Search Results (529)

The rapid rise of antimicrobial resistance (AMR) has created an urgent need for innovative therapeutic strategies beyond conventional antibiotics. Smart nano-antibiotics have emerged as advanced antimicrobial systems capable of improving drug delivery, enhancing pathogen targeting, overcoming biofilm-associated resistance, and reducing systemic toxicity. This review discusses recent progress in stimuli-responsive nanoplatforms, including pH-responsive, enzyme-responsive, temperature-sensitive, and redox-activated systems for precision antimicrobial therapy. The role of artificial intelligence in nanomaterial design, toxicity prediction, drug release optimization, and personalized treatment development is also critically examined. Furthermore, the review highlights targeted antimicrobial delivery, multifunctional nano-drug combination systems, biosensor integration, and autonomous AI-driven therapeutic platforms for combating multidrug-resistant infections. Current challenges related to toxicity, regulatory limitations, scalability, and AI data reliability are discussed alongside emerging clinical and industrial developments. Smart nano-antibiotics represent a promising next-generation approach for improving precision antimicrobial therapy and addressing the growing global burden of antimicrobial resistance. Full article

Salmonella remains one of the most critical zoonotic pathogens in the poultry sector, linked to animal disease, foodborne illness, and the global crisis of antimicrobial resistance (AMR). Poultry acts as a major reservoir, enabling Salmonella transmission from hatchery to retail products through horizontal, vertical, and environmental routes. Despite the use of biosecurity, vaccination, antibiotics, and chemical decontamination, effective and sustainable control across the poultry value chain remains difficult, particularly in the face of rising multidrug-resistant strains and growing consumer concerns over chemical residues. Bacteriophages (phages), viruses that selectively infect and lyse bacteria, have emerged as a promising biological alternative for Salmonella control. Although many studies have reported the effectiveness of phages against bacterial species, including Salmonella, in the poultry industry, reports on their full potential to combat antimicrobial-resistant Salmonella across the entire poultry value chain remain limited. Therefore, this review synthesizes current evidence on the application of phages throughout the poultry value chain, including on-farm interventions, processing plant decontamination, and food packaging and storage. Findings from the reviewed articles indicate over a 90% reduction in Salmonella spp. in poultry farms and post-harvest meat, along with lower mortality in phage-treated groups compared to untreated groups; however, these outcomes depend on several factors (e.g., phage strains, concentrations, application methods, and environmental conditions). Laboratory, pilot, and field studies consistently demonstrate that phage preparations, especially when formulated as cocktails or combined with complementary interventions, can achieve substantial reductions in Salmonella, including antibiotic-resistant serovars, in live birds, eggs, poultry environments, and meat products. Unlike antibiotics and chemical sanitizers, phages act with high specificity, preserving beneficial microbiota and maintaining the sensory and nutritional quality of poultry products. Their safety has been supported by toxicological and genomic assessments, and several phage-based products have obtained regulatory approval, including Generally Recognized as Safe (GRAS) status for food applications in the United States. By integrating efficacy, safety, regulatory, and practical deployment data, this review highlights bacteriophages as a scientifically validated and One Health–aligned tool capable of reducing Salmonella transmission from farm to fork across the poultry value chain, thereby laying the foundation for their future adoption in the poultry industry. Phage-based interventions offer a sustainable pathway to enhance food safety, limit antimicrobial resistance (AMR) dissemination, and strengthen consumer confidence in poultry products. However, the major limitation is the emergence of phage-resistant bacterial strains, as well as the potential involvement of some phages in the transfer of resistance and virulence genes, which could raise public concern. Nevertheless, the use of phage cocktails and whole-genome sequencing, involving tools such as ResFinder and virulence finder, can facilitate the selection of safe phages for application. Full article

