Search Results (973)

There is a growing need to understand ciprofloxacin (CIP) resistance in less prevalent Salmonella serovars like Salmonella Dublin, which causes life-threatening conditions in both humans and animals. This study investigated potential factors contributing to CIP-resistance in a Salmonella Dublin isolate. The isolate was detected from an initial screening of 17 biobanked Salmonella isolates using the Kirby-Bauer disk diffusion (KBDF) method. The minimum inhibitory concentration (MIC) values of the identified CIP-resistant Salmonella Dublin isolate and a CIP-susceptible isolate of the same serovar were also obtained using the broth-dilution (BD) method. The two candidates were then challenged in 1/4 of their respective BD MICs for gene expression analysis, focusing on the acrAB efflux genes and the regulator genes marA, ramA, and soxS. Genomes of the isolates were also sequenced using the Oxford Nanopore sequencing platform, and then analyzed for mutations, antimicrobial resistance genes, and plasmids using ABRicate. The SWISS-MODEL server was used for protein modeling and comparison. For our results, the MIC values (KBDF; BD) for the CIP-resistant and CIP-susceptible Salmonella Dublin isolates were (1.5 μg/mL; 1.95 μg/mL) and (<0.125 μg/mL; 0.03 μg/mL), respectively. Both isolates had genes (mdtK, emrR, emrA, and emrB) notable for fluoroquinolone resistance, with the CIP-susceptible isolate also carrying the IncFII(S) plasmid. Expression of the acrA, acrB, ramA, and soxS genes was markedly higher in the CIP-resistant isolate, which also harbored an Asparagine (N) to Serine (S) mutation at position 868 in the GyrA protein. This mutation, however, caused no significant structural change. Despite reporting on a single CIP-resistant Salmonella Dublin isolate, our result highlights the potentially significant role of an efficient efflux system in contributing to CIP resistance in this isolate, even when no impactful mutations were identified. Full article

Water contamination with pharmaceuticals is a global challenge that affects both aquatic and human life. The presence of these pharmaceuticals has increased in recent years due to their high demand. In this study, varying compositions of Cu-NiO nanocomposites were synthesized using Sutherlandia frutescens plant extracts. The synthesized nanoparticles were characterized using UV–vis, FTIR, XRD, SEM, EDS and TGA. The photocatalytic activity of these materials was tested on SMX and CIP antibiotics. Furthermore, their antibacterial efficiency against Gram-negative and Gram-positive bacterial strains was investigated. XRD, through phase identification and SEM/EDS, confirmed the formation of nanocomposites with elements of Cu, O and Ni. The 15% CuNiO nanocomposite demonstrated the highest thermal stability with a minimal weight loss of 3%. The 15% CuNiO had the highest degradation efficiencies of 92% and 85% for SMX and CIP, respectively. The catalyst could be reusable for up to three trials with a 65% efficiency against CIP, while the photogenerated electrons (e⁻) were the most reactive species for the degradation of pharmaceuticals. Lastly, these materials were noted to have antibacterial efficiency against both Gram-negative and -positive strains, with the highest zone of inhibition against E. coli. This study has shown that novel green nanocomposites from S. frutescence can be used for targeting multiple pollutants simultaneously by degrading antibiotics efficiently and removing various bacterial strains. Full article

