Search Results (2,740)

The most prevalent growth of Candida cells is based on biofilm development, which causes the intensification of antifungal resistance against a large range of chemicals. Nanoparticles can be synthesized using green methods via various biological extracts and reducing agents to control Candida biofilms. This study aims to compare copper oxide nanoparticles (CuONPs) synthesized through chemical methods and those synthesized using Cinnamomum verum-based green methods against Candida infections and their biofilms isolated from Iraqi patients, with the potential to improve treatment outcomes. The physical and chemical properties of these nanoparticles were characterized using Fourier-transform infrared spectroscopy (FT-IR,) scanning electron microscopy (SEM), transmission electron microscopy (TEM), atomic force microscopy (AFM) and X-ray diffraction (XRD). Four strains of Candida were isolated and characterized from Iraqi patients in Tikrit Hospital and selected based on their ability to form biofilm on polystyrene microplates. The activity of green-synthesized CuONPs using cinnamon extract was compared with both undoped and doped (Fe, Sn) chemically synthesized CuONPs. Four pathogenic Candida strains (Candida glabrata, Candida lusitaniae, Candida albicans, and Candida tropicalis) were isolated from Iraqi patients, demonstrating high biofilm formation capabilities. Chemically and green-synthesized CuONPs from Cinnamomum verum showed comparable significant antiplanktonic and antibiofilm activities against all strains. Doped CuONPs with iron or tin demonstrated lower minimum inhibitory concentration (MIC) values, indicating stronger antibacterial activity, but exhibited weaker anti-adhesive properties compared to other nanoparticles. The antiadhesive activity revealed that C. albicans strain seems to produce the most resistant biofilms while C. glabrata strain seems to be more resistant towards the doped CuONPs. Moreover, C. tropicalis was the most sensitive to all the CuONPs. Remarkably, at a concentration of 100 µg/mL, all CuONPs were effective in eradicating preformed biofilms by 47–66%. The findings suggest that CuONPs could be effective in controlling biofilm formation by Candida species resistant to treatment in healthcare settings. Full article

This study evaluates the influence of fiber type, geometry, and interfacial behavior on the physical and mechanical performance of cementitious composites reinforced with recycled pulp from beverage cartons (RPBC), bamboo fiber (BF), and eucalyptus fiber (EF) as the sole reinforcing agents. The BF was rounded in shape and had the highest aspect ratio, while the ribbon-shaped EF exhibited the highest tensile strength index. The RPBC fibers were fibrillated and the shortest, with a ribbon shape. Flexural strength results showed that RPBCC achieved a maximum strength that was 47.6% higher than the control specimen (0% fiber), outperforming both BF- and EF-reinforced counterparts. This superior performance is attributed to the higher fibrillation level of the ribbon-shaped RPBC fibers, which promoted better fiber–matrix bonding. As the fiber content increased, the bulk density of EFC and BFC decreased linearly, while RPBC composites showed only a modest decrease in density. Porosity steadily increased in EFC and BFC, whereas a non-linear trend was observed in RPBCC, likely due to its unique morphology and fibrillation. Conversely, EFC exhibited significantly higher maximum fracture toughness (3600 J/m² at 10 wt.%) compared to PBFCC (1600 J/m² at 14 wt.%) and BFC (1400 J/m² at 14 wt.%). This enhancement is attributed to extensive fiber pullout mechanisms and increased energy absorption during crack propagation. Overall, all composite types demonstrated flexural strength values above 4 MPa, placing them in the Grade I category. Those reinforced with 10–14% RPBC exhibited strengths of 11–12 MPa, categorizing them as Grade II according to ASTM C1186-02. Full article

Curcumin is widely recognized for its various pharmacological properties, including antioxidant, anti-inflammatory, and anti-tumor activities. Nevertheless, the development of curcumin as a therapeutic agent is impeded by its limited oral bioavailability, which stems from its chemical instability, poor aqueous solubility, and rapid degradation. This study aimed to develop granule formulations incorporating poly(N-isopropylacrylamide)-grafted hyaluronic acid or HA-g-pNIPAM to enhance dissolution and protect curcumin from degradation. Three formulations were developed: F10 (HA-g-pNIPAM physically mixed with curcumin), F10 Encap (curcumin encapsulated within HA-g-pNIPAM), and F11 (curcumin granules without HA-g-pNIPAM). The stability results showed that F10 Encap effectively maintained curcumin content throughout the study period, retaining approximately 94% of its initial concentration by day 30, compared to 70% from F11 (p < 0.05) at 30 °C and 75% relative humidity. All dried curcumin granules exhibited excellent flowability, as determined by the angle of repose measurements. All three formulations exhibited a consistent particle size distribution across replicates, with a peak in the 150–180 μm size range. The sustained release observed for F10 Encap and F10 after the initial burst suggested that the HA-g-pNIPAM provided a controlled release mechanism, ensuring continuous curcumin dissolution over 240 min in gastric and intestinal conditions. These findings suggested that HA-g-pNIPAM improved dissolution and stability of curcumin. Full article

