Spss 22.0 analysis software

All experiments were repeated at least three times or more different repetitions. SPSS 22.0 analysis software was used for the statistical analyses, and the differences between groups were calculated via one-way ANOVA or using the Chi-square test. The data are presented as the means ± standard deviations (x ± sd). *P < 0.05 was considered to indicate a significant difference, while **P < 0.01 represented a highly significant difference.

All in vitro experiments were repeated three times independently, and three random high-power fields were selected for quantitative analysis in each experiment. All data were presented as mean ± SD. Two-tailed unpaired Student's t-test was used for comparing two group parameters. One-way analysis of variance (ANOVA) was used for comparing multiple group parameters. Homogeneity of variance was tested first, and then, the differences between groups were assessed by post hoc multiple comparisons. Specifically, if no heterogeneity was observed, the Bonferroni test was used to assess the differences between groups. However, if heterogeneity did exist, the Welch test was used to test the equality of means and the Dunnett's T3 was used to assess the differences between groups. The investigators were blinded to allocation during experiments and outcome assessment. The level of significance was set at P < 0.05 and indicated by “^∗” compared as denoted by bar, P < 0.01 was indicated by “^∗∗” compared as denoted by bar. All data analysis was conducted with SPSS 22.0 analysis software (SPSS Inc.).

Data were expressed as mean ± standard deviation. Student’s t test was applied for comparisons between two groups. One-way analysis of variance (ANOVA) was used for comparisons among three or more groups. P < 0.05 was considered significantly different. The symbol “*” denoted p < 0.05, and “**” denoted p < 0.01. All data analysis was conducted with SPSS 22.0 analysis software (SPSS Inc, Chicago, IL, USA).

Data were processed using Microsoft excel software and the inhibition rate was calculated using the formula IR(%) = (1 − N/N₀) × 100, where N and N₀ were the algal density of the experimental group and the control group, respectively. Statistical analysis was performed using SPSS 22.0 analysis software and the one-way ANOVA tested the significance of algae inhibition in each experimental group; multiple comparisons between groups were performed using the least significant difference (LSD) method, with p < 0.05 indicating significant differences and p < 0.01 indicating highly significant differences.