Search Results (38)

As a crucial reactive oxygen species, hydrogen peroxide (H₂O₂) serves as both a physiological regulator and a pathological indicator in human systems. Its urinary concentration has emerged as a valuable biomarker for assessing metabolic disorders and renal function. While conventional colorimetric determination methods predominantly employ enzymatic or nanozyme catalysts, we present an innovative non-catalytic approach utilizing the redox-responsive properties of organic neutral radicals. Specifically, we designed and synthesized a novel radical TTM-DMODPA based on the tris (2,4,6-trichlorophenyl) methyl (TTM) scaffold, which exhibits remarkable optical tunability and oxidative sensitivity. This system enables dual-mode H₂O₂ quantification: (1) UV-vis spectrophotometry (linear range: 2.5–250 μmol/L, LOD: 1.275 μmol/L) and (2) smartphone-based visual analysis (linear range: 2.5–250 μmol/L, LOD: 3.633 μmol/L), the latter being particularly suitable for point-of-care testing. Validation studies using urine samples demonstrated excellent recovery rates (96–104%), confirming the method’s reliability for real-sample applications. Our work establishes a portable, instrument-free platform for urinary H₂O₂ determination, with significant potential in clinical diagnostics and environmental monitoring. Full article

This prospective, non-blinded study assessed the performance of a portable anesthesia machine with an oxygen concentrator (PAM_OC) across various oxygen flow rates and vaporizer settings, incorporating both in vitro and in vivo experiments. The oxygen delivery test measured the time required to reach 90% fraction of inspired oxygen (FIO₂) at various flow rates. The vaporizer test assessed the time to stabilize maximum fraction of inspired isoflurane (FIIso) concentration at various oxygen flow rate and vaporizer settings. In the in vivo test, six adult male Beagle dogs (11.4 ± 1.4 kg) were evaluated. The in vivo evaluation included monitoring physiological parameters during isoflurane anesthesia. The higher flow rates significantly reduced the time to plateau for FIO₂ (p < 0.001). Maximum FIIso values were lower than the vaporizer dial settings, and increased oxygen flow rates significantly reduced the time required to reach target values (p < 0.001). Physiological parameters remained stable throughout anesthesia, confirming adequate oxygenation and anesthetic maintenance. The PAMoc, despite its lower pounds per square inch, yielded predictable outcomes consistent with those obtained in conventional anesthesia systems. These results demonstrated the viability of the PAMoc for anesthesia administration in the field and other challenging environments. Full article

Tryptophan-like fluorescence (TLF) is a key indicator of water contamination, particularly of microbial origin and biodegradable organic compounds. This study introduces an Internet of Things (IoT)-enabled portable device (IoT-TLF-PD) for real-time monitoring of microbial quality and biochemical oxygen demand (BOD₅). The device was tested using surface water (S1), secondary wastewater (S2), and final wastewater effluents (S3). Results showed significant correlations between TLF intensity, Escherichia coli (E. coli) counts, and BOD₅, with R² values of 0.77 (S1), 0.61 (S2), and 0.76 (S3) for BOD₅, and 0.60 (S2) to 0.68 (S3) for E. coli. Considering various water samples, a strong correlation was found between E. coli and BOD₅ with TLF intensity normalized by total organic carbon (TOC) concentration (TLF intensity/TOC). The R² value for E. coli was 0.92, and for BOD₅, it was 0.77. This indicates the necessity of accounting for organic matter concentration when interpreting TLF intensity in water quality assessments. The study confirmed the potential of the IoT-TLF-PD to serve as a cost-effective, real-time indicator for assessing water quality, especially for detecting microbial contamination. This technology offers a valuable tool for environmental monitoring and water management. Full article

In the context of developing countries, medical instruments are imported from foreign countries. To overcome this challenge, herein the design of an oxygen analyzer using ultrasonic flow sensor technology and a microcontroller while promoting local innovation and reducing dependency on imported equipment is presented. Moreover, this design aims to enhance patient care by ensuring accurate oxygen concentration and flow rate measurements on ventilators and oxygen concentrators. The data measured using the proposed system have been validated by comparison with data obtained using standard oxygen analyzer equipment like the VT-900 Gas Flow Analyzer from Fluke Biomedical and the Ultra Max oxygen analyzer. Measurements were conducted on hospital ventilators, with oxygen concentration (FiO₂) being set to range from 21% to 100%, with increments of 5%, and the flow rate was set to range from 1 L/m to 10 L/m. The results show an error value of 2.1% for oxygen concentration measurements and a value of 0.6 L/m for flow rate measurements. Based on our analysis, it can be concluded that the proposed system works well. Additionally, it offers portability, affordability, and user-friendliness, overcoming the limitations of existing options. This project seeks to contribute to the healthcare infrastructure in developing countries like Nepal, India, Bangladesh, etc., by providing a domestically produced solution for oxygen analysis. Full article

