The prevalence of MCI affected by sex, age,education, which was lower in eastern than that in western China.

BackgroundAtherogenic index of plasma (AIP) has been reported to be associated with cardiovascular diseases. However no study has yet systematically evaluated the association between AIP and obesity and its advantage in obesity prediction compared with conventional lipid components.MethodsA total of 6465 participants aged over 30 years were included in this study. Blood lipid components including triglyceride (TG), total cholesterol (TC), high-density lipoprotein cholesterol (HDL-C) and low-density lipoprotein cholesterol (LDL-C) were measured, and AIP was calculated as log10(TG/HDL-C). Pearson correlation analyses, multivariable logistic analyses and predictive analyses were used to evaluate the association and discrimination ability between AIP, four conventional lipid profiles and obesity.ResultsSubjects in the higher quartiles of AIP all had a significantly increased risk of obesity compared with those in the lowest quartile (P for trend< 0.01). AIP showed a stronger association with obesity than the conventional lipid components as the pearson coefficient reached up to 0.372 and the adjusted odds ratio was 5.55. Using AIP rather than HDL-C and TG significantly improved risk prediction for obesity (AUC improvement = 0.011, P = 0.011; Continuous net reclassification index = 29.55%, P < 0.01; Category net reclassification index = 6.06%; Integrated discrimination improvement = 0.68%, P < 0.01).ConclusionsHigher AIP level was positively and strongly associated with obesity. AIP is a novel and better biomarker associated with obesity. Controlling the AIP level would be more helpful for the prevention of obesity.

BackgroundBrain derived neurotrophic factor (BDNF) is one of the most important regulatory proteins in the pathophysiology of major depressive disorder (MDD). Increasing numbers of studies have reported the relationship between serum/plasma BDNF and antidepressants (ADs). However, the potential effects of several classes of antidepressants on BDNF concentrations are not well known. Hence, our meta-analyses aims to review the effects of differential antidepressant drugs on peripheral BDNF levels in MDD and make some recommendations for future research.MethodsElectronic databases including PubMed, EMBASE, the Cochrane Library, Web of Science, and PsycINFO were searched from 1980 to June 2016. The change in BDNF levels were compared between baseline and post-antidepressants treatment by use of the standardized mean difference (SMD) with 95% confidence intervals (CIs). All statistical tests were two-sided.ResultsWe identified 20 eligible trials of antidepressants treatments for BDNF in MDD. The overall effect size for all drug classes showed that BDNF levels were elevated following a course of antidepressants use. For between-study heterogeneity by stratification analyses, we detect that length of treatment and blood samples are significant effect modifiers for BDNF levels during antidepressants treatment. While both SSRIs and SNRIs could increase the BDNF levels after a period of antidepressant medication treatment, sertraline was superior to other three drugs (venlafaxine, paroxetine or escitalopram) in the early increase of BDNF concentrations with SMD 0.53(95% CI = 0.13–0.93; P = 0.009).ConclusionsThere is some evidence that treatment of antidepressants appears to be effective in the increase of peripheral BDNF levels. More robust evidence indicates that different types of antidepressants appear to induce differential effects on the BDNF levels. Since sertraline makes a particular effect on BDNF concentration within a short amount of time, there is potential value in exploring its relationship with BDNF and its pharmacological mechanism concerning peripheral blood BDNF. Further confirmatory trials are required for both observations.

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Since December 2019, an outbreak of coronavirus disease 2019 (COVID-19) has posed significant threats to the public health and life in China. Unlike the other 6 identified coronaviruses, the SARS-Cov-2 has a high infectious rate, a long incubation period and a variety of manifestations. In the absence of effective treatments for the virus, it becomes extremely urgent to develop scientific and standardized proposals for prevention and control of virus transmission. Hereby we focused on the surgical practice in Neurosurgery Department, Tongji Hospital, Wuhan, and drafted several recommendations based on the latest relevant guidelines and our experience. These recommendations have helped us until now to achieve 'zero infection' of doctors and nurses in our department, we would like to share them with other medical staff of neurosurgery to fight 2019-nCoV infection.

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Ranking problem of web-based rating system has attracted many attentions. A good ranking algorithm should be robust against spammer attack. Here we proposed a correlation based reputation algorithm to solve the ranking problem of such rating systems where user votes some objects with ratings. In this algorithm, reputation of user is iteratively determined by the correlation coefficient between his/her rating vector and the corresponding objects' weighted average rating vector. Comparing with iterative refinement (IR) and mean score algorithm, results for both artificial and real data indicate that, the present algorithm shows a higher robustness against spammer attack.