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Background Aedes albopictus is the dominant mosquito species in residential areas in Shanghai. There are many types of small containers with accumulated water in residential areas, providing a large number of breeding environments for Aedes alpopicuts and leading to an increasing transmission risk of mosquito-borne diseases. Objective To use random forest to predict breeding of Aedes mosquitoes in small aquatic container habitat in two concentrated reconstruction communities of rural areas in Shanghai, and to understand associated influence of environmental factors on the breeding of Aedes mosquitoes in the process of urbanization.Methods Small-scale habitat surveys of Aedes mosquitoes were carried out in two suburb concentrated reconstruction communities (Community A and B) in Shanghai, and the environment where the habitat was located was recorded and analyzed in both communities. The habitat where eggs, larvae, or pupae were found was recorded as positive. Spatial weight matrix was applied on a household basis, and global Moran's I index was used to carry out spatial autocorrelation analysis on the small-scale habitat and positive habitat in the environment of the two communities. When Moran's I is greater than 0, it means that the data present a positive spatial correlation; when Moran's I is less than 0, it means that the data are spatially negatively correlated; when Moran's I is 0, the spatial distribution is random. Combining the results of P and Z values, we explored the spatial distribution characteristics of small-scale habitat and positive habitat in the community environment. Random forest algorithm in machine learning was used to classify and sort environmental-related factors, and predict the breeding of Aedes mosquitoes in small aquatic habitat; receiver operating characteristic (ROC) curve was used to carry out model fitting evaluation. Results The environmental factors including building location (χ2=23.35, P<0.001), open space (χ2=8.83, P=0.003), and having trees (χ2=11.02, P=0.001) had a significant impact on the positive rate of small-scale habitat. The results of spatial characteristics analysis showed that the global Moran's I index of small-scale habitat was −0.092 (Z=−1.09, P=0.274) in Community A and 0.034 (Z=0.52, P=0.602) in Community B, and the global Moran's I index of positive habitat was −0.092 (Z=−1.14, P=0.255) in Community A and 0.070 (Z=0.95, P=0.342) in Community B. Since the P values of Community A and B were greater than 0.1 and the Z values were between −1.65 and 1.65, for both small-scale habitat and positive habitat the spatial characteristics were randomly distributed and no significant spatial aggregation was found. In the fitted random forest algorithm classification prediction model with the top 10 characteristic factors of importance, the area under curve (AUC) value was 0.95, and the prediction fitting effect was satisfactory. The results of classification and sorting indicated that counts of household small-scale habitat and positive habitat were the most important factors for breeding. Conclusion The random forest model constructed by environmental factor indicators can be used to predict the breeding situation of Aedes mosquitoes in small-scale aquatic habitat, and provide a basis for scientific prevention and control of mosquito breeding for the target area.
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Coronavirus disease 2019 (COVID-19) has caused the public health crisis in the whole world. Anti-androgens block severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) entry and protect against severe clinical COVID-19 outcomes. GT0918, a novel androgen receptor antagonist, accelerated viral clearance and increased recovery rate in outpatients by blocking SARS-CoV-2 infection though down-regulating ACE2 and TMPRSS2 expression. Further clinical study showed that GT0918 reduced mortality rate and shortened hospital stay in hospitalized COVID-19 patients. GT0918 also exhibits protective efficacy in severe COVID-19 patient in critical care. However, the mechanism of GT0918 treatment for severe COVID-19 disease is unknown. Here, we found GT0918 decreased the expression and secretion of proinflammatory cytokines through NF-{kappa}B signaling pathway. The acute lung injury induced by LPS or Poly(I:C) was also attenuated in GT0918-treated mice, compared with vehicle control group. Moreover, GT0918 elevated the NRF2 protein level but not mRNA transcription activity. GT0918 induced proinflammatory cytokines downregulation was partially dependent on NRF2. In conclusion, our data demonstrate that GT0918 reduced cytokine release and suppressed inflammatory responses through inhibiting NF-{kappa}B signaling and activating NRF2. GT0918 is not only effective for treatment of mild to moderate COVID-19 patients, but also a potential therapeutic drug for severe COVID-19 patients by reducing the risk of cytokine storm and acute respiratory distress syndrome.
