Search Results (826)

Since the onset of industrialization, the safety of arable land has become a pressing global concern, with soil salinization emerging as a critical threat to agricultural productivity and food security. To address this challenge, the cultivation of economically valuable salt-tolerant plants has been proposed as a viable strategy. In the study, we investigated the physiological and molecular responses of Lycium ruthenicum Murr. to varying NaCl concentrations. Results revealed a concentration-dependent dual effect: low NaCl levels significantly promoted seed germination, while high concentrations exerted strong inhibitory effects. To elucidate the mechanisms underlying these divergent responses, a combined analysis of metabolomics and transcriptomics was applied to identify key metabolic pathways and genes. Notably, salt stress enhanced photosynthetic efficiency through coordinated modulation of ribulose 5-phosphate and erythrose-4-phosphate levels, coupled with the upregulation of critical genes encoding RPIA (Ribose 5-phosphate isomerase A) and RuBisCO (Ribulose-1,5-bisphosphate carboxylase/oxygenase). Under low salt stress, L. ruthenicum maintained intact cellular membrane structures and minimized oxidative damage, thereby supporting germination and early growth. In contrast, high salinity severely disrupted PS I (Photosynthesis system I) functionality, blocking energy flow into this pathway while simultaneously inducing membrane lipid peroxidation and triggering pronounced cellular degradation. This ultimately suppressed seed germination rates and impaired root elongation. These findings suggested a mechanistic framework for understanding L. ruthenicum adaptation under salt stress and pointed out a new way for breeding salt-tolerant crops and understanding the mechanism. Full article

The persistent challenge of fracture-driven interference (FDI) during large-scale hydraulic fracturing in the southern Sichuan Basin has severely compromised shale gas productivity, while the existing research has inadequately addressed both FDI risk reductions and the optimization of reservoir stimulation. To bridge this gap, this study developed a mechanistic model of the competitive multi-cluster fracture propagation under non-uniform perforation conditions and established a perforation-based design methodology for the mitigation of horizontal well interference. The results demonstrate that spindle-shaped perforations enhance the uniformity of fracture propagation by 20.3% and 35.1% compared to that under uniform and trapezoidal perforations, respectively, with the perforation quantity (48) and diameter (10 mm) identified as the dominant control parameters for balancing multi-cluster growth. Through a systematic evaluation of the fracture communication mechanisms, three distinct inter-well types of FDI were identified: Type I (natural fracture–stress anisotropy synergy), Type II (natural-fracture-dominated), and Type III (stress-anisotropy-dominated). To mitigate these, customized perforation schemes coupled with geometry-optimized fracture layouts were developed. The surveillance data for the offset well show that the pressure interference decreased from 14.95 MPa and 6.23 MPa before its application to 0.7 MPa and 0 MPa, achieving an approximately 95.3% reduction in the pressure interference in the application wells. The expansion morphology of the inter-well fractures confirmed effective fluid redistribution across clusters and containment of the overextension of planar fractures, demonstrating this methodology’s dual capability to enhance the effectiveness of stimulation while resolving FDI challenges in deep shale reservoirs, thereby advancing both productivity and operational sustainability in complex fracturing operations. Full article

The main soil type in the Sanjiang Plain of Northeast China, dryland albic soil is of great significance for studying nutrient distribution characteristics. This study focuses on 852 Farm in the typical dryland albic soil area of the Sanjiang Plain, using a combination of paired t-test, geostatistics, correlation analysis, and principal component analysis to systematically reveal the spatial differentiation of soil nutrients in the black soil layer and white clay layer of dryland albic soil, and to clarify the impact mechanism of plow layer nutrient characteristics on crop productivity. The results show that the nutrient content order in both the black and white clay layers is consistent: total potassium (TK) > organic matter (OM) > total nitrogen (TN) > total phosphorus (TP) > alkali-hydrolyzable nitrogen (HN) > available potassium (AK) > available phosphorus (AP). Both layers exhibit a spatial pattern of overall consistency and local differentiation, with spatial heterogeneity dominated by altitude gradients—nutrient content increases with decreasing altitude. Significant differences exist in nutrient content and distribution between the black and white clay layers, with the comprehensive fertility of the black layer being significantly higher than that of the white clay layer, particularly for TN, TP, TK, HN, and OM contents (effect size > 8). NDVI during the full maize growth period is significantly positively correlated with TP, TN, AK, AP, and HN, and the NDVI dynamics (first increasing. then decreasing) closely align with the peak periods of available nitrogen/phosphorus and crop growth cycles, indicating a strong coupling relationship between vegetation biomass accumulation and nutrient availability. These findings provide important references for guiding rational fertilization, agricultural production layout, and ecological environmental protection, contributing to the sustainable utilization of dryland albic soil resources and sustainable agricultural development. Full article

