Search Results (80,200)

Phytochrome-interacting factors (PIFs) were initially recognized as pivotal regulators of plant light signaling pathways. However, mounting evidence suggests that PIFs also exert significant influences on plant development and responses to stress. Here, we identified seven PIF genes in the potato genome and conducted comprehensive characterizations through phylogenetics, gene structure, conserved motif, synteny, chromosomal location analyses and cis-regulatory element. Transcriptome data and gene expression analysis showed that the StPIF4 gene was markedly induced by mannitol-induced water deficit. Additionally, the StPIF4 protein was primarily localized in the nucleus and plasma membrane. In order to explore the function of the StPIF4 gene under mannitol-induced water deficit, the StPIF4 gene was cloned, and several StPIF4 overexpression (OE) lines (OE-8, OE-10, and OE-11) and three RNA interference (RNAi) transgenic lines (RNAi-5, RNAi-9, and RNAi-11) were obtained. The OE lines displayed notable enhancements in various growth parameters such as plant height, leaf number, branch number, fresh weight, dry weight, total root length, root surface area, number of root forks, and number of root tips under mannitol-induced water deficit compared to the wild-type (WT) lines, whereas these parameters were significantly decreased in the RNAi lines. The activities of antioxidant enzymes (SOD, POD, CAT) and the accumulation of proline and soluble sugars were also significantly increased under mannitol-induced water deficit, whereas the levels of thiobarbituric acid reactive substances (TBARSs) and reactive oxygen species (ROS), including hydrogen peroxide (H₂O₂) and O₂⁻, were significantly reduced in the OE lines compared to WT plants under mannitol-induced water deficit. Moreover, the stomatal aperture of the leaves and the water loss rate in the leaves of the OE lines were significantly reduced under mannitol-induced water deficit compared to the WT plants, whereas for the RNAi lines they were significantly increased. In addition, the overexpression of StPIF4 also upregulated expression of drought-responsive genes and ABA content under mannitol-induced water deficit. Collectively, these results highlight the positive role of the StPIF4 gene in enhancing potato tolerance to mannitol-induced water deficit by decreasing stomatal aperture, enhancing ROS scavenging and mitigating oxidative damage. Full article

Background/objectives: severe mastitis is one of the leading causes of mortality in dairy cows. Its primary complication is shock, predominantly associated with systemic inflammatory response syndrome, which remains extremely challenging for practitioners to manage. The average mortality rate is estimated at approximately 25%. Many authors recommend the use of fluoroquinolones for this indication. However, these antibiotics are classified as critically important for human health, and their use requires strict compliance with specific guidelines (bacteriological analysis and antimicrobial susceptibility testing). In addition, some practitioners remain reluctant to use this class of antibiotics in field conditions. Therefore, the present study aimed to evaluate the outcomes of systematic antibiotic therapy using fluoroquinolones in cases of severe mastitis and to identify factors that may influence treatment success. Methods: a total of 323 cows with severe mastitis were enrolled by eight participating veterinary clinics located across different regions of France. The study design included: (i) clinical scoring based on a standardized grid developed by practitioners routinely managing this condition, (ii) bacteriological analysis of milk samples (with antimicrobial susceptibility testing performed when Gram-negative bacteria were isolated), and (iii) post-treatment follow-up consisting of telephone interviews conducted at 5 and 15 days after inclusion. Cows presenting with a clinical score ≥3 (scale 0–36) in association with local signs of mastitis were classified as having severe mastitis and received an injection of 10 mg/kg marbofloxacin along with 2.2 mg/kg flunixin (unless another NSAID had been administered within the previous 24 h). When the clinical score was ≥6, cows additionally received intravenous fluid therapy consisting of 3 L of 7.2% NaCl, supplemented by oral drenching if spontaneous water intake was insufficient. Results: a total of 43 cows died or were euthanized during the study period, corresponding to a mortality rate of 13.3%. The mean clinical score at inclusion was 12.6. The clinical signs most strongly associated with mortality were decubitus and hypothermia at admission. Escherichia coli was isolated in 67.0% of severe mastitis cases, either as a single pathogen (82.9%) or in mixed infections (17.1%). Overall, Gram-negative bacteria (Escherichia coli, Klebsiella spp., Pseudomonas aeruginosa, other Gram-negative organisms) were identified in 79.0% of cases. A total of 188 coliform isolates were tested for antimicrobial susceptibility. All isolates (100%) were susceptible to marbofloxacin, as were all tested Gram-negative strains, whereas only 79.9% of E. coli isolates were susceptible to sulfonamide/trimethoprim. Compared with previously published data, the observed mortality rate was lower despite the poor clinical condition of cows at admission. Conclusion: the timeliness of initiating effective antimicrobial therapy appears to be a critical determinant of survival in cows with severe mastitis. Full article

