Search Results (5,485)

Nitrogen (N) and potassium (K) are essential macronutrients for plants whose functions and interactions profoundly influence plant physiological metabolism, environmental adaptation, and agricultural production efficiency. This review summarizes research advances in plant N and K nutrition and their interaction mechanisms, elucidating the key physiological functions of N and K individually and their respective absorption and transport mechanisms involving transporters such as NRTs and HAKs/KUPs. The review discusses the types of nutrient interactions (synergism and antagonism), with a primary focus on the physiological basis of N–K interactions and their interplay in root absorption and transport (e.g., K⁺-NO₃⁻ co-transport; NH₄⁺ inhibition of K⁺ uptake), photosynthesis (jointly optimizing CO₂ conductance, mesophyll conductance, and N allocation within photosynthetic machinery to enhance photosynthetic N use efficiency, PNUE), as well as sensing, signaling, co-regulation, and metabolism. This review emphasizes that N–K balance is crucial for improving crop yield and quality, enhancing fertilizer use efficiency (NUE/KUE), and reducing environmental pollution. Consequently, developing effective N–K management strategies based on these interaction mechanisms and implementing Balanced Fertilization Techniques (BFT) to optimize N–K ratios and application strategies in agricultural production represent vital pathways for ensuring food security, addressing resource constraints, and advancing green, low-carbon agriculture, including through coordinated management of greenhouse gas emissions. Full article

The transportation sector is a major consumer of primary energy and is a significant contributor to greenhouse gas emissions. Sustainable transportation requires identifying and quantifying factors influencing transport-related CO₂ emissions. This research aims to establish an adaptable, precise, and transparent forecasting structure for transport CO₂ emissions of the United States. For this reason, we proposed a multi-stage method that incorporates explainable Machine Learning (ML) and Feature Selection (FS), guaranteeing interpretability in comparison to conventional black-box models. Due to high multicollinearity among 24 initial variables, hierarchical feature clustering and multi-step FS were applied, resulting in five key predictors: Total Primary Energy Imports (TPEI), Total Fossil Fuels Consumed (FFT), Annual Vehicle Miles Traveled (AVMT), Air Passengers-Domestic and International (APDI), and Unemployment Rate (UR). Four ML methods—Support Vector Regression, eXtreme Gradient Boosting, ElasticNet, and Multilayer Perceptron—were employed, with ElasticNet outperforming the others with RMSE = 45.53, MAE = 30.6, and MAPE = 0.016. SHAP analysis revealed AVMT, FFT, and APDI as the top contributors to CO₂ emissions. This framework aids policymakers in making informed decisions and setting precise investments. Full article

While the Ankom RF system facilitates efficient high-throughput in vitro fermentation studies, its high cost and limited flexibility constrain its broader applicability. To address these limitations, we developed and validated a low-cost, modular gas monitoring system (FerME), assembled from commercially available components. To evaluate its performance and reproducibility relative to the Ankom RF system (Ankom Technology, Macedon, NY, USA), in vitro rumen fermentation experiments were conducted under strictly controlled and identical conditions. Whole rumen contents were collected approximately 2 h post-feeding from individual mid- or late-lactation dairy cows and immediately transported to the laboratory. Each fermenter received 50 mL of processed rumen fluid, 100 mL of anaerobically prepared artificial saliva buffer, and 1.2 g of the donor cow’s diet. Bottles were sealed with the respective system’s pressure sensors, flushed with CO₂, and incubated in a 50 L water bath maintained at 39 °C. FerME (New Taipei City, Taiwan) and Ankom RF fermenters were placed side-by-side to ensure uniform thermal conditions. To assess the effect of filter bag use, an additional trial employed Ankom F57 filter bags (Ankom Technology, Macedon, NY, USA; 25 μm pore size). Trial 1 revealed no significant differences in cumulative gas production, volatile fatty acids (VFAs), NH₃-N, or pH between systems (p > 0.05). However, the use of filter bags reduced gas output and increased propionate concentrations (p < 0.05). Trial 2, which employed filter bags in both systems, confirmed comparable results, with the FerME system demonstrating improved precision (CV: 4.8% vs. 13.2%). Gas composition (CH₄ + CO₂: 76–82%) and fermentation parameters remained consistent across systems (p > 0.05). Importantly, with 12 pressure sensors, the total cost of FerME was about half that of the Ankom RF system. Collectively, these findings demonstrate that FerME is a reliable, low-cost alternative for real-time rumen fermentation monitoring and could be suitable for studies in animal nutrition, methane mitigation, and related applications. Full article

