Search Results (33,648)

Medicinal plant production is essential for global health, yet how temperature, precipitation, and soil properties influence yield responses to fertilization remains poorly understood. Here, we conducted a meta-analysis of 668 observations from 79 studies, focusing on a wide range of plant species, to evaluate how nutrient inputs and environmental factors interact to shape medicinal plant productivity. We found that latitude, MAT, and MAP jointly determine global medicinal plant yield patterns. Yield increased with latitude and MAT but declined under prolonged fertilization and higher MAP. Optimal cultivation regions were identified between 15° and 35° absolute latitude, where temperature and precipitation conditions were most favorable. Compared with the arid environment of desertic climates, other regions, especially those with higher MAP in tropical areas, show a higher increase in yield. Our findings highlight that shifting precipitation-temperature regimes under climate change will affect fertilization outcomes on medicinal plant yield, emphasizing the need for spatiotemporally adaptive nutrient management strategies to ensure the sustainable yield of medicinal plants. Full article

Water resource management is critical for sustainable agriculture, especially in regions like Kazakhstan that face significant water scarcity challenges. This paper presents the development of a real-time water-level monitoring system designed to optimize water use in agriculture. The system integrates IoT sensors and cloud technologies, and analyzes data on water levels, temperature, humidity, and other environmental parameters. The architecture comprises a data collection layer with solar-powered sensors, a network layer for data transmission, a storage and integration layer for data management, a data processing layer for analysis and forecasting, and a user interface for visualization and interaction. The system was tested at the Left Bypass Canal in Taraz, Kazakhstan, demonstrating its effectiveness in providing real-time data for informed decision-making. The results indicate that the system significantly improves water use efficiency, reduces non-productive losses, and supports sustainable agricultural practices. Full article

Purslane is highly suitable for intensive microgreen cultivation due to its rapid growth, high germination rate, and exceptional nutritional profile, including omega-3 fatty acids, essential vitamins, and minerals. While previous studies have mostly emphasized its basic composition, our research investigated additional functional traits, such as pigment accumulation and antioxidant activity. We also explored the cultivation potential of a wild purslane genotype (G2), naturally growing in the Botanical Garden of the Slovak University of Agriculture in Nitra, as a sustainable alternative to commercially available seeds (G1). This study examined how genotype and substrate interactions influence growth performance, pigment concentration, and antioxidant capacity in Portulaca oleracea microgreens. Both genotypes were grown on two different substrates: agar mixed with perlite and mineral wool. Although conserved DNA-derived polymorphism marker analysis revealed a high degree of genetic similarity between G1 and G2, significant phenotypic differences were observed. G1 exhibited greater fresh biomass and shoot length, making it more visually appealing for commercial microgreen production. In contrast, G2 showed higher dry matter content and enhanced accumulation of chlorophylls and carotenoids. Antioxidant activity, measured by DPPH (2,2-diphenyl-1-picrylhydrazyl), ABTS (2,2′-azino-bis(3-ethylbenzothiazoline-6-sulfonic acid)), and FRAP (Ferric Reducing Antioxidant Power) assays, peaked in G1 cultivated on agar–perlite mix. These findings emphasize the importance of selecting the right genotype–substrate combination to optimize both quality and productivity in microgreen systems. Full article

This study established a biological fermentation process using Saccharomyces cerevisiae and Lactobacillus plantarum to deodorize squid cartilage homogenate. The optimal fermentation conditions for S. cerevisiae were determined as follows: fermentation time 105 min, temperature 34 °C, and inoculum size 0.85%. For L. plantarum, the optimum conditions were 79 min, 34.5 °C, and 4.5% inoculum. Based on electronic nose and HS-SPME-GC-MS analyses, S. cerevisiae outperformed L. plantarum in eliminating key offensive odor compounds, especially sulfur-containing compounds and aldehydes, while promoting the formation of pleasant aroma compounds such as esters and ketones (e.g., carvone and δ-pentenol). Mechanistic insights suggest that the enhanced deodorization efficiency of S. cerevisiae may be attributed to its multi-pathway synergistic metabolism, involving enzymes like dioxygenases and sulfide oxidases that facilitate the conversion of malodorous substances into odorless or pleasantly aromatic compounds. These findings provide a valuable theoretical and practical foundation for the high-value utilization of squid processing by-products and propose a promising bio-deodorization strategy for aquatic products. Full article

