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Sigmaplot 8

Manufactured by Merck Group
Sourced in United States

SigmaPlot 8.0 is a data analysis and graphing software developed by Systat Software, Inc. It is designed for creating high-quality graphs and visualizations from scientific data. The software provides a range of tools for data analysis, curve fitting, and statistical calculations.

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28 protocols using sigmaplot 8

1

Agonist-Induced Current Measurements

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Currents were measured using the acquisition software mentioned above. To monitor changes in the agonist-induced currents, a standard concentration was applied after 1–5 test substances were applied. To consider time-dependent sensitization or desensitization of receptors, amplitudes were normalized to the mean amplitude of the standard application before and after the test substance application. Concentration-response data for agonist-evoked currents were fit with the Hill equation using SigmaPlot 8.0. Data are expressed as the standard error of the mean (S.E.M.). Data sets were tested for statistically significant differences using Student’s t-test from SigmaPlot 8.0, and were corrected for multiple parallel tests using the Bonferroni method. Significance is indicated by * (p<0.05) or ** (p<0.01).
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2

Comparative Statistical Analysis in Research

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Data are presented as means ± s.e.m. Statistical analyses were performed using GraphPad Prism 7.03 or SigmaPlot 8.0 software. Independent samples t-tests were used to compare two groups. For two-by-two comparisons, two-way ANOVA analyses were performed (main effect of genotype shown with an asterisk over a horizontal line) followed by appropriate post-hoc tests corrected for multiple comparisons. For all tests P<0.05 was considered statistically significant.
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3

Statistical Analysis of Experimental Data

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The observed data were analyzed with computer-based software STATISTIX 8.1 using analysis of variance, and the least significant differences (LSD) test at 0.05 probability level was used to determine the significant difference among means (Steel et al., 1997 ). Moreover, Sigma-plot (8.0) software was used to prepare the graphs.
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4

Assessing Spontaneous Pain and Bite Force in Mice

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Mouse grimace scale (MGS) and BF were performed as previously described (Wang et al., 2017a (link), 2018 (link); Guo et al., 2019b (link)). All behavioral assays and video analysis were performed in a blinded manner. For MGS assay, the mice were videotaped for 30 min in each experimental time point and 10 images per 30 min session were manually captured. The scores of the five action units in each photograph were averaged, and a mean MGS score was obtained from the 10 images, which was presumed to reflect the level of spontaneous pain. For BF assay, mice were placed in a modified 60-ml plastic syringe with a wide opening at one end to accommodate the head of the mouse. To minimize stress, the mouse was released immediately from the syringe if it vigorously moved or tried to hide inside the syringe. The syringe containing the mouse was held manually and moved slowly at 0.5–1 cm/s toward bite plates so that the mouse could bite the plates. Spike 2 software was used to measure the voltage changes from transducer displacement. SigmaPlot 8.0 was used to convert the voltage change into force based on calibration using standard weights. Bite force was recorded for 120 s per session and the top five force measurements were averaged.
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5

Statistical Analysis of Experimental Data

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All data were processed and analyzed by Sigma-Plot 8.0 software. The normality test was done before t-test. The statistical significance was evaluated by t-test and p<0.05 was considered significant.
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6

Fetal DNA Fraction in Aneuploidy Screening

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Fetal DNA fractions were compared between the three fetal aneuploidy risk groups (HR, IR, LR) and assessed for correlation with the FTS test parameters; gestational age, crown-rump length (CRL), free β-subunit of human chorionic gonadotropin (free β-hCG), nuchal translucency (NT), pregnancy-associated plasma protein A (PAPP-A) as well as maternal weight using SigmaStat (version 3.5) software and visualized by SigmaPlot 8.0 and MedCalc (version 11.4.4.0). The measured free β-hCG, NT and PAPP-A were converted into multiples of the median (MoM) and log10 transformed to obtain a Gaussian distribution. Normality was assessed by the Kolmogorov-Smirnov Z test. We examined differences among groups using analysis of variance test (ANOVA) or Mann-Whitney Rank Sum Test as appropriate, with P value <0.05 to indicate statistical significance. Regression analysis (Pearson's Product-Moment Correlation) was used to assess the relationship between fetal DNA fraction and maternal weight as well as FTS parameters (gestational age, CRL, log10 free β-hCG MoM, log10 NT MoM, log10 PAPP-A MoM).
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7

Statistical Analysis of Experimental Data

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For the statistical analysis, Student's t tests (comparing two groups) or one‐way analyses of variance (ANOVAs) with Tukey post hoc tests were performed using GraphPad Prism software 8 and Sigma Plot 8.0. Differences were considered significant at *p < .05, **p < .01, and ***p < .001. All experiments were replicated six times and are shown as the mean ± SEM.
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8

Kinetic Modeling of Experimental Data

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In the different kinetics studies, the parameters were obtained by using the Sigma Plot 8.0 software that applies an iterative procedure, based on the Marquardt-Levenberg algorithm, which seeks the values of the parameters that minimize the sum of the squared differences between the observed and predicted values of the dependent variable.
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9

Flux Analysis and pH Dependence

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Data are reported as mean ± SE. Flux data were compared by
Student’s paired or unpaired 2-tailed T tests (Microsoft Excel), or by
ANOVA with Tukey post-hoc analysis (SigmaPlot). pH dependence data were fit to a
4-parameter Hill equation in SigmaPlot 8.0.
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10

Unpaired Student t-Test for Data Analysis

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Data were analyzed using the unpaired Student t-test tool of SigmaPlot 8.0, with P < 0.05 considered as a significant difference. The number of independent experiments (n) is indicated in each table or figure. Otherwise, figures show representative data of at least three experiments. Each independent experiment was the mean of at least three technical replicates. Several protein purifications were used during this work with low variations between purification batches (<10% variation in specific activity).
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