Search Results (153)

Rotavirus A (RVA) causes severe diarrhea in donkey foals, but rapid quantitative antigen assays for vaccine development and manufacturing control are lacking. We developed a VP6-based antigen-capture ELISA (acELISA) for donkey-origin RVA using rabbit anti-RVA polyclonal IgG as the capture antibody and horseradish peroxidase-conjugated mouse anti-VP6 monoclonal antibody 3F6 as the detector antibody. Assay conditions were optimized, and performance was evaluated through standard-curve analysis, specificity and repeatability testing, Western blot (WB) comparison, median tissue culture infectious dose (TCID₅₀), reverse transcription quantitative polymerase chain reaction (RT-qPCR), ultrafiltration membrane screening, and pilot-scale tangential flow filtration (TFF) monitoring. The optimized acELISA detected VP6 at 1 ng/mL and showed a linear range of 1–25 ng/mL, with no cross-reactivity with eight common equine pathogens, and intra- and inter-assay coefficients of variation below 10%. The acELISA estimates were consistent with Western blot densitometry. In process applications, the assay supported the selection of a 100 kDa membrane and monitored pilot-scale TFF, yielding 75.69% VP6 recovery and an 18-fold increase in antigen purity. This acELISA provides a specific and practical in-process tool for quantitative antigen monitoring in donkey rotavirus vaccine production and is intended to complement, rather than replace, infectivity- and genome-based assays. Full article

Membrane-based processes offer promising sustainable alternatives for the decolourisation and purification of starch hydrolysates, yet membrane selection and operating conditions remain the most critical challenges. This study systematically evaluates the performance of polymeric ultrafiltration (UF) and nanofiltration (NF) membranes for starch hydrolysate syrup treatment. Experiments were conducted in a lab-scale cross-flow filtration system using five UF and three NF flat-sheet polymeric membranes under varying temperatures, transmembrane pressures, and feed concentrations. Separation performance was assessed through colour removal, sugar recovery, permeate flux, and alongside indicators of fouling behaviour. UF membranes with molecular weight cut-offs of 100, 70, and 5 kDa exhibited the most favourable performance at 60 °C and 8 bar, achieving partial colour removal (18–32%) with high permeate fluxes (84–130 kg·m⁻²·h⁻¹) and limited sugar losses (0.7–19.9%). NF membranes showed significantly higher colour rejection (32–100%) but were associated with substantial sugar losses (up to 96%), limiting their applicability for selective decolourisation; however, their high sugar retention capacity suggests potential for product concentration and the removal of low-molecular-weight impurities. Overall, UF represents a suitable approach for partial colour removal in starch hydrolysates, while NF may be better suited for product concentration and the removal of low-molecular-weight impurities, as well as auxiliary applications such as water recovery. These findings provide a systematic basis for membrane selection and process optimisation in industrial starch hydrolysate purification. Full article

The sustained expansion of printing and dyeing operations has led to the discharge of large volumes of organic wastewater containing dyes. The resulting environmental pollution demands urgent solutions, making the development of efficient and eco-friendly methods for the elimination of dyeing wastewater critically important. The combination of alginate hydrogel membranes with advanced oxidation processes (AOPs) for water purification represents an emerging approach in the current field of water treatment. In this study, a calcium alginate membrane was loaded with a glaze containing highly active cobalt oxide to fabricate a glaze-calcium alginate (Glaze-CaAlg) composite membrane. The membrane achieved stable degradation of Orange G dye under optimal conditions, and a series of tests were conducted under varying conditions using pollutant concentrations close to those found in real water bodies. Under optimal conditions (glaze loading = 2.5 mL, PMS = 0.3 mmol/L, cross-flow filtration mode), the membrane achieved a 93.7% degradation efficiency of Orange G (10 ppm) within 45 min, with hydroxyl radicals (·OH, ~79%) identified as the predominant reactive species. The Glaze-CaAlg membrane also exhibited excellent reusability, maintaining a degradation efficiency of over 80% for Orange G across five consecutive cycles. Furthermore, sodium citrate was employed to react with the Glaze-CaAlg membrane, enabling the recovery and secondary application of the glaze. Membranes re-fabricated from the recovered glaze showed mechanical strength and catalytic efficiency comparable to those of the pristine membrane. The Glaze-CaAlg membrane possesses high catalytic activity and good stability. This work offers a sustainable, cost-effective, and recyclable catalytic membrane that converts a traditional ceramic material into an advanced functional material for wastewater remediation, with great potential for practical application in the treatment of refractory organic pollutants. Full article

