The phenolic compound content of each cultivar was expressed as means ± SD (standard deviation) of three replicates. The significant differences (p ≤ 0.05) between means were evaluated using Tukey’s HSD (Honest Significant Difference test). Cellular viability and metabolic activity results are presented as means ± standard deviation of 5 experimental repeats, each of 3 technical repeats. The data are expressed as percentage of the untreated control. Statistical analysis was performed by one-way analysis of variance (ANOVA) with the Dunnett’s post-test by SigmaPlot 13.0 software (Systat Software Inc., Surrey, UK). A value of p < 0.05 was taken as the level of significance. EC50 was calculated by SigmaPlot 13.0 (Systat Software Inc., Surrey, UK) software by means of four-parameter logistic function. Correlations were analyzed by Microsoft Office Excel 2010 (Microsoft, Redmond, WA, USA) software Correlation function.
Sigmaplot 13
Manufactured by Grafiti LLC
Sourced in United States, Germany, United Kingdom, Canada, Austria
SigmaPlot 13.0 is a data visualization and analysis software tool. It provides features for creating high-quality graphs and plots from scientific data.
Automatically generated - may contain errors
Lab products found in correlation
Prism 7, by GraphPad (13 mentions)
Sas 9, by SAS Institute (12 mentions)
Prism 9, by GraphPad (7 mentions)
Prism 8, by GraphPad (7 mentions)
Quatropro, by Corel (6 mentions)
Prism 6, by GraphPad (6 mentions)
Statistix 10, by SAS Institute (6 mentions)
Sigmastat, by Grafiti LLC (4 mentions)
Pclamp 9, by Molecular Devices (4 mentions)
Geneclamp 500b amplifier, by Molecular Devices (4 mentions)
Spss statistics 22, by IBM (3 mentions)
Spss statistics 27, by IBM (3 mentions)
Systat 13, by Grafiti LLC (3 mentions)
Matlab, by MathWorks (3 mentions)
Capillary pipettes, by Warner Instruments (3 mentions)
Digidata 1322a, by Molecular Devices (3 mentions)
Statistix 8, by SAS Institute (3 mentions)
2 2 azino bis 3 ethylbenzothiazoline 6 sulfonic acid substrate solution, by Merck Group (3 mentions)
Spectramax plus, by BMG Labtech (2 mentions)
Matlab, by Grafiti LLC (2 mentions)
689 protocols using sigmaplot 13
1
Phenolic Compounds and Cellular Viability
2
Cardiac Thrombus and Infarct Size Evaluation
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Data are presented as mean ± SD. For thrombus formation as well as myocardial infarction experiments, the sample sizes were calculated a priori using the ANOVA sample size analysis software tool of SigmaPlot 13 (Systat Software, San Jose, CA, USA). This calculation resulted in a required group size of n = 8 (power: 0.8; alpha: 0.05; estimated relevant effect size: 0.30; estimated SD: 0.17) in thrombus formation experiments, and a required group size of n = 6 for infarct size experiments (power 0.8; alpha 0.05; estimated relevant effect size: 0.25; estimated SD: 0.10). For infarct sizes and thrombus formation, differences between groups were analysed by one-way ANOVA with Tukey post hoc test. Comparisons of haemodynamics between groups or between different time points within a group were performed with a two-way ANOVA followed by Tukey’s post hoc test. Statistical data analysis was performed using GraphPad StatMate™ Version 1.01 (GraphPad Software, San Diego, CA, USA) or SigmaPlot 13 (Systat Software, San Jose, CA, USA). Differences were considered statistically significant when p values were less than 0.05.
3
Quantitative Analysis of Neuronal Features
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In the box plots, the boundaries of the box represent the 25th to 75th percentile, a black line or a white dot within the box marks the median, while the white line corresponds to the mean. Whiskers above and below the box indicate the 90th and 10th percentiles, respectively. In all other plots, error bars represent the standard error of the mean. Significance was tested by one-way ANOVA with Tukey’s post hoc test when the data followed a normal distribution. Otherwise, ANOVA on ranks with Dunn’s post hoc test was applied. A p-value < 0.05 was considered significant. N is the number of cultures, while n is the number of measured neurons unless specified otherwise. Statistical tests were performed with Sigma Plot 13 (Systat Software, Erkrath, Germany). Graphs were generated by Sigma Plot 13 (Systat Software, Erkrath, Germany), Igor (WaveMetrics, Portland, OR, United States) or Excel. Violin plots were generated using the webtool from http://shiny.chemgrid.org/boxplotr .
4
Quantitative Microscopy Analysis of Cellular Stress Markers
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Quantitative results of viability, early apoptosis markers, thioflavin T-fluorescence, the AO fluorescence ratio, and the BODIPY™ 581/591 C11 fluorescence ratio are presented as mean ± SEM. The statistical significance of differences between the groups was determined using ANOVA with subsequent application of the Newman–Keuls test. MaxStat Pro 3.6 software (MaxStat Software, Cleverns, Germany) and SigmaPlot 13 (Systat Software, Palo Alto, CA, USA) were used to perform all statistical analyses. Differences were considered statistically significant at (*) P < 0.05.
