Search Results (2,783)

Antimicrobial resistance (AMR) is increasingly becoming a major global public health concern, as antibiotics are losing their effectiveness at an alarming rate due to drug resistance. The ß-lactam group of antibiotics are widely used in dairy farms to treat animal infections, and their presence in the food chain is a significant concern. Addressing this issue requires the development of effective analytical tools for the rapid detection of antibiotics. In this work, a miniaturized Biosensor-on-Pillar platform was developed for detecting ß-lactam antibiotics in milk, which operates in a rapid, cost-effective, and user-friendly format, making it particularly suitable for resource-limited settings. The platform employs an enzyme induction-based approach, wherein Bacillus cereus spores germinate in the presence of β-lactam antibiotics, leading to the production of β-lactamase enzyme, which is then recognized using a chromogenic substrate functionalized on paper associated with the pillar platform. The developed biosensor can detect 12 β-lactam antibiotics with limits of detection (LODs) ranging from 1 to 1000 ppb, achieving sensitivity at or below the maximum residue limits (MRLs) set by regulatory bodies (FSSAI/CODEX) for the majority of the tested antibiotics. The performance of the platform, including the design, fabrication, and working principle, was further evaluated by analyzing six blind milk samples, yielding significant results compared to the commercially available AOAC-approved gold-standard method. Hence, the developed biosensor demonstrates promising potential for the rapid, cost-effective and high-throughput screening of milk samples for β-lactam antibiotics, benefiting the dairy industry and ensuring food safety. Full article

Heavy metal contamination of foods remains a persistent global challenge for food safety and public health, driven by industrialization, mining activities, intensive agriculture, and ongoing environmental degradation. This scoping review synthesizes peer-reviewed literature on the occurrence of priority toxic metals—arsenic, cadmium, lead, mercury, and nickel—in food matrices, with emphasis on contamination pathways, analytical detection strategies, and documented human health effects. The reviewed studies reveal widespread accumulation of heavy metals in staple foods, including cereals, vegetables, seafood, and processed products, with concentrations frequently approaching or exceeding international regulatory limits, particularly in regions exposed to strong anthropogenic pressure. Conventional laboratory-based techniques, such as atomic absorption spectrometry and inductively coupled plasma methods, remain the reference standards for quantitative determination and regulatory compliance; however, their application to large-scale or continuous monitoring is often constrained by cost, infrastructure, and operational complexity. Consequently, increasing attention has been directed toward emerging detection approaches, including portable X-Ray fluorescence, Raman/SERS spectroscopy, electrochemical biosensors, electronic tongues, and in situ magnetic measurements, as complementary tools for rapid screening and field-based surveillance. Among these, environmental magnetism and in situ magnetic techniques stand out as non-destructive, low-cost proxies capable of identifying metal-associated particulate contamination linked to food production systems. Chronic dietary exposure to heavy metals is consistently associated with neurotoxicity, nephrotoxicity, carcinogenicity, and oxidative stress, underscoring the need for integrated, multi-tiered monitoring frameworks to support early detection, risk assessment, and prevention. Full article

The rapid translocation of pesticide and metal residues in the environment and their entry into the food chain pose a significant risk to human health. Given the high global consumption of honey, quality control emphasizes the need for continuous monitoring and risk assessment. To evaluate contamination levels in honey from northern Croatia, a region with intensive agricultural land use, 38 comb honey and 22 extracted honey samples were collected by purposive one-time sampling in June 2023. These samples were analyzed for 190 pesticides using liquid chromatography–tandem mass spectrometry (LC-MS/MS) and gas chromatography–tandem mass spectrometry (GC-MS/MS), and for 17 trace metal(loid)s using inductively coupled plasma mass spectrometry (ICP-MS). The highest detection frequencies were observed for fipronil-sulfone, trifloxystrobin, and coumaphos in comb honey, and for N-(2,4-dimethylphenyl)-formamide (DMF) and N-(2,4-dimethylphenyl)-N′-methylformamidine (DPMF) in extracted honey. Glyphosate was the only pesticide to exceed the European Union (EU) maximum residue level (MRL) of 0.05 mg/kg in three honey samples. Elemental analysis quantified most target metals, with aluminum (Al), copper (Cu), iron (Fe), manganese (Mn), nickel (Ni) and zinc (Zn) being the most abundant, while silver (Ag), arsenic (As), and selenium (Se) were not detected in this study. None of the samples contained lead (Pb) above the regulatory limit for honey established in the EU (0.1 mg/kg). To ensure food safety, further efforts are required to assess the health risks associated with exposure to these contaminants through consumption of the evaluated food. Full article

