Search Results (2,019)

Active exosuits provide various assistive force profiles but are limited by battery life, weight, and complex maintenance requirements. Passive exosuits, by contrast, are economical and lightweight while also offering unlimited usage times; however, due to their fixed stiffness levels, they can provide only a limited set of optimized assistive force profiles for different movements. To address these issues, this paper proposes a new variable elastic band for semi-passive exosuits. It comprises rubber bands and webbings connected in parallel, with the elongation of the rubber bands restricted according to the webbing length. By connecting these segments in series, a range of elasticities can be generated. Experimental results confirmed that the band could generate different stiffness levels, which were accurately predicted with an average coefficient of determination (R²) of 0.9985 and an average root mean square error of 0.8993. Additionally, based on tests involving participants wearing the device, the variable elastic band effectively modulated the assistive force profile. These findings overcome the previous limitations of passive components, opening the door to future research on enhancing the efficiency of passive systems and enabling further customization. Full article

Rice sheath rot has progressively developed into a growing threat to global rice production, particularly in intensively managed systems conducive to disease development. Therefore, accurate identification of the causal pathogen and the development of sustainable management strategies represent urgent scientific requirements. In this study, we isolated the causal organism of rice sheath rot from infected rice tissues and identified it as Fusarium verticillioides based on multi-locus sequence analysis. Eight endophytic bacterial strains were recovered from healthy rice root systems. Among the isolates, Bacillus velezensis isolate 7-A exhibited the strongest antifungal activity against F. verticillioides. This isolate demonstrated broad-spectrum antifungal activity, with inhibition rates ranging from 54.8% to 71.8%. Phylogenetic analysis based on 16S rRNA and gyrB gene sequences identified it as B. velezensis. Further characterization revealed that B. velezensis 7-A is capable of secreting proteases and synthesizing siderophores. The filtered liquid from sterile fermentation markedly inhibited the growth of mycelium in F. verticillioides and induced marked morphological abnormalities. Liquid LC-MS analysis identified multiple antifungal active substances, including camphor, ginkgolides B, salicin, cinnamic acid, hydroxygenkwanin, stearamide, β-carotene, and others. A pot experiment demonstrated that the fermentation broth of B. velezensis 7-A effectively suppressed the occurrence of rice sheath rot, achieving a relative control efficacy of 61.3%, which is comparable to that of a 10% carbendazim water-dispersible granule (WDG). Additionally, isolate 7-A enhances plant disease resistance by activating the activities of key defense enzymes. These findings provide preliminary insights into its potential application in integrated and sustainable disease management programs. Full article

Long-term intensive cultivation has caused soil fertility decline and structural degradation in the Songnen Plain, thereby constraining maize root development and yield formation. As a fundamental conservation tillage practice, straw return enhances soil function by incorporating exogenous organic matter and regulating root-shoot physiological processes. However, the mechanism underlying yield improvement through root–photosynthesis–nitrogen synergy remains insufficiently understood. A field experiment was conducted to assess the effects of conventional tillage (CT), straw incorporation (SI), straw mulching (SM), and deep straw incorporation (DF) on maize physiological traits and yield. Compared with CT, DF markedly enhanced root morphology and physiology, increasing the root length, surface area, volume, and root-shoot ratio by 16.46%, 23.87%, 26.64%, and 51.34%, respectively. The root bleeding intensity increased by 23.63%, whereas amino acid and nitrate contents in the bleeding sap increased by 29.20% and 65.93%, respectively, indicating improved root nutrient transport capacity. The enhanced root system positively influenced shoot photosynthesis by increasing the chlorophyll SPAD value by 16.05%, net photosynthetic rate (P_n) by 11.28%, and the activities of RuBP, PEP, nitrate reductase (NR), and glutamine synthetase (GS) by 10.59%, 24.36%, 29.94%, and 12.47%, respectively. These synergistic improvements significantly promoted post-anthesis biomass accumulation and yield formation. DF increased nitrogen and dry matter accumulation at the R3 stage by 26.61% and 15.67%, respectively, and resulted in an average yield increase of 8.34%, which was primarily due to an 11.96% increase in 100-grain weight. Although SI and SM also improved certain physiological indices, their effects were weaker than those of DF. RF analysis identified sap nitrate content (RNO), bleeding intensity (RBI), root length (RL), and root volume (RV) as key yield determinants. PLS-SEM further revealed that straw return enhanced root morphology and bleeding traits (path coefficients: 0.96 and 0.82), which subsequently improved leaf photosynthetic traits (path coefficients: 0.52 and 0.39) and biomass accumulation (path coefficient: 0.71). Collectively, these improvements promoted post-anthesis nitrogen accumulation and dry matter partitioning into grains. These findings elucidated the physiological mechanism by which deep straw incorporation increased maize yield through root system optimization, providing a theoretical basis for conservation tillage optimization in the thin-layer Mollisol region of the Songnen Plain. Full article

