Search Results (1,151)

Parkinson’s disease (PD) is a complex neurodegenerative disorder characterised by progressive motor and non-motor impairment, in which current therapies remain symptomatic and fail to halt dopaminergic neuron loss. Growing evidence linking metabolic dysfunction, type 2 diabetes, and neurodegeneration has renewed interest in glucagon-like peptide 1 (GLP-1) receptor agonists as potential disease-modifying agents. While several recent reviews have explored the role of incretin-based therapies, the present work provides an integrative perspective by combining a mechanistic analysis of GLP-1 signalling pathways with a model-specific synthesis of preclinical findings and an appraisal of clinical translational relevance. We consolidate evidence across PI3K/Akt, MAPK/ERK, cAMP/PKA–CREB, and AMPK pathways, emphasising their convergence on mitochondrial homeostasis, proteostasis, neuroinflammation, and synaptic resilience. To enhance translational clarity, we summarise preclinical studies across major PD models, evaluate dose comparability and blood–brain barrier penetration, and identify pharmacokinetic and mechanistic factors that may explain divergent clinical outcomes. We also compare the therapeutic potential of key GLP-1 agonists, including exendin-4, liraglutide, semaglutide, lixisenatide, and emerging dual agonists. By integrating biochemical, preclinical, and clinical domains, this review provides a comprehensive framework for interpreting the current evidence and guiding the future development of incretin-based neuroprotective strategies in PD. Full article

Chemical warfare agents (CWAs) threaten peace and global security due to their extreme toxicity and devastating effects. Prompt discovery and detoxification are imperative to protect ourselves from these perilous agents. Metal–organic frameworks (MOFs), characterized by high specific surface areas, tunable porosities, and chemical stability, have attracted growing interest for the catalytic degradation of CWAs. However, the powder form of MOFs hinders their application in protection, and it is challenging to combine them with flexible carriers to protect humans. In this context, we provide an update on the recent development of MOF textile materials for the efficient degradation of CWAs. The research progress on different technologies for the catalytic degradation of CWAs and their simulants in MOF textiles in recent years is presented. Furthermore, challenges in developing MOF textiles for the catalytic degradation of CWAs and their simulants are highlighted. It is expected that these useful insights will be beneficial in constructing relevant MOF textiles for the degradation of CWAs. Full article

This paper investigates how the “Gastro Local” network in Brașov County, Romania, contributes to regional brand development by digitally communicating local gastronomic and cultural values. One hundred eighty social media posts created by Local Gastronomic Points (LGPs) were analyzed using a directed content analysis grounded in the Memorable Gastronomic Experience (MGE) and Online Destination Brand Experience (ODBE) frameworks. Results suggest that LGPs construct dense multimodal narratives combining gastronomic, environmental, emotional, and temporal cues, indicating that rural digital storytelling relies on layered experiential configurations. Hedonism, Local Culture, and Relaxation dominate experiential communication, while sensory and spatio-temporal cues structure online brand expression. Co-occurrence patterns and correspondence analysis indicate two potential branding logics: a sensory–hedonic strategy centred on visual pleasure, and an affective–symbolic contextual strategy anchored in heritage and rural temporality. The study contributes an integrated MGE × ODBE analytical model and suggests how small-scale food providers act as decentralized branding agents, supporting aspects of sustainable and authenticity-driven regional identity-building within this specific context. Full article

The proliferation of terrestrial and space-based communication systems introduces significant radio frequency interference (RFI), which severely compromises data acquisition for radio telescopes, necessitating robust and dynamic scheduling solutions. This study addresses this challenge by implementing a Deep Recurrent Reinforcement Learning (DRL) framework for the control and dynamic scheduling of the X-Y pedestal-mounted KMITL radio telescope, explicitly trained for RFI avoidance. The methodology involved developing a custom simulation environment with a domain-specific Convolutional Neural Network (CNN) feature extractor and a Long Short-Term Memory (LSTM) network to model temporal dynamics and long-horizon planning. Comparative evaluation demonstrated that the recurrent DRL agent achieved a mean effective survey coverage of 475 deg²/h, representing a 72.7% superiority over the non-recurrent baseline, and maintained exceptional stability with only 1.0% degradation in median coverage during real-world deployment. The DRL framework offers a highly reliable and adaptive solution for telescope scheduling that is capable of maintaining survey efficiency while proactively managing dynamic RFI sources. Full article