A circular tri-trophic system integrating aquaponics, i.e., combined cultivation of crops and fish, with insect rearing is presented for lettuce cultivation. The nutrition cycle among crops, insects and fish turns waste into resource, thereby increasing the sustainability of this food production system. A comprehensive evaluation of the system’s efficiency was performed, including the growth, functional and resource use efficiency traits of lettuce, the dynamics of which were followed in a pilot-scale aquaponics greenhouse, under three treatments: conventional hydroponics (HP) as the control, coupled aquaponics (CAP) with crops irrigated with fish-derived water, and decoupled aquaponics (DCAP), where fish-derived water was amended with fertilizers to reach the HP target. The main findings indicate comparable physiological performance between DCAP and HP, despite the slightly lower yield observed in the former. The CAP treatment exhibited a significant decrease in biomass accumulation and functional impairments, which were attributed to reduced nutrient levels in lettuce leaves. The DCAP treatment exhibited a 180% increase in fertilizer use efficiency compared to the HP treatment. We conclude that the tri-trophic cropping system with the implementation of DCAP variant is an effective system that enables the combined production of crops and fish, the latter being fed with sustainably derived insect protein. The tri-trophic system improves the environmental impact and sustainability of lettuce production, while making circularity feasible. Full article

A nanoparticle formulation was generated from distiller dried grains with solubles (DDGS), and its effect on the production of anthraquinones (AQs) was evaluated on Rubia tinctorum hairy roots. The DDGS material was washed with water and ethyl acetate to remove mainly the soluble organic/inorganic molecules and reduce the fat content, respectively, followed by an alkaline treatment to remove the polysaccharides. The resulting alkaline solutions were then lyophilized and redispersed in deionized water to generate a monodispersed nanoparticulate formulation (DDGS-NP) with a hydrodynamic diameter and zeta potential of 227 ± 42 nm and −53 ± 7 mV, respectively. The formulation demonstrated good colloidal stability over time, and sterilized DDGS-NPs maintained comparable physicochemical properties. The nanoparticles were enriched in protein fractions, unsaturated fatty acids, and orthophosphate anion components from DDGS, as determined by solid-state Nuclear Magnetic Resonance (NMR), X-ray photoelectron spectroscopy (XPS), organic elemental analysis (OEA), and inductively coupled plasma optical emission spectrometry (ICP-OES) techniques. The DDGS-NPs were tested at different concentrations on Rubia tinctorum hairy roots, in comparison to or in combination with methyl jasmonate (MeJ), for their capacity to induce the production of AQs. All DDGS-NP concentrations increased the production of specific AQs to 7.7 (100 mg L⁻¹), 7.8 (200 mg L⁻¹), and 9.3 µmol/gFW (500 mg L⁻¹), with an extracellular AQ accumulation of 18 µM for the highest DDGS-NP concentration, in comparison with the control hairy roots (~2 µM AQ). The plant growth was not affected at any of the tested nanoparticle concentrations. Interestingly, the combination of DDGS-NPs and MeJ resulted in the highest extracellular AQ accumulation in R. tinctorum root cultures. Full article