Groundwater contamination in chemical industrial parks (CIPs) is a significant threat to global water security due to spills, leaks, and discharges, as well as the complexity of concealing a diverse range of industrial pollutants. In this article, we collected 30 groundwater samples from zones of presumed influence across a CIP, including upstream background, within-park, periphery, and downstream, located in Luxian County, Sichuan, China. We employed excitation–emission matrix (EEM) fluorescence spectroscopy with parallel factor analysis (PARAFAC) coupled with comprehensive hydrochemical analysis to deconvolve the dissolved organic matter (DOM) signature and statistically link its fluorescent components to specific hydrogeochemical processes and anthropogenic sources. Results revealed that industrial activities have transformed the groundwater to Ca-HCO₃·Cl and Ca·Na-HCO₃·Cl types from the hydrochemical facies comprising Ca-HCO₃ and Ca·Mg-HCO₃ types. Hydrogeology and groundwater chemistry depend primarily on weathering and atmospheric precipitation, but industrial effluents and evaporation concentration also significantly affect them. EEM-PARAFAC identified three dominant fluorescent components: fulvic-like (C1), humic-like (C2), and tryptophan-like (C3), with the latter serving as a sensitive indicator of recent anthropogenic inputs. The spatial distribution of these components, particularly the enrichment of C3, is primarily governed by anthropogenic inputs (e.g., sewage leakage), modulated by local hydrological conditions. This work demonstrates the integration of optical spectroscopy with conventional hydrochemistry for source apportionment in complex industrial settings. It provides a mechanistic understanding of pollution propagation and a practical, rapid diagnostic tool for targeted groundwater protection in CIPs. Full article

Cellular senescence is a stress-induced cell-cycle arrest that constrains expansion of ultraviolet-damaged keratinocytes yet can remodel the microenvironment. This systematic review evaluated histological and genetic or epigenetic senescence markers in actinic keratosis (AK), cutaneous squamous cell carcinoma (cSCC), and basal cell carcinoma (BCC). PubMed, Scopus, and Web of Science were searched (January 2005–May 2025); 34 human studies were included. AK showed an early senescent signature with frequent cyclin-dependent kinase inhibitor p21 (p21CIP1) expression (82.1%) and DNA damage signaling, including phosphorylated histone H2AX (gamma-H2AX) positivity (77%). In invasive cSCC, p21^CIP1 fell to 43.9% and tumor suppressor p53 immunoreactivity often declined, whereas cyclin-dependent kinase inhibitor p16 (p16INK4a) commonly accumulated without arrest, including cytoplasmic staining at invasion fronts. Reported escape pathways involved c-Jun N-terminal kinase 2 activity and long noncoding RNA PVT1–dependent repression of p21. Telomerase reverse transcriptase (TERT) promoter mutations were prevalent in cSCC (about 50%) and BCC (up to 78%) but uncommon in AK, consistent with late telomerase activation. Study heterogeneity, variable antibody scoring, and limited assessment of senescence-associated beta-galactosidase and secretory mediators restricted cross-study comparability. Standardized, spatially resolved profiling may refine risk stratification and support senescence-targeted prevention and therapy in keratinocyte cancers. Full article

Seafood processing environments represent some of the most demanding hygienic settings in the global food sector. High humidity, variable temperatures, and heavy organic residues promote the persistence of Listeria monocytogenes, Vibrio spp., and Salmonella spp., making sanitation both critical and inherently complex. This review synthesizes recent advances in hygienic design, sanitation technologies, and workforce safety as interconnected elements of a single “hygiene continuum.” Building upon Codex, FDA, and European hygiene frameworks (2020–2024), the review examines how engineering design, Sanitation Standard Operating Procedures (SSOPs) and Good Manufacturing Practices (GMPs) systems, and occupational hygiene jointly determine microbial control, sustainability, and workforce well-being. Particular focus is given to biofilm dynamics, emerging disinfection technologies, and automation through cleaning-in-place (CIP) and cleaning-out-of-place (COP) systems. Recent trends—including digital monitoring, eco-efficient cleaning, and human-centered facility design—are discussed as drivers of next-generation hygiene management. Collectively, these insights demonstrate that hygienic performance in seafood processing is not a fixed endpoint but a living system linking design, management, and human behavior toward safe, sustainable, and resilient seafood production. Full article

