Search Results (223)

As the mobile cassette carrier of the methicillin resistance gene mecA that is transported across staphylococci species, the evolution and origin of Staphylococcal Cassette Chromosome mec (SCCmec)—and in particular, the composition of mecA and SCCmec—have been extensively discussed in the scientific literature; however, information regarding its dissemination across geographical limits and evolution over decades remains limited. In addition, whole-genome sequencing-based macro-analysis was unable to provide sufficiently detailed evolutionary information on SCCmec. Herein, the cassette chromosome recombinase genes ccrAB/C, as essential components of SCCmec, were employed to explore the evolution of SCCmec. This work established the basic taxonomy of 33 staphylococci species. The CUB of mecA, ccrAB/C of 12 SCCmec types and core genome of 33 staphylococci species were subsequently compared; the phylogenetic relationship of ccrAB/C was observed via SCCmec typing on a temporal and geographical scale; and the duplicate appearance of ccrAB/C was illustrated by comparing SCCmec compositions. The results highlighted a deviation in the CUB of mecA and ccrAB/C, which evidenced their exogenous characteristics to staphylococci, and provided theological support for the phylogenetic analysis of ccrAB/C as representative of SCCmec. Importantly, the phylogenetic relationship of ccrAB/C did not exhibit centralization over time; instead, similarly to mecA, ccrAB/C with similar identities had close clades across decades and geographical limits and different SCCmec types, which enabled us to discriminate SCCmec based on the sequence identity of ccrAB/C. In addition, the duplicate appearance of ccrAB/C and fixed composition of the ccrAB/C complex among different strains were indicative of more complicated transmission mechanisms than targeting direct repeats of SCCmec. Full article

Objective: In the present study, we used phenotypic and molecular methods to determine susceptibility to oxacillin in coagulase-negative staphylococci (CoNS) and estimate the prevalence of strains with low-level resistance to oxacillin, mecA-positive oxacillin-susceptible methicillin-resistant (OS-MRCoNS), and borderline oxacillin-resistant (BORCoNS). Methods: One hundred one CoNS strains were screened for oxacillin and cefoxitin susceptibility using phenotypic (disk diffusion, agar dilution, latex agglutination, and chromagar) and molecular (detection of mecA, mecB, and mecC) methods. Staphylococcal cassette chromosome mec (SCCmec) typing was performed. Results: Sixteen (15.8%) CoNS strains were mecA-positive, and 85 (84.2%) were mec-negative. Seven (6.9%) were classified as OS-MRCoNS, accounting for 43.8% of all mecA-positive strains. Twelve (11.9%) mec-negative strains were classified as borderline oxacillin resistant (BORCoNS). Compared with MRCoNS and BORCoNS, OS-MRCoNS strains demonstrated lower resistance to non-beta-lactams. SCCmec type I cassette was predominant. The disc-diffusion method with oxacillin accurately predicted OS-MRCoNS strains but did not provide reliable results for BORCoNS strains. Meanwhile, the latex agglutination test and CHROMagar culture accurately identified BORCoNS but not OS-MRCoNS. Conclusions: Finally, our findings imply that the recognition of methicillin resistance in CoNS requires a meticulous approach and that further research is needed to develop unified laboratory diagnostic algorithms to prevent the misreporting of borderline CoNS. Full article

