Search Results (1,752)

The transition to a decarbonised energy system in Ireland presents significant socio-technical challenges. This paper, focused on the work of the SMARTLAB project at the Citizen Innovation Lab in Limerick city, investigated the potential of a localised living lab approach to address these challenges. Engaging across 70 buildings and their inhabitants, the project captured the evolution of attitudes and intentions towards the clean energy transition in ways directly relevant to future policy implementation across grid redevelopment, smart service design, and national retrofit. Project methodology was framed by a living lab approach, with wireless energy and indoor environment sensors installed in participant buildings and participant journeys developed by harnessing the Citizen Innovation Lab ecosystem. The results indicate behaviour changes among participants, particularly focusing on indoor environmental conditions. The study concludes that embedded, localised living labs offer a methodological framework which can capture diverse datasets and encompass complex contemporary contexts towards transition goals. Full article

Tumor immunotherapy has revolutionized cancer treatment by harnessing the immune system to recognize and eliminate malignant cells, with immune checkpoint inhibitors targeting programmed death receptor 1 (PD-1), programmed death-ligand 1 (PD-L1), and cytotoxic T-lymphocyte-associated protein-4 (CTLA-4) demonstrating remarkable clinical success. However, challenges such as treatment resistance, immune-related adverse effects, and high costs highlight the need for novel therapeutic approaches. Aptamers, short, single-stranded oligonucleotides with high specificity and affinity for target molecules, have emerged as promising alternatives to conventional antibody-based therapies. This review provides a comprehensive analysis of aptamer-based strategies targeting immune checkpoints, with a particular focus on PD-1/PD-L1 and CTLA-4. We summarize recent advances in aptamer design, including bispecific and multifunctional aptamers, and explore their potential in overcoming immune resistance and improving therapeutic efficacy. Additionally, we discuss strategies to enhance aptamer stability, bioavailability, and tumor penetration through chemical modifications and nanoparticle conjugation. Preclinical and early clinical studies have demonstrated that aptamers can effectively block immune checkpoint pathways, restore T-cell activity, and synergize with other immunotherapeutic agents to achieve superior anti-tumor responses. By systematically reviewing the current research landscape and identifying key challenges, this review aims to provide valuable insights into the future directions of aptamer-based cancer immunotherapy, paving the way for more effective and personalized treatment strategies. Full article

In the era of rapid industrial automation advancements, the complexity of intelligent manufacturing equipment has been steadily escalated. Stringent demands for high-efficiency and high-precision diagnosis are increasingly being unmet by conventional fault diagnosis methods. To address these challenges, a novel fault diagnosis approach grounded in quantum Q-learning is presented in this paper. The distinct advantages of quantum computing are innovatively integrated with the decision-making framework of Q-learning through this method. By harnessing the multi-information-carrying capacities of qubits, vast amounts of multi-source heterogeneous data generated during equipment operation can be efficiently processed. Latent fault features are thereby rapidly uncovered, significantly reducing the time required for fault-feature extraction. Furthermore, optimal decisions can be dynamically formulated by Q-learning within evolving production environments, leveraging precise analysis outcomes from quantum computing. Real-time equipment status is continuously monitored to accurately identify fault types, pinpoint locations, and promptly generate targeted maintenance strategies. Fault-diagnosis tests conducted on typical industrial intelligent manufacturing equipment demonstrate that the quantum Q-learning method outperforms traditional approaches in terms of diagnosis accuracy, efficiency, and adaptability to complex fault patterns. This breakthrough opens up new frontiers for fault diagnosis in intelligent manufacturing systems. Full article

Indigenous students remain significantly underrepresented in medical education, contributing to persistent health inequities in their communities. Systemic barriers, including cultural isolation, inadequate resources, and biased curricula, hinder their success. But what if generative artificial intelligence (GAI) could be the game-changer? This scoping review explores the potential of generative artificial intelligence (GAI) in making medical education more inclusive and supportive for Indigenous students through a comprehensive analysis of existing literature. From AI-powered engagement platforms to personalised learning systems and immersive simulations, GAI can be harnessed to bridge the gap. While GAI holds promise, challenges like biased datasets and limited access to technology must be addressed. To unlock GAI’s potential, we recommend faculty development, expansion of digital infrastructure, and Indigenous-led AI design. By carefully harnessing GAI, medical schools can take a crucial step towards creating a more diverse and equitable healthcare workforce, ultimately improving health outcomes for Indigenous communities. Full article