The presence of emerging organic contaminants in water and effluents, including antibiotics, poses significant environmental and health risks. Moreover, while photocatalysis is a promising approach for their removal, the inefficient utilization of natural sunlight by common photocatalysts limits its large-scale use. This work demonstrates the enhanced sunlight-driven photodegradation of the antibiotic Ciprofloxacin (CIP) using a nanocomposite composed of carbon dots (CDs) and TiO₂ (NC_50:50). The CDs were obtained from corn stover, a major agricultural waste product. Initial testing was performed under artificial solar radiation: CIP was virtually fully degraded within 20 min, with a rate constant of 0.2372 min⁻¹ and a 217% enhancement of catalytic activity over commercial TiO₂. Validation under real-world irradiation conditions was subsequently made by performing photocatalytic assays under natural sunlight on different days under diverse meteorological conditions. The performance of NC_50:50 was retained, degrading CIP within 30 min under natural conditions. Notably, while degradation by-products were identified under both artificial and natural sunlight, they were subsequently photodegraded by the nanocomposite under these conditions. This enhanced performance was attributed to a combination of effects resulting from CDs’ incorporation, namely, improved absorption of visible light, enhanced charge separation, and increased specific surface area. Furthermore, the addition of CDs resulted in changes in the reactive species generation profile, which can alter the available degradation pathways. Thus, this study provides insight that can be useful for strategies aimed at the rational design of sunlight-active TiO₂-based photocatalysts with tunable surface reactivity. Full article

Background: Malva sylvestris (the common mallow) is an herbaceous species widely used in ethnobotanical practices to treat gastrointestinal, hepatic and urinary inflammation. Objectives: Despite these beneficial effects on human health, the antineoplastic potential of this plant has not yet been fully explored. Thus, in the present study, two human colon cancer cell lines (i.e., HCT-116 and Caco-2) were treated with an extract obtained from M. sylvestris flowers (MFE), whose composition in terms of phytochemicals and microRNAs has been recently published by our research group, to explore its potential bioactivity. Methods/Results: MTT and Trypan blue assays demonstrated that MFE reduced tumour cell growth without causing significant cytotoxicity or apoptosis. Following the diphenylboric acid 2-aminoethyl ester-induced fluorescence of some plant metabolites, microscopy analysis proved that MFE components crossed the cell membranes, accumulating into nuclei. Wound assay and transwell tests documented that MFE was also able to reduce cell motility and invasiveness. In both cell lines qPCR experiments demonstrated that MFE caused the over-expression of factors, like VIMENTIN and E-CADHERIN, which negatively influence epithelial–mesenchymal transition in colon cancers. However, the effects of MFE appeared to be time-, dose- and cell type-dependent. In fact, the treatment induced senescence in P53-null Caco-2 cells (i.e., ROS, β-galactosidase and P21^WAF1/Cip1) and a premise of differentiation (i.e., P27^Kip1) in P53-wild-type HCT-116 cells, also via the CDK2/c-MYC/AKT axis, justifying its antiproliferative property. In parallel, the transfection of tumour cells with pure synthetic miR160b-5p—a microRNA identified in M. sylvestris flowers and predicted to target the human CDK2 transcript—resulted in gene silencing, thereby suggesting its central role in mediating the cross-kingdom effects of MFE on the investigated cancer models. Conclusions: Overall, these findings open new perspectives on the common mallow as a source of potential antimetastatic compounds and on the possible use of its plant microRNAs in the development of gene therapies. Full article

