Nonalcoholic fatty liver disease (NAFLD) is rapidly becoming the most common cause of chronic liver disease due to an increase in the prevalence of obesity. The development of NASH leads to an increase in morbidity and mortality. While the first line of treatment is lifestyle modifications, including dietary changes and increased physical activity, there are no approved pharmacological treatment agents for NAFLD and NASH currently. Due to its complex pathophysiology, different pathways are under investigation for drug development with the focus on metabolic pathways, inflammation, and slowing or reversing fibrosis. There are several agents advancing in clinical trials, and promising results have been seen with drugs that affect hepatic steatosis, inflammation, and fibrosis. This review will provide an overview on NAFLD and some of the mechanisms of disease that are being targeted with pharmacologic agents.

Sepsis is a leading cause of death and is the most expensive condition to treat in U.S. hospitals. Despite targeted efforts to automate earlier detection of sepsis, current techniques rely exclusively on using either standard clinical data or novel biomarker measurements. In this study, we apply machine learning techniques to assess the predictive power of combining multiple biomarker measurements from a single blood sample with electronic medical record data (EMR) for the identification of patients in the early to peak phase of sepsis in a large community hospital setting. Combining biomarkers and EMR data achieved an area under the receiver operating characteristic (ROC) curve (AUC) of 0.81, while EMR data alone achieved an AUC of 0.75. Furthermore, a single measurement of six biomarkers (IL-6, nCD64, IL-1ra, PCT, MCP1, and G-CSF) yielded the same predictive power as collecting an additional 16 hours of EMR data(AUC of 0.80), suggesting that the biomarkers may be useful for identifying these patients earlier. Ultimately, supervised learning using a subset of biomarker and EMR data as features may be capable of identifying patients in the early to peak phase of sepsis in a diverse population and may provide a tool for more timely identification and intervention.

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Background. Since October 2021, there have been more than 500 cases of severe hepatitis of unknown origin in children reported worldwide, including 180 cases in the U.S. The most frequently detected potential pathogen to date has been adenovirus, typically serotype 41. Adenovirus is known to cause a self-limited infection in the immunocompetent host. However, in immunosuppressed individuals, severe or disseminated infections may occur. Method. We present the case of a two-year-old female who presented with cholestatic hepatitis and acute liver failure (ALF). Work up for etiologies of ALF was significant for adenovirus viremia, but liver biopsy was consistently negative for the virus. The risk for severe adenoviral infection in the setting of anticipated immunosuppression prompted us to initiate cidofovir to decrease viral load prior to undergoing liver transplantation. Result. Our patient received a successful liver transplant, cleared the viremia after 5 doses of cidofovir, and continues to maintain allograft function without signs of infection at the time of this report, 5 months posttransplant. Conclusion. Recent reports of pediatric hepatitis cases may be associated with adenoviral infection although the exact relationship is unclear. There is the possibility of the ongoing SARS-CoV-2 environment, or other immunologic modifying factors. All patients presenting with hepatitis or acute liver failure should be screened for adenovirus and reported to state health departments. Cidofovir may be used to decrease viral load prior to liver transplantation, to decrease risk of severe adenoviral infection.