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302 protocols using sigmaplot 14

1

Analyzing Epiphytic Bacterial Communities

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SigmaPlot 14 was used to analyze the
data. SigmaPlot 14, Microsoft office 2022, and OriginLab (OriginPro
8.5) were used to plot the graphs. Data were evaluated statistically
for normality using a Shapiro–Wilk test. T-test was used to determine statistically significant differences between
the number of PS-SMPs and PVC-SMPs in shoot and leaves. The data was
reported as mean ± standard deviation. Bacterial sequence analysis
was performed by Uparse software,45 (link) Uparse
v7.0.1090. Sequences with ≥97% similarity were assigned to
the same operational taxonomic units (OTUs). For each representative
sequence, Qiime in Mothur method was performed against the database
of SILVA138 Database46 (link) for species annotation.
The phylogenetic relationship of all OTUs representative sequences
was obtained by MUSCLE (Version 3.8.31). The biodiversity of each
sample was analyzed using OTUs, and Goods coverage. By principal coordinate
analysis (PCoA), dominance, Simpson, Shannon, and evenness indices
were calculated using Past 3 software (Version 3.20).47 Common and shared OTUs of epiphytic bacterial communities
between different treatments were identified using the Venn Diagram
package in R.
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2

Mechanical Stress Analysis of Engineered Tissue

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SPSS was used to confirm normality of data within each group and detect outliers using Shapiro-Wilk tests and Q-Q plots. All image analyses, biochemical, and tensile modulus data were analyzed by 2 and 3-way ANOVA using Tukey's t-test for post hoc analysis (SigmaPlot 14). Engineered 6 week clamped mechanical stress and strain data were analyzed by 1-way ANOVA with Tukey's t-test for post hoc analysis (SigmaPlot 14). Biochemical and collagen fiber diameter correlations were analyzed by Pearson's correlation. For all tests, p < 0.05 was considered the threshold for statistical significance. All data are expressed as mean ± standard error (S.E.M.).
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3

Kinetic Analysis of Protein Recruitment

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The F test was used for regression analysis to gain rate constants using a SigmaPlot 14 software algorithm. The F test is a null hypothesis test indicating that the simpler equation is correct. An F ratio is computed that compares the relative difference in the sum of squares of the two fits to the relative increase in the number of degrees of freedom. If F>>1, then the null hypothesis is rejected. In our case, when single and double exponential fits of the kinetic curves were compared, all curves showed F<1.0. All APE1 recruitments and dissociations showed single exponential kinetics. The 95% prediction band for a single exponential fit are shown in Supplementary figures to demonstrate that the data with standard errors were between the 95% band. All PARP1 recruitments showed double exponential kinetics. Statistical data analyses, t-test and ANOVA were performed in SigmaPlot 14.
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4

Improving NICU Care Outcomes

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Data are shown as mean ± SD, number, or rates. Data are graphed versus month and year, or versus year. The categorical data from the time after full NICU implementation is compared to the 3 quarters of 2015 prior to the full NICU implementation using Fisher’s Exact Test (Sigmaplot 14.0, Carlsbad, CA). Linear regression was used to compare 2 variables, for example, NICU survival versus number of NICU admissions (Sigmaplot 14.0). The slopes of NMR versus year for the time period 2006–2015 and 2016–2019 were compared using analysis of covariance (GraphPad Prism 9.0). A p-value of <0.05 is considered significant.
Details of the Development and Implementation of the Level III NICU at GPHC:
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5

Experimental Data Analysis Protocol

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SigmaPlot 14.0 software was used for experimental data processing and drawing. The statistical representation of experimental results was mean ± standard error (mean ± SE). For the in vitro experiments, the significant difference between groups was calculated using a t-test in SigmaPlot software. Whereas for In vivo experiments, One-way ANOVA plus post-hoc test (Scheffe method) was employed to calculate the P value. The P values less than 0.05 were considered statistically significant. Image J was employed for quantifying Western Blot and RT-PCR data, while SigmaPlot 14.0 was used for statistical analysis.
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6

