Search Results (944)

Essential oils have attracted considerable attention as natural antimicrobial agents for food preservation due to their broad-spectrum activity against foodborne microorganisms. Although numerous studies report strong antimicrobial effects under in vitro conditions, their effectiveness in real food systems is often substantially reduced. This review critically examines the discrepancy between in vitro antimicrobial activity and actual performance in food matrices. Particular attention is given to the influence of food matrix interactions, physicochemical instability, volatility, sensory limitations, and microbial adaptation on the efficacy of essential oils. A conceptual framework is presented to systematically summarize the major factors limiting antimicrobial performance in practical food applications. In addition, current strategies aimed at improving applicability, including encapsulation technologies, nanoemulsions, synergistic combinations, and active packaging systems, are discussed. Available evidence indicates that simplified experimental models frequently overestimate the practical efficacy of essential oils. More realistic and system-oriented evaluation approaches are therefore necessary to improve the translation of laboratory findings into food applications. Overall, essential oils remain promising candidates for natural food preservation, although their successful industrial application will depend on overcoming important technological and practical limitations. Full article

Background: Adverse drug reactions (ADRs) represent a major and often underestimated source of morbidity, hospitalization, and functional decline in older adults. The convergence of age-related pharmacokinetic and pharmacodynamic changes, multimorbidity, polypharmacy, and frailty creates a clinical environment in which ADR risk is not static but evolves along progressive trajectories—from mild, early manifestations toward severe, potentially irreversible outcomes. Understanding these trajectories is essential for rational geriatric prescribing. Methods: This narrative review synthesizes evidence from epidemiological studies, systematic reviews, Cochrane analyses, and clinical trials published between 2000 and 2025, focusing on adults aged 65 years and older with two or more chronic conditions. Sources were identified through a structured, non-systematic literature search of PubMed, EMBASE, Cochrane Library, Web of Science, and Scopus using the terms ‘adverse drug reactions’, ‘polypharmacy’, ‘multimorbidity’, ‘frailty’, ‘deprescribing’, and ‘pharmacokinetics’ in older adults, alone and in combination. Evidence quality was assessed narratively, distinguishing trial evidence from observational and expert consensus data. Results: ADRs in older adults are best classified using complementary frameworks—the augmented Type A to withdrawal Type E and failure-of-therapy Type F taxonomy (Types A–F), the Dose-Time-Susceptibility (DoTS) classification, and the EIDOS mechanistic scheme—which together capture the heterogeneity of drug-related harm in this population. Age-related pharmacokinetic changes (altered absorption, increased volume of distribution of lipophilic drugs, reduced hepatic and renal clearance) and pharmacodynamic shifts (heightened receptor sensitivity, baroreflex impairment, increased blood–brain barrier permeability) interact with polypharmacy and frailty to amplify ADR trajectories from mild to severe. Anticholinergic burden, prescribing cascades, and inappropriate polypharmacy function as structural accelerators of these trajectories. Medication review and deprescribing improve prescribing quality but evidence for hard outcome benefits remains of low to very low certainty. Emerging AI-enabled digital tools show promising accuracy for identifying frailty and pharmacological vulnerability, but this performance relates to frailty classification and has not yet been shown to prevent ADR trajectories; they require validation for routine clinical use. Conclusions: Recognizing ADRs in older adults as dynamic trajectories rather than isolated events repositions prescribing review and deprescribing from optional to essential clinical acts. An integrated approach combining pharmacological vigilance, comprehensive geriatric assessment, structured deprescribing, and emerging digital decision-support tools offers the most realistic pathway to reduce the trajectory-related burden of drug-related harm in complex older patients. Full article

In Industry 5.0 (I5.0), close-proximity human–robot collaboration demands communication beyond conventional alarms and speech. Nonverbal auditory communication offers a complementary modality, yet its role in I5.0 remains unmapped. This scoping review maps nonverbal auditory communication research in I5.0 Human–Robot Interaction (HRI) and compares it with general HRI literature to identify transfer potential and research gaps. Peer-reviewed English-language articles (2023–April 2026) addressing nonverbal sound in HRI contexts were included. Speech, emotion detection, haptic interfaces and non-HRI domains were excluded. A search with two syntaxes across Web of Science, Scopus, IEEE Xplore, ACM and MDPI, supplemented by citation searching, targeted I5.0-specific (Syntax S1) and general HRI auditory literature (Syntax S2). This created two article record sets, n1 and n2. Articles were organized following Arksey and O’Malley’s framework and PRISMA-ScR into four inductively derived clusters: Sonification, Multimodal Feedback Systems, Safety and Frameworks and Concepts. From 782 initial records, 16 (n1) and 32 (n2) articles were included. In I5.0, multimodal feedback dominates: intentionally designed nonverbal sounds improve situational awareness, reduce cognitive workload and increase perceived safety. Compared to n2, which is shaped by social robotics and emotion-driven sound design, five gaps emerge in I5.0: absent emotion-related sound perception research, missing field studies, missing industry-specific sound design frameworks, underutilized sonification for spatial awareness and safety and no unimodal auditory studies under realistic industrial conditions. A dedicated sound design framework operationalizing I5.0 communicative requirements into designable sound parameters is needed, alongside empirical validation under realistic industrial noise conditions. Full article