Harnessing abundant and renewable solar energy for photocatalytic hydrogen production is a highly promising approach to sustainable energy generation. To realize the practical implementation of such systems, the development of photocatalysts that simultaneously exhibit high activity, cost-effectiveness, and long-term stability is critically important. In this study, a Cd_0.8Zn_0.2S nanowire photocatalytic system decorated with graphene (GR) was prepared by a simple hydrothermal method. The introduction of graphene increased the reaction active area of Cd_0.8Zn_0.2S, promoted the separation of photogenerated charge carriers in the semiconductor, and improved the photocatalytic performance of the Cd₀.₈Zn₀.₂S semiconductor. The results showed that Cd_0.8Zn_0.2S loaded with 5% graphene exhibited the best photocatalytic activity, with a hydrogen production rate of 1063.4 µmol·g⁻¹·h⁻¹. Characterization data revealed that the graphene cocatalyst significantly enhances electron transfer kinetics in Cd₀.₈Zn₀.₂S, thereby improving the separation efficiency of photogenerated charge carriers. This study demonstrates a rational strategy for designing high-performance, low-cost composite photocatalysts using earth-abundant cocatalysts, advancing sustainable hydrogen production. Full article

Ancient grains, including wild rice, millet, fonio, teff, quinoa, amaranth, and sorghum, are re-emerging as vital components of modern diets due to their dense nutritional profiles and diverse health-promoting bioactive compounds. Rich in high-quality proteins, dietary fiber, essential micronutrients, and a broad spectrum of bioactive compounds such as phenolic acids, flavonoids, carotenoids, phytosterols, and betalains, these grains exhibit antioxidant, anti-inflammatory, antidiabetic, cardioprotective, and immunomodulatory properties. Their health-promoting effects are underpinned by multiple interconnected mechanisms, including the reduction in oxidative stress, modulation of inflammatory pathways, regulation of glucose and lipid metabolism, support for mitochondrial function, and enhancement of gut microbiota composition. This review provides a comprehensive synthesis of the essential nutrients, phytochemicals, and functional properties of ancient grains, with particular emphasis on the nutritional and molecular mechanisms through which they contribute to the prevention and management of chronic diseases such as cardiovascular disease, type 2 diabetes, obesity, and metabolic syndrome. Additionally, it highlights the growing application of ancient grains in functional foods and nutrition-sensitive dietary strategies, alongside the technological, agronomic, and consumer-related challenges limiting their broader adoption. Future research priorities include well-designed human clinical trials, standardization of compositional data, innovations in processing for nutrient retention, and sustainable cultivation to fully harness the health, environmental, and cultural benefits of ancient grains within global food systems. Full article

This narrative review explores the intricate relationship between the plasminogen activator system (PAS), comprising urokinase-type plasminogen activator (uPA) and tissue-type plasminogen activator (tPA), and a range of neuropsychiatric disorders, including depression and anxiety. By synthesizing existing preclinical and clinical evidence, we clarify the roles of uPA and tPA in the pathogenesis and potential treatments of these conditions. This narrative review emphasizes their involvement in modulating neuronal plasticity, synaptic remodeling, and neurotransmitter systems, which are pivotal in maintaining brain function and behavior. Additionally, this review highlights key mechanisms by which these activators influence the neurobiological processes underlying mood and cognitive dysfunction. Critical analysis identifies areas of consensus, such as the role of plasminogen activators in neuroinflammation and stress responses, while also addressing gaps and controversies in the literature. The findings underscore the therapeutic potential of targeting the uPA/tPA system for innovative interventions. By offering a nuanced understanding of their contributions to mood disorders, this review aims to inspire future research toward developing novel, mechanism-based treatment strategies that harness the PAS’ capacity to restore neural homeostasis and improve patient outcomes. Full article

Protein-polyphenol-based delivery vehicles are effective strategies for encapsulating bioactive compounds, thereby enhancing their solubility and bioaccessibility. In this study, dihydromyricetin/soy protein isolate (DHM/SPI) complexes were used as emulsifiers to prepare Pickering emulsions for DHM delivery. The results show that DHM and SPI form negatively charged complexes through hydrogen bonding, and the complex size decreases and stabilizes with increasing DHM addition. The size of the emulsion droplets was inversely related to the concentration of DHM addition (c), particle concentration (w), and ionic strength (i). Conversely, the increasing oil phase concentration (φ) was positively correlated with droplet size. The CLSM results confirmed the expected oil-in-water emulsion, while the rheological behavior of the Pickering emulsion highlighted its elastic, gel-like network structure and non-Newtonian fluid properties. Moreover, DHM effectively slowed lipid oxidation in the emulsion, and the bioaccessibility of DHM reached 33.51 ± 0.31% after in vitro simulated digestion. In conclusion, this emulsion system shows promising potential for delivering DHM and harnessing its bioactive effects. Full article