Microbial resistance to conventional antimicrobials is a growing public health challenge, driving the search for effective and sustainable alternatives. Among emerging strategies, the combination of silver nanoparticles (AgNPs), recognized for their potent antimicrobial action, with biosurfactants, natural, biodegradable compounds capable of interacting with microbial cell membranes and promoting their stabilization stands out. In this context, the aim of this study was to produce a biosurfactant by Candida glabrata UCP 1002 from agroindustrial residues, reducing costs and environmental impacts. The compound exhibited a surface tension of 29 mN/m, a critical micellar concentration of 0.3%, and a yield of 9 g/L; furthermore, it demonstrated stability across wide ranges of temperature, pH, and salinity. The AgNPs were synthesized using the biosurfactant as a stabilizing agent and ascorbic acid as a reducing agent, resulting in stable particles. In antimicrobial assays, the formulation inhibited Gram-positive microorganisms, Gram-negative microorganisms, and fungi. The best results were obtained against Pseudomonas aeruginosa (26.63%) and Candida albicans (28.11%), followed by Staphylococcus aureus (17.58%), Enterobacter sp. (14.42%), and Escherichia coli (13.68%). Although less effective than commercial antibiotics such as streptomycin and moxifloxacin, it showed potential as a complementary alternative in combating multidrug-resistant pathogens. Cytotoxicity assays revealed low toxicity toward normal cells (28.42% inhibition in Vero CCL-81) and minimal activity against tumor cells. The results demonstrate that the BS-AgNPs association combines relevant antimicrobial activity with environmental safety and biocompatibility, establishing itself as a promising and sustainable approach for application in health, industry, and the environment, with potential for scale-up production from low-cost raw materials. Full article

The rapid emergence of antimicrobial resistance has intensified the need for advanced therapeutic platforms capable of improving the efficacy, stability, and targeted delivery of antimicrobial agents. Electrospun nanofibers have emerged as highly promising materials for biomedical applications due to their large surface area, high porosity, tunable morphology, and ability to incorporate a broad range of bioactive compounds. This review provides a comprehensive overview of the design, fabrication, and biomedical applications of electrospun bioactive nanofibers functionalized with antimicrobial drugs. It presents the main nanofiber fabrication techniques, with particular emphasis on electrospinning and the influence of solution, process, and environmental parameters on fiber morphology and drug-loading efficiency. Natural, synthetic, and hybrid polymer systems commonly employed in electrospun antimicrobial nanofibers are analyzed in relation to their physicochemical properties, biocompatibility, and therapeutic performance. In addition, the review highlights different drug incorporation strategies, including encapsulation, immobilization, and surface coating, as well as the mechanisms of action of antimicrobial agents. Recent advances in nanotechnology-based antimicrobial systems and their role in overcoming analytical, biopharmaceutical, and drug-delivery limitations are also examined. Furthermore, the review addresses current challenges related to scalability, reproducibility, stability, and clinical translation of electrospun nanofibers. Finally, future perspectives focusing on multifunctional, stimuli-responsive, and personalized antimicrobial nanofiber systems are discussed as promising directions for combating bacterial infections and reducing the global burden of antimicrobial resistance. Full article

Pseudomonas aeruginosa, an opportunistic pathogen, is a major threat to hospital infection control and global public health due to its strong environmental adaptability, complex virulence systems, efficient biofilm formation capability, and widespread multidrug resistance. Traditional single-target antibiotics are often inadequate for clinical treatment. The research into Plant-Derived Bioactive Compounds for combating P. aeruginosa infections is reviewed, highlighting their advantages (many of which are extensively studied in Traditional Chinese Medicine) over conventional antibiotics. The antimicrobial mechanisms of these compounds include the inhibition of bacterial quorum sensing (QS) systems to suppress virulence factor expression rather than direct anti-bactericidal effects, delaying the development of resistance. The abundant natural medicinal plants and their diverse chemical structures provide ample material for active compound screening to identify unique chemical compositions with specific binding to pathogen targets. Plant-Derived Bioactive Compounds exhibit excellent safety profiles, targeting bacterial-specific pathways or host immune regulation, resulting in minimal off-target toxicity. Plant-Derived Bioactive Compounds exert anti-P. aeruginosa effects via inhibition of QS systems to reduce pathogenicity by disrupting intercellular signaling, suppressing biofilm formation/maturity to overcome biofilm-associated resistance, directly interacting with bacterial structure. Plant-Derived Bioactive Compounds are promising treatments for drug-resistant P. aeruginosa infections, providing lead compounds for novel anti-infective drug development. Full article