Cellular receptor recognition exerts fundamental roles during coronavirus infection. Clarifying the regulatory mechanism of virus receptor helps to better understand viral infection, transmission and pathogenesis; predict potential host and how viral escape from immune system; prevent coronavirus infection or develop treatment therapy. Herein, we summarize current understanding of host receptor recognition mechanisms in the different genera of coronavirus family. And we also review diverse methodologies of identification and clarification of virus receptors. The integration of structural biology, multi-omics, computational predictions, synthetic biology and artificially engineered viral receptors, provide a powerful framework for elucidating coronavirus–receptor interactions. This also supports the development of broad-spectrum antiviral agents, smart biosensors, and intervention strategies against emerging coronaviruses. Full article

Fault diagnosis methods based on deep learning have made certain progress in recent years. However, in actual industrial scenarios, there are severe strong background noise and limited computing resources, which poses challenges to the practical application of fault diagnosis models. In response to the above issues, this paper proposes a novel noise-resistant and lightweight fault diagnosis framework with nonlinear timestep degenerative greedy strategy (NTDGS) and dual residual horizontal feature pyramid (DRHFPN) for fault diagnosis in strong noise scenarios. This method takes advantage of the strong fitting ability of deep learning methods to model the agent in reinforcement learning by the ways of parameterization, fully leveraging the advantages of both deep learning and reinforcement learning methods. NTDGS is further developed to adaptively adjust the action sampling strategy of the agent at different training stages, improving the convergence speed of the network. To enhance the noise resistance of the network, DRHFPN is constructed, which can filter out interference noise at the feature map level by fusing local feature details and global semantic information. Furthermore, the feature map weighting attention mechanism (FMWAM) is designed to enhance the weak feature extraction ability of the network through adaptive weighting of the feature maps. Finally, the performance of the proposed method is evaluated in different datasets and strong noise environments. Experiments show that in various fault diagnosis scenarios, the proposed method has better noise resistance, higher fault diagnosis accuracy, and fewer parameters compared to other methods. Full article

The escalating global demand for energy-efficient and sustainable built environments has catalyzed the advancement of Building Energy Management Systems (BEMSs), particularly through their integration with cutting-edge technologies. This review presents a comprehensive and critical synthesis of the convergence between BEMSs and enabling tools such as the Internet of Things (IoT), wireless sensor networks (WSNs), and artificial intelligence (AI)-based decision-making architectures. Drawing upon 89 peer-reviewed publications spanning from 2019 to 2025, the study systematically categorizes recent developments in HVAC optimization, occupancy-driven lighting control, predictive maintenance, and fault detection systems. It further investigates the role of communication protocols (e.g., ZigBee, LoRaWAN), machine learning-based energy forecasting, and multi-agent control mechanisms within residential, commercial, and institutional building contexts. Findings across multiple case studies indicate that hybrid AI–IoT systems have achieved energy efficiency improvements ranging from 20% to 40%, depending on building typology and control granularity. Nevertheless, the widespread adoption of such intelligent BEMSs is hindered by critical challenges, including data security vulnerabilities, lack of standardized interoperability frameworks, and the complexity of integrating heterogeneous legacy infrastructure. Additionally, there remain pronounced gaps in the literature related to real-time adaptive control strategies, trust-aware federated learning, and seamless interoperability with smart grid platforms. By offering a rigorous and forward-looking review of current technologies and implementation barriers, this paper aims to serve as a strategic roadmap for researchers, system designers, and policymakers seeking to deploy the next generation of intelligent, sustainable, and scalable building energy management solutions. Full article