The Qinghai–Tibetan Plateau (QTP), often referred to as the “Third Pole” of the world, harbors alpine grassland ecosystems that play an essential role as global carbon sinks, helping to mitigate the pace of climate change. Nonetheless, alterations in natural environmental conditions coupled with escalating human activities have disrupted the seasonal growth cycles of grasslands, thereby intensifying degradation processes. To date, the key drivers and lifecycle dynamics of Grassland Depletion across the QTP remain contentious, limiting our comprehension of its ecological repercussions and regulatory mechanisms. This study comprehensively investigates grassland degradation on the Qinghai–Tibetan Plateau, analyzing its drivers and changes in ecological suitability during the growing season. By integrating natural factors (e.g., precipitation and temperature) and anthropogenic influences (e.g., population density and grazing intensity), it examines observational data from over 160 monitoring stations collected between the 1980s and 2020. The findings reveal three distinct phases of grassland degradation: an acute degradation phase in 1990 (GDI, Grassland Degradation Index = 2.53), a partial recovery phase from 1996 to 2005 (GDI < 2.0) during which the proportion of degraded grassland decreased from 71.85% in 1990 to 51.22% in 2005, and a renewed intensification of degradation after 2006 (GDI > 2.0), with degraded grassland areas reaching 56.39% by 2020. Among the influencing variables, precipitation emerged as the most significant driver, interacting closely with anthropogenic factors such as grazing practices and population distribution. Specifically, the combined impacts of precipitation with population density, grazing pressure, and elevation were particularly notable, yielding interaction q-values of 0.796, 0.767, and 0.752, respectively. Our findings reveal that while grasslands exhibit superior carbon sink potential relative to forests, their productivity and ecological functionality are undergoing considerable declines due to the compounded effects of multiple interacting factors. Consequently, the spatial distribution of ecologically suitable zones has contracted significantly, with the remaining high-suitability regions concentrating in the “twin-star” zones of Baingoin and Zanda grasslands, areas recognized as focal points for future ecosystem preservation. Furthermore, the effects of climate change and intensifying anthropogenic activity have driven the reduction in highly suitable grassland areas, shrinking from 41,232 km² in 1990 to 24,485 km² by 2020, with projections indicating a further decrease to only 2844 km² by 2060. This study sheds light on the intricate mechanisms behind Grassland Depletion, providing essential guidance for conservation efforts and ecological restoration on the QTP. Moreover, it offers theoretical underpinnings to support China’s carbon neutrality and peak carbon emission goals. Full article

Background/Objectives: One current cancer treatment is immunotherapy, in which tumor antigens (such as MAGE) or adjuvants (such as CpGs) can be used to induce the destruction of tumor cells by the immune system; however, the therapeutic response is generally weak. Therefore, it is necessary to develop a strategy that increases the immune response induced by tumor antigens and CpGs. We propose the coupling of tumor antigens and adjuvants to chitosan (Cs) microparticles to improve the immune response against cancer, as these microparticles can activate the innate immune response when recognized by macrophages and dendritic cells (DCs). Methods: Cs microparticles coupled with CpGs and tumor antigens were constructed with the emulsification method; then, their morphology, in vitro biological effect on DCs, and therapeutic effect in a murine melanoma model were analyzed. Results: The Cs microparticles showed a rounded morphology and a size of approximately 5 μ; in addition, they were not cytotoxic in in vitro assays and induced the production of IFNα. Finally, in the murine model of melanoma, treatment with Cs microparticles coupled to MAGE or CpGs reduced the tumor growth rate and increased both survival and the presence of cell death areas in the tumor parenchyma in contrast to the control group. Conclusions: The results suggest that treatment with Cs microparticles coupled to tumor antigen and/or CpGs can be considered a promising strategy in the field of immunotherapy based on the use of biomaterials. Full article

