Search Results (2,592)

Background/Objectives: Individual responses to CFTR modulators vary widely among people with cystic fibrosis (pwCF), underscoring the need for functional approaches that provide biological context alongside genotype-based therapy selection. Nasal epithelial cultures provide an individual-specific model for theratyping, but most studies rely on freshly isolated cells, restricting repeated testing and long-term sample use. In this study, we tested whether CFTR modulator responses measured in biobanked nasal cells were associated with real-world clinical outcomes. Methods: Cryopreserved nasal epithelial cells from 23 pwCF were differentiated at the air–liquid interface and assessed for CFTR modulator-responsive ion transport using Ussing chambers. In vitro responses were correlated with 6-month changes in sweat chloride concentration (SCC), FEV₁, and BMI. Results: Cryopreserved cultures retained donor-specific CFTR modulator responsiveness. Modulator-induced forskolin/IBMX-stimulated currents correlated with changes in SCC (R = −0.512). CFTR inhibitor-sensitive currents correlated with FEV₁ (R = 0.564). Associations between forskolin/IBMX-stimulated currents and FEV₁ were positive but did not reach statistical significance using two-tailed analysis. BMI changes showed no significant association. Conclusions: Biobanked nasal epithelial cultures preserve clinically relevant CFTR modulator responses at the cohort level, supporting their use as functional assays for population-level assessment in cystic fibrosis. This cryopreservation-based strategy enables repeated testing and may expand access to theratyping beyond freshly obtained samples. Full article

Background and Objectives: Given the non-specificity of symptoms and complex methods for diagnosing heart failure, which are not applicable in screening, it is of great importance to develop a simple screening method for identifying systolic dysfunction of the heart based on available biosignals, one of which is a single-channel electrocardiogram (ECG). The method does not require the participation of medical staff. Aim: To create a screening model for detecting left ventricular systolic dysfunction in a complex analysis of single-channel ECG parameters using machine learning algorithms Methods: We included 624 patients aged 18 to 90 years. All patients underwent echocardiography and single-channel I-lead ECG recording using a portable electrocardiograph. The left ventricle ejection fraction (LV EF) was determined in the apical 2-chamber and 4-chamber view using the BIPLANE Simpson method and confirmed by two independent experts. Single-channel ECG analysis was performed using advanced signal processing and machine learning techniques. Results: For identifying LV EF below 52% in men and below 54% in women, the best result was demonstrated by “Lasso regression”: sensitivity 79.2%, specificity 81.7%, AUC = 0.849. For detection of LVEF below 40%, the “Extra Trees” model was the best, with a sensitivity of 83.1% and a specificity of 82.7%, AUC = 0.972. External testing of the algorithm was conducted on a sample of 600 patients. The accuracy was 98%, specificity 98.4%, and sensitivity 93.5%. Conclusions: The results indicate quite high diagnostic accuracy of screening for left ventricular systolic dysfunction when analyzing single-channel ECG parameters using modern signal processing and machine learning technologies. Full article

This study investigates the feasibility of using waste heat from generator sets as the low-temperature heat source for heat pumps in off-grid energy systems, addressing the need for more efficient and self-sufficient heating solutions. A conceptual model was developed in which a generator and an air-to-water heat pump operate within an insulated thermal chamber, enabling the recovery of waste heat to maintain a stable 15 °C inlet temperature for the heat pump. Theoretical analysis was supplemented with preliminary experimental tests performed on a small generator placed in a thermally insulated enclosure. Measurements of temperature rise and heat output allowed for verification of the real heat-recovery efficiency, which reached approximately 28%. Based on real household heating demand, this study evaluated annual heat demand, heat pump electricity consumption, and fuel requirements for several recovery scenarios (28%, 45%, and 60%). The results show that maintaining a constant 15 °C source temperature significantly improves heat-pump efficiency, reducing annual electricity demand. Increasing heat-recovery efficiency from 28% to 60% reduces fuel consumption by more than half and lowers the annual operating costs. The findings confirm the potential of generator-supported heat-pump systems to enhance energy efficiency in off-grid applications and provide a sound basis for further optimization and real-scale validation. Full article

