Search Results (5,977)

Valine-glutamine motif proteins (VQ), plant-specific transcriptional co-regulators harboring the conserved FxxhVQxhTG motif, play pivotal roles in coordinating plant stress adaptation through dynamic interactions with WRKY transcription factors (WRKY), mitogen-activated protein kinases (MAPKs) cascades, and hormone signaling pathways. Evolutionary analyses reveal the characteristics of their evolutionary protection and ancient origin, with lineage-specific expansion via genome duplication events. Structurally, compact genes lacking introns and the presence of intrinsic disordered regions (IDRs) facilitate rapid stress responses and versatile protein interactions. Functionally, VQ proteins orchestrate abiotic stress tolerance (e.g., drought, salinity, temperature extremes) by modulating reactive oxygen species (ROS) homeostasis, osmotic balance, and abscisic acid/salicylic acid (ABA/SA)-mediated signaling. Concurrently, they enhance biotic stress resistance via pathogen-responsive WRKY-VQ modules that regulate defense gene expression and hormone crosstalk. Despite advances, challenges persist in deciphering post-translational modifications, tissue-specific functions, and cross-stress integration mechanisms. Harnessing CRISPR-based editing and multi-omics approaches will accelerate the exploitation of VQ genes for developing climate-resilient crops. This review synthesizes the molecular architecture, evolutionary dynamics, and multifunctional regulatory networks of VQ proteins, providing a roadmap for their utilization in sustainable agriculture. Full article

Intelligent Transportation Systems (ITSs) aim to improve mobility and reduce congestion, yet current solutions still struggle with scalability, sensing bottlenecks, and inefficient computational resource usage. These limitations impede the shift towards environmentally responsible mobility. This work introduces ORQCIAM (Orchestrated Reasoning based on Quantum Computing and Intelligence for Advanced Mobility), a modular framework that combines Quantum Computing (QC) and Large Language Models (LLMs) to enable real-time, energy-aware decision-making in ITSs. Unlike conventional ITS or AI-based approaches that focus primarily on traffic performance, ORQCIAM explicitly incorporates sustainability as a design objective, targeting reductions in travel time, fuel or energy consumption, and CO₂ emissions. The framework unifies cognitive, virtual, and federated sensing to enhance data reliability, while a hybrid decision layer dynamically orchestrates QC–LLM interactions to minimize computational overhead. Scenario-based evaluation demonstrates faster incident screening, more efficient routing, and measurable sustainability benefits. Across tested scenarios, ORQCIAM achieved 9–18% reductions in travel time, 6–14% lower estimated CO₂ emissions, and around a 50–75% decrease in quantum-optimization calls by concealing QC activation during non-critical events. These results confirm that dynamic QC–LLM coordination effectively decreases computational overhead while supporting greener and more adaptive mobility patterns. Overall, ORQCIAM illustrates how hybrid QC–LLM architectures can serve as catalysts for efficient, low-carbon, and resilient transportation systems aligned with sustainable smart-city goals. Full article

Objectives: Intermittent fasting regimens that include periods of prolonged fasting may mimic certain well-documented benefits of calorie restriction. In this narrative review, we synthesize preclinical and human data on endocrine adaptations during prolonged fasting protocols. Methods: We conducted a structured search of relevant databases, followed by data extraction and synthesis, with a focus on endocrine adaptations during prolonged fasting and their potential implications for healthspan. Results: Across various endocrine axes, prolonged fasting appears to induce a reproducible pattern marked by diminished anabolic signaling and transient activation of potential stress resilience pathways. However, the evidence is limited by small sample sizes, short follow-up durations, methodological heterogeneity, and dependence on surrogate endpoints. Endocrine outcomes are frequently secondary and reported inconsistently. Potential risks include transient hypogonadism, relative hypothyroidism, hypercortisolemia, orthostatic intolerance, electrolyte imbalances, catabolic loss of lean mass, and refeeding challenges. Conclusions: Overall, prolonged fasting activates conserved endocrine mechanisms that may confer plausible cardiometabolic benefits; however, their translation to clinical practice remains speculative. We highlight key knowledge gaps and propose directions for future research in this emerging field. Full article