Antimicrobial resistance (AMR) is a critical global public health crisis that is being exacerbated by widespread misuse of antibiotics and rapid bacterial adaptation. The progressive decrease in antibiotic efficacy is also compounded by a stagnating drug-discovery pipeline and underscores the urgent need for innovative and sustainable antimicrobial strategies. This review systematically delineates the core molecular mechanisms driving bacterial resistance, including enzymatic drug inactivation, target modification, reduced membrane permeability, and multidrug efflux pump overexpression. Furthermore, the potential of (flavonoids, alkaloids, and phenolics) as structurally diverse plant-derived compounds with multi-target activity is comprehensively assessed. The features of multi-target activity make them promising dual-function agents that may be capable of both direct antimicrobial action and resistance modulation. These natural products have distinct mechanisms from conventional antibiotics, low propensity for resistance, and versatile bioactivity as biofilm disruptors, enzyme inhibitors, and efflux pump blockers. Numerous phytochemicals exhibit potent synergistic effects with available antibiotics by effectively resensitizing resistant pathogens and extending the clinical utility of current antimicrobials. By integrating mechanistic understanding with translational potential, this review discusses phytochemicals as a sustainable resource for developing next-generation antimicrobial strategies as a complementary approach to revitalize therapeutic pipelines and combat multidrug-resistant infections. Full article

The growing concern over greenhouse gas emissions has prompted the need for efficient carbon dioxide (CO₂) capture technologies. This study focuses on simulating CO₂ adsorption using a zinc-based metal–organic framework (Zn-MOF-5). The primary aim is to develop and refine a robust MATLAB-based approach for equilibrium and kinetic modelling using the Linear Driving Force (LDF) model and Langmuir isotherm, capable of accurately predicting CO₂ adsorption performance under varying operational conditions. By employing advanced computational methods, this research seeks to streamline the process design and enhance the feasibility of sustainable CO₂ capture solutions. Excel was used for statistical analysis and validation, while MATLAB R2025a was utilised for equilibrium and kinetic modelling using the LDF model and the Langmuir isotherm. The independent effects of temperature, pressure, and flow rate were evaluated using the variable effect method. The study found a significant negative association between temperature and CO₂ uptake, consistent with the exothermic nature of the adsorption process. Pressure had a significant impact on adsorption, whereas flow rate had little effect within the investigated range. The simulated CO₂ uptake (21.196 mmol/g) closely matched the experimental data (21.07 mmol/g) with a 0.59% variance, validating the model’s trustworthiness. The research shows that Zn-MOF-5 has a strong adsorption potential and that simulation tools can significantly minimise experimental costs and time. Furthermore, it underscores the potential of simulation tools to significantly reduce experimental costs and time, paving the way for more efficient and effective carbon capture solutions. This initiative not only contributes to optimising process design but also promotes sustainable practices in addressing global CO₂ emissions. By contributing to process optimisation, this study aligns with the United Nations Sustainable Development Goal (SDG) 13: Climate Action, which emphasises the urgent need for innovative solutions to combat climate change and its impacts. Furthermore, it promotes sustainable practices to address global CO₂ emissions, thereby supporting broader efforts for environmental sustainability. Full article