Background/Objectives: In the context of preclinical studies, we have hitherto showcased that a low-molecular-weight ruthenium(III) complex we named AziRu holds significant potential for further developments as an anticancer candidate drug. When appropriately converted into stable nanomaterials and delivered into tumor cells, AziRu exhibits superior antiproliferative activity, benefiting from a multimodal mechanism of action. The activation of regulated cell death (RCD) pathways (i.e., apoptosis and autophagy) has been proved in metastatic phenotypes, including triple-negative breast cancer (TNBC) cells. This study focuses on a bioengineered lipophilic derivative of AziRu, named PalmiPyRu, that we are currently developing as a potential anticancer drug in preclinical studies. When delivered in this way, AziRu confirms a multimodal mechanism of action in effectively blocking the growth and proliferation of TNBC phenotypes. Special focus is reserved for the activation of the ferroptotic pathway as a consequence of redox imbalance and interference with iron homeostasis, as well as the glutathione biosynthetic pathway. Methods: Human preclinical models of specific TNBC phenotypes and healthy cell cultures of different histological origin were selected. After in vitro treatments, cellular responses were carefully analyzed, and targeted biochemical and molecular biology experiments coupled to confocal microscopy allowed us to explore the antiproliferative effects of PalmiPyRu. Results: In this study, we unveil that PalmiPyRu can enter TNBC cells and interfere with both the iron homeostasis and the cystine-glutamate antiporter system Xc-, causing significant oxidative stress and the accumulation of lipid oxidation products. The increase in intracellular reactive free iron and depletion of glutathione engender a lethal condition, driving cancer cells toward the activation of ferroptosis. Conclusions: Overall, these outcomes allow us, for the first time, to couple the antiproliferative effect of a ruthenium-based candidate drug with the inhibition of the Xc- antiporter system and Fenton chemistry, thereby branding PalmiPyRu as an effective multimodal inducer of ferroptosis. Molecular mechanisms of action deserve further investigations, and new studies are underway to uncover how interference with Xc- controls cell fate, allowing us to explore the connection between iron metabolism regulation, oxidative stress and RCD pathways activation. Full article

Atherosclerosis (AS), a progressive inflammatory disease of coronary arteries, the aorta, and the internal carotid artery, is considered one of the main contributors to cardiovascular disorders. Blood flow is restricted by accumulating lipid-rich macrophages (foam cells), calcium, fibrin, and cellular debris into plaques on the intima of arterial walls. Butyrate maintains gut barrier integrity and modulates immune responses. Butyrate regulates G-protein-coupled receptor (GPCR) signaling and activates nuclear factor kappa-B (NF-κB), activator protein-1 (AP-1), and interferon regulatory factors (IFRs) involved in the production of proinflammatory cytokines. Depending on the inflammatory stimuli, butyrate may also inactivate NF-κB, resulting in the suppression of proinflammatory cytokines and the stimulation of anti-inflammatory cytokines. Butyrate modulates mitogen-activated protein kinase (MAPK) to promote or suppress macrophage inflammation, muscle cell growth, apoptosis, and the uptake of oxidized low-density lipoprotein (ox-LDL) in macrophages. Activation of the peroxisome proliferator-activated receptor γ (PPARγ) pathway plays a role in lipid metabolism, inflammation, and cell differentiation. Butyrate inhibits interferon γ (IFN-γ) signaling and suppresses NOD-, LRR-, and pyrin domain-containing protein 3 (NLRP3) involved in inflammation and scar tissue formation. The dual role of butyrate in AS is discussed by addressing the interactions between butyrate, intestinal epithelial cells (IECs), endothelial cells (ECs) of the main arteries, and immune cells. Signals generated from these interactions may be applied in the diagnosis and intervention of AS. Reporters to detect early AS is suggested. This narrative review covers the most recent findings published in PubMed and Crossref databases. Full article

The production of β-alanine from fatty acid feedstocks presents a promising synthetic strategy due to its high carbon yield. However, the excessive reducing power generated during fatty acid utilization disrupts cellular redox balance, adversely affecting metabolism and limiting the efficiency and final yield of β-alanine production. To address this challenge, we engineered a co-production system in which excess reducing equivalents generated during fatty acid β-oxidation and β-alanine biosynthesis were consumed by growth-coupled lycopene biosynthesis. The resulting dual-pathway strain, SA01, achieved 44.78 g/L β-alanine and 3.07 g/L lycopene in bioreactor fermentation, representing a 21.45% increase in β-alanine production compared to the β-alanine-producing strain WA01, and a 74.43% increase in lycopene production compared to the lycopene-producing strain LA01. Further optimization in strain SA06, involving cofactor engineering to shift redox flow from NADH to NADPH, enhanced the titers to 52.78 g/L β-alanine and 3.61 g/L lycopene. Metabolite analysis confirmed a decrease in intracellular NADH and FADH₂ levels in SA06, indicating restoration of redox balance during the late fermentation phase. Additional improvements in the fermentation process, including gradual carbon source switching, optimization of the induction strategy, and fine-tuning of conditions during both growth and bioconversion phases, resulted in further increases in product titers, reaching 72 g/L β-alanine and 6.15 g/L lycopene. This study offers valuable insights into the development of microbial co-production systems, highlighting the critical role of dynamic cofactor and redox balance management, as well as process optimization, in improving production efficiency. Full article

