Search Results (38,037)

Immature rice is a distinctive cereal product widely consumed in Asian countries due to its natural green color, soft texture, unique flavor, and high nutritional value. However, its fragile structure and pigment sensitivity create significant processing challenges. This study investigates the effects of infrared (IR) roasting temperature (550–650 °C) and time (20–40 min) on the physicochemical, nutritional, and cooked-rice qualities of immature rice (Oryza sativa L., cv. RD6). A two-factor study with three level of factorials was designed and response surface methodology (RSM) was used to evaluate roasting variables and to identify optimal processing conditions (p ≤ 0.05). Increasing roasting severity decreased rice yield, moisture content, water activity, and chlorophyll content, while promoting grain darkening, increasing phenolic content, and enhancing cooked-rice expansion and hardness. Several responses exhibited significant linear and quadratic relationships with roasting conditions, with model coefficients of determination (R²) ranging from 0.676 to 0.829. Multi-response optimization using desirability analysis identified the optimal roasting condition as 650 °C for 20 min, which produced predicted values that closely matched experimental validation (p > 0.05). These results demonstrate that IR roasting provides an effective green-energy processing approach for producing value-added immature rice while maintaining desirable color, nutritional properties, and cooked-rice texture. Full article

Indole-3-acetic acid (IAA) is the main natural auxin and a key regulator of plant growth. However, most commercial auxins are synthetically produced from non-renewable resources. Here, we present a minimal synthetic biology platform for microbial IAA production that also serves as a teaching model for genetic circuit design and bioprocess development. We developed codon-optimized versions of the iaaM and iaaH genes, which encode tryptophan 2-monooxygenase and indole-3-acetamide hydrolase, and assembled them into a compact expression cassette in Escherichia coli TOP10. Correct expression of both enzymes was confirmed by SDS-PAGE. The engineered strain was cultivated in a low-cost medium made from avocado seed hydrolysate, an agro-industrial waste, supplemented with tryptophan as a precursor. IAA was quantified using the Salkowski colorimetric assay and further validated by HPLC, reaching approximately 303 µg/mL at 48 h, with the medium costing five times less locally than traditional LB. The supernatants containing biosynthetic IAA induced root formation in 100% of tobacco leaf explants, outperforming the commercial standard at the same concentration and confirming biological activity. Since this workflow follows the Design–Build–Test–Learn (DBTL) cycle, Design (pathway selection and codon optimization), Build (plasmid assembly), Test (protein expression, metabolite quantification, plant bioassays), and Learn (medium and process optimization), it provides a sustainable production method and an accessible educational platform for synthetic biology. Full article

Groundwater is a critical lifeline for ecosystems and human settlements in arid and semi-arid regions, yet it is increasingly vulnerable to the dual pressures of extreme climatic conditions and intensifying anthropogenic activities. This study investigated 24 groundwater and 4 river water samples to discuss the hydrogeochemical evolution and water quality suitability in the Tianjun Basin, a typical high-altitude arid basin on the northeastern Tibetan Plateau. The results indicate that groundwater is mildly alkaline (pH: 7.65–8.35) and predominantly fresh (TDS: 233.77–1061.42 mg/L). Hydrochemical facies evolve from HCO₃-Ca type in upstream areas to Mixed HCO₃-Na·Ca and Cl-Na types. Hydrochemical analysis suggests that silicate weathering and carbonate dissolution are the dominant natural processes, while cation exchange further modifies the ionic composition. Notably, anthropogenic nitrogen (NO₃⁻ and NH₄⁺) contamination, primarily from domestic sewage in the Tianjun Basin, has significantly impacted groundwater quality. Health risk assessment shows that infants are the most vulnerable group, with 16.67% of samples posing a non-carcinogenic risk via the oral pathway. Regarding irrigation suitability, while sodium hazards are generally low, a significant salinity hazard is identified due to elevated electrical conductivity in the arid environment. This poses a substantial risk of secondary soil salinization, necessitating strict salt management strategies to preserve long-term land productivity. These findings provide critical insights for the sustainable management of fragile groundwater resources in extreme arid environments. Full article

