We calculated GRO-seq read counts near active and inactive CEBPB-bound sites based on the CRE-seq data and observed a highly significant enrichment in GRO-seq signal at active sites compared to inactive binding events ( P = 5.65 × 10 −5 ) (Supplemental Fig. 7).
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The KR motif occurs 562 times in this CNE set, representing a highly significant enrichment over shuffled versions of the motif (p = 5.7 × 10 -5 ), and when compared to control genomic regions and the entire human genome (Table 1 , Methods and Additional File 4 ).
Also, all the other measures showed clearly significant results resembling the associations with the ACarPA status (all p < 5.7 × 10 –5 , Supplementary Table S3 ).
In contrast, there was a large and highly significant increase of input resistance in the responses to hyperpolarizing current injections, it more than doubled over control values ( Table 1 ; one-way ANOVA, p = 5.9 × 10 −5 , row g, Table 3 ).
Statistical analyses performed on the mean area amplitude of posterior N2 (attentional selection negativity ) showed that the attention condition was highly significant (F [3,75] = 16.06, GG adjusted p < 0.000059) with larger negativities to pseudo-targets than stimuli sharing only space location with the targets, and to the latter than to non-targets (see mean amplitude values in Figure 4 ).
When these tumor groups were compared, highly significant increased PARTICLE levels were noted when the WWOX FRA16D was intact (Chi-square association p = 0.000059, Figure 1B ).
Distance was found to be highly significant in this model ( p = 5.92e‐05; Table 2 ).
Pearson correlation analysis indicated a positive and highly significant correlation between TDO2 and CYP19A1 ( R = 0.78, P = 5.96 × 10 –5 ), TGFb3 ( R = 0.88, P = 3.3 × 10 –7 ), HOXA13 ( R = 0.62, P = 0.003), COL1A1 ( R = 0.65, P = 0.002), COL1A2 ( R = 0.60, P = 0.005), COL3A1 ( R = 0.79, P = 3.95 × 10 –5 ), CCND1 ( R = 0.65, P = 0.002), IGF2 ( R = 0.79, P = 3.48 × 10 –5 ), and WNT4 ( R = 0.56, P = 0.011) ( Figure 8 ).
The difference for DCH prevalence was statistically extremely significant (p-value = 0.00006, OR = 4.04005, CI95% = [1.96601; 8.30211]) when compared animals from collection A and collection B (Fig. 1A ).
Conversely, in the case of IC7 with bilateral entorhinal cortex involvement, the IC expression demonstrated a highly significant association only with age ( t = 4.05, p < 0.00006) and the association with Aβ attenuates substantially to a statistically insignificant level.
Specifically, the differentially expressed genes found between T10 and T20 in the pituitary only included 1 enriched GO term “neurohypophyseal hormone activity”, while the biological process of “response to steroid hormone” was highly significant ( p = 0.00006) before FDR correction but not after (FDR = 0.16181).
Predictive value of biomarkers and clinical variables on cumulative ICU survival ICU survival at 28-day was associated with highly significant values of IL-1RA serum levels ( P = 0.00006, HR 1.31, 95% CI 1.15–1.50) and SOFA score ( P = 0.001, HR 1.18, 95% CI 1.07–1.30) in septic patients.
Similarly, highly significant diabetes cis- and trans-acting eQTL-SNPs were identified ( p < 6.0 × 10 −5 and p < 6.0 × 10 −5 , respectively; Supplementary Spreadsheet 2 doi: 10.17608/k6.auckland.5285041 ).
In recording events with extra-food added ( N = 23 nests), it increased to 30.02% (95% CI = 18.72–41.32), which resulted in a highly significant effect of food supply in experimental nests (RMA, F = 24.32, df = 1, 22, P = 0.00006).
In comparison to the most common haplotype 1112, fasting insulin levels and HOMA-IR values of haplotypes 1221 and 2221 were significantly higher and lower, respectively ( Table 1 ), and the difference between 1221 and 2221 was highly significant ( P = 0.00006).
Our study indicates that ffEVs influenced the expression of various genes related to the MAPK pathway (GO:0032873, GO:1900744) in the Cp COCs group, which was also characterized by a highly significant increase in expansion during IVM ( p = 0.00006).
We identified altogether five such positions (with P < 6 × 10 −5 , binomial distribution; i.e., highly significant) all of them occurring in the metazoan 18S rRNAs.
Further, an alternative χ 2 test comparing the null expectation of no association between head-to-head competitions and ranked attraction index revealed this association was highly significant ( P = 0.00006).
The cross‐tabulation between PAP and hr‐HPV outcome has demonstrated a highly significant association ( p < 0.00006; Table 2 ).
For the TCGA data set, the correlation was decreased somewhat (Pearson r = 0.25 compared to 0.36 for the full data set) but still highly significant ( P = 6 × 10 -5 ), demonstrating that the correlation with age is only partially explained by IDH1 status.
Cited2 −/− embryos showed a modest yet highly significant decrease in levels of Lmo4 mRNA when compared with wild-type littermates (1.35-fold decrease; P = 0.00006, n = 12 Cited2 +/+ vs. n = 12 Cited2 −/− embryos), but Lmo4 −/− embryos did not show any difference in Cited2 levels (n = 12 Lmo4 +/+ vs. n = 12 Lmo4 −/− embryos; Fig. 5 a,b), indicating that Lmo4 is downstream of Cited2 .
Associations of the TIRAP gene haplotypes with ALI risk We next carried out haplotype analysis on the basis of these two associated SNPs and found that a two-allele model of risk provided the strongest predictor of risk, which was highly significant (P = 0.00006 in ALI group vs control group and P = 0.00003 in ALI group vs sepsis alone group).
All seven SNPs of the CEP68 gene showed linkage disequilibrium (LD), and the haplotype of CEP68_ht4 (T-G-A-A-A-C-G) showed a highly significant association with aspirin intolerance (OR = 2.63; 95% CI = 1.64–4.21; P = 6.0×10 −5 ).
In addition, a highly significant (p=0.00006) 1.6-fold elevation was seen in lactoylglutathione lyase (glyoxalase I, GLO-1) in Alkbh7 -/- vs.
After repacking of modeled structures, which led to structural fitting of contacting residues and displacement of their side-chain groups, the correlations of steric descriptors became weaker, while the correlations of hydrophobic descriptors still remained highly significant (p-value = 6x10 -5 ). 3.4 Identifying residue binding features in CDR3: peptide interface using machine learning At the final stage we performed RFE (Recursive Feature Elimination) analysis and applied the Random Forest (RF) algorithm to make predictive models for the per-residue contacting energy values for amino acid residue pairs in CDR3 loops and peptides.