Monitoring indoor air quality is vital for health, as CO₂ is a major pollutant. An automated system that accurately forecasts CO₂ levels can optimize HVAC management, preventing sudden increases and reducing energy waste while maintaining occupant comfort. Traditionally, such systems require extensive datasets collected over months to train algorithms, making them computational expensive and inefficient. To address this limitation, an adaptive IoT-based platform has been developed, leveraging a limited set of recent data to forecast CO₂ trends. Tested in a real-world setting, the system analyzed parameters such as physical activity, temperature, humidity, and CO₂ to ensure accurate predictions. Data acquisition was performed using the Smartex WWS T-shirt for physical activity data and the UPSense UPAI3-CPVTHA environmental sensor for other measurements. The chosen sensor devices are wireless and minimally invasive, while data processing was carried out on a low-power embedded PC. The proposed forecasting model adopts an innovative approach. After a 5-day training period, a Generative Adversarial Network enhances the dataset by simulating a 10-day training period. The model utilizes a Generative Adversarial Network with a Long Short-Term Memory network as the generator to predict future CO₂ values based on historical data, while the discriminator, also a Long Short-Term Memory network, distinguishes between actual and generated CO₂ values. This approach, based on Conditional Generative Adversarial Networks, effectively captures data distributions, enabling more accurate multi-step probabilistic forecasts. In this way, the framework maintains a Root Mean Square Error of approximately 8 ppm, matching the performance of our previous approach, while reducing the need for real training data from 10 to just 5 days. Furthermore, it achieves accuracy comparable to other state-of-the-art methods that typically requires weeks or even months of training. This advancement significantly enhances computational efficiency and reduces data requirements for model training, improving the system’s practicality for real-world applications. Full article

The uptake and accumulation of nanoplastics by plants have emerged as a major research focus. Exogenous selenium nanoparticles (SeNPs) are widely used to mitigate the toxicity of abiotic stresses, such as nanoplastics (NPs) and polyethylene (PE—NPs) nanoplastics, and represent a feasible strategy to enhance plant performance. However, the molecular mechanisms by which SeNPs alleviate the phytotoxicity of microplastics and nanoplastics remain poorly defined. To address this gap, we used Pistia stratiotes L. (P. stratiotes) as a model and silicon dioxide nanoparticles (SiO₂NPs) as a comparator, integrating physiological assays, ultrastructural observations, and proteomic analyses. We found that NP stress caused ultrastructural damage in root tips, exacerbated oxidative stress, and intensified membrane lipid peroxidation. SeNPs treatment significantly mitigated NP-induced oxidative injury and metabolic suppression. Compared to the NPs group, SeNPs increased T-AOC by 38.2% while reducing MDA and ·OH by 33.3% and 89.6%, respectively. Antioxidant enzymes were also elevated, with CAT and POD rising by 47.1% and 39.2%. SeNPs further enhanced the photosynthetic capacity and osmotic adjustment, reflected by increases in chlorophyll a, chlorophyll b, and soluble sugar by 49.7%, 43.8%, and 27.0%, respectively. In contrast, proline decreased by 17.4%, indicating stress alleviation rather than an osmotic compensation response. Overall, SeNPs outperformed SiO₂NPs. These results indicate that SeNPs broadly strengthen anti-oxidative defenses and metabolic regulation in P. stratiotes, effectively alleviating NP-induced oxidative damage. Proteomics further showed that SeNPs specifically activated the MAPK signaling cascade, phenylpropanoid biosynthesis, and energy metabolic pathways, enhancing cell-wall lignification to improve the mechanical barrier and limiting NPs translocation via a phytochelatin-mediated vacuolar sequestration mechanism. SiO₂NPs produced similar but weaker alleviative effects. Collectively, these findings elucidate the molecular basis by which SeNPs mitigate NPs’ phytotoxicity and provide a theoretical foundation and practical outlook for using nanomaterials to enhance phytoremediation in aquatic systems. Full article

