Excerpts

As for senior authorship, the difference between men and women was highly significant in both the 1999 (166 vs. 47, p = 2e-16), and in the 2009 cohort (188 vs. 115, p = 3e-5), but inspection of the absolute difference reveals that this difference is diminishing.

In the reference model (model 1), the effect of acid exposure was found to be significant and negatively associated with mobility (estimate = − 0.21, p = 0.001), while the observational time also showed a highly significant negative effect (estimate = − 0.24, p < 2 × 10 −16 ).

The microbial alpha diversity was significantly increased in gastric tumor compared with non-tumor tissues in three datasets P1, P3, and P4, with the exception of P2 which showed an opposite trend ( Figure S3A ), while the remaining datasets showed non-significant differences, resulting in a highly significant global Analysis of Variance (ANOVA; F -statistics: P < 2E−16) but a non-significant overall pairwise comparison ( P = 0.19).

Specifically, adjusting for African ancestry in a multiple regression model largely eliminated the highly significant effect of Black ethnicity on serum creatinine levels (decreased from P<2x10 -16 to a marginally significant P=0.05) whilst the highly significant effect of African ancestry on creatinine remained essentially unchanged when adjusted for Black ethnicity (P<2x10 -16 before and after adjustment).

Finally, LASSO analysis was not adjusted for age due to its high correlation with diagnosis (Pearson r = 0.74) and strong potential for solely predicting diagnosis, indicating a highly significant association (logistic regression estimate = 0.225, p < 2e‐16, Akaike information criterion [AIC] = 124,231).

However, the overlap between these two very different approaches is highly significant (Fisher's exact test, p < 2 × 10 −16 ), and the functional enrichments they identify are similar (see below).

8(B) ] by the end of D6, which was highly significant (χ 2 = 70.3, df = 1, P = 2.0E −16 , n = 32).

We found highly significant differences ( p < 2 e - 16 ) between most cluster pairs at K = 5, except clusters 2 and 5 ( p ≈ 1 ) and clusters 2 and 3 ( p = 1.2 e - 09 ).

Statistical analysis via disk diffusion assays revealed highly significant differences in inhibition zone diameters among microorganisms ( p < 2 × 10 −16 ).

t-PGCS DNMs and likely post-zygotic DNMs) we first fit a simple Poisson regression model that calculated the effect of paternal age on total autosomal DNM counts in the R statistical language (v3.5.1) as follows: glm(autosomal_dnms ~ dad_age, family = poisson(link='identity’)) This model returned a highly significant effect of paternal age on total DNM counts (1.72 DNMs per year of paternal age, p<2e-16), but was agnostic to the family from which each third-generation individual was ‘sampled.’ Importantly, a number of third-generation individuals in the CEPH/Utah cohort share grandparents, and may therefore be considered members of the same family, despite having unique second-generation parents ( Figure 3—figure supplement 1 ).

As predicted, αsyn-O treatment generated an increase in the number of editing sites in all cultures (15.8% in astrocyte-only, 26.2% in neuron-only, and 11.1% in astro-neuronal cultures), which was highly significant (chi-squared P value < 2 × 10 −16 for increased exonic proportion in all cases).

It behaved as a complete outlier, reducing the amount of DLK1 ~ 3-fold when compared to the average of the two negative controls, and this effect was highly significant (p = 2 × 10 -16 ) (Figure 1 B and see Additional file 2 : Table S2).

The dispersion parameter is clearly significant ( φ ˆ = 9.26 ; p<2e-16), indicating that there is strong evidence of overdispersion in the data that needs to be captured.

The analysis of variance (ANOVA) results (Supplementary Data 1 –Table B 3 ) showed a highly significant effect of landmarks on measurement variance ( p -value < 2 × 10 −16 ); however, no significant effect of the operator ( p -value = 1.00) or the interaction between landmark and operator was observed ( p -value = 0.968).

The models (for each plate and for each type of error) explained between 14.32% and 37.38% of the error distribution and were highly significant (P < 2 × 10 -16 ).

We observed that the A/I ratio was highly significant and associated with improved outcome (A/I ratio: HR = 0.77, P < 2x10 -16 ), while the total TIL score was associated with poorer outcome (TIL HR = 1.03, P = 0.0137).

The association between miR-100 and EMT markers was further validated in human tumors: from the Cancer Genome Atlas (TCGA) breast cancer data [17] , we observed a moderate but significant inverse correlation between miR-100 and E-cadherin expression levels ( Rs = −0.1, P = 0.006, Figure 1F ) and a highly significant positive correlation between miR-100 and vimentin expression levels ( Rs = 0.43, P <2×10 −16 , Figure 1G ). miR-100 suppresses tumor growth and is downregulated in human breast cancer We performed TCGA data analysis to determine the expression levels of miR-100 and miR-22 in human breast cancer.

We note that this overlap was highly significant ( Figure 2b , Fisher test P <2×10 −16 ), suggesting that age and tumor presence elicit common changes in the DNAm pattern of peripheral blood.

Smooth terms for latitude and longitude were highly significant (p < 2 × 10−16), further confirming the spatial structure of life expectancy outcomes.

We found the effect of rurality to be highly significant ( P < 2.0 × 10 -16 ), but it explains only 28% of the overall variation in log positional error magnitude.

The enrichment of TEs at species-specific binding sites were highly significant both with a chi-square test (Hs χ 2 = 142.8, Mm χ 2 = 131.4, both p < 2e −16 ) and with permutation tests (n = 10,000, p < 1e −5 ) ( Fig 5A ).

Highly significant associations (log-rank test, P < 2 × 10 –16 ) for all three variables were observed, in the whole series and in the two subsets (Fig. 1 ).

The results revealed that genotypic differences were highly significant (F = 15.97, p < 2e–16), indicating substantial variation among genotypes for the trait under study.

This was found to be a highly significant over-representation by goseq (Bonferroni adjusted p -value < 2 × 10 –16 , see Figure 2A and Supplementary Data File 2 ).

The genotype×broomrape race interaction was highly significant for TotAD ( F =3.17, P =2e-16), HeaAD ( F =2.96, P =2e-16), and NecAD ( F =3.63, P <2e-16) ( Supplementary Table S3 ).