This review explores the emerging role of functionalized hydrogels in modulating the microbiome for therapeutic applications in tissue regeneration and infection control. The skin and gut microbiomes play crucial roles in maintaining tissue homeostasis, regulating immune responses, and influencing the healing process. Disruptions in microbial balance—such as those observed in chronic wounds, autoimmune conditions, or post-surgical environments—can impair regeneration and increase susceptibility to infection. Hydrogels, due to their tunable physical and chemical properties, serve as versatile platforms for delivering probiotics, prebiotics, antimicrobials, and immune-modulatory agents. The encapsulation of beneficial bacteria, such as Lactobacillus plantarum or Prevotella histicola, within hydrogels could enhance bacterial viability, targeted delivery, and immune tolerance. Additionally, hydrogels functionalized with silver nanoparticles, nitric oxide donors, and bacteriocins have demonstrated effective biofilm disruption and pathogen clearance. These systems also promote favorable immune responses, such as M2 macrophage polarization and the induction of regulatory T cells, which are essential for tissue repair. Innovative approaches, including 3D bioprinting, self-healing materials, and photothermal-responsive hydrogels, expand the clinical versatility of these systems. Full article

This paper proposes a low-latency and scalable architecture for Edge-Enabled Digital Twin networked control systems (E-DTNCS) aimed at multi-robot collision avoidance and remote control in dynamic and latency-sensitive environments. Traditional approaches, which rely on centralized cloud processing or direct sensor-to-controller communication, are inherently limited by excessive network latency, bandwidth bottlenecks, and a lack of predictive decision-making, thus constraining their effectiveness in real-time multi-agent systems. To overcome these limitations, we propose a novel framework that seamlessly integrates edge computing with digital twin (DT) technology. By performing localized preprocessing at the edge, the system extracts semantically rich features from raw sensor data streams, reducing the transmission overhead of the original data. This shift from raw data to feature-based communication significantly alleviates network congestion and enhances system responsiveness. The DT layer leverages these extracted features to maintain high-fidelity synchronization with physical robots and to execute predictive models for proactive collision avoidance. To empirically validate the framework, a real-world testbed was developed, and extensive experiments were conducted with multiple mobile robots. The results revealed a substantial reduction in collision rates when DT was deployed, and further improvements were observed with E-DTNCS integration due to significantly reduced latency. These findings confirm the system’s enhanced responsiveness and its effectiveness in handling real-time control tasks. The proposed framework demonstrates the potential of combining edge intelligence with DT-driven control in advancing the reliability, scalability, and real-time performance of multi-robot systems for industrial automation and mission-critical cyber-physical applications. Full article

Obesity is a growing global health concern with widespread impacts on physical, psychological, and social well-being. Clinically, it is a major driver of type 2 diabetes (T2D), cardiovascular disease (CVD), non-alcoholic fatty liver disease (NAFLD), and cancer, reducing life expectancy by 5–20 years and imposing a staggering economic burden of USD 2 trillion annually (2.8% of global GDP). Despite its significant health and socioeconomic impact, earlier obesity medications, such as fenfluramine, sibutramine, and orlistat, fell short of expectations due to limited effectiveness, serious side effects including valvular heart disease and gastrointestinal issues, and high rates of treatment discontinuation. The advent of glucagon-like peptide-1 (GLP-1) receptor agonists (e.g., semaglutide, tirzepatide) has revolutionized obesity management. These agents demonstrate unprecedented efficacy, achieving 15–25% mean weight loss in clinical trials, alongside reducing major adverse cardiovascular events by 20% and T2D incidence by 72%. Emerging therapies, including oral GLP-1 agonists and triple-receptor agonists (e.g., retatrutide), promise enhanced tolerability and muscle preservation, potentially bridging the efficacy gap with bariatric surgery. However, challenges persist. High costs, supply shortages, and unequal access pose significant barriers to the widespread implementation of obesity treatment, particularly in low-resource settings. Gastrointestinal side effects and long-term safety concerns require close monitoring, while weight regain after medication discontinuation emphasizes the need for ongoing adherence and lifestyle support. This review highlights the transformative potential of incretin-based therapies while advocating for policy reforms to address cost barriers, equitable access, and preventive strategies. Future research must prioritize long-term cardiovascular outcome trials and mitigate emerging risks, such as sarcopenia and joint degeneration. A multidisciplinary approach combining pharmacotherapy, behavioral interventions, and systemic policy changes is critical to curbing the obesity epidemic and its downstream consequences. Full article

