Search Results (7,218)

Due to the indiscriminate use of antimicrobial drugs in the treatment of infectious diseases, human pathogenic bacteria have developed resistance to many commercially available antibiotics. Medicinal plants such as Convolvulus arvensis represent a renewable resource for the development of alternative therapeutic agents. This study aimed to evaluate the antibacterial activity of silver nanoparticles (AgNPs) biosynthesized from C. arvensis against two clinical antibiotic-resistant bacterial isolates. The pathogenic isolates were identified as Staphylococcus aureus MRSA and Escherichia coli ESBL using 16S rRNA gene sequencing. Silver nanoparticles were synthesized via a green synthesis approach, and their physicochemical properties were characterized using UV–Vis spectroscopy, scanning electron microscopy (SEM), Fourier transform infrared (FTIR) spectroscopy, zeta potential, and dynamic light scattering (DLS). The synthesized C. arvensis–AgNPs exhibited a surface plasmon resonance peak at 475 nm and predominantly spherical morphology with particle sizes ranging from 102.34 to 210.82 nm. FTIR analysis indicated the presence of O–H, C–O, C–N, C–H, and amide functional groups. The nanoparticles showed a zeta potential of −18.9 mV and an average hydrodynamic diameter of 63 nm. The antibacterial activity of the biosynthesized AgNPs was evaluated against methicillin-resistant S. aureus (MRSA and ATCC 29213) and E. coli (ESBL and ATCC 25922) using agar diffusion, minimum inhibitory concentration (MIC), and minimum bactericidal concentration (MBC) assays. Inhibition zones ranged from 10 to 13 mm, with MIC and MBC values of 12.5–25 µg/mL and 25–50 µg/mL, respectively. In addition, the nanoparticles exhibited antioxidant activity (DPPH assay, IC₅₀ = 0.71 mg/mL) and anti-inflammatory effects as determined by protein denaturation inhibition. No cytotoxic effects were observed in the MCF-7 cell line at the MIC level. These findings suggest that C. arvensis–AgNPs have potential as natural antimicrobial, antioxidant, and anti-inflammatory agents. Full article

Power supply for traction substations (TSs) of AC railways has traditionally been provided by 110–220 kV overhead transmission lines (OHL). These OHLs can be damaged during strong winds and ice formation. Furthermore, these lines generate significant electromagnetic fields (EMFs), which adversely affect maintenance personnel, the public, and the environment. Mitigating the resulting damages requires the establishment of protection zones, necessitating significant land allocation. Enhancing the reliability of power supply to traction substations and reducing EMF levels can be achieved through the use of gas-insulated lines (GIL), whose application in the power industry of many countries is continuously increasing. The aim of the research presented in this article was to develop computer models for determining the EMF of a GIL supplying a group of traction substations, taking into account actual traction loads characterized by non-sinusoidal waveforms and asymmetry. To solve this problem, an approach implemented in the Fazonord AC-DC software package, based on the use of phase coordinates, was applied. This allowed for the correct accounting of the skin effect and proximity effect in the massive current-carrying parts of the GIL, as well as the influence of asymmetry and harmonic distortions. The simulation results showed that the use of GIL brings the voltage unbalance factors at the 110 kV busbars of the traction substations within the permissible range, with the maximum values of these coefficients not exceeding 2%. The results of the harmonic distortion assessment demonstrated a significant reduction in harmonic distortion factors in the 110 kV network for the GIL compared to the OHL. The performed electromagnetic field calculations confirmed that the GIL generates magnetic field strengths one order of magnitude lower than those of the OHL. The obtained results lead to the conclusion that the use of gas-insulated lines for powering traction substations is highly effective, ensuring increased reliability, improved power quality, and a reduced negative impact of EMF on personnel, the public, the environment, and electronic equipment. Full article

