Search Results (34)

The object of this research is the process of water disinfection by means of high-frequency electrical discharge. The study addresses the problem of achieving high biological efficiency while reducing energy consumption and avoiding harmful by-products typical of traditional methods such as chlorination or UV irradiation. As a result, a comprehensive theoretical and experimental investigation was conducted, demonstrating that within 20 s of plasma exposure, E. coli, S. aureus, and P. aeruginosa bacteria were inactivated by 99.2–99.9%. The observed efficiency is explained by the synergistic action of reactive oxygen and nitrogen species (•OH, O₃, H₂O₂, NO₂⁻, NO₃⁻) formed in the plasma–water interface. The distinctive features of the obtained results include the establishment of optimal operating parameters-voltage U = 12–18 kV, frequency f ≈ 35 kHz, and gap distance d = 15 mm—under which the normalized specific energy input (SEI) was 6–9 kWh per cubic meter of water. This value represents the standard normalization used for plasma-based treatment systems, where the electrical energy delivered to the reactor is divided by the treated volume (1.0 L in our setup) and scaled to m³ for comparison with other studies, 30–40% lower than in previously reported plasma systems. The validated physicochemical model (Poisson, Navier–Stokes, and continuity equations) matched experimental data with R² ≥ 0.95, confirming its predictive capability for further scale-up. The practical significance of the results lies in the potential application of this method for decentralized and industrial water treatment systems. The reagent-free, energy-efficient, and environmentally safe nature of the proposed approach makes it suitable for sustainable water purification under real operating conditions. Full article

Body size awareness—a component of bodily self-representation—allows animals to match their own dimensions to environmental constraints. This study tested whether reedfish (Erpetoichthys calabaricus), a benthic ray-finned species with limited vision, can evaluate aperture passability relative to their body size. Eight fish performed a “body-as-obstacle” task. After training, each individual completed 36 trials in Experiment 1 (three passable circular apertures of different diameters) and 72 trials in Experiment 2 (one small passable and two larger non-passable apertures). We scored first approach, first penetration attempt, and full passage; data were analyzed with generalized linear models. In Experiment 1, choices were random, unaffected by aperture size or position. In Experiment 2, first approaches were random, but first penetration attempts—and ensuing passages—were directed almost exclusively to the single passable aperture. These results indicate near-field formation of pass/not-pass judgments, likely via tactile and hydrodynamic sensing. The behavioral dissociation between exploratory (epistemic) and goal-directed (pragmatic) actions supports a modular model of self-representation, where distinct sensorimotor loops underlie information gathering and goal execution. Thus, reedfish demonstrate body-size awareness and contribute to comparative evidence that modular self-representation and embodied anticipation may extend deep into vertebrate evolution. Full article

Fish species’ biological vocalizations serve as essential acoustic signatures for passive acoustic monitoring (PAM) and ecological assessments. However, limited availability of high-quality acoustic recordings, particularly for region-specific species like the brown croaker (Miichthys miiuy), hampers data-driven bioacoustic methodology development. In this study, we present a framework for reconstructing brown croaker vocalizations by integrating fk14 wavelet synthesis, PSO-based parameter optimization (with an objective combining correlation and normalized MSE), and deep learning-based validation. Sensitivity analysis using a normalized Bartlett processor identified delay and scale (length) as the most critical parameters, defining valid ranges that maintained waveform similarity above 98%. The reconstructed signals matched measured calls in both time and frequency domains, replicating single-pulse morphology, inter-pulse interval (IPI) distributions, and energy spectral density. Validation with a ResNet-18-based Siamese network produced near-unity cosine similarity (~0.9996) between measured and reconstructed signals. Statistical analyses (95% confidence intervals; residual errors) confirmed faithful preservation of SPL values and minor, biologically plausible IPI variations. Under noisy conditions, similarity decreased as SNR dropped, indicating that environmental noise affects reconstruction fidelity. These results demonstrate that the proposed framework can reliably generate acoustically realistic and morphologically consistent fish vocalizations, even under data-limited scenarios. The methodology holds promise for dataset augmentation, PAM applications, and species-specific call simulation. Future work will extend this framework by using reconstructed signals to train generative models (e.g., GANs, WaveNet), enabling scalable synthesis and supporting real-time adaptive modeling in field monitoring. Full article

