Search Results (14)

Antimicrobial resistance (AMR) presents a global health challenge, necessitating comprehensive surveillance and intervention strategies. Wastewater-based epidemiology (WBE) is a promising tool that can be utilized for AMR monitoring by offering population-level insights into microbial dynamics and resistance gene dissemination in communities. This review (n = 29 papers) examines the current landscape of utilizing WBE for AMR surveillance with a focus on methodologies, findings, and gaps in understanding. Reported methods from the reviewed literature included culture-based, PCR-based, whole genome sequencing, mass spectrometry, bioinformatics/metagenomics, and antimicrobial susceptibility testing to identify and measure antibiotic-resistant bacteria and antimicrobial resistance genes (ARGs) in wastewater, as well as liquid chromatography-tandem mass spectrometry to measure antibiotic residues. Results indicate Escherichia coli, Enterococcus spp., and Pseudomonas spp. are the most prevalent antibiotic-resistant bacterial species with hospital effluent demonstrating higher abundances of clinically relevant resistance genes including bla, bcr, qnrS, mcr, sul1, erm, and tet genes compared to measurements from local treatment plants. The most reported antibiotics in influent wastewater across studies analyzed include azithromycin, ciprofloxacin, clindamycin, and clarithromycin. The influence of seasonal variation on the ARG profiles of communities differed amongst studies indicating additional factors hold significance when examining the conference of AMR within communities. Despite these findings, knowledge gaps remain, including longitudinal studies in multiple and diverse geographical regions and understanding co-resistance mechanisms in relation to the complexities of population contributors to AMR. This review underscores the urgent need for collaborative and interdisciplinary efforts to safeguard public health and preserve antimicrobial efficacy. Further investigation on the use of WBE to understand these unique population-level drivers of AMR is advised in a proposed framework to inform best practice approaches moving forward. Full article

Indoor sports facilities face distinctive indoor air quality (IAQ) challenges due to high occupant density, elevated metabolic emissions, and diverse pollutant sources associated with physical activity. This review presents a narrative synthesis of multidisciplinary evidence concerning IAQ in sports environments. It explores major pollutant categories, including carbon dioxide (CO₂), particulate matter (PM), volatile organic compounds (VOCs), and airborne microbial agents, highlighting their sources, behavior during exercise, and associated health risks. Research shows that physical activity can increase PM concentrations by up to 300%, and CO₂ levels frequently exceed 1000 ppm in inadequately ventilated spaces. The presence of semi-volatile organics and bioaerosols further complicates pollutant dynamics, especially in humid and densely occupied areas. Measurement technologies such as optical sensors, chromatographic methods, and molecular techniques are reviewed and compared for their applicability to dynamic indoor settings. Existing IAQ standards across China, the USA, the EU, the UK, and WHO are examined, revealing a lack of activity-specific thresholds and insufficient responsiveness to real-time conditions. Mitigation strategies (e.g., including demand-controlled ventilation, use of low-emission materials, liquid chalk substitutes, and integrated HEPA-UVGI purification systems) are evaluated, many demonstrating pollutant removal efficiencies over 80%. The integration of intelligent building management systems is emphasized for enabling real-time monitoring and adaptive control. This review concludes by identifying research priorities, including the development of activity-sensitive IAQ control frameworks and long-term health impact assessments for athletes and vulnerable users. Full article

