Clinical application of endobronchial ultrasonography-guided transbronchial needle aspiration biopsy-a single center, large sample, real-world study.

BACKGROUND: Endobronchial ultrasonography-guided transbronchial needle aspiration biopsy (EBUS-TBNA) has been used for more than 10 years in China. Its clinical application and diagnostic value in different diseases with large sample was lack of report. METHODS: A retrospective analysis was performed about the application and diagnostic value of EBUS-TBNA in different disease of patients in Respiratory Intervention Center of Guangzhou Institute of Respiratory Health from January 2012 to July 2020. RESULTS: A total 5758 patients were included with 182 patients excluded for lack of information. Finally, data of 5576 patients (3798 males and 1778 females) were analyzed. For anesthetize, most patients were undergoing general anesthesia of intravenous with spontaneous breathing (69.4%), followed by general anesthesia of intravenous and inhalation with tracheal intubation and mechanical ventilation (17.9%) and conscious sedation and analgesia (12.8%). Lymph nodes were the main sites of biopsy obtained (76.4%). Tumors accounted for the highest proportion of disease (66.4%), followed by infection diseases (9.9%), sarcoidosis (3.9%), lymphoma (1.1%), and others (18.7%). The sensitivity of EBUS-TBNA for diagnosis of tumor was 89.7%, and 40.8% for infection diseases. There were significant differences in the puncture site and proportions of diseases between male and females (both p < 0.05). Higher diagnostic value was found in male patients (p < 0.05). CONCLUSION: EBUS-TBNA has good diagnostic value for different mediastinal and central pulmonary space-occupying lesions diseases, with highest sensitivity for tumors. Higher diagnostic value was found in male patients.

Analysis of the relationship between genomic GC Content and patterns of base usage, codon usage and amino acid usage in prokaryotes: similar GC content adopts similar compositional frequencies regardless of the phylogenetic lineages.

The GC contents of 2670 prokaryotic genomes that belong to diverse phylogenetic lineages were analyzed in this paper. These genomes had GC contents that ranged from 13.5% to 74.9%. We analyzed the distance of base frequencies at the three codon positions, codon frequencies, and amino acid compositions across genomes with respect to the differences in the GC content of these prokaryotic species. We found that although the phylogenetic lineages were remote among some species, a similar genomic GC content forced them to adopt similar base usage patterns at the three codon positions, codon usage patterns, and amino acid usage patterns. Our work demonstrates that in prokaryotic genomes: a) base usage, codon usage, and amino acid usage change with GC content with a linear correlation; b) the distance of each usage has a linear correlation with the GC content difference; and c) GC content is more essential than phylogenetic lineage in determining base usage, codon usage, and amino acid usage. This work is exceptional in that we adopted intuitively graphic methods for all analyses, and we used these analyses to examine as many as 2670 prokaryotes. We hope that this work is helpful for understanding common features in the organization of microbial genomes.

SMAL: A Resource of Spontaneous Mutation Accumulation Lines.

Mutation is the ultimate source of genetic variation and evolution. Mutation accumulation (MA) experiments are an alternative approach to study de novo mutation events directly. We have constructed a resource of Spontaneous Mutation Accumulation Lines (SMAL; http://cefg.uestc.edu.cn/smal), which contains all the current publicly available MA lines identified by high-throughput sequencing. We have relocated and mapped the mutations based on the most recent genome annotations. A total of 5,608 single base mutations and 540 other mutations were obtained and are recorded in the current version of the SMAL database. The integrated data in SMAL provide detailed information that can be used in new theoretical analyses. We believe that the SMAL resource will help researchers better understand the processes of genetic variation and the incidence of disease.