Nanotechnology offers transformative potential for wastewater treatment, yet its full-scale implementation remains bottlenecked by the “lab–reality gap”. While bench-scale studies using idealized matrices report outstanding pollutant removal efficiencies, performance routinely deteriorates in authentic wastewater due to complex matrix interferences, natural organic matter (NOM) competitive binding, fouling dynamics, and unpredictable nano–bio transformations. Moving beyond traditional reviews that focus heavily on material synthesis and theoretical capacities, this review provides a novel, systems-oriented, and function-driven perspective on environmental nanotechnology. We critically evaluate the operational stability and behavior of nano-enabled systems under realistic conditions, categorizing nanomaterial roles into reactive interfaces, selective barriers, signal generators, and biological modulators. Crucially, this work examines the synergistic integration of nanotechnology with advanced oxidation processes (AOPs), membrane bioreactors, and digital intelligence—including artificial intelligence (AI) and real-time nanosensing—to achieve smart fouling management and circular resource recovery. Finally, we propose a comprehensive, multidimensional evaluation framework that simultaneously assesses technical efficiency, stability, scalability, economic feasibility, environmental safety, and system compatibility. This review delivers a pragmatic roadmap to bridge the chasm between isolated laboratory discovery and robust, sustainable, field-scale wastewater engineering. Full article

Cybersecurity insider threats remain a significant challenge for modern organisations due to their potential to cause substantial financial and reputational damage. This paper presents a systematic review of insider-threat research (2019–2026) using the PRISMA methodology and introduces an empirically validated ensemble framework for insider-threat detection. The proposed approach combines User-Based Sequences (UBS), a self-supervised Transformer trained on next-token prediction and time-gap modelling, and an unsupervised anomaly detection ensemble operating on model-derived behavioural features. An answers directory is incorporated to provide grounded truth for insider entities and episodes within the CERT r6.2 dataset, enabling direct validation of detection outcomes. The framework integrates behavioural theory with machine-learning techniques to improve understanding of insider-threat precursors. Evaluation was performed using a seven-stage Isolation Forest ensemble incorporating multimodal behavioural and technical data streams. The approach successfully identified all insider users, achieving 100% recall and an AUROC of 0.93. Comparative analysis against a previously reported model showed comparable AUROC and perfect recall despite differences in evaluation methodology. While precision remained low (0.004) due to the extreme class imbalance in the full CERT r6.2 population (5 insiders among 4000 users), the results highlight the operational challenges of insider-threat detection in realistic enterprise environments. This research contributes a novel, reproducible framework that combines behavioural theory and advanced machine learning to support the detection and analysis of insider threats. Full article

The rapid expansion of high-protein dairy-based powders (HPDPs), including milk protein concentrates and isolates (MPC/MPI), whey protein concentrates and isolates (WPC/WPI), and micellar casein concentrates and isolates (MCC/MCI), has intensified the need to understand instability phenomena that emerge during processing and storage. These products are governed by protein-rich amorphous matrices, in which molecular mobility, interfacial composition, and mineral interactions dictate both physical stability and functional performance. Importantly, these physical instabilities are directly coupled with functional deterioration, particularly in terms of impaired wetting, dispersion, and dissolution during rehydration. This review presents an integrated mechanistic framework linking these instability phenomena across processing, storage, and reconstitution, thereby consolidating concepts that remain fragmented across the current literature on high-protein dairy matrices. Key controlling factors include glass transition temperature (Tg), water activity-induced plasticization, protein–protein and protein–mineral interactions, and surface compositional heterogeneity established during spray drying. These factors govern the progression from surface stickiness through uncontrolled agglomeration to caking, forming a consolidation continuum. In contrast to lactose-driven matrices, caking and agglomeration in HPDPs arise primarily from protein-mediated restructuring and inter-particle bonding, with lactose crystallization acting only as a secondary mechanism in mixed-composition grades. The review further distinguishes engineered agglomeration from storage-induced consolidation and evaluates advances in molecular mobility characterization and Tg-based stability mapping. Significant gaps remain in linking localized surface evolution, mineral redistribution, and inter-particle bridge chemistry under realistic environmental conditions. The review concludes by proposing a mobility-centered “stability-by-design” framework that integrates composition, processing, particle architecture, and storage conditions to guide the development of future HPDPs with improved physical stability and functional recovery. Full article