Downhole kick is one of the most severe safety hazards in deep and ultra-deep well drilling operations. Traditional monitoring methods, which rely on surface flow rate and fluid level changes, are limited by their delayed response and insufficient sensitivity, making them inadequate for early warning. This study proposes a real-time monitoring technique for gas content in drilling fluid based on the attenuation principle of Ba-133 γ-rays. By integrating laboratory static/dynamic experiments and Geant4-11.2 Monte Carlo simulations, the influence mechanism of gas–liquid two-phase media on γ-ray transmission characteristics is systematically elucidated. Firstly, through a comparative analysis of radioactive source parameters such as Am-241 and Cs-137, Ba-133 (main peak at 356 keV, half-life of 10.6 years) is identified as the optimal downhole nuclear measurement source based on a comparative analysis of penetration capability, detection efficiency, and regulatory compliance. Compared to alternative sources, Ba-133 provides an optimal energy range for detecting drilling fluid density variations, while also meeting exemption activity limits (1 × 10⁶ Bq) for field deployment. Subsequently, an experimental setup with drilling fluids of varying densities (1.2–1.8 g/cm³) is constructed to quantify the inverse square attenuation relationship between source-to-detector distance and counting rate, and to acquire counting data over the full gas content range (0–100%). The Monte Carlo simulation results exhibit a mean relative error of 5.01% compared to the experimental data, validating the physical correctness of the model. On this basis, a nonlinear inversion model coupling a first-order density term with a cubic gas content term is proposed, achieving a mean absolute percentage error of 2.3% across the full range and R² = 0.999. Geant4-based simulation validation demonstrates that this technique can achieve a measurement accuracy of ±2.5% for gas content within the range of 0–100% (at a 95% confidence interval). The anticipated field accuracy of ±5% is estimated by accounting for additional uncertainties due to temperature effects, vibration, and mud composition variations under downhole conditions, significantly outperforming current surface monitoring methods. This enables the high-frequency, high-precision early detection of kick events during the shut-in period. The present study provides both theoretical and technical support for the engineering application of nuclear measurement techniques in well control safety. Full article

Background: Given the poor prognosis of metastatic pancreatic adenocarcinoma (mPDAC), closer disease monitoring through liquid biopsy, most frequently based on serial measurements of cell-free mutated KRAS (KRAS^mut cfDNA), has become a highly active research focus, aimed at improving patients’ long-term outcomes. However, most of the available data show only a limited predictive and prognostic value of single-parameter-based methods. We hypothesized that a combined longitudinal analysis of KRAS^mut cfDNA and novel protein biomarkers could improve risk stratification and molecular monitoring of patients with mPDAC. Methods: We prospectively collected 160 plasma samples from 47 patients with mPDAC at our institution. Highly sensitive single-target ddPCR assays were employed to detect and quantify KRAS^mut cfDNA. Additionally, analysis of ten protein biomarkers was performed through Enzyme-linked Immunosorbent Assay (ELISA), and Carbohydrate-Antigen 19-9 (CA 19-9) dynamics were registered. Results: KRAS^mut cfDNA was detectable in 37/47 (78.7%) patients throughout the course of study, and CA 19-9 levels were elevated in 40 out of 47 (85.1%) patients. KRAS^mut cfDNA increase at the time of the first follow-up could predict inferior progression-free survival (PFS) (Hazard ratio (HR) = 3.40, p = 0.0003) and overall survival (OS) (HR = 4.91, p < 0.0001). In contrast to CA 19-9 kinetics, which were not predictive of outcome, integrated analysis of KRAS^mut cfDNA combined with six evaluated circulating protein biomarkers allowed basal risk stratification at the time of the first follow-up (HR = 10.2, p = 0.0014). Conclusions: A combined longitudinal analysis of KRAS^mut cfDNA with selected protein biomarkers offers significantly improved prognostic value for patients with mPDAC compared to single-parameter methods. This innovative approach is a step forward in the molecular monitoring of mPDAC and should be validated in further prospective studies. Full article

Oxytocin and cortisol (OXY and CORT) are hormones related to stress, cognitive, and social behaviors. Their detection is relevant to epidemiological studies aimed at investigating the effects of stressor factors on human life. The aim of this study was to develop and validate an assay for the measurement of OXY and CORT in saliva samples using liquid chromatography/tandem mass spectrometry (LC-MS/MS) in the presence of deuterated analogs. A 500 mL aliquot of oral fluid, obtained by the centrifugation of a chewed swab, was purified by solid-phase extraction. Analytes were then separated using C18 reversed-phase chromatography, subjected to positive electrospray ionization, and then quantified using a triple-quadrupole mass detector in multiple-reaction monitoring mode. The limits of quantification and the linear dynamic ranges were 2.0 × 10⁻³ and 0.5 nmol/L, and up to 1.0 × 10⁻¹ and 20 nmol/L for OXY and CORT, respectively. Inter- and intra-run precision, expressed as relative standard deviation, was <7%, and accuracy was within 93–104% of the theoretical concentrations. The evaluation of matrix effects showed that the use of internal standards controlled sources of bias. The high sensitivity of the method allowed the quantification of OXY and CORT in the salivary samples of both adults and children: levels of CORT ranged from 0.6 to 18.5 nmol/L, while OXY levels were two orders of magnitude lower (from 1.7 × 10⁻³ to 1.1 × 10⁻² nmol/L). To our knowledge, this is the first method that can analyze, in the same chromatographic run, both hormones in saliva samples. Full article

