“highly significant”

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).

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.

The linear regression was highly significant ( R 2 = 0.73, P -value ≤ 2 × 10 −16 ), with a coefficient (which translates to the -gamma value) of −0.75.

Evolutionary niche shift in response to the mean salinity The mean salinity experienced during evolution had a highly significant effect on acclimated tolerance surfaces ( P < 2 × 10 –16 , likelihood‐ratio test—hereafter LRT—between models with vs. without effects of salinity mean).

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 ).

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).

Notably, despite the absence of a significant indirect effect through AIP, TG exhibited a highly significant total effect on gout, driven by a strong direct effect independent of the AIP pathway (ADE = 0.1013, p < 2 × 10 −16 ) (Fig. 2 G, H, I, J) (File S1 : Table S13 – S17 ).

The highly significant (β = 2.02, z = 45.64, p < 2 × 10 −16 ) intercept, the model estimate of around 8 roadkill, shows a strong baseline effect for predictors at their reference values.

The intercept had an estimated coefficient of 0.8443, which is highly significant (p < 2e-16), indicating a strong positive relationship between the dependent variable and the constant term.

The total effect of the overall model did not quite pass our significance threshold of alpha <0.05 (total effect, p = 0.064), but we saw a significant average direct effect (ADE) of BMF on eGFR (ADE = −4.458, p = 0.012) and a highly significant average causal mediation effect (ACME) of BMF via 3-IS on eGFR (ACME = 1.343, p < 2E−16; Figure 7 B).

This leads to a highly significant coefficient ( β ˆ = 4.68 ; p<2e-16).

The correlation between CpG O/E and gene length is highly significant (Spearman’s r = 0.47, 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).

In parallel, a linear model assessing the direct association between mean relative abundance and response demonstrated a highly significant positive effect (estimate = 0.30, P < 2.0e−16), with dataset terms again showing no significant influence (all P > 0.05), underscoring the robustness of abundance-based signals across cohorts.

Immune gene expression differs by tissue The overall effect of tissue (gut versus whole body) on gene expression was highly significant (MANOVA, F 1,89 = 31.34, p < 2 × 10 −16 ).

There was a highly significant difference between the sensitivity groups ( p < 2e−16) but not between P. cactorum isolates ( p = 0.2046; Table S6 ).

Interestingly, in all tumors FOXP3 expression is highly significant, positively associated to GZMB expression levels ( p -value = 2.0E-16) Adaptive immune response strongly depends on the B cell response.

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).

This difference in wing length was highly significant (t = −57.479, p < 2e-16).

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 ).

The analysis of variance showed a highly significant effect of genotypes ( p < 2 × 10 −16 ) (Table S4 ).

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.

Data analysis showed a highly significant reduction of the average CpG methylation levels from 13.8% in control animals to 8.3% in KD samples over sixteen million mapped CpGs ( p < 2e-16, Wilcoxon rank sum test; Fig. 4a ).

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 ).