Digital Therapeutics: Emerging New Therapy for Nonalcoholic Fatty Liver Disease.

The increased prevalence of nonalcoholic fatty liver disease (NAFLD) worldwide is particularly worrisome, as no medication has been approved to treat the disease. Lifestyle modifications aimed at promoting weight loss and weight maintenance remain the current first-line treatment for NAFLD. However, due to the lack of standard and scientific guidance and out-of-hospital supervision, long-term outcomes of lifestyle interventions for patients with NAFLD are often unsatisfactory. In addition, the COVID-19 pandemic aggravated this dilemma. At the same time, digital therapeutics (DTx) are expected to be a new method for the convenient management and treatment of patients with NAFLD and are attracting a great deal of attention. DTx, which provide evidence-based medicine through software programs for remote intervention in preventing, treating, or managing diseases, overcome the drawbacks of traditional treatment. The efficacy of the approach has already been demonstrated for some chronic diseases, but DTx have not been fully developed for NAFLD. This study reviews the concepts, clinical value, and practical applications related to DTx, with an emphasis on recommendations based on unmet needs for NAFLD. A better understanding of the current state will help clinicians and researchers develop high-quality, standardized, and efficient DTx products, with the aim of optimizing the prognosis of patients with NAFLD.

Longitudinal proteomic investigation of COVID-19 vaccination.

Although the development of COVID-19 vaccines has been a remarkable success, the heterogeneous individual antibody generation and decline over time are unknown and still hard to predict. In this study, blood samples were collected from 163 participants who next received two doses of an inactivated COVID-19 vaccine (CoronaVac®) at a 28-day interval. Using TMT-based proteomics, we identified 1,715 serum and 7,342 peripheral blood mononuclear cells (PBMCs) proteins. We proposed two sets of potential biomarkers (seven from serum, five from PBMCs) at baseline using machine learning, and predicted the individual seropositivity 57 days after vaccination (AUC = 0.87). Based on the four PBMC's potential biomarkers, we predicted the antibody persistence until 180 days after vaccination (AUC = 0.79). Our data highlighted characteristic hematological host responses, including altered lymphocyte migration regulation, neutrophil degranulation, and humoral immune response. This study proposed potential blood-derived protein biomarkers before vaccination for predicting heterogeneous antibody generation and decline after COVID-19 vaccination, shedding light on immunization mechanisms and individual booster shot planning.