Background/Objectives: Chronic kidney disease (CKD) is a major global public health problem, and conventional biomarkers such as serum creatinine primarily reflect excretory function with limited sensitivity for early detection and for predicting progression. Amino acids (AAs) and acylcarnitines (ACs) reflect metabolic processes related to nitrogen metabolism and mitochondrial fatty-acid oxidation that are influenced by renal function. This study aimed to characterize CKD-associated alterations in AAs and ACs profiles using an integrated analytical framework combining differential analysis, supervised multivariate modeling, differential network enrichment analysis (DNEA), and cross-compartment plasma–urine profiling, moving beyond individual metabolite associations toward a multi-level characterization of CKD-associated metabolic reprogramming. Methods: Plasma and urine samples from 78 patients with CKD and plasma samples from 70 healthy controls were analyzed using flow-injection tandem mass spectrometry (FIA-MS/MS). An integrated targeted metabolomics framework combining differential, multivariate and network-based analyses including DNEA was applied to plasma and paired urine samples to characterize systemic and urinary metabolic alterations in CKD, focusing on AAs and ACs. Results: CKD was characterized by significant elevated short-chain dicarboxylic acylcarnitines, increased methylhistidine (MetHis) and argininosuccinic acid (ASA), together with reduced tryptophan, serine, methionine, and tyrosine in plasma. These metabolites were consistently identified across different analyses and correlated with kidney function markers. DNEA revealed coherent network-level reorganization, with acylcarnitine pathways gaining connectivity and centrality while amino acid modules lost integration in CKD. Cross-compartment analysis identified both systemic and compartment-specific patterns of metabolite distribution. An exploratory clustering-guided biomarker panel combining MetHis, C3DC, and Trp achieved an area under the curve (AUC) of 0.881 for discriminating patients with CKD from controls. Moreover, C6, C8, and C10 remained significantly associated with CKD after additional adjustment for estimated glomerular filtration rate (eGFR). Conclusions: Targeted metabolomic profiling revealed a coordinated metabolic signature in CKD suggesting disturbances in pathways related to fatty-acid oxidation, nitrogen imbalance, and altered amino acid metabolism. Network-level analysis provided evidence of systemic metabolic reorganization beyond individual metabolite changes. As findings derive from an observational cohort with high comorbidity prevalence, the identified signatures should be considered CKD-associated rather than CKD-specific. Full article

The increasing discharge of cobalt-containing effluents from metallurgical, electroplating, and battery-related industries necessitates the development of efficient and stable separation technologies. In this study, a sodium dodecyl sulfate (SDS)-assisted micellar-enhanced ultrafiltration (MEUF) process was systematically evaluated for the removal of Co²⁺ from aqueous solutions using a flat-sheet polyethersulfone (PES) membrane operated under crossflow conditions. The effects of surfactant concentration, initial solution pH, cobalt concentration, background electrolyte, and extended filtration time were examined to assess process performance and operational stability. Direct ultrafiltration of 50 mg L⁻¹ Co²⁺ without surfactant resulted in limited rejection (~18%). The introduction of SDS markedly improved removal efficiency, achieving >99% rejection at and above 1 critical micelle concentration (CMC). An SDS dosage of 1 CMC provided an optimal balance between permeate flux (~155 L m⁻² h⁻¹) and cobalt removal (>99%). The system maintained high rejection efficiency across a pH range of 3–9, demonstrating robust cobalt–micelle interactions. Increasing the initial cobalt concentration from 10 to 50 mg L⁻¹ caused a moderate decline in flux but did not significantly affect rejection efficiency. In contrast, elevated ionic strength due to NaNO₃ addition reduced both flux and cobalt removal, highlighting the influence of competing ions on micelle-mediated separation. Long-term continuous operation for 40 h showed stable permeate flux and sustained cobalt rejection above 99%, indicating minimal fouling. FTIR and SEM–EDS analyses confirmed membrane chemical stability and negligible cobalt deposition. These findings demonstrate that SDS-based MEUF is an effective and operationally stable approach for cobalt removal from contaminated water systems. Full article