This paper proposes efficient implementations of robot audition systems, specifically focusing on deployments using HARK, an open-source software (OSS) platform designed for robot audition. Although robot audition systems are versatile and suitable for various scenarios, efficiently deploying them can be challenging due to their high computational demands and extensive processing times. For scenarios involving intensive high-dimensional data processing with large-scale microphone arrays, our generalizable GPU-based implementation significantly reduced processing time, enabling real-time Sound Source Localization (SSL) and Sound Source Separation (SSS) using a 60-channel microphone array across two distinct GPU platforms. Specifically, our implementation achieved speedups of 23.3× for SSL and 3.0× for SSS on a high-performance server equipped with an NVIDIA A100 80 GB GPU. Additionally, on the Jetson AGX Orin 32 GB, which represents embedded environments, it achieved speedups of 14.8× for SSL and 1.6× for SSS. For edge computing scenarios, we developed an adaptable FPGA-based implementation of HARK using High-Level Synthesis (HLS) on M-KUBOS, a Multi-Access Edge Computing (MEC) FPGA Multiprocessor System on a Chip (MPSoC) device. Utilizing an eight-channel microphone array, this implementation achieved a 1.2× speedup for SSL and a 1.1× speedup for SSS, along with a 1.1× improvement in overall energy efficiency. Full article

This paper presents a novel algorithm to address resource allocation and network-slicing challenges in multiaccess edge computing (MEC) networks. Network slicing divides a physical network into virtual slices, each tailored to efficiently allocate resources and meet diverse service requirements. To maximize the completion rate of user-computing tasks within these slices, the problem is decomposed into two subproblems: efficient core-to-edge slicing (ECS) and autonomous resource slicing (ARS). ECS facilitates collaborative resource distribution through cooperation among edge servers, while ARS dynamically manages resources based on real-time network conditions. The proposed solution, a multiagent actor–critic resource scheduling (MAARS) algorithm, employs a reinforcement learning framework. Specifically, MAARS utilizes a multiagent deep deterministic policy gradient (MADDPG) for efficient resource distribution in ECS and a soft actor–critic (SAC) technique for robust real-time resource management in ARS. Simulation results demonstrate that MAARS outperforms benchmark algorithms, including heuristic-based, DQN-based, and A2C-based methods, in terms of task completion rates, resource utilization, and convergence speed. Thus, this study offers a scalable and efficient framework for resource optimization and network slicing in MEC networks, providing practical benefits for real-world deployments and setting a new performance benchmark in dynamic environments. Full article

Amino acids (AAs) have broad nutritional, therapeutic, and medical significance and thus are one of the most common active ingredients of nutritional supplements. Analytical strategies for determining AAs are high-priced and often limited to methods that require modification of AA polarity or incorporation of an aromatic moiety. The aim of this work was to develop a new method for the determination of L-arginine, L-ornithine, and L-lysine on low-cost microchip electrophoresis instrumentation conjugated with capacitively coupled contactless conductivity detection. A solution consisting of 0.3 M acetic acid and 1 × 10⁻⁵ M iminodiacetic acid has been identified as the optimal background electrolyte, ensuring the shortest possible analysis time. The short migration times of amino acids (t ≤ 64 s) and method simplicity resulted in high analysis throughput with high precision and linearity (R²$\ge$ 0.9971). The limit of detection values ranged from 0.15 to 0.19 × 10⁻⁶ M. The accuracy of the proposed method was confirmed by recovery measurements. The results were compared with CE-UV-VIS and HPLC-DAD methods and showed good agreement. This work represents the first successful demonstration of the ME-C⁴D analysis of L-arginine, L-ornithine, and L-lysine in real samples. Full article

Milk fat is an important indicator for evaluating milk quality and a symbol of the core competitiveness of the dairy industry. It can be improved through genetic and feed management factors. Interferon alpha-inducible protein 27 (IFI27) was found to be differentially expressed when comparing the transcriptome in high- and low-fat bovine mammary epithelial cells (bMECs) in our previous research. Therefore, this study aimed to investigate whether the IFI27 gene had a regulatory effect on lipid metabolism.We detected six SNPs in the IFI27 gene (UTR-(-127) C>A, UTR-(-105) T>A, UTR-(-87) G>A, I1-763 G>T, E2-77 G>A, E2-127 G>T) in a Chinese Holstein cow population. Association analysis of the polymorphism of IFI27 and milk quality traits showed that the AG and GG genotype of E2-77 G>A, and the GG and TT genotypes of E2-127 G>T were connected to milk fat (p < 0.05). Haplotype frequency analysis showed that H5H5 was associated with lower milk fat content (p < 0.05), while milk from H5H6 animals had a higher fat content (p < 0.05). Subsequently, IFI27 overexpression vectors (PBI-CMV3-IFI27) and interference vectors (Pb7sk-GFP-shRNA) were constructed. Overexpression of the IFI27 gene in bMECs caused a significant increase in triglycerides (TGs) content (p < 0.05) and decreases in cholesterol (CHOL) and nonestesterified fatty acid (NEFA) content (p < 0.05), while interference with IFI27 expression produced opposing changes (p < 0.05). In summary, IFI27 E2-77 G>A and IFI27 E2-127 G>T may be useful as molecular markers in dairy cattle to measure milk fat, and the IFI27 gene may play an important role in milk lipid metabolism. Full article