Background: Groundwater contamination with chlorinated hydrocarbons (CLHCs), particularly with tetrachloroethylene (PCE) and trichloroethylene (TCE), which are used in industry for degreasing and cleaning, can be considered a serious problem concerning the entire world. In addition to conventional groundwater monitoring from a network of wells, several screening methods have been proposed to identify and delineate groundwater contamination with volatile organic compounds (VOCs), such as soil gas measurement, bioindicators, direct-push technologies or geophysical techniques. The main objectives of this study were to confirm the feasibility of active soil gas screening for the characterisation of groundwater contamination with CLHCs under the wider area of the former refrigerator manufacturer (city of Zlaté Moravce, western Slovakia) and to evaluate the human health risks through exposure to CLHCs present in groundwater. Methods: a conventional site investigation based on concentration measurements using gas chromatography-mass spectrometry from monitoring wells and soil gas measurements using a portable photo-ionisation detector device were applied. Results: The chemical analyses showed the persistent contamination of groundwater, with PCE, TCE and other CLHCs, such as cis-1,2-dichloroethylene (cis-DCE) or 1,1,2-trichloroethane (TCA), being most severe in the zone of the former factory (up to 2690, 83,900, 6020 and 156 µg/L for PCE, TCE, cis-DCE and TCA, respectively), but also extended into the residential zone located 600 m along the groundwater flow line. Soil gas measurements of VOCs and other chemical parameters (methane (CH₄), total petroleum (TP), carbon dioxide (CO₂) and oxygen (O₂)) from a densely designed network of sampling points (n = 300) helped trace the current state of groundwater contamination. Spatial distribution maps of VOCs concentrations in soil gas clearly marked the areas of the highest CLHCs concentrations in groundwater. Principal component analysis (PCA) confirmed a significant correlation of VOCs and CLHCs with the first principal component, PC1, explaining up to 84% of the total variability of the concentration data, suggesting that VOCs in soil gas were a suitable marker of the extent of groundwater contamination with CLHCs. Despite severe groundwater contamination with CLHCs reaching residential areas, local residents were not exposed to non-carcinogenic risks, but a potential carcinogenic risk was present. Conclusions: based on the results, it could be confirmed that soil gas screening is an efficient and quick tool for identifying the sources of groundwater contamination with CLHCs as well as the level of this contamination. Full article

Background: The biomechanical and physiological adaptations to resisted running have been well documented in sprinting; however, their impact at submaximal speeds, such as those typical of long-distance running, remains unclear. This study aimed to evaluate the impact of running with a weighted vest, loaded with 5% and 10% of body mass, on the physiological and mechanical variables of trained trail runners. Methods: Fifteen male trail runners completed an incremental protocol to exhaustion on a treadmill with 0%, 5%, and 10% of their body mass (BM), in random order, with one week of separation between the tests. The maximality of the test was confirmed by measuring lactate concentrations at the end of the test. Oxygen consumption ($\dot{\mathrm{V}}$O₂) and respiratory exchange ratio (RER) were recorded using a portable gas analyzer (Cosmed K5), and ventilatory thresholds 1 and 2 (VT1, VT2) were calculated individually. Running power was averaged for each speed stage using the Stryd device. Finally, the peak values and those associated with VT1 and VT2 for speed, power (absolute and normalized by body mass), $\dot{\mathrm{V}}$O₂, RER, and the cost of transport (CoT) were included in the analysis. Results: One-way repeated-measures ANOVA revealed a detrimental effect of the extra load on maximum speed and speed at ventilatory thresholds (p ≤ 0.003), with large effect sizes (0.34–0.62) and a nonlinear trend detected in post hoc analysis. Conclusions: Using running power to control the intensity of effort while carrying extra weight provides a more stable metric than speed, particularly at aerobic intensities. Future research in trail running should investigate the effects of weighted vests across various terrains and slopes. Full article

