Search Results (2,986)

Radiation use efficiency (RUE) is closely associated with cotton biomass and yield, yet the synergistic regulation of phenotypic structure and physiological potential remains unclear. A field experiment (2024–2025) in Anyang, China, utilized three independent trials: six sowing dates (from 12 April to 12 May at 6-day intervals, S1–S6), six planting densities (1.5, 3.3, 5.1, 6.9, 8.7, and 10.5 × 10⁴ plants·ha⁻¹, D1–D6), and ten cultivars with distinct architectures (V1–V10). Feature importance and structural relationships were quantified via random forest (RF) and partial least squares structural equation modeling (PLS-SEM). Results indicated that delaying sowing reduced true leaf number (TLN) and plant height (PH), with the April 24 sowing (S3) optimizing leaf area index (LAI, 2.57) and light interception rate (iPAR, 0.61). Increasing density significantly enhanced population-level LAI, above-ground biomass, and RUE, despite a progressive decline in TLN. Among cultivars, CCRI 60 (V6) exhibited superior structural traits (PH: 72.94 cm; iPAR: 0.61), while CCRI 113 (V8) exhibited the highest maximum carboxylation rate (V_cmax, 88.9 μmol·m⁻²·s⁻¹) and RUE (4.88 g·MJ⁻¹). Across the comprehensive dataset (integrating the density, sowing date, and cultivar trials), iPAR exhibited the highest relative importance (42.01%) for RUE variation, while associated structural traits (PH, LAI, TLN) yielded a cumulative relative importance of 41.69%. RUE was strongly associated with biomass accumulation (path coefficient > 0.97), which subsequently optimized yield components. Conversely, within the cultivar-comparison subset, the relative importance of iPAR decreased to 17.95%, while V_cmax rose significantly to 19.20%. PLS-SEM indicated that canopy structure exerted a significant negative association with photosynthetic potential (V_cmax, J_max) within this cultivar subset (path coefficient ≈ −0.51), whereas enhanced physiological potential was positively associated with resource allocation to yield components (path coefficient ≈ 0.57). Consequently, mitigating the inherent trade-off between canopy structure and leaf photosynthetic capacity is critical for further improving RUE and cotton yield under similar production environments. Full article

Early flowering-related factors play pivotal roles in coordinating plant growth and reproductive development. In this study, we investigated the biological function of early flowering gene (ELF) in Arabidopsis thaliana using CRISPR/Cas9-mediated genome editing and construction of overexpression approaches. Two independent ELF overexpression (OE-ELF) and genome-edited (ge-elf) lines were generated and systemically analyzed. ELF overexpression significantly enhanced early seedling performance, increasing germination rate and seedling fresh weight by up to 8.7%, while genome-edited lines exhibited a marked reduction. Root growth was strongly promoted in OE-ELF plants, with root length increase of 85% and 75%, whereas ge-elf lines showed a reduction of up to 48%. At later developmental stages, OE-ELF plants displayed enhanced vegetative growth, including increased leaf length (32%), leaf area (91%), and accelerated flowering (21% earlier than wild type). In contrast, ge-elf delayed flowering by up to 25% and resulted in compact plant architecture. Reproductive development was severely compromised in ge-elf plants, which exhibited malformed inflorescences, reduced pollen germination, shortened silique (45%), and a drastic decrease in seed number per silique (70%). Conversely, OE-ELF plants showed increased silique number and seed per silique. Molecular analysis revealed that ELF positively regulates key flowering-related genes, including FLC, SOC1, AP1, and LFY, which correlated strongly with growth and reproductive traits. Our results demonstrate that ELF functions as a central regulator integrating vegetative growth, floral development, male fertility, and seed production in Arabidopsis thaliana. Full article

