Search Results (9,364)

Cytokines are key regulators of immune responses and tissue remodeling, playing a central role in physiological homeostasis and pathological inflammation. Dysregulation of cytokine signaling networks has been implicated in a wide range of diseases, where persistent inflammatory activation leads to progressive tissue destruction and impaired repair mechanisms. In the oral environment, cytokines critically influence the balance between tissue resorption and regeneration, particularly in processes involving dentin and alveolar bone remodeling. Pathological root resorption (PRR) represents a clinically significant model of cytokine-driven tissue destruction, characterized by the loss of dental hard tissues mediated by osteoclast-like cells within a dysregulated inflammatory microenvironment. Although mechanical, infectious, and iatrogenic factors are well-established triggers, they alone do not fully explain the variability in clinical outcomes, suggesting an important role for host-related factors. New research highlights the relationship between inflammatory signaling pathways, genetic susceptibility, and molecular biomarkers in shaping the onset and progression of PRR. In particular, the RANK/RANKL/OPG axis, cytokine networks, and gene polymorphisms have been identified as key determinants of osteoclast activation and resorptive activity. At the same time, advances in salivary and gingival crevicular fluid biomarker research provide new opportunities for early detection and real-time monitoring. Despite these advances, current knowledge remains fragmented, with heterogeneous study designs, inconsistent genetic associations, and a lack of standardized diagnostic protocols, all of which limit clinical translation. Therefore, a comprehensive and integrative synthesis of cytokine-mediated mechanisms in PRR is needed. This review aims to provide an updated and critical overview of cytokine and chemokine involvement in PRR, integrating molecular pathways, genetic determinants, and emerging biomarkers within a unified framework while highlighting translational implications for precision dentistry. Full article

The use of prosthetic devices can significantly improve the quality of life of individuals with limb amputations. However, existing prosthetic hands face multiple engineering and manufacturing challenges, making them economically inaccessible to a large portion of the population. This study focuses on the design and analysis of a cost-effective prosthetic hand capable of performing five fundamental grasp types: tripod, cylindrical, spherical, lateral, and pinch. The development process began with a biomechanical analysis of the human hand, followed by the derivation of a kinematic model. To ensure anthropomorphic fidelity, finger trajectories were synthesized using a computer vision-based algorithm that captured natural human motion. These trajectories were then mapped to the prosthetic control system. Experimental validation was conducted through rigorous goniometric analysis of the prototype’s execution. The results demonstrated the system’s effectiveness in replicating functional grasps, with a Root Mean Square Error (RMSE) within acceptable thresholds for assistive tasks. While the prototype achieved high motion correspondence, higher deviations were observed in distal joints due to mechanical transmission resistance and spring-return torque requirements. This work provides a scalable framework for tendon-driven prostheses, balancing advanced trajectory synthesis with a robust and accessible mechanical architecture. Full article

Faced with a global energy crisis and ecological degradation, overall water splitting (OWS) is a pivotal approach for renewable energy conversion and storage. However, its industrial application is hindered by the high energy barriers/sluggish kinetics of the anodic oxygen evolution reaction (OER), as well as the scarcity of precious metal catalysts limiting large-scale deployment. Herein, a cobalt-based layered double hydroxide (Co-LDH) was used as the precursor, and a multi-strategy synergistic modification (hydrothermal synthesis, Fe doping, sulfurization, and external magnetic field magnetization) was applied to fabricate the Fe-Co₃S₄-MS-20 min electrocatalyst. This strategy establishes Fe-Co bimetallic synergistic active centers, and magnetic treatment modulates the electron configuration of Fe 3d orbitals without changing the material’s lattice spacing or morphology. Structural characterizations and electrochemical measurements were used to investigate the effects of combined modifications on the catalyst’s phase structure, morphology, electronic structure, and trifunctional catalytic performance toward the hydrogen evolution reaction (HER), OER, and urea oxidation reaction (UOR). The Fe-Co₃S₄-MS-20 min catalyst exhibits a larger electrochemical active surface area, lower charge transfer resistance, and smaller Tafel slope in 1 M KOH, it achieves overpotentials of 165 mV for HER (10 mA·cm⁻²) and 310 mV for OER (100 mA·cm⁻²), along with superior UOR performance and long-term stability. In situ impedance and Raman spectroscopy confirm that magnetization accelerates charge transfer and promotes in situ reconstruction. Synergistic multi-strategy regulation optimizes the electronic structure of active centers, reducing electrocatalytic energy barriers. This work provides new insights into designing high-performance non-precious metal electrocatalysts and offers experimental support for external magnetic field regulation in electrocatalyst modification. Full article