The degradation of soil structure in black soils has become a key factor limiting the productivity of farmland ecosystems. However, systematic studies on restoring soil physical properties and improving crop yields through biological tillage remain scarce. In this study, Eisenia fetida was employed as a biological tillage agent to create soil macropores. An orthogonal experiment with three factors was conducted to investigate the mechanisms by which different gradients of soil moisture, decomposed straw, and soil compaction affect soil pore structure and the yield of Brassica chinensis L. X-ray-computed tomography (CT) was used to quantitatively characterize the macropore network mediated by earthworms. The results indicated that the critical threshold conditions for optimized biological tillage were 50 g of decomposed straw, a compaction of 50–150 kPa, and a soil moisture content of 30–37%. Under these conditions, earthworm activity significantly enhanced the leaf dry weight of Brassica chinensis L. by approximately 55.29%, while root dry weight increased by 96.60%. Compared with treatments of low soil moisture combined with 50 g of decomposed straw, higher moisture levels further increased total biomass by 75.46%. Compared with the control, earthworm-induced macropores had 27 times more pore throats than abiotic pores, and network models showed significantly improved connectivity, indicating enhanced soil structure. This study revealed a synergistic threshold of water–food–physical resistance regulation for soil structural improvement under biological tillage and innovatively proposed a biological tillage evaluation system based on CT-quantified pore networks and root structure–function relationships. These findings provide a theoretical basis for the ecological restoration of degraded black soils. Full article

Intercropping triggers coordinated changes in gene expression and metabolite accumulation across sugarcane roots, stems, and leaves, leading to higher crop yields—an effect that has drawn growing attention. Yet, how this transcriptional and metabolic interplay precisely enhances productivity remains poorly understood, limiting insight into intercropping’s yield-promoting mechanisms. This research explored the relationships between sugarcane, its metabolites, and transcriptomes through field trials integrated with multi-omics analysis. Data from the field showed clear differences in gene expression and metabolite patterns between monoculture and intercropped sugarcane. Plants under intercropping displayed stronger differential gene expression, greater metabolite diversity, and shifts in physiological traits. Metabolite variation was closely linked to gene regulation and network complexity, which in turn affected key agricultural characteristics including plant height, stem thickness, and sugar content. Follow-up experiments confirmed that applying zinc—a element boosted by intercropping—improved growth in monoculture sugarcane and modified its hormonal composition. These results highlight the important role of coordinated transcriptome-metabolite activity in intercropping systems. The study provides valuable perspectives for making intensive farming more economical and sustainable, supporting efforts to raise crop output and improve ecosystem functions. Full article