Oral squamous cell carcinoma (OSCC), an aggressive and poorly prognosed subtype of head and neck squamous cell carcinoma (HNSCC), has prompted urgent calls for innovative therapeutic approaches. Evodiamine (EVO), a natural alkaloid extracted from the Chinese herb Evodia rutaecarpa, has demonstrated significant potential in curbing tumor cell proliferation and slowing tumor expansion. However, its specific effects on cell senescence within the context of OSCC have remained shrouded in uncertainty. This study delves into the mechanisms of EVO’s impact on OSCC by harnessing databases such as the Traditional Chinese Medicine Systems Pharmacology Database and Analysis Platform (TCMSP), The Cancer Genome Atlas (TCGA), the Gene Expression Omnibus (GEO), and CellAge to pinpoint potential targets and carry out in-depth bioinformatics analysis. The findings reveal that EVO can markedly enhance the expression of the androgen receptor (AR) in OSCC cells, inducing cellular senescence and thereby inhibiting tumor progression. Furthermore, the research indicates that AR expression is considerably lower in OSCC tissues than in normal tissues. This low expression of AR in tumor tissues is closely associated with advanced clinical stages and unfavorable prognoses in HNSCC patients. These discoveries open up new avenues for therapeutic strategies, and suggest that AR holds promise as a potential therapeutic target for OSCC, and EVO may amplify its antitumor effects by enhancing AR-mediated cellular senescence in the treatment of OSCC. Full article

Policies and technical safeguards for artificial intelligence (AI) governance have implicitly assumed that AI systems will continue to operate via massive power-hungry data centers operated by large companies like Google and OpenAI. However, the present cloud-based AI paradigm is being challenged by rapidly advancing software and hardware technologies. Open-source AI models now run on personal computers and devices, invisible to regulators and stripped of safety constraints. The capabilities of local-scale AI models now lag just months behind those of state-of-the-art proprietary models. Wider adoption of local AI promises significant benefits, such as ensuring privacy and autonomy. However, adopting local AI also threatens to undermine the current approach to AI safety. In this paper, we review how technical safeguards fail when users control the code, and regulatory frameworks cannot address decentralized systems as deployment becomes invisible. We further propose ways to harness local AI’s democratizing potential while managing its risks, aimed at guiding responsible technical development and informing community-led policy: (1) adapting technical safeguards for local AI, including content provenance tracking, configurable safe computing environments, and distributed open-source oversight; and (2) shaping AI policy for a decentralized ecosystem, including polycentric governance mechanisms, integrating community participation, and tailored safe harbors for liability. Full article

Introduction: Liver transplantation remains the definitive treatment for end-stage liver disease but faces critical challenges including organ shortages and preservation difficulties, particularly with extended criteria donor (ECD) grafts. Hypothermic machine perfusion (HMP) represents a promising alternative to traditional static cold storage (SCS). Methods: This retrospective study analyzed outcomes from 62 liver transplant recipients between 2016 and 2025, comparing 8 grafts preserved by HMP using the Liver Assist^® system and 54 grafts preserved by SCS. Parameters assessed included postoperative complications, hemodynamic stability, ischemia times, and survival outcomes. Results: HMP significantly reduced surgical (0% vs. 75.9%, p = 0.01) and biliary complications (0% vs. 34.4%, p = 0.004), improved hemodynamic stability post-reperfusion (∆MAP%: 1 vs. 21, p = 0.006), and achieved superior one-year survival rates (100% vs. 84.4%). Despite longer ischemia periods, grafts treated with HMP exhibited fewer adverse effects from ischemia-reperfusion injury. Discussion: These findings highlight the substantial benefits of HMP, particularly in improving graft quality from marginal donors and reducing postoperative morbidity. Further adoption of this technology could significantly impact liver transplantation outcomes by expanding the viable donor pool. Conclusions: The study underscores the effectiveness of hypothermic machine perfusion (HMP) as a superior preservation method compared to traditional static cold storage (SCS), HMP appears to be associated with improved short-term outcomes in liver transplantation. By substantially reducing postoperative complications and enhancing graft viability, HMP emerges as a pivotal strategy for maximizing the use of marginal donor organs. Further research and broader clinical implementation are recommended to validate these promising results and to fully harness the potential of HMP in liver transplantation. Full article