Dynamic liquid level monitoring and measurement in oil wells is essential in ensuring the safe and efficient operation of oil extraction machinery and formulating rational extraction policies that enhance the productivity of oilfields. This paper presents an intelligent infrasound-based measurement method for oil wells’ dynamic liquid levels; it is designed to address the challenges of conventional measurement methods, including high costs, low precision, low robustness and inadequate real-time performance. Firstly, a novel noise reduction algorithm is introduced to effectively mitigate both periodic and stochastic noise, thereby significantly improving the accuracy of dynamic liquid level detection. Additionally, leveraging the PyQT framework, a software platform for real-time dynamic liquid level monitoring is engineered, capable of generating liquid level profiles, computing the sound velocity and liquid depth and visualizing the monitoring data. To bolster the data storage and analytical capabilities, the system incorporates an around-the-clock unattended monitoring approach, utilizing Internet of Things (IoT) technology to facilitate the transmission of the collected dynamic liquid level data and computed results to the oilfield’s central data repository via LoRa and 4G communication modules. Field trials on dynamic liquid level monitoring and measurement in oil wells demonstrate a measurement range of 600 m to 3000 m, with consistent and reliable results, fulfilling the requirements for oil well dynamic liquid level monitoring and measurement. This innovative system offers a new perspective and methodology for the computation and surveillance of dynamic liquid level depths. Full article

The aim of this study was to develop and validate a fast and sensitive bioanalytical method for the accurate quantification of fosfomycin concentrations in human prostatic tissue. The sample preparation method only required milligrams of tissue sample. Each sample was mixed with two times its weight of water and homogenized. A methanol solution that was three times the volume of the internal standard (fosfomycin-13C3) was added, followed by vortex mixing and centrifugation. After its extraction from the homogenized prostatic tissue, fosfomycin was quantified by means of a liquid chromatography–tandem mass spectrometry (LC-MS/MS) triple quadrupole system operating in negative electrospray ionization and multiple reaction monitoring detection mode. The analytical procedure was successfully validated in terms of specificity, sensitivity, linearity, precision, accuracy, matrix effect, extraction recovery, limit of quantification, and stability, according to EMA guidelines. The validation results, relative to three QC levels, were 9.9% for both the within-day and inter-day accuracy (BIAS%); 9.8% for within-day precision; and 9.9 for between-day precision. A marked matrix effect was observed in the measurements but was corrected by normalization with the internal standard. The average total recovery was high (approximatively 97% at the three control levels). The dynamic range of the method was 0.1–20 μg/g (R² of 0.999). Negligible carry-over was observed after the injection of highly concentrated samples. F in the sample homogenate extracts was stable at 10 °C and 4 °C for at least 24 h. In the tissue sample freeze–thaw experiments, a significant decrease in F concentrations was observed after only two cycles from −80 °C to room temperature. The novel method was successfully applied to measure fosfomycin in prostatic tissue samples collected from 105 patients undergoing prostatectomy. Full article