The utilisation of non-timber forest products (NTFPs) represents a key strategy for coping with food insecurity in rural areas worldwide, often resulting in their gradual depletion and extinction. One of the objectives of landscape restoration programmes is to restore depleted and conserve scarce NTFPs, as well as to preserve their various ecosystem services. However, the impact of these programmes on the well-being of local communities through their access to NTFPs remains understudied. The study focuses on the arid areas of the southern and central parts of the Maradi region in Niger in the Sahel, analysing how the landscape restoration programme contributes to improved access to NTFPs and their subsequent commercialisation to increase household incomes. The probit model with propensity score matching (PSM) reveals, on data from 379 households, that socioeconomic factors such as age, male gender, education level, and number of children, as well as access to NTFPs through donations, increase the chance of being selected as the programme beneficiary. On the other hand, ownership of goats, practising free collection, or purchasing NTFPs were typical for non-beneficiaries. The PSM analysis indicates that beneficiaries sell 11.81% more NTFPs on the market (p < 0.05). Furthermore, beneficiaries earn an average of 7297.40 CFA francs from forest products, compared to 3281.37 CFA francs for non-beneficiaries (p < 0.01). To enhance the impact of the programme, policymakers should prioritise outreach to underrepresented households and incorporate livestock management strategies. Strengthening local markets, storage facilities, and processing infrastructure can boost economic returns. Additionally, combining the conservation of NTFP-producing species with sustainable income activities can support both environmental and community resilience. Full article

Antimicrobial resistance (AMR) represents a threat to human, animal, and environmental health. This study evaluated the potential role of birds as AMR dispersers in white storks as a model species investigating dispersal between locations connected by their movements. Throughout a year, 346 samples were collected from two landfills (225 fecal samples) and two wetlands (93 fecal/28 water samples) based on satellite tracking data that confirmed continuous stork movements between foraging (landfill) and nighttime roosting (wetlands) locations. Samples were seeded in selective media with antibiotics for the isolation of antibiotic-resistant bacteria. A total of 313 isolates from 35 different bacterial species were obtained, with an AMR prevalence of 43.1% in fecal samples from landfills, 7.5% in fecal samples from wetlands, and 21.4% in water from wetlands. Multidrug resistant bacteria were only found in fecal samples (19.6% landfills/4.3% wetlands) and extended-spectrum beta-lactamase producing-bacteria were found exclusively in fecal samples from landfills with a marked presence during the fall migration period. Our study reveals marked differences in AMR prevalence and resistance phenotypes between study locations and fecal and water samples throughout the year, thus not supporting a clear role of storks as AMR dispersers. Nevertheless, similar changes in AMR phenotype prevalences during fall migration in stork faecal samples from one of the tested landfills and its paired wetland, and the significant increase in ESBL-producing Enterobacterales prevalence matching the arrival of migratory white storks in fall, underline the need for more in-depth genome-based studies to elucidate the role of white storks as dispersers or sentinels of AMR. Full article

