Search Results (75)

Hexavalent chromium (Cr(VI)) is a high-priority environmental pollutant due to its strong oxidizing properties, which cause DNA damage and other severe health effects. Conventional detection methods are often costly and lack real-time monitoring capabilities, creating a strong demand for cost-effective, real-time biosensors that meet industrial requirements. In this study, we developed a novel biosensor for continuous Cr(VI) monitoring using a single-chamber microbial fuel cell (MFC). The biological element is an engineered Escherichia coli strain (ChrA-ChrB-E. coli), constructed by introducing Cr(VI)-resistant (ChrA) and Cr(VI)-reducing (ChrB) genes. The presence of Cr(VI) affects bacterial metabolism and electron transfer within the MFC, generating a measurable signal proportional to the contaminant’s concentration. The biosensor demonstrated robust performance and characteristics. The recombinant strain retained functional activity after 450 days of storage at −20 °C. The system exhibited high sensitivity and excellent linearity (R² ≥ 0.999) across a broad Cr(VI) concentration range of 0.015–200 mg/L. During continuous monitoring of chrome tanning and electroplating wastewater, measurements deviated by less than 2.33% from the standard diphenylcarbazide (DPC) method; electroplating deviation was further reduced to −0.69% with EDTA pretreatment. In fishery water, the deviation was higher (−7.12%) due to dissolved oxygen (DO) interference but was reduced to −0.75% after mechanical stirring to remove DO. The biofilm bacterial community remained highly stable over six months in both wastewater types, with the inoculated ChrA-ChrB-E. coli strain maintaining dominance (>99.6%). These results substantiate the feasibility of using this biosensor for continuous, online, real-time detection of Cr(VI) in actual wastewater environments. Full article

This study addresses two critical challenges in rural Peru: the mismanagement of agro-industrial waste and the limited access to electricity. Over 40,000 tons of Cucumis sativus (cucumber) waste are generated annually in Peru, most of which is discarded without valorization. Microbial fuel cells (MFCs) offer a sustainable solution by converting organic waste into bioelectricity via electrogenic microorganisms. To evaluate the bioenergy potential of cucumber waste, three single-chamber MFCs were constructed using graphite and zinc electrodes under an external resistance of 100 ohms. The systems were inoculated with acclimated microbial consortia, and electrical, physicochemical, and microbiological parameters were monitored over 35 days. Results showed a maximum voltage of 0.589 V, a peak current of 2.292 mA, and a power density of 0.622 mW/m². Chemical oxygen demand (COD) was reduced by over 80%, and oxidation-reduction potential (ORP) reached 459.76 mV. Internal resistance was 24.515 ± 1.237 Ω, indicating high energy efficiency. Taxonomic analysis revealed a predominance of Gammaproteobacteria, Bacilli, Bacillus, Acetobacter, and Clostridium, confirming a functionally diverse and electroactive microbial community. These findings demonstrate that cucumber waste is a viable substrate for MFCs and support its potential for integrated waste valorization and decentralized bioenergy generation in rural Peruvian contexts. Full article

This study presents a model investigation into the development of tolerance to polyene antifungal drugs (nystatin and natamycin) in strains of Malassezia pachydermatis. This species, commonly associated with external ear canal infections in dogs, has emerged as increasingly significant in the broader context of growing fungal resistance to treatment. In the experiment, 10 strains of M. pachydermatis were passaged over a period of 105 weeks on media containing sublethal concentrations of nystatin and natamycin. Minimal inhibitory (MIC) and minimal fungicidal concentration (MFC) values were regularly assessed to monitor tolerance development. The results revealed a varied response among the strains: Some were eliminated during the process, while others showed a gradual increase in MIC values, up to fivefold in the case of nystatin. In several strains, acquired resistance remained stable even after passaging in drug-free conditions, whereas others reverted to their original susceptibility. The model demonstrated that resistance does not emerge immediately; significant changes appeared only after 30–45 passages. The authors propose this model as a valuable tool for tracking sequential changes that lead to resistance development. Such an approach may support targeted therapy development and help identify strains predisposed to drug adaptation. These findings hold promise for assessing therapeutic risk in immunosuppressed patients and for building resistance datasets that can support artificial intelligence algorithms in predicting fungal resistance mechanisms. Full article

