multivariable logistic regression analyses were performed adjusting for age, sex, and weight status. Results: Mouth breathing was reported in 61.8% of participants, snoring in 26.9%, and SDB in 13.4%. Positive screens for ADHD-inattentive (p < 0.001), ADHD-hyperactive/impulsive (p < 0.001), ADHD-combined (p < 0.001), ODD (p < 0.001), and anxiety/depression (p < 0.001) were significantly more frequent among children with SDB. In multivariable analysis, SDB remained independently associated with ADHD-combined subtype (OR = 6.22), ADHD-hyperactive/impulsive symptoms (OR = 5.84), oppositional-defiant disorder (OR = 4.91), and anxiety/depression (OR = 4.38). Conclusions: SDB was identified in a meaningful proportion of pediatric orthodontic patients and was significantly associated with multiple screening-defined behavioral symptom domains. These findings support consideration of brief airway- and sleep-oriented screening during orthodontic assessment, particularly in school-aged children presenting with mouth breathing, snoring, or behavioral concerns. Given the cross-sectional and questionnaire-based design, the findings should be interpreted as associative and warrant confirmation in prospective studies using objective sleep measures. Full article