Volcanic Scoria Lightweight Aggregate Concrete (VSLAC) has been identified as a material with considerable potential for use in carbon-neutral construction; however, its application is often hindered by two main issues. Firstly, the low density of scoria often results in aggregate segregation and stratification. Secondly, its high hygroscopicity can lead to shrinkage cracking. In order to address the aforementioned issues, this study proposes a multi-scale modification strategy. The cementitious matrix was first strengthened using a binary blend of Fly Ash and Ground Granulated Blast Furnace Slag (GGBS), followed by the incorporation of a ternary admixture system containing Styrene-Acrylic Emulsion (SAE), a foaming agent (FA), and alkali-treated Straw Fibres (SF) to enhance workability and durability. The findings of this study demonstrate that a mineral admixture comprising 10% Fly Ash and 10% GGBS results in a substantial enhancement of matrix compactness, culminating in a 20% increase in compressive strength. An orthogonal test was conducted to identify the optimal formulation (D13), which was found to contain 4% SAE, 0.1% FA, and 5% SF. This formulation yielded a compressive strength of 35.2 MPa, a flexural strength of 7.5 MPa, and reduced water absorption to 8.0%. A comparative analysis was conducted between the mineral admixture mix ratio (Control group) and the Optimal mix ratio (Optimization group). The results of this analysis reveal that the Optimization group exhibited superior durability and thermal characteristics. Specifically, the water penetration depth of the optimized composite was successfully restricted to within 3.18 mm, while its thermal insulation performance demonstrated a significant enhancement of 12.3%. In the context of freeze–thaw cycles, the modified concrete demonstrated notable durability, exhibiting a 51.4% reduction in strength loss and a marginal 0.64% restriction in mass loss. SEM analysis revealed that the interaction between SAE and the FA resulted in the densification of the Interfacial Transition Zone (ITZ). In addition, the 3D network formed by SF redistributed internal stresses, thereby shifting the failure mode from brittle fracture to ductile deformation. The findings demonstrate that modifying VSLAC at both micro- and macro-levels can effectively balance structural integrity with thermal efficiency for sustainable construction applications. Full article

Flammulina filiformis is the key industrial edible fungus that requires elevated CO₂ to promote the growth of long stipe and small pileus fruiting bodies. Heat shock transcription factors (HSFs) play vital roles in stress response and development regulation; yet the HSF gene family and its expression dynamics during fruiting body development in F. filiformis remain uncharacterized. This study aims to identify and characterize the HSF gene family in F. filiformis and to investigate their expression patterns during fruiting body development and in response to CO₂ treatments. In this study, 7 FfHSFs were identified, and their structures, sequence features, and phylogenetics were further analyzed. Expression patterns under CO₂ regulation were examined via qRT-PCR. The FfHSFs exhibited CDS lengths of 618–2298 bp, encoding 301–765 hydrophilic amino acids, with molecular weights ranging from 23.4 to 83.8 kDa and theoretical pI values between 4.75 and 9.15. All were predicted to be nuclear-localized. Cis-element analysis revealed motifs associated with growth regulation and stress responses such as low temperature, drought, and hypoxia. Phylogenetically, fungal HSFs were grouped into five clusters, with FfHSFs distributed across four. In this study, we examined the expression levels at four time points (0 h, 2 h, 12 h, and 36 h), under three different carbon dioxide concentrations (0.1%, 5%, and 20%) and in two types of tissues (pileus and stipe) for each six biological replicates. CO₂ treatments showed that 5% CO₂ significantly suppressed pileus expansion but not stipe elongation, while 20% CO₂ inhibited both. Under 20% CO₂ treatment, the pileus diameter decreased by approximately 40%, and simultaneously, the expression level of FfHSF1 decreased by about 70%. qRT-PCR indicated that FfHSF1 decreased with pileus expansion, whereas FfHSF4 increased. All FfHSFs were highly expressed in the stipe elongation zone. Elevated CO₂ down-regulated FfHSF1 in pileus and FfHSF6 in stipes. Based on these findings, it could be proposed that FfHSF1 and FfHSF6 might be candidate regulators in CO₂-mediated morphogenesis, providing insights into hormonal and environmental control of fruiting body development in F. filiformis. Full article

