We analyzed the thermal stability of the BstHPr protein through the site-directed point mutation Lys62 replaced by Ala residue using molecular dynamics simulations at five different temperatures: 298, 333, 362, 400, and 450 K, for periods of 1 μs and in triplicate. The results from the mutant thermophilic BstHPrm protein were compared with those of the wild-type thermophilic BstHPr protein and the mesophilic BsHPr protein. Structural and molecular interaction analyses show that proteins lose stability as temperature increases. Mutant and wild-type proteins behave similarly up to 362 K. However, at 400 K the mutant protein shows greater structural instability, losing more buried hydrogen bonds and exposing more of its non-polar residues to the solvent. Therefore, in this study, we confirmed that the salt bridge network of the Glu3–Lys62–Glu36 triad, made up of the Glu3–Lys62 and Glu36–Lys62 ion pairs, provides thermal stability to the thermophilic BstHPr protein. Full article

In the realm of international trade and economic development, the prediction of trade flows between countries is crucial for identifying export opportunities. Commonly used log-linear regression models are constrained due to difficulties when dealing with extensive, high-cardinality datasets, and the utilization of machine learning techniques in predictions offers new possibilities. We examine the predictive power of Graph Neural Networks (GNNs) in estimating the value of bilateral trade between countries. We work with detailed UN Comtrade data that represent annual bilateral trade in goods between any two countries in the world and more than 5000 product groups. We explore two different types of GNNs, namely Graph Convolutional Networks (GCNs) and Graph Attention Networks (GATs), by applying them to trade flow data. This study evaluates the effectiveness of GNNs relative to traditional machine learning techniques such as random forest and examines the possible effects of data drift on their performance. Our findings reveal the superior predictive capability of GNNs, suggesting their effectiveness in modeling complex trade relationships. The research presented in this work offers a data-driven foundation for decision-making and is relevant for business strategies and policymaking as it helps in identifying markets, products, and sectors with significant development potential. Full article

This study investigates the connection between madness and critiques of the chivalric romance genre in two late Renaissance works, Ludovico Ariosto’s Orlando Furioso and Miguel de Cervantes’s Don Quijote de la Mancha. The satire of chivalric romance in these works of fiction caution against nascent modes of thinking in imperial societies for the implementation of chivalric ideas to inspire and promote imperial conquests in Latin America through juxtaposition with the Muslim and Moorish conquest in the Maghreb and through metaphorical island governance. In order to make such critiques, these novels implement the madness of their parodic knights to disguise their critiques. This practice establishes a precedent which later literature can employ to make sociocultural critique covertly, to the detriment of disability representations as literary devices or metaphors. Full article

As new trends are emerging worldwide, including innovation breakthroughs and the need for a sustainable approach to different aspects of economy and entrepreneurship, the need for orienting society towards sustainable entrepreneurial behavior is emerging. In this context, according to the literature, entrepreneurial education can have a positive impact on fostering entrepreneurial intention in university students. The main research conducted in this study includes the identification of different opportunities and barriers that universities in Albania are facing, by conducting interviews and questionnaires with key stakeholders. The main barriers identified include the legislation gap and lack of governmental funding for entrepreneurial and sustainable courses, while the main opportunities from which universities can benefit include digital innovation and human resources skills management by providing an added value to their internal environment. The model proposed in this study to overcome barriers and benefit from opportunities includes two key stakeholders, government and universities, as the case study analysis of three universities in Albania predicts the need for more steps to be taken by these two key stakeholders included in the model, while future further research on governmental funding would be of high importance to the cost–benefit analysis of this kind of governmental support. Full article

Welding technology plays a vital role in the manufacturing process of ships, automobiles, and aerospace vehicles because it directly impacts their operational safety and reliability. Hence, the development of an accurate system for identifying welding defects in arc welding is crucial to enhancing the quality of welding production. In this study, a defect recognition method combining the Neighborhood Rough Set (NRS) with the Dingo Optimization Algorithm Support Vector Machine (DOA-SVM) in a multisensory framework is proposed. The 195-dimensional decision-making system mentioned above was constructed to integrate multi-source information from molten pool images, welding current, and vibration signals. To optimize the system, it was further refined to a 12-dimensional decision-making setup through outlier processing and feature selection based on the Neighborhood Rough Set. Subsequently, the DOA-SVM is employed for detecting welding defects. Experimental results demonstrate a 98.98% accuracy rate in identifying welding defects using our model. Importantly, this method outperforms comparative techniques in terms of quickly and accurately identifying five common welding defects, thereby affirming its suitability for arc welding. The proposed method not only achieves high accuracy but also simplifies the model structure, enhances detection efficiency, and streamlines network training. Full article

