Excerpts

The χ 2 testing of the frequencies of ABVIs in individuals with TB as the cause of death and individuals with NTB causes of death revealed a statistically extremely significant difference between the two groups (χ 2 = 18.357, df = 1, P<0.0001).

The logistic regression model was highly significant (p < 0.0001, Nagelkerke R2 = 0.35).

The coefficients for an unassigned genus of Bacteriaceae and for the genera Blautia , Dorea , Clostridium , Fusobacterium , Oscillospira , Phascolarctobacterium , Slackia and Streptococcus were highly significant (P<0.0001, S6 Table ).

As a cross-check, calculated (via DIC and TA) and directly measured pH values were compared and showed a highly significant correlation and no outliers (pH (total scale) = 0.9176 pH (NBS) +0.5453; r 2 = 0.99; p<0.0001).

The difference between circulating cfMTB-DNA amount quantified in the ‘Possible’ ATB group versus combined group of ‘Definite and Probable’ ATB was highly significant (p < 0.0001).

The meta-regression of the year over logit-transformed prevalence showed a trend towards an increasing prevalence of beta-blocker use from 1995 to 2015 with a slope of 0.1 (p<0.0001).

The cumulative GDD term is highly significant ( t = 74.77, df = 623, P < 0.0001).

5.7%); therefore, this ~2.5 fold enrichment was highly significant (P < 0.0001, hypergeometric distribution).

The association between up-regulation of CYP17A1 mRNA expression and DDTs concentration in sampled livers was highly significant (p < 0.0001).

Highly significant differences can be witnessed in these two sub-topics between GRI 401 (M = 0.006, SD = 0.003, p <0.0001****), GRI 402 (M = 0.005, SD = 0.003, p <0.0001****), GRI 404 (M = 0.004, SD = 0.002, p <0.0001****), GRI 405 (M = 0.016, SD = 0.008, p <0.0001****), GRI 407 (M = 0.005, SD = 0.003, p <0.0001****)

teguina ( n = 24), the effect of body mass on dominant frequency was marginal ( F 1,23 4.7, P = 0.04), but highly significant for minimum frequency ( F 1,23 37.1, P <0.0001) and maximum frequency ( F 1,23 16.3, P = 0.0006).

However, there was a highly significant intra-subject correlation between pre- and post-treatment irisin concentrations (R = 0.82, P<0.0001).

This difference was highly significant (p-value < 0.0001).

Adding calcium was associated with a highly significant reduction in SLS prevalence from about 60% without supplemented calcium to 15% in high and medium calcium-supplemented treatments (P < 0.0001, Fig 2 , Table 1 ).

This difference was highly significant using a paired t-test with data points paired by year (P<0.0001, df = 11).

Pair-wise permutation tests comparing predicted species richness between the entire small mammal assemblage, native species forest assemblage, and forest-specialist assemblage for the Atlantic Forest of Paraguay were highly significant ( P < 0.0001; Fig 2 ).

This analysis confirmed the highly significant effect of Hearing-loss [F(1,38) = 30.1, p < 0.0001, ω 2 = 0.43].

The difference between the TRAP-N/CSP-RT (comb) (10/10) and TRAP-N/CSP-T (comb) (0/10) groups was highly significant (p<0.0001, Fisher’s exact test).

= 21.5) was highly significant with t(116) = 5.5, p < 0.0001.

This difference was highly significant, t(70.14) = 4.04, p = .0001 (degrees of freedom using Satterthwaite’s correction for unequal variance).

In the presented patient cohorts the RFs reached highly significant predictions with an AUC of 0.8932±0.0052 ( p <0.0001 for NAFLD vs.

Correlation between genetic divergence and geographic proximity Despite forming an evolutionarily coherent population, the genetic structure among localities in the larger, Amazonas basin group was not insignificant, and F ST values ranged from 0.019 and non-significant (Alto Jurua x Nhamundá) to 0.475 and highly significant ( P <0.0001; Lábrea x Região dos Lagos in Amapá) ( S2 Table and S4 Fig ).

The effect of sex was highly significant in each cohort (P < 0.0001 in each cohort), with females more active than males ( Table 3 ).

Moreover, the correlation between grazing activity assessed hourly by individual video recording and direct observation was highly significant (Spearman correlation coefficient = 0.84, n = 24, P < 0.0001).

In both analyses, the duration effect was highly significant ( Fig 10A : χ 2 = 17.7, df = 1, P < 0.0001; Fig 10B : χ 2 = 12.1, df = 1, P < 0.0001), and showed that probability of plant infection increased with increasing duration of E1 events.