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For clinical data, mean change from baseline was determined for each time point and expressed asmean ± SEM for each treatment group. Total area under the curve (AUC) was calculated using the trapezoidal rule and treatment groups were compared by Student’s t-test. Additionally, for each time point, treatment groups were compared by ANOVA followed by Tukey’s Test. For all analyses, the p value < 0.05 was considered significant. Confounding factors, such as general compliance and compliance due to timing (i.e., overlap of the Christmas period) were factored into calculations where appropriate. The General Estimating Equation (GEE) analysis was also used where appropriate and is referenced in the text. Graphs were generated using Prism (Version 8.0, GraphPad Software) and the “ggplot2” R package [43]. 3. Results 3.1. Bioactivity Screening and Rice NPN Characteristics To explore the latent anti-inflammatory bioactivity within the rice proteome, a hydrolysate was generated and screened for bioactivity. The anti-inflammatory properties of the rice NPN were assessed in vitro in the human THP-1 macrophage cell line. Specifically, di ff erentiated THP-1 macrophages were treated with increasing concentrations of rice NPN for 24 h, before an inflammatory response was induced by further treatment of cells with the bacterial endotoxin LPS. In this model, the concentration of TNF- α secretion was used to quantify the inflammatory response. In Figure 1 we show that, at both test concentrations, treatment with rice NPN resulted in a statistically highly significant ( p < 0.001) reduction in TNF- α secretion compared to the untreated control. While a dose response was not attained by increasing the concentration of rice NPN, we do observe equivalent e ffi cacy (50% reduction versus untreated) at both 0.5 and 5 µ g / mL, which may be indicative of a saturation e ff ect (Figure 2a), importantly, rice NPN did not a ff ect cell viability (up to 500 µ g / mL; Figure S1). The rice NPN performed better than a known natural anti-inflammatory ingredient that was used as a positive control and comparator, namely DHA [39]. In Figure 2, we present the physicochemical characteristics of our rice NPN. Here, we see that in terms of peptide length the highest individual frequency observed for the rice NPN is 5 amino acids (AA), however, cumulatively most rice NPN peptides fall within the 10–15 amino acid size range (Figure 2a). Overall, rice NPN peptides feature a global charge range from − 4 to 2, where a net neutral charge (0) occurs with the highest frequency (Figure 2b). Finally, in Figure 2c, we see that the majority of peptides within the rice NPN are comprised of approximately 20%–40% hydrophobic residues. Foods 2020 , 9 , x FOR PEER REVIEW 8 of 20
Figure 1. Effect of rice natural peptide network (NPN) on lipopolysaccharides ( LPS)-induced TNF- α secretion from differentiated THP-1 macrophages . THP-1 macrophages were treated with rice NPN (0.5 and 5 μ g/mL) for 24 h before treating with 100 ng/mL of LPS for 24 h. The secretion of TNF- α was quantified by ELISA. Data presented are the mean ± SEM of at least 3 independent experiments (* p <0.05, *** p < 0.001). Figure1. E ff ect of rice natural peptide network (NPN) on lipopolysaccharides (LPS)-induced TNF- α secretion from di ff erentiated THP-1 macrophages. THP-1 macrophages were treated with rice NPN (0.5 and 5 µ g / mL) for 24 h before treating with 100 ng / mL of LPS for 24 h. The secretion of TNF- α was quantified by ELISA. Data presented are the mean ± SEM of at least 3 independent experiments (* p < 0.05, *** p < 0.001).
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