Background/Objectives: Hemodialysis (HD) is the commonest life sustaining form of kidney replacement therapy in the world; however, this method of treatment have many adverse effects, and even a single HD session affects many organs, including the eyes. The aim of this study was to assess the effect of a single HD session on the ophthalmologic findings in patients with End-stage Renal Disease (ESRD). The second aim of the study was to examine the correlation of these changes with each other and between changes in systemic stressors related to the HD session. Methods: This was a single-center cross-sectional observational study conducted on 32 patients undergoing HD. Selected parameters of the anterior and posterior segment of the eye as well as systemic parameters were assessed before and after a single HD session. Results: Best corrected visual acuity (BCVA) improved, and lens thickness (LT), axial length (AXL), average macular thickness (MT), central MT and total vessel density (VD) of the deep capillary plexus DCP increased significantly after a single HD session. The Schirmer test results, tear break up time (TBUT), anterior chamber depth (ACD), central and average choroidal thickness (CT) decreased significantly after HD. Body weight loss was the only significant systemic change. Decrease in TBUT correlated positively with Schirmer’s test results decrease. Increase in CCT correlated positively with AXL increase. Decrease in central and average CT correlated positively with IOP decrease. Increase in central MT correlated positively with increase in average MT. Decrease in central CT correlated positively with average CT decrease. Change in VD of the SCP correlated positively with change in VD of DCP. Apart from the positive correlation between SBP change and Schirmer’s test results change, there were no correlations between systemic and ophthalmic parameters changes. Conclusions: Our study showed that HD affected the parameters of the anterior and posterior segments of the eye. Numerous correlations between these changes suggest that they are interrelated and represent the complex response of the eye to the HD process. Full article

Although bamboo holds great promise as a sustainable construction material in industry, its susceptibility to cracking during drying compromises its mechanical performance and limits its structural applications. This study aims to develop a predictive model for bamboo cracking and investigate effective mitigation strategies. A crack evaluation model for round bamboo was established based on an analysis of tangential stress and validated experimentally in a climate chamber. The model demonstrated a prediction accuracy of 75–80% with a built-in safety margin, while analysis revealed that outer surface strain, inner surface strain, radial elastic modulus, and culm outer diameter all positively correlated with tangential stress, highlighting the importance of controlling these factors to prevent cracking. Moreover, a surface-bonded palm fiber wrapping method was proposed and tested, which significantly enhanced the crack resistance and delayed crack initiation. The effect was most pronounced in 1-year-old bamboo, while culms aged 3, 5, and 7 years remained crack-free until moisture content fell below 5%. The proposed model accurately predicts cracking behavior in bamboo, offering theoretical support for its structural use and practical insights for crack prevention. Full article

Microbial fuel cell (MFC) technology represents a promising bioelectrochemical approach for the simultaneous generation of electricity and treatment of high-strength wastewater. However, the performance of MFCs strongly depends on the metabolic potential and synergistic interactions of the inoculated microbial community. This study evaluated the electrochemical activity and COD removal efficiency of three individual bacterial strains, Lysinibacillus sphericus A1, Bacillus cereus A2 and Lactococcus lactis A4, compared with a developed consortium under long-term operation using poultry slaughterhouse wastewater as a substrate. All inocula were tested in dual-chamber MFCs for 30 days, and performance indicators included power output, voltage, and removal of chemical oxygen demand (COD). The consortium showed the highest power of 170 mW/m² and the optimal voltage–current ratio at a current of 900 mA/m² and 245 mV under decreasing external resistance from 1000 to 50 Ω. The highest COD removal (84.4%) was also recorded, surpassing all pure cultures and demonstrating a significant improvement compared with B. cereus A2 and L. lactis A4. Meanwhile, the lowest power of 52 mA/m² was recorded during testing of L. lactis A4, at 650 mA/m² and 120 mV. Compared with single cultures, the consortium produced approximately 15% higher power density than L. sphericus A1, about 29% higher than B. cereus A2, and more than threefold higher than L. lactis A4. This study highlights the potential of a consortium as an efficient biocatalyst for MFC-mediated wastewater treatment and suggests that selecting complementary strains with diverse metabolic functions can substantially improve system performance. Full article