Background: Candida albicans infects most reproductive-aged women, causing a prevalent infection known as Vulvovaginal Candida. As there has been an increase in resistance to widely used antifungal agents, particularly fluconazole, used in infections, local susceptibility profiles are needed to inform treatment options. Methods: This comparative observational study was carried out to determine the in vitro susceptibility of six antifungal compounds [fluconazole, voriconazole, itraconazole, ketoconazole, nystatin, and amphotericin B] to 163 vaginal Candida albicans isolates obtained in three hospitals in Tabuk, Saudi Arabia. MIC₅₀, MIC₉₀, and MFC values were calculated in Broth microdilution tests according to the standards of CLSI M27-A3. Friedman and Wilcoxon signed-rank tests were used to carry out statistical analysis. Results: It was observed that Amphotericin B and itraconazole recorded the lowest MIC and MFC, revealing better antifungal action. The worst performer was fluconazole with MIC₅₀ (13.79 μg/mL), MIC₉₀ (27.59 μg/mL), and MFC (37.93 μg/mL), and 85% resistance. It was found that there are significant differences between antifungal agents (p < 0.001), and amphotericin B and itraconazole always performed best compared to fluconazole and voriconazole. Conclusions: The results shows antifungal effectiveness as Amphotericin B and itraconazole are the most effective against vaginal Candida albicans isolates. There is a high rate of resistance to fluconazole, suggesting it should no longer be the first choice of treatment in this area. These findings highlight the need for local monitoring of drug resistance to guide treatment choices and emphasize the importance of using antifungals properly to prevent increased resistance. Full article

Limited access to electricity and high levels of CO₂ emissions—over 35 billion metric tons in recent years—highlight the urgent need for sustainable energy solutions, particularly in rural areas dependent on polluting fuels. To address this challenge, three single-chamber microbial fuel cells (MFCs) with carbon anodes and zinc cathodes were designed and operated for 35 days in a closed circuit. Voltage, current, pH, conductivity, ORP, and COD were monitored. FTIR-ATR spectroscopy (range 4000–400 cm⁻¹) was applied to identify structural changes, and polarization curves were constructed to estimate internal resistance. The main FTIR peaks were observed at 1027, 1636, 3237, and 3374 cm⁻¹, indicating the degradation of polysaccharides and hydroxyl groups. The maximum voltage reached was 0.961 ± 0.025 V, and the peak current was 3.052 ± 0.084 mA on day 16, coinciding with an optimal pH of 4.977 ± 0.058, a conductivity of 194.851 ± 2.847 mS/cm, and an ORP of 126.707 ± 6.958 mV. Connecting the three MFCs in series yielded a total voltage of 2.34 V. Taxonomic analysis of the anodic biofilm revealed a community dominated by Firmicutes (genus Lactobacillus: L. acidophilus, L. brevis, L. casei, L. delbrueckii, L. fermentum, L. helveticus, and L. plantarum), along with Bacteroidota and Proteobacteria (electrogenic bacteria). This microbial synergy enhances electron transfer and validates the use of carrot waste as a renewable source of bioelectricity for low-power applications. Full article

