Excerpts

This notion is in agreement with our data, where the regression analysis demonstrated a highly significant positive correlation between the galactose content and anti-cancer activity (R 2 = 0.58, p = 0.000 for B16F10 cell adhesion; R 2 = 0.95, p = 0.000 for anchorage-independent growth of HT-29 cells).

The differences between the different parts were highly significant, with p = 0.000.

Compared to the control level, highly significant ( p value = 0.000) increases in the germination percentage of Zea mays were found in the following descending order: U. fasciata. polysacch. 5 mg/mL > U. fasciata. polysacch. 10 mg/mL > U. lactuca. polysacch., 5 mg/mL > U. lactuca. polysacch., 10 mg/mL priming solution agent.

In Figure 2 A, LFX alone has obviously curbed biofilm formation, and except for the sample treated by 1⁄2 × MIC LFX ( p < 0.05, n = 4), the differences in other two cases by 1 × MIC and 2 × MIC LFX are extremely significant ( p = 0.000, n = 4) as compared with control.

In the 7th day ( Figure 1 C × MIC and 2 × MIC SH have exceedingly significant differences ( p = 0.000, n = 4).

The model exhibited excellent discriminative power with a C-index of 0.901, and highly significant statistical results ( p = 1.207 × 10 −48 ).

Because the persistence-length data did not satisfy normality (Shapiro–Wilk p = 0.002), differences between force fields were assessed using a Wilcoxon rank-sum test, which showed a highly significant effect of force field ( p -value ≈ 10 −17 ), whereas no significant differences were detected across chain lengths, suggesting that the persistence length is largely independent of chain length over the range considered.

STRING analysis revealed a highly significant enrichment of protein–protein interactions (PPI enrichment p < 1.0 × 10 −16 ), confirming that the identified proteins are functionally connected rather than randomly associated.

The slope coefficients were highly significant ( p -values < 2.2 × 10 −16 ), confirming a strong linear relationship between er and the IM-MS responses.

Monthly differences were highly significant (Kruskal–Wallis p < 2.2 × 10 −16 ), and this factor exhibited the strongest seasonal component among the three, with a seasonal strength of 33.77%.

In particular, the adjusted R 2 for the two fits in Figures 3A and 4C from [ 6 ], are respectively, 0.97 and 0.25, where F value (160) for the fit comparison is statistically highly significant (P~10 −15 ).

We found a highly significant ( p < 10 −12 ) positive ( R 2 > 0.51) correlation between levels of expression of 2071 transcripts whose expression was affected by both stimuli.

The statistical analysis of antioxidant capacity confirmed significant differences among the tested materials, with ANOVA results ( Table S5, Supplementary Materials ) indicating a highly significant effect (F = 73.01071, p = 1.46 × 10 −8 ).

The outcomes of the study outlined a statistically highly significant negative correlation between the level of education and drug use (Pearson test, R (38) = −0.9282; p < 0.00001).

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).

Additionally, the model reached a highly significant correlation ( p < 0.0001), and the lack of fit of this model is insignificant ( p > 0.05).

The level of significance ( p -value) for each test is indicated in the figures using the following notation: ns ( p > 0.05)—non-significant, * (0.01 < p ≤ 0.05)—significant, ** (0.001 < p ≤ 0.01)—very significant, *** (0.0001 < p ≤ 0.001)—highly significant, and **** ( p ≤ 0.0001)—extremely significant. 5.

In Table 3 , it can be seen that the model is highly significant ( p < 0.0001, f = 62.17), and the lack of fit is not significant ( p > 0.05, f = 1.44).

Statistical analysis confirmed that the differences between the EO and Trolox controls were highly significant ( p < 0.0001) for both methods. 2.5.

In particular, factor C was extremely significant ( p < 0.0001), indicating that the amount of PLA had the main effect on the particle size.

The prevention is highly significant ( p < 0.0001) with BEN extract from the third to the fifth hour.

The similarity between the two groups was also evaluated using PERMANOVA, which showed slightly significant differences between the HCC and control groups: p -value < 0.0001, but the pseudo-F value is low (pseudo-F = 1.43). 2.3.

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.

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).