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Confidence Intervals for Regression Parameters

Taken together, these data demonstrate for the first time, to our knowledge, that oral supplementation with (https://aprel-vologda.ru/hack/?patch=9724) the probiotic Lp299v improves vascular endothelial function in men with CAD for both conduit and resistance vessels through increasing NO bioavailability while concomitantly reduces systemic inflammation. These effects were observed, despite no significant favorable changes in traditional cardiovascular risk factors, suggesting that Lp299v supplementation may favorably impact vascular health at least, in part, through novel, yet-to-be-identified mediators. This concept is supported by clear differences in the plasma metabolite profiles when comparing pre- and post-Lp299v supplementation samples using 2-factor principal component analysis. Additionally, our in vivo and ex vivo vessel data suggest Lp299v’s favorable effects are independent of TMAO.

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Figure 2. Two-way principal component analysis of untargeted metabolite profiling performed on paired preprobiotic and postprobiotic supplementation plasma samples. Squares represent pre-Lactobacillus plantarum 299v (Lp299v) samples, and triangles represent post-Lp299v samples.

Background – In SigmaPlot (https://aprel-vologda.ru/hack/?patch=1803), we currently provide the (asymptotic) standard errors for the best-fit parameters in the nonlinear regression report. These errors measure the variability in the value of our parameter estimates due to the uncertainties in the observation measurements. However, we do not provide the user with a measure of the accuracy of our estimates to the true parameter values. That is the purpose of confidence intervals.

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We performed a paired t test to look for those OTUs that were significantly increased or decreased based on time point while taking the sample parings into account. All comparisons were performed using the relative abundances of OTUs and plotted in rank abundance. There were 70 overlapping OTUs found to be significantly different between pre- and post-supplementation in their abundance. Nineteen of the 70 OTUs were classified at the genus level. Lactobacillus and Bacillus species were found enriched in posttreatment samples. Before adjustment for multiple comparisons, Lactobacillus reuteri appeared more abundant in most of the posttreatment samples than pretreatment samples from all subjects in the study (P=0/0014; Online Figure IIC). OTU number 380, unclassified taxa in the Lactobacillaceae family, also appeared abundant in the posttreatment samples than pretreatment samples from most subjects (P=0/0028; Online Figure IID). After adjustment for a false discovery rate of 5%, none of the OTUs were significantly different between sampling points. All 70 OTUs with P <0/05 in unadjusted analyses are presented in Online Table I.

SigmaPlot Product Uses – Parameter Confidence Intervals in Reports

This is our default method, called the reduced chi-square method. The second method assumes each weight exactly equals the reciprocal of the population variance (the scale factor is 1). The choice of method is determined by the selection of the check box in the Equation Options dialog that is launched from the Regression Wizard. It is important to verify which method has been selected since it affects the values in the confidence intervals.

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Therefore, our data suggest further studies are needed to determine the identities and mechanisms of gut microbiome-produced metabolites changed by Lp299v supplementation that impact vascular endothelial function and systemic inflammation. One possible contributor in our study is propionate—an SCFA that increased with Lp299v supplementation.

Baker is supported by HL054075 and grant NNX15AD69G from the National Aeronautics and Space Administration. N. Salzman is supported by DK088831 and GM122503.

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We examined the richness, diversity, and taxonomic composition of each sample. Bacterial genus richness ranged from 334 to 530, whereas archaeal genus richness ranged from 8 to 25. There was no significant change in the bacterial genus richness and family level abundance detected in sample categories by time point of measurement (before and after Lp299v supplementation; Online Figure II). The top 9 classes represent ≈67% of each sample’s operational taxonomic units (OTUs; Online Figure III). None of the top 9 classes exhibited a significant change in the OTU proportion after probiotic supplementation (Online Figure IIIB).

Parameter Confidence Intervals in Reports

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SigmaPlot's help is almost entirely for how to use their program

Suboc, and J. Wang received support from T32HL007792. S. Tyagi is supported by T32GM089586.

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Figure 4. Impact of Lactobacillus plantarum 299v (Lp299v) supplementation on systemic inflammatory cytokines. Circulating plasma levels of IL (interleukin)-8 were significantly reduced by Lp299v supplementation (14±7 to 10±4 pg/mL; P=0/01; A). Lp299v similarly reduced systemic IL-12 levels (53±29 to 42±27 pg/mL; P=0/02; B).

Appendix D: When to Use Curve Fitting

During the probiotic intervention phase (Table 2), there were nonsignificant downward trends in total cholesterol (172±37 to 164±32 mg/dL; P=0/18) and LDL cholesterol (96±33 to 89±30 mg/dL; P=0/16) levels, whereas triglyceride (P=0/47) and HDL (high-density lipoprotein; P=0/22) levels showed no appreciable difference. Systolic BP increased after probiotic supplementation (132±11 to 138±12 mm Hg; P=0/04), but diastolic BP (P=0/49), heart rate, weight (P=0/67), and body mass index (P=0/76) remained unchanged. Vancomycin supplementation did not result in any changes in total cholesterol, LDL and HDL cholesterol, triglycerides, weight, body mass index, BP, and heart rate (Table 2).

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SigmaPlot software helps you quickly create exact graphs

Of course, the answer depends on how you plan to use the program. The main advantage of Prism is the data, graphs and analyses are linked. Update or replace the data, and the results all update. This is great for fixing mistakes, but also for running routine analyses. This means you can make a template easily. Just add new data, and you are done.

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A total of 11 006 metabolites were identified in the subject plasma sample. Two thousand nine hundred eighty-nine were identified based on known elution patterns. Results of the 2-factor principal component analysis are shown in Figure 2. A total of 114 compounds differed between preprobiotic and postprobiotic supplementation plasma samples at P<0/05. Twenty-nine were positively identified, whereas 85 remain unknown. After adjustment for multiple testing using Bonferroni correction, no individual metabolite differed significantly between time points.

Our data have several limitations. First, this work represents a small, interventional pilot study designed to determine whether Lp299v supplementation might have favorable effects on vascular function and systemic inflammation in humans and warrants further study. A larger, placebo-controlled randomized trial is necessary to validate our findings and further assess mechanisms of effect.