This comprehensive review maps the fast-evolving landscape in which artificial intelligence (AI) and deep-learning (DL) techniques converge with the Internet of Things (IoT) to manage energy, comfort, and sustainability across smart environments. A PRISMA-guided search of four databases retrieved 1358 records; after applying inclusion criteria, 143 peer-reviewed studies published between January 2019 and April 2025 were analyzed. This review shows that AI-driven controllers—especially deep-reinforcement-learning agents—deliver median energy savings of 18–35% for HVAC and other major loads, consistently outperforming rule-based and model-predictive baselines. The evidence further reveals a rapid diversification of methods: graph-neural-network models now capture spatial interdependencies in dense sensor grids, federated-learning pilots address data-privacy constraints, and early integrations of large language models hint at natural-language analytics and control interfaces for heterogeneous IoT devices. Yet large-scale deployment remains hindered by fragmented and proprietary datasets, unresolved privacy and cybersecurity risks associated with continuous IoT telemetry, the growing carbon and compute footprints of ever-larger models, and poor interoperability among legacy equipment and modern edge nodes. The authors of researches therefore converges on several priorities: open, high-fidelity benchmarks that marry multivariate IoT sensor data with standardized metadata and occupant feedback; energy-aware, edge-optimized architectures that lower latency and power draw; privacy-centric learning frameworks that satisfy tightening regulations; hybrid physics-informed and explainable models that shorten commissioning time; and digital-twin platforms enriched by language-model reasoning to translate raw telemetry into actionable insights for facility managers and end users. Addressing these gaps will be pivotal to transforming isolated pilots into ubiquitous, trustworthy, and human-centered IoT ecosystems capable of delivering measurable gains in efficiency, resilience, and occupant wellbeing at scale. Full article

The griffon vulture (Gyps fulvus fulvus) is a scavenger species that plays a vital ecological role in carrion removal. Successful survival and reproduction in captive and wildlife conditions require optimal physical status and plumage integrity. Nutritional and environmental factors, systemic diseases, and various etiological agents can influence feather alterations. Although frequently documented in captive psittacine species, feather abnormalities are extremely rare in wild birds. Since 2020, two free-living griffon vultures in northeastern Italy have been found in poor physical condition, unable to fly due to partial feather loss and malformation of remiges and rectrices. Histopathologic examination of follicles and peri-follicular tissue revealed atrophy, keratin replacement, vasculitis, and calamus dystrophy with lymphohistiocytic perivasculitis. Immunohistochemical and ultrastructural analysis identified the presence of virus-like particles in epithelial and inflammatory cells. Although virome analysis did not confirm the presence of this virus in pooled affected samples, this study provides the first report of an emerging plumage disorder in free-ranging griffon vultures, which requires further characterization. Full article

Pancreatic cancer is among the deadliest malignancies, with limited treatment options and poor prognosis. Novel strategies are therefore urgently needed. Sotorasib, a KRAS G12C-specific inhibitor, offers targeted treatment for a small subset of patients with this mutation. Electrochemotherapy (ECT), which enhances the cytotoxicity of chemotherapeutic agents through electroporation-induced membrane permeabilization, has shown promise in various tumor types, including deep-seated malignancies such as pancreatic cancer. Combining ECT with sotorasib may potentiate antitumor effects in KRAS G12C-mutated pancreatic cancer; however, preclinical data on such combinations are lacking. This proof-of-concept study evaluated the cytotoxic effects of ECT using bleomycin (BLM) or cisplatin (CDDP) in combination with sotorasib in KRAS G12C-mutated MIA PaCa-2 and KRAS G12D-mutated PANC-1 pancreatic cancer cell lines. ECT alone significantly reduced cell viability, particularly in MIA PaCa-2 cells, where electric pulses induced approximately 75% cell death. Combining ECT with sotorasib resulted in an additive effect on KRAS G12C-mutated MIA PaCa-2 cells, though no synergy was observed, likely due to the high intrinsic sensitivity to electric pulses. These results support the potential of combining physical and molecular therapies in a subset of pancreatic cancer patients and lay the groundwork for further in vivo studies to optimize treatment parameters and explore clinical translatability. Full article