Periodontal disease is a chronic inflammatory condition driven by polymicrobial biofilms whose interaction with the host immune response drives the destruction of tooth-supporting tissues. Within these communities, bacterial cell–cell communication—particularly quorum sensing (QS)—coordinates virulence factor expression, biofilm maturation, and interspecies behaviour, allowing pathogens to mount population-dependent attacks on the host. Disrupting these signals has therefore drawn growing attention as an anti-virulence strategy for biofilm-associated oral infection. Quorum quenching (QQ)—the inhibition or disruption of QS pathways—prevents bacteria from coordinating these virulence-related activities. The candidate inhibitors investigated to date fall into three broad classes: conventional antibiotics used at sub-inhibitory concentrations, plant-derived natural compounds, and synthetic molecules designed to interfere with signal synthesis, signal reception, or signal transduction. In experimental work on periodontal pathogens, agents from each class reduce biofilm formation, suppress virulence factor production, and disrupt microbial communication within polymicrobial biofilms. Clinical translation, however, lags behind the laboratory evidence. Most data still come from in vitro systems and animal models, and the ecological complexity of the oral biofilm makes therapeutic targeting difficult: signals that drive virulence in pathogens also support cooperation among commensals. Toxicity profiles, pharmacokinetics, and well-powered clinical trials are needed before quorum-quenching agents can be considered for routine periodontal care. Even with these caveats, targeting bacterial communication offers a different therapeutic logic from conventional antimicrobials: attenuating virulence rather than killing cells, and so exerting weaker selective pressure for resistance. Further dissection of QS networks in oral biofilms—and the rational design of quenching agents that act on pathogenic rather than commensal signalling—may yield useful adjuncts to current periodontal therapy. Full article

RNA-based therapeutics are becoming increasingly important in oncology, particularly following the rapid development of mRNA technologies during the COVID-19 pandemic, but their success strongly depends on how efficiently they can be delivered to target cells. Microfluidic technologies have redefined the design and manufacturing of RNA-based nanocomplexes, as they enable precise control over physicochemical features that are critical for clinical translation in oncology. This review examines recent developments in microfluidic-assisted synthesis of RNA nanocarriers, with a focus on cancer applications. Through a detailed analysis of material systems, device architectures, and formulation strategies, we explore how laminar flow environments enable reproducible encapsulation, tunable particle size, and improved payload stability. We examine the microfluidic assembly of lipid nanoparticles and polymeric carriers for RNA delivery, highlighting strategies to enhance durability, bioavailability, and cellular uptake. Advancements in process optimization, including flow parameter refinement and inline monitoring, are discussed alongside the influence of device geometries on mixing dynamics and nucleation. Beyond formulation, we explore the integration of microfluidics with tumor-on-chip platforms to evaluate transport, penetration, and therapeutic response in physiologically relevant cancer models. By connecting technological innovation with preclinical application, this work outlines the trajectory toward next-generation, personalized RNA nanomedicines enabled by microfluidic precision. Full article

