Excerpts

Intraoperative Risk Factors for Death Prolonged operation and CPB times were highly significant predictors of early mortality on univariable logistic regression analysis ( P <0.0001) and the entire surgery time remained significantly correlated with mortality in the multivariate analysis ( P <0.008) ( Tables 3 and 4 ).

The Pearson correlation coefficient between both parameters was 0.988, a highly significant ( P < 0.0001) positive relationship.

The Mann–Whitney U test indicated a highly significant difference ( p < 0.0001).

In particular, compared with the level observed at 0 d, the expression of BfmRS (eightfold), lepB (eightfold) and esp (17-fold) reached extremely significant levels at 5 days ( t = 10.64, df = 8, p = 0.0001), 3 days ( t = 25.63, df = 8, p < 0.0001) and 7 days ( t = 5.120, df = 8, p = 0.0009), respectively.

We found the height‐wind interaction parameter was strong and highly significant ( P < 0.0001) (Fig. 3A , Table S3 ).

All these final selected variables showed a highly significant negative relationship with the infection rate (p < 0.0001; Tmin r = − 0.25, AP r = − 0.23, RH r = − 0.21).

This model was highly significant (p<10 −4 ) and explained 7.5% of the variation in African ancestry levels between individuals (adjusted R 2 ).

putrida , P -value < 0.0001; all pairwise tests with element E were highly significant with a P -value < 0.0001, while no other pairs had P < 0.01).

Publication bias A highly significant publication bias was observed using both Egger’s test (t = 4.71, p < 0.0001) and Begg’s test (t = 7.70, p < 0.0001) ( Fig. 4 A & B).

In the Kruskal–Wallis analysis, the Ma QTL was supported with a highly significant (P < 0.0001) value of the K statistic, 15.9 for malic acid content.

Although the above particle size difference was insignificant ( P > 0.07; n = 6), the mean zeta potential difference was highly significant ( P < 0.0001; n = 6).

Despite its simplicity, our model was highly significant (P<0.0001) and explained 24% of the variation in the occurrence of stop codons among introns.

The analysis of variance confirms that the model is highly significant as is evident from Fisher’s F -test (104.99) and a very low P -value < 0.0001.

Interestingly, we observed a highly significant reduction in P2X3-labeled nerve fibers within the total fungiform papilla area ( Fig. 4 A and C ; 29.0% reduction; P < 0.0001).

The analysis of variance (one-way ANOVA) detected highly significant differences among RILs for all traits in each environment ( p < 0.0001, Appendix C ), which indicates that genetic factors explain a large fraction of the observed phenotypic variability.

Consistent with the target data, the effect of generation rate on CS1 was highly significant in all four simulations, with a very large effect size [Simulation 1A: F (5, 94.47) = 82.43, p < 0.0001, η 2 = 0.64; Simulation 1B: F (5, 96.54) = 65.16, p < 0.0001, η 2 = 0.71; Simulation 2A: F (5, 95.53) = 74.62, p < 0.0001, η 2 = 0.65; Simulation 2B: F (5, 97.278) = 29.85, p < 0.0001, η 2 = 0.54].

In pan-cancers, GPR18 mRNA expression levels demonstrated extremely significant Pearson correlations (Pearson R values) with MS4A1 and TIL-B levels across all 29 cancer types, except for DLBC and UVM ( R > 0.2, P < 0.0001; Fig. 4b , Supplementary Fig. 4 ).

This difference was highly significant ( p < 0.0001), indicating a significant enhancement in urinary function and overall quality of life in patients in the treatment group.

To check this we performed real-time RT-PCR on patient lymphoblastoid RNA and observed a highly significant drop of >75% in CARMIL2 expression levels for the F1 proband versus healthy controls ( p < 0.0001).

Moreover, a highly significant positive correlation was found between miR-424 and each of miR-199a, miR-183, and miR-224 (rho = 0.555, 0.364, and 0.359, respectively, p < 0.0001), and between miR-215 with miR-217 (0.529, p < 0.0001), in addition to the correlation between miR-199a and miR224 (rho = 0.515, p < 0.0001), and between miR-183 and miR-215 (rho = 0.361, p < 0.0001).

The log-rank test indicated highly significant differences in lifespan between control and mutant lines (p < 0.0001).

Whereas all the other groups showed a decreasing trend in comparison to the diabetic group with adjusted ( p < 0.0001****).

A highly significant Spearman’s correlation coefficient (r ≥ 0.91, p < 0.0001) was observed between the response to OVX836 NP and various heterologous influenza A strain NPs (including H5N1) in both age groups.

As a caveat, all nominally significant results were not retained after the Bonferroni correction for multiple comparisons ( p < 0.0001).

This analysis showed an increasing trend for TPs using the filgrastim biosimilar (from 34.4% in July 2015 to 49.8% in June 2016; p < 0.0001) compared with a decreasing trend for TPs using lenograstim (from 22.6% in July 2015 to 12.3% in June 2016; p < 0.0001) and pegfilgrastim (from 26.8% in July 2015 to 20.6% in June 2016; p < 0.0001).