Ship pollution emissions have attracted increasing attention in the maritime field due to the massive growth of maritime traffic activities. It is important to identify the ship emissions (SEs) magnitude and corresponding spatial and temporal distributions for the purposes of developing appropriate strategies to mitigate environment pollution. The aim of this study was to estimate ship pollution emissions with various typical merchant ship types under different sailing conditions. We estimated the emission variation with a ship traffic emission assessment model (STEAM2), and then the ship pollution emission distribution was further visualized using ArcGIS. We collected data from the automatic identification system (AIS) for ships in New York Harbor and further analyzed the spatiotemporal distribution of pollutant emissions from ships. The experimental results demonstrate that the ship pollutant emission volume in the New York Harbor area in 2022 was 3340 t, while the pollution in terms of CO, SO₂, C_XH_X, PM₁₀, NO_X, and PM_2.5 was 136, 1421, 66, 185, 1384, and 148 t, respectively. The overall SEs from container ships, passenger ships, and tankers account for a large amount of pollution discharge. The pollutant emissions of container ships are significantly greater than that of their counterparts. Moreover, the spatiotemporal distributions of ship pollutant discharge can vary significantly among different ship types and sailing conditions. Full article

In this paper, we present a new class of linear fractional differential operators that are based on classical Gaussian hypergeometric functions. Then, we utilize the new operators and the concept of differential subordination to construct a convex set of analytic functions. Moreover, through an examination of a certain operator, we establish several notable results related to differential subordination. In addition, we derive inclusion relation results by employing Briot–Bouquet differential subordinations. We also introduce a perspective study for developing subordination results using Gaussian hypergeometric functions and provide certain properties for further research in complex dynamical systems. Full article

Continuously monitoring and mapping glacial lake variation is of great importance for determining changes in water resources and potential hazards in alpine cryospheric regions. The semi-automated glacial lake mapping methods used currently are hampered by inherent subjectivity and inefficiency. This study used improved YOLOv5 strategies to extract glacial lake boundaries from Sentinel-2 imagery. These strategies include using the space-to-depth technique to identify small glacial lakes, and adopting the coordinate attention and the convolution block attention modules to improve mapping performance and adaptability. In terms of glacial lake extraction, the improved YOLOv5-seg network achieved values of 0.95, 0.93, 0.96, and 0.94 for precision (P), recall (R), mAP_0.5, and the F1 score, respectively, indicating an overall improvement in performance of 12% compared to that of the newest YOLOv8 networks. In High Mountain Asia (HMA), 23,108 glacial lakes with a total area of 1847.5 km² were identified in imagery from 2022 using the proposed method. Compared with the use of manual interpretation for lake boundary extraction in test sites of HMA, the proposed method achieved values of 0.89, 0.87, and 0.86 for P, R, and the F1 score, respectively. Our proposed deep learning method has improved accuracy in glacial lake extraction because it can address the challenge represented by frozen or high-turbidity glacial lakes in HMA. Full article

The addition of marine macroalgae to animal feed has garnered interest due to the demonstrated benefits of gut health in many livestock species. Most macroalgae have a higher mineral content than terrestrial vegetables, making them an attractive, sustainable source of minerals. However, some macroalgae contain elevated concentrations of iodine and arsenic, which may be transferred to the meat of livestock fed with macroalgae. This study evaluated the mineral profile of rabbit serum, muscle, liver, and kidney of rabbits fed diets supplemented with different marine macroalgae, with the goal of improving post-weaning gut health and reducing reliance on antibiotics. We found increased deposition of iodine in muscle, liver, and kidney due to macroalgae supplementation, which is particularly promising for regions with low iodine endemicity. Higher, though relatively low arsenic concentrations, compared to those in other animal meats and food sources, were also detected in the muscle, liver, and kidney of macroalgae-fed rabbits. The absence of apparent interactions with other micronutrients, particularly selenium, suggests that the inclusion of macroalgae in rabbit diets will not affect the overall mineral content. Enhanced bioavailability of elements such as phosphorus and iron may provide additional benefits, potentially reducing the need for mineral supplementation. Full article