Frequent occurrences of inter-regional emergencies constitute critical impediments to global security and sustainable development, necessitating enhanced intergovernmental emergency collaboration. This study employs a network evolutionary game model (NEGM) to examine how vertical interventions shape diffusion mechanisms of cooperative strategies among local governments. The results show that (1) solely intensifying penalties or rewards yields diminishing marginal returns in incentivizing local governments to adopt a proactive cooperative strategy; (2) elevating the cost-sharing index significantly accelerates the diffusion rate of cooperative strategies, effectively mobilizing broader subnational engagement in public health emergency response; and (3) the tripartite integration of penalty-based enforcement, reward incentives, and cost-sharing mechanisms demonstrates synergistic superiority over alternative policy instruments—whether implemented individually or in pairwise combinations. Full article

Endogenous growth theory explains the asymmetric dynamic relationship between economic and social development through human capital accumulation and innovation, institutional quality, and demand channels. The objective of this paper is to assess the dynamic relationship between social and economic development in developing countries, where institutional imperfections and development instability create the most pronounced asymmetries. A composite social development index, obtained using the entropy method, operationalizes social development as the expansion of human capabilities in three dimensions: health, education, and material security. A panel vector error correction model (PVECM), estimated using the generalized method of moments (GMM) on panel data from 18 countries in Central Asia, the Middle East, and North Africa for the period 2001–2023, revealed asymmetric dynamic relationships: improved social indicators are associated with a short-term slowdown in economic indicators and more favorable economic dynamics in the medium term. In contrast, economic growth is accompanied by a positive lagged response in social development, although the short-term response may reflect the costs of social adjustment. The influence of control variables confirms the positive role of agglomeration for economic development, revealing the social costs of rapid urbanization and demographic pressure on social development. Estimates of the error correction coefficients indicate a slow adaptation of the system to long-term equilibrium, high inertia, and institutional rigidity of macrosocial processes. Impulse response functions confirm the dynamic and delayed nature of the interaction between economic and social development and positive shocks in the medium term. The obtained empirical results substantiate the need for institutional regulation of policy decisions on human capital accumulation and innovation, as well as social reforms. Full article

Background Cytomegalovirus (CMV) infection is a major contributor to morbidity and mortality in recipients of hematopoietic stem cell transplant (HSCT), solid organ transplant (SOT), and chimeric antigen receptor T-cell (CAR-T) therapy. While antiviral agents remain the cornerstone of treatment, CMV-specific immunoglobulins (CMVIG) have been utilized as adjunct therapy with variable outcomes. This study aims to evaluate the virological response and tolerability of CMVIG in cases of severe or refractory CMV viremia, with or without CMV disease. Methods: We conducted a single-center retrospective case series of adult recipients of SOT, allogeneic HSCT, and/or CAR-T cell therapy who developed CMV viremia or disease and received at least one dose of CMVIG between May 2017 and May 2023 at our center. Virological improvement within 14 days of starting CMVIG and tolerability of CMVIG are the primary outcome of this study. Results: A total of 33 patients were included. Of these, 29 underwent transplantation [SOT: 48.2%, HSCT: 51.7%], and five underwent CAR-T cell therapy (one post-HSCT). High-risk CMV serostatus was present in 12%. CMV viremia was documented in 32 patients (97%), and tissue-invasive disease was present in 11 patients (33.3%). Virological response, was observed in 65.6% of the cohort. The median time to undetectable CMV viral load following CMVIG initiation was 28 days. CMVIG was well-tolerated. All-cause mortality at 90 days remained high (57%). Conclusion: In this case series, CMVIG demonstrated a virological response rate of 65.6% in patients with severe or refractory CMV infection. While CMVIG was well-tolerated with minimal adverse events, the high mortality rate despite virological response suggests that CMVIG may be insufficient for this critically ill population. Our findings should be interpreted as observational data from a small case series, and prospective controlled trials are needed to establish the true benefit of CMVIG in combination with standard antiviral therapy. Full article