The SCD is a rate-limiting enzyme that catalyzes the synthesis of monounsaturated fatty acids (MUFAs) in dairy cows; however, its role in the mammary gland of buffalo is not well understood. In this study, we isolated and characterized the complete coding sequence (CDS) of the buffalo SCD gene from mammary gland tissue and investigated its effects on milk fat synthesis using bioinformatics analyses, tissue differential expression detection, and cellular functional experiments. The cloned SCD gene has a CDS length of 1080 bp, encoding a protein of 359 amino acids. This protein is hydrophilic, lacks a signal peptide, and contains four transmembrane domains, including 10 conserved motifs and a Delta9-FADS domain, characteristic of the fatty acid desaturase family involved in unsaturated fatty acid biosynthesis within the endoplasmic reticulum. Molecular characterization revealed that the physicochemical properties, conserved domains, structures, and functions of buffalo SCD are highly similar to those in other Bovidae species. Among the tissues analyzed, SCD expression was highest in the mammary gland during lactation and in the cerebellum during dry-off period. Notably, SCD expression in the mammary gland was significantly higher during lactation compared to the dry-off period. Subcellular localization experiments confirmed that SCD functions in the endoplasmic reticulum of buffalo mammary epithelial cells (BuMECs). Functional overexpression and interference experiments in BuMECs demonstrated that SCD promotes milk fat synthesis by affecting the expression of lipid synthesis-related genes such as ACACA, FASN, and DGAT1, as well as milk fat regulatory genes like SREBFs and PPARG, thereby influencing intracellular triglyceride (TAG) content. Additionally, 18 single-nucleotide polymorphisms (SNPs) were identified in the buffalo SCD gene, with a specific SNP at c.-605, showing potential as molecular markers for improving milk production traits. These findings highlight that the SCD gene is a key gene in buffalo milk fat synthesis, involved in the de novo synthesis of milk fatty acids. Full article

This study investigated the toxigenic genes and antimicrobial resistance profiles of Staphylococcus aureus strains isolated from 260 raw milk samples collected from dairy farms in Türkiye. The results indicated that 60.7% of staphylococcal enterotoxin genes (sea, seb, sed, seg, sei, sej, sek, seq, sem, seo, and seu) and 21.4% of the tst and eta genes were positive, with most enterotoxin-positive samples carrying more than one gene. The sec, see, seh, sel, sen, sep, and etb genes were not identified in any samples. The prevalence of antibiotic resistance genes (mecA, blaR, blaI, blaZ, vanA, ermT, tetK, aac/aph, ant, dfrA, tcaR, IS256, and IS257) was high at 89.2%, with bla being the most frequently detected gene (75%). The mecA gene was present in 14.2% of samples, while tcaR was detected in 78.5%. Nevertheless, the mecC was not identified. Disinfectant resistance genes (qacA/B, qacC, qacJ, smr) were detected in 21.4% of the samples. The results of the disk diffusion test showed that 64.2% of strains were resistant to penicillin G and ampicillin, with additional resistance found for cefoxitin, teicoplanin, levofloxacin, norfloxacin, and other antibiotics. These findings highlight a significant public health and food safety risk associated with raw milk due to the presence of S. aureus strains with toxigenic genes and high antimicrobial resistance. Full article