Soils serve as critical carbon reservoirs, playing an essential role in climate change mitigation and agricultural sustainability. Accurate soil property determination relies on soil spectral reflectance data from Earth observation (EO), but current vegetation models often oversimplify soil conditions. This study introduces a novel approach that combines radiative transfer models (RTMs) with open-access soil spectral libraries to address this challenge. Focusing on conditions of low soil moisture content (SMC), photosynthetic vegetation (PV), and non-photosynthetic vegetation (NPV), the coupled Marmit–Leaf–Canopy (MLC) model is used to simulate early crop growth stages. The MLC model, which integrates MARMIT and PRO4SAIL2, enables the generation of mixed soil–vegetation scenarios. A simulated EO disturbed soil spectral library (DSSL) was created, significantly expanding the EU LUCAS cropland soil spectral library. A 1D convolutional neural network (1D-CNN) was trained on this database to predict Soil Organic Carbon (SOC) content. The results demonstrated relatively high SOC prediction accuracy compared to previous approaches that rely only on RTMs and/or machine learning approaches. Incorporating soil moisture content significantly improved performance over bare soil alone, yielding an R² of 0.86 and RMSE of 4.05 g/kg, compared to R² = 0.71 and RMSE = 6.01 g/kg for bare soil. Adding PV slightly reduced accuracy (R² = 0.71, RMSE = 6.31 g/kg), while the inclusion of NPV alongside moisture led to modest improvement (R² = 0.74, RMSE = 5.84 g/kg). The most comprehensive model, incorporating bare soil, SMC, PV, and NPV, achieved a balanced performance (R² = 0.76, RMSE = 5.49 g/kg), highlighting the importance of accounting for all surface components in SOC estimation. While further validation with additional scenarios and SOC prediction methods is needed, these findings demonstrate, for the first time, using radiative-transfer simulations of mixed vegetation-soil-water environments, that an EO-DSSL approach enhances machine learning-based SOC modeling from EO data, improving SOC mapping accuracy. This innovative framework could significantly improve global-scale SOC predictions, supporting the design of next-generation EO products for more accurate carbon monitoring. Full article

Crop growth monitoring at various growth stages is essential for optimizing agricultural inputs and enhancing crop yield. Nitrogen plays a critical role in plant development; however, its improper application can reduce productivity and, in the long term, degrade soil health. The aim of this study was to develop a non-invasive approach for nitrogen estimation through proxies (Nitrogen Flavanol Index) in Mentha arvensis using UAV-derived multispectral vegetation indices and machine learning models. Support Vector Regression, Random Forest, and Gradient Boosting were used to predict the Nitrogen Flavanol Index (NFI) across different growth stages. Among the tested models, Random Forest achieved the highest predictive accuracy (R² = 0.86, RMSE = 0.32) at 75 days after planting (DAP), followed by Gradient Boosting (R² = 0.75, RMSE = 0.43). Model performance was lowest during early growth stages (15–30 DAP) but improved markedly from mid to late growth stages (45–90 DAP). The findings highlight the significance of UAV-acquired data coupled with machine learning approaches for non-destructive nitrogen flavanol estimation, which can immensely contribute to improving real-time crop growth monitoring. Full article