Seed coating, which involves the application of materials such as nutrients, growth regulators, and protective agents, can significantly enhance seed germination. This review introduces and assesses a paradigm shift in seed technology: the conceptualization of seed coatings as engineered biofilm micro-habitats. This approach moves beyond mere physical protection and chemical delivery by utilizing the coating matrix to host beneficial microbial consortia that form functional biofilms, thereby creating the potential for a dynamic, living interface at the seed–root junction. Furthermore, guided by perspectives from chemistry biology, we synthesize design principles for these micro-habitats at a systems level. Within this framework, we demonstrate their potential to enhance crop growth, stress resilience, and pathogen suppression. By framing seed coating as a dynamic microbial environment, this review aims to guide future research and development toward ecology-driven seed enhancement strategies. Full article

Neurological disorders and cardiovascular disease (CVD) remain leading causes of global morbidity and mortality and often coexist, in part through shared mechanisms of chronic inflammation and oxidative stress. Neuroinflammatory signaling, including microglial activation, cytokine release, and impaired autonomic regulation, contributes to endothelial dysfunction, atherosclerosis, hypertension, and stroke, while cardiac and metabolic disturbances can reciprocally exacerbate brain pathology. Increasing evidence shows that several antidiabetic agents exert pleiotropic anti-inflammatory and antioxidant effects that extend beyond glycemic control. Metformin, SGLT2 inhibitors, DPP-4 inhibitors, and GLP-1 receptor agonists modulate key pathways such as AMPK, NF-κB, Nrf2 activation, and NLRP3 inflammasome suppression, with demonstrated vascular and neuroprotective actions in preclinical models. Clinically, GLP-1 receptor agonists and SGLT2 inhibitors reduce major cardiovascular events, improve systemic inflammatory markers, and show emerging signals for cognitive benefit, while metformin and DPP-4 inhibitors exhibit supportive but less robust evidence. This review synthesizes molecular, preclinical, and clinical data across drug classes, with particular emphasis on GLP-1 receptor agonists, and highlights outstanding translational questions including blood–brain barrier penetration, biomarker development, optimal patient selection, and timing of intervention. We propose a unified framework to guide future trials aimed at leveraging antidiabetic therapies such as DDP-4 anti-inflammatory and antioxidant interventions for neurological and cardiovascular diseases. Full article

Few studies have examined how formal and non-formal learning contexts can be systematically combined within teacher professional development, particularly in low- and middle-income country (LMIC) settings where non-formal education remains underdeveloped. This study addresses this gap by presenting the development and implementation of a Teacher–Lesson–School (TLS)-Based Personalized Teacher Professional Development model (PTPD-model) aimed at enhancing teachers’ functional and digital literacy as a prerequisite for fostering similar competencies among students. The novelty of the model lies in integrating formal subject-based instruction with non-formal school education (clubs, workshops, and project formats), positioning teachers not only as participants in formal Continuing Professional Development (CPD) courses but also as active agents of non-formal learning. The model draws upon international research frameworks, including the Programme for the International Assessment of Adult Competencies (PIAAC), the Teaching and Learning International Survey (TALIS), the Programme for International Student Assessment (PISA), the TLS approach, and the framework of Teacher Professional Development for Sustainable Development Goals (TPD for SDG). The study was conducted in 2023–2025 using a mixed, longitudinal, quasi-experimental design and a purposive sample (n= 80 teachers from 16 rural schools in Kazakhstan). A triangulated evaluation approach combined self-assessment and expert-based observations. The TLS-based PTPD model was implemented as a modular program with elements of coaching, personalization, and school-based projects. The findings demonstrate significant improvements in teachers’ digital and instructional competencies, lesson quality, and school-level engagement. This study provides one of the first systematic examinations of such integration in Central Asia, offering insights relevant to regional reforms, global education policy, and the achievement of Sustainable Development Goal 4.7 (SDG 4.7). Full article