Background/Objectives: Maternal immune activation (MIA) increases the risk of Autism Spectrum Disorders (ASD). Experimental models demonstrate that maternal exposure to bacterial endotoxin or the viral mimic polyinosinic:polycytidylic acid [poly (I:C)] reliably recapitulates ASD-like behavioral abnormalities in offspring, yet the underlying neurobiological mechanisms linking MIA to altered neurodevelopment remain incompletely understood. Increasing evidence highlights the placenta as a critical mediator in shaping fetal brain development through immunological and hormonal regulation. Likewise, disruption of placental regulatory functions upon MIA may therefore represent a mechanistic pathway. Here, we investigated how alterations in placental cytokine profiles, innate immune cell composition, and endocrine outputs relate to neuroinflammation and neurogenesis in the offspring. Methods: Pregnant mice at gestational day 12.5 received a single intraperitoneal injection of poly (I:C). Placental macrophages, neutrophils, inflammatory cytokines, and nerve growth factor (NGF) expression were examined 72 h later. Neurodevelopmental outcomes, including microglial activity and neurogenic markers, were evaluated in mouse offspring at postnatal day (P) 1 and 6. Results: MIA induced a significant accumulation of monocytes and neutrophils in the placenta, which was associated with elevated levels of a broad spectrum of inflammatory mediators, including Th17-biased proinflammatory cytokines, chemokines, and adhesion proteins, in the placenta and amniotic fluid. In contrast, the placenta-derived NGF levels were significantly reduced. MIA induced strong and sustained microglial activation in the fetal and neonatal brain. This inflammatory milieu was accompanied by disrupted cortical neurogenesis, characterized by a marked increase in Ki67+ neuronal progenitor cells (NPCs) in the subventricular zone (SVZ), overproduction of early-born Tbr1+ neurons at P1, later-born Satb2+ neurons at P6. Conclusions: Collectively, these findings suggest that heightened Th17 inflammatory signaling, coupled with impaired placental endocrine function, contributes to dysregulated cortical neurogenesis in the offspring. Full article

Dynamic contrast-enhancement (DCE) modality of MRI is typically considered secondary in prostate cancer (PCa) diagnostics, due to the common interpretation that its diagnostic power is lower than that of other modalities like T2-weighted (T2W) or diffusion-weighted imaging (DWI). To challenge this paradigm, this study introduces a novel concept of a difference map, which relies exclusively on DCE-MRI for the localization of peripheral zone prostate cancer using functional data analysis-based (FDA) signal processing. The proposed workflow uses discrete voxel-level DCE time–signal curves that are transformed into a continuous functional form. First-order derivatives are then used to determine patient-specific time points of greatest enhancement change that adapt to the intrinsic characteristics of each patient, producing diffmaps that highlight regions with pronounced enhancement dynamics, indicative of malignancy. A subsequent normalization step accounts for inter-patient variability, enabling consistent interpretation across subjects and probabilistic PCa localization. The approach is validated on a curated dataset of 20 patients. Evaluation of eight workflow variants is performed using weighted log loss, the best variant achieving a mean log loss of 0.578. This study demonstrates the feasibility and effectiveness of a single-modality, automated, and interpretable approach for peripheral prostate cancer localization based solely on DCE-MRI. Full article

Mining-induced seismicity presents significant challenges to the safety and operational continuity of underground mines, particularly in deep and highly stressed environments. This study proposes a methodological framework for seismic risk evaluation inspired by predictive-maintenance principles and applied to a high-resolution microseismic catalog from a Chilean underground mine. Using a combination of data filtering and correlation analyses, we identify the seismic parameters that control the most variability in the dataset: moment magnitude, frequency corner, and both dynamic and static stresses. Based on this, we perform a Principal Component Analysis (PCA), which clearly demonstrates the physical interconnection between the selected parameters, thereby helping to better characterize the seismic events and the mining environment. Using these results, a PCA-based risk map is constructed, enabling the delineation of zones with different levels of seismic risk. Additionally, a temporal tracking of potentially hazardous seismicity is included. The proposed methodology demonstrates that microseismic behavior can be effectively represented in a reduced-dimension space, offering a promising foundation for predictive and data-driven risk-assessment tools capable of supporting real-time decision-making in underground mining operations. Full article