Mechanical bar screens serve as the initial treatment stage used to catch insoluble and coarse debris from wastewater flow. They are essential equipment that ensures the protection and efficient operation of downstream facilities. Different parameters affect the performance of bar screens, including particle size, flow hydraulics, and screen design. Most previous studies have primarily focused on bar screens with rectangular bars and single-phase flow. However, investigating different bar shapes with the presence of waste debris as a second phase is crucial for achieving the optimal design and accurately predicting a bar screen’s efficiency. Therefore, four bar cross-section shapes were examined using 3D simulations of two-phase flow (water and particles). The discrete phase model (DPM) in ANSYS Fluent CFD software was used to represent waste particles in a Lagrangian framework and to evaluate their retention efficiency. The numerical results, validated by a previous study of a wastewater bar screen, indicate that the traditional rectangular bar shape traps a higher rate of debris but results in higher pressure losses. Alternative bar shapes, such as rounded, streamlined, and teardrop cross-sections, have been studied for design improvements. The improved teardrop shape presents significant effectiveness, offering a better balance between pressure loss reduction and enhanced particle separation efficiency. Based on this study, further investigations coupling CFD techniques with the particle tracking method can be carried out for the optimal design of other filtration equipment. Full article

Reliable quantification of microplastics in water remains challenging because most Raman-based methods require filtration, drying, or complex flow systems, which can lead to particle loss and signal instability. Here, we propose a simple dual-laser Raman strategy for the direct, real-time quantification of microplastics in water without pretreatment. By simultaneously integrating backscattering and transmission geometries using two identical 532 nm lasers, spatial variations in Raman scattering cross-sections, arising from particle motion and focal depth fluctuations, are effectively mitigated. The dual-laser configuration enhances Raman intensity by approximately 1.5-fold compared with backscattering and threefold compared with transmission alone (p < 0.001), enabling robust real-time detection with a temporal resolution of 0.1 s. Accurate particle counting is demonstrated using polystyrene (PS) standard beads and further validated for polyamide 6 (PA6) and polyvinyl chloride (PVC) particles with irregular morphologies and broad size distributions, with no false-positive events observed. By prioritizing simplicity and quantitative reliability over ultimate size resolution, the proposed strategy provides a practical approach for routine monitoring of microplastics in drinking water and industrial aqueous systems. Full article

Particulate matter (PM) emissions are common in technological processes, and effective mitigation requires gas pre-treatment before high-efficiency filtration to reduce fine and ultrafine PM that are particularly dangerous to the human health. This study evaluates a multichannel electric field manipulator (agglomerator) as a flow pre-treatment stage and investigates the aerodynamic conditions that govern particle–gas flow distribution and variation in trajectories and dynamics at different flow rates. These factors provide meaningful assumptions about the possible behavior of particles in the flow, and they are critical for optimizing an agglomeration and its intensity. Such phenomena can have an impact on the probability of agglomeration in the manipulator channels, i.e., the adherence of small particles into larger ones, and this allows for improving the design and operating conditions of the apparatus. Gas flow velocities and pressure were analyzed experimentally at various cross-sectional points in the inlet and outlet ducts at inflow rates of 3.4 L/s and 50 L/s. The static inlet pressure of the manipulator ranged from 8 Pa to 178 Pa. This study provides new insights into flow pre-treatment using the electric field mechanism in a multichannel modular apparatus and provides a reasonable understanding of the necessary characteristics of gas flow distribution to support subsequent improvements targeting higher agglomeration. Full article

Free chlorine removal from industrial wastewater using activated carbon filtration requires accurate modeling and optimal control to balance treatment efficiency and adsorbent consumption. In this study, a combined experimental–machine learning–optimization framework was developed to predict and optimize residual chlorine concentration in a pilot-scale activated carbon filtration unit. A total of 200 experimental runs were collected using a pilot activated carbon filtration system by varying flow rate, initial chlorine concentration, pressure, pH, temperature, and carbon dose. Two ensemble learning models, Random Forest (RF) and Gradient Boosting (GB), were trained and validated using five-fold cross-validation. Both models exhibited high predictive accuracy, with GB outperforming RF on the full dataset (R² = 0.9995, Root Mean Square Error (RMSE) = 0.0355 mg·L⁻¹, Mean Absolute Error (MAE) = 0.0276 mg·L⁻¹) and on the independent test set (R² = 0.9417). Feature importance and partial dependence analyses revealed that the initial chlorine concentration and activated carbon dose were the dominant controlling variables, while increasing flow rate led to higher residual chlorine levels. A multi-objective optimization strategy based on Pareto dominance was implemented using the trained GB model as a surrogate to simultaneously minimize residual chlorine and carbon consumption. The optimal compromise solution corresponded to an activated carbon dose of approximately 51.5 kg and a residual chlorine concentration of 0.156 mg·L⁻¹ at a flow rate of 43.1 m³·h⁻¹. The proposed framework demonstrates a reliable and cost-effective approach for predictive control and sustainable optimization of dechlorination processes in industrial wastewater treatment. Full article

