摘要：Background. The outbreak of COVID-19 started in mid-December 2019 in Wuhan, Central China. Up to February 18, 2020, SARS-CoV-2 has infected more than 70,000 people in China, and another 25 countries across five continents. In this study, we used 93 complete genomes of SARS-CoV-2 from the GISAID EpiFluTM database to decode the evolution and human-to-human transmissions of SARS-CoV-2 in the recent two months. Methods. Alignment of coding-regions was conducted haplotype analyses using DnaSP. Substitution sites were analyzed in codon. Evolutionary analysis of haplotypes used NETWORK. Population size changes were estimated using both DnaSP and Arlequin. Expansion date of population size was calculated based on the expansion parameter tau (τ) using the formula t=τ/2u. Findings. Eight coding-regions have 120 substitution sites, including 79 non-synonymous and 40 synonymous substitutions. Forty-two non-synonymous substitutions changed the biochemical property of amino acids. No evident combination was found. Fifty-eight haplotypes were classified as five groups, and 31 haplotypes were found in samples from both China and other countries, respectively. The rooted network suggested H13 and H35 to be ancestral haplotypes, and H1 (and its descendent haplotypes including all samples from the Hua Nan market) was derived H3 haplotype. Population size of SARS-CoV-2 were estimated to have a recent expansion on 6 January 2020, and an early expansion on 8 December 2019. Interpretation. Genomic variations of SARS-CoV-2 are still low in comparisons with published genomes of SARS-CoV and MERS-CoV. Phyloepidemiologic analyses indicated the SARS-CoV-2 source at the Hua Nan market should be imported from other places. The crowded market boosted SARS-CoV-2 rapid circulations in the market and spread it to the whole city in early December 2019. Furthermore, phyloepidemiologic approaches have recovered specific direction of human-to-human transmissions, and the import sources of international infectious cases.
摘要：Controllable D-D neutron sources have a long service life, low cost, and non-radioactivity. There are favorable prospects for its application in geophysical well logging, since traditional chemical radioactive sources used for well logging pose potential threats to the safety of the human body and environment. This paper presents an improved method to measure formation density that employs a D-D neutron source. In addition, the lithological effect on the measured density was removed to better estimate the formation porosity. First, we investigated the spatial distribution of capture gamma rays through Monte Carlo simulations as well as the relationship between the ratio of capture gamma ray counts and formation density to establish theoretical support for the design of density logging tools and their corresponding data processing methods. Second, we obtained the far to near detector counts of captured gamma rays for an optimized tool structure, and then established its correlation with the density and porosity of three typical formations with pure quartz, calcite, and dolomite minerals. Third, we determined the values for correcting the densities of sandstone and dolomite with the same porosity using limestone data as the reference and established the equations for calculating the correction values, which lays a solid foundation for accurately calculating formation porosity. We observed that the capture gamma ray counts first increased then decreased and varied in different formations; this was especially observed in high-porosity formations. Under the same lithologic conditions (rock matrix), as the porosity increases, the peak value of gamma ray counts moves toward the neutron source. At different detector-source distances, the ratio of the capture gamma ray counts was well correlated with the formation density. An equation of the formation density conversion was established based on the ratio of capture gamma ray counts at the detector-source distances of 30 cm and 65 cm, and the calculated values were consistent with the true values. After correction, the formation density was highly consistent with the true value of the limestone density, and the mean absolute error was -0.013 g/cm3. The calculated porosity values were very close to the true values, and the mean relative error was 2.33%, highlighting the accuracy of the proposed method. These findings provide a new method for developing D-D neutron source logging tools and their well-log data processing methods.
摘要：Background Cilostazol, an anti-platelet drug for treating coronary heart disease, has been reported to modulate immune cell functions. Plasmacytoid dendritic cells (pDCs) have been found to participate in the progression of atherosclerosis mainly through interferon a (IFN-alpha) production. Whether cilostazol influences pDCs activation is still not clear. In this study, we aimed to investigate the effects of cilostazol on cell activation and antigen presentation of pDCs in vitro in this study. Methods Peripheral blood mononuclear cells isolated by Ficoll centrifugation and pDCs sorted by flow cytometry were used in this study. After pretreated with cilostazol for 2 h, cells were stimulated with CpG-A, R848 or virus for 6 h or 20 h, or stimulated with CpG-B for 48 h and then co-cultured with naive T cell for five days. Cytokines in supernatant and intracellular cytokines were analyzed by ELISA or flow cytometry respectively. Results Our data indicated that cilostazol could inhibit IFN-alpha and tumor necrosis factor a (TNF-alpha) production from pDCs in a dose-dependent manner. In addition, the ability of priming naive T cells of pDCs was also impaired by cilostazol. The inhibitory effect was not due to cell killing since the viability of pDCs did not change upon cilostazol treatment. Conclusion Cilostazol inhibits pDCs cell activation and antigen presentation in vitro, which may explain how cilostazol protects against atherosclerosis.
摘要：Fungi have emerged as the fourth most common pathogens isolated in nosocomial bloodstream infections, and Candida albicans is the most common human fungal pathogen. Only a few antibiotics are effective in the treatment of fungal infections. In addition, the repetition and lengthy duration of fluconazole therapy has led to an increased incidence of azole resistance and treatment failure associated with C. albicans. To investigate the mechanism of drug resistance and explore new targets to treat clinically resistant fungal pathogens, we examined the large-scale gene expression profile of two sets of matched fluconazole-susceptible and -resistant bloodstream C. albicans isolates from bone marrow transplanted (BMT) patients for the first time by microarray analysis. More than 198 differentially expressed genes were identified and they were confirmed and validated by RT-PCR independently. Not surprisingly, the resistant phenotype is associated with increased expression of CDR mRNA, as well as some common genes involved in drug resistance such as CaIFU5, CaRTA2 and CaIFD6. Meanwhile, some special functional groups of genes, including ATP binding cassette (ABC) transporter genes (IPF7530, CaYOR1, CaPXA1), oxidative stress response genes (CaALD5, CaGRP1, CaSOD2, IPF10565), copper transport and iron mobilization-related genes (CaCRD1/2, CaCTR1/2, CaCCC2, CaFET3) were found to be differentially expressed in the resistant isolates. Furthermore, among these differentially expressed genes, some co-regulated with CaCDR1, CaCDR2 and CaIFU5, such as CaPDR16 and CaIFD6, have a DRE-like element and may interact with TAC1 in the promoter region. These findings may shed light on mechanisms of azole resistance in C. albicans and clinical antifungal therapy.