Demands for faster and more accurate methods to analyze microbial communities from natural and clinical samples have been increasing in the medical and healthcare industry. Recent advances in next-generation sequencing technologies have facilitated the elucidation of the microbial community composition with higher accuracy and greater throughput than was previously achievable; however, the short sequencing reads often limit the microbial composition analysis at the species level due to the high similarity of 16S rRNA amplicon sequences. To overcome this limitation, we used the nanopore sequencing platform to sequence full-length 16S rRNA amplicon libraries prepared from the mouse gut microbiota. A comparison of the nanopore and short-read sequencing data showed that there were no significant differences in major taxonomic units (89%) except one phylotype and three taxonomic units. Moreover, both sequencing data were highly similar at all taxonomic resolutions except the species level. At the species level, nanopore sequencing allowed identification of more species than short-read sequencing, facilitating the accurate classification of the bacterial community composition. Therefore, this method of full-length 16S rRNA amplicon sequencing will be useful for rapid, accurate and efficient detection of microbial diversity in various biological and clinical samples.

Background: Laboratory parameter abnormalities are commonly observed in COVID-19 patients; however, their clinical significance remains controversial. We assessed the prevalence, characteristics, and clinical impact of laboratory parameters in COVID-19 patients hospitalized in Daegu, Korea. Methods:We investigated the clinical and laboratory parameters of 1,952 COVID-19 patients on admission in nine hospitals in Daegu, Korea. The average patient age was 58.1 years, and 700 (35.9%) patients were men. The patients were classified into mild (N=1,612), moderate (N = 294), and severe (N = 46) disease groups based on clinical severity scores. We used chi-square test, multiple comparison analysis, and multinomial logistic regression to evaluate the correlation between laboratory parameters and disease severity.Results: Laboratory parameters on admission in the three disease groups were significantly different in terms of hematologic (Hb, Hct, white blood cell count, lymphocyte%, and platelet count), coagulation (prothrombin time and activated partial thromboplastin time), biochemical (albumin, aspartate aminotransferase, alanine aminotransferase, lactate, blood urea nitrogen, creatinine, and electrolytes), inflammatory (C-reactive protein and procalcitonin), cardiac (creatinine kinase MB isoenzyme and troponin I), and molecular virologic (Ct value of SARS-CoV-2 RdRP gene) parameters. Relative lymphopenia, prothrombin time prolongation, and hypoalbuminemia were significant indicators of CO-VID-19 severity. Patients with both hypoalbuminemia and lymphopenia had a higher risk of severe COVID-19.Conclusions: Laboratory parameter abnormalities on admission are common, are significantly associated with clinical severity, and can serve as independent predictors of CO-VID-19 severity. Monitoring the laboratory parameters, including albumin and lymphocyte count, is crucial for timely treatment of COVID-19.

Over the past decade or so, dramatic developments in our ability to experimentally determine the content and function of genomes have taken place. In particular, next-generation sequencing technologies are now inspiring a new understanding of bacterial transcriptomes on a global scale. In bacterial cells, whole-transcriptome studies have not received attention, owing to the general view that bacterial genomes are simple. However, several recent RNA sequencing results are revealing unexpected levels of complexity in bacterial transcriptomes, indicating that the transcribed regions of genomes are much larger and complex than previously anticipated. In particular, these data show a wide array of small RNAs, antisense RNAs, and alternative transcripts. Here, we review how current transcriptomics are now revolutionizing our understanding of the complexity and regulation of bacterial transcriptomes.

PURPOSE: Routine collection of patient-reported outcomes (PROs) for patients with advanced solid malignancies is an evidence-based practice and critical component of high-quality cancer care, but real-world adherence is poorly characterized. We sought to describe real-world adherence to PRO monitoring and its potential predictors. METHODS: We conducted a retrospective cross-sectional study using deidentified electronic health record data from a National Cancer Institute Cancer Center, encompassing one academic and two community sites. Participants included individuals with lung cancer receiving systemic therapy from January 1 to December 31, 2019. The primary outcome was patient-level adherence, defined as the proportion of treatment visits during which a PRO questionnaire (spanning symptoms, functional status, and global quality-of-life domains) was completed within 30 days. Practice-level performance was calculated as unadjusted mean patient-level adherence. We modeled patient-level adherence using multivariable ordinary least squares regression and identified covariates associated with adherence using a significance threshold of P < .05. RESULTS: In 2019, there were 18,604 encounters for 1,105 patients with lung cancer (mean [standard deviation] age 65.8 [10.2] years; 621 [56.2%] female; 216 [19.6%] Black) receiving systemic therapy. The mean patient-level PRO adherence ranged from 27.2% to 70.0% across sites and was 49.4% overall. Advanced age (≥ 65 years) and Black or African American race were negatively associated with PRO adherence ( P < .01). CONCLUSION: Across this real-world cohort of patients undergoing treatment for lung cancer, adherence to PRO monitoring lagged that achieved in seminal clinical trials, with potential age- and race-based disparities, demonstrating an implementation gap that could be addressed with standardized reporting of an adherence-based quality metric.

In this paper, we introduce our experience on the development of a three-dimensional audio-visual(3D AV) service system based on the terrestrial digital multimedia broadcasting (T-DMB) system. 3D AV service is now much more feasible than before with the fast advancement of hardware technologies, especially 3D flat panel display, processors and memory. 3D AV service over DMB system is very attractive due to the facts that (1) glassless 3D viewing with small display is relatively easy to implement and more suitable to the single user environment like DMB, (2) DMB is a new media and thus has more flexibility in adding new services on the existing ones, (3) 3D AV handling capability of 3D DMB terminal has lots of potential to generate new types of services if it is added with other components like built-in stereo camera. In order to provide successful 3D DMB services over existing DMB system, we need to solve several issues like (1) guaranteeing backward compatibility with the T-DMB system, (2) minimizing the overhead on the transmitted bit-rate and the required processing power of the terminal, (3) providing good 3D depth perception without a noticeable eye strain. We propose a very efficient and backward compatible system architecture for the 3D DMB, and show how we can get better depth perception with the limited bit budget of the DMB system.

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