Quantitative microscopy analysis (namely analysis of lysosomal size, mitochondrial circularity, ΔmΦ, ROS levels, and Pearson's correlation coefficient) was conducted following fluorescence quantitative microscopy guidelines.69–71 (link) In brief, images from three independent experiments were subjected to quantitative analysis. In each experiment, 10 randomly selected fields from each sample were imaged. To determine the sample size, we employed an accepted statistical methodology.72 (link) We used SigmaPlot 13 software (Systat Software, Palo Alto, CA, USA) to calculate the sample size, considering a minimum confidence level of 95% and a statistical power of 0.9. Under these conditions, the sample size was calculated to be 30. Thus, at least 30 randomly selected cells were used in fluorescence microscopy quantification.
Quantitative microscopy analysis (namely analysis of lysosomal size, mitochondrial circularity, ΔmΦ, ROS levels, and Pearson's correlation coefficient) was conducted following fluorescence quantitative microscopy guidelines.69–71 (link) In brief, images from three independent experiments were subjected to quantitative analysis. In each experiment, 10 randomly selected fields from each sample were imaged. To determine the sample size, we employed an accepted statistical methodology.72 (link) We used SigmaPlot 13 software (Systat Software, Palo Alto, CA, USA) to calculate the sample size, considering a minimum confidence level of 95% and a statistical power of 0.9. Under these conditions, the sample size was calculated to be 30. Thus, at least 30 randomly selected cells were used in fluorescence microscopy quantification.
5
Etheno-ATP Exchange Kinetics Analysis
6
Neuronal Sensitivity Analysis
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Data were analyzed with SigmaPlot 13.0 Software (Systat Software Inc., San Jose, CA, USA). Results are expressed as mean ± standard error of the mean (SEM). The number of the cells examined are represented by “n”. Parametric and non-parametric data were assessed using the one-way analysis of variance (ANOVA) and Kruskal–Wallis test, respectively. Chi-squared tests were used to assess changes in the proportion of capsaicin-sensitive neurons. A p-value of < 0.05 was considered statistically significant.
7
Soil Respiration Dynamics under Nitrogen Addition
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Repeated measurement ANOVA was conducted to examine the effects of N addition on Rs, Rh, Ra, soil temperature and moisture. The effects of different treatments on FRB, soil physicochemical properties, soil microbial biomass, Rs, Rh, Ra and Q 10 were studied by one-way ANOVA and Tukey HSD test. The relationship between Rs, Rh, Ra and soil physicochemical properties, microbial biomass and FRB was further discussed by using linear regression model.
We tted the measured soil temperature and soil moisture with R as an exponential equation (R = ae bT W c ) and obtained the Q 10 value from the b coe cient (Q 10 = e 10b ).
Where R represents the rate of soil respiration (Rs, Rh, Ra, μmol m -2 s -1 ); T represents the soil temperature at 5 cm depth (°C); W (%) represents soil volumetric moisture at 5 cm depth; and a, b, and c represent model parameters.
All analyses were performed with SPSS 22.0 software package (SPSS, Inc., Chicago, Illinois, USA), and graphs were prepared with SigmaPlot 13.0 software (Systat Software Inc., Chicago, IL, USA).
We tted the measured soil temperature and soil moisture with R as an exponential equation (R = ae bT W c ) and obtained the Q 10 value from the b coe cient (Q 10 = e 10b ).
Where R represents the rate of soil respiration (Rs, Rh, Ra, μmol m -2 s -1 ); T represents the soil temperature at 5 cm depth (°C); W (%) represents soil volumetric moisture at 5 cm depth; and a, b, and c represent model parameters.
All analyses were performed with SPSS 22.0 software package (SPSS, Inc., Chicago, Illinois, USA), and graphs were prepared with SigmaPlot 13.0 software (Systat Software Inc., Chicago, IL, USA).
8
Reproducibility Assessment of Periodontal Bacteria
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The reproducibility of two separate investigator and intra-investigator assessments were evaluated using Cohen’s kappa index. The intra- and inter-examiner agreements were 0.81 and 0.72, respectively. All statistical analyses were performed using SigmaPlot 13.0 software (Systat Software Inc., San Jose, USA) or R statistical software (https://www.R-project.org/ ). The differences in the characteristics and detection rates of the bacteria between the healthy controls and periodontitis patients were analyzed using the chi-squared or Fisher’s exact tests. Fisher’s exact tests were performed when the criteria for the chi-squared test were not fulfilled. Comparisons among all groups were performed using the Kruskal-Wallis test, and Dunn’s test was used to correct for multiple comparisons. P-values were considered statistically significant when the p-value was less than 0.05, and marginally significant when P > 0.05, up to 0.1.
9
Nanodot and Cumulative AK Correlation
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Nanodot readings and cumulative AK values are reported as medians (and range). The scatter plot was constructed using Excel spreadsheet. Linear regression trend line and formula were derived to evaluate the correlation between the two values. The correlation coefficient was calculated using a best-fit trend line for the data. Sigmaplot® 13.0 software (Systat Software Inc., San Jose, CA, USA) was used.
10
Analyzing Substance Interactions and Influences
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