Knowledge about the condition of electrical equipment in energy networks is of great importance to network operators. Partial discharges are a key parameter for evaluating the health of the insulation. While a quantifiable PD measurement for offline tests is state of the art, it is costly and labour-intensive. It, therefore, makes sense to carry out permanent monitoring during operation. At the medium-voltage level in the European interconnected grid, comprehensive monitoring of PD is not implemented. This study presents a novel sensor concept that is used to detect PD in medium-voltage switchgear and cables: the so-called Magnetic Flux Concentrator Sensor (MFCS). It is an inductive sensor concept with high sensitivity in the frequency range of a few MHz, like well-established High-Frequency Current Transformers (HFCTs) but with better magnetic saturation properties in specific use cases. The highly permeable ferrite core of the MFCS is unconventionally shaped, resulting in a higher-saturation field strength. Therefore, this sensor is not driven into saturation by the operating currents of typical MV power cables. Using the MFCS and conventional HFCT in a suitable combination enables direction-selective PD detection. This work presents the sensor concept and the method for directional detection of the PD location, as analysed and evaluated theoretically and practically with laboratory experiments. Full article

Dysregulated iron handling—including catalytic iron and ferroptosis, hepcidin–ferroportin signaling, ferritin dynamics, and neutrophil gelatinase-associated lipocalin (NGAL)-mediated siderophore transport—has been implicated in the initiation and propagation of acute kidney injury (AKI) across ischemia–reperfusion, sepsis, and nephrotoxic contexts. To provide a SANRA-aligned narrative synthesis of mechanistic and translational evidence on iron biology in AKI, clarifying biomarker readiness and therapeutic prospects while explicitly separating preclinical from human findings. PubMed, Scopus, and Web of Science (1 January 2000 to 30 September 2025), plus appraised grey literature (guidelines/registries) using predefined criteria (authority, update recency, and methodological transparency). Narrative review with comprehensive database searches, single-reviewer screening/extraction (acknowledged as a limitation), and qualitative synthesis. Evidence is organized by pathway (catalytic iron/ferroptosis, transferrin (Tf)/transferrin receptor (/TfR), ferritin/ferritin heavy chain (FtH), hepcidin–ferroportin and NGAL) and translational domain (biomarkers and therapeutics). Statements are tagged as [Preclinical] or [Human]. [Preclinical] Robust signals support roles for catalytic iron and ferroptosis, protection by iron chelation, hepcidin modulation, heme oxygenase 1 (HO-1)/FtH induction, and apotransferrin/NGAL-based strategies. [Human] Biomarkers such as NGAL show clinical utility for kidney injury detection, whereas catalytic iron assays (labile plasma iron [LPI]/bleomycin-detectable iron [BDI]) remain investigational with limited standardization. Observational links between iron-regulatory pathways and AKI risk exist, but interventional trials are sparse; dose, timing, and safety of iron-targeted strategies in defined AKI settings remain to be established. Iron-handling pathways are compelling targets for AKI prevention/mitigation, yet high-quality human trials are limited. Priorities include standardized catalytic-iron assays, biomarker-guided enrichment, and pragmatic trials of tractable interventions (e.g., peri-contrast or cardiopulmonary bypass settings). Until such evidence accumulates, recommendations beyond standard care should be avoided. Full article