Background: Schizophrenia is a complex neuropsychiatric disorder whose pathophysiology may involve oxidative stress-induced neuronal damage and inflammation. We conducted a cross-species study to elucidate oxidative stress dysregulation in schizophrenia. Methods: We measured peripheral oxidative stress biomarkers (malondialdehyde [MDA], nitric oxide [NO], reduced glutathione [GSH], superoxide dismutase [SOD], catalase [CAT], advanced protein oxidation products [APOP]), and C-reactive protein (CRP) in antipsychotic-naïve schizophrenia patients and matched controls. We also assayed liver enzymes (ALP, ALT, AST) as indicators of systemic metabolic stress. In parallel, we re-analyzed published single-cell RNA-sequencing data from a Setd1a^+/–^ mouse model of schizophrenia, focusing on prefrontal cortex (PFC) cell types and oxidative stress-related gene expression. Results: Patients with schizophrenia showed markedly elevated MDA and NO (indicators of lipid and nitrosative stress) and significantly reduced antioxidant defenses (GSH, SOD, CAT) versus controls (p < 0.01 for all comparisons). Notably, urban patients exhibited higher oxidative stress biomarker levels than rural patients, implicating environmental contributions. Liver function tests revealed increased ALT, AST, and ALP in schizophrenia, suggesting hepatic/metabolic dysregulation. Single-cell analysis confirmed dysregulated redox pathways in the schizophrenia model; PFC neurons from Setd1a^+/–^ mice displayed significantly lower expression of key antioxidant genes (e.g., Gpx4, Nfe2l2) compared to wild-type, indicating impaired glutathione metabolism. Conclusions: Our integrative data identify convergent oxidative stress imbalances in schizophrenia across species. These findings advance a mechanistic understanding of schizophrenia as a disorder of redox dysregulation and inflammation. They also have translational implications as augmenting antioxidant defenses (for example, with N-acetylcysteine or vitamins C/E) could mitigate oxidative injury and neuroinflammation in schizophrenia, representing a promising adjunct to antipsychotic therapy. Full article

Intercropping is an eco-friendly, sustainable agricultural model that significantly improves yield stability, nutrient use efficiency, and soil health through spatiotemporal niche complementarity, increases biodiversity, and improves soil health. Water and nitrogen play crucial roles in limiting and regulating efficient resource utilization and ecological sustainability in intercropping systems. Synchronizing water and nitrogen inputs to match crop demands optimizes the spatiotemporal distribution of these resources, alleviates interspecific competition, and promotes mutualistic interactions, which significantly impacts crop growth, yield, and soil environment. This paper reviews the mechanisms of intercropping and water–nitrogen coupling regulation, aligning water and nitrogen supply with crop growth patterns, spatial configuration parameters, irrigation management techniques, and environmental climate change, and explores the response mechanisms of water–nitrogen coupling on crop growth, yield, and soil environmental adaptation. It can provide some references for researchers, extension agents, and policymakers. Research indicates that water–nitrogen coupling can enhance photosynthetic efficiency, promote root development, optimize nutrient uptake, and improve soil water dynamics, nitrogen cycling, and microbial community structures. Intercropping enhances the climate resilience of agricultural systems by leveraging species complementarity for resource utilization, strengthening ecosystem stability, and improving buffering capacity against climate change impacts such as extreme precipitation and temperature fluctuations. Future studies should further elucidate the differential effect of water–nitrogen coupling across regions and climatic conditions, focusing on multidimensional integrated administration strategies. Combining precision agriculture technologies and climate change predictions facilitates the development of more adaptive water–nitrogen coupling models to provide theoretical support and technical guarantees for sustainable agriculture. Full article

Climate change has significantly affected marine fisheries. In recent years, marine heatwaves (MHWs) have intensified concurrently with increasing sea surface temperature (SST), particularly along the coast of Japan in the Northwest Pacific. Although the relationships between MHWs and large-scale climate patterns are well established, the long-term effects of MHWs on fisheries remain uncertain. Considering thermal adaptability, we analyzed the catches of warm- and cold-water species from commercially important fisheries in adjacent sea regions around Japan, correlating them with regional SSTs and MHW indices. Our results show that regional SSTs exhibited a persistent increasing trend, with major shifts occurring around 1988/89 and 1998/99. Pronounced interannual–decadal variabilities were observed in the leading principal components (PCs) of different species groups, with step changes concentrated in 1989~1992, 1999~2003, and 2009~2012. Notably, there was a significant negative response of cold groups to warming SSTs. Among warm-water species, only the Japanese sardine (Sardinops melanostictus) catch exhibited a strong correlation with climate change. Gradient forest analysis and threshold generalized additive models (TGAMs) further revealed the nonlinear, threshold-driven responses of the fish groups to environmental variability, which occurred after step changes in both the environmental factors and catches. Matching analysis between the annual change rates of catches and MHW indices confirmed the detrimental effects of strong MHWs on marine fisheries. Full article

