“highly significant”

The differences were considered to be statistically significant when p < 0.05 and highly significant when p < 0.01 or p < 0.001.

Among them, the turquoise module was significantly positively correlated with C20.3N6 ( P < 0.05) and negatively correlated with C22:6N3 ( P < 0.05), the blue module was significantly positively correlated with C17:1 T, C18:1N9T, C20:2 ( P < 0.05) and highly significant positively correlated with C20:3N6 ( P < 0.01), the brown module was significantly positively correlated with C17:0, C18:3N6 ( P < 0.05) and highly significant positively correlated with C18:1N12, C18:1N7, C18:1N9C, C20:1, SFA, MUFA ( P < 0.01).

the degree of decrease or increase, in the observation group were significantly greater than those in the control group, and this difference was highly significant statistically ( P < .01) (see Table 4 ). 3.4.

Similarly, YC in the EF group surpassed that in the LF group during both the early and late laying periods; however, the difference was only highly significant during the early laying period ( P < 0.01), with no significant difference observed in the late laying period ( P >0.05).

The present study analyzed the data were statistically highly significant ( p > .01) among different treatment groups (Table 3 ). 3.4.

For fiber diameter, marker density panel had significant effect on accuracy of GEBV ( P < 0.05 ), other factors in this study had highly significant effect on accuracy of GEBV ( P < 0.01 ).

There was a statistically highly significant difference seen between the S-ALP values between the test and control group (p<0.01) with higher values in the test group (Table 1 ).

2 C, AKR1B1 overexpression significantly enhanced proliferation compared with the pCDH control, with differences becoming evident at 72 h ( p < 0.05) and highly significant by 120 h ( p < 0.01).

The correlation between Cu and Cr was not significant but positive, while Cr and Pb have a highly significant correlation (P < 0.01).

Phytoplankton Community Structure About Environmental Factors Table 8 indicates that diversity index ( H’ ) and richness ( D ) exhibited a highly significant positive correlation with salinity ( p < 0.01) and a highly significant negative correlation with water temperature, nitrate nitrogen content, nitrite nitrogen content, and ammonia nitrogen content, respectively ( p < 0.01); the evenness ( J ) demonstrated a completely contrary relationship to H’ and D .

Additionally, age had a highly significant effect on all amino acids except Gly and Pro ( P < 0.01).

The difference among the three groups was statistically highly significant ( P < 0.01).

If 7 evaluators indicated correctly, the data was considered highly significant ( p < 0.01).

The reduction of nasopharyngeal viral load between control and treated animals was also highly significant at day 4 post-challenge ( p < 0.01 for IV and p < 0.001 for nebulized).

The linear term D, and the quadratic terms A 2 , B 2 , C 2 , and D 2 , showed highly significant effects ( p < 0.01).

Results were considered statistically significant for P < 0.05 and highly significant for P < 0.01.

As shown in Table 4 , the model was highly significant ( p < 0.01), and the lack‐of‐fit term was not significant ( p > 0.05).

The test for heterogeneity was highly significant, with p <0.01 for both abuse types and neglect.

Notably, there were no significant differences ( P >0.05) between any two consecutive measurements in L693, whereas changes in L661 were highly significant ( P <0.01) (Fig. 7a ).

The PCA loadings showed, along PC2, a close association between roughness and elasticity, which reflects the highly significant correlation coefficient ( r = 0.44, p < 0.01).

p values were considered significant at p < 0.05 and highly significant at p < 0.01.

All studies in this re-analysis, showed a highly significant main effect of the group factor (with at least p < 0.01) at standard Anovas.

Specifically, Acidobacteria showed a highly significant positive correlation with available phosphorus ( P < 0.01) and available potassium ( P < 0.05).

When analyzing the correlation between OX-40 IHC levels and mRNA expression of immune-related genes, we found the following markers of immune inflammation to have a highly significant positive association ( p ≤ 0.01): CD3, CD8, IFN-gamma, ICOS, CXCL9, CXCL10, CCL5, and granzyme K (Fig. 3 ).

This effect is reinforced by the highly significant effect of congruency ( F 1,5 = 44.4, P < 0.01).