Sodium–glucose co-transporter-2 inhibitors (SGLT2is) and GLP-1 receptor agonists (GLP-1 RAs) are now established as cornerstone therapies for patients with type 2 diabetes mellitus (T2DM), given their cardiovascular and renal protective properties. However, their use in patients with peripheral artery disease (PAD) remains controversial due to concerns raised in early trials about potential increases in lower limb complications, particularly amputations. This narrative review examines current evidence on the association between SGLT2is and GLP-1 RAs in PAD-related outcomes, including limb events, amputation risk, and cardiovascular and renal endpoints. Drawing from randomized controlled trials, real-world cohort studies, and systematic reviews, we provide an integrated perspective on the safety and utility of SGLT2is and GLP-1 RAs in individuals with PAD, highlight patient selection considerations, and identify areas for future investigation. Full article

This study is the first to investigate the performance of ultraviolet germicidal irradiation (UVGI) in underfloor air distribution (UFAD) systems. A simplified mathematical model is developed to predict airborne pathogen transport and inactivation by upper room UVGI in UFAD spaces. The proposed model is substantiated for the SARS-CoV-2 virus as a simulated pathogen through a comprehensive computational fluid dynamics methodology validated against published experimental data of upper room UVGI and UFAD flows. Simulations show an 11% decrease in viral concentration within the upper irradiated zone when a 15 W louvered germicidal lamp is utilized. Finally, a case study on Mycobacterium tuberculosis (M. tuberculosis) bacteria is carried out using the validated simplified model to optimize the use of return air and UVGI implementation, ensuring acceptable indoor air quality and enhanced energy efficiency. Results reveal that the UFAD-UVGI system may consume up to 13.6% less energy while keeping the occupants at acceptable levels of M. tuberculosis concentration and UV irradiance when operated with 26% return air and a UVGI output of 72 W. Full article

Background: Accumulating evidence indicates that SARS-CoV-2 infection results in long-term multiorgan complications, with the kidney being a primary target. This study aimed to characterize the long-term transcriptomic changes in the kidney following coronavirus infection using a murine model of MHV-1-induced SARS-like illness and to evaluate the therapeutic efficacy of SPIKENET (SPK). Methods: A/J mice were infected with MHV-1. Renal tissues were collected and subjected to immunofluorescence analysis and Next Generation RNA Sequencing to identify differentially expressed genes associated with acute and chronic infection. Bioinformatic analyses, including PCA, volcano plots, and GO/KEGG pathway enrichment, were performed. A separate cohort received SPK treatment, and comparative transcriptomic profiling was conducted. Gene expression profile was further confirmed using real-time PCR. Results: Acute infection showed the upregulation of genes involved in inflammation and fibrosis. Long-term MHV-1 infection led to the sustained upregulation of genes involved in muscle regeneration, cytoskeletal remodeling, and fibrotic responses. Notably, both expression and variability of SLC22 and SLC22A8, key proximal tubule transporters, were reduced, suggesting a loss of segment-specific identity. Further, SLC12A1, a critical regulator of sodium reabsorption and blood pressure, was downregulated and is associated with the onset of polyuria and hydronephrosis. SLC transporters exhibited expression patterns consistent with tubular dysfunction and inflammation. These findings suggest aberrant activation of myogenic pathways and structural proteins in renal tissues, consistent with a pro-fibrotic phenotype. In contrast, SPK treatment reversed the expression of most genes, thereby restoring the gene profiles to those observed in control mice. Conclusions: MHV-1-induced long COVID is associated with persistent transcriptional reprogramming in the kidney, indicative of chronic inflammation, cytoskeletal dysregulation, and fibrogenesis. SPK demonstrates robust therapeutic potential by normalizing these molecular signatures and preventing long-term renal damage. These findings underscore the relevance of the MHV-1 model and support further investigation of SPK as a candidate therapy for COVID-19-associated renal sequelae. Full article

