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Sigmaplot version 11

Manufactured by IBM
Sourced in United States

SigmaPlot version 11.0 is a data analysis and graphing software package developed by Systat Software Inc. The core function of SigmaPlot is to provide users with tools for data visualization, statistical analysis, and curve fitting.

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9 protocols using sigmaplot version 11

1

Statistical Analysis of Experimental Data

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Data were expressed as the mean ± standard error of the mean (SEM). Statistical analysis was performed with SigmaPlot version 11.0 and SPSS 13.0. Differences between the mean of two groups were assessed by Student's t test, and differences in the mean of multiple groups were assessed by one‐way ANOVA. Correlations of two groups and comparisons of quantitative values of expression were assessed by Pearson's test. A value of P < .05 was considered to indicate a statistically significant difference. All experiments were repeated three times.
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2

Statistical Analysis of Experimental Data

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Data were expressed as means ± standard errors of the means. Statistical analyses were performed with SigmaPlot version 11.0 and SPSS version 13.0. Differences between means were assessed with the Student's t test, paired t-test, or Mann–Whitney U test in cases of abnormally distributed data. In multiple comparisons, one-way analysis of variance was used. Pearson's test was used to detect the correction of two groups and compare quantitative values of expression. A value of P < 0.05 was considered statistically significant.
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3

Microplate ELISA for Protein-Protein Interactions

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We used a microplate enzyme-linked immunosorbent assay (ELISA) for measuring protein-protein interactions [22 (link)], as described in [14 (link)]. Purified DvCad1-CR peptides were biotinylated using sulfo-NHS (N-hydroxysuccinimide)-photocleavable biotin (Pierce, Rockford, IL, USA), dialyzed into 200 mM NaCl, 20 mM Na2CO3 (pH 8.0), and stored in aliquots at 4 °C. Microtiter plates (high-binding, 96-well Immulon 2HB plates; Thermo Fisher Scientific, Inc., Waltham, MA) were coated with 1.0 µg Cry3Bb/well in 50 μL coating buffer (100 mM Na2CO3, pH 9.6), with or without the 1000-fold molar excess unlabeled DvCad1-CR peptides. In competition binding assays, 20 nM biotinylated DvCad1-CR peptide was mixed with increasing concentrations of the unlabeled DvCad1-CR peptides. Cry3Bb toxin-coated or peptide-coated plates were washed and incubated with horse radish peroxidase-conjugated streptavidin (SA-HRP; Pierce), and then incubated with an HRP chromogenic substrate (1-Step Ultra TMB-ELISA, Thermo Fisher Scientific, Inc., USA), after washing, to detect bound SA-HRP. Color development was stopped by adding 3M sulfuric acid, and absorbance was measured at 450 nm using a microplate reader (MDS Analytical Technologies, Sunnyvale, CA, USA). Data were plotted and analyzed using the Sigma Plot Version 11.0 (SPSS Science, Chicago, IL, USA).
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4

Comprehensive Statistical Analysis

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Statistical analysis was carried out via SigmaPlot Version 11.0, SPSS13.0, and Excel 2007 software.
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5

Radiation Effects on Animal Models

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Experiments were performed with 10 animals per group per experimental condition. To check for normal distribution, we performed a Shapiro-Wilk test. All data followed a Gaussian distribution. One-way ANOVA and Student's t test were used to compare irradiated and nonirradiated animal results. All results are expressed as mean ± SEM. Statistical software used was SigmaPlot™ version 11.0 (SPSS Inc., France) was used for all statistical analysis. Results with P < 0.05 were considered statistically significant.
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6

Comparative Statistical Analysis of Data

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Statistical analysis of data was completed using SigmaPlot version 11 software (SPSS, Chicago, IL). One-way analysis of variance (ANOVA) was performed to compare mean responses among groups. For each end point, the group means were compared using the Bonferroni least significant difference procedure. A statistical probability (p) value of <0.05 was considered significant.
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7

Statistical Analysis of Research Findings

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All statistical analyses were performed using SigmaPlot Version 11 (SPSS Inc., Chicago, IL) and statistical significance was assessed using an α level of 0.05.
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8

Statistical Analysis of Herbicide Impacts

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The results were subjected to ANOVA by means of JMP software, version 5.0 (SAS Institute Inc., Cary, NC, USA). Data were compared by least-significant differences (LSD) on the basis of Tukey–Kramer Honestly Significant Difference test (α = 0.05), except for the data describing the influence of imazapic on amino acid content in HRT roots and in P. aegyptiaca attached to its roots, which were compared by LS Means Contrast test (α = 0.05). Data on the influence of imazapic and glyphosate on callus biomass, glyphosate on shikimic acid accumulation, imidazolinones on P. aegyptiaca ALS activity, and glyphosate on P. aegyptiaca EPSPS activity were computed by non-linear regressions using Sigma-Plot version 11.01 (SPSS Inc., Chicago, IL, USA). The data were arcsine-transformed before analysis. On the graphs, back-transformed means are presented. All experiments were conducted twice. These experiments were compared by Fisher t-test to prove homogeneity of the variances and then the data of the two experiments were combined, except for the experiment involving imazapic detection in tomato leaves, roots and attached broomrapes, where the data were not combined due to heterogeneity of variances. Results of those two experiments are therefore presented separately.
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9

Evaluating Chickpea Resistance to AHAS Inhibitors

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The results of the experiments on tobacco plants and the influence of the imazamox on chickpea plant phenotype were subjected to ANOVA using JMP Software, version 5.0 (SAS Institute Inc., NC, USA). Data were compared by LSD on the basis of the Tukey–Kramer honestly significant difference test (p < 0.05) and by standard errors of the means (SEM). Nonlinear regressions, using Sigma-Plot version 11.01 (SPSS), were computed for the chickpea cross-resistance to AHAS inhibitors. The chi-square test was used to determine mutation inheritance.
All experiments were conducted twice; the comparison of the two experiments was performed using Fisher’s t-test. Data were combined based on the homogeneity of the variances.
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