In the article we investigated the effectiveness of a synergistic system designed to reduce the fire hazard of flexible polyurethane (PUR) foams. The examined system consisted of a carbon-based filler graphene (G), carbon nanotubes (CNTs), or expanded graphite (EG) combined with melamine polyphosphate (MPP). The investigated polyurethane foams (PUR) were synthesized at room temperature via a polycondensation reaction between a polyol and an isocyanate, with an OH: NCO molar ratio of 2:1. Both the carbon fillers and melamine polyphosphate were homogeneously dispersed within the polyol component. Thermogravimetric analysis (TGA), cone calorimetry, and microcalorimetry were used to evaluate the influence of the fillers on the thermal stability and flammability of the PUR foams. The toxicity of the gaseous products was assessed using a coupled TG-gas analysis system, while the optical density of the evolved gases was determined using a Smoke Density Chamber (SDC). The obtained results demonstrated that the applied synergistic carbon-phosphorus filler system significantly reduced the fire hazard of the tested PUR foams. In particular, the EG5-MPP system enabled the formation of self-extinguishing materials. Full article

Organ-on-a-Chip (OOC) platforms are microfluidic systems that recreate key features of human organ physiology in vitro via controlled perfusion. Fluid mechanical stimuli strongly influence cell morphology and function, making this important for cardiovascular OOC applications exposed to pulsatile blood flow. However, many existing OOC devices employ relatively simple chamber geometries and steady inflow assumptions, which may cause non-uniform shear exposure to cells, create stagnant regions with prolonged residence time, and overlook the specific effects of pulsatile perfusion. Here, we used computational fluid dynamics (CFD) to investigate how chamber geometry and inflow conditions shape the near-wall flow environment on a cell culture surface at a matched cycle-averaged volumetric flow rate. Numerical results demonstrated that pillarized chambers markedly reduced relative residence time (RRT) versus the flat chamber, and the small pillar configuration produced the most uniform time-averaged wall shear stress (TAWSS) distribution among the tested designs. Phase-resolved analysis further showed that wall shear stress varies with waveform phase, indicating that steady inflow may not capture features of pulsatile perfusion. These findings provide practical guidance for pillar geometries and perfusion conditions to create more controlled and physiologically relevant microenvironments in OOC platforms, thus improving the reliability of cell experimental readouts. Full article

The construction of ultra-high voltage transmission lines puts extremely high demands on the high-altitude operation of heavy-load unmanned aerial vehicles (UAV). Air density and temperature at high altitudes have a great influence on the efficiency and stability of the UAV power system. Traditional regulation methods based on parameters pre-set or simple look-up tables cannot achieve the best adaptability. In this paper, we presents an intelligent method for the high-altitude adaptability control of heavy-load UAV power systems using a deep neural network. The proposed method collects real-time, multi-dimensional environmental parameters, including altitude, temperature, and air pressure, using a barometric altimeter and GPS receiver, constructs a High-Altitude Adaptive Regulation Network (HAARN), and intelligently learns complex nonlinear relationships to predict the optimal motor speed, propeller pitch angle, and current limit under the current environmental conditions so as to dynamically adjust power output. The HAARN model was trained on a dataset of 12,000 synchronized samples collected from both controlled environmental-chamber experiments (temperature range: −10 $°\mathrm{C}$ to 20 $°\mathrm{C}$; pressure range: 100–50 kPa, corresponding approximately to 0–5500 m) and multi-point plateau flight trials conducted at 2000 m, 3000 m, 4000 m, and 4500 m. This combined dataset was used for feature engineering, exhaustive-label generation, and model validation to ensure robust generalization across realistic high-altitude operating conditions. Experimental results show that, compared with traditional PID control and lookup-table approaches, the proposed method reduces thrust attenuation by about 12.5% and improves energy efficiency by 8.3% at the altitude of 4000 m. In addition, HAARN demonstrates consistent improvements across the tested altitude range (0–4500 m). Full article