The term bacterial biofilm refers to a complex community of microorganisms embedded within a self-produced matrix of extracellular polymeric substances. This structural organization creates an environment that, when present in an infectious context within a living organism, limits the effectiveness of conventional antibiotic therapy. Consequently, such conditions substantially promote the development of antibiotic resistance. The decline in the discovery of novel antibiotic agents, coupled with a concurrent increase in the prevalence of multidrug-resistant microorganisms, has intensified the search for alternative strategies to combat such infections. At the same time, advances in nanoscience have stimulated substantial research into the use of micro/nanorobots for the eradication of bacterial biofilms. These devices, engineered at the micro- to nanoscale, are capable of targeted intervention in otherwise inaccessible sites. However, the development of such “microscopic therapeutic agents” is still at an early stage. To date, the vast majority of available data has been derived from in vitro studies, while evidence regarding their feasibility, safety, and therapeutic effects in living organisms remains limited. This review discusses their antimicrobial mechanisms and critically evaluates the current evidence concerning their in vivo applications. Full article

The target price for naval equipment orders is driven by the coupling of multidimensional technical and economic factors, exhibiting typical characteristics such as high dimensionality, strong nonlinearity, multicollinearity, and small-sample fluctuations. Traditional cost estimation methods struggle to achieve high-precision fitting and interpretable decision support. To address these issues, this paper constructs an integrated prediction model that combines Boruta–Lasso two-stage feature selection, grid search-optimized CatBoost, and SHAP interpretability analysis. First, the Boruta algorithm is used for rough screening of feature significance, then Lasso regression is applied for sparse fine screening, effectively eliminating redundant features and significantly mitigating multicollinearity; grid search and five-fold repeated cross-validation are employed to optimize CatBoost hyperparameters, while 10 repeated experiments with random seeds are conducted to verify model generalization robustness. SHAP is used to quantify the marginal contribution of features, revealing nonlinear associations and statistical response transition points between core features and price. This study is based on 33 publicly available real data from main combat vessels, from which 198 modeling samples were generated through interpolation-based small-sample data augmentation. The interpolated samples were only used for data augmentation and were not considered independent empirical samples. All core conclusions were validated on the 33 original real samples, and there are no missing values in the dataset. Experimental results show that the proposed model achieved the best individual results on the test set, with a coefficient of determination of R² = 0.8949, root mean square error RMSE = 0.0554, and mean absolute error MAE = 0.0476. Across 10 repeated robustness experiments, the average results were R² = 0.8828, RMSE = 0.0586, and MAE = 0.0529, with overall performance better than comparison models such as XGBoost, random forest, and standard CatBoost. Ablation experiments validated the effectiveness of the two-stage Boruta–Lasso selection strategy in improving model accuracy and stability. SHAP attribution analysis shows that full-load displacement, number of vertical missile launch cells, number of phased array radars, and combat capability are core features highly correlated with price, all showing significant nonlinear positive correlations and clear statistical response transition points. The dataset in this study has no missing values, is entirely constructed based on publicly traceable data, and does not include confidential information such as internal shipyard costs. The findings reflect statistical associations rather than causal effects. However, the sample size and ship-type coverage are limited, so the model’s applicability is somewhat constrained, and its generalization ability needs to be further verified on larger-scale, multi-ship-type independent datasets. This model combines high prediction accuracy, strong robustness, and good interpretability, providing reliable technical support for ship equipment procurement pricing demonstration, full lifecycle cost management, and scientific procurement decision-making. Full article