This study aimed to monitor the oxygenation and blood supply in three quadriceps muscles [the vastus lateralis (VL), vastus medialis (VM), and rectus femoris (RF)] during squatting exercise to exhaustion. Eighteen young resistance-trained males performed five sets of 15 back squats in a Smith machine, with two warm-up sets [at 14% and 45% of the 15-repetition maximum (15RM)] and three main sets at 100% of the 15RM. Three near-infrared spectroscopy devices were attached to the VL, VM, and RF to record the muscle oxygen saturation (SmO₂) and total hemoglobin (tHb, an index of muscle blood supply). The blood lactate concentration was measured after each set with a portable analyzer. The SmO₂ and tHb data were analyzed by repeated-measures two-way ANOVA (muscle × set). Lactate data were analyzed by repeated-measures one-way ANOVA. The statistical significance was set at α = 0.05. The SmO₂ dropped during each set (hitting zero in many instances) and was reinstated during recovery. The three main sets caused severe deoxygenation in the VL and VM, as opposed to moderate deoxygenation in the RF. From one set to the next, the initial value and the drop in the SmO₂ increased, whereas the final SmO₂ value decreased. The tHb increased in the VL, did not change considerably in the VM, and decreased in the RF during each set. The blood lactate concentration increased gradually from one set to the next, reaching about 10 mmol/L. These findings show pronounced differences in the physiological and metabolic responses of three quadriceps muscles to squatting exercise, thus highlighting the importance of studying such responses at multiple sites. Full article

Biodigestion in farming and agriculture offers environmental and economic benefits, but investing in biodigesters carries real-world risks for enterprises. This study analyzes methane (CH₄) emissions from a poultry farm biodigester in Tenerife Island, Canary Islands, Spain, conceptualized as a right-angled prism measuring 45 m wide, 25 m long, and 12 m tall, with an internal volume of approximately 13,500 m³. Using a Neon tracer gas technique, CH₄ emission rates were quantified in situ during two surveys in February 2021 and October 2022, capturing seasonal variability in ambient conditions. Biogas analysis was performed using a portable micro-gas chromatograph in less than 5 min, revealing stable CH₄ production rates of approximately 200 kg·d⁻¹ (~310 m³·d⁻¹) and 330 kg·d⁻¹ (~500 m³·d⁻¹) for the two experiments, respectively. The composition of biogas indicated CH₄ concentrations of around 38–43%, with the remaining composition consisting of carbon dioxide (19–26%), nitrogen (36–27%), oxygen (7–4%), and trace amounts of other gases. A comparison with a theoretical model showed a good correlation. This approach enhances biodigester investment attractiveness by enabling enterprises to optimize efficiency promptly. The obtained data were used to estimate the energy potential of biogas from chicken farms in the Canary Islands. Full article

The rampant spread and death rate of the recent coronavirus pandemic related to the SARS-CoV-2 respiratory virus have underscored the critical need for affordable, portable virus diagnostics, particularly in resource-limited settings. Moreover, efficient and timely monitoring of vaccine efficacy is needed to prevent future widespread infections. Electrochemical immunosensing poses an effective alternative to conventional molecular spectroscopic approaches, offering rapid, cost-effective, sensitive, and portable electroanalysis of disease biomarkers and antibodies; however, efforts to improve binding efficiency and sensitivity are still being investigated. Graphene quantum dots (GQDs) in particular have shown promise in improving device sensitivity. This study reports the development of a GQD-functionalized point-of-contamination device leveraging the selective interactions between SARS-CoV-2-specific Spike (S) Protein receptor binding domain (RBD) antigens and IgG anti-SARS-CoV-2-specific S-protein antibodies at screen-printed carbon electrode (SPCE) surfaces. The immunocomplexes formed at the GQD surfaces result in the interruption of the redox reactions that take place in the presence of a redox probe, decreasing the current response. Increased active surface area, conductivity, and binding via EDC/NHS chemistry were achieved due to the nanomaterial inclusion, with 5 nm, blue luminescent GQDs offering the best results. GQD concentration, EDC/NHS ratio, and RBD S-protein incubation time and concentration were optimized for the biosensor, and inter- and intra-screen-printed carbon electrode detection was investigated by calibration studies on multiple and single electrodes. The single electrode used for the entire calibration provided the best results. The label-free immunosensor was able to selectively detect anti-SARS-CoV-2 IgG antibodies between 0.5 and 100 ng/mL in the presence of IgM and other coronavirus antibodies with an excellent regression of 0.9599. A LOD of 2.028 ng/mL was found, offering comparable findings to the literature-reported values. The detection sensitivity of the sensor is further compared to non-specific IgM antibodies. The developed GQD immunosensor was compared to other low-oxygen content carbon nanomaterials, namely (i) carbon quantum dot (CQD), (ii) electrochemically reduced graphene oxide, and (iii) carbon black-functionalized devices. The findings suggest that improved electron transfer kinetics and increased active surface area of the CNs, along with surface oxygen content, aid in the detection of anti-SARS-CoV-2 IgG antibodies. The novel immunosensor suggests a possible application toward monitoring of IgG antibody production in SARS-CoV-2-vaccinated patients to study immune responses, vaccine efficacy, and lifetime to meet the demands for POC analysis in resource-limited settings. Full article