The construction sector is undergoing a rapid transition toward more resilient, sustainable, and digitally connected systems, creating increasing demand for materials capable of providing functions beyond conventional structural performance. In this context, smart materials have emerged as promising solutions due to their ability to respond to mechanical, thermal, chemical, or electromagnetic stimuli through adaptive behaviors such as self-healing, structural sensing, energy regulation, vibration control, and reversible deformation. Despite growing scientific interest, available knowledge remains fragmented across specific material families and isolated application domains. Therefore, this study presents a PRISMA-based systematic review of smart materials in construction using peer-reviewed journal literature indexed in Scopus during the 2021–2026 period. The review examines the principal smart material families currently applied in construction, including self-healing concretes, self-sensing cementitious systems, Shape Memory Alloys (SMA), piezoelectric materials, phase change materials, adaptive coatings, conductive nanocomposites, and multifunctional geopolymers. Their engineering functions, structural and architectural applications, reported performance characteristics, sustainability contributions, digital integration potential, and implementation barriers are comparatively discussed and qualitatively synthesized based on the reviewed literature. The findings indicate that smart materials can improve durability, structural health monitoring, seismic resilience, thermal efficiency, lifecycle performance, and carbon reduction when properly integrated into buildings and infrastructure. However, large-scale adoption remains constrained by high initial costs, manufacturing scalability, regulatory uncertainty, long-term durability validation, and limited market confidence. The review further shows that the greatest future potential lies in combining material intelligence with IoT platforms, artificial intelligence, BIM environments, and digital twins. Overall, smart materials are positioned as strategic enablers of next-generation low-carbon, adaptive, and intelligent construction systems. Full article

Metformin, widely prescribed for type 2 diabetes mellitus (T2D), has emerged as a systemic immunomodulator with effects that extend far beyond glycemic control. Recent advances in immunometabolism reveal that metformin modulates innate immune responses through coordinated cellular metabolic reprogramming and epigenetic modification, which collectively modulate the functional phenotype of innate immune cells. This narrative review summarizes current evidence regarding the immunomodulatory effects of metformin on the innate immune system, with a focus on immunometabolism and epigenetic regulation. It explores how metformin modulates innate immunity by altering cellular energy sensing, mitochondrial function, and nutrient utilization. Such metabolic changes and alterations further reshape chromatin structure and architecture, as well as transcriptional profiles and programs. Through the regulation of glycolysis, fatty acid oxidation, and histone modification landscapes, metformin regulates the phenotypes of innate immune cells, which can be pro-inflammatory, tolerogenic, or homeostatic. This conceptual framework presents a new understanding of metformin. As well as acting as an anti-inflammatory agent, it may regulate immune memory. Full article

Morocco has developed one of the most comprehensive sustainability governance architectures among middle-income emerging economies, yet the relationship between its formal regulatory ambition and on-the-ground implementation effectiveness remains poorly understood. This narrative literature review provides an integrated, critically analytical account of Morocco’s sustainability governance system, organised around three interlocking dimensions: (i) a progressively strengthened legislative corpus anchored by the 2011 Constitution and Framework Law 99-12; (ii) a portfolio of national sustainability strategies aligning domestic policy with Paris Agreement commitments, Nationally Determined Contributions (NDCs), and the United Nations Sustainable Development Goals (SDGs); and (iii) corporate sustainability practices driven by regulatory obligations, international supply chain pressures, and ESG disclosure norms. Drawing on 124 sources, comprising 62 peer-reviewed articles, 38 legislative texts, and 24 institutional reports, and applying institutional isomorphism theory as an integrating analytical lens, the review advances three theoretical propositions concerning the conditions under which formal governance architectures translate into effective sustainability outcomes. It further proposes a validated conceptual framework and develops a comparative positioning of Morocco against peer economies (Tunisia, Egypt, South Africa, and Turkey). Critical implementation gaps are identified in enforcement capacity, SME integration, sustainability data infrastructure, and green finance, contributing a balanced and evidence-grounded assessment of Morocco’s sustainability transition. These findings offer actionable insights for policymakers, regulators, and business leaders operating in the Moroccan and broader African context. Full article