Background: Special Forces Operators often carry out missions in conditions where the use of motor vehicles is impossible. Additional external load across areas with variable inclination may reduce walking efficiency and consequently limit the combat capability of soldiers. The aim of the study was to determine how ground inclination affects the spatiotemporal structure of gait in Special Forces Operators (SFO) with different military loads. Methods: The study included 50 operators from Polish special forces units. Measurements of walking were performed using the h/p/cosmos Gaitway 1D + 3D treadmill. Tests were conducted at four uphill inclination levels: 0%, 5%, 10%, and 15%. Each participant completed trials both without external load and with a 27 kg load (helmet, tactical vest, and backpack). Statistical analyses were performed using the Friedman test, the Durbin–Conover post hoc test, and linear mixed models (LMM) to assess interaction effects. The Robinson Symmetry Index (SI) was calculated to assess asymmetry between the dominant and non-dominant limbs. Results: Increasing inclination caused statistically significant changes in the spatiotemporal structure of gait. The greatest modifications were observed at 10–15% inclinations, particularly under the maximum load of 27 kg. A significant shortening of step length and gait cycle time was noted, while cadence showed a slight upward trend, especially at a 15% inclination with the highest load. Step width remained stable. Conclusions: Ground inclination, especially when combined with the additional mass of military equipment, significantly affects the locomotion of Special Forces Operators. The stable SI values and consistent step width indicate a high level of gait stability and effective adaptive mechanisms. However, the extent of spatiotemporal modifications observed at inclinations of 10–15% with a 27 kg load may increase the risk of overuse injuries among operators. Full article

Addressing the high-dimensional, strongly constrained multi-objective optimization problem of air–ground collaborative jamming scheduling in complex terrain, existing methods are often limited by incomplete modeling and low optimization efficiency in discrete feasible regions. This paper proposes a Terrain-Aware Multi-Scale Discrete Operator (TA-MSDO). A joint optimization model integrating discrete terrain characteristics and practical combat constraints is first constructed. Then, by leveraging the topological adjacency of terrain units, TA-MSDO employs a block-level crossover and a multi-scale mutation mechanism, replacing traditional continuous genetic operations to enable efficient and directional exploration of the discrete feasible region. Integrating TA-MSDO into the NSGA-III framework yields the enhanced ENSGA3 algorithm. Experimental results in a typical hilly terrain scenario demonstrate that ENSGA3 achieves a statistically significant performance improvement over the decomposition-based MOEA/D algorithm in terms of maximum achievable suppression effectiveness and hypervolume. As a comprehensive metric integrating convergence and Pareto frontier coverage, hypervolume further verifies the superior comprehensive optimization capability of the proposed algorithm. Meanwhile, compared with other classic mainstream multi-objective optimization algorithms including NSGA-II, standard NSGA-III and SPEA2, the proposed algorithm exhibits clear positive advantages in the upper bound of suppression effectiveness for elite solutions and operational stability across random initializations, with a favorable trend in Pareto frontier coverage for multi-objective collaborative optimization. This work provides an effective solution for jamming resource scheduling in complex battlefield environments. Full article

Nitric oxide (NO) is a gaseous biocompatible radical molecule with demonstrated biomedical and antimicrobial benefits. Developing adaptable, long-lasting delivery systems for NO has become an essential goal for both combating resistant bacterial growth and providing sustained medical benefits. Silsesquioxane (SQ)-based organogels were chosen and synthesized as robust, tunable NO-release platforms. These highly stable SQ gel frameworks, composed of silicon–oxygen backbones with variable R groups, exhibited high porosity and surface area and offered chemical versatility, enabling control over NO loading and release. 3-Mercaptopropyl groups were utilized as sulfur-based NO-releasing substituents (-RSNOs), with additional R groups capable of altering accessibility to RSNO sites through hydrophobicity and steric hindrance. The NO release profile, rate, and duration of the functionalized gels were also tailored by adjusting the number of RSNO sites in the elastomeric system, thereby enabling a customizable release profile. This combination of NO-releasing silsesquioxanes with silicone elastomers yields composite materials that are integratable into biomedical applications, offering NO release up to 40 days within modeled physiological conditions in PBS buffer. Full article