The survival status of Lumnitzera littorea is near threatened globally and critically endangered in China. Clarifying its global distribution pattern and its changing trends under different future climate models is of great significance for the protection and restoration of its endangered status. To build a model for this purpose, this study selected 73 actual distribution points of Lumnitzera littorea worldwide, combined with 12 environmental factors, and simulated its potential suitable habitats in six periods: the Last Interglacial (130,000–115,000 years ago), the Last Glacial Maximum (27,000–19,000 years ago), the Mid-Holocene (6000 years ago), the present (1970–2000), and the future 2050s (2041–2060) and 2070s (2061–2080). The results show that the optimal model parameter combination is the regularization multiplier RM = 4.0 and the feature combination FC (Feature class) = L (Linear) + Q (Quadratic) + P (Product). The MaxEnt model has a low omission rate and a more concise model structure. The AUC values in each period are between 0.981 and 0.985, indicating relatively high prediction accuracy. Min temperature of the coldest month, mean diurnal range, clay content, precipitation of the warmest quarter, and elevation are the dominant environmental factors affecting its distribution. The environmental conditions for min temperature of the coldest month at ≥19.6 °C, mean diurnal range at <7.66 °C, clay content at 34.14%, precipitation of the warmest quarter at ≥570.04 mm, and elevation at >1.39 m are conducive to Lumnitzera littorea’s survival and distribution. The global potential distribution areas are located along coasts. Starting from the paleoclimate, the plant’s distribution has gradually expanded, and its adaptability has gradually improved. In China, the range of potential highly suitable habitats is relatively narrow. Hainan Island is the core potential habitat, but there are fragmented areas in regions such as Guangdong, Guangxi, and Taiwan. The modern centroid of Lumnitzera littorea is located at (109.81° E, 2.56° N), and it will shift to (108.44° E, 3.22° N) in the later stage of the high-emission scenario (2070s (SSP585)). Under global warming trends, it has a tendency to migrate to higher latitudes. The development of the aquaculture industry and human deforestation has damaged the habitats of Lumnitzera littorea, and its population size has been sharply and continuously decreasing. The breeding and renewal system has collapsed, seed abortion and seedling establishment failure are common, and genetic variation is too scarce. This may indicate why Lumnitzera littorea is near threatened globally and critically endangered in China. Therefore, the protection and restoration strategies we propose are as follows: strengthen the legislative guarantee and law enforcement supervision of the native distribution areas of Lumnitzera littorea, expanding its population size outside the native environment, and explore measures to improve its seed germination rate, systematically collecting and introducing foreign germplasm resources to increase its genetic diversity. Full article

Dengue is a rapidly spreading mosquito-borne viral infection, with increasing reports of outbreaks globally. According to the World Health Organization (WHO), by 30 April 2024, over 7.6 million dengue cases were reported, including 3.4 million confirmed cases, more than 16,000 severe cases, and over 3000 deaths. As dengue remains endemic in many regions, there is a critical need for the development of new vaccines and manufacturing processes that are efficient, cost-effective, and capable of meeting growing demand. In this study, we explore an alternative process development pathway for the future manufacturing of a dengue vaccine, utilizing Komagataella phaffii (Pichia pastoris) as the host organism, one of the most promising candidates for the expression of heterologous proteins in vaccine development. It combines the speed and ease of highly efficient prokaryotic platforms with some key capabilities of mammalian systems, making it ideal for scalable and cost-effective production. The key outcomes of our research include (i) demonstrating the versatility of the Komagataella phaffii platform in the production of dengue viral-like particles (VLPs); (ii) optimizing the culture process using Design of Experiments (DoE) approaches in small-scale bioreactors; (iii) developing a novel purification platform for enveloped VLPs (eVLPs), and (iv) establishing alternative biophysical characterization methods for the dengue vaccine prototype. These findings provide a promising foundation for efficient and scalable production of dengue vaccines, addressing both technical and operational challenges in vaccine manufacturing. Full article

