Rstudio

The experiment was a completely randomized design, with two treatments and three replications. Statistical analysis was performed using RStudio (v2021.9.0.351; Posit Software, PBC; Boston, MA, USA). The parameter means of each replicate in each cultivar by treatment combination were analyzed for the EDTF, harvest, and postharvest measurements (n = 3). Each sample was considered a replicate in the cannabinoid data (n = 3). Unpaired, two-tailed Student’s t-tests were performed between the 12 h and 13 h treatments for each parameter by cultivar combination. Statistical significance was determined at the p ≤ 0.05 level.

The search results and the study inclusion process were presented following the guideline of Preferred Reporting Items for Systematic Reviews and Meta-analyses (PRISMA) [36 (link)], and specifically, the extension for scoping review (PRISMA-ScR) [37 (link)]. See S2 File for the PRISMA-ScR checklist for this report. Extracted data were further tabulated into data tables (See S3 File) using Microsoft Excel 365 (Microsoft Corp, WA, USA). Descriptive and bibliometric analyses were conducted using Microsoft Excel 365 and R Studio (Posit Software, UK), running with R version 4.2.2 [38 ]. Network analysis was performed using the visNetwork package in R [39 ] to visualise the complex relationships among the data items.
The reviewers adopted a quantitative approach to analyse the extracted data’s bibliometrics, including authors, institutions, publications, references, MeSH terms, and research impacts based on Google Scholar citations to explore the translational status of the field. The potential beneficial actions and positive outcomes of RBAC ingestion on health and the possible applications for any disease conditions were also illustrated in tables and graphs.

In seven different study group settings, statistical analysis of the N-linked glycan data was performed between non-neoplastic colon samples (four pools of paired control samples), subgroups of MSI CRC samples, according to the tumor stage and BRAF mutation status, and stage II BRAF^V600E wt MSI CRCs were compared to stage II BRAF^V600E wt MSS tumors (Table 1). Both the relative abundances of proposed monosaccharide compositions and glycan classes were analyzed separately within these study groups. For statistical analyses, the nonparametric Kruskal–Wallis test was first used to verify the equality of the mean ranks of the groups, and the Mann–Whitney U test, along with the Benjamini–Hochberg false discovery rate (FDR) correction method [26 (link)], was then used for pairwise comparisons of the groups. RStudio (version 2022.07.2-576; Posit Software, Boston, MA, USA) was used for statistical analyses, and p-value < 0.05 was considered statistically significant. The results are shown as mean relative abundance ± standard error of mean (SEM) for the separately calculated neutral and acidic N-glycan compositions and structural glycan classes.

We used the Drugs@FDA database to identify all oncology indication approvals between February 1, 2018, and December 31, 2023. We then searched FDA approval packages, FDA announcements, and Google, in that order, to ascertain whether RTOR was used (eFigure in Supplement 1). In accordance with the Common Rule, this cross-sectional study was exempt from ethics review and informed consent because it used public nonidentifiable data. We followed the STROBE reporting guideline.
Using Drugs@FDA, we identified approval type (supplemental or original), first-in-class status,⁴ regulatory approval pathway (accelerated or traditional), efficacy end points (clinical or surrogate, per FDA definitions),⁵ sample size, and National Clinical Trial (NCT) numbers of pivotal trials supporting FDA approval. With NCT numbers, we searched ClinicalTrials.gov to extract trial design characteristics, including use of randomization, comparator group, and blinding, and start and primary completion dates. For indications approved based on only surrogate end points, we ascertained whether postmarketing studies were required to confirm clinical effectiveness.
Analyses were performed using Fisher exact and Mann-Whitney tests in RStudio, version 2023.09.1 + 494 (Posit Software). Two-tailed P < .05 was considered statistically significant.

Quantified lipid species concentrations were loaded into Perseus (version 1.6.15.0, Max Planck Institute for Biochemistry, Martinsried, Germany) and log2 transformed. Nonlinear iterative partial least squares (NIPALS) principal component analysis (PCA) was performed in RStudio (version 2022.07.1 + 554, Posit PBC, Boston, MA, USA), with 70% valid values in at least one patient. That corresponded to 13 lipid classes, 122 lipid species with the same fatty acyl chain length and extent of unsaturation, and 327 individual lipid species (Supplementary Table S2a–c). Results of the NIPALS PCA are visualized as scatter plots (Figure 5). Further testing was performed with Welch’s test. The results were filtered for p-value and fold-change significance (p-value ≤ 0.05, two-fold change). Significant lipid species are listed for each patient in Supplementary Table S3a–d.