Sigmaplot 12

Four plants (shoots including leaves) were used at each data point in triplicate for ORAC, total phenols and total flavonoids, and in duplicate for AA. Values were tested for significance with a two-way analysis of variance (ANOVA) and Holm-Sidak post-hoc analysis using SigmaPlot 12.5 (Systat Software, Inc.). The grouping factors were salinity and time; interactions were calculated for ORAC, TAA, phenols and flavonoid values.
Three plants (shoots including leaves) were pooled as one sample, and three (one, as starting value for the species comparison) pooled samples made one data point except for B. cylindrica where eight to nine leaves were analysed individually. The analysis was repeated three times in triplicate measurements for ORAC, total phenols and total flavonoids, and in duplicate for AA. Carotenoids and chlorophyll were measured three times. Results were tested for significance by one-way ANOVA and B. cylindrica by t-test in SigmaPlot 12.5 (Systat Software, Inc.).

The uptake of [³H]-AC by human respiratory epithelial cells was expressed as the cell-to-medium (cell/medium) ratio, which was calculated by the following equation [31 (link)]:

To estimate the kinetic uptake parameters of [³H]-AC, the initial uptake rates were fitted to Equation (3) by means of non-linear least-squares regression analysis using WinNonlin (Pharsight, Sunnyvale, CA, USA).

where v is the initial uptake rate of the substrate (nmol/(min/mg protein)), s is the substrate concentration in the medium (μM), K_m is the Michaelis–Menten constant (μM), and V_max is the maximum uptake rate (nmol/min/mg protein).
The time-dependent uptake was fitted using SigmaPlot 12.5 (Systat Software, Erkrath, Germany). One binding site was assumed and fitting was corrected for non-specific binding. Data were analyzed with SigmaPlot 12.5 (Systat Software, Erkrath, Germany) and shown as mean ± standard deviation (SD). Specifically for inhibition experiments, results were expressed as mean ± standard error of the mean (SEM). Statistical analysis was performed using unpaired and paired two-tailed Student’s t-test and one-way analysis of variance (ANOVA), as appropriate, and p-values < 0.05 were accepted to indicate statistical significance. All data were obtained from at least 3 independent experiments.

Data are presented as means ± SE in the text and in all figures and tables. P < 0.05 was considered significant. Differences between the two groups were evaluated with Student's t-test. All statistical analyses were performed in Sigma Plot 12.5 (Systat Software Inc., San Jose, USA). Pearson's correlation analysis was used to establish the presence of correlations. Whole-body fat oxidation was calculated from VO₂ and VCO₂ values during the last 60 s of each exercise step in the graded exercise tests, using standard indirect calorimetry equations [26 (link)]. For each subject, polynomial curve fitting (Sigma Plot 12.5, Systat Software Inc., San Jose, USA) was used to determine whole-body peak fat oxidation. For determination of fat oxidation at rest, data obtained during the hood measurements were used. The Cederholm index for glucose homeostasis was calculated as previously described [27 (link)]; briefly, glucose and insulin concentrations during the oral glucose tolerance test, body weight, and the amount of glucose ingested were taken into account when the index was calculated.

Those semiquantitative parameters of SUVmax and blood pool activity on the initial and delayed images were recorded as iSUV, dSUV, iBP, and dBP, respectively. Dichotomous results of infected and noninfected grafts were based on the reference standard, and the iSUV, dSUV, and RI of the 2 patient groups were compared by Mann–Whitney rank sum test. Performance of the conventional ¹⁸F-FDG PET/CT and DTPI were tested against the reference standard using receiver operating characteristic (ROC) curve analysis, and the optimal sensitivity, specificity, and accuracy for detecting infected grafts were derived at optimal cut off point from ROC curve (Sigmaplot 12.3, Systat Software Inc., San Jose, CA, USA). A P value <0.05 was considered significant.

Samples receiving less than 10,000 sequence reads were omitted from analysis. Differences in beta-diversity of all groups were tested via a two-way and one-way PERMANOVA of ranked Bray-Curtis (shared abundances of OTUs) similarity index using the open access Past 3.14 software package [26 ]. Principal coordinate analysis (PCoA) was also performed using the Past software package and the relative abundance data was fourth-root transformed to normalize the data. OTU richness and diversity indices were tested for normality using the Shapiro-Wilk method; differences were then tested via two-way ANOVA for normal data or Kruskal-Wallis ANOVA on ranks for non-normal data using SigmaPlot 12.3 (Systat Software Inc., San Jose, CA). Significant OTUs, hierarchical clustering, and random forest analysis were performed using cube root-transformed sequence data using open access MetaboAnalyst 3.0 (http://www.metaboanalyst.ca) [27 (link)]. We considered p values less than 0.05 significant.

For each play fighting measure, a mean and standard error of the mean (SEM) was generated for each group. Play fighting dependent measures were assessed independently using separate between group analyses of variance (ANOVA). Data were separated by age. Thus, the study design was a 2 × 2 × 2 analysis of variance (ANOVA), with the between subjects factors of prenatal exposure (ET or CT), postnatal manipulation (WC or NWC), and sex (male or female). Where the ANOVA identified an overall effect, post hoc comparisons were run using the Tukey test. Follow-up univariate ANOVAs were run on play behavior outcomes to determine the source of the difference.
Correlations were conducted to understand the impact of prenatal ethanol and sensory deprivation on the relationship between expression of 50 kHz USVs and frequency of social play. To do this, Pearson’s r was determined using number of 50 kHz and total number of play interactions. Males and females were analyzed together to increase the number of animals in each condition.
Correlations were run using SPSS 22.0 software (IBM Corp., Armonk, NY, USA), all other statistical analysis was done using SigmaPlot 12.3 software (Systat Software Inc., San Jose, CA, USA).