Certain bacteria use cell-to-cell chemical communication to coordinate community-wide phenotypic expression, including swarming motility, antibiotic biosynthesis, and biofilm production. Here we present a marine gram-positive bacterium that secretes secondary metabolites capable of quenching quorum sensing-controlled behaviors in several gram-negative reporter strains. Isolate C42, a Halobacillus salinus strain obtained from a sea grass sample, inhibits bioluminescence production by Vibrio harveyi in cocultivation experiments. With the use of bioassay-guided fractionation, two phenethylamide metabolites were identified as the active agents. The compounds additionally inhibit quorum sensing-regulated violacein biosynthesis by Chromobacterium violaceum CV026 and green fluorescent protein production by Escherichia coli JB525. Bacterial growth was unaffected at concentrations below 200 g/ml. Evidence is presented that these nontoxic metabolites may act as antagonists of bacterial quorum sensing by competing with N-acyl homoserine lactones for receptor binding.Taxonomically diverse marine bacteria have proven to be a rich resource for the discovery of structurally unique and bioactive secondary metabolites (5). Given the intense microbial competition for resources such as space and nutrients, it is probable that many excreted metabolites help mediate microbe-microbe interactions. Various antibiotics have been implicated as chemical defenses for marine bacteria, thus suggesting a role for the biosynthesis of toxic metabolites. For example, a pelagic Alteromonas species produces the antibiotic 2-n-pentyl-4-quinolinol, capable of influencing bacterial community structure on particles (25), and production of the antibiotic andrimid by a marine Vibrio species prevents colonization of surfaces by the particle specialist Vibrio cholerae (26).Though not yet widely studied, the secretion of nontoxic molecules could also play important roles in antagonistic marine microbial interactions. Quorum sensing pathways of competing bacteria are potential targets for such nontoxic chemical defenses. Bacterial communication is facilitated by the production and subsequent recognition of small signaling molecules (autoinducers) and can regulate important phenotypes, including bioluminescence, biofilm formation, swarming motility, antibiotic biosynthesis, and virulence factor production (3, 7, 15). Gram-negative bacteria commonly use N-acyl homoserine lactones (AHL) as signaling molecules, which bind their cognate receptor proteins to activate gene expression (10). These autoinducers share a conserved L-homoserine lactone moiety, and the length and sites of oxidation on the acyl chain dictate the species specificity (37). In contrast, gram-positive bacteria generally accomplish quorum sensing using posttranslationally modified peptides as autoinducers. For example, Staphylococcus aureus uses cyclic oligopeptides to regulate virulence factor production (11).Here we report the production of nontoxic secondary metabolites by a marine gram-pos...

The purified inactivated SARS vaccine could induce high levels of neutralizing antibody, and protect the monkeys from the challenge of SARS-CoV. The SARS vaccine prepared in the study appeared to be safe in monkeys.

The study aimed to evaluate the prevalence and possible factors associated with burnout (BO) among undergraduates in a university setting in Dali. This cross-sectional study involved students enrolled in different specialties. The method of stratified random sampling was used to conduct the investigation. The questionnaire included Maslach Burnout Inventory and the influencing factors. The data were analyzed using SPSS 16.0 (SPSS Inc., Chicago, IL). The quantitative data were compared using t tests or ANOVA. Multiple linear regression was used to assess the relationship between BO risk and relevant influencing factors. The prevalence of study BO was 38.1%. Significant differences of the mean scores on BO and low personal efficacy were observed between men and women, with women obtaining a higher score ( t = –2.588, P = .010; t = –2.929, P = .003; respectively). The scores of overall BO, emotional exhaustion (EE), and cynicism were low, whereas that of professional efficacy was higher for students with excellent marks ( P = .000). Students majoring in liberal arts obtained low scores of overall BO, EE, and cynicism. Nevertheless, their score for professional efficacy was higher than those from other specializations ( P < .05). Total BO, as the dependent variable, revealed that 3 predictors (social factors, school factors, and interpersonal communication) accounted for 30.8% of the variance ( R 2 = 0.308). A regression analysis of EE as the dependent variable identified that 2 variables (social and school factors) explained 45.8% of the variance ( R 2 = 0.458). BO among undergraduates is present in a university setting in Dali. A variety of factors including social factors, school factors, and interpersonal communication can influence the prevalence of BO. Therefore, society should strengthen employment and further understand psychology; schools and families must pay attention to the psychological development of college students.

In recent years, big data technology has been developed rapidly, among which data management and data analysis in big data technology are widely used at present, and have been successfully applied in all walks of life. Applying big data technology to the field of education is the current mainstream trend, and the use of big data technology for graduate education management is also one of the current hot topics. However, there are still many deficiencies in the existing graduate educational administration management mode. Therefore, this paper puts forward the innovation research of graduate educational administration management mode under the background of big data. This paper makes an in-depth investigation on the main problems existing in the traditional mode of graduate educational administration management in Colleges and universities. According to the results, the main problems are the lack of sense of belonging to the class, poor information transmission, and the disconnection between class management and tutor management. In view of these problems, this paper proposes an optimization and improvement scheme based on big data technology. According to the actual needs of the current graduate education management in China’s colleges and universities, combined with the advanced big data management and analysis technology, the program establishes a new big data technology university graduate educational administration management mode. The improvement scheme of this paper makes up for the shortcomings of the traditional mode of graduate educational administration. The corresponding survey results show that the graduate management mode based on big data technology can better integrate the school network resources, improve the management ability of the school and meet the needs of students.

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