C oronavirus disease 2019 (COVID-19) is a highly contagious and life-threatening infection caused by the severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2). 1 Identifying modifiable risk factors for COVID-19 would be of substantial public health benefit.To date, several studies exploring the association between use of acid suppressants and COVID-19 have produced conflicting results, 2-6 which makes it difficult to determine whether there is indeed an increased risk of SARS-CoV-2 infection and death for users of acid suppressants. Thus, we aimed to clarify the potential impact of acidsuppressant treatment on the risk of SARS-CoV-2 infection and death in patients with COVID-19.

Background and objectiveUpregulated T-cell immunoglobulin and mucin domain containing molecule-3 (Tim-3) in hepatitis B virus (HBV)-specific CD8+ T-cells contributes to CD8+ T-cell exhaustion during chronic HBV infection. The membrane-bound Tim-3 can be cleaved from the cell surface by sheddase, yielding soluble Tim-3 (sTim-3). This study investigated serum sTim-3 levels in patients with chronic HBV infection of various liver diseases.MethodsSerum sTim-3 levels were quantitatively determined in 288 patients with chronic HBV infection of various liver diseases. The sTim-3 levels were analyzed in relation to liver diseases including HBV-related hepatocellular carcinoma (HCC) and overall survival of HCC patients.ResultsSerum sTim-3 levels in the patients with chronic HBV infection were significantly elevated compared with healthy controls (P<0.001) and the levels from asymptomatic HBV carrier status, chronic hepatitis, liver cirrhosis to HCC were progressively increased. Serum sTim-3 levels were closely associated with the severity of liver function abnormalities. Importantly, serum sTim-3 levels were independently associated with HCC risk (OR, 4.310; 95% CI, 2.141–8.676, P<0.001) in comparison to non-HCC diseases in chronic HBV infection and significantly associated with the overall survival of HCC patients, with a level >3000 pg/mL being related to shorter overall survival than a level ≤3000 pg/mL (P=0.019).ConclusionSerum sTim-3 is involved in disease progression and HCC development in chronic HBV infection and its quantitative determination may be potentially used as a marker for monitoring the disease progression and predicting the HCC prognosis in chronic HBV infection.

Hepatocellular death contributes to progression of alcohol–associated (ALD-associated) and non–alcohol-associated (NAFL/NASH) liver diseases. However, receptor-interaction protein kinase 3 (RIP3), an intermediate in necroptotic cell death, contributes to injury in murine models of ALD but not NAFL/NASH. We show here that a differential role for mixed-lineage kinase domain–like protein (MLKL), the downstream effector of RIP3, in murine models of ALD versus NAFL/NASH and that RIP1-RIP3-MLKL can be used as biomarkers to distinguish alcohol-associated hepatitis (AH) from NASH. Phospho-MLKL was higher in livers of patients with NASH compared with AH or healthy controls (HCs). MLKL expression, phosphorylation, oligomerization, and translocation to plasma membrane were induced in WT mice fed diets high in fat, fructose, and cholesterol but not in response to Gao-binge (acute on chronic) ethanol exposure. Mlkl –/– mice were not protected from ethanol-induced hepatocellular injury, which was associated with increased expression of chemokines and neutrophil recruitment. Circulating concentrations of RIP1 and RIP3, but not MLKL, distinguished patients with AH from HCs or patients with NASH. Taken together, these data indicate that MLKL is differentially activated in ALD/AH compared with NAFL/NASH in both murine models and patients. Furthermore, plasma RIP1 and RIP3 may be promising biomarkers for distinguishing AH and NASH.

Background: Hepatocellular carcinoma (HCC) is the most common liver cancer and the mechanisms of hepatocarcinogenesis remain elusive. Objective: This study aims to mine hub genes associated with HCC using multiple databases. Methods: Data sets GSE45267, GSE60502, GSE74656 were downloaded from GEO database. Differentially expressed genes (DEGs) between HCC and control in each set were identified by limma software. The GO term and KEGG pathway enrichment of the DEGs aggregated in the datasets (aggregated DEGs) were analyzed using DAVID and KOBAS 3.0 databases. Protein-protein interaction (PPI) network of the aggregated DEGs was constructed using STRING database. GSEA software was used to verify the biological process. Association between hub genes and HCC prognosis was analyzed using patients’ information from TCGA database by survminer R package. Results: From GSE45267, GSE60502 and GSE74656, 7583, 2349, and 553 DEGs were identified respectively. A total of 221 aggregated DEGs, which were mainly enriched in 109 GO terms and 29 KEGG pathways, were identified. Cell cycle phase, mitotic cell cycle, cell division, nuclear division and mitosis were the most significant GO terms. Metabolic pathways, cell cycle, chemical carcinogenesis, retinol metabolism and fatty acid degradation were the main KEGG pathways. Nine hub genes (TOP2A, NDC80, CDK1, CCNB1, KIF11, BUB1, CCNB2, CCNA2 and TTK) were selected by PPI network and all of them were associated with prognosis of HCC patients. Conclusion: TOP2A, NDC80, CDK1, CCNB1, KIF11, BUB1, CCNB2, CCNA2 and TTK were hub genes in HCC, which may be potential biomarkers of HCC and targets of HCC therapy.