Bioactive phytochemicals, such as polyphenols, play vital roles in human health, but conventional extraction methods rely on hazardous solvents. This study establishes natural deep eutectic solvents (NADESs) as versatile and environmentally friendly alternatives for recovering a variety of bioactive compounds from plant materials. Five choline chloride-based NADESs were evaluated for their effectiveness in extracting betalains (from beetroot), carotenoids (from carrot and sweet potato), anthocyanins (from chokeberry pomace and red onion), and polyphenols (from Lonicera japonica flowers, hop cones, rowan berries, and spent coffee grounds). Notably, NADES2 outperformed water in betalain recovery (179.86 mg of betanin/100 g of beetroot), while NADES4 (choline chloride-urea, 1:2 molar ratio) matched the polyphenol extraction efficiency of ethanol. Using L. japonica flowers as a model for optimization, Response Surface Methodology (RSM) identified the solvent ratio and temperature as critical extraction parameters, using high ratios (12:1–15:1 v/w) and moderate heat (55–75 °C) to maximize recovery. NADES4 emerged as a high-performing solvent, achieving a total phenolic content (TPC) of 75.94 mg chlorogenic acid/g and antioxidant activity of 451.00 µmol Trolox/g under the following conditions: 60% aqueous dilution, 15:1 solvent ratio, and 80 °C, 30 min. These findings highlight NADESs as a green, tunable solvent system for phytochemical extraction across plant species, offering enhanced efficiency, reduced environmental impact, and alignment with sustainable practices. Full article

Climate Envelope Models (CEMs) commonly employ 19 bioclimatic variables to predict species distributions, yet selecting which variables to include remains a critical challenge. Although it seems logical to select ecologically relevant variables, the biological responses of many target species are poorly understood. Random Forest (RF), a popular method in CEMs, can effectively handle correlated and nonlinear variables. In light of these strengths, this study explores the full model hypothesis, which involves using all 19 bioclimatic variables in an RF model, using Crustulina guttata (Theridiidae: Araneae) as a test case. Four model variants—a simplified model with two variables, an ecologically selected model with seven variables, a statistically selected model with ten variables, and a full model with nineteen variables—were compared against a thousand randomly assembled models with matching variable counts. All models achieved high performance, though results varied based on the number of variables employed. Notably, the full model consistently produced stronger predictions than models with fewer variables. Moreover, specifying particular variables did not yield a significant advantage over random selections of equally sized sets, indicating that omitting variables may risk the loss of important information. Although the final model suggests that C. guttata may have dispersed beyond its native European range through artificial means, this study examined only a single species. Thus, caution is warranted in generalizing these findings, and additional research is needed to determine whether the full model hypothesis extends to other taxa and environmental contexts. In scenarios where ecological knowledge is limited, however, using all available variables in an RF model may preserve potentially significant predictors and enhance predictive accuracy. Full article