This study develops an integrated environmental–economic assessment framework to evaluate the life cycle environmental impacts and economic costs of CO₂ geological storage and produced water treatment in saline formations in China. Using a case study of a saline aquifer carbon storage project in the Ordos Basin, eight full-chain carbon capture, utilization, and storage (CCUS) scenarios were analyzed. The results indicate that environmental and cost performance are primarily influenced by technology choices across carbon capture, transport, and storage stages. The scenario employing potassium carbonate-based capture, pipeline transport, and brine reinjection after a reverse osmosis treatment (S5) achieved the most balanced outcome. Breakeven analyses under three carbon price projection models revealed that carbon price trajectories critically affect project viability, with a steadily rising carbon price enabling earlier profitability. By decoupling CCUS from power systems and focusing on unit CO₂ removal, this study provides a transparent and transferable framework to support cross-sectoral deployment. The findings offer valuable insights for policymakers aiming to design effective CCUS support mechanisms under future carbon neutrality targets. Full article

Background: Increasing regulatory pressure for maritime decarbonization (e.g., IMO CII, FuelEU) drives adoption of low-carbon fuels and prompts reassessment of regional ports’ competitiveness. This study aims to evaluate the economic and environmental viability of rerouting deep-sea container services to regional ports in a decarbonizing world. Methods: A scenario-based analysis is used to evaluate total costs and CO₂ emissions across the entire container shipping supply chain, incorporating deep-sea shipping, port operations, feeder services, and inland rail/road transport. The Port of Liverpool serves as the primary case study for rerouting Asia–Europe services from major ports. Results: Analysis indicates Liverpool’s competitiveness improves with shipping lines’ slow steaming, growth in hinterland shipment volume, reductions in the emission factors of alternative low-carbon fuels, and an increased modal shift to rail matching that of competitor ports (e.g., Southampton). A dual-port strategy, rerouting services to call at both Liverpool and Southampton, shows potential for both economic and environmental benefits. Conclusions: The study concludes that rerouting deep-sea services to regional ports can offer cost and emission advantages under specific operational and market conditions. Findings on factors and conditions influencing competitiveness and the dual-port strategy provide insights for shippers, ports, shipping lines, logistics agents, and policymakers navigating maritime decarbonization. Full article

Botryosphaeria dothidea is the causative agent of Chinese hickory trunk canker, which poses significant threat to the production of Chinese hickory (Carya cathayensis Sarg.). Previous studies reported that endophytic–pathogenic phase transition, also referred to as latent infection, plays an important role in the interaction of Botryosphaeria dothidea with various host plants, including Chinese hickory. However, the mechanism underlying this phase transition is not well understood. Here, we employed RNA-Seq to investigate transcriptional changes in B. dothidea during its phase transition upon interaction with Chinese hickory. A co-expression network was generated based on 6391 differentially expressed genes (DEGs) identified from different infection stages and temperature treatments. One co-expressed module was found that highly correlated with temperature treatments which simulated conditions of B. dothidea latent infection in the field. Subsequently, 53 hub genes were detected, and gene ontology (GO) enrichment analysis revealed three categories of enriched GO terms: transmembrane transport or activity, ion homeostasis or transport, and carbohydrate metabolism. One PacC transcriptional factor (BDLA_00001555, an ambient pH regulator), and one endo-β-1,3-glucanase (BDLA_00010249) were specifically upregulated under temperature treatments that corresponded with the activation stage of B. dothidea’s pathogenic state. The knockout mutant strain of BDLA_00001555 demonstrated defective capability upon the activation of the pathogenic state. This confirmed that BDLA_00001555, the PacC transcriptional factor, plays an important role in the latent infection phase of B. dothidea. Our findings provide insights into the pathogenic mechanism of Chinese hickory trunk canker disease. Full article

