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506 protocols using kaleidagraph

1

Statistical Analysis of Tumor Microenvironment

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Differences in cell survival, proliferation, and secretion of TSP-1 measured by ELISA were evaluated for statistical significance by ANOVA (Kaleidagraph, Synergy Software). Differences in the area of metastatic lesions between treated and untreated mice were evaluated for statistical significance by Student’s T-test (Kaleidagraph, Synergy Software). Differences in the fraction of TUNEL-positive cells between tumors treated with saline and tumors treated with the cyclic psap peptide were evaluated for statistical significance by Chi-Square and Fisher’s Exact Test. Differences in staining indices of ovarian cancer patient tumor microarrays were evaluated for statistical significance by Wilcoxon-Mann-Whitney analysis (Kaleidagraph, Synergy Software). For all analyses, P values <0.05 were considered statistically significant. All tests were two tailed. Original data for individual mice are provided in table S2.
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2

Analyzing Genetic Factors in Growth

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Data analysis was performed in R (www.r-project.org) and in KaleidaGraph (Synergy), and the plots were generated in KaleidaGraph. We tested for differences in male and female body size, L3 duration, relative expression of gbp1 and gbp2, ILP2 and ILP5 accumulation, pAKT/HH3 and pAKT/AKT ratios, and FRE luciferase activity using ANOVA and post hoc pairwise t tests. To test for differences in growth rates between genotypes, we fit the data using linear models regressing larval weight against age and tested for differences in the interaction term between larval age and genotype using ANCOVA and post hoc comparisons of the slopes of fitted lines using lstrends (HH and lsmeans packages).
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3

Src Kinase Activity Assay

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For the continuous spectrophotometric assay64 (link), 12.5 µM–800 µM ATP Src-optimal substrate peptide (AEEEIYGEFAKKK)34 (link) was combined with 12.5 µM–800 µM ATP. Concentrations of Src kinase domain used for these assays were 25 nM. The initial velocities were plotted and fit to the Michaelis–Menten equation in Kaleidagraph (Synergy Software) to determine KM.
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4

Determination of CRIP2-Cu+ Dissociation Constant

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The dissociation constant (KD) of hsCRIP2 for Cu+ was determined through competition assays with the chromogenic ligand bathocuproine disulfonate BCS ([Cu+(BCS)2]3− β2’ formation constant 1020.8 M−2, ε483 nm 13000 M−1 cm−1) (95 (link)) as previously shown (96 (link)). Immediately before the assay, CRIP2 was fully reduced by incubation with 5 mM TCEP on ice for 3 h, and the reducing agent was removed using a 3 kDa Centricon (Millipore Sigma). Cu+ solutions were generated in situ from CuSO4 in the presence of ascorbate. Briefly, 10 μM Cu+, 25 μM BCS in buffer 25 mM HEPES pH 8, 150 mM NaCl, 10 mM ascorbic acid were titrated with 1 - 30 μM purified CRIP2, incubated 5 min at room temperature, and the 300-800 nm absorption spectra were recorded. CRIP2-Cu+ KD was calculated by curve-fitting the experimental data to the equilibrium equations [1] and [2] (97 (link)), where M is the metal, L is the competing ligand and P are the Cu-sites in the protein. Reported errors are asymptotic standard errors provided by the fitting software (KaleidaGraph; Synergy).
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5

Biogeochemical Data Visualization Tools

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To draw the distributions and fluxes of biogeochemical variables, we used Ocean Data View (ver. 5.2.1, https://odv.awi.de/), Kaleida Graph (ver. 4.5.1, Synergy Software), and Microsoft PowerPoint for Office 365. The color contours in Figs. 1, 2a, and 3a were drawn by the weighted-average griding of Ocean Data View with x-y scale-lengths of 110-110, 65-65, and 40-30, respectively.
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6

Quantitative Data Analysis Methodology

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Quantitative data were expressed as mean ± standard error of mean (SEM). Single variable data were compared by paired-sample Student’s t-tests using the computer program KaleidaGraph® version 4.5.2 for Mac (Synergy Software; Reading, PA, USA). Also, multiple pair-comparisons were performed using Tukey’s test after ordinary one-way analysis of variance (ANOVA). Post hoc differences were considered statistically different at a value p < 0.05.
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7

Cilia Length Measurement Protocol

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Statistical analyses were done using Wilcoxon or two‐tailed Student's t‐tests. Significance probability values were P < 0.05. Statistical tests were performed in Excel (Microsoft) and KaleidaGraph (Synergy Software). Statistical analysis and mean ± standard deviation (s.d.) were performed on at least three independent biological replicates done in similar conditions. The measurement of cilia length by electron microscopy and data shown in Appendix Fig S6C and D were performed two times independently. The number of biological replicates and sampling sizes are indicated in figure legends and source data.
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8

Principal Component Analysis of Research Data

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Results were analyzed by KaleidaGraph (v. 5.0, Synergy Software, Reading, PA, USA). Statistical significance of differences was evaluated by one-way ANOVA using post hoc analysis with minimum significant difference. Principal component analysis was performed by a freely available web program, ClustVis (http://biit.cs.ut.ee/clustvis/) (accessed on 30 November 2022) [28 (link)]. For graphs of principal component analysis, prediction ellipses were such that, with a probability of 0.95, a new observation from the same group will fall inside the ellipse. Unit variance scaling was applied to rows; singular value decomposition with imputation was used to calculate principal components.
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9

Measuring Tryptase Enzymatic Activity

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The enzymatic activity of 1 nM tetrameric βI-tryptase was measured in 200 µL volume using 2 mM S-2288 chromogenic substrate (DiaPharma Group, Inc., West Chester, OH) was performed as previously described11 (link). The reaction velocity was determined by the rate at which p-nitroaniline (pNA) is released, which was measured spectrophotometrically at 405 nm using a SpectraMax M5e plate reader using Softmax Pro (v6.2.2) (Molecular Devices, Sunnyvale, CA). Inhibition plots were generated using 4-parameter fits from data collected from three independent experiments and statistical analysis was performed using KaleidaGraph (v4.1.3) (Synergy Software, Reading, PA).
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10

Quantitative Analysis of Spermatheca Fluorescence

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Bar graphs were made in Excel:mac (version 14.7.2 and 14.7.7; Microsoft
Corporation, Redmond, WA) and line graphs were made in KaleidaGraph (version
4.5.2; Synergy Software, Reading, PA). Measurements of distance between maximal
GFP fluorescence and maximal EXC-6 immunostain along spermatheca junctions were
subject to analysis of variation, with Tukey-Kramer post-hoc testing.
Differences for which p < 0.05 were considered statistically significant.
Quantitative ovulation data were analyzed using a chi-squared test of
independence, with post-hoc testing using a Bonferroni corrected p-value =
α / # of tests, where α = 0.05. See Supplementary Table S5 for
details.
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