Oxidative Potential and Developmental Toxicity

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Data was blank corrected by laboratory blank and blank filter extracts where noted. All figures were generated with SigmaPlot 14.0 (San Jose, CA). For oxidative potential and chemical characterization data, histograms and statistical significance calculations (one- or two-way analysis of variance (ANOVA) tests and pairwise multiple comparison procedures (Hom-Sidak method) with significance set at p<0.05) were completed in SigmaPlot 14.0. For developmental toxicity screening in zebrafish, statistical significance was computed as previously reported.15 (link)
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7

Overcoming ABCG2-mediated Chemoresistance

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The MDCKII cells were seeded as described in the WST-1 assay section, and treated with increasing concentrations of mitoxantrone (0.01 µM up to 50 µM) or solvent (0.1% DMSO) for 48 h. In order to detect a reversal of the ABCG2-mediated chemoresistance, novel ABCG2 interacting compounds (QCc, DMQCa, DMQCb, DMQCc, and DMQCd) were added to mitoxantrone in 1.0 µM for 48 h. Afterwards, the WST-1 assay was performed as described [37 (link)]. The left-shift factor was calculated from IC50 minus SEM from the mitoxantrone alone treatment by IC50 plus SEM from combined use of mitoxantrone and carborane-based derivatives (QCc, DMQCa, DMQCb, DMQCc, and DMQCd). Data were tested for normality by the Shapiro Wilk test and significant differences between the mitoxantrone treatment groups were determined by two-way ANOVA with the Holm-Šidák post hoc test using SigmaPlot 14.5. The IC50 values were defined as 50% reduced cell viability and calculated with SigmaPlot 14.5 by nonlinear regression. All data were normalized against the vehicle control and were expressed as mean ± SEM, calculated from at least three independent experiments.
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8

Cocaine Addiction Behavioral Dynamics

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The parameters measured were the latency to the onset of activity, the duration of activity, the calculated cocaine level at the onset of activity (the satiety threshold), and the calculated cocaine level at the cessation of activity (the remission threshold). These data were collected from multiple rats over multiple sessions, however, as rats lost catheter patency the overall number of animals used fluctuated. All the parameters were analyzed using SigmaPlot 14.5. ANOVA was conducted to compare SCH23390 doses and statistical significance was determined by comparing the values to the vehicle.
Following administration of h2E2 the same parameters were collected each day for 21 days, and statistical significance of these values were compared to the baseline using a One Way ANOVA. Baseline values were collapsed across days. The mean of 3–5 sessions for each of the 7 rats was calculated. These values were averaged. The ANOVA was conducted using SigmaPlot 14.5.
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9

Autofluorescence of Compounds in ABCG2 Assay

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The autofluorescence of all compounds was investigated with a modified Hoechst 33342 accumulation assay. The MDCKII-hABCG2 and MDCKII-WT cells were seeded and treated as previously described for the Hoechst accumulation assay. Afterwards, the cells were washed twice with ice-cold PBS buffer, lyzed with 100 µL/well 0.1% (v/v) SDS/PBS, and, subsequently, the intracellular fluorescence was measured by spectrofluorometer (360 nm excitation/465 nm emission wavelengths, Tecan Infinite F200 Pro, Crailsheim, Germany). The protein amounts were quantified by BCA assay. For this approach, the Hoechst 33342 dye was not added. The background of non-treated cells was subtracted from the measured intracellular fluorescence and was correlated to the protein amount for MDCKII-hABCG2 or MDCKII-WT cells, respectively. All data were expressed as mean ± SEM and tested for normality by the Shapiro Wilk test using SigmaPlot 14.5. An autofluorescence was defined as the significant increase in total intracellular relative fluorescence unit (RFU) in comparison to the solvent-treated control and was determined by one-way ANOVA with Holm-Šidák post hoc test using SigmaPlot 14.5. As the negative control, the ABCG2-Inhibitor Ko143 (1 µM) was added.
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10

Comprehensive Statistical Analysis Methods

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GraphPad Prism 8 software (San Diego, CA) was used for statistical analyses. For comparing two groups, unpaired t tests were used. For comparisons between three or more groups, one-way analysis of variance (ANOVA) followed by Tukey’s post-hoc test for multiple comparisons between treatment groups was conducted. For analyzing the nest building behavior, a two-way repeated measures ANOVA was performed using the Sigma Plot 14 (San Jose, CA) software. Differences were accepted as significant at p < 0.05. Statistical details of each experiment are provided within the relevant result and legend sections.
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