Identification of Hub genes with prognostic values in colorectal cancer by integrated bioinformatics analysis.

Background: Our study aimed to investigate the Hub genes and their prognostic value in colorectal cancer (CRC) via bioinformatics analysis.

Methods: The data set of colorectal cancer was downloaded from the GEO database (GSE21510, GSE110224 and GSE74602) for differential expression analysis using the GEO2R tool. Hub genes were screened by protein-protein interaction (PPI) comprehensive analysis.

A novel proteomic-based model for predicting colorectal cancer with Schistosoma japonicum co-infection by integrated bioinformatics analysis and machine learning.

Schistosoma japonicum infection is an important public health problem and the S. japonicum infection is associated with a variety of diseases, including colorectal cancer. We collected the paraffin samples of CRC patients with or without S.

Does the greening of the tax system promote the green transformation of China's heavily polluting enterprises?

Climate change and pollution are the major environmental problems facing the world today. The emission of industrial pollution is not only related to the development of low carbon and green economy but also affects the ecological environment and climate change of human beings. The greening of the tax system is an important reform to help China's green development.