Taraxacum kok-saghyz (T. kok-saghyz) is a promising alternative crop for natural rubber production, in which root development is closely associated with rubber synthesis; however, the molecular mechanisms governing root architecture formation remain largely unclear. NAC transcription factors play pivotal roles in plant root development, yet their functions in T. kok-saghyz have not been systematically investigated. In this study, a genome-wide analysis identified 34 NAC family members in T. kok-saghyz. Through transcriptomic analysis following methyl jasmonate (MeJA) treatment, 27 genes significantly responsive to MeJA signaling were screened. Sequence analysis revealed that all TkNAC proteins contain a conserved NAM domain. Subcellular localization assays confirmed that TkNAC16, TkNAC20, TkNAC23, and TkNAC30 are localized to the nucleus. Yeast two-hybrid and bimolecular fluorescence complementation assays demonstrated that TkNAC16/18/20/23/30 can form extensive heterodimers. Overexpression lines of T. kok-saghyz exhibited significantly increased root length, while leaf growth exhibited line- and stage-specific effects. Collectively, this study provides the first systematic identification of the NAC transcription factor family in T. kok-saghyz, elucidates their involvement in methyl jasmonate signaling responses, the construction of heterodimerization networks, and the positive regulation of root elongation. These findings provide crucial genetic resources and a theoretical basis for dissecting the molecular mechanisms underlying the coordinated improvement of root development and rubber yield in T. kok-saghyz. Full article

Accurate and automated extraction of solid waste sites from remote-sensing imagery constitutes a pivotal demand for contemporary environmental regulation and risk mitigation. However, in high-resolution remote-sensing imagery, solid waste sites are typically represented as a single semantic image object (SIO), which is composed of multiple physical image parcels (PIPs) exhibiting significant variations in scale, morphology, and spectral properties. This intrinsic heterogeneity substantially increases the complexity and uncertainty of multi-class site identification. To address this challenge, this paper proposes WasteMOE Net (WMN), which is developed based on the core concept of modeling the SIO–PIP relationship. WMN adopts a heterogeneous expert selection mechanism combined with a nested mixture-of-experts architecture. It thus enables adaptive perception of complex PIPs across diverse scenarios and their integrated discrimination at the SIO level. In addition, by incorporating the explicit nonlinear representation capability of the KAN network, WMN effectively improves multi-class recognition accuracy while maintaining computational efficiency. Furthermore, this study constructs a high-resolution solid waste site dataset in accordance with the SIO–PIP-aware annotation principle, encompassing five representative categories: tailings ponds (TP), construction spoil sites (CSS), landfill sites (LS), garbage dump sites (GDS), and excavation sites (ES). Experimental results show that WMN achieves mAP50 values of 74.2% (GDS), 63.5% (CSS), 80.9% (ES), 85.4% (TP), and 83.1% (LS) in detection tasks, and 75.4%, 64.1%, 83.0%, 86.7%, and 84.1% for the corresponding categories in segmentation tasks. It achieves competitive performance compared with state-of-the-art methods in both tasks. Further, in a real-world application over Loudi City, China, WMN completed the processing of a 490.67 km² area within 1.34 h. The recognition accuracies for GDS and ES reached 54.8% and 65.3%, respectively. Finally, the proposed method has been successfully integrated into a GIS-based solid waste pollution risk prevention system, which markedly boosts the overall efficiency of environmental monitoring and on-site inspections. Full article

