Current status of research on nutritional support in end-stage liver disease / 临床肝胆病杂志

There is a high prevalence rate of malnutrition in patients with end-stage liver disease, which often promotes disease progression and has a negative impact on the prognosis of patients. This article briefly describes the etiology of malnutrition in end-stage liver disease and introduces the research advances in nutrition screening, evaluation, and treatment in end-stage liver disease in China and globally, hoping to provide inspiration for nutritional support in patients with end-stage liver disease in China.

Machine learning based on holographic scattering spectrum for mixed pollutants analysis.

Determination of complex pollutants often involves many high-cost and laborious operations. Today's pop machine-learning (ML) technology has exhibited their amazing successes in image recognition, drug designing, disease detection, natural language understanding, etc. ML-driven samples testing will inevitably promote the development of related subjects and fields, but the biggest challenge ahead for this process is how to provide some intelligible and sufficient data for various algorithms. In this work, we present a full strategy for rapid detecting mixed pollutants through the synergistic application of holographic spectrum and convolutional neural network (CNN). The results have shown that a well-trained CNN model could realize quantitative analysis of the mixed pollutants by extracting spectral information of matters, suggesting the strategy's value in facilitating the study of complex chemical systems.