Fabricating breast tumor models that mimic the natural breast tissue-like microenvironment (normal or cancerous) both physically and bio-metabolically, despite extended research, is still a challenge. A native-mimicking breast tumor model is the demand since complex biophysiological mechanisms in the native breast tissue hinder deciphering the root causes of cancer initiation and progression. Hydrogels, which mimic the natural extracellular matrix (ECM), are increasingly demanded for various biomedical applications, including tissue engineering and tumor modeling. Their biomimetic 3D network structures have demonstrated significant potential to enhance the breast tumor model, treatment, and recovery. Additionally, 3D tumor organoids cultivated within hydrogels maintain the physical and genetic traits of native tumors, offering valuable platforms for personalized medicine and therapy response evaluation. Hydrogels are broadly classified into static and dynamic hydrogels. Static hydrogels, however, are inert to external stimuli and do not actively participate in biological processes or provide scaffolding systems. Dynamic hydrogels, on the other hand, adapt and respond to the surrounding microenvironment or even create new microenvironments according to physiological cues. Dynamic hydrogels typically involve reversible molecular interactions—through covalent or non-covalent bonds—enabling the fabrication of hydrogels tailored to meet the mechanical and physiological properties of target tissues. Although both static and dynamic hydrogels can be advanced by incorporating active nanomaterials, their combinations with dynamic hydrogels provide enhanced functionalities compared to static hydrogels. Further, engineered hydrogels with adipogenic and angiogenic properties support tissue integration and regeneration. Hydrogels also serve as efficient delivery systems for chemotherapeutic and immunotherapeutic agents, enabling localized, sustained release at tumor sites. This approach enhances therapeutic efficacy while minimizing systemic side effects, supporting ongoing research into hydrogel-based breast cancer therapies and reconstructive solutions. This review summarizes the roles of dynamic hydrogels in breast tumor models. Furthermore, this paper discusses the advantages of integrating nanoparticles with dynamic hydrogels for drug delivery, cancer treatment, and other biomedical applications, alongside the challenges and future perspectives. Full article

Tris(2-chloroethyl) phosphate (TCEP), as an organophosphate contaminant, poses a significant threat to the growth and development of plants, especially roots. This study aimed to clarify the mechanisms of TCEP’s toxicity and damage to root systems, as well as the mechanisms of its damage to the respiration and energy metabolism of alfalfa root cells. The results showed that TCEP obviously affected the root length, root surface area, root volume, and root diameter of alfalfa. With increasing stress intensity, the total mitochondrial respiration rate and Cytochrome C Oxidase (COX) pathway respiration rate progressively declined, while the Alternative Oxidase (AOX) pathway respiration rate and its proportion of total respiration gradually rose. In addition, adenosine triphosphate (ATP) content and root vigor were significantly reduced. Moreover, with an increase in TCEP concentration, root superoxide anion radical content in alfalfa root cells was significantly elevated, while superoxide dismutase (SOD) and catalase (CAT) activities were significantly lowered, and ascorbate peroxidase (APX) and peroxidase (POD) activities were significantly enhanced. The present study indicated that respiration was disrupted, causing a lack of ATP in root cells under TCEP. Both the overproduction of reactive oxygen species (ROS) from the mitochondrial respiratory electron transport chain (mECT) and the deficiency of ROS-scavenging enzymes caused ROS accumulation, which led to the destruction of the cell membrane structure and exacerbated the disruption of the respiratory metabolism. The disruption of the conversion and reuse of energy by TCEP affected root growth and development. Full article

The dehesa, as a socio-ecological system and cultural landscape, is a strategic resource for environmental education, territorial sustainability, and the intergenerational transmission of knowledge. This study analyzes the perception of primary school students in Extremadura regarding this environment, using a mixed methodology that combines statistical, semantic, and spatial analysis. The results show a generally positive assessment of the dehesa heritage, although accompanied by a disconnect between this symbolic assessment and direct experience of the territory, especially in urban contexts. It identifies significant differences between students from rural and urban environments in terms of their knowledge of trades, products, and dehesa spaces, as well as their preferred activities in the dehesa. While rural students show greater interest in operational activities and direct contact with the environment (such as feeding livestock and milking), urban students lean toward sensory or symbolic experiences (such as consuming products or occasional harvesting), reflecting different ways of connecting with the territory. Spatial analysis reveals that more than 80% of schools are located less than 5 km from well-preserved dehesa areas, which represents an opportunity to integrate these landscapes into formal education. However, inequalities in access from special education centers have been detected, posing challenges in terms of territorial and educational equity. This study concludes that the dehesa should be recognized as an open classroom, capable of fostering roots, ecological literacy, and cultural sustainability through contextualized and territory-sensitive pedagogical approaches. Full article