To address wellbore instability and the technical challenges associated with high-density water-based drilling fluid loss control in deep shale gas formations of the Sichuan-Chongqing region in China, a novel nano-micro sealant designated CLG-Seal was synthesized via molecular structural optimization. The molecular structure of newly developed CLG-Seal exhibits distinct core–shell structural characteristics. The inorganic nano-silica constitutes the rigid core of CLG-Seal, which guarantees its plugging performance. The hydrophobically associating polymer which is coated on the surface of nano-silica constructs the flexible shell of CLG-Seal, endowing the CLG-Seal with excellent gel-forming capacity, adhesion film-forming capacity, deformability and perfect dispersibility. Transmission electron microscopy and scanning electron microscopy were employed to characterize the morphology of the CLG-Seal nanomicron-scale plugging agent. The sealing performance and underlying mechanisms of CLG-Seal were subsequently evaluated via particle plugging apparatus tests, displacement experiments, and etched glass micromodel simulations. Field trials conducted in the third section of Well WY3-2-3HF validated the application effectiveness of this agent in drilling fluid systems. The results indicate that the nano-micro sealant CLG-Seal exhibits a median particle size of D₅₀ is 146 nm, which can be modulated by adjusting the synthesis conditions. The nano-micro sealant CLG-Seal significantly mitigates fluid loss in low-permeability microfractures and fissures. Notably, a concentration of merely 3% is sufficient to achieve optimal nano-micro plugging performance. The results of the mechanism study indicate that while the CLG-Seal particles are close to each other, the polymer chains with flexible long chain structure which are coated on the surface of nano-silica constructs tend to be intertwined, forming a cross-linked network structure of gel film, thereby increasing the interaction between nano-micron particles and forming an impermeable plugging film. In addition, due to the nanoscale effect, the CLG-Seal has a strong tendency to adsorb onto the surface of shale rock through hydrogen bonding with the shale matrix. The hydrophobically associating polymer with high elastic modulus and excellent mechanical properties can enhance the pressure-bearing capacity of the filter cake through elastic deformation. Therefore, these nano-micron particles can form a strong sealing film on the filter cake and at the micropores of shale rock, thereby creating a dense mud cake on the outside of the shale formation. Field trial results demonstrate that the incorporation of the nano-micro sealant CLG-Seal into the drilling fluid for the third section of Well WY3-2-3HF reduced the PPA fluid loss to 4.6 mL. This value represents a substantial reduction compared to adjacent wells and signifies a remarkable improvement over the drilling fluids previously employed in the Longmaxi Formation of this block. Furthermore, the treated drilling fluid exhibited a superior filtration control pressure capacity of 10.5 MPa. The operation was completed successfully without any lost circulation or wellbore instability, and achieved a drilling footage of 42 h with an average penetration rate of 7.81 m/h. The mud weight was reduced by approximately 0.08–0.10 g/cm³ compared to offset wells. These results confirm the excellent application efficiency of the newly developed CLG-Seal in field operations. Full article

The global burden of type 2 diabetes mellitus (T2DM) and metabolic dysfunction-associated steatotic liver disease (MASLD) continues to rise at an alarming pace, with substantial pathophysiological overlap driven by insulin resistance, visceral obesity, and chronic low-grade inflammation. MASLD may progress to metabolic dysfunction-associated steatohepatitis (MASH), with increased risk of cirrhosis and hepatocellular carcinoma. Glucagon-like peptide 1 (GLP-1)-based therapies have transformed the management of T2DM and obesity. They exert pleiotropic effects whose basis remains incompletely understood. Concurrently, Akkermansia muciniphila has emerged as a keystone gut microbiota species with demonstrated hepatoprotective potential in preclinical models of MASLD/MASH. This narrative review positions A. muciniphila simultaneously as a target of GLP-1-mediated microbiome remodeling and as an independent modulator of hepatoprotection in MASLD/MASH. A structured search of PubMed, Scopus, and Web of Science (last searched: 12 April 2026) was conducted using terms related to Akkermansia muciniphila, GLP-1 receptor agonists, MASLD/MASH and T2DM. A total of 174 records were identified. Of these, 148 were excluded due to duplication or non-relevant study design. 26 studies (23 preclinical, 3 clinical) were included in the synthesis, directly addressing A. muciniphila. Preclinical evidence demonstrates that liraglutide, semaglutide, exenatide, and tirzepatide increase A. muciniphila abundance, while A. muciniphila in turn enhances endogenous GLP-1 secretion via the P9/ICAM-2 axis, forming a hypothetical positive feedback loop. A working mechanistic model integrating these bidirectional interactions is proposed, alongside a discussion of current limitations and future research priorities, including microbiome-guided clinical trials in MASLD/MASH populations. Full article