Multiple myeloma (MM) is one of the most common hematological malignancies and remains incurable. However, the survival of multiple myeloma patients has significantly increased due to the implementation of novel therapies along with autologous stem cell transplantation, changing the natural history of the disease. Consequently, there is an unmet need for more sensitive response assessment techniques capable of quantifying minimal tumor burden to identify patients at higher risk of early relapse. Multiparameter flow cytometry (MFC) is an essential tool for diagnosing and monitoring patients with various hematological conditions and has recently gained prominence in identifying, characterizing, and monitoring malignant plasma cells. The implementation of Next-Generation Flow (NGF) by EuroFlow aims to overcome the pitfalls of conventional MFC, including lack of standardization and lower sensitivity, by offering standardized and optimized protocols for evaluating response depth. Both MFC and NGF have wide-ranging applications in MM for diagnosis and measurable residual disease (MRD) monitoring. Plasma cell identification and clonality evaluation through MFC and NGF assist in diagnostic workup and are routinely used to assess therapeutic response through MRD analysis. Additionally, flow cytometry is applied for circulating tumor plasma cell (CTPC) enumeration, which has demonstrated significant prognostic value. Immune composition studies through MFC may provide better understanding of disease biology. Furthermore, MFC provides additional information about other bone marrow cell populations, assessing cellularity, immunophenotypic characteristics of plasma cells, and possible hemodilution. This review explores the applications of MFC and NGF in MM, highlighting their roles in diagnosis, response assessment, and prognosis. Beyond their established use in MRD monitoring, flow cytometry-derived immunophenotypic profiles show strong potential as cost-effective prognostic tools. We advocate for future studies to validate and integrate these markers into risk stratification models, complementing cytogenetic analyses and guiding individualized treatment strategies. Full article

The underutilization of fruit waste in agroindustry—particularly star fruit—leads to leachate generation, emissions, and disposal costs, highlighting the need for circular alternatives that treat organic fractions while producing energy. This study evaluated the bioelectrochemical conversion of carambola (Averrhoa carambola) residues in single-chamber microbial fuel cells (MFCs). Three 1000 mL reactors were constructed using carbon anodes and zinc cathodes, operated for 35 days with continuous voltage recording and daily monitoring of pH, conductivity, and ORP. Polarization curves were obtained, and FTIR and SEM analyses were conducted to characterize substrate transformation and anode colonization. The anodic biofilm was also profiled using metagenomics. Measurements were performed using calibrated electrodes and a data logger with one minute intervals. The systems exhibited rapid startup and reached peak performance on day 22, with a voltage of 1.352 V, current of 3.489 mA, conductivity of 177.90 mS/cm, ORP of 202.01 mV, and pH of 4.89. The V–I curve indicated an internal resistance of 16.51 Ω, and the maximum power density reached 0.517 mW/cm². FTIR revealed a reduction in bands associated with carbohydrates and proteins, consistent with biodegradation, while SEM confirmed extensive biofilm formation and increased anode surface roughness. Metagenomic analysis showed dominance of Acetobacter (59.35%), with Bacteroides (12.93%) and lactobacilli contributing to fermentative and electrogenic synergies. Finally, the series connection of three MFCs generated 2.71 V, sufficient to power an LED, demonstrating the feasibility of low-power applications and the potential for system scalability. Full article

This work presents a proof of concept including simulation and experimental validations of acoustic gas sensor prototypes for trace CO₂ detection up to 1 ppm. For the detection of lower gas concentrations especially, the dependency of acoustic resonances on the molecular weights and, consequently, the speed of sound of the gas mixture, is exploited. We explored two resonator types: a cylindrical acoustic resonator and a Helmholtz resonator intrinsic to the MEMS microphone’s geometry. Both systems utilized mass flow controllers (MFCs) for precise gas mixing and were also modeled in COMSOL Multiphysics 6.2 to simulate resonance shifts based on thermodynamic properties of binary gas mixtures, in this case, N₂-CO₂. We performed experimental tracking using Zurich Instruments MFIA, with high-resolution frequency shifts observed in µHz and mHz ranges in both setups. A compact and geometry-independent nature of MEMS-based Helmholtz tracking showed clear potential for scalable sensor designs. Multiple experimental trials confirmed the reproducibility and stability of both configurations, thus providing a robust basis for statistical validation and system reliability assessment. The good simulation experiment agreement, especially in frequency shift trends and gas density, supports the method’s viability for scalable environmental and industrial gas sensing applications. This resonance tracking system offers high sensitivity and flexibility, allowing selective detection of low CO₂ concentrations down to 1 ppm. By further exploiting both external and intrinsic acoustic resonances, the system enables highly sensitive, multi-modal sensing with minimal hardware modifications. At microscopic scales, gas detection is influenced by ambient factors like temperature and humidity, which are monitored here in a laboratory setting via NDIR sensors. A key challenge is that different gas mixtures with similar sound speeds can cause indistinguishable frequency shifts. To address this, machine learning-based multivariate gas analysis can be employed. This would, in addition to the acoustic properties of the gases as one of the variables, also consider other gas-specific variables such as absorption, molecular properties, and spectroscopic signatures, reducing cross-sensitivity and improving selectivity. This multivariate sensing approach holds potential for future application and validation with more critical gas species. Full article