Wildfires increasingly threaten human life, ecosystems, and infrastructure, with events like the 2025 Palisades and Eaton fires in Los Angeles County underscoring the urgent need for more advanced prediction frameworks. Existing physics-based and deep-learning models struggle to capture dynamic wildfire spread across both 2D and 3D domains, especially when incorporating real-time, multimodal geospatial data. This paper explores how generative artificial intelligence (AI) models—such as GANs, VAEs, and transformers—can serve as transformative tools for wildfire prediction and simulation. These models offer superior capabilities in managing uncertainty, integrating multimodal inputs, and generating realistic, scalable wildfire scenarios. We adopt a new paradigm that leverages large language models (LLMs) for literature synthesis, classification, and knowledge extraction, conducting a systematic review of recent studies applying generative AI to fire prediction and monitoring. We highlight how generative approaches uniquely address challenges faced by traditional simulation and deep-learning methods. Finally, we outline five key future directions for generative AI in wildfire management, including unified multimodal modeling of 2D and 3D dynamics, agentic AI systems and chatbots for decision intelligence, and real-time scenario generation on mobile devices, along with a discussion of critical challenges. Our findings advocate for a paradigm shift toward multimodal generative frameworks to support proactive, data-informed wildfire response. Full article

Aquilaria sinensis (Lour.) Gilg, the exclusive botanical source of Chinese agarwood, holds significant medicinal value. This study investigated the agarwood-inducing potential of a Fusarium strain obtained through prior isolation work. Through integrated morphological characterization and molecular phylogenetic analysis, the strain was conclusively identified as Fusarium equiseti. GC-MS analysis revealed that fungal inoculation induced the synthesis of characteristic sesquiterpenes and aromatic compounds consistent with natural agarwood profiles. Quantitative determination demonstrated progressive accumulation of agarotetrol, a key quality marker, reaching 0.034%, 0.039%, and 0.038% at 2, 4, and 6 months post-inoculation, respectively—significantly exceeding levels from physical wounding (p < 0.05) and PDA control treatments. Histological examination showed characteristic yellow-brown oleoresin deposits concentrated in the inner phloem, mirroring the anatomical features of wild-type agarwood. Critical quality parameters measured in December-harvested samples included ethanol extractives (17.69%), chromone derivatives 2-[2-(4-methoxyphenyl) ethyl] chromone, and 2-(2-phenylethyl) chromone (2.13%), all meeting or surpassing the specifications outlined in the National Standard for Agarwood Classification (LY/T 3223-2020). These comprehensive findings establish F. equiseti as a promising microbial agent for sustainable agarwood production in A. sinensis plantations. Full article

In this paper, mussel shells were used to produce chitin, chitosan, and calcium acetate using chemical processes, searching for an alternative environmentally friendly biopolymer and calcium source. Mussel shells were treated with acetic acid as a demineralizing agent, resulting in separate solid fractions and calcium solution. The solid was further purified to produce chitin by deproteinization and decolorization processes, and then the deacetylation process was used to obtain chitosan. The calcium solution was evaporated to produce calcium acetate powder. The yields of extracted chitin, chitosan, and calcium acetate from 100 g of mussel shells were 2.98, 2.70, and 165.23 g, respectively. The prepared chitin, chitosan, and calcium acetate were analyzed by Fourier transform infrared (FTIR) spectrophotometry, X-ray diffraction (XRD), thermogravimetric analysis (TGA), and scanning electron microscope (SEM) to confirm the chemical and physical properties. The analysis results of chitin and chitosan revealed the similarity to chitosan derived from crustaceans and insects in terms of functional group, structure and morphologies. The prepared calcium acetate shows FTIR and XRD data corresponding to calcium acetate monohydrate (Ca(CH₃COO)₂·H₂O) similar to synthesized calcium acetate in previous research. In addition, the mineral contents of calcium acetate identified by X-ray fluorescence (XRF) analysis exhibit 97.8% CaO with non-toxic impurities. This work demonstrated the potential of the production process of chitin, chitosan, and calcium acetate for the development of a sustainable industrial process with competitive functional performance against the commercial chitin and chitosan production process using crustacean shells and supported the implementation of a circular economy. Full article

