Simca p v12

Statistical analysis of behavior measurements involved two-way repeated-measures ANOVA followed by a post-hoc Bonferroni test. Multivariate statistical analysis including principal component analysis (PCA) and partial least-squares discriminant analysis (PLS-DA) was used to analyze data from MS or NMR spectra and the response variable by SIMCA-P⁺ v12.0 (Umetrics, Umeå, Sweden). All analyses involved using IBM SPSS v23.0. Descriptive statistics are presented as mean ± SD, median (range), or number (%). Student’s t, Fisher’s exact, or chi-square test was used to compare groups. Paired t test or Wilcoxon signed-rank test was used to compare paired data. All calculated p-values were two-tailed. Statistical significance was defined at p < 0.05.

Metabolites in mycelia of A. flavus A3.2890 cultured in a GMS liquid medium with or without 40 mg/mL D-glucal for 5 d were purified, silyl-derivatized and analyzed with GC-TOF MS as described previously [18 (link)], with minor modifications. The column temperature was held at 100°C for 3 min, and raised to 150°C at a rate of 10°C/min, then to 250°C at 5°C/min, finally to 300°C at 10°C/min, and held for 15 min at 300°C. PLS analysis was performed using SIMCA-P V12.0 (Umetrics, Sweden).

The lipidomic data were processed to the data matrix by the MS-DIAL software before further statistical analysis. MetaboAnalyst 4.0 (http://www.metaboanalyst.ca) and SIMCA-P V12.0 (Umetrics, Umeå, Sweden) were used for univariate and multivariate analysis, respectively. QC and DNA-based normalization methods were applied during data preprocessing. For human subject samples, the FDR- adjust P-value < 0.05 and fold change > 1.5 or < 0.67 were set as a criterion for selecting significant features. For Calu-3 cell-based samples, FDR adjust P-value < 0.05 and fold change > 1.25 or < 0.8 used as a cut-off. In multivariate analysis, the partial least squares discriminant analysis was applied to find important variables with discriminative power.
The significant lipid features were identified by searching accurate MS and MS/MS fragmentation pattern data in the MS-DIAL internal lipid database, MassBank of North America (MoNA, http://mona.fiehnlab.ucdavis.edu/), METLIN database (http://metlin.scripps.edu/), and LIPID MAPS (http://www.lipidmaps.org/). For confirmation of lipid identity using authentic chemical standards, the MS/MS fragmentation patterns of the chemical standards were compared with those of the candidate lipids measured under the same LC–MS condition. Pathway analysis was performed by Metaboanalyst and KEGG mapper.

The direct injection MS metabolomic analysis was conducted by using an AB Sciex 4000 QTrap system (AB Sciex, Framingham, MA, USA). The equipped ion source was an electrospray ionization source. A 20 μl sample was injected for each run. The mobile phase was 80% acetonitrile aqueous solution. The initial flow rate was 0.2 ml/min. Afterward, the flow rate was set to 0.01 ml/min within 0.08 min, kept constant until 90 s, returned to 0.2 ml/min within 0.01 min, and held constant for another 30 s. The ion spray voltage was 4.5 kV. The curtain gas pressure was set at 20 psi. A 35 psi pressure was applied to the ion source gas 1 and gas 2. The auxiliary gas temperature was maintained at 350 °C. Analyst v1.6.0 software (AB Sciex) was used for system control and data collection. ChemoView 2.0.2 (AB Sciex) was used for data preprocessing. Partial least squares discriminant analysis (PLS-DA) was performed by using SIMCA-P v12.0 (Umetrics, Umeå, Sweden).

All lipidomics data was processed to a usable data matrix by the MS-DIAL software for further analysis 35 (link), 36 (link). MetaboAnalyst 5.0 (http://www.metaboanalyst.ca) and SIMCA-P V12.0 (Umetrics, Umeå, Sweden) were used for univariate and multivariate analyses, respectively. Prior to statistical analysis, the data matrix needs to perform QC or DNA-based normalization for better comparison 35 (link)-37 (link). The significant lipid features were identified by matching accurate MS and MS/MS fragmentation pattern data from the public database such as the MS-DIAL internal lipid database 35 (link), MassBank of North America (MoNA, http://mona.fiehnlab.ucdavis.edu/), METLIN database (http://metlin.scripps.edu/), and LIPID MAPS (http://www.lipidmaps.org/). For confirmation of lipid identity using authentic chemical standards, the MS/MS fragmentation patterns of the chemical standards were compared with those of the candidate lipids measured under the same LC-MS condition. MetaboAnalyst and KEGG mapper were used to perform significant lipids pathway analyses 38 (link).