Hypoxic preconditioning is increasingly explored to enhance the survival and vascularization of fat grafts. In this study, nanofat from donor mice was exposed to hypoxia (1% O₂) for 24 h to investigate the effects of this preconditioning protocol on the viability, gene expression and vascularization capacity of this mechanically processed fat derivative. Ex vivo analyses revealed that hypoxic preconditioning does neither affect apoptotic nor necrotic cell death within nanofat but significantly upregulates the expression of hypoxia-inducible factor (HIF)-1α and stromal cell-derived factor (SDF)-1 compared to non-preconditioned nanofat. Moreover, preconditioned nanofat exhibited a pro-angiogenic protein expression profile. For in vivo analyses, dermal substitutes were either seeded with preconditioned or non-preconditioned nanofat and transferred into dorsal skinfold chambers of mice to assess their vascularization by intravital fluorescence microscopy. Unexpectedly, implants seeded with preconditioned nanofat exhibited a significantly reduced functional microvessel density when compared to non-preconditioned controls. Immunohistochemical analyses also confirmed a lower microvessel density within the implants of the preconditioned group. These findings suggest that hypoxic preconditioning at 1% O₂ for 24 h cannot be recommended for enhancing the regenerative in vivo vascularization capacity of nanofat. Therefore, milder preconditioning protocols with shorter periods of hypoxia or higher oxygen levels should be alternatively tested in future studies. Full article

Resistance against water penetration is one of the key indicators of concrete durability in humid and pressurized environments. An intelligent model based on the XGBoost machine-learning algorithm was developed to predict the water penetration depth, using 1512 independent experimental measurements. The influential variables included water pressure, pressure duration, thermal cycles, fiber content, curing, and compressive strength. The investigated concrete specimens and field-tested structures in this study were exposed to arid and hot climatic conditions, and the proposed model was developed within this environmental context. To accurately simulate the water transport behavior, a cylindrical-chamber test was employed, enabling non-destructive and in-situ evaluation of structures. Correlation analysis revealed that compressive strength had the strongest negative influence (r = −0.598), while free curing exhibited the strongest positive influence (r = +0.654) on penetration depth. After hyperparameter optimization, the XGBoost model achieved the best performance (R² = 0.956, RMSE = 1.08 mm, MAE = 0.81 mm). Feature importance analysis indicated that penetration volume, pressure, and curing were the most significant predictors. According to the partial dependence analysis, both pressure and duration exhibited an approximately linear increase in penetration depth, while a W/C ratio below 0.45 and curing markedly reduced permeability. Microstructural interpretation using MIP, XRD, and SEM tests supported the physical interpretation of the trends identified by the machine-learning model. The results demonstrate that machine-learning-models can serve as fast and accurate tools for assessing durability and predicting permeability under severe environmental conditions. Finally, the permeability of several real structures was evaluated using the machine-learning approach, showing excellent prediction accuracy. Full article

In order to analyze the effect of environmental factors on the release of negative air ions (NAI) by green tree species, this study conducted an open top chamber (OTC) control test in Beijing. The tree species selected were Acer truncatum, Sophora japonica, Pinus bungeana, and Pinus tabuliformis. The experiment investigated the effects of environmental factors on NAI release under different relative humidity conditions. The results of the study showed that (1) the NAI release contribution (L), NAI release coefficient (n), NAI release rate (s), NAI instantaneous present amount (v), and total NAI release amount (Z) all showed positive responses to humidity. (2) Under constant temperature and light intensity, all five capability indicators increased with the humidity gradient (40–80%) and reached their maximum values at 80% humidity. (3) NAI release was positively correlated with humidity, and the correlation coefficients were: Pinus tabuliformis (R² = 0.33) > Sophora japonica (R² = 0.17) > Acer truncatum (R² = 0.15) = Pinus bungeana (R² = 0.15, p < 0.05). (4) Under constant temperature and light intensity, the NAI release contribution (L) and NAI release coefficient (n) responded most strongly to humidity in the 40–60% range, while the total NAI release amount (Z), NAI release rate (s), and NAI instantaneous present amount (v) responded more significantly in the 60–80% range. Acer truncatum showed the strongest response in terms of NAI release contribution (L) and NAI release coefficient (n), while Sophora japonica exhibited the most significant response in terms of NAI release rate (s), NAI instantaneous present amount (v), and total NAI release amount (Z). This study, conducted using an OTC, clarifies the independent role of humidity on NAI released by green tree species, providing a scientific basis for forest recreation and urban green space planning. Full article