Annona muricata (soursop) is a tropical medicinal plant widely used in traditional medicine across Africa, the Caribbean, and parts of South America. While its ethnomedicinal applications span a range of conditions, including infections, inflammation, and anemia-related symptoms, its potential relevance to hematopoiesis has not been systematically examined. This narrative review synthesizes ethnomedicinal knowledge, phytochemical composition, and experimental evidence to explore the biological plausibility by which A. muricata may indirectly influence hematopoietic processes. Bioactive constituents of A. muricata, including flavonoids, polyphenols, and acetogenins, have demonstrated antioxidant, anti-inflammatory, and immunomodulatory properties in preclinical models. These effects are particularly relevant given the established roles of oxidative stress and chronic inflammation in disrupting hematopoietic stem and progenitor cell function and bone marrow homeostasis. Rather than proposing direct erythropoietic activity, this review emphasizes indirect, marrow-supportive mechanisms through which A. muricata may contribute to the preservation of hematopoietic function under conditions of physiological or inflammatory stress. The limitations of the current evidence base, including the predominance of in vitro and animal studies and the absence of direct hematopoietic endpoints in humans, are critically discussed. Overall, this review provides a cautious, integrative framework linking A. muricata bioactivity to hematopoietic regulation and highlights key gaps that must be addressed before any translational or clinical relevance can be established. Full article

Under China’s dual-carbon goals, Green Finance Policy (GFP) and the Environmental Protection Tax Policy (ETP) are key tools for firm-level green transformation, yet their joint micro-effects remain underexplored. Using Shanghai and Shenzhen A-share listed firms from 2011–2022, this study treats the overlapping rollout of the Green Finance Reform and Innovation Pilot Zones and the Environmental Protection Tax reform as a staggered quasi-natural experiment and applies a multi-period DID to identify their synergistic effect on Corporate Green Technology Innovation. Results show that each policy alone promotes green innovation and that their coordination further strengthens the effect. The synergy operates mainly by easing financing constraints and increasing R&D investment. The effect is stronger among firms with better resources, governance, and digitalization, and in regions with stronger institutional environments; it is also more evident in non-heavy-polluting and non-manufacturing sectors. While the policy mix raises both innovation quantity and quality, it does not significantly improve total factor productivity, indicating a “weak Porter effect.” These findings provide micro-level evidence on GFP–ETP synergy and inform the refinement of green finance, environmental tax design, and firm-level green transition policies. Full article

The construction sector is responsible for significant global energy consumption and CO${}_2$ emissions, largely driven by carbon-intensive materials such as ordinary Portland cement and steel. In response to increasing decarbonization and circular economy demands, several strategically relevant categories of sustainable construction materials have been developed, particularly natural and bio-based systems, recycled and waste-derived materials, low-carbon cementitious binders, and emerging multifunctional composites. However, research remains fragmented across material classes and performance metrics. This systematic review evaluates advances published between 2018 and 2026 following the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) 2020 methodology. Peer-reviewed studies were systematically identified and analyzed to compare mechanical performance, durability, embodied carbon reduction, and life-cycle environmental impacts across these selected material pathways. The results indicate substantial decarbonization potential. Low-carbon cementitious materials report CO${}_2$ reductions of approximately 10–75% relative to conventional systems, while engineered timber and bamboo demonstrate 28–70% lower carbon footprints due to reduced embodied energy and biogenic carbon storage. Recycled aggregates and industrial by-products enhance circularity but remain sensitive to transport distance and processing intensity. Trade-offs between mechanical capacity and environmental performance are evident in lightweight and bio-based systems. Overall, sustainability gains are maximized through integrated hybrid construction strategies rather than isolated material substitution. This review provides a comparative evidence-based synthesis and identifies key research gaps and implementation challenges for accelerating low-carbon construction. Full article

Phenolic compounds are vital bioactive constituents in fruits, yet modern strawberry breeding has often reduced their diversity. Here, we employed a multi-omics approach integrating UPLC-MS/MS-based metabolomics and RNA-seq transcriptomics to investigate the divergence in phenolic profiles and their transcriptional regulation between a wild strawberry (Fragaria nilgerrensis, HM) and three cultivated varieties (white ‘Danxue’ (DX), pink ‘Fenyu’ (FY), and red ‘Red Face 99’ (RF)). The wild HM genotype exhibited higher antioxidant activity and a significantly more complex phenolic profile, dominated by high-abundance galloylated and benzoylated glucosides (e.g., digallic acid methyl ester, salicylic acid-2-O-glucoside) that were largely absent or depleted in cultivated fruits. In contrast, the cultivated varieties displayed specialized yet simplified profiles: DX accumulated hydroxycinnamoyl galactonic acids, FY was enriched in feruloylated glucosides, and RF was characterized by coumaroyl-glucose derivatives. Transcriptomic analysis identified a set of MYB transcription factors (e.g., FxaYL_531g0581170, FxaYL_642g0175720) significantly upregulated in wild HM, with strong correlations to key bioactive phenolics such as 4-hydroxybenzoate and salicylic acid derivatives. These findings illustrate how selective breeding has reshaped phenolic composition through alterations in MYB regulatory networks. The wild strawberry germplasm thus represents a valuable natural reservoir for biofortification strategies aimed at restoring the nutritional and functional quality of modern strawberry cultivars. Full article