Plastic pollution is an increasingly pressing environmental concern due to its persistence in ecosystems. To address this issue, this study evaluates polyethylene biodegradation and bioelectricity generation using Aspergillus ochraceopetaliformis in microbial fuel cells (MFCs). Single-chamber MFCs were designed (three) with carbon and zinc electrodes, where the fungus was cultivated in a nutrient-rich medium to enhance its metabolic activity. Parameters such as pH, power density, and FTIR spectra were monitored to assess plastic biodegradation. The results demonstrated a significant reduction in polyethylene mass and structure, along with a maximum generation of 0.921 V and 4.441 mA on day 26, with a power density of 0.148 mW/cm² and a current of 5.847 mA/cm². The optimal pH for fungal activity in the MFC was recorded at 7.059. Furthermore, FTIR analysis revealed a decrease in peak intensity at 1470 cm⁻¹ and 723 cm⁻¹, indicating structural modifications in the treated plastics. Furthermore, microbial fuel cells connected in series successfully powered an LED bulb, generating a maximum voltage of 2.78 V. These findings confirm the feasibility of using Aspergillus ochraceopetaliformis for biodegradation and bioelectricity generation, although practical applications require further optimization of system conditions and improvements in long-term stability. This research contributes to the development of biotechnological strategies for plastic waste management, sustainable integrating approaches with energy potential. Full article

This study discussed the influence of acetate and sodium chloride concentration on monitoring 2,4-dichlorophenol(2,4-DCP) by electroactive bacteria. The performance of the reactor was represented by power density, and the electrochemical activity was represented by redox capacity. At the same time, micro-electrodes were used to detect the redox potential between biofilms, and the changes in extracellular polymers and microbial community structure under different conditions were also explored. With acetate concentration of 1 g/L and sodium chloride concentration of 0.0125 g/L, the electroactive microorganisms were more sensitive to toxic substances and responded fast. The biofilm also evenly covered on the surface of the carrier, which aided in the diffusion of substances. Although the maximum power density monotonically increased with acetate concentration, high concentration of substrate may mask the inhibitory effect and affect the judgment of inhibitory results. The content of protein and polysaccharide increased monotonically with sodium chloride concentration. However, more polysaccharides would lead to high resistance to electron transfer. Compared to sodium chloride, the microbial content was more affected by acetate. The electroactive microorganisms had strong adaptability to salinity. In practical application, it is conducive to increase the sensitivity of MFCs to reasonably reduce the concentration of acetic acid and sodium chloride. Full article