Stack-driven ventilation is one of the key forms of natural ventilation. Yet, it has rarely been tested at full scale, even though such studies offer critical evidence for validating simplified theoretical models. To investigate stack-driven ventilation experimentally, a full-scale Future Home house was tested under controlled laboratory conditions in an environmental chamber at Energy House 2.0, in the absence of wind and with a stable indoor–outdoor temperature difference. The indoor air was heated to 35 °C, while the surrounding chamber was maintained at 15 °C. Subsequently, six windows were opened simultaneously for 24 h, three on the ground floor and three on the first floor. Air velocities were measured at each opening with hot-wire probes and converted into volumetric flow rates. The total inflow averaged 1.19 m³/s compared with a theoretical prediction of 1.93 m³/s, indicating systematic overestimation by the stack effect equation. A back-calculation suggested a discharge coefficient of 0.37 instead of 0.60. The cooling energy from natural ventilation was quantified and evaluated for its capability to reduce internal air temperature in overheating conditions. The findings increase the understanding of buoyancy-driven ventilation, while underlining the need to calibrate simplified equations against experimental data. Full article

We report a laboratory search for axion-like particles (ALPs) in the eV mass range using a variable-angle three-beam-stimulated resonant photon collider. The scheme independently focuses and collides three laser beams, providing a cosmology- and astrophysics-independent test. By varying the angles of incidence, the center-of-mass energy can be scanned continuously across the eV range. In this work, we operated the collider in a vacuum chamber at a large-angle configuration, verified the spacetime overlap of the three short pulses, and performed a first search centered at $m_a\simeq 2.27\mathrm{eV}$. No excess was observed. Thus, we set a $95\%$ C.L. upper limit on the pseudoscalar two-photon coupling, with a minimum sensitivity of $g/M\simeq 4.2\times {10}^{-10}{\mathrm{GeV}}^{-1}$ at $m_a=2.27\mathrm{eV}$. This provides the first model-independent upper limit on the coupling that reaches the KSVZ benchmark in the eV regime and demonstrates the feasibility of eV-scale mass scans in the near future. Full article

The study aimed to determine the effect of acute, one-time physical effort performed under different environmental temperature conditions on erythrocyte deformability in healthy young men. This exploratory randomized parallel-group study involved 30 men randomly assigned to an experimental group exercising at −10 °C in a climatic chamber and a control group exercising under thermoneutral outdoor conditions. Erythrocyte deformability was assessed using the elongation index (EI), reflecting erythrocyte elasticity and the ability to pass through microcirculation vessels. Participants performed an incremental 20 m shuttle run test. Venous blood samples were collected before and immediately after exercise, and erythrocyte deformability was analyzed using a Lorrca analyzer across a shear stress range of 0.30–60.00 Pa. A two-factor repeated-measures analysis of variance was applied. An increase in EI after exercise was observed in both groups, predominantly at higher shear stress values, indicating enhanced erythrocyte deformability under conditions of increased shear forces. However, the magnitude of post-exertion changes differed between groups. At lower shear stress levels (0.30 Pa and 0.58 Pa), EI tended to decrease after exercise. These findings indicate that a single bout of physical effort influences erythrocyte deformability, while the potential effects of cold exposure on this response remain uncertain and warrant further investigation. Full article