Produce supply chains play a critical role in ensuring fruits and vegetables reach consumers efficiently, affordably, and at optimal freshness. In recent decades, hub-and-spoke network models have emerged as valuable tools for optimizing sustainable cold food supply chains. Traditional optimization efforts typically focus on removing inefficiencies, minimizing lead times, refining inventory management, strengthening supplier relationships, and leveraging technological advancements for better visibility and control. However, the majority of models rely on deterministic approaches that overlook the inherent uncertainties of crop yields, which are further intensified by climate variability. Rising atmospheric CO₂ concentrations, along with shifting temperature patterns and extreme weather events, have a substantial effect on crop productivity and availability. Such uncertainties can prompt distributors to seek alternative sources, increasing costs due to supply chain reconfiguration. This research introduces a stochastic hub-and-spoke network optimization model specifically designed to minimize transportation expenses by determining optimal distribution routes that explicitly account for climate variability effects on crop yields. A use case involving a cold food supply chain (CFSC) was carried out using several weather scenarios based on climate models and real soil data for California. Strawberries were selected as a representative crop, given California’s leading role in strawberry production. Simulation results show that scenarios characterized by increased rainfall during growing seasons result in increased yields, allowing distributors to reduce transportation costs by sourcing from nearby farms. Conversely, scenarios with reduced rainfall and lower yields require sourcing from more distant locations, thereby increasing transportation costs. Nonetheless, supply chain configurations may vary depending on the choice of climate models or weather prediction sources, highlighting the importance of regularly updating scenario inputs to ensure robust planning. This tool aids decision-making by planning climate-resilient supply chains, enhancing preparedness and responsiveness to future climate-related disruptions. Full article

Various factors influence the formation and adjustment of network freight prices, including transportation costs, cargo characteristics, and policies and regulations. The interaction of these factors increases the difficulty of accurately predicting network freight prices through regressions or other machine learning models, especially when the amount and quality of training data are limited. This paper introduces large language models (LLMs) to predict network freight prices using their inherent prior knowledge. Different data sorting methods and serialization strategies are employed to construct the corpora of LLMs, which are then tested on multiple base models. A few-shot sample dataset is constructed to test the performance of models under insufficient information. The Chain of Thought (CoT) is employed to construct a corpus that demonstrates the reasoning process in freight price prediction. Cross entropy loss with LoRA fine-tuning and cosine annealing learning rate adjustment, and Mean Absolute Error (MAE) loss with full fine-tuning and OneCycle learning rate adjustment to train the models, respectively, are used. The experimental results demonstrate that LLMs are better than or competitive with the best comparison model. Tests on a few-shot dataset demonstrate that LLMs outperform most comparison models in performance. This method provides a new reference for predicting network freight prices. Full article

Although concentrated solar power (CSP) coupled with calcium looping (CaL) offers a promising avenue for efficient thermal chemical energy storage, calcium-based sorbents suffer from accelerated structural degradation and decreased CO₂ capture capacity during multiple cycles. This study used Density Functional Theory (DFT) calculations to investigate the mechanism by which Mg and Ni doping improves the adsorption/desorption performance of CaO. The DFT results indicate that Mg and Ni doping can effectively reduce the formation energy of oxygen vacancies on the CaO surface. Mg–Ni co-doping exhibits a significant synergistic effect, with the formation energy of oxygen vacancies reduced to 5.072 eV. Meanwhile, the O²⁻ diffusion energy barrier in the co-doped system was reduced to 2.692 eV, significantly improving the ion transport efficiency. In terms of CO₂ adsorption, Mg and Ni co-doping enhances the interaction between surface O atoms and CO₂, increasing the adsorption energy to −1.703 eV and forming a more stable CO₃²⁻ structure. For the desorption process, Mg and Ni co-doping restructured the CaCO₃ surface structure, reducing the CO₂ desorption energy barrier to 3.922 eV and significantly promoting carbonate decomposition. This work reveals, at the molecular level, how Mg and Ni doping optimizes adsorption–desorption in calcium-based materials, providing theoretical guidance for designing high-performance sorbents. Full article