The purpose of the present study was to evaluate the concentrations of some bone turnover markers in preterm neonates with uncomplicated clinical course in the first month of life. Samples from 13 preterm neonates were collected at three different times: at birth (T0) from umbilical cord blood (UCB); and at 15 (T1) and 30 (T2) days of life from peripheral blood (PB). The concentrations of calcium (Ca), phosphate (P), total alkaline phosphatase (ALP), Collagen Type 1 Amino-terminal Propeptide (PINP), osteocalcin (OC), Collagen Type 1 Carboxyl-Terminal Telopeptide (CTX) and Leptin were assessed. A statistically significant difference for ALP concentration at birth versus T1 and T2 was found. An evident increase in the median concentrations of CTX, OC and PINP from T0 to T2 were observed. A significant difference was also found for Leptin concentration at T0 compared to T1. In preterm infants, in the absence of acute or chronic medical conditions and without risk factors for metabolic bone disease (MBD) of prematurity, there is a significant increase in bone turnover markers during the first month of life. The knowledge of the variations in these markers in the first weeks of life, integrated by the variations in the biochemical indicators of bone metabolism, could help in recognizing any conditions at risk of developing bone diseases. Full article

Cephalometry is a crucial examination in orthodontic diagnostics and during the planning of orthognathic surgical procedures. The objective of this article was to compare cephalometric measurements conducted by different specialists and systems tailored for such measurements, as well as to evaluate the capabilities of artificial intelligence in this field. In January 2024, we conducted electronic searches in the PubMed, Scopus, and Web of Science (WoS) databases. In the Scopus database, the results were refined to titles, abstracts, and keywords, while in PubMed, they were narrowed down to titles and abstracts. In WoS, the results were refined only to abstracts. The search criteria were based on the following terms: (cephalometric) AND (analysis) AND (discrepancy) AND ((orthodontic) OR (radiologist)). A total of 263 articles were identified, of which 17 met the criteria and were incorporated into the review. The review allowed us to conclude that the accuracy of cephalometric measurements relied on the expertise of the operator—specialists with more experience exhibited greater precision compared to novices or individuals not specialized in orthodontics. Cephalometric measurement computer programs yielded outcomes that streamlined work processes, minimized human errors, and enhanced precision. A novel aspect involved the application of artificial intelligence, which also demonstrated high precision and a substantial reduction in working time, although its utilization still necessitates further enhancements. Further research was required to address these limitations and to optimize the incorporation of technology in orthodontic and orthognathic surgery practices. Full article

Changing consumer preferences and increasing demands require adjustments in brewery operations and beer production methods. Recent trends indicate a marked decline in interest in high-alcohol beers and an increasing demand for low- and no-alcohol alternatives. The aim of this study was to evaluate and compare the volatile compound profiles produced by Saccharomyces cerevisiae var. chevalieri, a yeast strain specifically developed for non-alcoholic beer production, with a reference sample fermented with a standard Saccharomyces cerevisiae US-05 strain. Two mashing profiles were compared (with and without saccharification pause). The wort obtained was fermented with and without hops. The chemical composition and aroma compounds of the resulting beers were analysed using different chromatographic techniques (HPLC, GC-FID, GC-MS and CG-O). The modification of the mashing profile helped to obtain wort with about 50% lower maltose content. A lower FAN (free amino nitrogen) content was also observed, but this did not affect the fermentation process. Beers fermented with the Saccharomyces cerevisiae var. chevalieri strain had an average alcohol content of 0.5–0.8% v/v. This strain consumed about 25% of the available maltose. The resulting beers were dominated by fruity, floral and herbal aromas. In addition, beers fermented with a non-alcoholic beer strain scored highest in the sensory analysis. Full article