Chinese coalbed methane (CBM) reservoirs exhibit characteristically low recovery rates due to adsorbed gas dominance and “three-low” properties (low permeability, low pressure, and low saturation). CO₂ thermal drive (CTD) technology addresses this challenge by leveraging dual mechanisms—thermal desorption and displacement to enhance production; however, its effectiveness necessitates uniform fracture networks for temperature field homogeneity—a requirement unmet by conventional long-fracture fracturing. To bridge this gap, a coupled seepage–heat–stress–fracture model was developed, and the temperature field evolution during CTD in coal under non-uniform fracture networks was determined. Integrating multi-cluster fracture propagation with stress barrier and intra-stage stress differential characteristics, a stress-barrier-responsive diverting fracturing technology meeting CTD requirements was established. Results demonstrate that high in situ stress and significant stress differentials induce asymmetric fracture propagation, generating detrimental CO₂ channeling pathways and localized temperature cold islands that drastically reduce CTD efficiency. Further examination of multi-cluster fracture dynamics identifies stress shadow effects and intra-stage stress differentials as primary controlling factors. To overcome these constraints, an innovative fracture network uniformity control technique is proposed, leveraging synergistic interactions between diverting parameters and stress barriers through precise particle size gradation (16–18 mm targeting toe obstruction versus 19–21 mm sealing heel), optimized pumping displacements modulation (6 m³/min enhancing heel efficiency contrasted with 10 m³/min improving toe coverage), and calibrated diverting concentrations (34.6–46.2% ensuring uniform cluster intake). This methodology incorporates dynamic intra-stage adjustments where large-particle/low-rate combinations suppress toe flow in heel-dominant high-stress zones, small-particle/high-rate approaches control heel migration in toe-dominant high-stress zones, and elevated concentrations (57.7–69.2%) activate mid-cluster fractures in central high-stress zones—collectively establishing a tailored framework that facilitates precise flow regulation, enhances thermal conformance, and achieves dual thermal conduction and adsorption displacement objectives for CTD applications. Full article

The growing awareness of celiac disease and gluten sensitivities has generated interest in gluten-free products. Whole sorghum (Sorghum bicolor) is an excellent source of nutrients and is gluten-free. However, the absence of gluten makes it technologically challenging to produce leavened products. This research aims to utilize a response surface methodology to optimize the specific loaf volume and crumb firmness of a whole sorghum-based gluten-free bread formulation, evaluating different levels of milk powder, egg white, yeast, sugar, psyllium husk powder, xanthan gum, and soy lecithin. The models fit achieved an $R^2\ge 80\%$. The optimized formulation increased the specific loaf volume from 1.7 to 2.8 cm³ g⁻¹ and decreased crumb firmness from 10.6 to 3.7 N compared to the initial gluten-free bread formulation (C1). Egg white, milk powder, and psyllium contribute to the formation of a gluten-like network, which enables gas retention, dough expansion, and volume increase. In addition, soy lecithin, among hydrocolloids, enhances dough stability and moisture retention, resulting in a softer crumb. Sensory evaluation indicated good consumer acceptability (average score of 7 on a 9-point hedonic scale), particularly for texture and flavor. These findings suggest that optimal formulation of sorghum achieves both technological and sensory properties, supporting its potential as a viable gluten-free bread alternative. Full article

The application of plasma technology in agriculture has emerged as a promising approach to enhance plant health and manage microbial interactions, offering potential solutions for sustainable crop production and disease control. This study contributes to this field by exploring the effects of plasma treatments on plant physiology and microbial dynamics, with a focus on their potential to improve agricultural outcomes. This investigation aims to systematically determine optimal plasma seed treatment parameters for enhancing plant vigor and promoting beneficial microbial associations while minimizing pathogenic interactions in Arabidopsis thaliana. This study focuses on understanding the effects of various plasma treatments on chlorophyll content, root length, microbial growth, and microbial quantification in plants and microbes. The treatments involve the use of an atmospheric jet plasma handheld device, a globe plasma, and a glow discharge plasma chamber with air and argon. These treatments were applied for varying time durations from 10 s to 5 min. The results demonstrated that the globe plasma treatment for 1 min significantly enhanced chlorophyll a extraction and root length, outperforming the other treatments. Additionally, the study examined the impact of plasma on plant–microbe interactions to assess whether plasma treatments affect beneficial microbes. Plasma treatments showed minimal impact on most beneficial microbe activity, though species-specific sensitivities were observed, with Pseudomonas cedrina showing moderate growth inhibition, revealing no significant disruption to their activity. The microbial quantification assays indicated that the globe plasma treatment effectively reduced microbial counts, while combined treatment with plant and microbe plasma together did not yield significant changes. Additionally, the chlorophyll estimation of plasma-treated samples indicated that the globe plasma and atmospheric jet plasma treatments were effective in enhancing chlorophyll content, whereas the combined treatment with both plant and microbe plasma did not yield significant changes. These findings suggest that plasma treatments, especially the globe plasma, are effective in improving plant health and controlling microbial activity. Future research should focus on optimizing plasma conditions, exploring the influence of plasma parameters and the underlying mechanisms, and expanding the scope to include a wider range of plant species and microbial strains to maximize the benefits of plasma technology in agriculture. Full article