The microbial community plays a crucial role in plant health and sustainable agricultural development by influencing plant physiology and development. This study aimed to explore the biocontrol potential of Bacillus subtilis A9, an endophytic bacterium isolated from Morchella esculenta, against rot disease caused by Lecanicillium aphanocladii. Metagenomic and metabolomic analyses were conducted on M. esculenta samples sprayed with B. subtilis A9 and a control group sprayed with LB medium. Metagenomic sequencing revealed that B. subtilis A9 significantly altered the microbial community structure and functional composition of M. esculenta, enriching genes related to biofilm formation, arginine and proline metabolism, and sulfur metabolism. Metabolomic analysis indicated significant upregulation of stress-resistant metabolites such as L-proline, ketoleucine, and pelargonic acid. Integrated multi-omics analysis demonstrated a strong correlation between the microbial community structure and the metabolomic profile, suggesting that B. subtilis A9 may be related to the disease-resistance response in the M. esculenta microecosystem. These findings provide a theoretical basis for the biological control of M. esculenta rot disease and support the development of green biocontrol strategies. Full article

Cage-based tilapia farming is highly vulnerable to rapid variations in water-quality parameters, particularly dissolved oxygen (DO) fluctuations, which can cause fish stress, fish mortality, and economic losses. In this study, we developed and field-evaluated an Internet of Things (IoT)- and LoRa-based water-quality-monitoring and aeration-actuation system for open-water tilapia cage farming. The system consists of distributed control nodes, a main node, a cloud database, and a mobile application for real-time monitoring of DO, pH, and water temperature, as well as remote and automatic oxygen-pump actuation. An automatic probe-lifting mechanism is integrated into the control node to reduce probe-submersion duration and mitigate the risk of sensor fouling during field operation. Field validation showed that the node equipped with the probe-lifting mechanism achieved better agreement with the reference instruments than the continuously submerged node, particularly for DO measurement, with RMSE values of 0.186 mg/L and 0.683 mg/L, respectively. A communication-performance evaluation showed 100% packet reception up to 1640 m, whereas packet reception was reduced at the longest tested distance of 2290 m, indicating that the field-deployment range should be interpreted cautiously under the tested LoRa configuration. Detection-latency experiments showed sub-second responsiveness, with average delays of 208.6–289.7 ms for single-hop communication and 438.9–529.4 ms for two-hop communication. Expert evaluation and farmer satisfaction assessment indicated positive perceptions of the system’s usability and practical relevance. However, the study has several limitations, including the short field-validation period, limited sensor replication, and a lack of direct fish production outcome measurements, which should be considered when interpreting the findings. Overall, the proposed system provides a practical platform for water-quality monitoring and aeration actuation in cage-based tilapia farming. Full article

This study presents a novel integrated methodology for optimizing forest fire emergency rescue vehicle scheduling through the synergistic combination of a multi-criteria demand urgency grading framework and mechanistic fire spread propagation modeling, enhancing spatiotemporal resource allocation efficiency under evolving wildfire scenarios. The research focuses on three core aspects: First, a multi-dimensional demand urgency evaluation system is established, incorporating fire threat, response efficiency, and path factors. Subjective and objective weights are determined through fuzzy analytic hierarchy process and entropy method, respectively, while grey relational analysis TOPSIS method is employed for prioritizing affected areas. The model’s validity is verified using wildfire data from the Greater Khingan Mountains. Second, a multi-objective vehicle scheduling model is developed, combining total rescue time, cost, and urgency ranking index via weighted sum method. A fire spread model is innovatively introduced to dynamically adjust urgency classification, with genetic algorithm (GA) and Genetic Simulated Annealing Algorithm (GASA) designed for solution optimization. Finally, empirical analysis of 13 fire cases in the Greater Khingan Mountains (2020) demonstrates that GASA outperforms GA, achieving 17% reduction in rescue time, 1% cost savings, 22% shorter travel distance, and 0.7% improvement in urgency ranking. Incorporating the fire spread model enhances the urgency ranking index by 10.78%, where the improvement is defined as the percentage increase in the achieved objective function value f3 compared to the solution obtained without dynamic fire propagation information. By integrating dynamic urgency assessment with intelligent algorithms, this research constructs a spatiotemporal-aware emergency scheduling framework aligned with forest fire evolution patterns, providing theoretical foundations and practical strategies to enhance rescue efficiency and resource allocation, with significant implications for disaster management. Full article