Increasing environmental pollution has intensified the focus on sustainability, encouraging the development of eco-friendly materials. This study reports the synthesis of binary (ZnO–TiO₂) and ternary (SnO₂–ZnO–TiO₂) compounds and their loading with Au/Ag/Pt/P noble metals (NMs) to enhance photodegradation efficiency under visible light compared to pristine TiO₂. The compounds were synthesized in a single step via laser pyrolysis, and then noble metal deposition through chemical impregnation and reduction was performed. Structural and morphological analyses revealed TiO₂-based nanoparticles with varied morphologies decorated with noble metal nanoparticles with sizes between 2 and 6 nm (for Pt and Pd). Photocatalytic tests demonstrated a significant improvement in Methyl Orange (MO) degradation under visible light, especially for Ag-loaded samples. The degradation rate increased from 1.03 × 10⁻³ min⁻¹ (TZ) to 22.65 × 10⁻³ min⁻¹ (TZS_Ag), while it was 0.09 × 10⁻³ min⁻¹ for the commercial P25 sample. Biocompatibility assays indicated lower cytotoxicity than Degussa P25, with Au- and Pd-loaded samples showing improved compatibility with HaCaT and HEK293 cells. Overall, these findings demonstrate that the developed TiO₂-based nanocomposites, designed through a novel and sustainable strategy combining binary/ternary heterostructures with noble metal loading, are promising candidates for efficient visible light-driven photocatalytic environmental decontamination with enhanced biological compatibility. Full article

The built environment in Saudi Arabia accounts for approximately 78% of the country’s total electricity consumption, positioning building energy performance as one of the most consequential levers available to policymakers pursuing the kingdom’s net-zero greenhouse gas emissions target for 2060 and Vision 2030’s sustainability agenda. Despite the progressive introduction of the Saudi Building Code (SBC) energy chapters SBC 601, SBC 602, and the Saudi Green Building Code (SgBC 1001), a persistent gap remains between regulatory intent and measurable outcomes across Saudi Arabia’s five distinct climatic zones. Building codes are, by design, generic policy instruments encompassing structural, fire, accessibility, and energy provisions; this paper focuses specifically on the energy and sustainability dimensions and critically examines how the SBC’s update cycle and prescriptive compliance architecture shape actual performance outcomes. This study presents three explicit research questions: (RQ1) What zone-differentiated energy savings does SBC implementation deliver across residential typologies? (RQ2) How does the Mostadam national rating system compare with international benchmarks in the Saudi context, and what caveats govern that comparison? (RQ3) What evidence-based policy interventions are needed to transition from compliance-led to performance-led building energy governance? Drawing on a systematic synthesis of 53 building energy simulation models (2018–2025), official programme data, and a structured comparative analysis of Mostadam against LEED v4.1 and BREEAM, the study finds EUI reductions of 5–25% from SBC compliance, with the largest savings in the hot–humid coastal zone. Seven prioritised policy recommendations are proposed, addressing code revision, financial incentives, digital monitoring, renewable energy thresholds, and capacity building. Full article

