Study on potential antigenicity and functional properties of whey protein treated by high hydrostatic pressure based on structural analysis.

High hydrostatic pressure (HHP) is extensively utilized in the field of food processing due to its remarkable ability to preserve the freshness of food. The potential antigenicity of ß-lactoglobulin (ß-LG) in whey protein isolate (WPI, 3%) treated by HHP was detected by enzyme linked immunosorbent assay (ELISA) using monoclonal antibodies. Furthermore, the impact of pressure-induced structural alterations on the emulsification properties and antioxidant activity of WPI was investigated. The findings revealed that pressures exceeding 300 MPa resulted in molecular aggregation, the formation of inter-molecular disulfide bonds, and an increase in surface hydrophobicity (H0). The percentage of ß-sheet decreased along with the pressure. The results showed the increment of α-helix and ß-turn with pressure. ELISA demonstrated a significant reduction in the antigenicity of ß-LG following HHP treatment (100-600 MPa), with a slight recovery observed at 300 MPa. These spatial structural modifications led to the unfolding of the ß-LG molecule, thereby enhancing its digestibility. Moreover, HHP treatment substantially improved the antioxidant properties, with the exposure to hydrophobic amino acids contributing to increased antioxidant properties and emulsion stability.

The Empirical Analysis of Bitcoin Price Prediction Based on Deep Learning Integration Method.

As a new type of electronic currency, bitcoin is more and more recognized and sought after by people, but its price fluctuation is more intense, the market has certain risks, and the price is difficult to be accurately predicted. The main purpose of this study is to use a deep learning integration method (SDAE-B) to predict the price of bitcoin. This method combines two technologies: one is an advanced deep neural network model, which is called stacking denoising autoencoders (SDAE). The SDAE method is used to simulate the nonlinear complex relationship between the bitcoin price and its influencing factors. The other is a powerful integration method called bootstrap aggregation (Bagging), which generates multiple datasets for training a set of basic models (SDAES). In the empirical study, this study compares the price sequence of bitcoin and selects the block size, hash rate, mining difficulty, number of transactions, market capitalization, Baidu and Google search volume, gold price, dollar index, and relevant major events as exogenous variables uses SDAE-B method to compare the price of bitcoin for prediction and uses the traditional machine learning method LSSVM and BP to compare the price of bitcoin for prediction. The prediction results are as follows: the MAPE of the SDAE-B prediction price is 0.016, the RMSE is 131.643, and the DA is 0.817. Compared with the other two methods, it has higher accuracy and lower error, and can well track the randomness and nonlinear characteristics of bitcoin price.

Vanillic Acid as a Promising Xanthine Oxidase Inhibitor: Extraction from Amomum villosum Lour and Biocompatibility Improvement via Extract Nanoemulsion.

Gout is an oxidative stress-related disease. Food-derived vanillic acid, a promising xanthine oxidase inhibitor, could potentially be used as a safe, supportive, and therapeutic product for gout. The extraction of vanillic acid from a classic Chinese herbal plant Amomum villosum with ethanol was investigated in the study. The optimum conditions were determined as extraction time of 74 min, extraction temperature of 48.36 °C, and a solid-to-liquid ratio of 1:35 g·mL-1 using the Box-Behnken design (BBD) of response surface methodology (RSM). The experimental extraction yield of 9.276 mg·g-1 matched with the theoretical value of 9.272 ± 0.011 mg·g-1 predicted by the model. The vanillic acid in Amomum villosum was determined to be 0.5450 mg·g-1 by high-performance liquid chromatography-diode array detection (HPLC-DAD) under the optimum extraction conditions and exhibited xanthine oxidase (XO) inhibitory activity, with the half-maximal inhibitory concentration (IC50) of 1.762 mg·mL-1. The nanoemulsion of Amomum villosum extract consists of 49.97% distilled water, 35.09% Smix (mixture of tween 80 and 95% ethanol with 2:1 ratio), and 14.94% n-octanol, with a particle size of 110.3 ± 1.9 nm. The nanoemulsion of Amomum villosum extract exhibited markable XO inhibitory activity, with an inhibition rate of 58.71%. The result demonstrated the potential benefit of Amomum villosum as an important dietary source of xanthine oxidase inhibitors for gout.