Addressing the carbon footprint in pig production is a fundamental technical basis for achieving carbon neutrality and peak carbon emissions. Only by systematically studying the carbon footprint can the goals of carbon neutrality and peak carbon emissions be effectively realized. This study aims to reduce the carbon footprint through optimized feeding strategies based on minimizing carbon emissions. To this end, this study conducted a full-lifecycle monitoring of the carbon footprint during pig growth from December 2024 to May 2025, optimizing feeding strategies using a real-time pig weight estimation model driven by deep learning to reduce resource consumption and the carbon footprint. We introduce EcoSegLite, a lightweight deep learning model designed for non-contact real-time pig weight estimation. By incorporating ShuffleNetV2, Linear Deformable Convolution (LDConv), and ACmix modules, it achieves high precision in resource-constrained environments with only 1.6 M parameters, attaining a 96.7% mAP50. Based on full-lifecycle weight monitoring of 63 pigs at the Pianguan farm from December 2024 to May 2025, the EcoSegLite model was integrated with a life cycle assessment (LCA) framework to optimize feeding management. This approach achieved a 7.8% reduction in feed intake, an 11.9% reduction in manure output, and a 5.1% reduction in carbon footprint. The resulting growth curves further validated the effectiveness of the optimized feeding strategy, while the reduction in feed and manure also potentially reduced water consumption and nitrogen runoff. This study offers a data-driven solution that enhances resource efficiency and reduces environmental impact, paving new pathways for precision agriculture and sustainable livestock production. Full article

The current management of severe traumatic brain injury (TBI) focuses on maintaining cerebral perfusion pressure (CPP) to prevent or minimize secondary brain injury, limit cerebral edema, optimize oxygen delivery to the brain, and reduce primary neuronal damage by addressing contributing risk factors such as hypotension and hypoxia. Hypotension and cardiac dysfunction are common in patients with severe TBI, often requiring treatment with intravenous fluids and vasopressors. The primary categories of resuscitation fluids include crystalloids, colloids (such as albumin), and blood products. Fluid osmolarity is a critical consideration in TBI patients, as hypotonic fluids, such as balanced crystalloids, may increase the risk of cerebral edema development and worsening. Hyperosmolar therapy is a common therapeutic approach in patients with intracranial hypertension; however, its use as a resuscitation fluid is not associated with benefits in patients with TBI and is not recommended. Given the contradictory results of trials on blood transfusion strategies in patients with TBI, the transfusion approach should be tailored to individual systemic and cerebral physiological parameters. The evaluation of recent randomized clinical trials will provide insight into whether a liberal or restrictive transfusion strategy is preferred for this patient population. Hemodynamic and multimodal neurological monitoring to assess cerebral oxygenation, autoregulation, and metabolism are essential tools for detecting early hemodynamic alterations and cerebral injury, guiding resuscitation management, and contributing to improved outcomes. Full article

The increasing integration of automation and intelligent sensing technologies in daily-use ceramic manufacturing poses new challenges for efficient scheduling under hybrid flow-shop and shared-kiln constraints. To address these challenges, this study proposes a Mixed-Integer Linear Programming (MILP) model and an Improved Discrete Hippopotamus Optimization (IDHO) algorithm designed for smart, network-aware production environments. The MILP formulation captures key practical features such as batch processing, no-idle kiln constraints, and machine re-entry dynamics. The IDHO algorithm enhances global search performance via segment-based encoding, nonlinear population reduction, and operation-specific mutation strategies, while a parallel evaluation framework accelerates computational efficiency, making the solution viable for industrial-scale, time-sensitive scenarios. The experimental results from 12 benchmark cases demonstrate that IDHO achieves superior performance over six representative metaheuristics (e.g., PSO, GWO, Jaya, DBO), with an average ARPD of 1.04%, statistically significant improvements (p < 0.05), and large effect sizes (Cohen’s d > 0.8). Compared to the commercial solver CPLEX, IDHO provides near-optimal results with substantially lower runtime. The proposed approach contributes to the development of intelligent networked scheduling systems for cyber-physical manufacturing environments, enabling responsive, scalable, and data-driven optimization in smart sensing-enabled production settings. Full article

