Novel soybean-based high protein bar rich in isoflavones improves insulin sensitivity in diabetic Wistar rats

Effect of red clover isoflavones on hormone, immune, inflammatory, and plasma biochemistry in lactating dairy cows

This study was to conducted to investigate the effect of red clover isoflavones on the health indicated by immune status and blood biochemistry in dairy cows. Sixty-eight healthy Holstein lactating cows were randomly divided into four treatments (n = 17 per treatment) from 5 blocks according to milk yield using a randomized complete block design. No initial differences in parity (2.13 ± 1.21), days in milk (165 ± 21 d), and milk yield (33.93 ± 3.81 kg/d) between groups. Cows were fed the basal diet supplemented with 0, 2, 4, or 8 g/kg red clover extract (RCE) in diet (dry matter based). Feeding, refusal feed weights, and milk yield were recorded three consecutive days in weeks 0, 4, 8, and 12. Blood was collected from the tail vein of the cows on the last day of weeks 4, 8 and 12, 1 h after the morning feeding, and analyzed for hormones, immunoglobulins, inflammatory markers, and markers of liver and kidney activities. The dry matter intake was significantly decreased by 3.7% in the 8 g/kg group (P < 0.05). The fat-corrected milk yield was significantly higher in both of the 2 and 4 g/kg groups (P < 0.01). Plasma estradiol and prolactin showed a quadratic effect with increasing RCE levels, with the highest in the 4 g/kg group (P < 0.05). Plasma tumor necrosis factor (TNF)-α, interleukin (IL)-6, and IL-1β levels decreased linearly with increasing dietary RCE levels. Plasma IL-18 levels showed a quadratic effect with increasing dietary RCE levels, with significantly lower levels in both of the 2 and 4 g/kg groups (P < 0.05). Plasma immunoglobulin A and D-lactic acid levels showed a quadratic effect with increasing dietary RCE levels, with significantly higher level in the 4 g/kg group (P < 0.05). The liver function and kidney activity makers were similar (P > 0.05). These results recommend the supplementation of RCE at a level from 2 to 4 g/kg DM.

Extrusion of casein and whey protein isolate enhances anti-hardening and performance in high-protein nutrition bars

Model high-protein nutrition bars (HPNBs) were formulated by incorporating whey protein isolate (WPI) and casein (CN) at various extrusion temperatures (50, 75, 100, 125, and 150 °C) with a protein content of 45 g per 100 g. The free sulfhydryl groups, amino groups, hardness, and microstructures of HPNBs were analyzed periodically at 37 °C over a storage period of 45 days. Specifically, sulfhydryl group, amino group and surface hydrophobicity of extruded whey protein isolate (WPE) and extruded casein (CE) were significantly reduced (P < 0.05) compared to those of unextruded protein. HPNBs formulated with WPE (HWPE) and CE (HWCE) exhibited a slower hardening rate compared to those formulated with unmodified protein. Moreover, the color difference, hardness and sensory score of HPNBs after 45 days of storage were used as indicators, and the results of the TOPSIS multiple index analysis indicated that HPNB formulated with WPI extruded at 150 °C possessed the best quality characteristics.

Mathematical Modeling and Optimization of Lactobacillus Species Single and Co-Culture Fermentation Processes in Wheat and Soy Dough Mixtures

To improve food production via fermentation with co-cultures of microorganisms (e.g., multiple lactic acid bacteria-LAB strains), one must fully understand their metabolism and interaction patterns in various conditions. For example, LAB can bring added quality to bread by releasing several bioactive compounds when adding soy flour to wheat flour, thus revealing the great potential for functional food development. In the present work, the fermentation of three soy and wheat flour mixtures is studied using single cultures and co-cultures of Lactobacillus plantarum and Lactobacillus casei. Bio-chemical processes often require a significant amount of time to obtain the optimal amount of final product; creating a mathematical model can gain important information and aids in the optimization of the process. Consequently, mathematical modeling is used to optimize the fermentation process by following these LAB’s growth kinetics and viability. The present work uses both multiple regression and artificial neural networks (ANN) to obtain the necessary mathematical model, useful in both prediction and process optimization. The main objective is to find a model with optimal performances, evaluated using an ANOVA test. To validate each obtained model, the simulation results are compared with the experimental data.

Antidiabetic potential of soy protein/peptide: A therapeutic insight

Soybean (Glycine max) harbours high quality proteins which have been evident to exhibit therapeutic properties in alleviating many diseases including but not limited to diabetes and its related metabolic complications. Since diabetes is often manifested with hyperglycemia, impaired energy homeostasis and even low-grade chronic inflammation, plenty of information has raised the suggestion for soy protein supplementation in preventing and controlling these abnormalities. Moreover, clinical intervention studies have established a noteworthy correlation between soy protein intake and lower prevalence of diabetes. Besides soy protein, various soy-derived peptides also have been found to trigger antidiabetic response in different in vitro and in vivo models. Molecular mechanisms underlying the antidiabetic actions of soy protein and peptide have been predicted in many literatures. Results demonstrate that components of soy protein can act in diversified ways and modulate various cell signaling pathways to bring energy homeostasis and to regulate inflammatory parameters associated with diabetic pathophysiology. The main objective of the present review lies in a systemic understanding of antidiabetic role of soy protein and peptide in the context of impaired glucose and lipid metabolism, and inflammation.

Acceptability of peanut candy with different proportions of Kinako soy flour and substitution of sucrose by sucralose

ABSTRACT Objective The aim of this research was to produce new formulations of peanut “paçoca” candy, replacing peanut flour with Kinako flour, and check if the addition of this ingredient bears a negative impact on acceptance. Methods Eight formulations of peanut “paçoca” candy, sweetened with sucrose and sucralose, were prepared with partial and total replacement of peanut flour by Kinako flour. The assessment of the acceptance was carried out by 121 tasters, using the 9cm unstructured hedonic scale. Willingness to purchase the different samples was evaluated by a 5-point scale. In addition, a sociodemographic questionnaire was applied. The results were submitted to ANOVA and Tukey’s test. Results Most of the survey participants stated that they rarely consume soybeans and/or soy derivatives. Regarding acceptance, among the eight formulations analyzed, samples sweetened with sucrose, containing either 100% peanut flour and 50% peanut flour replaced by Kinako flour, did not differ significantly between them (p<0.05) and were the most appreciated by consumers considering the flavor and overall impression attributes. Conclusion The results showed that replacing peanut flour with Kinako flour in peanut “paçoca” candy is feasible and that more sensory studies are needed to add this flour to other foods, to provide the nutritional benefits present in soybean.