Staphylococcus aureus, a common cause of bovine mastitis, is known for its ability to acquire to antimicrobial resistance and to secrete numerous virulence factors that can exacerbate inflammation. In addition, alpha-hemolysin has an important role in S. aureus infections, diversity of the hla gene (that produces alpha-hmolysin) in S. aureus isolated from bovine mastitis has not been well characterized. The objective was, therefore, to determine diversity of virulence genes, hla gene sequences, and clonal profiles of S. aureus from bovine mastitis in Chinese dairy herds, and to evaluate inter-relationships. The antimicrobials resistance varies from as low as 1.9% (2/103) for CTX to as high as 76.7% (79/103) for penicilin in the 103 isolates and 46 (44.7%) S. aureus were determined as multi-resistant isolates with diverse resistance patterns. Thirty-eight virulence gene patterns (with variable frequencies) were identified in the 103 isolates and correlated with MLST types, indicating a great diversity. Although the hla gene also had great diversity (14 genotypes), Hla peptides were relatively more conserved. With 7 clonal complexes identified from 24 spa types and 7 MLST types. Regarding the letter, ST 97 was the dominant type in S. aureus from bovine mastitis in China. Furthermore, based on phylogenetic analysis, there was a distinct evolutionary relationship between the hla gene and MLST. Multi-resistant S. aureus occurred in bovine mastitis with diverse resistance patterns. The diversity of virulence gene profiles, especially the hla gene and, their relationship with molecular types were reported for the first time in S. aureus from bovine mastitis, which will be useful for future studies on immunogenicity and vaccine development. In addition, based on the distinct evolutionary relationship between the hla gene and MLST types, we inferred that the hla gene has potential role for molecular typing of S. aureus.
Bovine protothecal mastitis results in considerable economic losses worldwide. However, Prototheca zopfii induced morphological alterations and oxidative stress in bovine mammary epithelial cells (bMECs) is not comprehensively studied yet. Therefore, the aim of this current study was to investigate the P. zopfii induced pathomorphological changes, oxidative stress and apoptosis in bMECs. Oxidative stress was assessed by evaluating catalase (CAT), superoxide dismutase (SOD), glutathione peroxidase (GPx), malondialdehyde (MDA) contents and lactate dehydrogenase (LDH) activity, while ROS generation and apoptosis was measured by confocal laser scanning microscopy. The results revealed that infection of P. zopfii genotype II (GTII) significantly changed bMECs morphology, increased apoptotic rate and MDA contents at 12 h (p < 0.05) and 24 h (p < 0.01) in comparison with control group, in time-dependent manner. LDH activity and ROS generation was also increased (p < 0.01) at 12 h and 24 h. However, SOD and CAT contents in bMECs infected with GTII were decreased (p < 0.05) at 12 h, while GPx (p < 0.01), SOD (p < 0.05) and CAT (p < 0.01) levels were reduced at 24 h. In case of GTI, only CAT and GPx activities were significantly decreased when the duration prolonged to 24 h but lesser than GTII. This suggested that GTII has more devastating pathogenic effects in bMECs, and the findings of this study concluded that GTII induced apoptosis and oxidative stress in bMECs via the imbalance of oxidant and antioxidant defenses as well as the production of intracellular ROS.
Integrons are important genetic elements that allow easy acquisition and dissemination of antimicrobial resistance genes. Studies reporting occurrence of integrons in
The lying time of cows is a key indicator of their health and comfort. The ability to automatically recognize the lying posture of cows while simultaneously realizing individual cow identification can play an important role in improving cow welfare, increasing milk yield, detecting cow diseases in a timely manner and enabling precision dairy farming management. In this paper, a method of individual identification for lying dairy cows in a barn based on YOLOX and a feature extraction network named CowbodyNet is proposed. In practical applications, when new cows enter the barn, there is no need to collect a large number of images to retrain the model. In practical application, it is very convenient to collect several images of newly added individual cows and store them in the database. First, the low-light images collected at night are enhanced by the multiscale retinex with chromaticity preservation (MSRCP) algorithm to improve the image quality. Then, the YOLOX target detection algorithm is applied to detect and segment cows in the lying posture. Following this, the segmented images of lying cows are input into CowbodyNet to generate feature vectors, which are used to construct a feature vector database. Subsequently, the Euclidean distances between the feature vector of a cow to be identified and the feature vectors in the database are calculated to determine the identification result. The proposed method achieves 94.43% lying cow identification accuracy on a data set containing top-view images of 72 cows. Finally, the individual cow detection and identification model is successfully deployed on the Jetson Xavier NX embedded platform. The results demonstrate the effectiveness and practicability of the proposed cow identification method. This study provides effective technical support for the practical application of identifying individual lying cows. The results show the effectiveness and practicability of the proposed cow identification method.
The accuracy of ASV for HMIs detection was negatively affected by organic matter or organic macromolecules present in soil samples due to the formation of complexes, i.e., the complexation of organic matter to HMIs, which weakened the electroactivity of HMIs and finally caused distortion of the ASV detection results. Therefore, we proposed an efficient, low-cost, accurate and green method for the ASV detection of Pb(II) and Cd(II) in soil extracts by restoring the ASV signals of target HMIs based on LPUV-H 2 O 2 advanced oxidation photolysis, which could be used as a new strategy for the quantitative determination of organic HMIs in soil. The effect of different concentrations of humic acid sodium (HAS) on the stripping responses of target HMIs was investigated first. The key parameters of the proposed LPUV-H 2 O 2 photolysis system for the restoration of stripping responses were optimized. Additionally, the restoration mechanism of the HMIs’ stripping responses was studied by total organic carbon (TOC), UV–vis spectroscopy (UV), fluorescence spectroscopy (FS) and Fourier transform infrared spectroscopy (FTIR). The measurement results showed that the stripping signals of target HMIs in the simulated soil samples can be restored to nearly 100% with good repeatability, and the restoration ratio of the stripping signal fluctuated within 10%. Moreover, the analysis of real soil samples was carried out to further verify the feasibility of the proposed LPUV-H 2 O 2 -photolysis-based pretreatment method for ASV detection, wherein the concentrations of HMIs were calculated by the standard addition method. The analysis results of real samples showed that 93.7% of Cd(II) and 92.5% of Pb(II) in soil extracts were detectable.
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