The high altitude in mountainous regions results in lower atmospheric pressure, oxygen concentration and temperature, leading to lower combustion efficiency in motor vehicles. Therefore, there may be differences in carbon dioxide (CO₂), carbon monoxide (CO), and nitrogen oxides (NO_x) emissions characteristics at different altitudes. In this study, a portable emission measurement system was used to investigate the effects of varying elevations on the emission factors of CO₂, CO, and NO_x on diesel and gasoline-powered vehicles at altitudes ranging from 2270 to 4540 m in the Qinghai–Tibet Plateau of China. Additionally, the influencing factors of CO₂, CO, and NO_x emissions were studied. Results showed that the CO₂, CO, and NO_x emission factors for diesel vehicles varied in the range of 161.83–195.54, 0.59–0.77, and 4.61–6.58 g/km; the population means with 90% confidence intervals were 178.54, 0.68, and 5.60 g/km, respectively. For gasoline vehicles, the CO₂, CO, and NO_x emission factors varied in the range of 161.66–181.98, 0.95–1.06, and 0.12–0.25 g/km; the population means with 90% confidence intervals were 171.82, 1.01, and 0.19 g/km, respectively. Overall, the emission factors of diesel vehicles were higher than those of gasoline vehicles, and the emissions increased with increasing altitude. Atmospheric pressure was identified as the primary environmental factor affecting CO₂, CO, and NO_x emissions. As the speed of motor vehicles increased, the emission of CO₂ also increased, while there was a quadratic relationship with acceleration. This study provides a reference and guidance for vehicle pollution control in high-altitude regions. Full article

Direct methanol fuel cells (DMFCs) are promising form of energy conversion technology that have the potential to take the role of lithium-ion batteries in portable electronics and electric cars. To increase the efficiency of DMFCs, many operating conditions ought to be optimized. Developing a reliable fuzzy model to simulate DMFCs is a major objective. To increase the power output of a DMFC, three process variables are considered: temperature, methanol concentration, and oxygen flow rate. First, a fuzzy model of the DMFC was developed using experimental data. The best operational circumstances to increase power density were then determined using the beetle antennae search (BAS) method. The RMSE values for the fuzzy DMFC model are 0.1982 and 1.5460 for the training and testing data. For training and testing, the coefficient of determination (R²) values were 0.9977 and 0.89, respectively. Thanks to fuzzy logic, the RMSE was reduced by 88% compared to ANOVA. It decreased from 7.29 (using ANOVA) to 0.8628 (using fuzzy). The fuzzy model’s low RMSE and high R² values show that the modeling phase was successful. In comparison with the measured data and RSM, the combination of fuzzy modeling and the BAS algorithm increased the power density of the DMFC by 8.88% and 7.5%, respectively, and 75 °C, 1.2 M, and 400 mL/min were the ideal values for temperature, methanol concentration, and oxygen flow rate, respectively. Full article

In recent years, research on emotion recognition has become more and more popular, but there are few studies on emotion recognition based on cerebral blood oxygen signals. Since the electroencephalogram (EEG) is easily disturbed by eye movement and the portability is not high, this study uses a more comfortable and convenient functional near-infrared spectroscopy (fNIRS) system to record brain signals from participants while watching three different types of video clips. During the experiment, the changes in cerebral blood oxygen concentration in the 8 channels of the prefrontal cortex of the brain were collected and analyzed. We processed and divided the collected cerebral blood oxygen data, and used multiple classifiers to realize the identification of the three emotional states of joy, neutrality, and sadness. Since the classification accuracy of the convolutional neural network (CNN) in this research is not significantly superior to that of the XGBoost algorithm, this paper proposes a CNN-Transformer network based on the characteristics of time series data to improve the classification accuracy of ternary emotions. The network first uses convolution operations to extract channel features from multi-channel time series, then the features and the output information of the fully connected layer are input to the Transformer netork structure, and its multi-head attention mechanism is used to focus on different channel domain information, which has better spatiality. The experimental results show that the CNN-Transformer network can achieve 86.7% classification accuracy for ternary emotions, which is about 5% higher than the accuracy of CNN, and this provides some help for other research in the field of emotion recognition based on time series data such as fNIRS. Full article