Whole genome sequencing (WGS) has the potential to greatly enhance AMR (Anti-microbial Resistance) surveillance. To characterize the prevalent pathogens and dissemination of various AMR-genes, 73 clinical isolates were obtained from blood and respiratory tract specimens, were characterized phenotypically by VITEK-2 (bioMerieux), and 23 selected isolates were genotypically characterized by WGS (Illumina). AST revealed high levels of resistance with 50.7% XDR, 32.9% MDR, and 16.4% non-MDR phenotype. A total of 11 K. pneumoniae revealed six sequence types, six K-locus, and four O-locus types, with ST437, KL36, and O4 being predominant types, respectively. They carried ESBL genes CTX-M-15 (90.9%), TEM-1D (72.7%), SHV-11 (54.5%), SHV-1, SHV-28, OXA-1, FONA-5, and SFO-1; NDM-5 (72.7%) and 63.6%OXA48-like carbapenamases; 90.9%OMP mutation; dfrA12, sul-1, ermB, mphA, qnrB1, gyrA831, and pmrB1 for other groups. Virulence gene found were Yerisiniabactin (90.9%), aerobactin, RmpADC, and rmpA2. Predominant plasmid replicons were Col(pHAD28), IncFII, IncFIB(pQil), and Col440. A total of seven XDR A. baumannii showed single MLST type(2) and single O-locus type(OCL-1); with multiple AMR-genes: blaADC-73, blaOXA-66, blaOXA-23, blaNDM-1, gyrA, mphE, msrE, and tetB. Both S. aureus tested were found to be ST22, SCCmec IVa(2B), and spa type t309; multiple AMR-genes: blaZ, mecA, dfrC, ermC, and aacA-aphD. Non-MDR Enterococcus faecalis sequenced was ST 946, with multiple virulence genes. This study documents for the first-time prevalent virulence genes and MLST types, along with resistance genes circulating in our center. Full article

Mobile Edge Computing (MEC) is crucial for reducing latency by bringing computational resources closer to the network edge, thereby enhancing the quality of services (QoS). However, the broad deployment of cloudlets poses challenges in efficient network slicing, particularly when traffic distribution is uneven. Therefore, these challenges include managing diverse resource requirements across widely distributed cloudlets, minimizing resource conflicts and delays, and maintaining service quality amid fluctuating request rates. Addressing this requires intelligent strategies to predict request types (common or urgent), assess resource needs, and allocate resources efficiently. Emerging technologies like edge computing and 5G with network slicing can handle delay-sensitive IoT requests rapidly, but a robust mechanism for real-time resource and utility optimization remains necessary. To address these challenges, we designed an end-to-end network slicing approach that predicts common and urgent user requests through T distribution. We formulated our problem as a multi-agent Markov decision process (MDP) and introduced a multi-agent soft actor–critic (MAgSAC) algorithm. This algorithm prevents the wastage of scarce resources by intelligently activating and deactivating virtual network function (VNF) instances, thereby balancing the allocation process. Our approach aims to optimize overall utility, balancing trade-offs between revenue, energy consumption costs, and latency. We evaluated our method, MAgSAC, through simulations, comparing it with the following six benchmark schemes: MAA3C, SACT, DDPG, S2Vec, Random, and Greedy. The results demonstrate that our approach, MAgSAC, optimizes utility by 30%, minimizes energy consumption costs by 12.4%, and reduces execution time by 21.7% compared to the closest related multi-agent approach named MAA3C. Full article

