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Additional file 3: Figure S1: Sensitivity analysis demonstrating the association of dyslipidemia with COVID-19 mortality.

Additional file 2: Fig. S1. Core genome phylogeny for ST239 and ST59. Fig. S2. Regression of root-to-tip distance against sampling time for core genome alignments. Fig. S3. Global core genome phylogenies for ST239 and ST59. Fig. S4. Shared core and accessory genes amongst Chinese ST239 and ST59 isolates. Fig. S5. Conservation of accessory genome homology groups (HGs) across the Chinese ST239 and ST59 isolates. Fig. S6. Presence/absence of mobile genetic elements (MGEs) amongst Chinese ST239 and ST59 isolates. Fig. S7. Presence/absence of antimicrobial resistance genes amongst Chinese ST239 and ST59 isolates. Fig. S8. Presence/absence of virulence genes amongst Chinese ST239 and ST59 isolates. Fig. S9. Number of resistance (AMR) genes carried between ST sub-lineages. Fig. S10. Changing trends of antimicrobial resistance (AMR) mutations/elements within ST239 and ST59 lineages over time. Fig. S11. Number of virulence genes carried between ST sub-lineages and within ST239 and ST59 sub-lineages. Fig. S12. Trends of virulence mutations/elements within Chinese ST239 and ST59 lineages over time. Fig. S13. Core genome phylogeny for ST239 annotated for sasX. Fig. S14. Methicillin resistance acquisition analyses. Fig. S15. Presence absence of virulence genes against cell lysis phenotype. Fig. S16. Colony counts at 0 hours and 96 hours for three ST59 isolates (wild-type and knock-out) compared to two possible ST239 control strains. Table S2. Inferred tMRCA, clock rates and marginal likelihoods inferred by Bayesian dating analyses. Table S3. The distribution of mobile genetic elements (MGEs) in different sub-lineages. Table S4. Bonferroni corrected p-values following fitting of a generalized linear model (GLM) for VFDB virulence gene presence / absence against cell lysis phenotype. Table S5. Relative adaptive difference (S), fitness (F) and fitness cost (C) estimated from the in vitro competition experiment between ST59-WT and ST59 ��chp.

Additional file 1: Table SI: Quality assessment of included studies (cohort studies)

Additional file 3: Figure S1: Sensitivity analysis demonstrating the association of dyslipidemia with COVID-19 mortality.

Additional file 2: Table SII: Quality assessment of included studies (case–control studies)

Additional file 2: Table SII: Quality assessment of included studies (case–control studies)

Hepatocellular carcinoma (HCC) is one of the most common neoplasms, and metastasis is the most important feature for HCC-related deaths. Mounting evidence implies the dynamic regulatory role of SIRT2, a histone deacetylase, in cancer cells. Unfortunately, the role of SIRT2 and the antitumor activity of its inhibition are not known in HCC. The present study aims to evaluate the biological function of SIRT2 in HCC and identify the target of SIRT2 as well as evaluate its therapeutic efficacy. We found that SIRT2 was upregulated in HCC tissues compared to adjacent normal tissues, and this was correlated with reduced patient survival. Although CCK8 and colony-formation assays showed that SIRT2 inhibiton marginally promotes proliferation in HCC cell lines, SIRT2 knockdown decreased the invasion of HCC cells. We demonstrated that downregulation of SIRT2 could inhibit its downstream target phosphoenolpyruvate carboxykinase 1 and glutaminase, which is related to mitochondrial metabolism and the E-Cadherin pathway. These results demonstrate, for the first time that downregulation of SIRT2 decreases migration as well as invasion in human HCC cells, indicating that inhibiting SIRT2 may be an effective therapeutic strategy for treating HCC.