Floods are among the most catastrophic natural disasters globally, causing significant damage to both life and infrastructure. Consequently, immediate and accurate assessment of inundated areas is critical for effective emergency response. While optical remote sensing is typically used for flood assessment, it is often ineffective during active flood events due to persistent cloud cover and precipitation. To address this, this research develops a deep learning method utilizing Synthetic Aperture Radar (SAR), which offers all-weather, 24 h imaging capabilities. Specifically, an attention-based differential Siamese U-Net was developed to detect temporal changes in bi-temporal SAR imagery (e.g., Sentinel-1) acquired before and after flood events. The method was evaluated on the S1GFloods dataset, comprising 5360 bi-temporal Sentinel-1 SAR image pairs across 46 flood incidents on six continents. Experimental results demonstrate a flood Intersection over Union (IoU) of 92.43%, an F1 score of 96.07%, and a recall of 97.64%. These metrics rank the proposed approach third overall among top-performing methods on this dataset. Notably, the high recall rate indicates the model is particularly beneficial for emergency response, as it minimizes the number of undetected flooded areas. Despite utilizing a CNN-based architecture that is less complex than Vision Transformer models, this method achieves results comparable to the state-of-the-art DAM-Net, with a performance difference of only 0.77%. Full article

Generative artificial intelligence (GenAI) tools such as ChatGPT have attracted growing attention in higher education, particularly in relation to how students perceive their usefulness, usability, and educational value. However, existing studies are often descriptive and rarely translate perception data into exploratory quantitative indicators that can support structured evaluation under uncertainty. To address this gap, this study develops an exploratory Monte Carlo simulation framework for quantifying perception-based student success in the context of GenAI use. The term Perception-Based Student Success Score is used here as an exploratory proxy indicator derived from students’ positive evaluations of usability, efficiency, learnability, and perceived integration; it does not represent direct academic achievement, grades, retention, or objectively measured learning outcomes. A PRISMA-informed structured literature search in Scopus identified nineteen empirical studies published between 2023 and 2025, of which six reported item-level means and standard deviations suitable for probabilistic modelling. One coherent 10-item, 5-point Likert-scale usability-oriented instrument was selected as a canonical proof-of-concept dataset and used to parameterise an inverse-variance-weighted Monte Carlo simulation generating 10,000 synthetic observations. The results show that the weighting structure substantially influences the simulated outcome. In particular, System Efficiency and Learning Burden received the largest inverse-variance weight and therefore had the strongest influence on the composite score. This dominance should be interpreted cautiously because low variance in Likert-scale data may reflect response homogeneity or ceiling effects rather than substantive importance alone. The study offers a transparent, reproducible, and privacy-preserving proof-of-concept framework linking structured literature search, item-level summary statistics, and probabilistic modelling. Full article

Current manual laser cleaning methods often require highly skilled operators to achieve fast and reliable cleaning. This study investigated the feasibility of measuring thermal processes during laser metal cleaning to support the development of an automated and intelligent laser cleaning system. The measurement system was based on fast infrared (IR) diagnostics and used a field programmable gate array (FPGA) for fast signal analysis. Experiments were conducted on steel substrates covered with paint, scale, or corrosion. Thermal response in real-time for every laser pulse was monitored. Paints showed no solidification plateau, while steel exhibited a clear plateau above the ablation threshold. The scaled surface showed longer time intervals and higher heat accumulation. A histogram of time intervals enabled statistical analysis of the process. Time-resolved temperature values revealed hidden processes. These findings demonstrated the potential of IR thermal diagnostics for evaluating surface conditions and providing real-time data to optimise, monitor, and control laser cleaning processes. Full article

Intensifying climate change poses a major challenge to biodiversity conservation by weakening the ability of protected area systems to support species movement and ecological processes. However, protected area network planning has paid limited attention to the integration of climate connectivity and network resilience. Taking the highly urbanized Yangtze River Delta (YRD) as a case study, this study developed an integrated framework for climate-connected protected area network optimization. Specifically, climate refugia potential and species distribution probability were integrated to identify source areas, climate connectivity corridors were delineated by coupling landscape resistance with temperature gradients, and complex-network-based resilience analysis was applied to evaluate network responses under multiple disturbance and recovery scenarios. The results showed that: (1) climate stability, climate heterogeneity, and species distribution probability generally exhibited a south-to-north decreasing pattern, and 205 source areas were identified, mainly concentrated in the western and southern mountainous regions; (2) 459 climate connectivity corridors were extracted, forming a network backbone in the western and southern mountains, whereas corridors were relatively sparse in the plains and highly urbanized coastal areas; and (3) the network was highly vulnerable under critical-node-targeted, human-pressure-oriented, and climate-risk-oriented attack scenarios, while critical-node-priority recovery was the most effective strategy for restoring network function. These findings provide scientific support for cross-regional coordination, restoration prioritization, and long-term adaptive management in climate-connected protected area network planning. Full article