Membrane-less fuel cells are a promising power source for portable applications that enable the solving of membrane-related issues, such as water management and high cost, in conventional fuel cells. Apparently, research on this system uses a single electrolyte. This study focused on enhancing the performance of membrane-less fuel cells by introducing multiple reactants that are dual electrolytes with hydrogen peroxide (H₂O₂) and oxygen as oxidants in membrane-less direct methanol fuel cells (DMFC). The conditions tested for the system are (a) acidic, (b) alkaline, (c) dual medium with oxygen as an oxidant, and (d) dual medium and dual oxygen and hydrogen peroxide as an oxidant. Additionally, the effect of fuel utilization on different electrolyte and fuel concentrations was also studied. It was found that the fuel utilization decreases dramatically with the increasing of the fuel concentration, but it improved with the increasing of the electrolyte concentration until 2M. The performance of the dual oxidants in dual-electrolyte membrane-less DMFCs was 15.5 mW cm⁻² of the power density achieved before optimization. Later, the system was optimized, and the power density increased to 30 mW cm⁻². Finally, this work presented the stability of the cell using the suggested parameters from the optimization process. This study indicated that the performance of the membrane-less DMFC increased for dual electrolytes with mixed oxygen and hydrogen peroxide as oxidants compared to a single electrolyte. Full article

Introduction: Toxic aldehydic lipid oxidation products (LOPs) arise from the thermo-oxidative deterioration of unsaturated fatty acids present in heated culinary oils when exposed to high-temperature frying episodes, and currently these effects represent a major public health concern. Objectives: In this study, we investigated the applications of low-field (LF), benchtop NMR analysis to detect and quantify toxic aldehyde species in culinary oils following their exposure to laboratory-simulated shallow frying episodes (LSSFEs) at 180 °C. Four culinary oils of variable fatty acid (FA) composition were investigated to determine the analytical capabilities of the LF NMR instrument. Oil samples were also analysed using a medium-field (400 MHz) NMR facility for comparative purposes. Results: Aldehydes were quantified as total saturated and total α,β-unsaturated classes. The time-dependent production of α,β-unsaturated aldehydes decreased in the order chia > rapeseed ≈ soybean > olive oils, as might be expected from their polyunsaturated and monounsaturated FA (PUFA and MUFA, respectively) contents. A similar but inequivalent trend was found for saturated aldehyde concentrations. These data strongly correlated with medium-field ¹H NMR data obtained, although LF-determined levels were significantly lower in view of its inability to detect or quantify the more minor oxygenated aldehydic LOPs present. Lower limit of detection (LLOD) values for this spectrometer were 0.19 and 0.18 mmol/mol FA for n-hexanal and trans-2-octenal, respectively. Aldehydic lipid hydroperoxide precursors of aldehydic LOPs were also detectable in LF spectra. Conclusions: We therefore conclude that there is scope for application of these smaller, near-portable NMR facilities for commercial or ‘on-site’ quality control determination of toxic aldehydic LOPs in thermally stressed frying oils. Full article

The current study aimed to evidence the strengths and weaknesses of two indirect methods for assessing the anaerobic alactic contribution to a specific CrossFit^® workout. Thirty experienced crossfitters performed the Fran workout at maximal intensity, and ventilatory data were collected during the recovery period using a telemetric portable gas analyser to assess the oxygen uptake (VO₂) of the off-kinetics fast component (Ana_recovery). The kinetics of maximal phosphocreatine splitting (Ana_PCr) were determined based on the literature. No differences between the two methods were observed (31.4 ± 4.0 vs. 30.4 ± 4.1 kJ for Ana_recovery and Ana_PCr, respectively). Despite the existence of some caveats (e.g., errors derived from a delay at the onset of VO₂ recovery and the assumption of given values in the concentration of phosphocreatine per kilogram of wet muscle, respectively) in both methods, the data indicate that they yield similar results and allow for estimations of alactic energy contribution from a short-duration and high intensity CrossFit^® routine. The current data contributes to CrossFit^® workout evaluations and training strategies, helping researchers to evaluate crossfitters more accurately. The advantage of the two methods used in the current study is that they are non-invasive, which differs greatly from muscle biopsies. Full article