A hybrid AI and LLM-enabled architecture is presented for real-time decision support in industrial batch processes, where supervision still relies heavily on human operators and ad hoc SCADA logic. Unlike algorithmic contributions proposing novel AI methods, this work addresses the practical integration and deployment challenges arising when applying existing AI techniques to safety-critical industrial environments with legacy PLC/SCADA infrastructure and real-time constraints. The framework combines deterministic rule-based agents, fuzzy and statistical enrichment, and large language models (LLMs) to support monitoring, diagnostic interpretation, preventive maintenance planning, and operator interaction with minimal manual intervention. High-frequency sensor streams are collected into rolling buffers per active process instance; deterministic agents compute enriched variables, discrete supervisory states, and rule-based alarms, while an LLM-driven analytics agent answers free-form operator queries over the same enriched datasets through a conversational interface. The architecture is instantiated and deployed in the Clean-in-Place (CIP) system of an industrial beverage plant and evaluated following a case study design aimed at demonstrating architectural feasibility and diagnostic behavior under realistic operating regimes rather than statistical generalization. Three representative multi-stage CIP executions—purposively selected from 24 runs monitored during a six-month deployment—span nominal baseline, preventive-warning, and diagnostic-alert conditions. The study quantifies stage-specification compliance, state-to-specification consistency, and temporal stability of supervisory states, and performs spot-check audits of numerical consistency between language-based summaries and enriched logs. Results in the evaluated CIP deployment show high time within specification in sanitizing stages (100% compliance across the evaluated runs), coherent and mostly stable supervisory states in variable alkaline conditions (state-specification consistency ${\Gamma }_s\ge 0.98$), and data-grounded conversational diagnostics in real time (median numerical error below 3% in audited samples), without altering the existing CIP control logic. These findings suggest that the architecture can be transferred to other industrial cleaning and batch operations by reconfiguring process-specific rules and ontologies, though empirical validation in other process types remains future work. The contribution lies in demonstrating how to bridge the gap between AI theory and industrial practice through careful system architecture, data transformation pipelines, and integration patterns that enable reliable AI-enhanced decision support in production environments, offering a practical path toward AI-assisted process supervision with explainable conversational interfaces that support preventive maintenance decision-making and equipment health monitoring. Full article

Background/Objectives: The high prevalence of fluoroquinolone-resistant E. coli in healthy children represents a significant public-health risk, facilitating the spread of antimicrobial resistance and increasing the potential for difficult-to-treat extraintestinal infections with severe clinical outcomes. This study aimed to investigate the prevalence of fluoroquinolone resistance in multidrug-resistant E. coli isolated from presumptively healthy children in St. Petersburg, Russia, with a particular focus on fluoroquinolone resistance determinants. Methods: Phenotypic AST was performed on 307 E. coli isolates from fecal pediatric samples, comprising 230 isolates from 2012 to 2013 and 77 isolates from 2021 to 2022. A subset (n = 47) of MDR isolates underwent whole-genome sequencing. Results: The frequency of MDR E. coli strains rose significantly from 15.7% to 32.5% over the study period. The most significant increases in resistance among E. coli strains were to third-generation cephalosporins (CTX, CTZ) and fluoroquinolones (CIP), rising fourfold over a decade. Based on phenotypic resistance profiles of MDR E. coli to quinolones, the highest resistance rates were observed for MFX (80.9%) followed by NAL (74.5%), LVX (44.7%) and CIP (40.4%). Genotypic analysis revealed distinct pathways: low-level NAL resistance required only an S83 mutation in gyrA, whereas low-level MFX resistance was predominantly conferred by a plasmid-borne qnr gene. In contrast, resistance to CIP and LVX involved at least three QRDR mutations: S83L and D87N/Y in gyrA, and S80I in parC. Notably, our study showed the predominance of the ST131 and ST38 clones in E. coli isolated from pediatric samples. Conclusions: Our findings suggest that the efficacy of moxifloxacin for empirical treatment of infections caused by MDR E. coli might be severely compromised. Overall, the current study highlights that the pediatric gut microbiota serves as a reservoir for resistant E. coli with the expansion of multidrug-resistant clones independently of direct antibiotic selection pressure. Full article