Peloids are natural materials widely used in balneotherapy and dermatological treatments because of their physicochemical and mineralogical properties. Despite Serbia’s long tradition of spa-based pelotherapy, comprehensive data on the chemical and radiological characteristics of local peloids remain limited. In this study, peloid samples from 13 spa locations across four regions of Serbia were systematically investigated. The aim was to determine their physicochemical properties, elemental composition, and natural radioactivity, to assess their suitability and safety for therapeutic use. The analyzed samples exhibited pronounced variability in pH (6.59–9.52), electrical conductivity (77.5–6610 μS/cm), salinity (below detection limit to 4%), and total dissolved solids, reflecting diverse geological and hydrochemical properties. Inductively coupled plasma optical emission spectrometry revealed site-specific variations in macro- and microelements, influenced primarily by local lithology and sedimentary environments, with limited indications of anthropogenic inputs. Gamma spectrometric analysis showed that the activity concentrations of naturally occurring radionuclides (²²⁶Ra, ²³²Th, ⁴⁰K, ²³⁸U, ²³⁵U, ²¹⁰Pb) were within ranges commonly reported for therapeutic muds worldwide, while anthropogenic ¹³⁷Cs was generally low. Radiological hazard indices were below internationally recommended safety limits. A preliminary screening of dermal exposure to potentially toxic elements indicated no significant noncarcinogenic risk (HI < 1) and acceptable carcinogenic risk (TCR) levels. Overall, this study provides a comprehensive chemical and radiological baseline for Serbian peloids, supporting their safe use in controlled therapeutic and wellness applications and highlighting the importance of site-specific characterization for quality assessment. Full article

Microplastics (MPs) are pervasive environmental contaminants detected in terrestrial, aquatic, and human systems. Emerging evidence indicates that MPs interact with microbiota through biofilm formation, induction of oxidative stress, enrichment of antibiotic resistance genes (ARGs), and disruption of short-chain fatty acid metabolism, leading to dysbiosis and altered host immune responses. These interactions contribute to dysbiosis, altered immune responses, and increased dissemination of ARGs, which pose health risks. This review synthesizes current knowledge on mechanisms of microplastic–microbiota interactions, highlighting evidence from in vitro, in vivo, and environmental studies. We discuss methodological challenges, including variability in particle types, concentrations, aging, and analytical approaches. Recent advances in multi-omics techniques provide deeper mechanistic understanding and reveal functional consequences of MP exposure. We outline key knowledge gaps and propose future research directions to assess the impact of microplastic exposure on ecosystems and human health. Full article

Acute myeloid leukemia (AML) remains a highly morbid malignancy in which outcomes are constrained not only by disease refractoriness and relapse, but also by therapy-related toxicity—particularly infections, mucosal injury, and delayed hematopoietic reconstitution. The gut microbiota has emerged as a potentially modifiable layer of host vulnerability and resilience during AML treatment. Microbiome disruption is detectable already at diagnosis, even in antibiotic-naïve patients, and is often characterized by reduced community diversity, depletion of anaerobic taxa linked to short-chain fatty acids (SCFAs) production, and enrichment of pathobiont-associated profiles. During induction, cytotoxic therapy and antimicrobials precipitates diversity loss, domination events, and persistent shifts beyond discharge. Clinically, the most consistent translational signal is the association between baseline or early-treatment microbiome features and infectious outcomes, while emerging data suggest that diagnosis-time microbiome structure may also relate to hematologic recovery kinetics. Mechanistic models converge on pathways linking barrier integrity, microbial metabolites (notably butyrate and other SCFAs), immune calibration, and inflammatory translocation of microbial products. These insights support hypotheses: antimicrobial stewardship may preserve microbiome function; ecosystem repair strategies such as autologous fecal microbiota transfer (A-FMT) are feasible and can restore community structure; and metabolite or nutritional interventions merit evaluation in immunocompromised hosts. Regimen-specific microbiome effects and microbiome–drug interactions suggest that treatment choice could have downstream microbiome-mediated consequences. We synthesize evidence, outline interventional concepts, and define methodological priorities for next-generation trials assessing causality and clinical benefit. Progress will require longitudinal sampling, multi-omic integration (metabolomics, resistomics, and barrier/inflammatory biomarkers), and interventional designs linking microbiome dynamics to clinically meaningful outcomes. Full article

