Statistical analysis confirmed that IC 50 treatment caused a highly significant increase in intracellular ROS generation compared with the untreated control group (0 μg/100 μL; **** p < 0.0001).
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The results indicated that the regression model was highly significant ( F = 116.64, p < 0.0001), while the lack-of-fit term was not significant ( p > 0.05) [ 34 ].
The model was highly significant ( p < 0.0001), while the lack-of-fit term was not significant ( p > 0.05), indicating a good fit and significant main effects.
For VAY, all linear effects (X 1 2 , X 2 2 , X 3 2 ) and interaction terms were highly significant ( p < 0.0001), with the linear term of extraction time (X 1 ) in UAE and the liquid–solid ratio (X 2 ) in WBE displaying particularly significant. 2.2.2.
Table 2 shows that the model is highly significant with a low p -value ( p < 0.0001).
Worsening was highly significant when compared to basal values (BV; p < 0.0001 vs.
24 ppm), and was highly significant ( p < 0.0001).
However, the production of xylanase mainly depends on the moisture level, as the quadratic and linear effects of this factor were highly significant ( p < 0.0001), confirming the single-factor experiment results ( Table 2 ) and the influence in the metabolic rate of the interaction between these two parameters.
The ANOVA results ( Table 1 ) suggest that the model was highly significant with a high F value (F model = 62.16) and a very low probability p -value ( p < 0.0001) [ 21 ].
The regression model was highly significant ( F = 121.05, p < 0.0001), while the lack of fit ( p = 0.97 > 0.05) was insignificant relative to the pure error, indicating a good fit of the regression equation to the experiment.
From the variance analysis, it is shown that the p -value of the regression model is extremely significant ( p < 0.0001).
The regression model is highly significant ( p < 0.0001), but the out-of-fit phase is not significant, with R 2 of 0.9741, indicating that the model fits well and can reasonably predict the taxanes yield within the ranges of the variables [ 33 ].
Statistical analysis confirmed that the differences between the EO and Trolox controls were highly significant ( p < 0.0001) for both methods. 2.5.
The post hoc Tukey’s test shown in Figure 5 provides strong statistical evidence for this cytotoxic effect, particularly at 100 μg/mL, which showed highly significant reductions in cell viability ( p < 0.0001).
Statistical analysis revealed highly significant differences between the control group and both the Recoveron and methanolic propolis extract-treated groups ( p < 0.0001 in both cases).
The results show that the differences between strains, oils and antibiotics were very highly significant p < 0.0001 ( Table 3 ).
The second-order model obtained in terms of coded variables for extraction efficiency ( E (%)) of BB seed oil using UAE is given by Equation (1): (1) E % = 80.74 + 9.375 X 1 − 2.495 X 1 2 + 2.875 X 2 − 3.495 X 2 2 + 0.5 X 3 − 2.745 X 3 2 − 1.25 X 1 X 2 − X 1 X 3 + X 2 X 3 The ANOVA statistic for extraction efficiency (the response variable) proved that the regression model is highly significant, having a very high F-value of 46.67 and a low p -value of p < 0.0001.
6.65 X 2 X 3 − 35.03 X 1 2 − 47.97 X 2 2 − 29.11 X 3 2 Y 2 (TFC) = 58.85 + 5.13 X 1 + 0.27 X 2 − 1.13 X 3 − 0.43 X 1 X 2 + 0.80 X 1 X 3 − 0.39 X 2 X 3 − 4.51 X 1 2 − 2.53 X 2 2 − 1.71 X 3 2 The results of the analysis of variance in Table 2 suggest that the fitted models for TPC and TFC were both highly significant ( p < 0.0001), while the lack of fit was not significant ( p -values: 0.2161 and 0.3343, respectively), indicating a good fitness for the models.
Highly significant differences ( p < 0.0001) were observed among all sample types across all parameters, indicating substantial textural modifications resulting from blend composition.
Highly significant main effects of cell line (F = 428.7, p < 0.0001), ICG concentration (F = 312.4, p < 0.0001), and time after irradiation (F = 189.6, p < 0.0001), a significant line × concentration interaction (F = 67.3, p < 0.0001) confirmed the difference in sensitivity.
The results indicated that the model for 2, 6-DIPA hydrolysis efficiency is highly significant, with an F-value of 50.59 and a p -value < 0.0001.
The prevention is highly significant ( p < 0.0001) with BEN extract from the third to the fifth hour.
Multiple regression analysis of the experimental data yielded the following second-order polynomial equation (Equation (1)), which describes the relationship between the response variable and the independent variables: (1) Oil yield (%) = 33.84 + 0.5783A + 0.8342B + 0.4008C + 0.8633D + 0.5550AB + 0.2425AC + 0.1675AD + 0.6150BC − 0.2725BD + 0.2550CD − 2.08A 2 − 1.31B 2 − 2.09C 2 − 1.32D 2 As shown in Table 3 , the regression model was highly significant ( p < 0.0001), while the lack-of-fit test was not significant ( p > 0.05), indicating that the model is statistically valid and well-fitted to the experimental data.
ANOVA results ( Table 1 ) indicated that the model was highly significant ( p < 0.0001), while the lack-of-fit was not ( p = 0.5908).
The serum IL1α levels were similar for both groups when the comparison was performed using a Tukey’s test ( p = 0.778); however, the linear test for trend indicated a significant trend ( p = 0.0001).