Global precipitation is becoming increasingly intense due to the extreme climate. Therefore, creating new technology to manage water resources is crucial. To create a sustainable urban and ecological environment, a water level and water quality control system implementing artificial intelligence is presented in this research. The proposed smart monitoring system consists of four sensors (two different liquid level sensors, a turbidity and pH sensor, and a water oxygen sensor), a control module (an MCU, a motor, a pump, and a drain), and a power and communication system (a solar panel, a battery, and a wireless communication module). The system focuses on low-cost Internet of Things (IoT) devices along with low power consumption and high precision. This proposal collects rainfall from the preceding 10 years in the application region as well as the region’s meteorological bureau’s weekly weather report and uses artificial intelligence to compute the appropriate water level. More importantly, the adoption of dynamic adjustment systems can reserve and modify water resources in the application region more efficiently. Compared to existing technologies, the measurement approach utilized in this study not only achieves cost savings exceeding 60% but also enhances water level measurement accuracy by over 15% through the successful implementation of water level calibration decisions utilizing multiple distinct sensors. Of greater significance, the dynamic adjustment systems proposed in this research offer the potential for conserving water resources by more than 15% in an effective manner. As a result, the adoption of this technology may efficiently reserve and distribute water resources for smart cities as well as reduce substantial losses caused by anomalous water resources, such as floods, droughts, and ecological concerns. Full article

We obtained evidence that mouse BV2 microglia synthesize neurosteroids dynamically to modify neurosteroid levels in response to oxidative damage caused by rotenone. Here, we evaluated whether neurosteroids could be produced and altered in response to rotenone by the human microglial clone 3 (HMC3) cell line. To this aim, HMC3 cultures were exposed to rotenone (100 nM) and neurosteroids were measured in the culture medium by liquid chromatography with tandem mass spectrometry. Microglia reactivity was evaluated by measuring interleukin 6 (IL-6) levels, whereas cell viability was monitored by the 3-(4,5-dimethylthiazol-2-yl)-2,5-diphenyltetrazolium bromide assay. After 24 h (h), rotenone increased IL-6 and reactive oxygen species levels by approximately +37% over the baseline, without affecting cell viability; however, microglia viability was significantly reduced at 48 h (p < 0.01). These changes were accompanied by the downregulation of several neurosteroids, including pregnenolone, pregnenolone sulfate, 5α-dihydroprogesterone, and pregnanolone, except for allopregnanolone, which instead was remarkably increased (p < 0.05). Interestingly, treatment with exogenous allopregnanolone (1 nM) efficiently prevented the reduction in HMC3 cell viability. In conclusion, this is the first evidence that human microglia can produce allopregnanolone and that this neurosteroid is increasingly released in response to oxidative stress, to tentatively support the microglia’s survival. Full article

Monitoring the therapeutic response of colorectal cancer (CRC) patients is crucial to determine treatment strategies; therefore, we constructed a liquid biopsy-based approach for tracking tumor dynamics in non-metastatic (nmCRC) and metastatic (mCRC) patients (n = 55). Serial blood collections were performed during chemotherapy for measuring the amount and the global methylation pattern of cell-free DNA (cfDNA), the promoter methylation of SFRP2 and SDC2 genes, and the plasma homocysteine level. The average cfDNA amount was higher (p < 0.05) in nmCRC patients with recurrent cancer (30.4 ± 17.6 ng) and mCRC patients with progressive disease (PD) (44.3 ± 34.5 ng) compared to individuals with remission (13.2 ± 10.0 ng) or stable disease (12.5 ± 3.4 ng). More than 10% elevation of cfDNA from first to last sample collection was detected in all recurrent cases and 92% of PD patients, while a decrease was observed in most patients with remission. Global methylation level changes indicated a decline (75.5 ± 3.4% vs. 68.2 ± 8.4%), while the promoter methylation of SFRP2 and SDC2 and homocysteine level (10.9 ± 3.4 µmol/L vs. 13.7 ± 4.3 µmol/L) presented an increase in PD patients. In contrast, we found exact opposite changes in remission cases. Our study offers a more precise blood-based approach to monitor the treatment response to different chemotherapies than the currently used markers. Full article