Background/Objectives: Naegleria fowleri is a free-living protozoan that causes primary amoebic meningoencephalitis, a rapidly progressing central nervous system infection with high mortality rates and limited treatment options. Targeting virulence-associated proteins is essential for effective drug development. Fowlerpain-1 (FWP1), a papain-like cysteine protease (CP) implicated in extracellular matrix degradation and host–cell cytotoxicity, has been investigated as a therapeutic target. This study aimed to evaluate the FWP1 pocket geometry and stefin binding using an integrated in silico structural biology approach. Methods: A computational pipeline was used, including AlphaFold2-Multimer modeling of FWP1–stefin complexes, 20-ns molecular dynamics simulations under NPT conditions for conformational sampling, and molecular mechanics Poisson–Boltzmann surface area free energy calculations. Three natural CP inhibitors (stefins) were investigated. Structural stability was assessed using root mean square deviations, and binding profiles were characterized using protein–protein interaction analysis. Results: Stable FWP1–stefin interaction interfaces were predicted, with human stefin A showing favorable binding free energy. Two conserved motifs (PG and QVVAG) were identified as critical mediators of active-site recognition. Druggability analysis revealed a concave pocket with both hydrophobic and polar characteristics, consistent with a high-affinity ligand-binding site. Conclusions: This computational study supports a structural hypothesis for selective FWP1 inhibition and identifies stefins as promising scaffolds for developing structure-guided protease-targeted therapeutics against N. fowleri. Full article

The naphthazarins shikonin and alkannan are strongly chromogenic, dark red enantiomers, each of which has biological activity, that are found primarily in the plant family Boraginaceae. These compounds and their many chemical metabolites, derivatives, oligomers, and analogs (“shikonoids”) are an important group of phytochemicals, utilized since antiquity as components of dyes, traditional medicines, and food and cosmetics. They are now recognized for their potent anti-inflammatory and regulatory activity on a variety of molecular signaling pathways in humans. Since many Boraginaceae species are overly exploited or endangered, we developed a pilot-scale in vitro shikonoid production system using Plagiobothrys arizonicus (Gray) Greene ex A.Gray, the Arizona popcorn flower, native to the southwestern USA and the Sonoran floristic province in the Madrean region of Mexico. Aseptic root cultures were initiated from fresh leaf tissue and stimulated to continuously produce shikonoids in liquid shake cultures layered under paraffin oil from which the shikonoids were extracted and concentrated. The crude, red extracellular product from these rapidly expanding root masses was also fractionated by Centrifugal Counter-Current Chromatography (CCC) into its component shikonin derivatives. A number of these shikonoids profoundly up-regulated detoxification and antioxidant proteins (phase 2 enzymes) and inhibited inflammation in mammalian cell bioassay systems. This prototype shikonoid production methodology can be readily scaled to either batch or chemostat culture. Full article

Given the increasing demand for water and the need to reduce energy consumption, modern wastewater treatment systems should be characterised by high pollutant removal efficiency while consuming low resources. Hydrophytic wastewater treatment plants with vertical flow through a soil-plant bed (VFCW) are one solution that meets these requirements. The efficiency of these systems largely depends on the biological activity of the bed, of which free-living soil nematodes are an important component. The study presented in this paper aimed to assess the relationship between the quality of domestic wastewater flowing into VFCW beds and the abundance and trophic structure of soil nematode communities. The analysis was carried out on two real-world sites, where VFCW beds were the third stage of the plant bed system. Both treatment plants received only domestic wastewater. Statistical analysis showed no significant differences (p > 0.05) in the physicochemical composition of the wastewater flowing into the two treatment plants, indicating homogeneous system feed conditions. Nevertheless, canonical correspondence analysis (CCA) showed that the relationships between effluent parameters and the abundance of individual nematode trophic groups differed in each bed, suggesting the influence of local environmental and biocenotic conditions. In particular, bacterivorous nematodes—key to bed function—were shown to be sensitive to different sets of variables at the two sites despite similar effluent composition. These results confirm that the rhizosphere—a zone of intense interactions between plant roots, microorganisms, and soil microfauna—plays a critical role in shaping the biological activity of the bed. Nematodes, particularly bacterivorous nematodes, support the mineralisation of organic matter and nutrient cycling, resulting in increased efficiency of treatment processes. The stability of the total nematode abundance, irrespective of inflow conditions, demonstrates the bed biocenosis high ecological resilience to external disturbances. The study’s results highlight the importance of an ecosystem approach in designing and managing nature-based solutions (NBS) treatment plants, which can be a sustainable component of sustainable water and wastewater management. Full article