Background/Objectives: Non-small cell lung cancer (NSCLC) remains associated with high mortality, frequent late-stage diagnosis, biological heterogeneity, and recurrence after treatment. Although molecular and immunohistochemical biomarkers have transformed treatment selection, there remains a need for accessible, repeatable, and clinically practical circulating biomarkers that may support prognosis and post-treatment monitoring. This review discusses prolactin (PRL) as a candidate supplementary biomarker in NSCLC, with particular emphasis on its biological rationale, potential prognostic relevance, and possible role in personalized risk stratification after systemic therapy. Methods: This narrative review summarizes current evidence on established biomarkers in NSCLC, the physiology and regulation of PRL, PRL/PRLR signaling in cancer biology, mechanisms of PRL dysregulation in lung cancer, and available clinical observations concerning PRL alterations in NSCLC. Particular attention is given to the distinction between prognostic and predictive biomarkers, longitudinal monitoring, pituitary involvement, immune checkpoint inhibitor-related endocrine effects, and biological, pharmacological, and analytical confounders affecting PRL interpretation. Results: Current evidence suggests that PRL may be biologically relevant in NSCLC through its involvement in pathways related to cell proliferation, survival, angiogenesis, invasion, epithelial–mesenchymal transition, immune modulation, and possible therapy resistance. Clinical observations indicate that altered PRL levels may occur in advanced disease, pituitary involvement, systemic inflammation, stress, or during anticancer and supportive treatment. However, PRL lacks cancer specificity and is influenced by multiple confounders, including circadian rhythm, stress, endocrine disorders, macroprolactin, cachexia, medications, and assay variability. Available clinical data remain limited and are largely derived from small studies or case-based evidence. Conclusions: PRL should not currently be considered a standalone diagnostic, predictive, or treatment-selective biomarker in NSCLC. Its most realistic potential role is as a supplementary circulating marker within multimarker prognostic and monitoring models. Prospective validation with standardized sampling, assay procedures, and confounder adjustment is required before clinical implementation. Full article

Wind turbines are increasingly deployed at larger scales and in harsher operating environments, leading to greater structural complexity, stronger load variability, and higher maintenance demands across both drivetrain and structural components. Reported field data indicate that gearboxes and bearings account for approximately 30–40% of total turbine downtime, while blade-related failures contribute roughly 20–25% of reported failure events, primarily through fatigue, delamination, leading-edge erosion, and lightning-induced defects. In parallel, large-scale and offshore turbines show increasing susceptibility to tower fatigue cracking, corrosion-assisted degradation, and flange joint bolt-preload loss under cyclic and environmental loading. This review provides a comprehensive applied-engineering synthesis of failure mechanisms, reliability challenges, and monitoring strategies for major wind turbine components, including gearboxes, bearings, blades, towers, and flange joints. A wide range of condition monitoring, structural health monitoring (SHM), and prognostics and health management (PHM) approaches is critically examined, including vibration analysis, acoustic emission, ultrasonic inspection, infrared thermography, impedance-based sensing, electromagnetic methods, machine vision, SCADA-based diagnostics, and artificial-intelligence-assisted fault classification. The review compares these techniques in terms of detectable damage types, spatial coverage, sensitivity, deployment practicality, and limitations under real operating conditions. In addition, statistical reliability methods and data-driven models are discussed to interpret failure trends and uncertainty. Recent AI-based studies have reported fault classification accuracies exceeding 90% under controlled or semi-controlled conditions; however, their field reliability remains constrained by data imbalance, domain shift, limited labeled failure datasets, model interpretability, and insufficient validation under realistic turbine operating environments. The main contribution of this review is an integrated applied synthesis that connects drivetrain and structural failure mechanisms with measurable monitoring indicators, diagnostic technologies, AI-enabled PHM limitations, and predictive-maintenance decision needs. The paper provides practical guidance for monitoring design, early fault detection, predictive maintenance, and long-term reliability improvement in next-generation wind turbine systems. Full article