Lentil (Lens culinaris Medik. subsp. culinaris) is a Mediterranean legume crop of high value due to nutritional quality and adaptability; however, its cultivation is increasingly threatened due to climate uncertainty and reduction in genetic diversity in modern cultivars. The present research study evaluated 31 Greek lentil accessions (twenty-two landraces and nine commercial cultivars of both small and large seed types) in a semi-arid environment of Central Greece, over two cropping seasons, focusing on phenological, morphological, yield, and quality traits. The great diversity observed at the morpho-phenological and qualitative levels implies the high genotypic diversity of these genetic resources. Small-seeded landraces performed better in seed and biological yield, harvest index, and protein content, having greater phenological stability and tolerance to the Mediterranean environments. In particular, the highest seed yield was observed in LAX small-seeded landrace (1930 kg ha⁻¹), followed by TSO (1559 kg ha⁻¹), DIG (1449 kg ha⁻¹), and EGL (1437 kg ha⁻¹) small-seeded landraces. As for the regression analysis, seed yield was positively correlated with days to flowering (TF: r = 0.076, p < 0.01), plant height (PH: r = 0.143, p < 0.05), number of pods per plant (NPP: r = 0.941, p < 0.001), number of seeds per pod (NPP: r = 0.432, p < 0.001), number of branches (NPB: r = 0.234, p < 0.01), biological yield (BY: r = 0.683, p < 0.001), and harvest index (HI: r = 0.650, p < 0.001). Principal component analysis (PCA) distinguished small-seeded landraces associated with adaptive and yield traits from large-seeded cultivars associated with seed size. Greek lentil landraces, especially the small-seeded genotypes (e.g., LAX and DIG), have great potential for use in the development of climate-tolerant and high-yielding lentil varieties adapted for sustainable Mediterranean production. Breeding programs can target the crossing of landraces with large-seeded cultivars (e.g., IKAm and THEm) to develop varieties that combine stress tolerance, adaptation, and high productivity with adaptation to different seed sizes. Subsequent studies on drought tolerance and heat resistance are still important for continued improvement in lentil productivity in a changing climate. Full article

Community-managed forests within agroforestry landscapes are vital for both carbon sequestration and agricultural sustainability. This study assesses the Hariyali Community Forest (HCF) in western Nepal, emphasizing its role in carbon storage within a Sal (Shorea robusta)-dominated lowland forest containing diverse native and medicinal species. Stratified field inventories combined with satellite-derived biomass and land-use/land-cover data were used to quantify carbon stocks and spatial trends. In 2022, the mean aboveground carbon density was 165 tC ha⁻¹, totaling approximately 101,640 tC (~373,017 tCO₂e), which closely matches satellite-based trends and indicates consistent carbon accumulation. Remote sensing from 2015–2022 showed a net tree cover gain of 427 ha compared to a 2000 baseline of 188 ha, evidencing effective community-led regeneration. The 615 ha Sal-dominated landscape also sustains agroforestry, small-scale horticulture, and subsistence crops, integrating livelihoods with conservation. Temporary carbon declines between 2020 and 2022, linked to localized harvesting and management shifts, highlight the need for stronger governance and local capacity. This study, among the first integrated carbon assessments in Nepal’s lowland Sal forests, demonstrates how community forestry advances REDD+ (Reducing Emissions from Deforestation and Forest Degradation, and the role of conservation, sustainable management of forests, and enhancement of forest carbon stocks in developing countries) objectives while enhancing rural resilience. Linking field inventories with satellite-derived biomass and land-cover data situates community forestry within regional environmental change and SDG (Sustainable Development Goals) targets (13, 15, and 1) through measurable ecosystem restoration and livelihood gains. Full article