Organic dyes are critical components in industries ranging from textiles, plastics, and paper to food, cosmetics, and pharmaceuticals. However, their widespread use leads to significant environmental pollution. Consequently, developing efficient methods to treat dye wastewater is urgently needed. In this work, a high-performance composite membrane was developed with a poly(dibenzo-18-crown-6) covalent organic polymer (COP) interlayer. The chemical structure of the COP was verified by FT-IR, and BET analysis indicated that the as-synthesized material possesses a predominantly mesoporous structure with a minor microporous contribution. Subsequently, the membrane was fabricated by depositing a COP colloid on a nylon-66 support via vacuum filtration, followed by the formation of a dense polyamide (PA) active layer through interfacial polymerization (IP) between amine and acyl chloride monomers. Systematic evaluation of dye separation performance using a cross-flow filtration setup identified optimal operating conditions. Under these conditions, the membrane demonstrated effective molecular sieving behavior, achieving both high dye rejection and favorable solvent permeability. In long-term stability tests, the membrane maintained a rejection rate of over 99% for Congo red over 48 h, while sustaining a water flux of 103.2 L m⁻² h⁻¹ bar⁻¹ (LMH/bar). Furthermore, the membrane exhibited promising potential for dye desalination applications, achieving a high Congo red/potassium chloride separation selectivity of 186.8 with a flux of 138.2 LMH/bar. This study confirms that the poly(dibenzo-18-crown-6)-based composite membrane is a reliable and efficient material for molecular separation in wastewater treatment. Full article

The adsorption of methylene blue (MB) on poly(vinylidene fluoride) (PVDF) and PVDF/titanium dioxide(TiO₂) membranes with 1.5 wt% dosage was examined through batch adsorption and dynamic cross-flow filtration experiments. The effects of pH, temperature, and initial MB concentration on adsorption performance were evaluated via batch experiments. The Thomas model was applied to analyze the membrane filtration process, while kinetic, isothermal, and thermodynamic models were integrated to elucidate the adsorption mechanisms. Results demonstrated that low temperature and high initial MB concentration significantly improved MB adsorption on both membranes. Under neutral pH conditions (pH = 7), the maximum adsorption capacities of PVDF and PVDF/TiO₂ membranes reached 1.518 ± 0.025 mg/g and 0.189 ± 0.008 mg/g, respectively. The adsorption processes on both membranes conformed to the pseudo-second-order kinetic model, with optimal fitting to the Langmuir isotherm model. Thermodynamic analysis revealed physical adsorption mechanisms, as evidenced by adsorption free energy (E) calculated via the Dubinin–Radushrevich model Notably, PVDF membrane exhibited a more pronounced mass transfer zone height (h_Z = 2.3 ± 0.1 cm) and achieved higher adsorption capacity (2.1 ± 0.09 mg/g) than PVDF/TiO₂ membranes (0.25 ± 0.01 mg/g). The TiO₂ incorporation reduced hybrid membrane adsorption capacity and significantly mitigated membrane fouling caused by adsorption, with PVDF/TiO₂ membranes showing a 32 ± 2.5% lower flux decline rate than PVDF membranes with less MB into the pores. This study provides fundamental data supporting the combined application of “adsorption–subsequent oxidation” using PVDF-based membranes in dye wastewater treatment. Full article

Background/Objectives: Patients in need of specialized palliative care are clinically highly complex, with pain being the most prevalent problem. Furthermore, in these patients, a self-report for characterization of pain could be difficult to obtain. This cross-sectional, exploratory study investigates the use of clinical parameters and peripheral blood biomarkers for potentially identifying and characterizing pain (assessed using Pain Assessment in Advanced Dementia (PAINAD) and Numeric Scale (NS)) in patients under palliative care, including a population with dementia where pain is often underdiagnosed. Methods: Fifty-three patients with non-oncological diseases were analyzed in a cross-sectional study using medical and nursing records. Among previous biomarkers related to monocytes and platelets assessed by flow cytometry, we selected the most significative ones for pain characterization in a logistic regression analysis (multivariate analysis), alongside patient-specific characteristics such as renal function, nutritional status, and age. Results: Our exploratory findings suggest strong relationships between chronic pain and advanced age, reduced glomerular filtration rate (GFR), and malnutrition within this cohort. Furthermore, the percentage of lymphocytes, total and classical monocytes, the relative expression in monocytes of CD206, CD163, the CD163/CD206 ratio, and the relative expression in platelets of CD59 emerged as potential predictors of pain. Statistical analyses highlighted the challenges of multicollinearity among variables such as age, GFR, and nutritional status. A classification model further suggested that all patients over 65 years in our specific sample reported pain. Conclusions: This pilot study provides preliminary support for prior evidence linking chronic pain to aging, nutritional deficits, and renal impairment, and highlights potential novel peripheral blood biomarkers for pain assessment. This work emphasizes the promise of clinical and molecular biomarkers to improve pain detection and management, contributing to personalized and effective palliative care strategies. Full article