Riverine environmental information includes important data to collect, and the data collection still requires personnel’s field surveys. These on-site tasks still face significant limitations (i.e., hard or danger to entry). In recent years, as one of the efficient approaches for data collection, air-vehicle-based Light Detection and Ranging technologies have already been applied in global environmental research, i.e., land cover classification (LCC) or environmental monitoring. For this study, the authors specifically focused on seven types of LCC (i.e., bamboo, tree, grass, bare ground, water, road, and clutter) that can be parameterized for flood simulation. A validated airborne LiDAR bathymetry system (ALB) and a UAV-borne green LiDAR System (GLS) were applied in this study for cross-platform analysis of LCC. Furthermore, LiDAR data were visualized using high-contrast color scales to improve the accuracy of land cover classification methods through image fusion techniques. If high-resolution aerial imagery is available, then it must be downscaled to match the resolution of low-resolution point clouds. Cross-platform data interchangeability was assessed by comparing the interchangeability, which measures the absolute difference in overall accuracy (OA) or macro-F1 by comparing the cross-platform interchangeability. It is noteworthy that relying solely on aerial photographs is inadequate for achieving precise labeling, particularly under limited sunlight conditions that can lead to misclassification. In such cases, LiDAR plays a crucial role in facilitating target recognition. All the approaches (i.e., low-resolution digital imagery, LiDAR-derived imagery and image fusion) present results of over 0.65 OA and of around 0.6 macro-F1. The authors found that the vegetation (bamboo, tree, grass) and road species have comparatively better performance compared with clutter and bare ground species. Given the stated conditions, differences in the species derived from different years (ALB from year 2017 and GLS from year 2020) are the main reason. Because the identification of clutter species includes all the items except for the relative species in this research, RGB-based features of the clutter species cannot be substituted easily because of the 3-year gap compared with other species. Derived from on-site reconstruction, the bare ground species also has a further color change between ALB and GLS that leads to decreased interchangeability. In the case of individual species, without considering seasons and platforms, image fusion can classify bamboo and trees with higher F1 scores compared to low-resolution digital imagery and LiDAR-derived imagery, which has especially proved the cross-platform interchangeability in the high vegetation types. In recent years, high-resolution photography (UAV), high-precision LiDAR measurement (ALB, GLS), and satellite imagery have been used. LiDAR measurement equipment is expensive, and measurement opportunities are limited. Based on this, it would be desirable if ALB and GLS could be continuously classified by Artificial Intelligence, and in this study, the authors investigated such data interchangeability. A unique and crucial aspect of this study is exploring the interchangeability of land cover classification models across different LiDAR platforms. Full article

Although usually studied as separate processes, plant growth and plant development are strictly interrelated. The BBCH scale (“Biologische Bundesanstalt, Bundessortenamt, and CHemical industry”) has become one of the primary classification systems for documenting the growth and developmental stages of many plant species. Specifically, the BBCH scale for hops (Humulus lupulus L.) separately describes growth and development during the vegetative stage. This study aims to develop an integrated approach to better understand the interaction between vertical growth rates and vegetative development in hops. Growth rates and development patterns of the Cascade hop cultivar were assessed in semi-arid (Sicily, Italy) and subtropical (Florida, USA) climates. The Gompertz model accurately described vertical growth, while a modified Gaussian model effectively captured hop growth rates (HGRs). A strong correlation between growth and developmental stages was identified, allowing for the inference of growth dynamics from developmental observations during the vegetative phase. Growth and developmental stages showed a 71% match across both environments, with minor phase shifts influenced by growing conditions. From an applied perspective, understanding the growth characteristics associated with developmental stages is crucial for addressing challenges posed by pests and diseases in emerging hop-growing regions. This integrated approach offers valuable insights into optimizing cultivation practices for diverse environmental conditions. Full article