Mitochondria are essential organelles involved in metabolism, energy production, and cell signaling. Assessing mitochondrial morphology is key to tracking cell metabolic activity and function. Quantifying these structural changes may also provide critical insights into disease pathogenesis and therapeutic responses. This work details the development and validation of a novel, quantitative image analysis pipeline for the characterization and classification of dynamic mitochondrial morphologies. Utilizing high-resolution confocal microscopy, the pipeline integrates first-order statistics (FOS) and a comprehensive suite of gray-level texture analyses, including gray level co-occurrence matrix (GLCM), gray level run length matrix (GLRLM), gray level dependence matrix (GLDM), gray level size zone matrix (GLSZM), and neighboring gray tone difference matrix (NGTDM) with machine learning approaches. The method’s efficacy in objectively differentiating key mitochondrial structures—fibers, puncta, and rods—which are critical indicators of cellular metabolic and activation states is demonstrated. Our open-source pipeline provides robust quantitative metrics for characterizing mitochondrial variation. Full article

Background: recently, regenerative medicine has introduced a new branch of science that facilitates the repair of damaged tissues and organs in acute myocardial infarction. This study explores the role of the C-type natriuretic peptide (CNP) system in myocardial infarction (MI) and its modulation by Apelin-13 functionalized patches (A-13p). Methods: using an experimental rat model of ischemia/reperfusion, the rats were divided into four groups: Sham, Infarct, Sham with A-13p, and Infarct with A-13p. Cardiac tissue from the infarct, border, and remote zones was analyzed for CNP and its receptors’ mRNA expression via Real-Time PCR. Results: histological analysis, 4 weeks post A-13p implantation, showed no damage from A-13p implantation in either MI or Sham groups, with reduced left ventricle wall thinning in the Infarct group treated with A-13p. CNP mRNA expression was higher in the infarcted groups (p = ns), especially in the border/infarct zone (BZ + IZ), compared to the Sham group (p = 0.05). NPR-B receptor expression was higher in the RZ than in (BZ + IZ), both in the absence (p = 0.02) and presence of patches (p = 0.01), while NPR-C expression was lower. No significant differences were observed in VEGF mRNA levels across the groups. Conclusions: the findings suggest that the CNP system is involved in MI and that A-13p modulates CNP expression, highlighting CNP as a potential target for therapeutic strategies aimed at regulating vascular remodeling and angiogenesis in MI treatment. Full article

The subject of this research is the exploration of the potential of remote sensing and Geographic Information Systems (GIS) for basin-scale spatio-temporal monitoring of drought and its impacts in the Ukrina River Basin, Bosnia and Herzegovina (BH), during the last decade (2015–2024). The aim is to integrate meteorological, hydrological, agricultural, and socio-economic drought signals and to delineate areas of long-term drought exposure. Meteorological drought was evaluated using CHIRPS precipitation and the Standardized Precipitation Index (SPI) calculated at 1-, 3-, 6-, and 12- month accumulation scales using Gamma fitting and a fixed long term reference period; hydrological drought was examined using available water-level records complemented by the Standardized Water Level Index (SWLI) and supported by correspondence with standardized ERA5-Land runoff anomalies; agricultural drought was mapped using remote sensing indices—the Temperature Condition Index (TCI), Vegetation Condition Index (VCI), and Vegetation Health Index (VHI)—calculated from MODIS satellite data; and socio-economic effects were assessed using municipal crop-production statistics (2015–2019). The results indicate that drought conditions were most pronounced in 2015, 2017, 2021, and especially 2022, showing consistent agreement between precipitation deficits, hydrological responses, and vegetation stress, while 2016, 2018–2020, 2023, and 2024 were generally more favorable. As a key novelty, a persistent drought-prone zone was delineated by intersecting drought-affected areas across major episodes, providing a basin-scale identification of chronic drought hotspots for a river basin in BH. The persistent zone covers 40.02% of the basin and spans nine cities and municipalities, with >93% located in Prnjavor, Derventa, Stanari, and Teslić. Hotspots are concentrated mainly in lowlands below 400 m a.s.l., with a statistically significant concentration across lower elevation classes, indicating higher long-term exposure in the central and northern valley sectors, and land use overlay further highlights high relative exposure of productive land. Overall, the integrated remote sensing and GIS framework strengthens drought monitoring by providing spatially explicit and repeatable evidence to support targeted adaptation planning and drought-risk management. Full article