The harmonized multi-sensor satellite data assists users by providing seamless analysis-ready data with enhanced temporal resolution. The Harmonized Landsat Sentinel (HLS) product has gained popularity due to the seamless integration of Landsat OLI and Sentinel-2 MSI, achieving a temporal resolution of 2.8 to 3.5 days. However, applications that require monitoring intervals of less than three days or cloudy data can limit the usage of HLS data. Gaofen-1 (GF-1) Wide Field of View (WFV) data provides the capacity further to enhance the data availability by harmonization with HLS. In this study, GF-1/WFV data is harmonized with HLS by employing deep learning-based conditional Generative Adversarial Networks (cGANs). The harmonized WFV data with HLS provides an average temporal resolution of 1.5 days (ranging from 1.2 to 1.7 days), whereas the temporal resolution of HLS varies from 2.8 to 3.5 days. This enhanced temporal resolution will benefit applications that require frequent monitoring. Various processes are employed in HLS to achieve seamless products from the Operational Land Imager (OLI) and Multispectral Imager (MSI). This study applies 6S atmospheric correction to obtain GF-1/WFV surface reflectance data, employs MFC cloud masking, resamples the data to 30 m, and performs geographical correction using AROP relative to HLS data, to align preprocessing with HLS workflows. Harmonization is achieved without using BRDF normalization and bandpass adjustment like in the HLS workflows; instead, cGAN learns cross-sensor reflectance mapping by utilizing a U-Net generator and a patchGAN discriminator. The harmonized GF-1/WFV data were compared to the reference HLS data using various quality indices, including SSIM, MBE, and RMSD, across 126 cloud-free validation tiles covering various land covers and seasons. Band-wise scatter plots, histograms, and visual image color quality were compared. All these indices, including the Sobel filter, histograms, and visual comparisons, indicated that the proposed method has effectively reduced the spectral discrepancies between the GF-1/WFV and HLS data. Full article

Plastic pollution remains a critical global environmental challenge, with conventional disposal methods contributing to ecosystem degradation. Simultaneously, energy scarcity affects numerous rural communities, limiting development opportunities. This study presents an innovative approach that integrates microbial fuel cells (MFCs) with Klebsiella oxytoca to simultaneously degrade plastic waste and generate bioelectricity. The monitoring results over 40 days revealed optimal performance on day 28, with a peak voltage of 0.714 ± 0.026 V and an electric current of 3.149 ± 0.124 mA. The biocatalyst exhibited an electrical conductivity of 140.466 ± 5.180 mS/cm and an oxidation-reduction potential of 109.519 ± 5.35 mV, indicating efficient electron transfer. Furthermore, the MFCs achieved a maximum power density of 11.391 ± 0.814 mW/cm² with a current density of 5.106 mA/cm², demonstrating their potential for sustainable energy production. Fourier transform infrared (FTIR) analysis confirmed structural modifications in the plastic, with decreased vibrational peaks indicative of polymer degradation. Additionally, scanning electron microscopy (SEM) micrographs revealed porosity and surface cracks, highlighting Klebsiella oxytoca’s biodegradation capacity. These findings establish the viability of bioelectrochemical systems for simultaneous waste remediation and renewable energy generation, paving the way for scalable applications in environmental biotechnology. By coupling microbial degradation with electricity production, this research supports the development of sustainable solutions aligned with the principles of circular economy and climate change mitigation. Full article

The xeno-fungusphere, a novel microbial ecosystem formed by integrating exogenous fungi, indigenous soil microbiota, and electroactive microorganisms within microbial fuel cells (MFCs), offers a transformative approach for agricultural remediation and medicinal plant conservation. By leveraging fungal enzymatic versatility (e.g., laccases, cytochrome P450s) and conductive hyphae, this system achieves dual benefits. First, it enables efficient degradation of recalcitrant agrochemicals, such as haloxyfop-P, with a removal efficiency of 97.9% (vs. 72.4% by fungi alone) and a 27.6% reduction in activation energy. This is driven by a bioelectric field (0.2–0.5 V/cm), which enhances enzymatic activity and accelerates electron transfer. Second, it generates bioelectricity, up to 9.3 μW/cm², demonstrating real-world applicability. In medicinal plant soils, xeno-fungusphere MFCs restore soil health by stabilizing the pH, enriching dehydrogenase activity, and promoting nutrient cycling, thereby mitigating agrochemical-induced inhibition of secondary metabolite synthesis (e.g., ginsenosides, taxol). Field trials show 97.9% herbicide removal in 60 days, outperforming conventional methods. Innovations, such as adaptive electrodes, engineered strains, and phytoremediation-integrated systems, have been used to address soil and fungal limitations. This technology bridges sustainable agriculture and bioenergy recovery, offering the dual benefits of soil detoxification and enhanced crop quality. Future IoT-enabled monitoring and circular economy integration promise scalable, precision-based applications for global agroecological resilience. Full article

