Search Results (23,133)

Drought stress severely limits wheat growth, development and yield. Endophytic fungi play a crucial role in plant growth and drought resistance. In agricultural production, they hold significant application potential as biocontrol agents capable of mitigating drought-induced damage. However, the mechanisms underlying changes in endophytic fungal community structure under drought stress remain unclear. Our study employed amplicon sequencing to investigate the structure of endophytic fungal communities in wheat roots under different water treatments, comparing structural and functional changes between different treatments. Results revealed that drought stress led to the greatest accumulation of relative abundance in the phylum Ascomycota (86.4%). At the genus level, Stachybotrys (increase 994.2%), Fusarium (increase 94.6%) and Aspergillus (increase 295.6%) showed the most significant increases in relative abundance. Co-occurrence network and Sankey diagram analysis revealed that wheat roots formed a drought-specific endophytic fungal community centered around Stachybotrys, Fusarium and Aspergillus, which indirectly enhanced crop drought tolerance. Our findings provide a theoretical foundation for future agricultural strategies to improve crop drought resistance through precise regulation of microbial communities. Full article

Rice is a vital staple food crop worldwide and also one of the major sources of greenhouse gas (GHG) emissions, generating substantial methane (CH₄) and nitrous oxide (N₂O). As one of the key management practices for rice production, the GHG mitigation potential of water management has attracted extensive attention, whereas its global scalability remains to be further investigated. Based on 15,458 global observations of field experimental data, we employed advanced machine learning methods to quantify the GHGs and soil carbon sequestration of global rice systems around 2020. Furthermore, we identified the optimal spatial distribution of GHG mitigation for five rice water management practices (continuous flooding (CF), flooding–midseason drainage–reflooding (FDF), alternate wetting and drying irrigation (AWD), flooding–midseason drainage–intermittent irrigation (FDI), and rainfed cultivation (RF)) through scenario simulation, under the premise of no yield reduction. The results of machine learning simulation showed that optimizing water management could reduce global rice greenhouse gas emissions by 39.17%, equivalent to 340.46 Mt CO₂ eq, while increasing rice yields by 3.55%. This study provides valuable insights for the optimization of agricultural infrastructure and the realization of agricultural sustainable development. Full article

Mangrove forests provide essential climate regulation and coastal protection, yet fine-scale quantification of carbon dynamics remains limited in the Sundarbans due to spatial heterogeneity and tidal influences. This study estimated canopy structural and photosynthetic dynamics from 2019 to 2023 by integrating 10 m spatial high-resolution remote sensing with a light use efficiency (LUE) modeling framework. Leaf Area Index (LAI) was retrieved at 10 m resolution using the PROSAIL radiative transfer model applied to Sentinel-2 data to characterize the canopy structure of the mangrove forest. LUE-based Gross Primary Productivity (GPP) was estimated using Sentinel-2 vegetation and water indices and MODIS fPAR with station observatory temperature data. Annual carbon uptake showed clear interannual variation, ranging from 1881 to 2862 g C m⁻² yr⁻¹ between 2019 and 2023. GPP estimates were strongly correlated with MODIS-GPP (R² = 0.86, p < 0.001), demonstrating the method’s reliability for monitoring mangrove carbon sequestration. LUE-based Solar-induced Chlorophyll Fluorescence (SIF) was derived at 10 m resolution and compared with TROPOMI-SIF observations to assess correspondence (R² = 0.88, p < 0.001) with photosynthetic activity. LAI, GPP and SIF exhibited pronounced seasonal and interannual variability on photosynthetic activity, with higher values during the monsoon growing season and lower values during dry periods. Mean NDVI declined from 2019 to 2023 and modeled annual carbon uptake ranged from approximately 43 to 65 Mt CO₂ eq, with lower sequestration in 2022–2023 associated with climatic stress. Strong correlations among LAI, NDVI, GPP, and SIF indicated consistent coupling between photosynthetic activity and carbon uptake in the mangrove ecosystem. These results provide a fine-scale assessment of mangrove carbon dynamics relevant to conservation and climate-mitigation planning in tropical regions. Full article

