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Background People undergoing mass home- and community-based quarantine are vulnerable to mental health disorders during outbreaks of coronavirus disease (COVID-19), but few studies have evaluated the associated psychosocial factors. Objective This study aimed to estimate the prevalence of anxiety and depressive symptoms and identify associated demographic and psychosocial factors in the general Chinese population during the COVID-19 pandemic quarantine period. Methods Participants aged 18 years or above were recruited in a cross-sectional online survey using snowball sampling from February 26-29, 2020. The survey included questions on demographics, family relationships, chronic diseases, quarantine conditions, lifestyle, COVID-19 infection, and anxiety and depressive symptoms. Logistic regression analyses were conducted to identify factors associated with elevated anxiety or depressive symptoms. Results Out of 2331 participants, 762 (32.7%) experienced elevated anxiety or depressive symptoms. Nine risk factors associated with anxiety or depressive symptoms included younger age, reduced income, having cancer or other chronic diseases, having family members living with cancer, concerns related to COVID-19 infection for themselves or family members, living alone, having family conflicts, having <3 or >8 hours of sedentary time per day, and worsened sleep quality. Conclusions The findings highlight an urgent need for psychological support for populations at high risk for elevated anxiety or depressive symptoms during the COVID-19 pandemic.

Background Psychiatric morbidities have been associated with a risk of severe infections through compromised immunity, health behaviours, or both. However, data are scarce on the association between multiple types of pre-pandemic psychiatric disorders and COVID-19. We aimed to assess the association between pre-pandemic psychiatric disorders and the subsequent risk of COVID-19 using UK Biobank. Methods For this cohort analysis, we included participants from UK Biobank who were registered in England and excluded individuals who died before Jan 31, 2020, (the start of the COVID-19 outbreak in the UK) or had withdrawn from UK Biobank. Participants diagnosed with a psychiatric disorder before Jan 31 were included in the group of individuals with pre-pandemic psychiatric disorders, whereas participants without a diagnosis before the outbreak were included in the group of individuals without pre-pandemic psychiatric disorders. We used the Public Health England dataset, UK Biobank hospital data, and death registers to collect data on COVID-19 cases. To examine the relationship between pre-pandemic psychiatric disorders and susceptibility to COVID-19, we used logistic regression models to estimate odds ratios (ORs), controlling for multiple confounders and somatic comorbidities. Key outcomes were all COVID-19, COVID-19 specifically diagnosed in inpatient care, and COVID-19-related deaths. ORs were also estimated separately for each psychiatric disorder and on the basis of the number of pre-pandemic psychiatric disorders. As a positive disease control, we repeated analyses for hospitalisation for other infections. Findings We included 421 014 UK Biobank participants in our study and assessed their COVID-19 status between Jan 31 and July 26, 2020. 50 809 participants were diagnosed with psychiatric disorders before the outbreak, while 370 205 participants had no psychiatric disorders. The mean age at outbreak was 67·80 years (SD 8·12). We observed an elevated risk of COVID-19 among individuals with pre-pandemic psychiatric disorders compared with that of individuals without such conditions. The fully adjusted ORs were 1·44 (95% CI 1·28–1·62) for All COVID-19 cases, 1·55 (1·34–1·78) for Inpatient COVID-19 cases, and 2·03 (1·59–2·59) for COVID-19-related deaths. We observed excess risk, defined as risk that increased with the number of pre-pandemic psychiatric disorders, across all diagnostic categories of pre-pandemic psychiatric disorders. We also observed an association between psychiatric disorders and elevated risk of hospitalisation due to other infections (OR 1·74, 95% CI 1·58–1·93). Interpretation Our findings suggest that pre-existing psychiatric disorders are associated with an increased risk of COVID-19. These findings underscore the need for surveillance of and care for populations with pre-existing psychiatric disorders during the COVID-19 pandemic. Funding National Natural Science...

