ABSTRACT
In modern society, people's pace of life is fast, and the pressure is enormous, leading to increasingly prominent issues such as obesity and sub-health. Traditional fitness methods cannot meet people's needs to a certain extent. Therefore, this work aims to use technology to change people's lifestyles and compensate for traditional fitness methods' shortcomings. Firstly, this work overviews neurorobotics, providing neural perception and control functions for aerobics intelligent fitness system. Secondly, the connection between big data and machine learning (ML), big data technology products, and the ML process are discussed. The Spark big data platform builds node data for calculation, and the decision tree algorithm is used for data preprocessing. These are important for future intelligent fitness analysis. This work proposes an aerobics intelligent fitness system based on neurorobotics technology and big data analysis and develops a recommendation system for the best fitness exercise. This system utilizes neural perception and control functions, combined with big data and ML technology, to solve the obesity and sub-health problems faced by people in fast-paced and high-pressure lifestyles. By harnessing the computational capabilities of the Spark big data platform and applying the decision tree algorithm for data preprocessing, the system can furnish users with personalized fitness plans and optimization recommendations. This work conducts a model performance study on 35 % aerobic fitness data on intelligent fitness Android v1.0.8 to evaluate the system's data processing ability and training effectiveness. Moreover, the aerobics intelligent fitness system models based on neurorobotics, big data, and ML are evaluated. The results indicate that normalizing the data using the Min-Max method leads to a decrease in the F1 value and a reduction in data set errors. Consequently, the dataset studied by the system model is beneficial to improving the work efficiency of the aerobics intelligent fitness system. After the comprehensive human quality of the system model is evaluated, the actual average score of the comprehensive human quality of the 13 users tested before the aerobics intelligent fitness system test is 91.44, and the average prediction score is 90.88. The results of the two tests are similar. Thus, using the intelligent fitness system can enable the user to obtain system feedback according to the actual training effect, thereby playing a guiding role in the intelligent fitness of aerobics for the user. This work designs and implements the aerobics intelligent fitness system close to the human body's training effect, further enhancing the specialization and individualization of sports and fitness.
ABSTRACT
Nattokinase is an alkaline serine protease secreted by natto during fermentation. Despite its good thrombolytic effect, it is intolerant to gastrointestinal conditions and is easily digested and degraded into polypeptides, oligopeptides, and amino acids. However, whether these peptides inhibit fat-digesting enzymes and other biological activities remains unknown. To explore the bioactivity of peptides produced through nattokinase degradation, nattokinase was subjected to simulated digestion in the gastrointestinal tract, and 41 small peptides were obtained through the enzymolysis of gastric enzymes, pancreases, and chymotrypsin. Four pancreatic lipase (PL) inhibitory peptides (SW, ASF, GAY, and PGGTY) were selected based on their activity scores, water solubility, and toxicity predictions. The molecular docking results revealed that hydrogen bonds and electrostatic interactions were the main forces for inhibiting PL activity. The results of enzyme activity verification revealed that all four peptides inhibited PL activity. Among them, GAY exhibited the strongest inhibitory effect, with an inhibitory rate of 10.93 % at a concentration of 1 mg/mL. Molecular dynamics simulations confirmed that the GAY-1ETH complex demonstrated good stability. Natto foods containing nattokinase own the activity of inhibiting fat-digesting enzymes and show antiobesity potentials.
ABSTRACT
Cancer immunotherapy has attracted much attention in recent years because of the ability of immune system to identify tumor cells and limit their growth. Icariin (ICA) is a natural flavonoid glucoside isolated from Epimedium plants and has shown a variety of pharmacological activities such as anti-inflammatory effects, immunological regulation and anticancer potency. Furthermore, it has immunoadjuvant effects on enhancing Th1-immune response, suggesting that ICA may serve as an adjuvant for cancer immunotherapy. In this study, we used P815 mouse mastocytoma tumor model and immunized them with P815AB peptide and/or ICA. Our results demonstrated that ICA could increase the cytotoxic T lymphocytes (CTL) response for P815AB peptide on the tumor-bearing DBA/2J mice. In addition, the percentage of CD4+CD8+/CD3+CD69+/CD69+NKG2D+ positive cells in splenocytes of the tumor-bearing mice all significantly increased after combined immunization with ICA and P815AB peptide. This illustrated that ICA could enhance the immunogenicity of P815AB and improve the ability of T cells and CTLs in recognizing the tumor cells. Moreover, ICA improved the function of peritoneal macrophages with effects of inhibition on tumor growth. Besides, we discussed the possible mechanism of ICA to enhance body immunity by detecting the expression level of MHC-I and related genes in B16-F10 and RMA/S cells. The results suggested that ICA has the potential to up-regulate LMP/TAP related molecules and induce the expression of MHC-I, which increase the immune surveillance and keep cancer in remission. In conclusion, ICA showed an anti-tumor effect both in vitro and in vivo and may be an effective antigen adjuvant for cancer treatment by enhancing tumor-specific immunity.