CD19-targeted therapies, including monoclonal antibodies, antibody–drug conjugates, and chimeric antigen receptor (CAR) T-cell products, have significantly improved outcomes in relapsed/refractory diffuse large B-cell lymphoma (R/R DLBCL). Despite their clinical efficacy, resistance and antigen modulation pose substantial challenges, especially in patients requiring sequential therapy. This review provides a comprehensive overview of CD19 biology and its relevance as a therapeutic target. We examine mechanisms of resistance such as antigen loss, epitope masking, and T-cell exhaustion, as well as the implications of tumor microenvironmental immunosuppression. Future efforts should prioritize the integration of real-time diagnostics, such as flow cytometry, immunohistochemistry, and transcriptomic profiling, and AI-assisted predictive models to optimize therapeutic sequencing and expand access to personalized immunotherapy. Full article

Bupleurum is a Chinese medicinal material widely used in clinical practice. Its medicinal component is the dried roots of either the Umbrella plant Bupleurum chinense DC or Bupleurum scorzonerifolium Willd. This review systematically searched major scientific databases such as Web of Science, PubMed, and ScienceDirect, and found that it contains various bioactive substances including saikosaponins, polysaccharides, flavonoids, and volatile oils. These components have demonstrated significant efficacy in anti-tumor, anti-inflammatory, and neuroprotective activities. Research has confirmed that this medicinal herb can exert its pharmacological effects by promoting tumor cell apoptosis, inhibiting cell proliferation, regulating inflammatory signaling pathways, and alleviating neuroinflammation. Additionally, its antipyretic and antiviral properties have also garnered widespread attention. However, clinical data regarding its optimal dosage, administration routes, and safety are still insufficient, necessitating further trials for validation. Investigating the synergistic effects of Bupleurum with other drugs and the safety of its use in different populations are also key directions of current research. Given the urgent need for efficient and sustainable healthcare in modern society, a deep understanding of the mechanisms and safety of Bupleurum is of significant importance for its validation as a foundation for new drug development. In summary, Bupleurum, as a multifunctional natural product, has broad application prospects and is expected to play a greater role in future medical research and clinical practice. Full article

Against the backdrop of urban–rural integrated development, special ecological function zones, as spatial carriers with significant regional ecological value and rural development functions, are confronted with a striking conflict between ecological conservation and regional advancement. This contradiction is comprehensively reflected in the interactions among land use functions (LUFs) that differ in nature and intensity. Therefore, exploring the trade-off and synergy (TOS) among regional LUFs is not only of great significance for optimizing territorial spatial patterns and advancing rural revitalization but also provides scientific evidence for the differentiated administration of regional land use. Taking 185 townships in the Funiu Mountain area of China as research units, this study constructs a land use assessment system based on the ‘Production–Living–Ecological’ (PLE) framework, utilizing multi-source datasets from 2000 to 2020. Spearman correlation analysis, geographically weighted regression (GWR), and bivariate local spatial autocorrelation methods are employed to examine the spatio-temporal dynamics of LUFs and the spatial non-stationarity of their TOSs. The findings indicate that, throughout the research period, the production function (PF) displayed a fluctuating declining trend, whereas the living function (LF) and ecological function (EF) demonstrated a fluctuating increasing trend. Notably, EF held an absolute dominant position in the overall structure of LUFs. This is highly consistent with the region’s positioning as a special ecological function zone and also a direct reflection of the effectiveness of continuous ecological construction over the past two decades. Spatially, PF is stronger in southern, eastern, and northern low-altitude townships, correlating with higher levels of economic development; LF is concentrated around townships near county centers; and high EF values are clustered in the central and western areas, showing an opposite spatial pattern to PF and LF. A synergistic relationship is observed between PF and LF, while both PF and LF exhibit trade-offs with EF. The TOSs between different function changes demonstrate significant spatial non-stationarity: linear synergy was the primary type for PF-LF, PF-EF, and LF-EF combinations, but each combination exhibited unique spatial characteristics in terms of non-stationarity. Notably, towns identified as having different types of trade-off relationships in the study of spatial non-stationarity are key areas for township spatial governance and optimization. Through the allocation of regional resources and targeted policy tools, the functional relationships can be adjusted and optimized to attain sustainable land use. Full article