Reverse osmosis (RO) is the key process for textile dyeing wastewater reuse applications. Membrane fouling reduces both permeability and rejection capability, negatively affecting the technological economy of RO process. Membrane cleaning is critical to recovery of the permeability of fouled RO membranes. Based on multi-batch filtration and cleaning experiments, this study systematically evaluated the RO membrane fouling potential of pre-treated textile dyeing wastewater by a membrane bioreactor and the recovery performance of fouled RO membranes after different cleaning methods. A significant decline (more than 15%) in RO membrane permeability occurred after RO membrane permeate production of 625 L/m² at a water recovery ratio of 60%. Protein-like substances and soluble microbial products were identified as the primary organic foulants via three-dimensional fluorescence excitation-emission matrix spectrometry (3D-FEEM). The single forward flushing with either pure water, acid, alkaline, or sodium hypochlorite solutions with a low active chlorine concentration showed very limited recovery of fouled RO membrane permeability. The combined forward flushing with acid followed by alkaline solutions restored fouled membrane permeability by up to 87% of a new RO membrane. The addition of pure water backwashing at a transmembrane pressure (TMP) of 0.5 MPa after both acid and alkaline solutions combined forward flushing restored fouled membrane permeability by up to 97% of a new RO membrane but deteriorated the rejection capability of the RO membrane. The backwashing parameters were further optimized at a TMP of 0.125 MPa and crossflow velocity (CFV) of 0.5 m/s, achieving fouled RO membrane permeability by up to 96% of a new RO membrane, and there were no negative effects on the rejection capability of the RO membrane. Alkaline forward flushing followed by pure water backwashing was the dominant contributor for fouled RO membrane permeability recovery. A preliminary economic analysis showed that the total chemical cost per RO production was 0.763 CNY/m³ and could be further reduced via removing acid cleaning and replacing combined alkaline flushing and pure water backwashing with alkaline backwashing. Full article

In recent decades, rotating dynamic filtration (RDF) has attracted considerable attention due to its high efficiency and low energy consumption. While most studies have focused on separation behavior and membrane fouling, energy consumption in RDF has received limited attention. This study investigates the specific energy consumption (SEC) of the RDF process for ship exhaust gas cleaning (EGC) desulfurization wastewater treatment and proposes an optimization method based on both energy consumption and equipment cost. The total SEC increases with rotational velocity, circulation flow, feed concentration, and membrane size but decreases with temperature and remains unaffected by the number of membrane elements. In RDF, the total SEC is only 9.05–19.29% of that in tubular cross-flow filtration (CFF) at equivalent shear force ranging from 3.86 Pa to 121.14 Pa. Operating energy and investment costs are primarily determined by the number of membrane elements and the rotational velocity. According to the economic analysis, the lowest treatment cost for EGC wastewater is CNY 6.09 per cubic meter for a 5 m³·h⁻¹ capacity, using 84 membrane elements (374 mm, 0.2 µm) at a rotational velocity of 200 rpm, an operating pressure of 200 kPa, and a temperature of 40 °C. Full article

With the growing interest in fabricating nanofiltration membranes using novel materials and techniques, there is an increasing need to evaluate the practical viability of innovative membranes at the early stages of development. In many materials research laboratories, access to professionally manufactured membrane-evaluation systems may be limited. Here we present a pressure-driven filtration system for evaluation of nanofiltration membranes, which can be constructed from 3D-printed parts and widely available off-the-shelf components at a cost of approximately 60 €. The system uses a stirred cross-flow design capable of circulating the feed solution in the filter cell and maintaining a stable solute concentration during extended filtration experiments—as in conventional cross-flow cells. It is suitable for the filtration of aqueous solutions containing dyes, inorganic salts, and dilute acids. Validation was performed by filtering a 2000 mg L⁻¹ MgSO₄ solution through a Veolia RL membrane at 7.6 bar, achieving a 96.5% rejection rate and a permeance of 7.5 L m⁻² h⁻¹ bar⁻¹ after 24 h of continuous operation. Full article