The accelerating global demand for sustainable energy, driven by population growth, industrialization, and environmental concerns, has intensified the search for renewable alternatives to fossil fuels. Biofuels, including bioethanol, biodiesel, biogas, and biohydrogen, offer a viable and practical pathway to reducing net carbon dioxide (CO₂) emissions. Yet, their large-scale production remains constrained by biomass recalcitrance, high pretreatment costs, and the enzyme-intensive nature of conversion processes. Recent advances in enzyme immobilization using magnetic nanoparticles (MNPs), covalent organic frameworks, metal–organic frameworks, and biochar have significantly improved enzyme stability, recyclability, and catalytic efficiency. Complementary strategies such as cross-linked enzyme aggregates, carrier-free immobilization, and site-specific attachment further reduce enzyme leaching and operational costs, particularly in lipase-mediated biodiesel synthesis. In addition to biocatalysis, nanozymes—nanomaterials exhibiting enzyme-like activity—are emerging as robust co-catalysts for biomass degradation and upgrading, although challenges in selectivity and environmental safety persist. Green synthesis approaches employing plant extracts, microbes, and agro-industrial wastes are increasingly adopted to produce eco-friendly nanomaterials and bio-derived supports aligned with circular economy principles. These functionalized materials have demonstrated promising performance in esterification, transesterification, and catalytic routes for biohydrogen generation. Technoeconomic and lifecycle assessments emphasize the need to balance catalyst complexity with environmental and economic sustainability. Multifunctional catalysts, process intensification strategies, and engineered thermostable enzymes are improving productivity. Looking forward, pilot-scale validation of green-synthesized nano- and biomaterials, coupled with appropriate regulatory frameworks, will be critical for real-world deployment. Full article

D-Tagatose is a rare sugar of interest as a low-calorie sweetener, and enzymatic isomerization of D-galactose is a practical production route. L-arabinose isomerase (L-AI; EC 5.3.1.4) is a promising catalyst for the above process, but many characterized L-AIs perform best at alkaline pH and high temperature and often require substantial divalent metal supplementation (e.g., Mn²⁺/Co²⁺), which complicates food-grade processing. Lactic acid bacteria (LAB) are attractive sources of food-compatible enzymes, yet structural information for LAB-derived L-AIs has been limited. Here, we report the 2.6 Å X-ray crystal structure of L-AI from Latilactobacillus sakei 23K (LsAI) and define its oligomeric assembly. Although the asymmetric unit contains a single monomer, crystallographic symmetry reconstructs a D₃-symmetric homohexamer composed of two face-to-face trimers, consistent with a higher-order assembly in solution. Interface analysis shows predominantly polar interaction networks, and normalized B-factor mapping reveals localized flexibility near active-site-proximal regions. These findings provide a structural basis for understanding LAB-derived L-AIs and support structure-guided engineering toward food-grade, low-metal biocatalysts for rare-sugar production. Full article

Over the past five years, generative AI has carved out a major role in architecture, especially in education and visual idea generation. Most of the time, the literature talks about AI as a tool, an assistant, or sometimes a co-creator, always highlighting efficiency and the end product in architectural design. There is a steady rise in empirical studies, yet the real impact on how young architects learn still lacks a solid theory behind it. In this systematic review, we dig into peer-reviewed work from 2015 to 2025, looking at how generative AI fits into architectural design education. Using PRISMA guidelines, we pull together findings from 40 papers across architecture, design studies, human–computer interaction and educational research. What stands out is a clear tension: on one hand, students crank out more creative work; on the other, their reflective engagement drops, especially when AI steps in as a replacement during early ideation instead of working alongside them. To address this, we introduce the idea of “AI sparring”. Here, generative AI is not just a helper—it becomes a provocateur, pushing students to think critically and develop stronger architectural concepts. Our review offers new ways to interpret AI’s role, moving beyond seeing it just as a productivity booster. Instead, we argue for AI as an active, reflective partner in education, and we lay out practical recommendations for studio-based teaching and future research. This paper is a theoretical review and conceptual proposal, and we urge future studies to test these ideas in practice. Full article