Methicillin-resistant Staphylococcus aureus (MRSA) has been included by the World Health Organization in its list of “priority pathogens” because of its widespread prevalence and the severity of the infections it causes. The role of food in infections caused by MRSA is unknown, although strains of this microorganism have been detected in various items for human consumption. In order to gain an overview of any possible role of food in MRSA infections, a review was undertaken of studies published between January 2001 and February 2024 relating to MRSA. These comprised research that focused on fish and shellfish, eggs and egg products, foods of vegetable origin, other foodstuffs (e.g., honey or edible insects), and drinking water. In most of these investigations, no prior enrichment was carried out when isolating strains. Three principal methods were used to confirm the presence of MRSA, namely amplification of the mecA gene by PCR, amplification of the mecA and the mecC genes by PCR, and disc diffusion techniques testing susceptibility to cefoxitin (30 μg) and oxacillin (1 μg). The great diversity of methods used for the determination of MRSA in foods and water makes comparison between these research works difficult. The prevalence of MRSA varied according to the food type considered, ranging between 0.0% and 100% (average 11.7 ± 20.3%) for fish and shellfish samples, between 0.0% and 11.0% (average 1.2 ± 3.5%) for egg and egg products, between 0.0% and 20.8% (average 2.5 ± 6.8%) for foods of vegetable origin, between 0.6% and 29.5% (average 28.2 ± 30.3%) for other foodstuffs, and between 0.0% and 36.7% (average 17.0 ± 14.0%) for drinking water. Full article

Leptin (LEP), a protein hormone well-known for its role in metabolic regulation, has recently been linked to lipid metabolism in cattle. However, its function in buffalo mammary glands remains unclear. To address this issue, we isolated and identified the LEP gene and conducted experiments to investigate its function in buffalo mammary epithelial cells (BuMECs). In this study, two transcript variants of LEP, designated as LEP_X1 and LEP_X2, were identified. The coding sequences (CDS) of LEP_X1 and LEP_X2 are 504 bp and 579 bp in length, encoding 167 and 192 amino acid residues, respectively. Bioinformatics analysis revealed that LEP_X2 is a hydrophobic protein with an isoelectric point below 7 and contains a signal peptide, while LEP_X1 is hydrophilic and lacks a signal peptide. Our study found that LEP gene expression in lactating BuMECs was significantly higher than in non-lactating cells, with LEP_X2 expression remarkably higher than LEP_X1 in lactating BuMECs. Overexpression of both LEP_X1 and LEP_X2 significantly promoted the expression of genes related to milk fat synthesis in lactating BuMECs, including STAT3, PI3K, mTOR, SCD, and SREBF1, accompanied by an increase in cellular triglycerides (TG). Interestingly, LEP_X2 overexpression significantly suppressed LEP_X1 expression while increasing intracellular TG concentration by 12.10-fold compared to LEP_X1 overexpression, suggesting an antagonistic relationship between the two variants and supposing LEP_X2 plays a dominant role in milk fat synthesis in lactating BuMECs. Additionally, four nucleotide substitutions were identified in the buffalo LEP CDS, including a nonsynonymous substitution c.148C>T (p.Arg50Cys), which was predicted to decrease the stability of the LEP protein without affecting its function. These results collectively underscore the significant role of LEP in milk fat synthesis and can provide a basis for molecular breeding strategies of buffalo. Full article

In the rapidly evolving domain of mobile edge–cloud computing (MECC), the proliferation of Internet of Things (IoT) devices and mobile applications poses significant challenges, particularly in dynamically managing computational demands and user mobility. Current research has partially addressed aspects of service migration and resource allocation, yet it often falls short in thoroughly examining the nuanced interdependencies between migration strategies and resource allocation, the consequential impacts of migration delays, and the intricacies of handling incomplete tasks during migration. This study advances the discourse by introducing a sophisticated framework optimized through a deep reinforcement learning (DRL) strategy, underpinned by a Markov decision process (MDP) that dynamically adapts service migration and resource allocation strategies. This refined approach facilitates continuous system monitoring, adept decision making, and iterative policy refinement, significantly enhancing operational efficiency and reducing response times in MECC environments. By meticulously addressing these previously overlooked complexities, our research not only fills critical gaps in the literature but also enhances the practical deployment of edge computing technologies, contributing profoundly to both theoretical insights and practical implementations in contemporary digital ecosystems. Full article