Hypertension (HTN) is a major contributor to kidney damage, leading to conditions such as nephrosclerosis and hypertensive nephropathy, significant causes of chronic kidney disease (CKD) and end-stage renal disease (ESRD). HTN is also a risk factor for stroke and coronary heart disease. Oxidative stress, inflammation, and activation of the renin–angiotensin–aldosterone system (RAAS) play critical roles in causing kidney injury in HTN. Genetic and environmental factors influence the susceptibility to hypertensive renal damage, with African American populations having a higher tendency due to genetic variants. Managing blood pressure (BP) effectively with treatments targeting RAAS activation, oxidative stress, and inflammation is crucial in preventing renal damage and the progression of HTN-related CKD and ESRD. Interactions between genetic and environmental factors impacting kidney function abnormalities are central to HTN development. Animal studies indicate that genetic factors significantly influence BP regulation. Anti-natriuretic mechanisms can reset the pressure–natriuresis relationship, requiring a higher BP to excrete sodium matched to intake. Activation of intrarenal angiotensin II receptors contributes to sodium retention and high BP. In HTN, the gut microbiome can affect BP by influencing energy metabolism and inflammatory pathways. Animal models, such as the spontaneously hypertensive rat and the chronic angiotensin II infusion model, mirror human essential hypertension and highlight the significance of the kidney in HTN pathogenesis. Overproduction of reactive oxygen species (ROS) plays a crucial role in the development and progression of HTN, impacting renal function and BP regulation. Targeting specific NADPH oxidase (NOX) isoforms to inhibit ROS production and enhance antioxidant mechanisms may improve renal structure and function while lowering blood pressure. Therapies like SGLT2 inhibitors and mineralocorticoid receptor antagonists have shown promise in reducing oxidative stress, inflammation, and RAAS activity, offering renal and antihypertensive protection in managing HTN and CKD. This review emphasizes the critical role of NOX in the development and progression of HTN, focusing on its impact on renal function and BP regulation. Effective BP management and targeting oxidative stress, inflammation, and RAAS activation, is crucial in preventing renal damage and the progression of HTN-related CKD and ESRD. Full article

This review aims to advance the development of biofloc technology (BFT), providing more sustainable and efficient practices for the farming of the Japanese sea cucumber (Apostichopus japonicus). BFT is a sustainable aquaculture method that promotes nutrient recycling and effective carbon source management, offering significant advantages such as improving water quality, enhancing growth performance, and boosting the physiological activity and disease resistance of cultured animals. In A. japonicus farming, the optimal carbon source is glucose, and the ideal carbon-to-nitrogen (C/N) ratio ranges between 15 and 20. Microbial additives, such as the Bacillus species, have been shown to enhance biofloc formation and growth, as well as the immune responses in A. japonicus. However, the technology also faces limitations, including finding suitable biofloc culture protocols that match the physiological habits of A. japonicus and potential challenges with biofloc stability under varying environmental conditions. Based on existing research, this review discusses these limitations in the farming of A. japonicus. Additionally, it compares biofloc farming models for other economically important aquatic species. By addressing these key aspects, this review offers insights to enhance BFT performance, ultimately contributing to more efficient and sustainable A. japonicus aquaculture practices. Full article

Background: Autism spectrum disorder (ASD) is a neurodevelopmental disorder characterized by impairments in social interaction and restricted and repetitive behaviors. Oxidative stress may be a critical link between mitochondrial dysfunction and ASD as reactive oxygen species (ROS) generated from pro-oxidant environmental toxicants and activated immune cells can result in mitochondrial failure. Recently, mitochondrial dysfunction, autoimmunity, and abnormal lipid mediators have been identified in multiple investigations as an acknowledged etiological mechanism of ASD that can be targeted for therapeutic intervention. Methods: The relationship between lipid mediator markers linked to inflammation induction, such as phospholipase A2/cyclooxygenase-2 (PLA2/Cox-2), and the mitochondrial dysfunction marker anti-mitochondrial antibodies (AMA-M2), and anti-histone autoantibodies in the etiology of ASD was investigated in this study using combined receiver operating characteristic (ROC) curve analyses. This study also sought to identify the linear combination for a given set of markers that optimizes the partial area under ROC curves. This study included 40 age- and sex-matched controls and 40 ASD youngsters. The plasma of both groups was tested for PLA2/COX-2, AMA-M2, and anti-histone autoantibodies’ levels using ELISA kits. ROC curves and logistic regression models were used in the statistical analysis. Results: Using the integrated ROC curve analysis, a notable rise in the area under the curve was noticed. Additionally, the combined markers had markedly improved specificity and sensitivity. Conclusions: The current study suggested that measuring the predictive value of selected biomarkers related to mitochondrial dysfunction, autoimmunity, and lipid metabolism in children with ASD using a ROC curve analysis could lead to a better understanding of the etiological mechanism of ASD as well as its relationship with metabolism. Full article