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Background: Alzheimer's disease (AD) patients are often accompanied by depressive symptoms, but its underlying mechanism remains unclear. The present study aimed to explore the potential role of microRNAs in the comorbidity of AD and depression. Methods: The miRNAs associated with AD and depression were screened from databases and literature and then confirmed in the cerebrospinal fluid (CSF) of AD patients and different ages of transgenic APP/PS1 mice. AAV9-miR-451a-GFP was injected into the medial prefrontal cortex (mPFC) of APP/PS1 mice at seven months, and four weeks later, a series of behavioral and pathological analyses were performed. Results: AD patients had low CSF levels of miR-451a, which was positively correlated with the cognitive assessment score, but negatively with their depression scale. In the mPFC of APP/PS1 transgenic mice, the miR-451a levels also decreased significantly in the neurons and microglia. Specific virus vector-induced overexpression of miR-451a in the mPFC of APP/PS1 mice ameliorated AD-related behavior deficits and pathologies, including long-term memory defects, depression-like phenotype, β-amyloid load, and neuroinflammation. Mechanistically, miR-451a decreased the expression of neuronal β-secretase 1 of neurons through inhibiting Toll-like receptor 4/Inhibitor of kappa B Kinase β/ Nuclear factor kappa-B signaling pathway and microglial activation by inhibiting activation of NOD-like receptor protein 3, respectively. Conclusion: This finding highlighted miR-451a as a potential target for diagnosing and treating AD, especially for those with coexisting symptoms of depression.

Objective: Fat loss theory under various oxygen conditions has been disputed, and relevant systematic review studies are limited. This study is a systematic review and meta-analysis to assess whether hypoxic exercise training (HET) leads to superior fat-reducing compared with normoxic exercise training (NET).Methods: We searched PubMed, Web of Science, CNKI, ProQuest, Google Scholar, Cochrane Library, and EBSCOhost from inception to June 2022 for articles comparing the effects of hypoxic and normoxic exercise on body composition indicators, glycometabolism, and lipometabolism indicators in obese and overweight adults. Only randomized controlled trials (RCTs) were included. The effect sizes were expressed as standardized mean difference (SMD) and 95% confidence intervals (CI). Between-study heterogeneity was examined using the I2 test and evaluated publication bias via Egger’s regression test. The risk of bias assessment was performed for each included trial using Cochrane Evaluation Tool second generation. The meta-analysis was performed by using R 4.1.3 and RevMan 5.3 analytic tools.Results: A total of 19 RCTs with 444 subjects were analyzed according to the inclusion and exclusion criteria. Among them, there were 14 English literature and five Chinese literature. No significant difference in body composition (SMD -0.10, 95% CI -0.20 to -0.01), glycometabolism and lipid metabolism (SMD -0.01, 95% CI -0.13 to -0.10) has been observed when comparing the HET and NET groups. We only found low heterogeneity among trials assessing glycometabolism and lipometabolism (I2 = 20%, p = 0.09), and no publication bias was detected.Conclusion: The effects of HET and NET on fat loss in overweight or obese people are the same. The application and promotion of HET for fat reduction need further exploration.

Recurrent event data are common in clinical studies when participants are followed longitudinally, and are often subject to a terminal event. With the increasing popularity of large pragmatic trials and a heterogeneous source population, participants are often nested in clinics and can be either susceptible or structurally unsusceptible to the recurrent process. These complications require new modeling strategies to accommodate potential zero-event inflation as well as hierarchical data structures in both the terminal and non-terminal event processes. In this paper, we develop a Bayesian semiparametric model to jointly characterize the zero-inflated recurrent event process and the terminal event process. We use a point mass mixture of non-homogeneous Poisson processes to describe the recurrent intensity and introduce shared random effects from different sources to bridge the non-terminal and terminal event processes. To achieve robustness, we consider nonparametric Dirichlet processes to model the residual of the accelerated failure time model for the survival process as well as the cluster-specific frailty distribution, and develop a Markov Chain Monte Carlo algorithm for posterior inference. We demonstrate the superiority of our proposed model compared with competing models via simulations and apply our method to a pragmatic cluster-randomized trial for fall injury prevention among the elderly.