Background: Parkinson’s is among the fastest-growing neurological disorders, characterised by motor and non-motor symptoms that affect daily function and quality of life. With no cure, sustainable management strategies are essential. Self-management is a key component, enabling people with Parkinson’s to actively manage symptoms, treatment, and lifestyle, reflecting the wider long-term conditions (LTCs) approach to improving outcomes and well-being of people affected by these conditions. However, more than half of people living with Parkinson’s (PwP) report difficulties in engaging with self-management, often due to limited knowledge, confidence, or access to tailored interventions. Aims: This paper explores the theoretical underpinnings, key drivers, and current evidence base for self-management in Parkinson’s. It examines the relevance and limitations of applying LTC models to a progressive and highly individualized condition such as Parkinson’s. Despite global guideline recommendations, self-management support remains a significant unmet need. While self-management has the potential to improve adherence, symptom control, and activity levels, uncertainties remain about what constitutes effective, meaningful support. There is a need for a nuanced, person-centered approach embedded within integrated care systems. Conclusions: To date, self-management has not demonstrated sustained benefits for PwP, in part due to limitations in how current models are conceptualized and delivered. This paper highlights the challenges of existing approaches and proposes a new framework that enables and empowers PwP and their support networks to live well with Parkinson’s. Rooted in partnership, enablement, and co-production, the proposed model promotes the development of personalized toolkits of strategies that help individuals navigate and mitigate the challenges of life with Parkinson’s. This reframing has important implications for future research, clinical practice, and policy. Full article

This paper proposes a novel methodology based on two intelligent algorithms for regulating the power output of a multi-rotor turbine system. A proportional-integral plus second-order integral regulator is utilized to regulate the energy output of an induction generator. The designed controller is characterized by its ease of configuration, cost-effectiveness, high robustness, and ease of implementation. The controller’s parameters are tuned using a genetic algorithm (GA) and a rooted tree optimization (RTO) algorithm, with the objective of maximizing operational performance and power quality. In accordance with the proposed design methodology, the optimal values for the parameters of the designed strategy are attained through the implementation of integral time-weighted absolute error (ITAE). The present controller has been designed to deviate from conventional controllers, and a comparison will be made between the two using MATLAB under various operating conditions. The operational performance was evaluated in comparison to the conventional algorithm in terms of current quality, torque ripples, threshold overshoot, system parameter changes, and so forth. The experimental results, as measured by the tests conducted, demonstrated that the proposed RTO-based regulator exhibited enhancements of up to 89.88% (traditional control) and 51.92% (GA) in active power ripples, 68.19% (compared to traditional control) in ITAE, 51.91% (traditional control) in reactive power overshoot, and 0.5% (compared to GA) in active power response time. Conversely, the proposed GA-based regulator yielded a steady-state error value that was 96.55% superior to the traditional approach and 86.48% more accurate than the RTO algorithm. Moreover, the efficacy of the RTO-based control system was found to be considerably augmented under variable system parameters. Total harmonic distortion improvements of 69% were observed compared to traditional control methods, and 1% compared to the GA technique. The findings of this study offer significant insights into enhancing the robustness of multi-rotor turbine systems and improving power quality. Full article