BackgroundAtherosclerosis constitutes the leading contributor to morbidity and mortality in cardiovascular and cerebrovascular diseases. Lipid deposition and inflammatory response are the crucial triggers for the development of atherosclerosis. Recently, microRNAs (miRNAs) have drawn more attention due to their prominent function on inflammatory process and lipid accumulation in cardiovascular and cerebrovascular disease. Here, we investigated the involvement of miR-21 in lipopolysaccharide (LPS)-induced lipid accumulation and inflammatory response in macrophages.MethodsAfter stimulation with the indicated times and doses of LPS, miR-21 mRNA levels were analyzed by Quantitative real-time PCR. Following transfection with miR-21 or anti-miR-21 inhibitor, lipid deposition and foam cell formation was detected by high-performance liquid chromatography (HPLC) and Oil-red O staining. Furthermore, the inflammatory cytokines interleukin 6 (IL-6) and interleukin 10 (IL-10) were evaluated by Enzyme-linked immunosorbent assay (ELISA) assay. The underlying molecular mechanism was also investigated.ResultsIn this study, LPS induced miR-21 expression in macrophages in a time- and dose-dependent manner. Further analysis confirmed that overexpression of miR-21 by transfection with miR-21 mimics notably attenuated lipid accumulation and lipid-laden foam cell formation in LPS-stimulated macrophages, which was reversely up-regulated when silencing miR-21 expression via anti-miR-21 inhibitor transfection, indicating a reverse regulator of miR-21 in LPS-induced foam cell formation. Further mechanism assays suggested that miR-21 regulated lipid accumulation by Toll-like receptor 4 (TLR4) and nuclear factor-κB (NF-κB) pathway as pretreatment with anti-TLR4 antibody or a specific inhibitor of NF-κB (PDTC) strikingly dampened miR-21 silence-induced lipid deposition. Additionally, overexpression of miR-21 significantly abrogated the inflammatory cytokines secretion of IL-6 and increased IL-10 levels, the corresponding changes were also observed when silencing miR-21 expression, which was impeded by preconditioning with TLR4 antibody or PDTC.ConclusionsTaken together, these results corroborated that miR-21 could negatively regulate LPS-induced lipid accumulation and inflammatory responses in macrophages by the TLR4-NF-κB pathway. Accordingly, our research will provide a prominent insight into how miR-21 reversely abrogates bacterial infection-induced pathological processes of atherosclerosis, indicating a promising therapeutic prospect for the prevention and treatment of atherosclerosis by miR-21 overexpression.

The Three Gorges Project (TGP) is the world’s largest water conservation project. The post-construction low-flow water level at the same discharge below the dam has declined, but there remains disagreement over whether the flood level has increased. Measured water levels and upstream and downstream flow data from 1955 to 2016 show that, post-construction: (1) the low-flow water level at the same discharge decreased, and the lowest water level increased due to dry-season reservoir discharge; (2) the decline of the low-flow water level below the dam was less than the undercutting value of the flow channel of the river; (3) the flood level at the same discharge below the dam was slightly elevated, although peak water levels decreased; (4) flood characteristics changed from a high discharge–high flood level to a medium discharge – high flood level; and (5) an expected decline in the flood level downstream was not observed. Channel erosion and the adjustment of rivers and lakes tend to reduce flood levels, while river bed coarsening, vegetation, and human activities downstream increase the flood level. Although the flood control benefits of the Three Gorges Dam (TGD) and the upstream reservoirs are obvious, increased elevation of the downstream flood level remains a concern.

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Background: Patients with heart failure (HF) with diabetes mellitus have distinct biomarker profiles compared with those without diabetes mellitus. SFRP5 (secreted frizzled-related protein 5) is an anti-inflammatory adipokine with an important suppressing role on the development of type 2 diabetes mellitus (T2DM). This study aimed to evaluate the prognostic value of SFRP5 in patients with HF with and without T2DM. Methods: The study included 833 consecutive patients with HF, 312 (37.5%) of whom had T2DM. Blood samples were collected at presentation, and SFRP5 levels were measured. The primary outcome was the composite end points of first occurrence of HF rehospitalization or all-cause mortality during follow-up. Results: During median follow-up of 2.1 years, 335 (40.2%) patients in the cohort experienced the composite primary outcome. After adjustment for multiple risk factors, each doubling of SFRP5 level was associated with a 21% decreased risk of primary outcomes in the overall study population ( P <0.001). Subgroup analyses showed that the association between level of SFPR5 and primary outcomes may be stronger in patients with T2DM (hazard ratio, 0.69 [95% CI, 0.61–0.79]) than in patients without T2DM (hazard ratio, 0.89 [95% CI, 0.79–1.01]; interaction P =0.006). Similar associations were observed when taking SFRP5 as a categorical variable. Addition of SFRP5 significantly improved discrimination and reclassification of the incident primary outcomes beyond clinical risk factors and N-terminal pro-B-type natriuretic peptide in all patients with HF and those with T2DM (all P <0.01). Conclusions: SFRP5 is an independent novel biomarker for risk stratification in HF, especially in HF with T2DM.

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Fine-grained object retrieval has attracted extensive research focus recently. Its state-of-the-art schemes are typically based upon convolutional neural network (CNN) features. Despite the extensive progress, two issues remain open. On one hand, the deep features are coarsely extracted at image level rather than precisely at object level, which are interrupted by background clutters. On the other hand, training CNN features with a standard triplet loss is time consuming and incapable to learn discriminative features. In this paper, we present a novel fine-grained object retrieval scheme that conquers these issues in a unified framework. Firstly, we introduce a novel centralized ranking loss (CRL), which achieves a very efficient (1,000 times training speedup comparing to the triplet loss) and discriminative feature learning by a "centralized" global pooling. Secondly, a weakly supervised attractive feature extraction is proposed, which segments object contours with top-down saliency. Consequently, the contours are integrated into the CNN response map to precisely extract features "within" the target object. Interestingly, we have discovered that the combination of CRL and weakly supervised learning can reinforce each other. We evaluate the performance of the proposed scheme on widely-used benchmarks including CUB200-2011 and CARS196. We have reported significant gains over the state-of-the-art schemes, e.g., 5.4% over SCDA [Wei et al., 2017] on CARS196, and 3.7% on CUB200-2011.

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