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Abstract Ginsenoside Rb1 exhibits a wide range of biological activities, and gut microbiota is considered the main metabolic site for Rb1. However, the impact of gut microbiota on the pharmacokinetics of Rb1 are still uncertain. In this study, we investigated the gut microbiome changes and the pharmacokinetics after a 30 d Rb1 intervention. Results reveal that the systemic exposure and metabolic clearance rate of Rb1 and Rd were substantially affected after orally supplementing Rb1 (60 mg/kg) to rats. Significant increase in the relative abundance of Bacteroides cellulosilyticus in gut microbiota and specific glycoside hydrolase (GH) families, such as GH2, GH92, and GH20 were observed based on microbiome and metagenomic analysis. Moreover, a robust association was identified between the pharmacokinetic parameters of Rb1 and the relative abundance of specific Bacteroides species, and glycoside hydrolase families. Our study demonstrates that Rb1 administration significantly affects the gut microbiome, revealing a complex relationship between B. cellulosilyticus, key GH families, and Rb1 pharmacokinetics.

Beef cattle in the farm are active, which leads the collection of posture of the beef cattle changeable, so it is difficult to automatically measure the body size of the beef cattle. Aiming at the above problems, an automatic measurement method for beef cattle's body size under multi-pose was proposed by analyzing the skeleton features of beef cattle head and the edge contour features of beef cattle images. Firstly, the consumer-grade depth camera Azure Kinect DK was used to collect the top-view depth video data directly above the beef cattle and the video data were divided into frames to obtain the original depth image. Secondly, the original depth image was processed by shadow interpolation, normalization, image segmentation and connected domain to remove the complex background and obtain the target image containing only beef cattle. Thirdly, the Zhang-Suen algorithm was used to extract the beef cattle skeleton of the target image, and calculated the intersection points and endpoints of the skeleton, so as to analyze the characteristics of the beef cattle head to determine the head removal point , and to remove the beef cattle head information from the image. Finally, the curvature curve of the beef cattle profile was obtained by the improved U-chord curvature method. The body measurement points were determined according to the curvature value and converted into three-dimensional spaces to calculate the body size parameters. In this paper, the postures of beef cattle, which were analyzed by a large amount of depth image data, were divided into left crooked, right crooked, correct posture, head down and head up, respectively. The test results showed that the head removal method proposed based on the skeleton in multiple postures hads head removel success rate higher than 92% in the five postures. Using the body measurement point extraction method based on the improved U-chord curvature proposed, the average absolute error of body length measurement was 2.73 cm, the average absolute error of body height measurement was 2.07 cm, and the average absolute error of belly width measurement was 1.47 cm. The method provides a better way to achieve the automatic measurement of beef cattle body size in multiple poses.

Hyperlipidemia, characterized by elevated serum lipid concentrations resulting from lipid metabolism dysfunction, represents a prevalent global health concern. Ginsenoside Rb1, compound K (CK), and 20(S)-protopanaxadiol (PPD), bioactive constituents derived from Panax ginseng, have shown promise in mitigating lipid metabolism disorders. However, the comparative efficacy and underlying mechanisms of these compounds in hyperlipidemia prevention remain inadequately explored. This study investigates the impact of ginsenoside Rb1, CK, and PPD supplementation on hyperlipidemia in rats induced by a high-fat diet. Our findings demonstrate that ginsenoside Rb1 significantly decreased body weight and body weight gain, ameliorated hepatic steatosis, and improved dyslipidemia in HFD-fed rats, outperforming CK and PPD. Moreover, ginsenoside Rb1, CK, and PPD distinctly modified gut microbiota composition and function. Ginsenoside Rb1 increased the relative abundance of Blautia and Eubacterium, while PPD elevated Akkermansia levels. Both CK and PPD increased Prevotella and Bacteroides, whereas Clostridium-sensu-stricto and Lactobacillus were reduced following treatment with all three compounds. Notably, only ginsenoside Rb1 enhanced lipid metabolism by modulating the PPARγ/ACC/FAS signaling pathway and promoting fatty acid β-oxidation. Additionally, all three ginsenosides markedly improved bile acid enterohepatic circulation via the FXR/CYP7A1 pathway, reducing hepatic and serum total bile acids and modulating bile acid pool composition by decreasing primary/unconjugated bile acids (CA, CDCA, and β-MCA) and increasing conjugated bile acids (TCDCA, GCDCA, GDCA, and TUDCA), correlated with gut microbiota changes. In conclusion, our results suggest that ginsenoside Rb1, CK, and PPD supplementation offer promising prebiotic interventions for managing HFD-induced hyperlipidemia in rats, with ginsenoside Rb1 demonstrating superior efficacy.