Human digital twins (HDTs) are patient-specific computational models that combine medical imaging, physiological measurements and predictive algorithms. They are moving from an exciting concept to a realistic clinical opportunity. The key question is no longer whether HDTs can be built. The key question is which methods are mature enough to support clinical decisions and what is still missing for routine use. This systematic review maps the methodological landscape of HDTs and highlights practical bottlenecks that limit clinical translation. A PRISMA 2020 guided search of PubMed, Scopus, IEEE Xplore, and the Cochrane Library, covering publications from 2016 to 2026, identified 151 eligible studies. Bibliometric mapping and thematic synthesis were used to characterize research clusters, computational paradigms, and collaboration patterns. Three dominant application streams were identified: cardiovascular HDTs for hemodynamic simulation and procedural planning, musculoskeletal HDTs for biomechanics-driven orthopedic innovation, and neurological HDTs integrating neuroimaging with computational neuroscience. Across domains, the strongest technical trend is the rise in hybrid pipelines that combine physics-based simulation, including finite element and computational fluid dynamics models, with machine learning for segmentation, parameter identification, reduced-order modeling, and faster inference. However, reporting of verification, validation, uncertainty quantification, and explicit context of use remains uneven and prospective clinical evidence is still limited. Overall, the literature shows rapid progress toward clinically credible HDTs, while highlighting the need for scalable computation, standardized credibility pipelines, and workflow-integrated platforms to support safe and reproducible clinical adoption. Full article

The increasing concentration of atmospheric CO₂ has intensified the urgent need for efficient and sustainable carbon capture technologies. Covalent organic frameworks (COFs) have emerged as a highly promising class of porous crystalline materials for CO₂ adsorption and separation owing to their structural tunability, high surface area, and precisely designable pore environments. This review summarizes recent advances in COF-based CO₂ capture systems, covering pristine COFs, functionalized frameworks, composite materials, and membrane-based architectures. In pristine COFs, CO₂ adsorption is mainly governed by micropore confinement and physisorption within well-defined channels, where surface area and pore size distribution play key roles. Functionalized COFs introduce additional active sites, including amine groups, heteroatoms, ionic functionalities, and alkali metal centers, which significantly enhance CO₂ affinity through stronger electrostatic and acid–base interactions, often leading to mixed physisorption–chemisorption behavior. Composite COFs and mixed-matrix membranes further improve performance through synergistic effects, interfacial engineering, and enhanced mass transport. Despite these advantages, challenges remain in achieving an optimal balance between capacity, selectivity, and regenerability under realistic conditions such as humidity, low CO₂ partial pressure, and multicomponent gas streams. Issues related to scalable synthesis, structural stability, and processability also limit practical applications. Overall, this review highlights key structure–property relationships and outlines future directions, including humid-stable COFs, direct air capture, computational design strategies, and advanced membrane technologies, for next-generation CO₂ capture materials. Full article

Prostate cancer is the most common cancer diagnosed in men and the incidence is rising globally. Disease-related mortality however remains comparatively low. There is now irrefutable evidence that many men do not need treatment if diagnosed with early cancer and can instead be safely managed conservatively. Active surveillance is therefore now an increasingly popular management option for these men. A minority of men on surveillance however will experience disease progression to a point where radical treatment is necessary. It is therefore logical to consider interventions that might slow down or abrogate this natural history. This is particularly important for subgroups of men with early cancer who are at a higher risk of progression and where the risk–benefit of therapeutic intervention is much more favourable. In this narrative review we explore the literature on known molecular and genetic events in prostate cancer which may drive progression. Our principal focus was to consider mechanisms that could be realistically targeted by therapeutics. We further consider key attributes that early cancer therapeutic trials should incorporate in their design. These include risk-stratified patient selection, bespoke dosing schedules and the importance of unambiguous, clinically meaningful endpoints in this new trial space. Full article

Microplastics (MPs) have emerged as persistent environmental contaminants due to their persistence, widespread distribution, and potential risks to the environment and human health. This review focuses on the sources of MPs, their potential environmental risks, and human impacts, as documented in the recent literature from 2020 to 2026. Recent studies focusing on pathways, environmental weathering, and toxicity were evaluated and synthesized into the analysis. Previous studies have demonstrated that microplastics are transported across and between environmental compartments. Environmental degradation, driven by ultraviolet radiation, mechanical fragmentation, and oxidation, can alter microplastics’ surface characteristics, which may affect microplastic mobility, reactivity, and the solid-state adsorption of contaminants. Human exposure occurs primarily through ingestion and inhalation, with dermal and occupational exposure also contributing under certain conditions. Emerging evidence from in vitro, animal, and human tissue studies suggests that smaller particles, particularly nanoplastics, may contribute to oxidative stress, inflammation, and cellular injury; however, important uncertainties remain regarding environmentally realistic exposure levels, long-term health outcomes, and the extrapolation of experimental findings to real-world human health risk. Overall, the current literature highlights the need for standardized methodologies, improved integration of environmental monitoring and exposure assessment, and stronger evidence to support risk assessment and policy development. Full article