Classification of vehicle engines using the chemical composition of the exhaust from these engines can be used to identify the engine’s design and verify compliance with environmental regulations through the vehicle’s emissions. This paper describes a method to identify the type of vehicles using machine learning (ML), where low-cost MQ series sensors measure the gases and particle emissions from a vehicle exhaust system, while simultaneously collecting and measuring the vehicle’s temperature and humidity levels. A custom-designed multi-sensor exhaust sensing module is employed to capture real-time exhaust emissions prior to entering the atmosphere. Exhaust samples are collected from vehicles representing three major engine categories: petrol, diesel, and compressed natural gas (CNG). In addition, fresh air samples are collected as a baseline environmental reference for comparison. All exhaust measurements are collected under controlled and consistent engine operating conditions to ensure comparable emission profiling across vehicle classes. To ensure consistent combustion-based emission profiling, this study focuses on conventional fuel-powered vehicles. MQ-series gas sensors are sensitive to combustion by-products emitted during engine operation, such as carbon monoxide (CO), hydrocarbons (HC), while also exhibiting cross-sensitivity to other gaseous components present in exhaust mixtures. Nevertheless, the proposed system performs pattern-based classification using relative sensor response signatures. Standardization of data is achieved through z-score normalization. The best models developed (based on three separate experimental designs) are trained and validated using six supervised machine learning algorithms such as Logistic Regression, Support Vector Machine (RBF), k-Nearest Neighbors, Random Forest, Gradient Boosting Decision Tree, and XGBoost and are compared against one another. Evaluation of the tested algorithms using various evaluation metrics demonstrated that ensemble models outperformed all other algorithms, achieving the highest accuracy of 99.5%. Furthermore, noise analysis confirms that the proposed solution maintains high classification accuracy (more than 89%) even under substantial sensor perturbations mimicking the real-world deployment. The solution proposed below illustrates how using gas sensors and advanced algorithms can provide accurate exhaust identification and identify engines in real-time. Full article

Low-light (LL) stress is a major abiotic limiting factor in protected cherry tomato production, adversely affecting vegetative growth, inducing oxidative damage, and disrupting fruit sugar metabolism. To clarify the regulatory role of exogenous abscisic acid (ABA) in mitigating LL stress, we examined the effects of varying ABA concentrations on plant growth, antioxidant capacity, and fruit sugar metabolism in cherry tomatoes under low-light conditions. A two-factor randomized complete block design, with two light regimes—normal light (NL, 100% natural sunlight) and low light (LL, 25% natural sunlight)—and three ABA concentrations (CK: 0 mg·L⁻¹, T1: 10 mg·L⁻¹, T2: 20 mg·L⁻¹). Fruits were sampled at three typical ripening stages (green mature, breaker, and red ripe) to evaluate vegetative and reproductive physiological responses. The results showed that exogenous ABA application effectively suppressed LL-induced excessive stem elongation and alleviated LL-caused reductions in stem diameter and biomass accumulation. ABA treatment significantly increased peroxidase (POD) activity and reduced malondialdehyde (MDA) and hydrogen peroxide (H₂O₂) accumulation, thereby relieving LL-triggered oxidative damage. In addition, ABA regulated key sugar-metabolizing enzymes (soluble acid invertase (SAI), sucrose synthase (SS), sucrose phosphate synthase (SPS), and amylase (Amy)) and the transcript levels of related functional genes (HXK1, SPS, SS, AI), thereby mediating stage-dependent fruit sugar metabolism under LL stress. In conclusion, exogenous ABA effectively modulates vegetative growth, antioxidant homeostasis, and stage-specific fruit sugar metabolism, ultimately alleviating low-light stress damage in cherry tomato. Among the tested treatments, 20 mg·L⁻¹ ABA exhibited the most pronounced mitigation effects, which can be recommended as an optimal foliar application concentration for cherry tomato cultivation in low-light protected facilities. Full article