Background: Physical inactivity and sedentary behaviour are major public health concerns associated with an increased risk of non-communicable diseases, reduced quality of life, and substantial healthcare burden. In recent years, technology-based interventions, including wearable devices, mobile health applications, artificial intelligence-driven systems, and adaptive digital platforms, have been increasingly adopted to promote physical activity and reduce sedentary time in adult populations. However, the evidence remains fragmented across intervention types, behavioural targets, and population groups. The aim of this scoping review was to map the recent literature on digital interventions designed to promote active lifestyles in adults, with a specific focus on their reported impact on physical activity promotion and sedentary behaviour reduction. Methods: This scoping review was conducted in accordance with the PRISMA-ScR guidelines. A literature search was performed in PubMed and Scopus using a predefined search strategy combining terms related to digital technologies, physical activity, sedentary behaviour, and adult populations. Studies published in English between 2022 and 2026 were considered. After removal of duplicates and screening of titles and abstracts, full texts were assessed according to predefined eligibility criteria. Data were charted descriptively and synthesised narratively to identify the main intervention models and emerging research trends. Results: The search identified 887 records, of which 35 studies were included in the final synthesis. The literature included was grouped into four broad categories: wearable devices and mHealth tools for monitoring and goal-setting; adaptive interventions based on Just-In-Time Adaptive Interventions, artificial intelligence, and gamification; advanced technologies such as Internet of Things systems and exoskeleton-based approaches; and hybrid interventions combining digital tools with human support or environmental modifications. Overall, technology-based interventions were generally associated with increases in step count, moderate-to-vigorous physical activity, and adherence to movement-related behaviours. In contrast, their effectiveness in reducing sedentary behaviour was less consistent and appeared to depend more strongly on context-sensitive prompting, posture-focused strategies, and multicomponent or hybrid intervention models. Conclusions: Digital health interventions represent a promising strategy for promoting physical activity in adults, but their impact on sedentary behaviour reduction remains more limited and heterogeneous. The findings suggest that simply increasing exercise is not sufficient to address prolonged sitting and that more tailored, adaptive, and context-aware approaches are needed. Future research should prioritise methodological standardisation, longer follow-up periods, and interventions specifically designed to interrupt sedentary time across different adult populations. Full article

Objectives: Contrast-enhanced magnetic resonance imaging (CE-MRI) plays an important role in the diagnosis, treatment monitoring, and follow-up of brain tumors. However, the use of gadolinium-based contrast agents (GBCAs) is limited in patients with contraindications, such as severe renal impairment or situations requiring repeated examinations. This study aimed to develop a diffusion model-based Difference-Aware Guided Control Network (DAGCN) for synthesizing high-quality contrast-enhanced T1-weighted MRI (T1-CE) from non-contrast T1-weighted images in combination with an auxiliary sequence. Methods: Using the BraTS 2021 dataset, we proposed a two-stage generative framework that first localizes lesion-related enhancement cues and then guides image synthesis. In the first stage, a Difference-Aware Fusion and Prediction (DAFP) module was designed to extract complementary information from non-contrast T1-weighted images and an auxiliary sequence (T2-weighted or FLAIR) through dual-branch feature extraction and cross-modal channel attention fusion, followed by prediction of a lesion-related discrepancy map. In the second stage, the predicted discrepancy map was concatenated with the original T1-weighted images and introduced into a ControlNet-guided diffusion model to constrain the reverse denoising process and generate the target T1-CE image. Model performance was evaluated by visual comparison, quantitative metrics including peak signal-to-noise ratio (PSNR), structural similarity index measure (SSIM), visual information fidelity (VIF), and normalized cross-correlation (NCC), as well as blinded radiologist scoring of image quality (IQ), clinical replaceability (IC), contrast enhancement (CE), and lesion conformity (CF). Results: DAGCN generated synthetic T1-CE images with preserved global anatomical structure and faithful local lesion enhancement without the need for contrast agent administration. Compared with baseline methods, DAGCN achieved the highest PSNR and NCC under both T1 + T2 and T1 + FLAIR settings, while showing competitive SSIM and VIF performance. Visual comparison and radiologist-based subjective evaluation further indicated improved lesion-focused enhancement fidelity and reduced false-positive enhancement. Among the two auxiliary sequence settings, the T1 + FLAIR configuration provided more specific lesion localization and cleaner background suppression than the T1 + T2 configuration, particularly by reducing interference from cerebrospinal fluid signals. Conclusions: The proposed DAGCN framework enables the synthesis of clinically informative contrast-enhanced-like MRI from non-contrast multi-sequence inputs and may provide a promising alternative for patients in whom gadolinium administration is contraindicated or should be avoided. In particular, the FLAIR-guided setting showed advantages in lesion specificity, background cleanliness, and overall diagnostic quality. Full article