Argania spinosa L. Skeels is an ecological pillar of the arid zones of South-West Morocco, currently threatened by the drastic climate change. This study investigates the effect of the combined application of compost (C) and subsurface water retention technology (SWRT) on field performances of one-(1Y) and two-year-old (2Y) argan seedlings. A randomized field trial was performed with four treatments: Control, C, SWRT, and C + SWRT. We evaluated soil properties, growth, and physiology, alongside biochemical parameters including stress markers, compatible solutes, antioxidant enzyme activities, and secondary metabolites. The results reveal the significant effect of C and/or SWRT on argan seedlings performances, particularly in 1Y subjects. The C + SWRT strongly stimulated stem elongation (246% vs. 163%), stomatal conductance (75% vs. 99%), photosynthetic efficiency (18% vs. 11%), and chlorophyll a content (80% vs. 65%) in 1Y and 2Y seedlings, respectively, compared to their corresponding controls. Under the same treatment, malondialdehyde levels were significantly reduced by 37% in 1Y seedlings and 23% in 2Y seedlings. In addition, catalase activity and soluble sugar, protein, and polyphenol content increased by 38, 43, 26, and 21%, respectively, in the younger seedlings and by 53, 51, 18, and 19%, respectively, in the elder seedlings. In terms of soil health, C + SWRT significantly enhanced total organic carbon and matter, available phosphorus, and reduced electrical conductivity. In summary, the C + SWRT application significantly improved argan plant performances, with a particularly marked effect on 1Y seedlings, which makes this combination an alternative solution to enhance the resilience of the argan tree in the era of climate change and promote the success of the reforestation program. Full article

Eutrophication remains a persistent challenge in the Romanian Black Sea coastal zone, driven by excess nutrient inputs from riverine and coastal sources and further intensified by climate change. This study assesses eutrophication dynamics and explores mitigation options using an integrated framework that combines in situ observations, satellite-derived chlorophyll a data, machine learning, and system dynamics modelling. Water samples collected during two field campaigns (2023–2024) were analyzed for nutrient concentrations and linked with chlorophyll a products from the Copernicus Marine Service. Random Forest analysis identified dissolved inorganic nitrogen, phosphate, salinity, and temperature as the most influential predictors of chlorophyll a distribution. A system dynamics model was subsequently used to explore relative ecosystem responses under multiple management scenarios, including nutrient reduction, enhanced zooplankton grazing, and combined interventions. Scenario-based simulations indicate that nutrient reduction alone produces a moderate decrease in chlorophyll a (45% relative to baseline conditions), while restoration of grazing pressure yields a comparable response. The strongest reduction is achieved under the combined scenario, which integrates nutrient reduction with biological control and lowers normalized chlorophyll a levels by approximately two thirds (71%) relative to baseline. In contrast, a bloom-favourable scenario results in a several-fold increase in chlorophyll a of 160%. Spatial analysis highlights persistent eutrophication hotspots near the Danube mouths and urban discharge areas. These results demonstrate that integrated strategies combining nutrient source control with ecological restoration are substantially more effective than single-measure interventions. The proposed framework provides a scenario-based decision-support tool for ecosystem-based management and supports progress toward achieving Good Environmental Status under the Marine Strategy Framework Directive. Full article

Camellia oleifera, a woody oil crop unique to China, plays a crucial role in alleviating the global pressure of edible oil supply and maintaining ecological security. However, it remains challenging to accurately forecast Camellia oleifera yield in complex landscapes using only remote sensing data. The aim of this study is to develop an interpretable deep learning model, namely Shapley Additive Explanations–guided Attention–long short-term memory (SALSTM), for estimating Camellia oleifera yield by integrating an improved spectral bloom index and environmental parameters. The study area is located in Hengyang City in Hunan Province. Sentinel-2 imagery, meteorological observation from 2019 to 2023, and topographic data were collected. First, an improved spectral bloom index (ISBI) was constructed as a proxy for flowering density, while average temperature, precipitation, accumulated temperature, and wind speed were selected to represent environmental regulation variables. Second, a SALSTM model was designed to capture temporal dynamics from multi-source inputs, in which the LSTM module extracts time-dependent information and an attention mechanism assigns time-step-wise weights. Feature-level importance derived from SHAP analysis was incorporated as a guiding prior to inform attention distribution across variable dimensions, thereby enhancing model transparency. Third, model performance was evaluated using root mean square error (RMSE) and coefficient of determination (R²). The result show that the constructed SALSTM model achieved strong predictive performance in predicting Camellia oleifera yield in Hengyang City (RMSE = 0.5738 t/ha, R² = 0.7943). Feature importance analysis results reveal that ISBI weight > 0.26, followed by average temperature and precipitation from flowering to fruit stages, these features are closely associated with C. oleifera yield. Spatially, high-yield zones were mainly concentrated in the central–southern hilly regions throughout 2019–2023, In contrast, low-yield zones were predominantly distributed in the northern and western mountainous areas. Temporally, yield hotspots exhibited a gradual increasing while low-yield zones showed mild fluctuations. This framework provides an effective and transferable approach for remote sensing-based yield estimation of flowering and fruit-bearing crops in complex landscapes. Full article