Camellia oleifera, commonly known as oil-tea, serves as one of China’s most economically important oil crops. To ensure continued production yield and quality, biological control measures, operating within the framework of integrated pest management, have been extensively adopted nationwide. Integrated pest management facilitates effective management of arthropod pests afflicting C. oleifera by integrating biological control strategies with traditional chemical control methods. This approach significantly reduces the reliance on chemical pesticides and minimizes adverse environmental impacts. Over 600 natural enemy species targeting pests have been documented within the C. oleifera agroecosystems in China including approximately 38 viral agents along with 41 fungal, 166 parasitoid, 336 predator, and several bacterial species. Notably, both insectile natural enemies and fungal biopesticides derived from microbial resources are currently being used at scale in C. oleifera cultivation regions, serving as crucial alternatives to the use of conventional chemical pesticides. This paper comprehensively reviews recent progress in research and the application of synergistic integration of biological control with traditional pest management strategies for C. oleifera. The current status of research on natural enemy resources is analyzed and knowledge gaps in the domain of C. oleifera pest management are identified. Furthermore, future research trajectories are proposed that are intended to provide a scientific basis for the green and sustainable development of the C. oleifera industry. Full article

This study builds on a previously developed typo-morphological method used for the rural architecture of the “Capo Due Rami” area and tests its transferability to the northern sector of Sabaudia within the Pontine reclamation system. Beyond the historical, typological, and landscape dimensions explored earlier, this research adds a further analytical component focused on the relationship between settlement form and territorial planning. This extension represents the major methodological contribution of the study, allowing the repetitive structure of Opera Nazionale Combattenti farm units to be interpreted not only as a building system but also as an implicit territorial-planning device. The case study, located in the northern sector of Sabaudia, explores the relationships between the colonial settlements of the Opera Nazionale Combattenti (ONC), the agrarian framework, and the reclamation infrastructures, interpreting the repetition of settlement models as an implicit form of territorial planning. Using an integrated framework based on field surveys, archival materials, and multiscale cartographic analyses, the observation sheets show how architectural features, land-division schemes, and reclamation infrastructures are structurally interrelated. The results show that this new analytical dimension enhances the method’s interpretative capacity, highlighting the role of typological standardization in shaping the spatial and cultural structure of the reclaimed landscape. They reveal the morphological and functional consistency between architecture and landscape. Overall, the investigation confirms the coherence and replicability of the expanded approach. It shows that rural architecture is not only the material expression of a productive model but also an active agent in constructing and regulating the Pontine agrarian territory. Rural building emerges not only as the material outcome of a productive model but also as an active agent in shaping the agrarian territory. The research helps establish a comparative framework for interpreting Italian rural landscapes, supporting the valorization of vernacular heritage and reflection on the implicit planning principles embedded in typological architecture. Full article

To address the issue of sound absorption valleys in open-cell aluminum foam and enhance mid-to-high frequency (800–6300 Hz) performance, we developed a novel pore-penetrating 316L stainless steel fiber–aluminum foam (PPFCAF) composite using an infiltration method. The formation mechanism of the pore-penetrating fibers, the resultant pore-structure, and the accompanying sound absorption properties were investigated systematically. The PPFCAF was fabricated using 316L stainless steel fiber–NaCl composites created by an evaporation crystallization process, which ensured the full embedding of fibers within the pore-forming agent, resulting in a three-dimensional fiber-pore interpenetrating network after infiltration and desalination. Experimental results demonstrate that the PPFCAF with a porosity of 82.8% and a main pore size of 0.5 mm achieves a sound absorption valley value of 0.861. An average sound absorption coefficient is 0.880 in the target frequency range, representing significant improvements of 9.8% and 9.9%, respectively, higher than that of the conventional infiltration aluminum foam (CIAF). Acoustic impedance reveal that the incorporated fibers improve the impedance matching between the composite material and air, thereby reducing sound reflection. Finite element simulations further elucidate the underlying mechanisms: the pore-penetrating fibers influence the paths followed by air particles and the internal surface area, thereby increasing the interaction between sound waves and the solid framework. A reduction in the main pore size intensifies the interaction between sound waves and pore walls, resulting in a lower overall reflection coefficient and a decreased reflected sound pressure amplitude (0.502 Pa). In terms of energy dissipation, the combined effects of the fibers and refinement increase the specific surface area, thereby strengthening viscous effects (instantaneous sound velocity up to 46.1 m/s) and thermal effects (temperature field increases to 0.735 K). This synergy leads to a notable rise in the total plane wave power dissipation density, reaching 0.0609 W/m³. Our work provides an effective strategy for designing high-performance composite metal foams for noise control applications. Full article