Dopamine transporter (DAT) mutations are associated with neurological and psychiatric diseases, and DAT gene knockout in rats (DAT-KO) provides an opportunity to evaluate the DAT role in pathological conditions. We analyzed DAT expression and co-expression with other genes in the substantia nigra and striatum in public transcriptomic data represented in the GEO repository and then estimated the identified DAT co-expression pattern in DAT-KO rats by RT-PCR. In silico analysis confirmed DAT expression in the substantia nigra and absence of DAT mRNA in the striatum. Also, DAT is co-expressed with genes involved in dopamine signaling, but these associations are disrupted in dopamine neuron-damaging conditions. To estimate this co-expression pattern when DAT expression is lost, we evaluate it in the substantia nigra of DAT-KO rats. However, in DAT-KO rats the associations between genes involved in dopamine signaling were not disturbed compared to wild-type littermates, and tyrosine hydroxylase expression upregulation in the substantia nigra of these animals may be considered as compensation for the loss of dopamine reuptake. Further studies of expression regulation in dopamine neurons of DAT-KO rats may provide valuable information for compensatory mechanisms in substantia nigra dopaminergic neurons. Full article

The administration of isolated mitochondria is a promising strategy for protecting cells from oxidative damage. This study aimed to identify mitochondrial characteristics that contribute to stronger protective effects. We compared two types of mitochondria isolated from C6 cells with similar ATP-producing capacity but differing in outer membrane integrity. To evaluate their stability in extracellular conditions, we examined their behavior in serum. Both types underwent mitochondrial permeability transition to a similar extent; however, under intracellular-like conditions after serum incubation, mitochondria with intact membranes retained more polarized mitochondria. Notably, mitochondria with intact outer membranes were internalized more efficiently than those with damaged membranes. In H9c2 cells, both types of mitochondria similarly increased intracellular ATP levels 1 h after administration under all tested conditions. When co-administered with H₂O₂, both suppressed oxidative damage to a comparable degree, as indicated by similar H₂O₂-scavenging activity in solution, comparable intracellular ROS levels, and equivalent preservation of electron transport chain activity. However, at higher H₂O₂ concentrations, cells treated with mitochondria possessing intact outer membranes exhibited greater survival 24 h after co-administration. Furthermore, when mitochondria were added after H₂O₂-induced damage and their removal, intact mitochondria conferred superior cell survival compared to damaged ones. These findings suggest that while both mitochondrial types exert comparable antioxidant effects, outer membrane integrity prior to administration plays a critical role in enhancing cell survival under conditions of oxidative stress. Full article

Manganese (Mn) excess and low pH often coexist in some citrus orchard soils. Little information is known about the underlying mechanism by which raising pH reduces Mn toxicity in citrus plants. ‘Sour pummelo’ (Citrus grandis (L.) Osbeck) seedlings were treated with 2 (Mn2) or 500 (Mn500) μM Mn at a pH of 3 (P3) or 5 (P5) for 25 weeks. Raising pH mitigated Mn500-induced increases in Mn, iron, copper, and zinc concentrations in roots, stems, and leaves, as well as nitrogen, phosphorus, potassium, calcium, magnesium, sulfur, copper, iron, and zinc distributions in roots, but it mitigated Mn500-induced decreases in nitrogen, phosphorus, potassium, calcium, magnesium, sulfur, and boron concentrations in roots, stems, and leaves, as well as nutrient imbalance. Raising pH mitigated Mn500-induced necrotic spots on old leaves, yellowing of young leaves, decreases in seedling growth, leaf chlorophyll concentration, and CO₂ assimilation (A_CO2), increase in root dry weight (DW)/shoot DW, and alterations of leaf chlorophyll a fluorescence (OJIP) transients and related indexes. Further analysis indicated that raising pH ameliorated Mn500-induced impairment of nutrient homeostasis, leaf thylakoid structure by iron deficiency and competition of Mn with magnesium, and photosynthetic electron transport chain (PETC), thereby reducing Mn500-induced declines in A_CO2 and subsequent seedling growth. These results validated the hypothesis that raising pH reduced Mn toxicity in ‘Sour pummelo’ seedlings by (a) reducing Mn uptake, (b) efficient maintenance of nutrient homeostasis under Mn stress, (c) reducing Mn excess-induced impairment of thylakoid structure and PEPC and inhibition of chlorophyll biosynthesis, and (d) increasing A_CO2 and subsequent seedling growth under Mn excess. Full article