Background: This study aimed to develop a fully nested, information leakage-free machine-learning workflow to predict the volumetric response of meningioma to Gamma Knife radiosurgery (GKRS) from pre-treatment MRI and to compare the predictive value of radiomic, fractal, lacunarity and clinical/radiosurgical features. GKRS is widely used for treating meningiomas because of its high precision and efficacy. Variability in tumor volumetric response highlights the need for reliable predictors of treatment outcome. Methods: This retrospective cohort study included 204 patients treated with GKRS for grade I meningioma. Radiomic, fractal and lacunarity features were extracted from pre-treatment CE-T1w 3-Tesla MRIs. Feature signatures were generated using a machine-learning workflow incorporating five feature selectors based on a consensus principle to reduce spurious feature selection, followed by five classifiers to predict binary outcome. Results: The models demonstrated consistent predictive performance in the test folds, with AUC values from 0.77 to 0.84. Supplementing radiomic features with clinical, fractal or lacunarity features did not improve predictive performance. Conclusions: Radiomic features showed the strongest predictive value for meningioma volumetric response to GKRS. Darker intratumoral intensity values were associated with a favorable volumetric response, possibly reflecting biologically less active tumor regions. The supplied code enables individual-level prediction for newly encountered patients. Full article

Background: This review summarizes the current knowledge on the composition, bioactive constituents, health-related effects, and by-product utilization of sea buckthorn (Hippophaë rhamnoides L.) seed and pulp oils. Review approach: This review covers studies on fatty acid composition, minor bioactive compounds, antioxidant and anti-inflammatory activities, lipid metabolism-related effects, and the valorization of processing by-products, with evidence primarily derived from in vitro and in vivo studies. Results: Sea buckthorn produces two distinct oils: seed oil, characterized by high levels of polyunsaturated fatty acids, tocopherols, and phytosterols, and pulp oil, which is rich in palmitoleic acid and carotenoids. These compositional differences contribute to their antioxidant, anti-inflammatory, and lipid-regulating activities. In addition, the utilization of by-products, particularly polyphenol- and fiber-rich residues, has gained increasing attention for improving resource efficiency and sustainability of the industry. Conclusions: Sea buckthorn oil is a promising source of functional lipids and bioactive compounds. However, current evidence is largely based on experimental studies, and further research is needed to clarify the mechanisms of action, bioavailability, dose–response relationships, and clinical efficacy. Advances in green extraction technologies and integrated utilization strategies may further support the sustainable development of sea buckthorn resources. Full article

Background: T-cell acute lymphoblastic leukemia (T-ALL) remains a challenging malignancy with limited targeted therapies. Natural phenanthrene derivatives represent a promising source of antileukemic agents. Objective: We screened a library of natural phenanthrene-type compounds to identify cytotoxic leads in Jurkat T-ALL cells and investigated the mechanisms underlying their activity, including potential synergy with the proteasome inhibitor bortezomib (BTZ). Methods: Jurkat cells were treated with thirteen natural compounds at 10 and 20 µM for 48 h; cell viability was assessed by WST-1 cell viability assay. Dose–response curves were generated to calculate IC₅₀ values. Apoptosis was evaluated by Hoechst 33342/PI staining and Annexin V/PI flow cytometry. Synergy with BTZ was analyzed using a fixed-ratio combination index (CI) approach and IC₅₀ shift analysis. ER stress signaling was characterized by Western blotting, quantitative RT-PCR of UPR genes (GRP78, ATF6), and immunoprecipitation of GRP78 followed by ubiquitin immunoblotting. Results: Among the compounds screened, Cypripedin showed the most potent cytotoxicity with an IC₅₀ of 6.52 µM. It induced a dose-dependent increase in apoptosis. Combination with BTZ yielded a CI < 0.5 and reduced BTZ IC₅₀ from 3.43 to 1.88 ng/mL. Cypripedin activated the unfolded protein response (UPR), modulated key ER stress markers including GRP78, p-PERK, p-eIF2α, p-JNK, and ATF6, downregulated UPR gene transcripts, and promoted GRP78 ubiquitination. Molecular docking predicted strong binding of Cypripedin to the GRP78 ATPase domain (Vina score −7.630 kcal/mol), supporting its mechanism of action. Conclusion: Cypripedin induces apoptosis in Jurkat T-ALL cells, synergizes with BTZ, and modulates ER stress through GRP78 ubiquitination. These findings support its further development as a potential T-ALL therapeutic. Full article