Background/Objectives: Renal cell carcinoma (RCC) is a common and often asymptomatic malignancy with limited treatment options for advanced stages. Chronic inflammation and cellular senescence—collectively termed “inflammaging”—are emerging as key contributors to tumor progression. This study aimed to investigate the expression of inflammaging-related markers in RCC tissues, focusing on the role of PTX3, IL-6, and senescence-associated proteins in the tumor microenvironment. Methods: A retrospective cohort of 57 patients with clear cell RCC who underwent nephrectomy was analyzed. Formalin-fixed paraffin-embedded samples from tumor, peritumoral, and normal renal tissues were examined using confocal immunofluorescence microscopy to assess PTX3, IL-6, p21, and p16 expression. Senescence-associated β-galactosidase staining was performed to identify senescent cells. Serum IL-6 levels were measured by ELISA, and survival analysis was conducted using Kaplan–Meier curves and Cox regression analysis. Results: PTX3 and IL-6 were significantly upregulated in both peritumoral and tumor tissues compared to normal kidney samples (p < 0.001). Expression of senescence markers p21 and p16 were elevated in peritumoral areas (p < 0.001) as compared to normal renal tissues, but their expression was reduced or absent in the tumor core. High-grade and high-stage tumors exhibited stronger PTX3 and IL-6 expression and lower levels of cell cycle inhibitors (p < 0.001). Patients with elevated serum IL-6 levels had significantly lower 5-year cancer-specific survival (p < 0.005) and shorter progression-free survival (p < 0.001). Conclusions: Our findings suggest that peritumoral tissue in RCC exhibits a senescent and proinflammatory phenotype that may support tumor progression. PTX3 and IL-6 are potential biomarkers of disease severity and prognosis. Targeting inflammaging pathways could offer new therapeutic strategies for RCC, particularly in aggressive disease forms. Full article

This study investigates the determinants of green energy penetration in the Next Eleven (N-11) economies over the period 2000–2022, with a particular focus on the roles of foreign direct investment (FDI), green transition, governance quality, industrial growth, and urbanization. The primary objective of the study is to assess how investment flows, structural transformation, and institutional capacity jointly shape the adoption of renewable energy in fast-growing emerging economies. To achieve this goal, the study employs a second-generation panel econometric and machine-learning framework that accounts for cross-sectional dependence, slope heterogeneity, and long-run equilibrium relationships. Specifically, cross-sectional dependence and slope homogeneity tests are conducted, followed by CADF and CIPS unit root tests and the Westerlund cointegration approach. Long-run effects are then estimated using Partialing-Out LASSO and Cross-Fit machine-learning estimators, complemented by SHAP analysis to interpret nonlinear and heterogeneous effects. The results indicate that green transition, governance quality, and urbanization significantly promote green energy penetration. In contrast, FDI and industrial growth exert adverse effects, reflecting carbon-intensive investment and production structures. The findings highlight the importance of coordinated investment strategies, institutional strengthening, and urban planning in accelerating renewable energy transitions in emerging economies. These results provide policy-relevant insights for achieving sustainable energy development while supporting long-term economic growth in the N-11 countries. Full article

A second-order nonsingular terminal sliding mode control (SONTSMC) is proposed to solve the stabilization and tracking problems of an inverted pendulum. Although, a first-order sliding mode controller with the integral of the cart position can eliminate the offset in the cart position caused by incorrect calibration of the pendulum angle while balancing the pendulum at the upright equilibrium position, its control precision and chattering reduction can be improved by using a higher-order sliding mode controller. Therefore, the SONTSMC is designed by combining nonsingular sliding mode control and first-order sliding mode control to construct a second-order sliding mode controller that enhances tracking accuracy and reduces the chattering problems associated with sliding mode control. The performance of the proposed control is compared with that of the linear quadratic regulator sliding mode control (LQRSMC) and the integral linear quadratic regulator sliding mode control (ILQRSMC) for CIP’s stabilization and tracking. The results indicate that SONTSMC significantly increases the control performance of CIP while efficiently utilizing control energy. Full article

