In December 2019, a new type viral pneumonia cases occurred in Wuhan, Hubei Province; and then named “2019 novel coronavirus (2019-nCoV)” by the World Health Organization (WHO) on 12 January 2020. For it is a never been experienced respiratory disease before and with infection ability widely and quickly, it attracted the world’s attention but without treatment and control manual. For the request from frontline clinicians and public health professionals of 2019-nCoV infected pneumonia management, an evidence-based guideline urgently needs to be developed. Therefore, we drafted this guideline according to the rapid advice guidelines methodology and general rules of WHO guideline development; we also added the first-hand management data of Zhongnan Hospital of Wuhan University. This guideline includes the guideline methodology, epidemiological characteristics, disease screening and population prevention, diagnosis, treatment and control (including traditional Chinese Medicine), nosocomial infection prevention and control, and disease nursing of the 2019-nCoV. Moreover, we also provide a whole process of a successful treatment case of the severe 2019-nCoV infected pneumonia and experience and lessons of hospital rescue for 2019-nCoV infections. This rapid advice guideline is suitable for the first frontline doctors and nurses, managers of hospitals and healthcare sections, community residents, public health persons, relevant researchers, and all person who are interested in the 2019-nCoV.

Methodological quality (risk of bias) assessment is an important step before study initiation usage. Therefore, accurately judging study type is the first priority, and the choosing proper tool is also important. In this review, we introduced methodological quality assessment tools for randomized controlled trial (including individual and cluster), animal study, non-randomized interventional studies (including follow-up study, controlled before-and-after study, before-after/ pre-post study, uncontrolled longitudinal study, interrupted time series study), cohort study, case-control study, cross-sectional study (including analytical and descriptive), observational case series and case reports, comparative effectiveness research, diagnostic study, health economic evaluation, prediction study (including predictor finding study, prediction model impact study, prognostic prediction model study), qualitative study, outcome measurement instruments (including patient - reported outcome measure development, content validity, structural validity, internal consistency, cross-cultural validity/ measurement invariance, reliability, measurement error, criterion validity, hypotheses testing for construct validity, and responsiveness), systematic review and meta-analysis, and clinical practice guideline. The readers of our review can distinguish the types of medical studies and choose appropriate tools. In one word, comprehensively mastering relevant knowledge and implementing more practices are basic requirements for correctly assessing the methodological quality.

Background: The burden of kidney, bladder, and prostate cancers has changed in recent decades. This study aims to investigate the global and regional burden of, and attributable risk factors for genitourinary cancers during the past 30 years. Methods: We extracted data of kidney, bladder, and prostate cancers from the Global Burden of Disease 2019 database, including incidence, mortality, disability-adjusted life-years (DALYs), and attributable risk factors from 1990 to 2019. Estimated annual percentage changes (EAPC) were calculated to assess the changes in age-standardized incidence rate, age-standardized mortality rate (ASMR), and age-standardized DALYs rate (ASDR). The associations between cancers burden and socio-demographic index (SDI) were also analyzed. Results: Compared with 1990, the global incident cases in 2019 were higher by 154.78%, 123.34%, and 169.11% for kidney, bladder, and prostate cancers, respectively. During the 30-year study period, there was a downward trend in ASMR and ASDR for bladder cancer (EAPC = − 0.68 and − 0.83, respectively) and prostate cancer (EAPC = − 0.75 and − 0.71, respectively), but an upward trend for kidney cancer (EAPC = 0.35 and 0.12, respectively). Regions and countries with higher SDI had higher incidence, mortality, and DALYs for all three types of cancers. The burden of bladder and prostate cancers was mainly distributed among older men, whereas the burden of kidney cancer increased among middle-aged men. Smoking related mortality and DALYs decreased, but high body mass index (BMI) and high fasting plasma glucose (FPG) related mortality and DALYs increased among kidney, bladder, and prostate cancers during the study period. Conclusions: Kidney, bladder, and prostate cancers remain major global public health challenges, but with distinct trend for different disease entity across different regions and socioeconomic status. More proactive intervention strategies, at both the administrative and academic levels, based on the dynamic changes, are needed.

Objective: To identify candidate biomarkers correlated with clinical prognosis of patients with bladder cancer (BC). Methods: Weighted gene co-expression network analysis was applied to build a co-expression network to identify hub genes correlated with tumor node metastasis (TNM) staging of BC patients. Functional enrichment analysis was conducted to functionally annotate the hub genes. Protein-protein interaction network analysis of hub genes was performed to identify the interactions among the hub genes. Survival analyses were conducted to characterize the role of hub genes on the survival of BC patients. Gene set enrichment analyses were conducted to find the potential mechanisms involved in the tumor proliferation promoted by hub genes. Results: Based on the results of topological overlap measure based clustering and the inclusion criteria, top 50 hub genes were identified. Hub genes were enriched in cell proliferation associated gene ontology terms (mitotic sister chromatid segregation, mitotic cell cycle and, cell cycle, etc.) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathways (cell cycle, Oocyte meiosis, etc.). 17 hub genes were found to interact with ≥5 of the hub genes. Survival analysis of hub genes suggested that lower expression of MMP11, COL5A2, CDC25B, TOP2A, CENPF, CDCA3, TK1, TPX2, CDCA8, AEBP1, and FOXM1were associated with better overall survival of BC patients. BC samples with higher expression of hub genes were enriched in gene sets associated with P53 pathway, apical junction, mitotic spindle, G2M checkpoint, and myogenesis, etc. Conclusions: We identified several candidate biomarkers correlated with the TNM staging and overall survival of BC patients. Accordingly, they might be used as potential diagnostic biomarkers and therapeutic targets with clinical utility.