Mitochondria are essential organelles involved in metabolism, energy production, and cell signaling. Assessing mitochondrial morphology is key to tracking cell metabolic activity and function. Quantifying these structural changes may also provide critical insights into disease pathogenesis and therapeutic responses. This work details the development and validation of a novel, quantitative image analysis pipeline for the characterization and classification of dynamic mitochondrial morphologies. Utilizing high-resolution confocal microscopy, the pipeline integrates first-order statistics (FOS) and a comprehensive suite of gray-level texture analyses, including gray level co-occurrence matrix (GLCM), gray level run length matrix (GLRLM), gray level dependence matrix (GLDM), gray level size zone matrix (GLSZM), and neighboring gray tone difference matrix (NGTDM) with machine learning approaches. The method’s efficacy in objectively differentiating key mitochondrial structures—fibers, puncta, and rods—which are critical indicators of cellular metabolic and activation states is demonstrated. Our open-source pipeline provides robust quantitative metrics for characterizing mitochondrial variation. Full article

Soybean, Glycine max (L.) Merrill, is usually grown on a large scale, with pest control based on chemical insecticides. However, the overuse of chemicals has led to several adverse effects requiring more sustainable approaches to pest control. Results from Integrated Pest Management (IPM) employed on Brazilian soybean farms indicate that adopters of the technology have reduced insecticide use by approximately 50% relative to non-adopters, with yields comparable to or slightly higher than those of non-adopters. This reduction can be explained not only by the widespread use of Bt soybean cultivars across the country but also by the adoption of economic thresholds (ETs) in a whole Soybean-IPM package, which has reduced insecticide use. However, low refuge compliance has led to the first cases of pest resistance to Cry1Ac, thereby leading to the return of overreliance on chemical control and posing additional challenges for IPM practitioners. The recent global agenda for decarbonized agriculture might help to support the adoption of IPM since less chemical insecticides sprayed over the crops reduces CO₂-equivalent emissions from its application. In addition, consumers’ demand for less pesticide use in food production has favored the increased use of bio-inputs in agriculture, helping mitigate overdependence of agriculture on chemical inputs to preserve yields. Despite the challenges of adopting IPM discussed in this review, the best way to protect soybean yield and preserve the environment remains as IPM, integrating plant resistance (including Bt cultivars), ETs, scouting procedures, selective insecticides, biological control, and other sustainable tools, which help sustain environmental quality in an ecological and economical manner. Soon, those tools will include RNAi, CRISPR-based control strategies, among other sustainable alternatives intensively researched around the world. Full article

Residential barbecuing is becoming increasingly popular worldwide, especially in cities, where it is not only a leisure activity but also an important social and cultural practice. Consequently, the number of grills and smokers in use continues to grow. This study evaluated the environmental performance of a household wood-pellet barbecue dual-function smoker/grill using a life cycle assessment (LCA) approach. The functional units selected were per cooking time (1 h) and per unit of energy delivered (1 kWh) at different cooking settings on the smoker. The results show that most of the impacts, including global warming potential (GWP) and resource use, originate from the production of the smoker itself, whereas emissions released during combustion, especially NO_x, are the main contributors to impacts such as acidification and smog formation. The GWP per hour of operation ranged from 0.44 to 0.63 kg CO₂ eq. From an operational perspective, cooking at intermediate temperatures (between 110 and 175 °C) generally leads to lower impacts per hour than very low-temperature smoking. When considering entire meals, meat typically accounts for most of the total impact, with the smoker’s contribution comparatively small. Overall, the study provides a useful reference and shows that both equipment design and food choices play a role in barbecue sustainability. Full article