Real-time and accurate monitoring of dynamic deflection is of great significance for health monitoring and condition assessment of bridge structures. This paper proposes an improved step-type liquid level sensing system (LLSS) for dynamic deflection monitoring. Layout of straight-line-type pipeline is replaced by step-type pipeline in this improved deflection monitoring system, which can remove the interference of the inclination angle on the measurement accuracy and is applicable for dynamic deflection monitoring. Fluid dynamics are first analyzed to demonstrate that measurement accuracy is interfered with by the fluid velocity induced by structural vibration, and ANSYS-FLOTRAN is applied for analyzing the influence range caused by the turbulent flow. Finally, a step-type LLSS model is designed and experimented with to verify the influence of the three key parameters (initial displacement excitation, step height, and distance from the measurement point to the elbow) on the measurement accuracy, and the reasonable placement scheme for the measurement point is determined. The results show that the measurement accuracy mainly depends on the turbulent flow caused by step height. The measurement error gets smaller after about 1.0 m distance from the elbow. To ensure that the measurement error is less than 6%, the distance between the measurement point and the elbow should be larger than 1.0 m. Full article

We describe a fiber-optic system to measure the liquid level inside a container. The technique is based on the extraction of the temperature profile of the fiber by using a fiber Bragg grating (FBG) array. When the temperatures of the liquid and the gas are different, the liquid level can be estimated. We present a physical model of the system and the experimental results and we compare different algorithms to extract the liquid level from the temperature profile. We also show how air convection influences the temperature profile and the level of estimation accuracy. We finally show dynamic response measurements which are used to obtain the response time of the sensor. Turbomachinery monitoring is proposed as one possible application of the device. Full article

Coalbed methane (CBM) is one kind of clean-burning gas and has been valued as a new form of energy that will be used widely in the near future. When producing CBM, the working level within a CBM wellbore annulus needs to be monitored to dynamically adjust the gas drainage and extraction processes. However, the existing method of measuring the working level does not meet the needs of accurate adjustment, so we designed a new sensor for this purpose. The principle of our sensor is a liquid pressure formula, i.e., the sensor monitors the two-phase flow patterns and obtains the mean density of the two-phase flow according to the pattern recognition result in the first step, and then combines the pressure data of the working level to calculate the working level using the liquid pressure formula. The sensor was tested in both the lab and on site, and the tests showed that the sensor’s error was ±8% and that the sensor could function well in practical conditions and remain stable in the long term. Full article

Marine biotoxin-contaminated seafood has caused thousands of poisonings worldwide this century. Given these threats, there is an increasing need for improved technologies that can be easily integrated into coastal monitoring programs. This study evaluates approaches for monitoring toxins associated with recurrent toxin-producing Alexandrium and Dinophysis blooms on Long Island, NY, USA, which cause paralytic and diarrhetic shellfish poisoning (PSP and DSP), respectively. Within contrasting locations, the dynamics of pelagic Alexandrium and Dinophysis cell densities, toxins in plankton, and toxins in deployed blue mussels (Mytilus edulis) were compared with passive solid-phase adsorption toxin tracking (SPATT) samplers filled with two types of resin, HP20 and XAD-2. Multiple species of wild shellfish were also collected during Dinophysis blooms and used to compare toxin content using two different extraction techniques (single dispersive and double exhaustive) and two different toxin analysis assays (liquid chromatography/mass spectrometry and the protein phosphatase inhibition assay (PP2A)) for the measurement of DSP toxins. DSP toxins measured in the HP20 resin were significantly correlated (R² = 0.7–0.9, p < 0.001) with total DSP toxins in shellfish, but were detected more than three weeks prior to detection in deployed mussels. Both resins adsorbed measurable levels of PSP toxins, but neither quantitatively tracked Alexandrium cell densities, toxicity in plankton or toxins in shellfish. DSP extraction and toxin analysis methods did not differ significantly (p > 0.05), were highly correlated (R² = 0.98–0.99; p < 0.001) and provided complete recovery of DSP toxins from standard reference materials. Blue mussels (Mytilus edulis) and ribbed mussels (Geukensia demissa) were found to accumulate DSP toxins above federal and international standards (160 ng g⁻¹) during Dinophysis blooms while Eastern oysters (Crassostrea virginica) and soft shell clams (Mya arenaria) did not. This study demonstrated that SPATT samplers using HP20 resin coupled with PP2A technology could be used to provide early warning of DSP, but not PSP, events for shellfish management. Full article