Abiotic stresses, including drought, salinity, alkalinity, temperature extremes, flooding, heavy metals, and emerging pollutants, challenge plant growth and productivity by disturbing water relations, ion balance, redox homeostasis, membrane stability, energy metabolism, and developmental progression. Although substantial progress has been made in the identification of stress-responsive hormones, second messengers, kinases, transcription factors, transporters, and metabolic regulators, plant stress adaptation cannot be fully explained by linear signaling cascades or single tolerance genes. A major unresolved question is how early molecular events are reorganized into coordinated physiological and developmental outputs that support survival, recovery, and productivity. In this review, we propose an intermolecular interaction-driven adaptive remodeling framework for plant abiotic stress responses. This framework emphasizes that stress tolerance emerges from dynamic changes in receptor–ligand recognition, protein–protein interactions, calcium decoding, redox-sensitive modification, phosphorylation networks, transcriptional regulation, chromatin-associated control, and metabolite-mediated feedback. We further emphasize ROS as integrative redox switches that connect stress sensing, defense activation, senescence-related transitions, and recovery, and chromatin-associated mechanisms as regulators that may stabilize primed or memory-like adaptive states. We discuss how these interaction networks converge on core signaling hubs, including abscisic acid, reactive oxygen species, Ca²⁺, and kinase/phosphatase systems, and how they remodel stomatal behavior, root architecture, ion and pH homeostasis, redox buffering, metabolism, development, and reproductive resilience. We further highlight how natural variation, multi-omics, genome editing, high-throughput phenotyping, and field validation can translate interaction-centered stress biology into crop resilience. This perspective provides a conceptual bridge between molecular stress perception, network behavior, physiological adaptation, and climate-resilient agriculture. Full article

Efficient and financially sustainable social protection systems are essential under conditions of economic instability and increasing social demand. However, traditional administrative models are often characterized by high operational costs, procedural complexity, and delayed benefit delivery. This study examines the role of digitalization, process automation, and AI-driven administrative solutions in reducing administrative expenses while enhancing the sustainability and resilience of social protection systems. An integrated Automation Index is developed using standardized proxy indicators that reflect reductions in operational and transaction costs associated with digital and automated technologies. To assess future trajectories of administrative expenses, scenario-based modelling is applied under three digital transformation paths—baseline, moderate, and intensive. Administrative efficiency is estimated using a translog Stochastic Frontier Analysis (SFA) framework. The results indicate that digitalization and automation significantly reduce administrative costs only when supported by favorable institutional conditions, including decentralized governance, effective inter-agency coordination, and clearly regulated administrative procedures. Under the intensive digital transformation scenario, administrative expenses decline substantially relative to the baseline, while system responsiveness and beneficiary coverage improve. In contrast, weak institutional environments limit the efficiency gains of technological solutions. The study concludes that AI agents and automated systems should be viewed not as substitutes for human decision-making but as tools for optimizing administrative architectures. This transition from resource-intensive to technology-intensive models is particularly important for developing countries seeking sustainable social protection under constrained fiscal conditions. Full article

Greenhouse microclimate regulation is challenging due to nonlinear coupling among temperature, humidity, soil moisture, and light intensity, which limits the effectiveness of conventional threshold-based and PID control strategies under time-varying environmental disturbances. This paper presents a forecast-augmented ensemble control framework that combines Random Forest, Gradient Boosting, and Support Vector Machine classifiers with one-hour-ahead weather forecasts for closed-loop greenhouse microclimate regulation. The proposed system was deployed and validated in a working greenhouse cultivating cucumber (cv. ‘Madora F1’) over 28 consecutive days. Sensor measurements and forecast inputs were processed through a unified preprocessing pipeline, while control actions were generated through majority voting and executed on Raspberry Pi 4B edge hardware with a worst-case inference latency below 18 ms. The proposed framework achieved a temperature RMSE of 0.83 °C during field deployment. For reference, RMSE values of 3.21 °C and 1.94 °C were obtained for the threshold-based and PID baseline controllers, respectively, under the adopted disturbance-consistent evaluation protocol. Compliance rates reached 96.4% for temperature, 94.1% for relative humidity, and 97.2% for soil moisture across 40,320 resampled observation intervals (60 s analysis grid) derived from the original 10 s acquisition stream. Integration of short-term weather forecasts enabled anticipatory irrigation management, reducing irrigation pump operation by 18% without compromising soil-moisture compliance and yielding an estimated annual energy saving of 158 kWh per greenhouse zone. Unlike prediction-oriented greenhouse artificial-intelligence studies, the proposed approach implements a deployable forecast-augmented closed-loop control architecture validated under continuous real-world greenhouse operation. Full article