This article considers the issues of ensuring operational performance and environmental sustainability of marine diesel engines by using biodiesel fuel. This research was conducted on 5S60ME-C8 MAN-B&W Diesel Group and 6DL-16 Daihatsu Diesel marine diesel engines, which are operated using RMG380 petroleum fuel and B10 and B30 biodiesel fuels. The efficiency of biofuel usage was assessed based on environmental (reduced nitrogen oxide concentration in exhaust gases) and economic (increased specific effective fuel consumption) criteria. It was found that the use of B10 and B30 biofuels provides a reduction in nitrogen oxide concentration in exhaust gases by 14.71–25.13% but at the same time increases specific effective fuel consumption by 1.55–6.01%. Optimum fuel injection advance angles were determined that ensure the best thermal energy, economic and environmental performance of diesel engines. The optimum angle of biofuel supply advance is determined experimentally and should correspond to the limits recommended by the diesel engine operating instructions. It has been proven experimentally that the use of biofuel increases the environmental sustainability of marine diesel engines by 13.75–29.42%. It increases the diesel engines environmental safety in case of emergency situations as well as accidental and short-term emissions of exhaust gases with an increased content of nitrogen oxides into the atmosphere phenomena that are possible in starting modes of diesel engine operation as well as in modes of sudden load changes. It is the increase in the environmental friendliness of marine diesel engines in the case of using biofuel that is the most positive criterion and contributes to the intensity of biofuel use in power plants of sea vessels. Full article

Antimicrobial therapy is the most frequently used medical intervention for bovine mastitis in the dairy industry. This study aims to monitor the extent of the antimicrobial resistance (AMR) problem in Staphylococcus aureus in the dairy industry in Western Romania. Twenty farms were selected by random sampling in a transverse epidemiological study conducted across four counties in Western Romania and divided into livestock units. This study assessed the association between the resistance genes to phenotypic expression of resistance and susceptibility. Isolates of S. aureus were identified and q-PCR reactions were used to detect antibiotic resistance genes. One hundred and fifty bovine and 20 human samples were positive for S. aureus. Twenty five percent of bovine isolates (30/120) and none(0/30) of the human isolates were methicillin-resistant S. aureus (MRSA). All isolates were susceptible to fosfomycin, ciprofloxacin, netilmicin, and resistant to ampicillin and penicillin. S. aureus isolates regarded as phenotypically resistant (R) were influenced by the origin of the samples (human versus bovine, χ2 = 36.510, p = 0.013), whether they were methicillin-resistant S. aureus (χ2 = 108.891, p < 0.000), the county (χ2 = 103.282, p < 0.000) and farm of isolation (χ2 = 740.841, p < 0.000), but not by the size of the farm (χ2 = 65.036, p = 0.306). The multiple antibiotic resistance index was calculated for each sample as the number regarded as phenotypically resistant (R)/total antibiotics tested (MARI = 0.590 ± 0.023) was significantly higher (p < 0.000) inmethicillin-resistant S. aureus (0.898 ± 0.019) than non-methicillin-resistant S. aureus (0.524 ± 0.024) isolates. For the antibiotics tested, the total penetrance (P%) of the resistance genes was 59%, 83% for blaZ, 56% for cfr, 50% for erm(B), 53% for erm(C), 57% for mecA and 32% for tet(K). Penetrance can be used as a parameter for guidance towards a more accurate targeting of chemotherapy. P% in S. aureus was strongly positively correlated with the multiple antibiotic resistance index (r = +0.878, p < 0.000) with the potential to use the same limit value as an antibiotic management decision criterion. Considering cow mastitis, the penetrance value combined with the multiple antibiotic resistance index suggests that penetrance could serve as a useful parameter for more precise targeting of chemotherapy for S. aureus. Full article