Virus-like particles (VLPs) have the potential to become a versatile carrier platform for vaccination against multiple diseases. In the light of short process development timelines and the demand for reliable and robust processes, metabolic modeling of cell culture processes offers great advantages when coupled with a Quality-by-Design (QbD) development approach. A previous work was able to demonstrate the accurate prediction of HEK293F PiggyBac cell concentration as well as VLP titer and metabolite production with a reduced metabolic model. This work presents the reduced metabolic model for a more productive cell line Sleeping Beauty and emphasizes the need for model re-parameterization when the producer cell line changes. The goal of precise prediction for a fed-batch and continuous HEK293 cultivation can, therefore, be achieved. In terms of decision-making for downstream unit operations, a soft sensor for the prediction of main impurities like proteins and DNA was introduced for the first time for the production of lentiviral vectors with several terms describing the release of impurities like DNA and proteins, growth-related protein production, and enzymatic degradation activity associated with cell dissociation in an accurate manner. The additional information can contribute to a more efficient design phase by reducing experimental effort as well as during cultivation with data-based decision-making. With the aid of real-time process data acquisition through process analytical technology (PAT), its predictive power can be enhanced and lead to more reliable processes. Full article

Scientifically and accurately assessing the interaction between changes in human activity intensity and the surrounding ecological environment along the Qinghai–Tibet Railway is of great significance for the optimized construction of the railway and the restoration of the regional ecological environment. Based on different spatial distribution scales and construction phases of the Qinghai–Tibet Railway, this study integrates multi-source remote sensing data to construct a long-term spatiotemporal dataset of human activity intensity in the region. Drawing on analytical methods from production theory, a coupling theoretical framework based on remote sensing ecological models is proposed to quantitatively reveal the coupling relationships between the ecological environment and human activities across varying spatiotemporal scales along the Qinghai–Tibet Railway. The study finds that (1) the spatiotemporal distribution of human activity intensity along the Qinghai–Tibet Railway demonstrates clear patterns, with expansion primarily radiating from transportation corridors and their intersections, and marked spatial heterogeneity across different segments. Overall, human activity intensity increased slowly between 1990 and 2002, followed by a significant rise during the construction and opening of the Golmud–Lhasa section (2001–2007). From 2013 to 2020, the growth rate began to slow. Within a 0–30 km buffer zone centered on railway station locations (with a 15 km radius), the growth rate of human activity intensity generally decreased with increasing distance from the railway. In the 30–60 km buffer zone, this trend tended to stabilize. (2) The coupling process between ecological quality and human activity intensity across different spatiotemporal scales along the railway exhibits considerable spatial and temporal heterogeneity and complexity. The decoupling relationship is dominated by strong and weak decoupling patterns, with strong decoupling being the most prevalent. Weak decoupling is mainly distributed along the sides of the railway. Overall, in most areas along the railway, ecological quality has shown a certain degree of improvement alongside increasing human activity intensity; however, the rate of ecological improvement is generally lower than the rate of increase in human activity intensity. In some areas adjacent to the railway, intensified human activities have led to a decline in ecological quality, though the resulting ecological pressure remains relatively low. Full article

This study develops a one-pot anodic templating electrodeposition strategy using dual-cation-crosslinking and interpenetrating networks, coupled with pulsed electrical signals, to fabricate a vessel-mimetic multilayered tubular hydrogel. Typically, the anodic electrodeposition is performed in a mixture of sodium alginate (SA) and carboxymethyl chitosan (CMC), with the ethylenediaminetetraacetic acid calcium disodium salt hydrate (EDTA·Na₂Ca) incorporated to provide a secondary ionic crosslinker (i.e., Ca²⁺) and modulate the cascade reaction diffusion process. The copper wire electrodes serve as templates for electrochemical oxidation and enable a copper ion (i.e., Cu²⁺)-induced tubular hydrogel coating formation, while pulsed electric fields regulate layer-by-layer deposition. The dual-cation-crosslinked interpenetrating hydrogels (CMC/SA-Cu/Ca) exhibit rapid growth rates and tailored mechanical strength, along with excellent antibacterial performance. By integrating the unique pulsed electro-fabrication with biomimetic self-assembly, this study addresses challenges in vessel-mimicking structural complexity and mechanical compatibility. The approach enables scalable production of customizable multilayered hydrogels for artificial vessel grafts, smart wound dressings, and bioengineered organ interfaces, demonstrating broad biomedical potential. Full article