We propose a tri-fold learning algorithm, called Neuroevolution of Hybrid Neural Networks in a Robotic Agent (acronym in Spanish, NRNH-AR), based on deep reinforcement learning (DRL), with self-supervised learning (SSL) and unsupervised learning (USL) steps, specifically designed to be implemented in a small autonomous navigation robot capable of operating in constrained physical environments. The NRNH-AR algorithm is designed for a small physical robotic agent with limited resources. The proposed algorithm was evaluated in four critical aspects: computational cost, learning stability, required memory size, and operation speed. The results obtained show that the performance of NRNH-AR is within the ranges of the Deep Q Network (DQN), Deep Deterministic Policy Gradient (DDPG), and Twin Delayed Deep Deterministic Policy Gradient (TD3). The proposed algorithm comprises three types of learning algorithms: SSL, USL, and DRL. Thanks to the series of learning algorithms, the proposed algorithm optimizes the use of resources and demonstrates adaptability in dynamic environments, a crucial aspect of navigation robotics. By integrating computer vision techniques based on a Convolutional Neuronal Network (CNN), the algorithm enhances its abilities to understand visual observations of the environment rapidly and detect a specific object, avoiding obstacles. Full article

Lost circulation is a major challenge in oil and gas drilling operations, severely restricting drilling efficiency and compromising operational safety. Conventional bridging and plugging materials rely on precise particle-to-fracture size matching, resulting in low success rates. Self-healing gels penetrate loss zones as discrete particles that progressively swell, accumulate, and self-repair in integrated gel masses to effectively seal fracture networks. Self-healing gels effectively overcome the shortcomings of traditional bridging agents including poor adaptability to fractures, uncontrollable gel formation of conventional downhole crosslinking gels, and the low strength of conventional pre-crosslinked gels. This work employs stearyl methacrylate (SMA) as a hydrophobic monomer, acrylamide (AM) and acrylic acid (AA) as hydrophilic monomers, and graphene oxide (GO) as an inorganic dopant to develop a GO-based self-healing organic–inorganic hybrid plugging material (SG gel). The results demonstrate that the incorporation of GO significantly enhances the material’s mechanical and rheological properties, with the SG-1.5 gel exhibiting a rheological strength of 3750 Pa and a tensile fracture stress of 27.1 kPa. GO enhances the crosslinking density of the gel network through physical crosslinking interactions, thereby improving thermal stability and reducing the swelling ratio of the gel. Under conditions of 120 °C and 6 MPa, SG-1.5 gel demonstrated a fluid loss volume of only 34.6 mL in 60–80-mesh sand bed tests. This gel achieves self-healing within fractures through dynamic hydrophobic associations and GO-enabled physical crosslinking interactions, forming a compact plugging layer. It provides an efficient solution for lost circulation control in drilling fluids. Full article

Acoustic coupling agents serve as critical interfacial materials connecting piezoelectric transducers with microfluidic chips in acoustofluidic systems. Their performance directly impacts acoustic wave transmission efficiency, device reusability, and reliability in biomedical applications. Considering the rapidly growing body of research in the field of acoustic microfluidics, this review aims to serve as an all-in-one reference on the role of acoustic coupling agents and relevant considerations pertinent to acoustofluidic devices for anyone working in or seeking to enter the field of disposable acoustofluidic devices. To this end, this review seeks to summarize and categorize key aspects of acoustic couplants in the implementation of acoustofluidic devices by examining their underlying physical mechanisms, material classifications, and core applications of coupling agents in acoustofluidics. Gel-based coupling agents are particularly favored for their long-term stability, high coupling efficiency, and ease of preparation, making them integral to acoustic flow control applications. In practice, coupling agents facilitate microparticle trapping, droplet manipulation, and biosample sorting through acoustic impedance matching and wave mode conversion (e.g., Rayleigh-to-Lamb waves). Their thickness and acoustic properties (sound velocity, attenuation coefficient) further modulate sound field distribution to optimize acoustic radiation forces and thermal effects. However, challenges remain regarding stability (evaporation, thermal degradation) and chip compatibility. Further aspects of research into gel-based agents requiring attention include multilayer coupled designs, dynamic thickness control, and enhancing biocompatibility to advance acoustofluidic technologies in point-of-care diagnostics and high-throughput analysis. Full article