Background: Fused deposition modeling (FDM) is one of the most well-known and often published methods for 3D-printed drug delivery systems. In early scientific reports, the active pharmaceutical ingredients were added by soaking, but later, a new milestone was established, after researchers started to manufacture their own filaments by hot-melt extrusion (HME). The number of publications covering this method has multiplied in the last decade, a wide range of natural and synthetic polymers have been tested with versatile active pharmaceutical ingredient components, and various printing parameters and their effects have been investigated. Objectives: In this review, we aim to synthesize how the available quality by design approaches and the scientific results established so far can facilitate the creation of a guideline for appropriate quality production of HME-FDM 3D-printed pharmaceuticals. Methods: Based on PRISMA 2020 guidelines, a systematic search of relevant publications from 2015 to 2025 was carried out using the PubMed database. Twenty-six articles were included, based on number of monitored parameters and methodological description. Reporting of important quality processes and material parameters was assessed. Results: HME, the FDM, and analytical testing experiences were compared and collected into three tables from the selected publications. In two different sections, the pharmacopeial dosage-form tests and the involvement of process analytical technologies (PAT) were also analyzed. We found that reporting of influential parameters is heterogenous, and lack of robust reporting schemes limits the development of QbD approaches. Conclusions: Regarding the data, trends were synthetized, and a guideline was created which is limited by inconsistent parameter reporting. Full article

Riverine systems in tropical deltaic environments are increasingly exposed to hydrological variability driven by climate change, sea level rise, and extreme precipitation. In Nigeria’s Niger Delta, recurrent flooding and environmental degradation are intensifying pressures on freshwater ecosystems and dependent communities. This study examines hydrological stressors in riverine settlements of Bayelsa State and explores associated socio-ecological responses. Using an exploratory qualitative design, data were collected from 51 women residing in highly vulnerable riverine communities through 24 in-depth interviews and three focus group discussions. Thematic analysis identified prolonged flooding, riverbank erosion, salinity intrusion, water quality deterioration, and oil pollution, as key drivers of declining fisheries, reduced agricultural productivity, and household water insecurity. These stressors have prompted relocation, livelihood diversification, and reliance on indigenous adaptation practices. The study recommends: (1) installation of community-based flood early warning systems; (2) routine monitoring of surface water quality and salinity; (3) enforcement of oil spill remediation and pollution control measures; (4) rehabilitation of wetlands and natural drainage channels; and (5) targeted support for climate-resilient livelihoods such as aquaculture and elevated farming systems. These measures are critical for sustaining freshwater ecosystems and strengthening resilience in vulnerable deltaic communities. Full article

Cold stress (CS) represents a major environmental factor that adversely affects plant growth, development, and productivity. To cope with low-temperature conditions, plants have evolved sophisticated mechanisms for CS perception and response, mediated through complex cellular signaling networks and physiological processes. Central to these adaptive responses are phytohormones, which function either independently or through synergistic and antagonistic interactions to fine-tune CS tolerance. This review synthesizes current knowledge on the roles of major classical phytohormones and signaling metabolites in regulating CS tolerance in plants. We first outline the molecular mechanisms involved in CS sensing and signal transduction, highlighting the roles of membrane-associated sensors, calcium signaling, and downstream transcriptional networks. Then, we discuss the contributions of key classical phytohormones, including auxin, abscisic acid, ethylene, salicylic acid, cytokinin, jasmonic acid, brassinosteroids, gibberellic acid, strigolactones, and signaling metabolites, including melatonin and gamma-aminobutyric acid, to CS tolerance, highlighting their individual and interacting roles in modulating gene expression regulation, antioxidant defense and physiological adaptations. We also discuss the crosstalk between these hormones, emphasizing the dynamic and often context-dependent nature of their interactions in response to CS. Furthermore, the review highlights recent advances in CRISPR/Cas9-based genome editing strategies targeting phytohormone biosynthesis, signaling, and response pathways to improve CS tolerance in plants. By integrating hormonal signaling, molecular regulation, and modern biotechnological tools, this review provides a comprehensive framework for understanding phytohormone-mediated CS adaptation and offers perspectives for developing climate-resilient crops through genetic and agronomic approaches. Full article