Solar energy is a type of renewable and sustainable energy. Enhancing the acquisition and utilization of solar radiation in urban residential areas is a crucial strategy for advancing sustainable development goals. The morphology of urban residential areas plays a vital role in determining their solar radiation acquisition (SRA) potential. Existing studies have primarily focused on exploring the correlation between the individual morphology index and SRA potential for residential areas. However, in the actual process of project design, there is a common need to simultaneously adjust multiple morphology indexes according to specific criteria. The question of “How to compare the magnitude of the impact of simultaneous changes in multiple morphology indexes on the SRA potential of a residential area” has not yet been systematically analyzed and fully answered. This study compares the sensitivity of multiple morphology indexes when changed collectively and assesses their comprehensive impact on the SRA potential of residential areas. The aim is to determine how to comprehensively control multiple morphology indexes in the early planning and design stages to maximize solar energy utilization in residential areas. It is concluded that, when considering the floor area ratio index under identical conditions, an increase in building density proves more advantageous for enhancing SRA compared to an increase in building height. In cases where the building height is less than 24 m and the floor area ratio is below 1.5, elevating the building density yields greater photovoltaic (PV) potential for the residential area. With a limited site area, the impact of building height on SRA far outweighs that of the layout. The layout does not significantly affect the annual solar radiation amount per unit of external surface area (ASU). With increasing building height, the impact of layout on heating season solar radiation amount per unit of external surface area (HSU) becomes more pronounced. A vertical staggered layout and a row layout exhibit significantly superior performance compared to a horizontal staggered layout in this regard. However, when the building height exceeds 24 m and the floor area ratio surpasses 1.5, the PV potential of the vertical staggered layout surpasses that of the row layout and horizontal staggered layout for the same building height. The influence of building height on SRA is slightly greater than that of the building orientation under similar conditions. The change in SRA potential with orientation under the same height follows a consistent pattern. Full article

Skin barrier function, prevent colon cancer, head and neck cancer, and decrease liver cholesterol. However, the mechanism of action has not yet been elucidated. In this study, we propose a new working hypothesis regarding the health benefits and functions of glucosylceramide: decreased fecal hardness. This hypothesis was verified using an in vitro hardness test. The hardness of feces supplemented with glucosylceramide was significantly lower than that of the control. Based on these results, a new working hypothesis of dietary glucosylceramide was conceived: glucosylceramide passes through the small intestine, interacts with intestinal bacteria, increases the tolerance of these bacteria toward secondary bile acids, and decreases the hardness of feces, and these factors synergistically result in in vivo effects. This hypothesis forms the basis for further studies on the health benefits and functions of dietary glucosylceramides. Full article

The importance of gamma-aminobutyric acid (GABA) in plants has been highlighted due to its critical role in mitigating metal toxicity, specifically countering the inhibitory effects of copper stress on rice plants. This study involved pre-treating rice plants with 1 mM GABA for one week, followed by exposure to varying concentrations of copper at 50 μM, 100 μM, and 200 μM. Under copper stress, particularly at 100 μM and 200 μM, plant height, biomass, chlorophyll content, relative water content, mineral content, and antioxidant activity decreased significantly compared to control conditions. However, GABA treatment significantly alleviated the adverse effects of copper stress. It increased plant height by 13%, 18%, and 32%; plant biomass by 28%, 52%, and 60%; chlorophyll content by 12%, 30%, and 24%; and relative water content by 10%, 24%, and 26% in comparison to the C50, C100, and C200 treatments. Furthermore, GABA treatment effectively reduced electrolyte leakage by 11%, 34%, and 39%, and the concentration of reactive oxygen species, such as malondialdehyde (MDA), by 9%, 22%, and 27%, hydrogen peroxide (H₂O₂) by 12%, 38%, and 30%, and superoxide anion content by 8%, 33, and 39% in comparison to C50, C100, and C200 treatments. Additionally, GABA supplementation led to elevated levels of glutathione by 69% and 80%, superoxide dismutase by 22% and 125%, ascorbate peroxidase by 12% and 125%, and catalase by 75% and 100% in the C100+G and C200+G groups as compared to the C100 and C200 treatments. Similarly, GABA application upregulated the expression of GABA shunt pathway-related genes, including gamma-aminobutyric transaminase (OsGABA-T) by 38% and 80% and succinic semialdehyde dehydrogenase (OsSSADH) by 60% and 94% in the C100+G and C200+G groups, respectively, as compared to the C100 and C200 treatments. Conversely, the expression of gamma-aminobutyric acid dehydrogenase (OsGAD) was downregulated. GABA application reduced the absorption of Cu²⁺ by 54% and 47% in C100+G and C200+G groups as compared to C100, and C200 treatments. Moreover, GABA treatment enhanced the uptake of Ca²⁺ by 26% and 82%, Mg²⁺ by 12% and 67%, and K⁺ by 28% and 128% in the C100+G and C200+G groups as compared to C100, and C200 treatments. These findings underscore the pivotal role of GABA-induced enhancements in various physiological and molecular processes, such as plant growth, chlorophyll content, water content, antioxidant capacity, gene regulation, mineral uptake, and copper sequestration, in enhancing plant tolerance to copper stress. Such mechanistic insights offer promising implications for the advancement of safe and sustainable food production practices. Full article