Background and Clinical Significance: Tyrosine kinase inhibitors (TKIs) have transformed Philadelphia chromosome-positive chronic myeloid leukemia (Ph+ CML) into a largely manageable chronic disease. However, off-target toxicities are increasingly recognized; rarer complications such as bone marrow edema (BME) remain underreported. BME is a radiological syndrome characterized by excess intramedullary fluid on fat-suppressed T2/STIR magnetic resonance imaging sequences and may progress to irreversible osteochondral damage if unrecognized. We report a case series of TKI-associated BME and propose a practical diagnostic-therapeutic framework. Case Presentation: We describe three patients with Ph+ CML who developed acute, MRI-confirmed BME of the lower limb during TKI therapy. Case 1 developed unilateral then bilateral knee BME, temporally associated first with dasatinib and subsequently with imatinib; symptoms improved after TKI interruption, bisphosphonate therapy, and supportive measures, and did not recur after switching to bosutinib. Case 2 presented with proximal femoral BME during long-term imatinib; imatinib was stopped, intravenous neridronate administered, and bosutinib initiated with clinical recovery and later near-complete radiological resolution. Case 3 experienced multifocal foot and ankle BME during imatinib; symptoms resolved after drug discontinuation and bisphosphonate therapy, and disease control was re-established with bosutinib without recurrence of BME. All patients underwent molecular monitoring and mutational analysis to guide safe therapeutic switching. Discussion: Temporal association across cases and the differential kinase profiles of implicated drugs suggest PDGFR (and to a lesser extent, c-KIT) inhibition as a plausible mechanistic driver of TKI-associated BME. PDGFR-β blockade may impair pericyte-mediated microvascular integrity, increase interstitial fluid extravasation, and alter osteoblast/osteoclast coupling, promoting intramedullary edema. Management combining MRI confirmation, temporary TKI suspension, bone-directed therapy (bisphosphonates, vitamin D/calcium), symptomatic care, and, when required, therapeutic switching to a PDGFR-sparing agent (bosutinib) led to clinical recovery and preservation of leukemia control in our series. Conclusions: BME is an underrecognized, potentially disabling, TKI-related adverse event in CML. Prompt recognition with targeted MRI and a multidisciplinary, stepwise approach that includes temporary TKI adjustment, bone-directed therapy, and consideration of PDGFR-sparing alternatives can mitigate morbidity while maintaining disease control. Prospective studies are needed to define incidence, risk factors, optimal prevention, and management strategies. Full article

Modified tuber starches have gained relevance as innovative and versatile materials for the encapsulation of bioactive compounds, distinguishing themselves from synthetic polymers due to their biocompatibility, biodegradability, and tunable functionality. This review analyzes the effects of physical, chemical, and biochemical modifications on the composition and morphological, rheological, thermal, and techno-functional properties of tuber starches, as well as their development prospects as coating materials in encapsulation techniques such as spray drying, freeze-drying, electrospinning, and emulsification. The evidence reviewed indicates that modified tuber starches exhibit reduced retrogradation, higher thermal resistance, improved solubility, and better digestibility, facilitating their application as protective agents. The main challenges for their industrial implementation are identified and analyzed, including the standardization of processes, scalability, and the ambiguous regulatory framework. In the future, research in this area should be directed toward the optimization of “clean-label” methodologies and the valorization of non-conventional tuber sources, thereby consolidating the development of safer, more effective, and more sustainable encapsulation systems for the food industry. Full article