The emergence of electrically conductive polymeric materials has revolutionized the landscape of sustainable energy technologies, presenting unprecedented opportunities for advancing both photovoltaic conversion systems and electrochemical energy-storage platforms. These remarkable macromolecular materials exhibit distinctive characteristics including adjustable electronic band structures, exceptional mechanical adaptability, solution-phase processability, and cost-effective manufacturing potential. This extensive review provides an in-depth examination of the fundamental principles governing charge carrier mobility in conjugated polymer systems, explores diverse synthetic methodologies for tailoring molecular architectures, and analyzes their transformative applications across multiple energy technology domains. In photovoltaic technologies, electrically conductive polymers have driven major advancements in organic solar cells and photoelectrochemical systems, significantly improving energy conversion efficiency while reducing manufacturing costs. In electrochemical energy storage, their integration into supercapacitors and rechargeable lithium-based batteries has enhanced charge storage capability, accelerated charge–discharge processes, and extended operational lifespan compared with conventional electrode materials. This comprehensive analysis emphasizes emerging developments in hybrid composite architectures that combine conductive polymers with carbon-based nanomaterials, metal oxides, and other functional components to create next-generation flexible, lightweight, and wearable energy systems. By synthesizing fundamental materials chemistry with device engineering perspectives, this review illuminates the transformative potential of electrically conductive polymers in establishing sustainable, efficient, and resilient energy infrastructures for future technological landscapes. Full article

Background and Objectives: In the difficult socio-economic situation of recent years, particular attention has been paid to factors that may have a protective effect on mental health. One of these factors is the individual resource known as ego-resiliency. The aim of the study was to assess ego-resiliency as a potential protective factor against stress symptoms and to determine effective coping strategies in a group of patients with Generalized Anxiety Disorder (GAD) during the COVID-19 pandemic. Materials and Methods: The study was conducted from March 2020 to March 2022 among patients attending a Mental Health Clinic in the Upper Silesian metropolitan area of Poland. A total of 68 participants with a confirmed diagnosis of GAD (42 women, 26 men) completed the Ego-Resiliency Scale (ER89-R12), the Coping Inventory for Stressful Situations (CISS), and the Perceived Stress Scale (PSS-10). Results: The mean score on the ER89-R12 was 32.85 ± 6.52 points, with no significant gender differences. The mean PSS-10 score was 22.48 ± 5.61, corresponding to a moderate to high perceived stress level. Significant negative correlations were found between ego-resiliency and perceived stress, and positive correlations between ego-resiliency and task-focused coping. Conclusions: Ego-resiliency may serve as a protective factor against stress and promote adaptive, task-focused coping strategies in patients with Generalized Anxiety Disorder. Strengthening ego-resiliency may be a relevant therapeutic target in clinical interventions. Full article

Soil salinization–alkalization is a critical abiotic constraint on global agriculture, threatening agroecosystem sustainability. Leymus chinensis, a high–quality perennial forage with strong stress resilience, is an ideal model for studying saline–alkali tolerance in graminaceous crops. We integrated physiological, transcriptomic, and metabolomic profiling to dissect its responses under moderate vs. severe carbonate stress, mimicking natural saline–alkali soils rather than single salt stress treatments. Multi–omics analysis revealed drastic reprogramming of energy metabolism, carbohydrate homeostasis, water transport, and secondary metabolism. Our novel finding reveals that L. chinensis uses stress–severity–dependent mechanisms, with flavonoid biosynthesis as a central “regulatory hub”: moderate saline–alkali stress acts as a stimulus for “Adaptive Activation” (energy + antioxidants), promoting growth, while severe stress exceeds tolerance thresholds, causing “systemic imbalance” (oxidative damage + metabolic disruption) and growth retardation. Via WGCNA and metabolome–transcriptome modeling, 22 transcription factors linked to key flavonoid metabolites were identified, functioning as molecular switches for stress tolerance. Our integrated approach provides novel insights into L. chinensis’ tolerance networks, and the flavonoid biosynthesis pathways and regulatory genes offer targets for precision molecular breeding to enhance forage stress resistance and mitigate yield losses from salinization–alkalization. Full article