Aquaponic systems are the integration of aquaculture and hydroponic systems to enhance productivity, reduce land use, and improve sustainability. This review focused on commonly used life cycle assessment (LCA) methodologies, system boundaries, and functional units used in aquaponics, standard impact categories, and identified hotspots. The scope is worldwide and encompasses a variety of aquaponic designs, fish species, and crops, illustrating the diversity of the systems examined. The analysis indicates that aquaponics provides the considerable environmental advantages of decreased fertilizer consumption and water conservation in comparison with aquaculture and hydroponic system. However, aquaponics systems are characterized by high energy consumption and may produce greater greenhouse gas (GHG) emissions compared to traditional farming methods when reliant on fossil fuel energy sources. Studies show that fish feed production, system infrastructure, and electricity usage for pumps, lights, heating, and other controls are hotspots. Harmonized comparisons of previous studies show methodological differences, especially in fish–plant co-production. Despite these variations, most believe that energy efficiency, renewable energy, feed optimization, and waste reuse may make aquaponics more sustainable. The study recommends the inclusion of broader environmental and social impacts. Also, future focus might be on making a standard functional unit or specifying system boundaries which might provide different accurate outcomes. Full article

Lightning rods, while essential for protecting weather radars from direct lightning strikes, act as persistent non-meteorological scatterers that can interfere with signal transmission and reception and thereby degrade detection accuracy and product quality. Existing studies have mainly focused on X-band and C-band systems, and robust, measurement-based quantitative assessments for S-band dual-polarization radars remain scarce. In this study, a controllable tilting lightning rod, a high-precision Far-field Antenna Measurement System (FAMS), and an S-band dual-polarization weather radar (SAD radar) are jointly employed to systematically quantify lightning-rod impacts on antenna electromagnetic parameters under different rod elevation angles and azimuth configurations. Typical precipitation events were analyzed to evaluate the influence of the lightning rods on dual-polarization parameters. The results show that the lightning rod substantially elevates sidelobe levels, with a maximum enhancement of 4.55 dB, while producing only limited changes in the antenna main-beam azimuth and beamwidth. Differential reflectivity () is the most sensitive polarimetric parameter, exhibiting a persistent positive bias of about 0.24–0.25 dB in snowfall and mixed-phase precipitation, while no persistent azimuthal anomaly is evident during freezing rain; the co-polar correlation coefficient () is only marginally affected. Collectively, these results provide quantitative, far-field evidence of lightning-rod interference in S-band dual-polarization radars and provide practical guidance for more reasonable lightning-rod placement and configuration, as well as useful references for -oriented polarimetric quality-control and correction strategies. Full article

As transparency and sustainability gain strategic importance, the mass balance approach under chain of custody (MB-CoC) has become a central mechanism for assessing product carbon footprints (PCFs) in complex chemical value chains. The MB-CoC enables the attribution of renewable and recycled feedstock characteristics via certified bookkeeping when physical segregation or molecular tracing is infeasible—thus complementing PCF methodologies based on ISO 14067 and the LCA standards ISO 14040/44. However, the methodological integration of the MB-CoC into ISO-conformant PCFs remains insufficiently defined and empirically underexplored. This paper systematically reviews the interaction between the MB-CoC and PCF/LCA frameworks. It (i) synthesizes the allocation rules of ISO 14040/44/67 and the attribution principles of the MB-CoC according to ISO 22095 and key industry initiatives; (ii) analyzes academic publications, guidelines, and corporate applications; and (iii) identifies methodological tensions concerning system boundaries, allocation logic, residual mixes, treatment of biogenic and recycled carbon, and risks of double counting. Our review reveals five recurring insights across the literature: the need for certification and standardization; the importance of primary data and residual mixes; the requirement for ISO conformity; the necessity of transparent reporting of conventional versus alternative inputs; and the lack of independent empirical case studies. Addressing these gaps through harmonized rules, residual mix development, and comparative applications will be essential for establishing the MB-CoC as a robust instrument for circularity, decarbonization, and regulatory compliance, developed by interdisciplinary research and industry approaches. Full article