Background/Objectives: Patient-derived mesenchymal stem cells (MSCs) represent a promising avenue for myocardial regeneration, yet therapeutic application remains limited by inconsistent differentiation capacity and the absence of standardized cardiogenic induction protocols. This study demonstrates a proof-of-concept for guiding patient-specific bone marrow MSCs toward a functional cardiomyocyte phenotype using paracrine signals from differentiating iPSC-derived cardiomyocytes (iPSC-CMs). Materials and Methods: MSCs were maintained in conditioned medium from a concurrent, validated iPSC-CM differentiation protocol, with evaluation via immunocytochemistry, optical mapping, and whole-cell patch-clamp recordings. Results: Differentiated MSCs acquired organized sarcomeric architecture with cross-striations and displayed spontaneous calcium oscillations with decay kinetics matching source iPSC-CMs (CaT50 ≈ 283 ms vs. 301 ms). In co-culture, MSC-derived cells exhibited synchronized calcium dynamics with iPSC-CMs, confirming functional coupling, while patch-clamp detected hallmark cardiac ion currents (INa, ICa,L, and IKv). Morphologically, MSC-CMs displayed more mature, elongated rod-like shapes. Conclusions: Although current densities indicate partial immaturity, their reproducible detection validates successful cardiomyogenic commitment. This “parallel differentiation” platform eliminates donor-specific protocol tuning, providing a streamlined, paracrine-mediated approach to generate autologous cardiomyocyte-like cells for disease modeling, pharmacological testing, and future regenerative applications. Full article

The burgeoning scale of Pre-trained Large Models (PLMs) has intensified the demand for efficient inference without compromising performance, while existing large model collaborative frameworks have shown promise, they often suffer from functional redundancy among experts and limited robustness in complex cross-domain scenarios. In this paper, we propose Tri-gate Routing for Inference via Decoupled Efficient Network Technologies (TRIDENT), a highly efficient and robust heterogeneous collaborative inference framework. TRIDENT leverages the complementary inductive biases of MLP (for statistical patterns) and KAN (for symbolic logic) to maximize reasoning potential with minimal parametric overhead. To address feature homogenization in traditional distillation, we introduce Orthogonal Feature Decoupling Distillation, utilizing an orthogonality loss ${\mathcal{L}}_{orth}$ for functional decoupling and a reconstruction loss ${\mathcal{L}}_{recon}$ to anchor decoupled features to the PLM knowledge manifold. During inference, a Dual-Threshold Arbiter effectively detects expert hallucinations by integrating individual confidence ${\tau }_{con}$ and heterogeneous consistency ${\tau }_{agree}$. Extensive experiments on CIFAR-100-LT, XNLI, and GSM8K demonstrate that TRIDENT significantly reduces the Invocation Rate (IR) of PLMs while maintaining high accuracy. Our findings reveal a distinct Pareto optimal balance and validate the spontaneous division of labor between heterogeneous experts. By transcending the limitations of single-architecture systems, TRIDENT provides a robust and interpretable pathway for efficient collaborative intelligence. Full article

This study systematically compared the induction and resuscitation characteristics of the viable but non-culturable (VBNC) state in Klebsiella pneumoniae FY170-1 following sublethal exposure to sodium hypochlorite (NaClO) or glutaraldehyde (GA). Treatment with 30 mg/L NaClO or 60 mg/L GA for 60 min reduced culturability to below the detection limit (<1 CFU/mL). However, CTC staining showed that 50.80% and 63.44% of cells, respectively, retained respiratory activity, while SYTO 9/PI staining indicated that membrane integrity was largely preserved, consistent with induction of the VBNC state. Scanning electron microscopy revealed distinct morphological alterations in the two groups. NaClO-induced VBNC cells showed surface depressions and wrinkling, consistent with oxidative damage, whereas GA-induced cells exhibited filamentous and net-like surface structures, consistent with aldehyde-mediated cross-linking. Among the tested additives, sodium succinate showed the strongest resuscitation-promoting effect under the experimental conditions, with OD600 increasing after approximately 2 h of incubation. Post-resuscitation analysis further revealed marked differences between the two VBNC states. In resuscitated NaClO-induced VBNC cells, ATP partially recovered, but reactive oxygen species remained elevated and catalase activity showed little recovery. In contrast, resuscitated GA-induced VBNC cells exhibited lower ATP recovery but more rapid normalization of ROS and better recovery of oxidative stress-related parameters. Total protein analysis and SDS-PAGE further supported distinct patterns of protein-level alteration between the two treatments. Overall, these findings suggest that NaClO and GA induce phenotypically distinct VBNC states in K. pneumoniae, with different recovery behaviors and stress response profiles. Sodium succinate was identified as the most effective recovery-promoting additive under the tested conditions. These results highlight the risk of underestimating bacterial survival when culturability is used as the sole indicator of disinfection efficacy and support the need for more comprehensive viability assessment. Full article