The nutritional value of goat milk is determined by the composition of its fatty acids, with particular importance placed on the role of unsaturated fatty acids in promoting human health. CircRNAs have been known to affect fatty acid metabolism through different pathways. In this study, high-throughput sequencing was employed to construct expression profiles of mammary tissue harvested during the dry period and peak lactation stages of dairy goats. Differentially expressed circRNAs and mRNAs were screened, revealing significantly higher expression levels of circRNA-08436 and ELOVL6 during the peak lactation period compared with the dry period. Thus, circRNA-08436 and ELOVL6 were chosen for subsequent studies. The findings demonstrated that circRNA-08436 not only promotes the synthesis of triglyceride (TAG) and cholesterol in goat mammary epithelial cells (GMECs), but also increases the concentrations of saturated fatty acids in the cells. Through the utilization of software prediction, the dual luciferase reporter system, and qRT-PCR, it was observed that circRNA-08436 binds to miR-195, with its overexpression reducing the expression levels of miR-195 and inhibiting TAG synthesis. In addition, circRNA-08436 upregulated the expression levels of the miR-195 target gene ELOVL6. The data also revealed that YTHDC1 facilitated the transport of circRNA-08436 from the nucleus to the cytoplasm, while YTHDC2 in the cytoplasm functioned as a “reader” to identify and degrade circRNA-08436. Taken together, these findings contribute to a better understanding of the molecular regulation of fatty acid metabolism in the mammary glands of dairy goats, thus offering a sound theoretical basis for the production of high-quality goat milk. Full article

This study utilizes the super-efficiency SBM model to assess green total factor productivity, employs textual analysis to assess formal environmental regulation, and applies the entropy weighting method to assess informal environmental regulation using a dataset of 284 cities between 2003 and 2020. This study also employs the two-way fixed effects model and SDM to empirically examine the impact of dual environmental regulation on urban green total factor productivity. Based on the research results, the overall trend indicates that dual environmental regulation has a positive “U”-shaped impact on the green total factor productivity of both local and neighboring areas, and the improvement of green total factor productivity in the local area will lead to a corresponding increase in the green total factor productivity of neighboring cities. Heterogeneity analysis shows that formal environmental regulation has a significant effect in the Yangtze River Delta, the Pearl River Basin, and non-resource-based cities, but not in the Bohai Rim Economic Circle or resource-based cities; in all regions outside the Pearl River Basin, informal environmental regulation has a non-linear “marginal increasing effect” on green total factor productivity. These findings remain robust to a number of robustness and endogeneity issues. The study findings indicate that to optimize the influence of dual environmental regulation on green total factor production, governments should meticulously devise new environmental regulations and build novel channels for regional collaboration to enhance their supportive effects. Full article

Light-field images (LFIs) are gaining increased attention within the field of 3D imaging, virtual reality, and digital refocusing, owing to their wealth of spatial and angular information. The escalating volume of LFI data poses challenges in terms of storage and transmission. To address this problem, this paper introduces an MSHPE (most-similar hierarchical prediction encoding) structure based on light-field multi-view images. By systematically exploring the similarities among sub-views, our structure obtains residual views through the subtraction of the encoded view from its corresponding reference view. Regarding the encoding process, this paper implements a new encoding scheme to process all residual views, achieving lossless compression. High-efficiency video coding (HEVC) is applied to encode select residual views, thereby achieving lossy compression. Furthermore, the introduced structure is conceptualized as a layered coding scheme, enabling progressive transmission and showing good random access performance. Experimental results demonstrate the superior compression performance attained by encoding residual views according to the proposed structure, outperforming alternative structures. Notably, when HEVC is employed for encoding residual views, significant bit savings are observed compared to the direct encoding of original views. The final restored view presents better detail quality, reinforcing the effectiveness of this approach. Full article

