Excerpts

From the GWAS for each trait, we first selected SNPs that were significant ( P < 0.05, marker-wise) in at least three of the five environments, with at least one environment with highly significant differences ( P < 0.01).

If a significant trend was detected at p ≤ 0.01, Williams’ test was used [ 21 ]; if the trend was not significant Dunnett’s test was used [ 22 ].

For all of the traits, the variations due to genotypes under this study were enormously significant (p<0.01).

There was a highly significant correlation ( p < 0.01) between the processing speed estimate C and retirement status (Retired).

Furthermore, the ginger-treated groups showed a highly significant (p < 0.01) increase in HDL-cholesterol (HDL-C) and a high decrease (<0.01) in LDL-cholesterol and VLDL-cholesterol compared with the control group.

Except for SB216763 and XAV939 in A2780cis, these findings were highly significant ( p < 0.01 or p < 0.001) at the selected concentrations of 100 μM SB216763, 50 μM XAV939 and 50 nM triptolide (Fig. 3 b).

It dropped by 62% of the original in 8 days which was highly significant (Student's t test, p<0.01).This confirmed that the v-ATPaseA targeting dsRNA expressed in transgenic plants, interrupted transcription of the target gene in the insect and caused mortality.

However, no matter what level of significance is used, we found an increased mortality rate in the patients shifted from ICU to PACU (group III-b) and there is a clear trend that the difference between these patients and the patients from groups I ( P = 0.01), II ( P = 0.01) and III-a ( P = 0.02) can be considered significant.

The reduction in CST from baseline to mo3 was highly significant ( p < 0.01).

Sodium valproate (400 mg/kg) increased the latency to 142.50 ± 5.65 s which was highly significant ( P < 0.01) when compared to control.

Two groups were compared using Tukey’s procedure; differences were deemed statistically significant if * P < 0.05 and highly significant if ** P < 0.01.

In this study, the groups were considered to be significantly different if P < 0.05 and extremely significant if P < 0.01.

A highly significant difference in the Ace index ( p < 0.01) and a significant difference in the Chao1 index ( p < 0.05) were observed between the H2 and H3 habitats.

In the BF group, daily feed intake showed an extremely significant positive correlation with TAN ( p < 0.01), except for days 21–36.

In the genus-level heatmap ( Figure 4B ), marked by red boxes, Haemophilus and Fusobacterium exhibited high abundance (red) in the non-tumor group (S.N, bottom row) but were significantly decreased (blue) in the lung cancer group (S.L, top row), with statistical tests showing highly significant differences ( P < 0.01, dark red diamonds).

Those differences are highly significant (χ 2 = 19.77, df = 7, p < 0.01).

The difference between age groups was highly significant for the kidneys ( p ≤ 0.01) and significant for the liver ( p ≤ 0.05).

The difference between superior and inferior hemispheres in all subjects were statistically significant in the glaucoma patient group in all 11 sectors ( t -test, p < 0.001), partially significant in 5 / 11 ( t -test, p < 0.01), and no statistical difference in most sectors of the normal group (1 / 11 sectors was significant, t -test, p < 0.9).

Differences were considered statistically significant with * P < 0.05 and highly significant with ** P < 0.01.

GSH is distinguished by slightly higher concentrations in the samples from the pond; the difference between the batch grown in natural conditions and the one in the RAS is, however, slightly significant according to Šídák’s multiple comparisons test ( p < 0.01) in the liver and intestine ( Figure 1 D).

There was a significant positive correlation between unclassified Erysipelotrichaceae and ADG ( P < 0.05), a highly significant negative correlation between Clostridium sensu stricto 1 and ADFI ( P < 0.01), and a significant negative correlation between Romboutsia and ADFI ( P < 0.05).

Interactive Effects of Nitrogen Levels and Growth Stages on Rhizome and Tiller Bud Density of Kentucky Bluegrass Nitrogen addition, phenological stage, and their interaction had highly significant effects on the rhizome bud density, tiller bud density, and total belowground bud density of Kentucky bluegrass ( Figure 2 a–c) ( p < 0.01).

It was shown in Table 3 that the regression model was highly significant (P < 0.01), and the linear relationship between the dependent variable and examined variable was significant (R2=0.9898).

The difference in three categories of functional genes was extremely significant among the following groups ( Figure S2 ) ( P < 0.01).

In general, habitats of different exposures and depths showed distinct and highly significant differences in current velocities (Kruskall-Wallis ANOVA, H 8 = 3499.93, p<0.01, N = 7190).