In natural agricultural environments, plant disease monitoring faces significant challenges, including a highly uneven (long-tail) distribution of disease species, tiny scales of early-stage lesions, and complex, variable backgrounds. These factors hinder the ability of existing lightweight models to balance detection accuracy and computational efficiency. To address these issues, this paper proposes a detection scheme driven by the synergy of data distribution reshaping and model architecture optimization. At the data level, we propose the CALM-Aug augmentation strategy. Based on the statistical distribution characteristics of disease categories, this strategy utilizes object-level copy-paste logic to specifically compensate for the feature shortcomings of rare disease samples. It introduces a teacher-guided screening mechanism and employs accept–reject sampling to ensure the pathological consistency of the augmented samples, thereby alleviating the model’s inductive bias toward head categories. At the model architecture level, using YOLOv11 as the baseline, the YOLO11-ARL model adapted to agricultural scenarios is constructed. It enhances sensitivity to early point-like disease spots through Efficient Multi-Scale Convolutional Pyramids and lightweight decoupled detection heads. Furthermore, a Layer-wise Adaptive Feature-guided Distillation Pruning (LAFDP) algorithm is utilized to extract a lightweight version, YOLO11-ARL-PD, achieving a significant reduction in parameters and computational cost. Experimental results on the PlantDoc dataset show that the final model achieves a precision of 89.0% and an mAP@0.5 of 85.3%. Compared to the baseline model YOLOv11n, YOLO11-ARL-PD improves precision and average precision by 7.7 and 2.6 percentage points, respectively, while reducing parameters by 51.93% and weights by 46.15%. Cross-dataset tests prove the good generalization performance of the proposed method. This study indicates that, under lightweight constraints, jointly optimizing the training distribution and model architecture is an effective way to improve plant disease monitoring and to support the edge deployment of smart crop-protection systems. All resources for CALM-Aug are available at wyz-2004/CALM-Aug on GitHub. Full article

Background/Objectives: Previous research has shown that mental disorders are common in the general population in Latvia, while access to specialised psychiatric services is limited, particularly in rural areas. General practitioners, therefore, have a crucial role in the early detection and management of these conditions. Previous studies and national initiatives have highlighted an unmet need for continuing education in psychiatry tailored to the Latvian primary care context. In response, the first Latvian telementoring programme, the “ECHO School of Psychiatry” (Extension for Community Healthcare Outcomes, ECHO), was launched in 2023 to enhance general practitioners’ competencies and decision-making in mental healthcare. This study explored general practitioners’ experiences and perceptions of participation in the programme and its perceived impact on their practice, using a qualitative approach. Methods: Thirteen women general practitioners who had participated in the programme between October 2023 and February 2025 were recruited using voluntary response sampling, via email invitations from programme coordinators. Individual semi-structured interviews were conducted remotely between May and September 2025, audio-recorded, transcribed verbatim, and the resulting transcripts were analysed thematically using an inductive approach, supported by NVivo software. Data collection continued until no new themes emerged. Results: Four main themes emerged from the thematic analysis: (1) participants’ perceptions of the structure and educational value of the programme; (2) perceived impact of the programme on clinical practice and decision-making; (3) programme limitations in addressing professional isolation and fostering collaboration; (4) suggestions for programme improvement. Themes illustrate participants’ perceptions of the programme’s value, its impact on practice, and recommendations for further development. Conclusions: This study provides insights into the strengths and areas for improvement of the “ECHO School of Psychiatry” as perceived by general practitioners. It also acknowledges current challenges in primary care, such as limited access to specialists and professional isolation. Full article

