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To illustrate a machine learning-based approach for identifying and investigating moderators of alcohol use intervention effects in aggregate-data meta-analysis.<br /><br /> We illustrated the machine learning technique of random forest modeling using data from an ongoing meta-analysis of brief substance use interventions implemented in general healthcare settings. A subset of 40 trials testing brief alcohol interventions (BAIs) was used; these trials provided 344 estimates of post-intervention effects on participants' alcohol use as well as data on 20 potential moderators of intervention effects. These candidate moderators included characteristics of trial methodology and implementation, intervention design and participant samples.<br /><br /> The best-fitting random forest model identified 10 important moderators from the pool of 20 candidate moderators. Meta-regression utilizing the selected moderators found that inclusion of prescriptive advice in a BAI session significantly moderated BAI effects on alcohol use. Observed effects were also significantly moderated by several methodological characteristics of trials, including the type of comparison group used, the overall level of attrition and the strategy used to address missing data. In a meta-regression model that included all candidate moderators, fewer coefficients were found to be significant, indicating that the use of a preliminary data reduction technique to identify only important moderators for inclusion in final analyses may have yielded improved statistical power to detect moderation.<br /><br /> Machine learning methods can be valuable tools for clarifying the influence of trial, intervention and sample characteristics on alcohol use intervention effects, in particular when numerous candidate moderators are available.<br /><br />Machine learning methods can be valuable tools for clarifying the influence of trial, intervention and sample characteristics on alcohol use intervention effects, in particular when numerous candidate moderators are available.It has been demonstrated that trimethylamine N-oxide (TMAO) serves as a driver of atherosclerosis, suggesting that reduction of TMAO level might be a potent method to prevent the progression of atherosclerosis. Herein, we explored the role of TMAO in the stability of carotid atherosclerotic plaques and disclosed the underlying mechanisms. The unstable carotid artery plaque models were established in C57/BL6 mice. L-carnitine (LCA) and methimazole (MMI) administration were applied to increase and reduce TMAO levels. Hematoxylin and eosin (H&amp;E) staining, Sirius red, Perl's staining, Masson trichrome staining and immunohistochemical staining with CD68 staining were used for histopathology analysis of the carotid artery plaque. M1 and M2 macrophagocyte markers were assessed by RT-PCR to determine the polarization of RAW264.7 cells. MMI administration for 2 weeks significantly decreased the plaque area, increased the thickness of the fibrous cap and reduced the size of the necrotic lipid cores, whereas 5-week of administration of MMI induced intraplate hemorrhage. LCA treatment further deteriorated the carotid atherosclerotic plaque but with no significant difference. In mechanism, we found that TMAO treatment impaired the M2 polarization and efferocytosis of RAW264.7 cells with no obvious effect on the M1 polarization. In conclusion, the present study demonstrated that TMAO reduction enhanced the stability of carotid atherosclerotic plaque through promoting macrophage M2 polarization and efferocytosis.Synapse and synapse-associated proteins (SAPs) play critical roles in various neurodegeneration diseases and brain tumors. However, in lower-grade gliomas (LGG), SAPs have not been explored systematically. Herein, we are going to explore SAPs expression profile and its clinicopathological significance in LGG which can offer new insights to glioma therapy. In the present study, we integrate a list of SAPs that covered 231 proteins with synaptogenesis activity and post synapse formation. The LGG RNA-seq data were downloaded from GEO, TCGA and CGGA database. The prognosis associated SAPs in key modules of PPI (protein-protein interaction networks) was regarded as hub SAPs. Western blot, quantitative reverse transcription PCR (qRT-PCR) and immunochemistry results from HPA database were used to verify the expression of hub SAPs. There were 68 up-regulated SAPs and 44 down-regulated SAPs in LGG tissue compared with normal brain tissue. Data from function enrichment analysis revealed functions of differentially expressed SAPs in synapse organization and glutamatergic receptor pathway in LGGs. Survival analysis revealed that four SAPs, GRIK2, GABRD, GRID2 and ARC were correlate with the prognosis of LGG patients. Interestingly, we found that GABRD were up-regulated in LGG patients with seizures, indicating that SAPs may link to the pathogenesis of seizures in glioma patients. The four-SAPs signature was revealed as an independent prognostic factor in gliomas. Our study presented a novel strategy to assess the prognostic risks of LGGs, based on the expression of SAPs.Acute leukemia is a hematological malignant tumor. [https://www.selleckchem.com/products/gsk-3484862.html check details] Long non-coding RNA urothelial cancer-associated 1 (UCA1) is involved in the chemo-resistance of diverse cancers, but it is unclear whether UCA1 is associated with the sensitivity of acute leukemia cells to daunorubicin (DNR). DNR (100 nM) was selected for functional analysis. The viability, cell cycle progression, apoptosis, and invasion of treated acute leukemia cells (HL-60 and U-937) were evaluated by cell counting kit-8 (CCK-8) assay, flow cytometry assay, or transwell assay. Protein levels were detected with Western blot analysis. Expression patterns of UCA1 and miR-613 were assessed by quantitative real-time polymerase chain reaction (qRT-PCR). The relationship between UCA1 and microRNA-613 (miR-613) was verified by dual-luciferase reporter assay. We observed that UCA1 expression was elevated in HL-60 and U-937cells. DNR constrained viability, cell cycle progression, invasion, and facilitated apoptosis of HL-60 and U-937 cells in a dose-dependent manner, but these impacts mediated by DNR were reverted after UCA1 overexpression.