At the 15th day ( Figure 3C ), however, there was extremely significant difference between Aurantimicrobium and Reyranella ( p ≤ 0.01).
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The differences in both axial and secondary root lengths between the treatment and control groups were highly significant ( p < 0.01).
Non-metric multidimensional scaling (NMDS) revealed highly significant differences in β -diversity among varieties ( p < 0.01; Figure 2 ).
The ANOVA results showed that moisture content treatment had an extremely significant effect on the number of LAB and yeast ( P < 0.01), and additive treatment had an extremely significant effect on the LAB and Enterobacteriaceae quantities in the silages ( P < 0.001).
(3) Range analysis and variance analysis The range and variance analysis of the residual proportions of Cu and Zn over 30 days ( Tables 3 , 4 ) revealed that the primary and secondary influencing factors were in the order of activated carbon addition (C) > C/N (B) > moisture content (A): activated carbon addition had the largest range (Cu: R = 17.6, Zn: R = 17.1) and the impact reached a highly significant level (p < 0.01); C/N followed closely (Cu: R = 8.5, Zn: R = 9.2), with the impact reaching a significant level (p < 0.05); moisture content had the least impact (Cu: R = 3.9, Zn: R = 1.8), with significant effects only on Cu (p < 0.05).
Evaluation of the explanatory power of cardiac structure and function indicators for gut microbiota variation Based on dbRDA analysis, significant associations were found between LVFWd, MWTd, and ET with gut microbiota ( p < 0.05), while LV_MASS_I showed a highly significant association with gut microbial communities ( p < 0.01).
Relationship between soil microbial communities and physicochemical properties/enzyme activities Correlation analysis between the top 20 genera and physicochemical properties revealed the following: for bacteria ( Figure 6A ), AK showed a highly significant positive correlation with Blastococcus ( p < 0.01) and significant positive correlations with Rubrobacter, unclassified_c_Actinobacteria, Pseudonocardia, norank_f_67-14, Nocardioides , and Skermanella ( p < 0.05), but a significant negative correlation with Sphingomonas .
For example, in a study conducted to evaluate the carvacrol-erythromycin synergistic effect against erythromycin-resistant Group A Streptococci, highly significant synergy (FIC Index ≤ 0.5, p < 0.01) was detected in 21 out of 32 strains ( Magi et al., 2015 ).
polyphylla demonstrated a highly significant negative correlation with the abundance of Ascomycota ( R = −0.8815, P < 0.01), while showing significant positive correlations with Mortierellomycota ( R = 0.7120), Rozellomycota ( R = 0.6781), Aphelidiomycota ( R = 0.8001), and Monoblepharomycota ( R = 0.6809).
The absolute LDA values of the five biomarkers were all greater than four, indicating highly significant differences ( p < 0.01), which may be the key biomarkers leading to differences in the bacterial community structure among the PF, CC, and SC, and different intensities of OC sample plots.
Only OTUs that displayed highly significant ( P < 0.01) associations with one tissue type were considered as indicator OTUs.
Enteritidis ATCC 13076 was highly significant ( p < 0.01) ( Supplementary Tables 1, 3 ).
NO 3 - -N was notably correlated with bacterial community diversity (Shannon and Simpson indexes), with NO 3 - -N and the Simpson index showing an extremely significant positive correlation ( r = 0.656, P < 0.01).
Meanwhile, NM, MD and BPD groups were all significantly separated, and the difference was found to be highly significant by Adonis test ( p < 0.01).
Regarding physicochemical parameters ( Supplementary Figure S2 ), temperature was negatively correlated with most genes, showing highly significant correlations with tetG , sul2 , aac(6′)-Ib-cr , and intI2 ( p < 0.01). pH correlated negatively with sul2 ( p < 0.01) and positively with tetW ( p < 0.05).
For the genus of bacteria, Acetobacter was significantly positively correlated with Ethyl caprylate, Phenylethyl Alcohol, 2,3-Butanediol, and Ethyl Acetate ( p < 0.01), Staphylococcus showed a significant positive correlation with Methyl oleate ( p < 0.05), and an extremely significant negative correlation with all 9 flavor substances ( p < 0.01); Brevibacillus has a highly significant correlation ( p < 0.01) with Ethyl caprylate, 3-Methyl-1-butanol, Phenylethyl Alcohol, Ethyl Acetate, and 2,3-Butanediol.
Asterisks indicate a statistically significant difference compared with TMV, “ ∗ ” indicate a significant difference ( P < 0.05) and “ ∗∗ ” indicate an extremely significant difference ( P < 0.01).
As shown in Figure 5B , a significant difference ( P < 0.05) in the number of bacteria recovered from lung was found between the wild-type and Δ cpxAR -treated groups, and there was a highly significant difference ( P < 0.01) in the number of bacteria recovered from lung between the wild-type and Δ wecA -treated groups.
There was a highly significant difference in FPA of the two strains ( p < 0.01).
S-ALP activity was significantly and positively correlated with AN, and AP showed a highly significant correlation ( p < 0.01) and significant correlation ( p < 0.05) with AK.
Independent t-tests revealed that the treatment exerted a highly significant positive effect on both dry weight and rhizomorph numbers ( p < 0.01).
Differences were considered statistically significant at p < 0.05 and highly significant at p < 0.01.
The main effects of time on both Thr and Cys were highly significant ( p < 0.01).
Statistical analysis demonstrated that six parameters, including TOC, pH, TN, NO 3 -N, WT, and TP, exhibited highly significant differences ( p < 0.01).
LEFSe analyses highlighted compartment-specific biomarkers: Acidobacteria, Basidiomycota, and Ascomycota were enriched in distinct zones (rhizosphere, roots, and leaves), with Actinobacteria exhibiting highly significant correlations ( P < 0.01) with flavonoids, lipids, and quinones, while Acidobacteria, Basidiomycota, and Ascomycota were strongly linked to steroids and tannins ( P < 0.05).