Achieving sustainable economic growth requires a careful balance between public debt accumulation and the macroeconomic stability necessary for long-term development. While public debt can support growth through productive public investment, excessive debt may crowd out private investment, raise borrowing costs, and undermine financial stability, ultimately threatening economic sustainability. In this context, the quality of institutions plays a pivotal moderating role by fostering responsible debt management and ensuring that debt-financed investments contribute to sustainable development. In this context, this study investigates the relationship between public debt and economic growth, with a focus on the moderating role of institutional quality (IQ). Utilizing an unbalanced panel of 115 countries over the period from 1996 to 2021, this study tests the hypothesis that robust institutional frameworks mitigate the negative impact of public debt on economic growth. To address potential endogeneity, this study employs the dynamic system Generalized Method of Moments (GMM) estimation technique. The results reveal that, although the direct effect of public debt on economic growth is negative, the interaction between public debt and IQ yields a positive influence. Furthermore, the results indicate the presence of a threshold beyond which public debt begins to exert a beneficial effect on economic growth, whereas its impact remains adverse below this threshold. These findings underscore the critical importance of sound debt management strategies and institutional development for policymakers, suggesting that effective government governance is essential to harnessing the potential positive effects of public debt on economic growth. Full article

Against the backdrop of the increasing penetration rate of new energy year by year, power systems face a continuously growing demand for flexibility. Under the structure of such a new power system, it is essential not only to introduce diverse flexible power sources but also to explore the flexible regulation capabilities of existing conventional power sources. To fully utilize the flexibility of thermal power units (TPUs), this study proposes a real-time optimal scheduling strategy for a wind–thermal energy-storage integrated system with an adaptive time division and variable objectives. Based on the evaluation results of the real-time flexible supply–demand relationship within a regional power grid, the operation modes of TPUs are categorized into three types: economic mode, peak shaving mode, and coordination mode. For each operation mode, corresponding optimization objectives are defined, and an energy storage control strategy is developed to assist in the peak shaving of TPUs. While effectively harnessing the flexibility of TPUs, the proposed method reduces both the frequency and capacity of TPUs entering deep peak shaving. Using data from a province in Northwest China as a case study, simulation calculations and analyses demonstrate that the proposed method increases renewable energy consumption by 314.37 MWh while decreasing system economic benefits by CNY 129,000. Compared with traditional scheduling methods for TPUs to accommodate renewable energy, the system benefit increases by CNY 297,000, and an additional 13.53 MWh of peak wind power is accommodated. These results confirm that the proposed scheduling strategy can significantly enhance the system’s ability to integrate new energy while maintaining its economic efficiency. Full article

Microbial fuel cells (MFCs) are bio-electrochemical systems that harness microorganisms to convert organic pollutants in wastewater directly into electricity, offering a dual solution for sustainable wastewater treatment and renewable energy generation. This paper presents a holistic techno-economic and environmental feasibility assessment of large-scale MFC deployment in Dhaka’s industrial zone, Bangladesh, as a relevant case study. Here, treating 100,000 cubic meters of wastewater daily would require a capital investment of approximately USD 500 million, with a total project cost ranging between USD 307.38 million and 1.711 billion, depending on system configurations. This setup has an estimated theoretical energy recovery of 478.4 MWh/day and a realistic output of 382 MWh/day, translating to a per-unit energy cost of USD 0.2–1/kWh. MFCs show great potential for treating wastewater and addressing energy challenges. However, this paper explores remaining challenges, including high capital costs, electrode and membrane inefficiencies, and scalability issues. Full article

Thylakoid-based photosynthetic biofuel cells (TBFCs) harness the inherent light-driven electron transfer pathways of photosynthesis to enable sustainable solar-to-electrical energy conversion. While TBFCs offer a unique route toward biohybrid energy systems, their practical deployment is hindered by sluggish electron transfer kinetics, unstable redox mediators, and inefficient interfacing between biological and electrode components. This review critically examines recent advances in TBFCs, with a focus on three key surface engineering strategies: (i) incorporation of nanostructured materials to enhance electrode conductivity and surface area; (ii) application of redox mediators to facilitate charge transfer between photosynthetic proteins and electrodes; and (iii) functional exploitation of individual thylakoid components, including Photosystem I (PSI) and Photosystem II (PSII), to augment photogenerated current output. By systematically evaluating current advancements, this review highlights the synergistic role of materials and biological components in advancing TBFC technology and offers insights into next generation biohybrid solar energy systems with enhanced efficiency and scalability. Full article