This study presents an integrated stochastic framework for assessing and forecasting drought dynamics in the western Bhagirathi–Hooghly River Basin, encompassing the districts of Bankura, Birbhum, Burdwan, Medinipur, and Purulia. Employing multiple probabilistic and statistical techniques, including the gamma-based standardized precipitation index (SPI), effective drought index (EDI), rainfall anomaly index (RAI), and the auto-regressive integrated moving average (ARIMA) model, the research quantifies spatio-temporal variability and projects drought risk under non-stationary climatic conditions. The analysis of century-long rainfall records (1905–2023), coupled with LANDSAT-derived vegetation and moisture indices, reveals escalating drought frequency and severity, particularly in Purulia, where recurrent droughts occur at roughly four-year intervals. Stochastic evaluation of rainfall anomalies and SPI distributions indicates significant inter-annual variability and complex temporal dependencies across all districts. ARIMA-based forecasts (2025–2045) suggest persistent negative SPI trends, with Bankura and Purulia exhibiting heightened drought probability and reduced predictability at longer timescales. The integration of remote sensing and time-series modelling enhances the robustness of drought prediction by combining climatic stochasticity with land-surface responses. The findings demonstrate that a hybrid stochastic modelling approach effectively captures uncertainty in drought evolution and supports climate-resilient water resource management. This research contributes a novel, region-specific stochastic framework that advances risk-based drought assessment, aligning with the broader goal of developing adaptive and probabilistic environmental management strategies under changing climatic regimes. Full article

Pancreatic β-cells are metabolically active endocrine cells with a high oxygen demand to sustain glucose-stimulated insulin secretion (GSIS). Hypoxia, arising from vascular disruption, islet isolation, or pathological states such as type 2 diabetes (T2D) and obstructive sleep apnoea (OSA), is a potent metabolic stressor that impairs β-cell function, survival, and differentiation. At the molecular level, hypoxia-inducible factors (HIF-1α and HIF-2α) orchestrate transcriptional programs that shift β-cell metabolism from oxidative phosphorylation to glycolysis, modulate mitochondrial function, and regulate survival pathways such as autophagy and mitophagy. Crosstalk with nutrient-sensing mechanisms, redox regulation, growth factor signaling, and protein synthesis control further shapes adaptive or maladaptive outcomes. Hypoxia alters glucose, lipid, and amino acid metabolism, while mitochondrial dysfunction, oxidative stress, and inflammatory signaling contribute to progressive β-cell failure. Therapeutic strategies including incretin hormones, GABAergic signaling, erythropoietin, ChREBP inhibition, and activation of calcineurin–NFAT or oxygen-binding globins—offer potential to preserve β-cell viability under hypoxia. In islet transplantation, oxygen delivery technologies, ischemic preconditioning, mesenchymal stem cell–derived exosomes, and encapsulation systems show promise in mitigating hypoxic injury and improving graft survival. This review synthesizes current knowledge on β-cell responses to hypoxic stress, with emphasis on metabolic reprogramming, molecular signaling, and translational interventions, underscoring that targeted modulation of β-cell metabolism and oxygen handling can enhance resilience to hypoxia and improve outcomes in diabetes therapy and islet transplantation. Full article

Climate change has intensified the frequency, scale, and interconnection of disasters, challenging the resilience of urban social–ecological systems. Progress remains fragmented because studies on climate adaptation, disaster risk, and resilience often evolve in isolation. Using an integrated methodological approach that combines bibliometric and knowledge mapping analyses of 2396 climate change, 1228 disaster risk, and 989 climate-related disaster risk publications (1994–2024) from the Web of Science Core Collection, this study explores global trends, collaboration networks, and thematic evolution. Results show that (1) disaster risk research remains centered on emergency management; (2) climate change resilience emphasizes adaptive governance and nature-based transformation; and (3) climate-related disaster studies increasingly address compound hazards and cross-sectoral feedback. Synthesizing these strands, this study develops a Dynamic Resilience Framework integrating multi-level feedbacks, governance coordination, and spatiotemporal coupling across robustness, redundancy, transformability, and learnability. The framework identifies future research priorities in multi-risk governance, urban transformability, and justice-oriented adaptation. Full article