Purpose To investigate the involvement of hsa-microRNA-195-5p (miR-195) in progression and prognosis of human prostate cancer (PCa). Experimental Design qRT-PCR was performed to detect miR-195 expression in both PCa cell lines and clinical tissue samples. Its clinical significance was statistically analyzed. The roles of miR-195 and its candidate target gene ribosomal protein S6 kinase, 70kDa, polypeptide 1 (RPS6KB1) in PCa progression were confirmed based on both in vitro and in vivo systems. Results MiR-195 downregulation in PCa tissues was significantly associated with high Gleason score (P=0.001), positive metastasis failure (P<0.001) and biochemical recurrence (BCR, P<0.001). Survival analysis identified miR-195 as an independent prognostic factor for BCR-free survival of PCa patients (P=0.022). Then, we confirmed the tumor suppressive role of miR-195 through PCa cell invasion, migration and apoptosis assays in vitro, along with tumor xenografts growth, angiogenesis and invasion in vivo according to both gain-of-function and loss-of-function experiments. Additionally, RPS6KB1 was identified as a novel direct target of miR-195 through proteomic expression profiling combined with bioinformatic target prediction and luciferase reporter assay. Moreover, the re-expression and knockdown of RPS6KB1 could respectively rescue and imitate the effects induced by miR-195. Importantly, RPS6KB1 expression was closely correlated with aggressive progression and poor prognosis in PCa patients as opposed to miR-195. Furthermore, we identified MMP-9, VEGF, BAD and E-cadherin as the downstream effectors of miR-195-RPS6KB1 axis. Conclusion The newly identified miR-195-RPS6KB1 axis partially illustrates the molecular mechanism of PCa progression and represents a novel potential therapeutic target for PCa treatment.

Background The clinical manifestations and factors associated with the severity of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infections outside of Wuhan are not clearly understood. Methods All laboratory-confirmed cases with SARS-Cov-2 infection who were hospitalized and monitored in Guangzhou Eighth People’s Hospital were recruited from January 20 to February 10. Results A total of 275 patients were included in this study. The median patient age was 49 years, and 63.6% had exposure to Wuhan. The median virus incubation period was 6 days. Fever (70.5%) and dry cough (56.0%) were the most common symptoms. A decreased albumin level was found in 51.3% of patients, lymphopenia in 33.5%, and pneumonia based on chest computed tomography in 86%. Approximately 16% of patients (n = 45) had severe disease, and there were no deaths. Compared with patients with nonsevere disease, those with severe disease were older, had a higher frequency of coexisting conditions and pneumonia, and had a shorter incubation period (all P &lt; .05). There were no differences between patients who likely contacted the virus in Wuhan and those who had no exposure to Wuhan. Multivariate logistic regression analysis indicated that older age, male sex, and decreased albumin level were independently associated with disease severity. Conclusions Most of the patients infected with SARS-CoV-2 in Guangzhou, China are not severe cases and patients with older age, male, and decreased albumin level were more likely to develop into severe ones.

BackgroundThe NIMA-related kinase 2 (NEK2) is a serine/threonine kinase that is involved in regulation of centrosome duplication and spindle assembly during mitosis. Dysregulation of these processes causes chromosome instability and aneuploidy, which are hallmark changes of many solid tumors. However, whether aberrant expression of NEK2 is associated with outcome of prostate cancer (PCa) patients remains to be determined.MethodsExpression of NEK2 in human PCa cells and primary PCa tissues was assessed by quantitative RT-PCR. Expression of NEK2 in human PCa cells was depleted with siRNA. Effects of the depletion on cell proliferation, survival, and tumorigenicity were assessed both in vitro with cell cultures and in vivo with subcutaneous implantation of xenografts. In silico analyses of the online Taylor dataset were carried out to determine whether the expression level of NEK2 correlated with the clinicopathological characteristics of prostate cancer.ResultsCompared with benign human prostatic epithelial cells and tissues, the expression of NEK2 was elevated in human PCa cells and primary PCa tissues. Depleting NEK2 expression inhibited human PCa cell proliferation in vitro and xenograft growth in vivo. Expression level of NEK2 in PCa positively correlated with the Gleason score and pathologic stage of the patient.ConclusionThe results suggest that overexpression of NEK2 has the potential to serve as a biomarker for PCa prognosis. Further validation with large sample pool is warrant.

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The relationship between linkage disequilibrium (LD) and recombination fraction can be used to infer the pattern of genetic variation and evolutionary process in humans and other systems. We described a computational framework to construct a linkage–LD map from commonly used biallelic, single-nucleotide polymorphism (SNP) markers for outcrossing plants by which the decline of LD is visualized with genetic distance. The framework was derived from an open-pollinated (OP) design composed of plants randomly sampled from a natural population and seeds from each sampled plant, enabling simultaneous estimation of the LD in the natural population and recombination fraction due to allelic co-segregation during meiosis. We modified the framework to infer evolutionary pasts of natural populations using those marker types that are segregating in a dominant manner, given their role in creating and maintaining population genetic diversity. A sophisticated two-level EM algorithm was implemented to estimate and retrieve the missing information of segregation characterized by dominant-segregating markers such as single methylation polymorphisms. The model was applied to study the relationship between linkage and LD for a non-model outcrossing species, a gymnosperm species, Torreya grandis, naturally distributed in mountains of the southeastern China. The linkage–LD map constructed from various types of molecular markers opens a powerful gateway for studying the history of plant evolution.