Realizing the construction of intelligent farming by using advanced information technology, thus improving the living welfare of dairy cows and the economic benefits of dairy farms has become an important goal and task in dairy farming research field. Computer vision technology has the advantages of non-contact, stress-free, low cost and high throughput, and has a broad application prospect in animal production. On the basis of describing the importance of computer vision technology in the development of intelligent farming industry, this paper introduced the cutting-edge technology of cow physiological parameters and disease diagnosis based on computer vision, including cow temperature monitoring, body size monitoring, weight measurement, mastitis detection and lameness detection. The introduction coverd the development process of these studies, the current mainstream techniques, and discussed the problems and challenges in the research and application of related technology, aiming at the problem that the current computer vision-based detection methods are susceptible to individual difference and environmental changes. Combined with the development status of farming industry, suggestions on how to improve the universality of computer vision technology in intelligent farming industry, how to improve the accuracy of monitoring cows' physiological parameters and disease diagnosis, and how to reduce the influence of environment on the system were put forward. Future research work should focus on research and developmentof algorithm, make full use of computer vision technology continuous detection and the advantage of large amount of data, to ensure the accuracy of the detection, and improve the function of the system integration and data utilization, expand the computer vision system function. Under the premise that does not affect the ability of the system, to improve the study on the number of function integration and system function and reduce equipment costs.

The impact of corrosion degree, axial compression ratio, reinforcement ratio of longitudinal bar and horizontal distribution rebar, and stirrup of boundary column on seismic performance of RC shear walls were investigated. The corrosion forms (rust expansion cracks and corroded steel bars), failure process, hysteretic characteristics, bearing capacity, and deformability were compared. Subsequently, a numerical model of corroded RC shear walls was established adopting shell elements. Finally, according to the numerical simulation method, considering the uncertainty of corrosion degree and material parameters, the vulnerability models of RC shear wall components with different corrosion degrees were built. The results show that the mechanical properties of the shear wall were seriously deteriorated due to the corrosion of steel bars, and the ultimate displacement and ductility coefficient of severely corroded specimens were reduced by 28.5% and 12.27% respectively, compared to non-corroded specimens. A proposed numerical modeling method for corroded RC shear walls based on shell element is accurate, and the bearing capacity error and energy dissipation error of the simulation and test results were less than 20%. As the degree of corrosion grew, the probability of shear wall components experiencing more severe failure added significantly. When the displacement angle was 1/120 (This is the limit value of elastic-plastic displacement angle specified in the code), the probability of DS3 and DS4 occurring in the shear wall with a corrosion degree of 0% were 56% and 39.44%, and the probability of DS4 and DS5 occurring in the shear wall with a corrosion degree of 10% were 41.1% and 38.44%. [ABSTRACT FROM AUTHOR]

According to the operating conditions and load requirements of the lifting exoskeleton, a harmonic reducer with large reduction ratio and high torque output is designed in this paper (Xiang Guoqi, 2005). From the perspective of structural dynamics (Donghui et al., 2015; Zuguang et al., 2011), use ANSYS simulation software to study the motion intensity of the harmonic reducer and verify the reliability of the whole structure system; Secondly, the modal analysis of the whole machine was carried out and former sixth-order natural frequencies were extracted; Simulate and analyze the frequency-amplitude relationship of the whole machine structure system at low frequencies, and analyze possible resonance and vibration problems. Finally, take the key component flexspline as the research object, and extract former sixth-order natural frequencies; Simulate and analyze the frequency-amplitude relationship of the whole structure system at low frequencies to verify its motion performance.