Accident reports provide a detailed account of environmental causes, unsafe human behaviors, and subsequent chain reactions. These records serve as essential resources for analyzing accident mechanisms and exploring potential risk patterns within production safety processes. Currently, Graph based Retrieval-Augmented Generation (RAG), which integrates Large Language Models (LLMs) with Knowledge Graphs (KGs), has emerged as a leading approach for complex causal question answering over extensive unstructured accident documentation. However, the application of this technology in the production safety domain still encounters two primary challenges. First, knowledge graph construction using a single granularity fails to capture fine-grained case details and macro-level standard systems. Second, traditional one-step retrieval paradigms lack the capacity to track deep causal chains or interpret the complex logic of multi-factor coupling. To address these limitations, we propose CausalAgent, a hierarchical graph-enhanced multi-agent framework for causal question answering in production safety accident reports. This framework innovatively combines a Hierarchical Causal Graph (HC-Graph) and a Multi-Agent Collaborative Reasoning (MACR) mechanism. Specifically, the HC-Graph employs a two-layer architecture that links a fine-grained instance layer with a national standard causation layer to resolve conflicts in semantic granularity. The MACR mechanism converts complex natural language queries into executable structured queries and logic verification steps through the sequential cooperation of four specialized agents, namely the Graph Parsing Agent, the Problem Analysis Agent, the Query Generation Agent, and the Reasoning Insight Agent. CausalAgent enables in-depth mining of accident causation mechanisms and provides scientific, robust and interpretable intelligent support for data-driven risk assessment and emergency decision-making. Experiments on real-world accident datasets demonstrate that CausalAgent achieves a $100.0\%$ query execution rate and an $87.3\%$ reasoning accuracy, outperforming the SOTA baseline by $45.2\%$ in terms of absolute accuracy. Full article

Radionuclide contamination of surface water bodies poses a significant environmental challenge, particularly for low-productivity dystrophic systems where natural self-purification capacity is limited. This study aimed to assess the potential of phytoplankton and bottom sediments as biogeochemical barriers for radionuclides. Laboratory modeling of ⁹⁰Sr, ²³³U, ²³⁹Pu, and ²⁴¹Am accumulation was conducted using samples of Lake Dryazlo (Tver Oblast) water and bottom sediments as a representative dystrophic model system. Sorption onto phytoplankton biomass over a single growing season was estimated at 1.89 × 10⁴, 5.41 × 10⁴, 6.64 × 10⁴, and 4.04 × 10⁴ Bq g⁻¹ dry biomass for ⁹⁰Sr, ²³³U, ²³⁹Pu, and ²⁴¹Am, respectively. Actinide immobilization in bottom sediments depended on mineral composition and microbial community activity. Ammophos addition increased radionuclide removal from the liquid phase by 2–5-fold through enhanced phytoplankton productivity, and promoted actinide fixation via phosphate mineral phase formation and stimulation of anaerobic sulfur- and iron-cycling bacteria. These results demonstrate a viable biogeochemical barrier approach applicable to the decommissioning of radioactive waste storage ponds and remediation of radionuclide-contaminated water bodies. Full article

The growing interest in clean-label and naturally preserved foods has pushed the scientific community to research essential oils (EOs) as sustainable, multifunctional alternatives to chemical preservatives. These plant volatile compounds exhibit strong antimicrobial and antioxidant activities, making them promising ingredients for natural preservation. Fermented meat products, though highly nutritional, are particularly at risk of microbial spoilage and contamination by foodborne pathogens due to their complex microbiota and processing conditions. This review examines the role of EOs as natural antimicrobials in fermented meat systems, summarizing their mechanisms of action, efficiency against key pathogens, and impact on safety, shelf life, and sensory attributes. Additionally, it discusses technological challenges related to volatility, stability, and sensory alterations, and outlines mitigation strategies such as encapsulation, nanoemulsions, and controlled-release delivery systems. By critically presenting current progress and identifying research gaps such as standardization and matrix interactions, this review contributes to the development of effective, natural, and clean-label preservation strategies. These insights support innovation and sustainability in the meat processing industry by bridging the gap between antimicrobial efficacy and sensory acceptability. Full article