To address the limitations of low model accuracy and single-scenario settings in traditional rainfall-induced landslide hazard assessments, this study focuses on Yongren County, Yunnan Province—a region where landslides pose significant threats to sustainable socio-economic development and infrastructure resilience. Eight controlling factors—lithology, slope, terrain relief, distances to faults, rivers, and roads, vegetation coverage, and elevation—were used to build a landslide susceptibility index system. Three internationally recognized machine learning models, Random Forest (RF), Support Vector Machine (SVM), and Extreme Gradient Boosting (XGBoost), were applied for comparison. The XGBoost model was further coupled with rainfall scenario analysis, simulating three rainfall scenarios—normal, 10-year, and 20-year return periods—to form a framework integrating “high-precision susceptibility prediction–multi-scenario rainfall driving–dynamic hazard assessment.” Results show that XGBoost achieved the highest accuracy and stability, with AUC and overall accuracy exceeding those of RF and SVM, supporting high-precision multi-scenario simulations. High-hazard zones expanded from road-disturbed areas under normal rainfall to riverbanks under 10-year rainfall and to fault-fracture and road–river interaction zones under 20-year rainfall. This study provides a transferable framework for sustainable landslide risk management, enabling precision prevention, optimizing resource allocation for disaster risk reduction, and supporting evidence-based policy-making for sustainable development and climate adaptation in similar geological settings. Full article

This study presents a replicable methodology for identifying and evaluating the tourism potential of natural and cultural heritage through a comprehensive inventory. It aims to enhance regional competitiveness and foster sustainable destination development. The methodology combines bibliographic review, field observation, and local surveys, and it was validated through its application in a tourist destination city in Colombia, where resources were systematically classified and evaluated using qualitative and quantitative criteria, focusing on preservation quality and market relevance. The results revealed a rich and underutilized heritage portfolio with exceptional potential in categories such as religious architecture, goldsmithing traditions, local festivals, and natural riverine ecosystems. The city demonstrated a high capacity for developing tourism products grounded in cultural identity and environmental preservation. This methodology offers a robust, adaptable tool for tourism planning, bridging heritage valuation with market relevance. By integrating structured evaluation with local knowledge, the model supports data-driven decision-making and inclusive governance—essential for combating overtourism and promoting long-term resilience in heritage towns. Full article

Considering the trade-off between profit maximization and adaptability to supply chain disruptions, we examine herein the decision-making for configuration and distribution plans in a supply chain. Supply chain disruptions are caused by facility accidents and disasters. In this work, we investigate an optimal configuration and distribution plan in the supply chain with disruptions, including the opening of additional facilities while maintaining the optimum supply amounts to customers in the profit maximization plan when no such disruptions occur. Assuming the existence of uncertainties in demands and supplies, we formulate a two-stage model with a simple recourse, in which decisions on the supply chain configuration are made at the first stage. Decisions on the distribution are made at the second stage after the demands and supplies are realized. For such a configuration and distribution in the supply chain, we propose TSA-SCD (Two-Stage Analysis for Supply Chain Disruptions), a novel decision-making framework considering the trade-off between profit maximization and adaptability to supply chain disruptions. Accordingly, we perform numerical experiments with different degrees of disruptions to verify the effectiveness of the proposed decision method. Full article

Climate change poses increasing risks to the ecological and social foundations of Nature-Based Tourism (NBT), particularly within urbanized and protected landscapes. This study examines how the existing literature conceptualizes climate vulnerability and resilience across Urban Protected Areas (UPAs) and Natural Protected Areas (NPAs), addressing an identified gap in comparative NBT scholarship. Using a semi-systematic literature review of 72 peer-reviewed studies published between 2010 and 2025, guided by PRISMA procedures, the analysis synthesizes conceptual framings, methodological orientations, and thematic trends across ecological, social, and demographic dimensions. Results reveal a persistent geographical bias toward the Global North and a strong emphasis on NPAs (67%), where resilience is primarily understood as an ecological or governance attribute. In contrast, UPA studies increasingly adopt participatory, health-adaptive, and accessibility-oriented approaches, though only about 10% explicitly consider aging populations. Comparative synthesis highlights distinct methodological preferences and a continued underrepresentation of health, well-being, and equity dimensions within current adaptation frameworks. The literature indicates that advancing climate-resilient tourism depends on hybrid models that link urban innovation, ecosystem restoration, and inclusive governance. Integrating regenerative tourism principles, traditional ecological knowledge, and health-adaptive infrastructure emerges as a promising direction for promoting socially equitable and ecologically robust adaptation strategies in protected areas affected by accelerating climate change. Full article