Thermal regulation of lithium-ion (Li-ion) battery modules is a critical constraint for electric vehicle (EV) safety and durability, particularly during high-C-rate operation. Phase change materials (PCMs) have emerged as promising passive solutions due to their latent heat storage capability; however, current literature is heavily biased toward organic paraffin-based systems and lacks structured benchmarking across PCM categories and integration architectures. This review provides a systematic comparative assessment of PCM-based battery thermal management systems (BTMSs) comprising organic, inorganic, and eutectic materials under EV-relevant discharge conditions. The review is structured according to the conventional classification of PCMs; however, the available literature is predominantly focused on organic materials, particularly paraffin-based PCMs, leading to greater depth of analysis for this category. Thermophysical properties are analyzed in conjunction with discharge rate, module configuration, and hybrid cooling strategies. The results indicate that peak temperature mitigation is weakly correlated with latent heat magnitude when thermal conductivity remains below critical values. Conductivity-enhanced composites incorporating expanded graphite or metal foams significantly improve heat diffusion, reducing hotspot intensity and inter-cell temperature gradients under medium-to-high C-rates. Pure passive PCM systems exhibit thermodynamic limitations during sustained high-power operation due to saturation effects, underscoring the need for hybrid architectures for continuous heat rejection. This work establishes a structured benchmarking framework and demonstrates that effective thermal conductivity, integration strategy, and discharge-dependent design dominate BTMS performance over latent heat alone. The findings also reveal that inorganic and eutectic PCM-based BTMSs remain comparatively less explored in the literature, particularly at the battery module level and under realistic electric vehicle operating conditions, highlighting opportunities for future research. Full article

The innate–adaptive immune interface is a decisive control point determining whether therapeutic interventions induce durable protection, antitumor immunity, inflammatory, or immune tolerance. Many immunotherapies fail in translation because immunity is often treated as a single-output system rather than a spatially and temporally organized network shaped by tissue context, antigen-presenting cell fate, biomolecular conditioning, and metabolic state. This review introduces the immunoscape framework as a nanobiotechnology-oriented model for linking immune-state mapping with controllable translational variables, including delivery route, release kinetics, first-contact immune cells, lymphatic routing, biomolecular corona identity, antigen-presenting cell fate, and safety-gate assessment. Unlike systems immunology, which primarily describes immune networks, or conventional immune engineering, which often focuses on selected payloads, targets, or platforms, the immunoscape framework provides a design layer for predicting context-dependent immune outcomes. We discuss two converging strategies for reprogramming this interface: natural biologics, including beta-glucans, polyphenols, microbial metabolites, and extracellular vesicles; and smart nanomaterials, including lipid nanoparticles, biomimetic vesicles, lymph node-targeted platforms, and stimulus-responsive nanoarchitectures. We further propose translational design rules to guide clinically realistic immune-reprogramming nanomedicines for cancer, infectious, inflammatory, and regenerative applications. Full article

The excessive emission of greenhouse gases (CO₂, CH₄, SF₆, and CF₄.) is a primary driver of global climate change, making the development of efficient adsorption and separation technologies critically important for achieving carbon reduction goals. Metal–organic frameworks (MOFs) have attracted considerable attention in this field due to their crystalline porous structures, ultrahigh surface areas, and tunable pore architectures. However, pristine MOFs face significant bottlenecks including poor water stability, high bed pressure drops caused by their powdered form, and limited mass transfer, which severely hinder their industrial application. The integration of MOFs with functional materials such as carbon materials, polymers, metal oxides, and porous SiO₂ offers a synergistic strategy to overcome these limitations. Carbon materials provide hydrophobic barriers and mesoporous transport channels, polymers enhance processability and mechanical strength, metal oxides introduce basic sites for enhanced chemisorption, and MOF-on-MOF heterostructures enable atomic-level interfacial integration and pore synergy. This review systematically summarizes recent advances in MOF composites for the separation of CO₂, CH₄, and fluorinated greenhouse gases (SF₆, CF₄.), with an emphasis on design strategies, structure–performance relationships, and synergistic mechanisms across different composite types. Finally, the current challenges including scalable synthesis, long-term stability, and separation performance under realistic conditions are discussed, and future directions toward rational design and functional synergy for industrial carbon capture and fluorinated gas emission reduction are envisioned. Full article