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Molecules 2019, 24, 1388 3 of 14 2. Results and Discussion 2.1. Optimization of the Cur-CS/Alg NP Formulation The use of response surface methodology (RSM) is an effective approach in the optimization of the Cur-CS/Alg NP formulation [20,22]. In this study, a Box-Behnken statistical design (BBD) was employed to identify the optimum curcumin concentrations (X1) and Tween® 80 (X2) and the CS/Alg mass ratio (X3) that would result in a Cur-CS/Alg NP formulation with a particle size and zeta potential within the desirable range and a maximal encapsulation efficiency (EE) and loading capacity (LC). The observed responses of the Cur-CS/Alg NP formulation at different levels of the factors are shown in Table 1, where the three dependent values ranged from 199 to 1120 nm for particle size (Y1), −30.8 mV to −10.8 mV for zeta potential (Y2), 45.7% to 54.5% for the EE (Y3), and 4.0% to 27.4% for the LC (Y4). Table 1. Factors and observed responses in the Box-Behnken statistical design for optimization of the Cur-CS/Alg NP formulation. Run Factor Response X1 X2 X3 Y1 Y2 Y3 Y4 (mg/mL) (% w/v) 0.5 0.5 2 2 1 1 1 1 0.5 2 0.5 2 1 1 1 (nm) 282 ± 63 263 ± 57 330 ± 14 294 ± 46 295 ± 61 281 ± 34 984 ± 80 1120 ±8 4 267 ± 52 199 ± 37 899 ± 6 992 ± 180 255 ± 88 245 ± 102 287 ± 37 (mV) −22.3 ± 5.7 −24.3 ± 1.8 −22.1 ± 4.4 −20.6 ± 2.2 −11.4 ± 2.5 −10.8 ± 5.2 −27.4 ± 1.4 −28.4 ± 1.6 −14.3 ± 1.1 −13.5 ± 6.0 −30.8 ± 1.4 −25.4 ± 1.6 −25.0 ± 2.2 −22.4 ± 1.0 −21.8 ± 0.8 (%) 46.9 ± 0.2 49.0 ± 0.6 45.7 ± 0.2 48.8 ± 0.3 48.4 ± 0.2 54.5 ± 1.6 48.9 ± 0.1 48.2 ± 0.4 49.2 ± 0.8 49.5 ± 1.5 46.9 ± 0.6 46.0 ± 0.2 48.8 ± 0.3 49.2 ± 0.9 47.8 ± 1.1 (%) 7.1 ± 1.6 24.0 ± 1.3 4.7 ± 1.8 14.6 ± 1.0 9.9 ± 5.9 27.4 ± 9.6 4.0 ± 0.7 12.5 ± 2.9 10.9 ± 3.7 18.1 ± 4.1 7.6 ± 3.4 6.0 ± 2.2 11.9 ± 5.1 12.3 ± 5.4 11.8 ± 4.3 1 0.5 2 1.5 3 0.5 4 1.5 5 0.5 6 1.5 7 0.5 8 1.5 9 1 10 1 11 1 12 1 13 1 14 1 15 1 0.1:1 0.1:1 0.1:1 0.1:1 0.05:1 0.05:1 0.2:1 0.2:1 0.05:1 0.05:1 0.2:1 0.2:1 0.1:1 0.1:1 0.1:1 Regression analysis was performed using the Design Expert® software to simultaneously fit the responses obtained from all 15 formulations into linear, interaction, and quadratic models. Table 2 summarizes the sequential model sum of squares, lack of fit, and model summary statistics obtained from the regression analysis. Table 2. Summary of the results of the regression analysis of the responses. Response Y1 (Particle size) Y2 (Zeta potential) Y3 (EE) Y4 (LC) Model Linear 2FI Quadratic Linear 2FI Quadratic Linear 2FI Quadratic Linear 2FI Quadratic Sequential Lack of Fit p-Value p-Value <0.0001 0.0198 0.9273 0.0140 0.0004 0.2076 0.0005 0.2065 0.8404 0.1569 0.0030 0.8698 0.0520 0.1363 0.2574 0.1471 0.0082 0.6047 0.0002 0.0063 0.3127 0.0064 0.6684 0.0042 Adjusted R2 0.8251 0.7723 0.9882 0.7263 0.6591 0.9594 0.3517 0.4471 0.9010 0.7726 0.7948 0.7534 Predicted R2 0.7453 0.4327 0.9236 0.5988 0.1750 0.9002 −0.0626 −0.7347 0.6598 0.6473 0.4137 −0.9670 Remark Suggested Suggested Suggested SuggestedPDF Image | Synergistic Effects of Photo-Irradiation and Curcumin-Chitosan
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