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BackgroundP.1 lineage (Gamma) was first described in the State of Amazonas, northern Brazil, in the end of 2020, and has emerged as a very important variant of concern (VOC) of SARS-CoV-2 worldwide. P.1 has been linked to increased infectivity, higher mortality and immune evasion, leading to reinfections and potentially reduced efficacy of vaccines and neutralizing antibodies. MethodsThe samples of 276 patients from the State of Amazonas were sent to a central referral laboratory for sequencing by gold standard techniques, through Illumina MiSeq platform. Both global and regional phylogenetic analyses of the successfully sequenced genomes were conducted through maximum likelihood method. Multiple alignments were obtained including previously obtained unique human SARS-CoV-2 sequences. The evolutionary histories of spike and non-structural proteins from ORF1a of northern genomes were described and their molecular evolution was analyzed for detection of positive (FUBAR, FEL, and MEME) and negative (FEL and SLAC) selective pressures. To further evaluate the possible pathways of evolution leading to the emergence of P.1, we performed specific analysis for copy-choice recombination events. A global phylogenomic analysis with subsampled P.1 and B.1.1.28 genomes was applied to evaluate the relationship among samples. ResultsForty-four samples from the State of Amazonas were successfully sequenced and confirmed as P.1 (Gamma) lineage. In addition to previously described P.1 characteristic mutations, we find evidence of continuous diversification of SARS-CoV-2, as rare and previously unseen P.1 mutations were detected in spike and non-structural protein from ORF1a. No evidence of recombination was found. Several sites were demonstrated to be under positive and negative selection, with various mutations identified mostly in P.1 lineage. According to the Pango assignment, phylogenomic analyses indicate all samples as belonging to the P.1 lineage. ConclusionP.1 has shown continuous evolution after its emergence. The lack of clear evidence for recombination and the positive selection demonstrated for several sites suggest that this lineage emergence resulted mainly from strong evolutionary forces and progressive accumulation of a favorable signature set of mutations.
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Objectivemany potential factors contribute to the outbreak of COVID-19.It aims to explore the effects of various meteorological factors on the incidence of COVID-19. MethodsTaking Hubei province of China as an example, where COVID-19 was first reported and there were the most cases, we collected 53 days of confirmed cases (total 67773 cases) and ten meteorological parameters up to March 10. Correlation analysis and linear regression were used to judge the relationship of meteorological factors and increment of COVID-19 confirmed cases. ResultsUnder 95% CI, the increment of confirmed cases in Hubei were correlated with four meteorological parameters of average pressure, average temperature, minimum temperature and average water vapor pressure (equivalent to absolute humidity).The average pressure was positively correlated with the increment (r=+0.358).The negative correlations included average temperature (r=-0.306), minimum temperature (r=-0.347), and average water vapor pressure (r=-0.326). The linear regression results show if minimum temperature increases by 1{square}, the incremental confirmed cases in Hubei decreases by 72.470 units on average. ConclusionStatistically, the incidence of COVID-19 was correlated with average pressure, average temperature, minimum temperature and average water vapor pressure. It is positively correlated with the average pressure and negatively correlated with the other three parameters. Compared with relative humidity, 2019-nCov is more sensitive to water vapor pressure. The reason why the epidemic situation in Hubei expanded rapidly is significantly related to the climate characteristics of low temperature and dryness of Hubei in winter.
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Cytochrome P450 (CYP) enzymes metabolize numerous endogenous substrates, such as retinoids, androgens, estrogens and vitamin D, that can modulate important cellular processes, including proliferation, differentiation and apoptosis. The aim of this study is to characterize the expression of CYP genes in CD34+ human cord blood hematopoietic stem and early progenitor cells (CBHSPCs) as a first step toward assessment of the potential biological functions of CYP enzymes in regulating the expansion or differentiation of these cells. CD34+ CBHSPCs were purified from umbilical cord blood via antibody affinity chromatography. Purity of CD34+ CBHSPCs was assessed using fluorescence-activated cell sorting. RNA was isolated from purified CD34+ CBHSPCs and total mononuclear cells (MNCs) for RNA-PCR analysis of CYP expression. Fourteen human CYPs were detected in the initial screening with qualitative RT-PCR in CD34+ CBHSPCs. Further quantitative RNA-PCR analysis of the detected CYP transcripts yielded evidence for preferential expression of CYP2R1 in CD34+ CBHSPCs relative to MNCs; and for greater expression of CYP1B1 in MNCs relative to CD34+ CBHSPCs. These findings provide the basis for further studies on possible functions of CYP2R1 and CYP1B1 in CBHSPCs׳ proliferation and/or differentiation and their potential utility as targets for drugs designed to modulate CD34+ CBHSPC expansion or differentiation.
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Objective To investigate the effects of selenium-and zinc-enriched probiotics on the content of selenium and zinc in blood,antioxidation function and intestinal microflora in canine.Method Eight 18-month native canines,female and male in half,were randomly divided into the control and treatment groups on average.The control group received basal diet,the treatment group received basal diet supplemented with 2.0g selenium-and zinc-enriched probiotics everyday.To determine the experimental indices,the samples were collected on D0,D15 and D30,respectively.Results Compared with the control group,on D15,the content of selenium and zinc in blood,blood GPX,serum SOD,T-AOC and the amount of Lactobacillus in the experimental group were significantly increased,while the amount of Escherichia coli significantly decreased,but the serum MDA and the amount of Bifidobacterium,Staphylococcus and Enterococcus had no significant change.On D30,the content of selenium in blood,serum SOD,T-AOC and the amount of Lactobacillus were very significantly increased,while the content of zinc in blood,blood GPX and the amount of Bifidobacterium significantly increased;but serum MDA and the amount of Escherichia coli,Staphylococcus and Enterococcus very significantly decreased.Conclusion Selenium-and zinc-enriched probiotics could increase content of selenium and zinc in blood,enhance antioxidation function,improve and regulate the intestinal microflora.
