Background The number of cumulative confirmed cases of COVID-19 in the United States has risen sharply since March 2020. A county health ranking and roadmaps program has been established to identify factors associated with disparity in mobility and mortality of COVID-19 in all counties in the United States. The risk factors associated with county-level mortality of COVID-19 with various levels of prevalence are not well understood. Methods Using the data obtained from the County Health Rankings and Roadmaps program, this study applied a negative binomial design to the county-level mortality counts of COVID-19 as of August 27, 2020 in the United States. In this design, the infected counties were categorized into three levels of infections using clustering analysis based on time-varying cumulative confirmed cases from March 1 to August 27, 2020. COVID-19 patients were not analyzed individually but were aggregated at the county-level, where the county-level deaths of COVID-19 confirmed by the local health agencies. Clustering analysis and Kruskal–Wallis tests were used in our statistical analysis. Results A total of 3125 infected counties were assigned into three classes corresponding to low, median, and high prevalence levels of infection. Several risk factors were significantly associated with the mortality counts of COVID-19, where higher level of air pollution (0.153, P < 0.001) increased the mortality in the low prevalence counties and elder individuals were more vulnerable in both the median (0.049, P < 0.001) and high (0.114, P < 0.001) prevalence counties. The segregation between non-Whites and Whites (low: 0.015, P < 0.001; median:0.025, P < 0.001; high: 0.019, P = 0.005) and higher Hispanic population (low and median: 0.020, P < 0.001; high: 0.014, P = 0.009) had higher likelihood of risk of the deaths in all infected counties. Conclusions The mortality of COVID-19 depended on sex, race/ethnicity, and outdoor environment. The increasing awareness of the impact of these significant factors may help decision makers, the public health officials, and the general public better control the risk of pandemic, particularly in the reduction in the mortality of COVID-19. Graphic abstract

Background: A growing number of evidences suggest that TMZ applications can generate impressive benefits for APT and PC patients. However, the definite role of TMZ for individuals remains unclarified due to the variation between studies. And the predictive factors to alter its efficacy remain debatable.Objective: To evaluate the long-term effectiveness and safety profile of TMZ in the treatment of pituitary malignancies, and delineate the predictors during its clinical employment.Results: A literature retrieval was conducted from online databases for studies published up to December 31, 2020. Twenty one studies involving 429 patients were identified. TMZ exhibited 41% radiological overall response rate (rORR). The biochemical response rate was determinate in 53% of the functioning subset. Two-year and 4-year survival rate were 79 and 61%, respectively. TMZ prolonged the median PFS and OS as 20.18 and 40.24 months. TMZ-related adverse events occurred in 19% of patients. Regarding predictors of TMZ response, rORR was dramatically improved in patients with low/intermediate MGMT expression than those with high-MGMT (&gt;50%) (p &lt; 0.001). The benefit of TMZ varied according to functioning subtype of patients, with greater antitumor activities in functioning subgroups and fewer activities in non-functioning sets (p &lt; 0.001). Notably, the concomitant therapy of radiotherapy and TMZ significantly increased the rORR (p = 0.007).Conclusion: TMZ elicits clinical benefits with moderate adverse events in APT and PC patients. MGMT expression and clinical subtype of secreting function might be vital predictors of TMZ efficacy. In the future, the combination of radiotherapy with TMZ may further improve the clinical outcomes than TMZ monotherapy.

OBJECTIVETo date, long noncoding RNAs (lncRNAs) have proven to function as key regulators in tumorigenesis. Among these lncRNAs, MEG3 displays low levels in various neoplasms and tumor cell lines. However, the regulatory mechanism of MEG3 and MIR-376B-3P, one of the microRNAs from downstream gene clusters of the DLK1-MEG3 locus, remains insufficiently defined.METHODSThe authors used quantitative real-time polymerase chain reaction analysis to analyze whether decreased MEG3 and MIR-376B-3P expression levels were associated with the invasiveness of clinical nonfunctioning pituitary adenomas (CNFPAs) in 30 patients. Furthermore, functional experiments unveiled the pathophysiological role of MEG3, MIR-376B-3P, and HMGA2 in pituitary-derived folliculostellate (PDFS) cell lines. Moreover, dual-luciferase reporter assay, Western blot analysis, and immunofluorescence were applied to reveal the correlations among MEG3, MIR-376B-3P, and HMGA2.RESULTSMEG3 and MIR-376B-3P were decreased in patients with CNFPA, and their transcriptional levels were highly associated with invasive CNFPAs. Moreover, excessive expression of MEG3 and MIR-376B-3P inhibited tumorigenesis and promoted apoptosis in PDFS cells. Importantly, the authors found that MEG3 acted as an enhancer of MIR-376B-3P expression. Furthermore, as a target gene of MIR-376B-3P, HMGA2 served as an oncogene in pituitary adenoma and could be negatively regulated by MEG3 via enriching MIR-376B-3P.CONCLUSIONSThis study offers a novel mechanism of an MEG3/MIR-376B-3P/HMGA2 regulatory network in CNFPAs, which may become a breakthrough for anticancer treatments.