A low-carbon economy serves as a core pathway and pivotal engine for advancing the SDGs. Drawing on provincial panel data across 30 Chinese administrative regions spanning 2011–2023, the present study empirically examines how new infrastructure interacts with low-carbon economic development levels and their underlying transmission mechanisms by building an econometric model. Empirical results demonstrate that “new infrastructure” generates a notably positive facilitating impact on low-carbon economic development, with this influence being more pronounced in the central and western regions of China and policy pilot zones, while a rebound effect is identified in eastern China. Among various types of new infrastructure, information infrastructure and innovation infrastructure play particularly prominent roles, while integrated infrastructure shows a positive yet statistically insignificant impact. Mechanism analysis reveals that new infrastructure advances low-carbon economic progress primarily by curbing capital factor misallocation, while the elevation of the population urbanization level can amplify the facilitative impact of new infrastructure on the low-carbon economy. On this basis, it is imperative to raise investment in new infrastructure and enhance its systematic coordination with traditional infrastructure; implement differentiated layout strategies aligned with regional features; rationally steer the population urbanization process; and effectively facilitate the decoupling of carbon emissions from economic growth, thereby furnishing a robust underpinning for the full attainment of SDGs. Full article

Metal pollution from metallurgical emissions poses serious environmental and public health risks in Kazakhstan. A replicated pot-culture experiment (n = 4) in a completely randomized design under controlled phytotron conditions evaluated biomass production and metal accumulation in six crop and forage species, alfalfa (Medicago sativa), amaranth (Amaranthus spp.), corn (Zea mays), mustard (Brassica juncea), rapeseed (Brassica napus), and sunflower (Helianthus annuus); three ornamental species, purple coneflower (Echinacea purpurea), marigold (Tagetes spp., ‘Tiger Eyes’), and sweet alyssum (Lobularia maritima); and three native wild plants, greater burdock (Arctium lappa), horse sorrel (Rumex confertus), and mug wort (Artemisia vulgaris). Plants were grown in soils collected from the Qarmet industrial zone in Temirtau, central Kazakhstan. Initial soil analysis revealed substantial mixed-metal contamination, ranked as Mn > Ba > Zn > Sr > Cr > Pb > Cu > Ni > B > Co. Mn reached 1059 mg·kg⁻¹, ~50-fold higher than B (22.7 mg·kg⁻¹). Ba (620 mg·kg⁻¹) exceeded FAO/WHO limits sixfold, Zn (204 mg·kg⁻¹) surpassed the lower threshold, and Pb (41.6 mg·kg⁻¹) approached permissible levels, while Cr, Cu, Ni, Co, and Sr were lower. Biomass production varied markedly among species: corn and sunflower produced the highest shoot biomass (126.8 and 60.9 g·plant⁻¹), whereas horse sorrel had the greatest root biomass (54.4 g·plant⁻¹). Root-to-shoot ratios indicated shoot-oriented growth (>1–8) in most species, except horse sorrel and burdock (<1). Metal accumulation was strongly species-specific. Corn and marigold accumulated Co, Pb, Cr, Mn, Ni, Cu, B, and Ba but showed limited translocation (transfer function, TF < 0.5), whereas sunflower, amaranth, and mug wort exhibited moderate to high translocation (TF > 0.8 to <1) for selected metals. Corn is recommended for high-biomass metal removal, marigold for stabilization, sunflower, horse sorrel, and mug wort for multi-metal extraction, and amaranth and coneflower for targeted Co, Ni, and Cu translocation, supporting sustainable remediation of industrially contaminated soils. Full article