Diabetic cardiomyopathy (DCM) features progressive fibrotic remodeling, but the shared molecular circuitry connecting diabetes mellitus (DM) to cardiomyopathy (CM) remains unclear. We integrated three DM- and three CM-related Gene Expression Omnibus (GEO) datasets and corrected batch effects with sva, verified by violin plots, principal component analysis (PCA), and silhouette coefficients computed on all common genes (DM: 0.9489 to −0.1016; CM: 0.9693 to −0.045; PC1/PC2 inter-batch differences abolished after normalization). Differential expression analysis identified 2562 DM Differentially expressed genes (DEGs) and 1414 CM DEGs, and their intersection yielded 91 common DEGs (51 upregulated, 40 downregulated). Protein–protein interaction (PPI) analysis prioritized 25 hub genes, whose enrichment profiles implicated insulin resistance/insulin signaling and adrenergic signaling in cardiomyocytes. TRRUST-based inference further defined a regulatory network centered on seven key genes (HIF-1α, ACTN4, ABCB1, LTBP1, CLU, TIMP2, and MYH11). To nominate a candidate target of oxymatrine (OMT), we performed docking and molecular dynamics (MD) simulations for representative complexes; OMT showed the most stable interaction with LTBP1, maintaining a consistently short pocket distance (~0.2 nm), the highest contact frequency, and the lowest MM/PBSA binding free energy (−15.32 kcal/mol), with favorable contributions dominated by van der Waals and nonpolar solvation terms. In primary cardiac fibroblasts (CFs), high glucose (HG, 30 mM glucose) induced proliferative and profibrotic activation, whereas OMT (0.4–0.8 mM) reduced HG-driven proliferation without detectable toxicity below 1.2 mM, suppressed FN, collagen I/III, and α-SMA expression, and inhibited migration. OMT also normalized HG-induced cell-cycle skewing by restoring G0/G1-phase occupancy and reducing S-phase entry, with effects comparable to metformin. Finally, HG increased LTBP1 expression and upregulated SMAD3/SMAD4, while OMT attenuated LTBP1 induction and suppressed downstream TGF-β/SMAD activation. Together, these data integrate cross-dataset transcriptomics with mechanistic validation to position LTBP1 as a putative antifibrotic node targeted by OMT, supporting inhibition of the LTBP1/TGF-β/SMAD axis as a candidate strategy to counter DCM-associated fibrosis. Full article

The ultraviolet B (UVB) sunburn model is a well-established human experimental pain paradigm for investigating underlying inflammatory pain mechanisms and is used in preclinical drug development research. This scoping review aimed to provide an overview of how UVB-induced cutaneous inflammation has been applied across experimental studies, with particular emphasis on methodological characteristics, sensory outcomes, and reported safety aspects. A total of 12 studies published between 1999 and 2025, comprising 367 participants, met the inclusion criteria. Across all studies, UVB irradiation produced a clearly demarcated inflammatory response accompanied by pronounced primary hyperalgesia. Peak primary hyperalgesia was typically observed between 24 and 48 h following irradiation and remained detectable for at least 72 h. Heterogeneity was identified using UVB dose calibration strategies, spectral properties of the irradiation source, size and anatomical location of the irradiated area, timing of sensory assessment, and applied testing methodologies. In contrast to the consistent induction of primary hyperalgesia, secondary hyperalgesia was reported inconsistently and appeared to depend on methodological conditions. Post-inflammatory hyperpigmentation was reported primarily after irradiation with three minimal erythema doses, whereas lower doses appeared to provide a more favorable balance between hyperalgesia induction and tolerability. Overall, the UVB sunburn model reliably induces primary inflammatory hyperalgesia in humans. However, careful selection and standardization of methodological parameters are essential to optimize its use in mechanistic and early-phase analgesic research. Full article