Deep learning has attained state-of-the-art results in general image segmentation problems; however, it requires a substantial number of annotated images to achieve the desired outcomes. In the medical field, the availability of annotated images is often limited. To address this challenge, few-shot learning techniques have been successfully adapted to rapidly generalize to new tasks with only a few samples, leveraging prior knowledge. In this paper, we employ a gradient-based method known as Model-Agnostic Meta-Learning (MAML) for medical image segmentation. MAML is a meta-learning algorithm that quickly adapts to new tasks by updating a model’s parameters based on a limited set of training samples. Additionally, we use an enhanced 3D U-Net as the foundational network for our models. The enhanced 3D U-Net is a convolutional neural network specifically designed for medical image segmentation. We evaluate our approach on the TotalSegmentator dataset, considering a few annotated images for four tasks: liver, spleen, right kidney, and left kidney. The results demonstrate that our approach facilitates rapid adaptation to new tasks using only a few annotated images. In 10-shot settings, our approach achieved mean dice coefficients of 93.70%, 85.98%, 81.20%, and 89.58% for liver, spleen, right kidney, and left kidney segmentation, respectively. In five-shot sittings, the approach attained mean Dice coefficients of 90.27%, 83.89%, 77.53%, and 87.01% for liver, spleen, right kidney, and left kidney segmentation, respectively. Finally, we assess the effectiveness of our proposed approach on a dataset collected from a local hospital. Employing five-shot sittings, we achieve mean Dice coefficients of 90.62%, 79.86%, 79.87%, and 78.21% for liver, spleen, right kidney, and left kidney segmentation, respectively. Full article

Flying base stations, also known as aerial base stations, provide wireless connectivity to the user and utilize their aerial mobility to improve communication performance. Flying base stations depend on traditional stationary terrestrial base stations for connectivity, as stationary base stations act as the gateway to the backhaul/cloud via a wired connection. We introduce the flying base station channel capacity to build on the Shannon channel capacity, which quantifies the upper-bound limit of the rate at which information can be reliably transmitted using the communication channel regardless of the modulation and coding techniques used. The flying base station’s channel capacity assumes aerial mobility and ideal positioning for maximum channel capacity. Therefore, the channel capacity limit holds for any digital and signal processing technique used and for any location or positioning of the flying base station. Because of its inherent reliance on the stationary terrestrial base station, the flying base station channel capacity depends on the stationary base station’s parameters, such as its location and SNR performance to the user, in contrast to previous research, which focused on the link between the user and the flying base station without the stationary base station. For example, the beneficial region (where there is a positive flying base station capacity gain) depends on the stationary base station’s power and channel SNR in addition to the flying base station’s own transmission power and whether it has full duplex vs. half-duplex capability. We jointly study the mobility and the wireless communications of the flying base station to analyze its position, channel capacity, and beneficialness over the stationary terrestrial base station (capacity gain). As communication protocols and implementations for flying base stations undergo development for next-generation wireless networking, we focus on information-theoretical analyses and channel capacity to inform future research and development in flying base station networking. Full article

This study is dedicated to advancing practical and experimental knowledge within sustainable construction and enhancing community productivity, focusing on cattail schoenoplectus californicus, Cyperaceae fibers in Imbabura, Ecuador. The research aims to meticulously analyze and understand cattail fibers’ physical and mechanical properties, characteristics, and potential applications through extensive laboratory testing. The study strives to contribute significantly to the ongoing discussions surrounding sustainable building materials by offering a rich repository of scientific data and insights from our in-depth investigations. Furthermore, we delve into biotechnology and biomimicry, seeking inspiration from the natural world to innovate our construction methodologies. Our exploration also encompasses the technical dimensions of a building, artisanal craftsmanship, eco-conscious design principles, and the evaluation of seismic strength within architectural, structural, and acoustical design frameworks. Through this comprehensive approach, we aspire to illuminate new pathways for employing cattail in sustainable construction practices. Full article

Various metabolites, including phytohormones, phytoalexins, and amino acids, take part in the plant immune system. Herein, we analyzed the effects of L-methionine (Met), a sulfur-containing amino acid, on the plant immune system in tomato. Treatment with low concentrations of Met enhanced the resistance of tomato to a broad range of diseases caused by the hemi-biotrophic bacterial pathogen Pseudomonas syringae pv. tomato (Pst) and the necrotrophic fungal pathogen Botrytis cinerea (Bc), although it did not induce the production of any antimicrobial substances against these pathogens in tomato leaf tissues. Analyses of gene expression and phytohormone accumulation indicated that Met treatment alone did not activate the defense signals mediated by salicylic acid, jasmonic acid, and ethylene. However, the salicylic acid-responsive defense gene and the jasmonic acid-responsive gene were induced more rapidly in Met-treated plants after infection with Pst and Bc, respectively. These findings suggest that low concentrations of Met have a priming effect on the phytohormone-mediated immune system in tomato. Full article