Contemporary societies are characterized by increasing role multiplicity and accelerated social change, intensifying identity-related strain and inter-role conflict. Although role theory, narrative identity research, and psychological flexibility frameworks have independently advanced the understanding of psychological adaptation, an integrative structural model explaining how life domains are hierarchically organized and reorganized over time remains underdeveloped. This manuscript introduces Casa Vital (Vital House), a dynamic structural model that conceptualizes identity as a hierarchical architecture of interdependent life domains organized around a central integrative function. The model proposes three core constructs: structural coherence, structural modes (rigidity/flexibility) and self-directed agency, and argues that psychological adaptation depends not only on emotional regulation or narrative coherence but also on the capacity to reorganize domain hierarchies in alignment with personal values and contextual demands. By positioning identity at a meso-structural level of analysis, the framework integrates sociological, narrative, and contextual behavioral traditions while offering testable hypotheses and a falsifiable research agenda. Casa Vital expands the current models of adaptation by introducing hierarchical structural reorganization as a central component of identity functioning in complex contemporary contexts. Full article

Plants must continuously balance the trade-offs between growth and defense, a constraint that is exacerbated by biotic and abiotic stresses, particularly when they occur together. Ethylene (ET) serves as a central, integrative regulatory node controlling this by linking developmental programs to stress-responsive signaling networks. Advances at the molecular and systems levels have revealed that ET mediates the redistribution of metabolic resources via coordinated regulation of its synthesis, perception, and downstream signaling. The ETR (Ethylene Receptor)-CTR1 (Constitutive Triple Response 1)-EIN2 (Ethylene Insensitive 2)-EIN3(Ethylene Insensitive 3) signaling module lies at the core of this network, integrating multiple hormonal pathways. Through dynamic crosstalk with jasmonic acid (JA), salicylic acid (SA), abscisic acid (ABA), auxin (AUX), and gibberellins (GA), ET enables the fine-tuned coordination of growth inhibition, immune activation, and stress acclimation in response to environmental fluctuations. Processes such as induced systemic resistance, programmed cell death, and architectural plasticity further reinforce this regulatory framework, with ethylene-responsive transcription factors, including ERFs (ethylene responsive factor gene family) and WRKYs, acting as critical convergence points. Emerging insights into ACC (1-aminocyclopropane-1-carboxylic acid) -dependent signaling, chromatin remodeling, and tissue-specific regulation expand the functional scope of ET beyond traditional hormone paradigms. At the same time, the ability of pathogens to manipulate ET signaling underscores its dual role in both promoting immunity and facilitating susceptibility. By integrating molecular, physiological, and ecological perspectives, this review highlights ET as a central coordinator of plant stress resilience and growth optimization, providing a unifying framework for understanding how plants adapt to complex and dynamic environments. Full article