This paper focuses on the mathematical and numerical modeling of a non-classical macro fiber composite (MFC) piezoelectric transducer, MFC-P2, integrated with an aluminum cantilever beam for energy harvesting applications. It seeks to harness the transverse vibration energy in the environment to power small electronic devices, such as wireless sensors, where conventional power sources are inconvenient. The P2-type macro fiber composites (MFC-P2) are specifically designed for transverse energy harvesting applications. They offer high electric source capacitance and improved electric charge generation due to the strain developed perpendicularly to the voltage produced. The system is modeled analytically using Euler–Bernoulli beam theory and piezoelectric constitutive equations, capturing the electromechanical coupling in the d31 mode. Numerical simulations are conducted using COMSOL Multiphysics 6.29 to reduce the complexity of the mathematical model and analyze the effects of material properties, geometric configurations, and excitation conditions. The theoretical model is based on the transverse vibrations of a cantilevered beam using Euler–Bernoulli theory. The natural frequencies and mode shapes for the first four are determined. Depending on these, the resonance frequency, voltage, and power outputs are evaluated across a 12 kΩ resistive load. The results demonstrate that the energy harvester effectively operates near its fundamental resonant frequency of 10.78 Hz, achieving the highest output voltage of approximately 0.1952 V and a maximum power output of 0.0031 mW. The generated power is sufficient to drive ultra-low-power devices, validating the viability of MFC-based cantilever structures for autonomous energy harvesting systems. The application of piezoelectric phenomena and obtaining electrical energy from mechanical vibrations can be powerful solutions in such systems. The application of piezoelectric phenomena to convert mechanical vibrations into electrical energy presents a promising solution for self-powered mechatronic systems, enabling energy autonomy in embedded sensors, as well as being used for structural health monitoring applications. Full article

Multicolor flow cytometry (MFC) is a key method for assessing measurable residual disease (MRD) in acute lymphoblastic leukemia (ALL). However, very few approaches were developed for MRD in T-cell ALL (T-ALL). To identify MRD markers suitable for T-ALL, we analyzed the expression of CD2, CD3, CD4, CD5, CD7, CD8, CD10, CD34, CD45, CD48, CD56, CD99, and HLA-DR in T-ALL patients at diagnosis. The median fluorescence intensities (MFIs) of surface CD3, CD4, CD5, CD7, CD8, CD45, CD48, CD99, and CD16+CD56 were also evaluated at Day 15 and the end-of-induction (EOI). The MFC data from 198 pediatric T-ALL patients were analyzed retrospectively. At diagnosis, the most common antigens were identified, and the MFI of T-lineage antigens in blasts was compared to that in T lymphocytes. At follow-up, the MFIs of the proposed MRD markers were compared to those observed at diagnosis. The most common T-ALL antigens were CD7 (100.0%), intracellular CD3 (100.0%), CD45 (98.5%), and CD5 (90.9%). The MFIs of T-lineage antigens in blasts differed significantly from those in T lymphocytes. By the EOI, a substantial modulation of sCD3, CD4, CD5, CD7, CD8, and CD45 was observed. CD48 and CD99 were the most stable markers. The proposed MRD markers (sCD3, CD4, CD5, CD7, CD8, CD45, CD48, CD99, CD16+CD56) enabled MFC-MRD monitoring in virtually all T-ALL patients. Full article