Dengue is a rapidly spreading mosquito-borne disease caused by the dengue virus (DENV) and has emerged as a severe public health problem around the world. Guangdong, one of the southern Chinese provinces, experienced a serious outbreak of dengue in 2014, which was believed to be the worst dengue epidemic in China over the last 20 years. To better understand the epidemic, we collected the epidemiological data of the outbreak and analyzed 14,594 clinically suspected dengue patients from 25 hospitals in Guangdong. Dengue cases were then laboratory-confirmed by the detection of DENV non-structural protein 1 (NS1) antigen and/or DENV RNA. Afterwards, clinical manifestations of dengue patients were analyzed and 93 laboratory-positive serum specimens were chosen for the DENV serotyping and molecular analysis. Our data showed that the 2014 dengue outbreak in Guangdong had spread to 20 cities and more than 45 thousand people suffered from dengue fever. Of 14,594 participants, 11,387 were definitively diagnosed. Most manifested with a typical non-severe clinical course, and 1.96 % developed to severe dengue. The strains isolated successfully from the serum samples were identified as DENV-1. Genetic analyses revealed that the strains were classified into genotypes I and V of DENV-1, and the dengue epidemic of Guangdong in 2014 was caused by indigenous cases and imported cases from the neighboring Southeast Asian countries of Malaysia and Singapore. Overall, our study is informative and significant to the 2014 dengue outbreak in Guangdong and will provide crucial implications for dengue prevention and control in China and elsewhere.

Background: The number of cumulative confirmed cases of COVID-19 in the United States has risen sharply since March 2020. A county health ranking and roadmaps program has been established to identify factors associated with disparity in mobility and mortality of COVID-19 in all counties in the United States. Methods: To find out the risk factors associated with county-level mortality of COVID-19 with various levels of prevalence, a negative binomial design was applied to the county-level mortality counts of COVID-19 as of April 15, 2020 in the United States. In this design, the infected counties were categorized into three levels of infections using clustering analysis based on time-varying cumulative confirmed cases from March 1 to April 15, 2020. COVID-19 patients were not analyzed individually but were aggregated at the county-level, where the county-level deaths of COVID-19 confirmed by the local health agencies. Findings: 2692 infected counties were assigned into three classes corresponding to low, medium, and high prevalence levels of infection. Several risk factors were significantly associated with the mortality counts of COVID-19, where elder (0.221, P=0.001) individuals were more vulnerable and higher level of air pollution (0.186, P=0.005) increased the mortality in the metropolis areas. The segregation between non-Whites and Whites had higher likelihood of risk of the deaths in all infected counties. Interpretation: The mortality of COVID-19 depended on sex, race/ethnicity, and outdoor environment. The increasing awareness of the impact of these significant factors may lead to the reduction in the mortality of COVID-19.

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BackgroundCurrently, it is difficult to estimate the possibility of recurrence of nonfunctioning pituitary adenomas (NFPAs). Markers such as Ki-67 or transcription factors rely on postoperative pathology, while few indices can be used for preoperative prediction. Therefore, we aimed to investigate the predictive effectiveness of supra-intrasellar volume and tumor-carotid distance based on measurements derived from preoperative magnetic resonance imaging (MRI) data.MethodNinety-eight cases of NFPAs were evaluated, along with their clinical characteristics and MRI features. Four radiologic indices were analyzed, including intrasellar tumor volume, suprasellar tumor volume, maximum horizontal tumor diameter, and intercarotid distance. The ratio of supra-intrasellar volume and ratio of tumor-carotid distance were measured using 3D Slicer software, and the sum of two ratios was defined as the V-D value. The correlation between recurrence and multiple factors was analyzed using univariate and multivariate logistic regression and Kaplan-Meier analysis, and ROC curves were used to estimate the prognostic performance of radiologic measurements in NFPAs.ResultThe supra-intrasellar volume ratio, tumor-carotid distance ratio and V-D value were significantly correlated with the recurrence of NFPAs. The predictive importance of the V-D value reached 84.5%, with a sensitivity of 83.7% and specificity of 67.3%. The cutoff limit of the V-D value was 1.53, and patients with V-D values higher than 1.53 tended to relapse much earlier.ConclusionThe V-D value has predictive importance for the recurrence of NFPAs preoperatively. Patients with higher V-D values will undergo recurrence earlier and should be given greater consideration in terms of surgery and follow-up time.