This study introduces the Sustainable Development Goals Achievement Measurement Framework (SDG-AMF), a novel analytical tool used to systematically evaluate the relationships between digitalization and the Sustainable Development Goals (SDGs). Unlike the United Nations (UN) E-Government Development Index (EGDI) and Organization for Economic Co-operation and Development (OECD) Digital Government Indicators (DGIs) frameworks, the proposed SDG-AMF links digitalization indicators to specific SDG outcomes using proxy-based time-series analysis. The SDG-AMF provides a unified, statistically grounded approach that connects digital development with measurable sustainability outcomes. Using direct, high-quality time-series data (2010–2024) from internationally recognized sources, the framework maps key digitalization indicators such as Internet penetration, e-government maturity, research and development (RD) expenditure, gross domestic product (GDP) per capita, and gender participation in information and communication technology (ICT) to the selected SDG targets (SDGs 4, 5, 8, 9, and 16). Through correlation and regression analyses, the study identifies enabling and inhibiting relationships, highlighting Saudi Arabia’s strengths in digital infrastructure and e-government maturity while emphasizing areas for improvement, such as civic participation and RD intensity. Comparative benchmarking with digitally advanced economies underscores Saudi Arabia’s strengths in Internet penetration and e-government maturity, while gaps in RD investment are identified. The SDG-AMF provides policymakers with a replicable roadmap and scalable model to align foundational connectivity and governance reforms with advanced digital transformation, facilitating progress toward achieving Sustainable Development Goals worldwide. This research contributes original methodological insights and equips stakeholders with practical tools to monitor, compare, and accelerate SDG progress in the digital era. Full article

People living with HIV-1 (PLWH) are part of the so-called “fragile” populations to which COVID-19 vaccines were/are strongly recommended. The fact that most widely used COVID-19 vaccines rely on the production of a biologically active SARS-CoV-2 Spike protein expressed by synthetic mRNA poses the relevant question of whether and how this vaccination influences the fate of the HIV-1 reservoir. This report presents a detailed analysis of the literature data on the effects of SARS-CoV-2 Spike and COVID-19 vaccines on HIV-1 latently infected cells. Despite being limited in number, the experimental evidences consistently indicate that vaccine mRNA and/or SARS-CoV-2 Spike can effectively reactivate latent HIV-1. This conclusion has been drawn after “in vitro”, “ex vivo”, and “in vivo” assays, and with virus-associated Spike, soluble Spike, or its intracellular expression, as well as with COVID-19 mRNA vaccines. On the other hand, real-world observations on vaccinated PLWH under antiretroviral therapy (ART) provided evidence of HIV-1 reactivation almost exclusively in PLWH with unsuppressed viremia, as measured in terms of size of the HIV-1 reservoir. Although several issues still need to be clarified through urgent additional investigations, these data suggest the possibility that the Spike protein and/or the vaccine mRNA molecules affect the HIV-1 latency in PLWH. Full article

The rapid evolution of coronaviruses (CoVs) requires researchers to develop specific yet broad-spectrum detection methods to monitor their constant genomic changes. The goal of the present study was to establish a current pan-coronavirus RT-PCR system capable of detecting a wide variety of CoVs and useful for the investigation of virus diversity and host spectrum. For optimization, one-step and two-step nested RT-PCRs with three RT enzymes were examined, amplifying a ~600 bp long product of the RNA-dependent RNA polymerase. As templates, the in vitro transcribed RNA of ten pathogenic CoVs (SARS-CoV, SARS-CoV-2, NL-63, OC43, feline CoV, porcine epidemic diarrhea virus or PEDV, transmissible gastroenteritis virus or TGEV, canine CoV, bat CoV, and infectious bronchitis virus) were applied instead of the often-used DNA standards. A limit of detection of 5–50 copies/reaction was achieved with a random hexamer-primed two-step RT-PCR and a touchdown cycling profile, representing a lower detection limit and higher specificity compared to previously published primer sets. Swine origin pooled samples (n = 121), collected from apparently healthy herds in Hungary, were tested with the novel RT-PCR system. Sequences of porcine respiratory CoV/TGEV and porcine hemagglutinating encephalomyelitis virus were identified in 24 oral fluid and nasal swab pools, demonstrating the circulation of these viruses in this country, as well as the suitability of the new PCR for their detection. The results highlighted the importance of adequate RT enzyme selection and the use of RNase inhibitors in sample preparation and conservation. Full article