Objective:The present study aimed to conduct a clinical analysis of nosocomial infections in hospitalized cancer pa-tients and propose effective precautionary measures. Methods:We retrospectively analyzed 56,430 cases of discharges from the Cancer Institute and Hospital of Tianjin Medical University between January and December 2012. Results:Among 825 cases, the rate of noso-comial infections was 1.46%;46.42%of the patients aged>60 years. The highest infection rate was observed in the Medical Depart-ment of Stomach Cancer. The highest composing rate was recorded in the Department of Hepatobiliary Cancer. The major pathogenic bacteria were Gram-negative bacilli;fungal infections were relatively rare. The most vulnerable body parts were the abdomen and diges-tive tract, which were mainly infected by pathogenic Escherichia coli. Conclusion:Healthcare workers should consider the importance of influencing factors and take precautionary measures to reduce the rate of nosocomial infections in cancer patients.

On January 22, 2020, China National Center for Bioinformation (CNCB) released the 2019 Novel Coronavirus Resource (2019nCoVR), an open-access information resource for the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). 2019nCoVR features a comprehensive integra-tion of sequence and clinical information for all publicly available SARS-CoV-2 isolates, which are manually curated with value-added annotations and quality evaluated by an automated in-house pipeline. Of particular note, 2019nCoVR offers systematic analyses to generate a dynamic landscape of SARS-CoV-2 genomic variations at a global scale. It provides all identified variants and their detailed statistics for each virus isolate, and congregates the quality score, functional annotation,and population frequency for each variant. Spatiotemporal change for each variant can be visualized and historical viral haplotype network maps for the course of the outbreak are also generated based on all complete and high-quality genomes available. Moreover, 2019nCoVR provides a full collection of SARS-CoV-2 relevant literature on the coronavirus disease 2019 (COVID-19), including published papers from PubMed as well as preprints from services such as bioRxiv and medRxiv through Europe PMC. Furthermore, by linking with relevant databases in CNCB, 2019nCoVR offers data submission services for raw sequence reads and assembled genomes, and data sharing with NCBI. Collectively, SARS-CoV-2 is updated daily to collect the latest information on genome sequences, variants, hap-lotypes, and literature for a timely reflection, making 2019nCoVR a valuable resource for the global research community. 2019nCoVR is accessible at https://bigd.big.ac.cn/ncov/.