Honokiol Mitigates Metabolic-Associated Fatty Liver Disease by Regulating Nrf2 and RIPK3 Signaling Pathways.

BACKGROUND/AIMS:  Metabolic-associated fatty liver disease (MAFLD) is a common cause of chronic liver disease worldwide. However, there is currently no recognized effective drugs for treating it. MATERIALS AND METHODS:  In this study, we investigated the efficacy of Honokiol (HNK) in vitro for mitigating MAFLD. Then, 0.4 mM palmitic acid (PA) and LO2 cells were used to establish the MAFLD model. The protective effect of HNK on MAFLD was confirmed by Oil Red O staining and cell counting kit (CCK-8) assay in LO2 cell line. Quantitative real-time polymerase chain reaction (qRT-PCR) and Western blot were carried out to analyze the regulatory role of HNK on Nrf2 and RIPK3 signaling pathways. The effect of HNK and its downstream signaling pathways on oxidative stress were verified by the detection of reactive oxygen species (ROS), malondialdehyde (MDA), catalase (CAT), and superoxide dismutase (SOD). The concentration of IL-1ß, IL-6L, and TNF-α was assessed by enzyme-linked immunosorbent assay (ELISA). RESULTS:  The middle concentration of HNK (50 µmol/L) was selected as the best option for inhibiting lipidosis and oxidative stress in MAFLD models. Honokiol mitigates MAFLD via activation of nuclear factor E2-related factor 2 (Nrf2) signaling pathways in vitro. Honokiol suppressed MAFLD via activating the Nrf2 signaling pathway to play an antioxidant and anti-inflammatory role. Also, HNK regulates Nrf2 and RIPK3 signaling pathways to mitigate MAFLD. CONCLUSION:  Our results showed that HNK may suppress the oxidative stress and inflammation in MAFLD via activation of Nrf2 signaling pathway.

Risk Factors and Prognosis Analysis of Upper Gastrointestinal Bleeding in Patients With Acute Severe Cerebral Stroke.

GOALS: We aim to explore the relationship between the use of proton pump inhibitors (PPIs) and upper gastrointestinal bleeding (UGIB). We develop a nomogram model to predict mortality in critically ill stroke patients. STUDY: This is a retrospective study based on the MIMIC IV database. We extracted clinical information including demographic data, comorbidities, and laboratory indicators. Univariate and multivariable logistic regressions were used to assess and identify risk factors for the occurrence of UGIB and for the in-hospital mortality of critically ill stroke patients. The resulting model was used to construct a nomogram for predicting in-hospital mortality. RESULTS: Five thousand seven hundred sixteen patients from the MIMIC-IV database were included in our analysis. UGIB occurred in 109 patients (1.9%), whereas the PPI use rate was as high as 60.6%. Chronic liver disease, sepsis, shock, anemia, and increased level of urea nitrogen were independent risk factors for the occurrence of UGIB in severe stroke patients. We identified age, heart failure, shock, coagulopathy, mechanical ventilation, continuous renal replacement therapy, antiplatelet drugs, anticoagulation, simplified acute physiology score-II, and Glasgow coma score as independent risk factors for in-hospital mortality in severe stroke patients. The C-index for the final nomograms was 0.852 (95% confidence interval: 0.840, 0.864). CONCLUSIONS: We found that the overall rate of UGIB in severe stroke patients is low, whereas the rate of PPI usage is high. In our study, PPI was not identified as a risk factor for the occurrence of UGIB and UGIB was not associated with all-cause mortality. More clinical trials are needed to evaluate the benefits of using PPI in critically ill stroke patients.