24 research outputs found

    Characterization of Francisella species isolated from the cooling water of an air conditioning system.

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    Strains of Francisella spp. were isolated from cooling water from an air conditioning system in Guangzhou, China. These strains are Gram negative, coccobacilli, non-motile, oxidase negative, catalase negative, esterase and lipid esterase positive. In addition, these bacteria grow on cysteine-supplemented media at 20 °C to 40 °C with an optimal growth temperature of 30 °C. Analysis of 16S rRNA gene sequences revealed that these strains belong to the genus Francisella. Biochemical tests and phylogenetic and BLAST analyses of 16S rRNA, rpoB and sdhA genes indicated that one strain was very similar to Francisella philomiragia and that the other strains were identical or highly similar to the Francisella guangzhouensis sp. nov. strain 08HL01032 we previously described. Biochemical and molecular characteristics of these strains demonstrated that multiple Francisella species exist in air conditioning systems

    On the Function, Subject, and Capacity of the Religious Property System in China

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    To construct our religious property system, we must first define its purpose and function, and then clarify the connotation, subject, and capacity of religious property, the premise of which is to scientifically understand the nature, purpose and function of religions. The"religious purpose"of the religious property system is different in its appeal to different subjects: The state, religious groups and believers. For different types of property, religious purposes differ in directness and indirectness, but they are unified in the realization of the basic religious policy of the Party and the state

    Prime-boost vaccination of mice and rhesus macaques with two novel adenovirus vectored COVID-19 vaccine candidates.

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    ABSTRACTCOVID-19 vaccines are being developed urgently worldwide. Here, we constructed two adenovirus vectored COVID-19 vaccine candidates of Sad23L-nCoV-S and Ad49L-nCoV-S carrying the full-length gene of SARS-CoV-2 spike protein. The immunogenicity of two vaccines was individually evaluated in mice. Specific immune responses were observed by priming in a dose-dependent manner, and stronger responses were obtained by boosting. Furthermore, five rhesus macaques were primed with 5 × 109 PFU Sad23L-nCoV-S, followed by boosting with 5 × 109 PFU Ad49L-nCoV-S at 4-week interval. Both mice and macaques well tolerated the vaccine inoculations without detectable clinical or pathologic changes. In macaques, prime-boost regimen induced high titers of 103.16 anti-S, 102.75 anti-RBD binding antibody and 102.38 pseudovirus neutralizing antibody (pNAb) at 2 months, while pNAb decreased gradually to 101.45 at 7 months post-priming. Robust T-cell response of IFN-γ (712.6 SFCs/106 cells), IL-2 (334 SFCs/106 cells) and intracellular IFN-γ in CD4+/CD8+ T cell (0.39%/0.55%) to S peptides were detected in vaccinated macaques. It was concluded that prime-boost immunization with Sad23L-nCoV-S and Ad49L-nCoV-S can safely elicit strong immunity in animals in preparation of clinical phase 1/2 trials

    Folic acid therapy reduces the first stroke risk associated with hypercholesterolemia among hypertensive patients

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    Background and Purpose - We sought to determine whether folic acid supplementation can independently reduce the risk of first stroke associated with elevated total cholesterol levels in a subanalysis using data from the CSPPT (China Stroke Primary Prevention Trial), a double-blind, randomized controlled trial. Methods - A total of 20 702 hypertensive adults without a history of major cardiovascular disease were randomly assigned to a double-blind daily treatment of an enalapril 10-mg and a folic acid 0.8-mg tablet or an enalapril 10-mg tablet alone. The primary outcome was first stroke. Results - The median treatment duration was 4.5 years. For participants not receiving folic acid treatment (enalapril-only group), high total cholesterol (≥ 200 mg/dL) was an independent predictor of first stroke when compared with low total cholesterol (\u3c200 mg/dL; 4.0% versus 2.6%; hazard ratio, 1.52; 95% confidence interval, 1.18-1.97; P=0.001). Folic acid supplementation significantly reduced the risk of first s roke among participants with high total cholesterol (4.0% in the enalapril-only group versus 2.7% in the enalapril-folic acid group; hazard ratio, 0.69; 95% confidence interval, 0.56-0.84 P\u3c0.001; number needed to treat, 78; 95% confidence interval, 52-158), independent of baseline folate levels and other important covariates. By contrast, among participants with low total cholesterol, the risk of stroke was 2.6% in the enalapril-only group versus 2.5% in the enalapril-folic acid group (hazard ratio, 1.00; 95% confidence interval, 0.75-1.30; P=0.982). The effect was greater among participants with elevated total cholesterol (P for interaction=0.024). Conclusions - Elevated total cholesterol levels may modify the benefits of folic acid therapy on first stroke. Folic acid supplementation reduced the risk of first stroke associated with elevated total cholesterol by 31% among hypertensive adults without a history of major cardiovascular diseases

    Semi-Supervised Deep Metric Learning Networks for Classification of Polarimetric SAR Data

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    Recently, classification methods based on deep learning have attained sound results for the classification of Polarimetric synthetic aperture radar (PolSAR) data. However, they generally require a great deal of labeled data to train their models, which limits their potential real-world applications. This paper proposes a novel semi-supervised deep metric learning network (SSDMLN) for feature learning and classification of PolSAR data. Inspired by distance metric learning, we construct a network, which transforms the linear mapping of metric learning into the non-linear projection in the layer-by-layer learning. With the prior knowledge of the sample categories, the network also learns a distance metric under which all pairs of similarly labeled samples are closer and dissimilar samples have larger relative distances. Moreover, we introduce a new manifold regularization to reduce the distance between neighboring samples since they are more likely to be homogeneous. The categorizing is achieved by using a simple classifier. Several experiments on both synthetic and real-world PolSAR data from different sensors are conducted and they demonstrate the effectiveness of SSDMLN with limited labeled samples, and SSDMLN is superior to state-of-the-art methods
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