*4.10. Statistical Analysis of Biochemical Data*

The researchers were blinded for all preliminary analyses. The atherogenic index of plasma was calculated using log(triglycerides/HDL-cholesterol) (Dobiášová and Frohlich 2001) [51]. The insulin-resistance homeostasis model assessment (HOMA) index was calculated as (fasting insulin (mU/L) × fasting glucose (mmol/L))/22.5 (Matthews, Hosker et al., 1985) [52]. The OGTT was assessed by the fasting glucose measure (mmol/L) and the 2-h glucose measure (mmol/L). Participants who withdrew from the study were excluded from the statistical analysis. For those who completed the study, all participant demographics, as well as plasma, urine, and dietary data were expressed as the median (25th and 75th percentile) and were tested for normality using the Shapiro–Wilk test. Gender across the three treatment groups was compared using a chi-squared test. Baseline, finish, and change data were compared across the three treatment groups using ANOVA for normally distributed data or Kruskal–Wallis for nonparametric data. If a significant difference among the three groups existed, further post hoc tests were applied: Tukey's test for parametric data and Dunn's test for nonparametric data, with statistical significance assessed as *p* < 0.05. JMP Pro was used for plasma and dietary data statistical analyses.

In Study 2, SPSS Version 21 was used for analysis. For all metabolic and inflammatory outcome variables, an ANCOVA was used to test for a treatment effect of the SXRG extract on the six-week and twelve-week outcome measures using four groups. In all analyses, the baseline value was used as the only covariate to control for baseline values. The six-week to twelve-week measures were not analyzed separately due to potential carryover effects; instead, the baseline to twelve weeks was considered, which used the true baseline as a covariate.

The relationship between the different genera and the outcome variables at baseline was assessed using Spearman's correlation. Spearman's correlations were also used to determine whether the change in cytokines was related to the change in any specific gut microbiota genera.

#### **5. Conclusions**

Favorable effects on non-HDL cholesterol levels were only seen in the study population, with baseline elevated levels in Study 1. SXRG84 had a beneficial effect on inflammatory markers in overweight and obese participants. The relationship to gut flora shifts is complex, and more work is needed. Importantly, there were no changes in blood counts or other markers that indicated a compromise in health. There is potential for SXRG84 supplements to reduce inflammatory markers connected to metabolic disorders in overweight and obese participants.

**Supplementary Materials:** The following are available online at https://www.mdpi.com/article/ 10.3390/md20080500/s1, Figure S1: Flow diagram of study participants in study 1, Figure S2: Participant diagram for study 2, Figure S3: The different genera of bacteria are shown with the change in bacteria in the placebo group in blue and the change in the average active groups shown in yellow, Table S1: Comparison of Dietary Intake between three treatment groups, Table S2: Urinary F2-Isoprostane levels per treatment group for overweight and obese participants. Study 1, Table S3: Adherance to dietary guidelines for study population at each of the three timepoints, Table S4: blood count data from Study 1, post intervention across the three groups, including change data. Average change in before versus after for each treatment of 2 g, 4 g and placebo groups, and final levels.

**Author Contributions:** Conceptualization, L.A.R., B.J.M. and P.W.; methodology, L.A.R.; formal analysis, L.A.R.; investigation, P.W. and B.J.M.; resources, B.J.M. and P.W.; data curation, L.A.R.; writing—original draft preparation, L.A.R. and J.H.F.; writing—review and editing, J.H.F., B.J.M., L.A.R. and P.W; supervision, B.J.M.; project administration, L.A.R.; funding acquisition, B.J.M. and P.W. All authors have read and agreed to the published version of the manuscript.

**Funding:** This research was funded by the University of Wollongong, Science, Medicine and Health Research Partnership Grants (Gut, skin and metabolic health study of seaweed dietary fibers— BioBelly Study 2, 2017).

**Institutional Review Board Statement:** The study was conducted according to the guidelines of the Declaration of Helsinki and approved by the University of Wollongong Human Research Ethics Committee (approval CT13/002 and approval 2017/101) and registered with the Australian New Zealand Clinical Trials Registry (ACTRN12615001057572 and ACTRN12617001010381).

**Informed Consent Statement:** Informed consent was obtained from all subjects involved in the study.

**Data Availability Statement:** Data are not publicly available due to participant confidentiality as defined by ethics committee. De-identified data are available on request from the corresponding author. **Acknowledgments:** We would like to acknowledge our participants for taking part in Study 1 and Study 2; Trevor Mori for the F2 isoprostane analysis; and Nicola Zamai and William Paton for their research assistant support and Eluned Price for assistance with the dietary analysis. We would also like to acknowledge to Dan Harmelin for his guidance.

**Conflicts of Interest:** P.W. is the CEO of Venus Shell Systems, which provided the extract for this study.