Background/Objectives: Numerous natural compounds have been reported to exhibit anti-virulence properties against pathogenic bacteria. Particularly, plants constitute a rich source of anti-quorum-sensing (QS) and anti-biofilm compounds with highly diverse chemical structures. Notably, several studies reported that plant-derived pentacyclic triterpenoids exert anti-biofilm activity against Pseudomonas aeruginosa without affecting bacterial viability, suggesting that this class of naturally occurring chemical compounds may represent a source of potent and clinically relevant anti-biofilm agents. Methods: To further investigate this hypothesis, we evaluated several commercially available pentacyclic triterpenoid acids of the oleanane, ursane and lupane types for their potential impact on QS mechanisms and biofilm formation in the P. aeruginosa PAO1 model strain. Results: Oleanane-type (oleanolic acid and maslinic acid), ursane-type (ursolic acid and corosolic acid) and lupane-type (betulinic acid) triterpenoids inhibited the expression of the QS-regulated lasB and rhlA genes as well as biofilm formation, without affecting bacterial growth. Among tested compounds, oleanolic and ursolic acids, at 400 µM, exhibited the strongest anti-biofilm activities, with 45% and 40% inhibition, respectively. Fluorescence microscopy revealed a marked disorganization of biofilm architectures, with bacterial communities failing to establish compact cell-to-cell attachment and confluent microcolonies. Further analyses indicated that these triterpenoid acids did not affect the expression of QS-regulator genes (lasR/I and rhlR/I), suggesting that their impact on lasB and rhlA expression and biofilm formation is independent of the las and rhl systems. Conclusions: These findings suggest that oleanane and ursane triterpenoid acids represent promising chemical backbones for the development of strategies aimed at inhibiting P. aeruginosa biofilm formation. Full article

Cholangiocarcinoma (CCA) is an aggressive and molecularly heterogeneous malignancy characterized by a profoundly immunosuppressive tumor microenvironment (TME) and historically limited therapeutic options. Recent advances have redefined the treatment paradigm, with phase III trials establishing chemoimmunotherapy as a standard of care and multi-omic profiling elucidating the interplay between tumor genomics, stromal architecture, and immune regulation. Despite these gains, durable clinical benefit remains confined to a minority of patients, reflecting convergent mechanisms of primary and acquired resistance—including immune exclusion, myeloid-dominant suppression, and genotype-driven “cold” tumor states. In this review, we synthesize emerging insights into the immune landscape of CCA, integrating data from single-cell, spatial, and translational studies to define the cellular and molecular circuits governing immune evasion. Beyond canonical biomarkers such as mismatch repair and microsatellite status, we highlight how spatial organization of immunity—in particular, tertiary lymphoid structures, dynamic myeloid and stromal interactions, and pathway-level features—shape immunotherapy responsiveness. We also examine how tumor-intrinsic alterations, including IDH1 mutation, FGFR2 fusions, KRAS activation, and MTAP loss, define distinct immunologic phenotypes with direct implications for immunotherapeutic response and biomarker-driven patient selection. We evaluate the expanding clinical trial landscape of immunotherapy in CCA and more broadly in BTC, including adoptive cell therapies and cancer vaccines. Together, these advances position CCA as a paradigm of how tumor genotype and microenvironment co-evolve to define immunotherapy sensitivity and resistance. Full article

Under the dual constraints of global food security and ecological protection, conventional agriculture is hampered by low resource efficiency and sluggish environmental response. Crop digital twin technology establishes a dynamic virtual reality system that integrates crops, environment, and water to enable real-time interaction and optimization. Based on the existing literature, this paper reviews the concept, architecture, and core modules of this technology and summarizes its applications in precision irrigation and crop monitoring. There are three major bottlenecks that persist, including limited high-frequency multi-source sensing and spatiotemporal fusion, insufficient parameter calibration and dynamic updating, and weak cross-scale integration from plant to watershed. Water is increasingly recognized as the key constraint and control variable and acting as both the central physiological driver of crop growth and the mass-flow link that connects the soil–plant–atmosphere continuum. The spatiotemporal dynamics of crop water deficit, compensatory root water uptake, evapotranspiration feedback, and the hydraulic behavior of irrigation-district canal systems constitute the core hydrological processes that must be simulated within the digital twin. Synchronizing crop water demand, soil moisture dynamics, atmospheric evapotranspiration, and irrigation scheduling within a unified spatiotemporal framework establishes a complete sensing, diagnosis, prediction and regulation technical chain. This chain offers a core pathway for alleviating agricultural water scarcity, improving irrigation efficiency, and ensuring food security. Full article