Background/Objectives: Cyanobacteria represent a diverse group of microorganisms capable of synthesizing a broad array of biologically active metabolites. Some of these compounds, believed to contribute to the ecological and evolutionary success of cyanobacteria, are increasingly being investigated for potential biomedical and biotechnological applications. They also hold promise in combating the growing threat of antimicrobial resistance (AMR). This screening study aimed to identify Baltic cyanobacterial strains with the potential to produce antibacterial compounds active against streptococci and mycobacteria, as well as quorum sensing inhibitors. Methods/Results: Extracts from forty-four cyanobacterial strains were tested using a broth microdilution assay. The most pronounced activity was observed for extracts derived from two Pseudanabaenaceae strains (KUCC C3 and C4), two Anabaena spp. strains (CCNP 1405 and CCNP 1406), and Aphanizomenon sp. KUCC C1. Inhibition of quorum sensing was the most frequently detected activity, with 30% of the tested extracts inhibiting violacein production in Chromobacterium violaceum ATCC 12472. Growth inhibition of Gram-positive bacteria was less common: 16% of cyanobacterial strains inhibited Streptococcus pyogenes ATCC 12344, and 11% inhibited Mycobacterium smegmatis ATCC 14468. Bioassay-guided fractionation of Aphanizomenon sp. KUCC C1, followed by LC–MS/MS analysis, revealed the presence of glycerolipids and glycolipids, including diacylglycerols (DAGs) and galactosyldiacylglycerols (MGDGs and DGDGs), as major constituents of fractions exhibiting quorum quenching activity. Conclusions: These findings highlight the potential of Baltic cyanobacteria as a source of natural compounds capable of disrupting bacterial communication and growth, offering prospects for the development of novel antimicrobial and anti-virulence agents. Full article

Deepfakes and adjacent synthetic-media capabilities have become a systemic challenge for information integrity, security, and digital trust. Countermeasures now span passive detection methods that infer manipulation from content traces, active provenance systems that cryptographically bind metadata to media, and watermarking approaches that embed detectable signals into content or generative processes. This review presents a rigorous synthesis of tools and technologies to combat deepfakes across modalities (image, video, audio, and selected multimodal settings), drawing primarily from the peer-reviewed literature, standardized benchmarks, and official technical specifications and reports. The review analyzes detection methods, provenance and authentication technologies, with emphasis on cryptographic manifests and threat models, watermarking and content provenance, including diffusion-era watermarking and industrial deployments, adversarial robustness and attacker adaptation, datasets and benchmarks, evaluation metrics across tasks, and deployment and scalability constraints. A dedicated section addresses legal, ethical, and policy issues, focusing on emerging transparency obligations and platform governance. The review finds that no single countermeasure is sufficient in realistic adversarial settings. The strongest practical approach is a layered defense that combines provenance, watermarking, content-based detection, and human oversight. The study concludes with limitations of the current evidence base and prioritized research directions to improve generalization, interoperability, and trustworthy user experiences. Full article

Background: The global rise in multidrug-resistant (MDR) Gram-negative bacteria (GNB) poses an urgent challenge for infection control and antibiotic stewardship. Among these, Klebsiella pneumoniae is a major cause of hospital-acquired infections and is listed as a critical priority pathogen by the World Health Organization. Peru reports an exceptionally high prevalence of MDR K. pneumoniae, underscoring the need for innovative antimicrobial approaches. Methods: Here, we describe the isolation and characterization of lytic Klebsiella bacteriophage from sewage samples collected from the Huatanay River (Cusco, Peru) in 2023. Phages were isolated using the reference strain MDR K. pneumoniae ATCC BAA-2814. Then, they were screened against 50 clinical MDR K. pneumoniae strains. Results: The phage H33IIK demonstrated effective antibacterial capability, showing strict host specificity for K. pneumoniae, thermal stability, moderate pH tolerance, and high burst size. Whole-genome sequencing analysis classified it within the class Caudoviricetes, family Ackermannviridae, and genus Taipeivirus. The genomic analysis confirmed the absence of lysogeny-related, antimicrobial resistance, and virulence genes, supporting its suitability and safety for potential biotechnological applications. Conclusions: These findings highlight phage H33IIK as a lytic agent effective against MDR K. pneumoniae. It could contribute to the development of phage-based approaches to combat MDR GNB. Full article