Background/Objectives: Although children’s playgrounds foster physical, cognitive and emotional health, sandpits can harbour antibiotic-resistant bacteria, representing a health concern for kids. Therefore, this point prevalence study investigated the presence and antimicrobial resistance of Escherichia coli in sandpits at four schools in Durban to ascertain the potential risk to schoolchildren and inform school authorities of the need to prevent such occurrences. Methods: Twenty samples were collected from schools on a single day. E. coli was isolated using colilert-18^® and confirmed using PCR. Antibiotic susceptibility testing was performed against 19 antibiotics using the disc diffusion method and Clinical and Laboratory Standards Institute (CLSI) guidelines. Results: E. coli was detected in 2/4 schools (50%), yielding 100 pure isolates. Of these, 71% (31 Site B and 40 Site C isolates) were resistant to at least one of the antibiotics tested, displaying 36 antibiograms. The highest resistance was to CFX (n = 40), and the lowest was to AMK and MEM (n = 1). All isolates were susceptible to CIP, CHL, GEN and TZP. At Site B, the highest resistance was against CFX (n = 16) and the lowest against AMK, CTX and NAL (n = 1). The highest resistance at Site C was against TET (n = 26), and the lowest against ATH and AUG (n = 1). Twenty isolates (20%) were multidrug-resistant, displaying resistance to at least one antibiotic from 3 classes. Conclusions: These results show that children with poor hygiene practices could get sick from playing in sandpits. Schools must change their sand regularly and ensure that sandpits are constantly exposed to the sun. Full article

Today, relational databases are widely used in information systems. SQL (structured query language) is taught extensively in universities and professional schools across the globe as a programming language for its data management and accesses. Previously, we have studied a web-based programming learning assistant system (PLAS) to help novice students learn popular programming languages by themselves through solving various types of exercises. For SQL programming, we have implemented the grammar-concept understanding problem (GUP) and the comment insertion problem (CIP) for its initial studies. In this paper, we propose an SQL Query Description Problem (SDP) as a new exercise type for describing the SQL query to a specified request in a MySQL database system. To reduce teachers’ preparation workloads, we integrate a generative AI-assisted SQL query generator to automatically generate a new SDP instance with a given dataset. An SDP instance consists of a table, a set of questions and corresponding queries. Answer correctness is determined by enhanced string matching against an answer module that includes multiple semantically equivalent canonical queries. For evaluation, we generated 11 SDP instances on basic topics using the generator, where we found that Gemini 3.0 Pro exhibited higher pedagogical consistency compared to ChatGPT-5.0, achieving perfect scores in Sensibleness, Topicality, and Readiness metrics. Then, we assigned the generated instances to 32 undergraduate students at the Indonesian Institute of Business and Technology (INSTIKI). The results showed an average correct answer rate of 95.2% and a mean SUS score of 78, which demonstrates strong initial student performance and system acceptance. Full article

Quick Quantitative (QQ) immunoassays have been increasingly applied for the measurement of enrofloxacin (ENR) and ciprofloxacin (CIP) residues in aquaculture due to their speed and convenience. However, their quantitative reliability remains limited because measurement uncertainty (MU) is rarely considered during field testing. To enhance the metrological reliability of QQ-based residue analysis, we developed AquaUncertainty Pal, a mobile application that embeds real-time MU computation into the QQ workflow. The software automatically evaluates uncertainty sources during sampling and pipetting, visualizes the uncertainty budget, and guides users through optimized operations. The framework was validated against ISO/IEC 17025–accredited LC–MS/MS and assessed through a user study involving 20 frontline technicians. With the integrated software, pipetting precision (RSD) at 100 μL improved from 4.1% to 1.79%, the inter-operator variability (CV) decreased by 52%, and conformity assessment accuracy for samples near the maximum residue limit (MRL) increased from 25% to 70%. This suggests that real-time MU visualization effectively guided technicians toward consistent pipetting and interpretation behavior. These results demonstrate that integrating MU into the QQ workflow is both feasible and effective, substantially improving reliability and providing a replicable digital framework for uncertainty-informed residue monitoring in aquaculture. Full article