This work focuses on rapid, catalyst-free synthesis of a new series of acetylenic phosphonates as promising building blocks for creating antiviral and anticancer agents. A comprehensive assessment of the biological activity of the synthesized compounds was conducted. Dialkyl phosphonates 4d, 4e, and 4g were found to exhibit pronounced antiproliferative activity against human cancer cell lines, with the greatest IC₅₀ = 6 μg/mL against the K562 cell line. Further studies revealed that these compounds cause significant disorganization of the actin cytoskeleton, leading to the loss of stress fibers and reduced cell motility. In contrast, diamide derivatives demonstrated a more favorable safety profile, with low cytotoxicity and moderate antiviral activity against influenza A (H1N1) virus, among which compound 6b achieved a selectivity index of 5 with IC₅₀ = 56.9 μg/mL. Screening studies of both dialkyl and diamide acetylenic phosphonates revealed some features of the interaction with kinase and nonkinase targets used for drug development and provide a basis for the subsequent rational design of novel selective anticancer agents based on the acetylenic phosphonate scaffold. Full article

Development of sustainability systems for assessment of environmental impacts remains a paramount challenge for green and circular manufacturing of polymers. In this study, a comprehensive life cycle assessment (LCA) framework is developed for European polymeric waste by integrating OpenLCA, Ecoinvent v3.11, and Python-based machine learning (ML) algorithms. Cradle-to-gate, service-life, and cradle-to-grave assessments are performed for representative thermoplastic composite systems, including PP–PET–cotton, HDPE–glass fiber, and PEEK–carbon fiber composites, covering domestic, engineering, and high-performance polymer categories. The results demonstrate that raw material extraction and manufacturing stages dominate environmental impacts, contributing the highest shares to climate change, ecotoxicity, and non-renewable energy consumption. PP-based composite systems exhibit the lowest overall environmental burdens due to lower processing energy and simpler molecular structures, while HDPE-based systems show moderate impacts. PEEK-based composites present the highest impacts per unit mass, driven by energy-intensive synthesis and high processing temperature. Environmental impacts are evaluated using EF v3.1 and ReCiPe methodologies, supported by Monte Carlo simulations and ML-assisted uncertainty quantification. Monte Carlo simulations and ML-assisted LCA provide probabilistic ranges, uncertainty quantification, and predictive insights into impact indicators, enabling the development of a quantitative sustainability system based on probability–impact relationships. A Europe-wide assessment of 57 Mt of polymeric waste highlights that environmental burdens are concentrated in countries with high polymer production and consumption, emphasizing the importance of energy mix, recycling efficiency, and waste management strategies. Overall, this work demonstrates that digitalized LCA coupled with ML offers a powerful decision-support framework for sustainable polymer design, recycling optimization, and circular economy policy development, supporting the transition toward low-carbon and resource-efficient polymer systems in Europe. Full article

Airports, as Critical National Infrastructure (CNI), operate as tightly coupled socio-technical systems exposed to multifaceted threats, including cyber, physical, social, environmental, and Chemical, Biological and Radiological (CBR) threats. This study presents a structured review of the synthesis of conceptual frameworks, airport structural configurations, sensor networks, and multi-domain threat landscapes, as well as airport security and resilience analysis, while comparatively examining risk assessment approaches. The review shows that existing approaches are effective for threat identification and prioritisation but remain predominantly static, with limitations in scalability, data dependency, and real-time applicability. To address these limitations, Threat-Vulnerability-Risk Assessment (TVRA) is adopted as a structured, reusable approach to support metric allocation, redundancy design, and emergency capability development. It further serves as a bridge between traditional risk assessment and resilience-oriented system design by enabling the transformation of static risk scores into scenario-based inputs, thereby supporting stress-testing and lifecycle-based resilience planning across the prepare, act, and recover phases. However, its inherently static structure limits its ability to capture temporal dynamics and cascading interdependencies, highlighting the need to integrate it with dynamic modelling approaches. Full article