Antagonistic bioactivity of an endophytic bacterium H-6

An endophytic bacterium, H-6, was isolated from leaves of Huperzia serrata grown in the Lushan Mountain, China. The strain was identified as Burkholderia sp. H-6 based on morphological, physiological and biochemical methods as well as on 16S rDNA analysis. This strain inhibited mycelium growth in vitro of 6 plant pathogenic fungi, especially of Phytophthora capsici, Fusarium graminearumt and Sclerotinia libertiana. In greenhouse pot experiments, soil drenches with cell densities of 106, 108 and 1010 CFU ml-1 H-6 reduced significantly P. capsici, in pepper seedling by 51.7, 58.7 and 60.2%, respectively, compared to the inoculated control, 3 weeks after sowing. Growth parameters such as lengths and fresh weights of roots and shoots of P. capsici-inoculated control plants were significantly lower compared to P. capsici-inoculated and H-6-treated plants, which is an added advantage of the strain used as potential biocontrol agent in future.Key words: Endophytic bacterium, 16S rDNA gene, antagonistic activity, Huperzia serrata

Genetic diversity of Escherichia coli isolated from commercial swine farms revealed by enterobacterial repetitive intergenic consensus PCR (ERIC-PCR) and repetitive extragenic palindrome PCR (REP-PCR)

The objective of this study was to use enterobacterial repetitive intergenic consensus PCR (ERIC-PCR) and repetitive extragenic palindrome PCR (REP-PCR) for the analysis of genetic diversity among Escherichia coli strains isolated from commercial swine farms in Sichuan province of China. Thirty four strains of E. coli were selected by selective medium and conventional biochemical test from fresh stool samples of swines in five farms in Sichuan province. The isolates were identified by 160 kinds of E. coli O serums. The results show that 30 strains were determined among 34 E. coli isolates, 12 kinds of O serogroups were obtained on the basis of the agglutination test. The predominant types are O23, O113 and O120, representing 35.4%. Furthermore, the genotypes and phylogenetic relationship of all isolates were analysed by Enterobacterial repetitive intergenic consensus PCR (ERIC-PCR) and repetitive extragenic palindrome PCR (REP-PCR), 34 E. coli isolates were clustered to 19 ERIC-PCR genotypes and 13 REP-PCR genotypes. The isolates from the same farm or sharing the same serotyping showed different genotype. And the isolates which could not be serotyped were genotyped by ERIC-PCR and REP-PCR. The analysis of genetic type and original source revealed that isolates from different farms had different genetic types. The subtypes of E. coli are also different within a single farm. Genetic variability with E. coli strains isolated from swine farms in China has been demonstrated. The presence of ERIC-PCR and REP-PCR sequences in the genome of E. coli was confirmed. ERIC-PCR and REP-PCR techniques are more rapid methods for molecular typing of E. coli strain. They are also useful methods for diversity survey of E. coli and the two methods analyzes genetic diversity of E. coli isolated in Sichuan of China.Key words: Escherichia coli, serotype, enterobacterial repetitive intergenic consensus PCR (ERIC-PCR), repetitive extragenic palindrome PCR (REP-PCR)

Luminescent Organic–Inorganic Hybrids of Functionalized Mesoporous Silica SBA-15 by Thio-Salicylidene Schiff Base

Novel organic–inorganic mesoporous luminescent hybrid material N, N′-bis(salicylidene)-thiocarbohydrazide (BSTC-SBA-15) has been obtained by co-condensation of tetraethyl orthosilicate and the organosilane in the presence of Pluronic P123 surfactant as a template. N,N′-bis(salicylidene)-thiocarbohydrazide (BSTC) grafted to the coupling agent 3-(triethoxysilyl)-propyl isocyanate (TESPIC) was used as the precursor for the preparation of mesoporous materials. In addition, for comparison, SBA-15 doped with organic ligand BSTC was also synthesized, denoted as BSTC/SBA-15. This organic–inorganic hybrid material was well-characterized by X-ray diffraction, Fourier transform infrared spectroscopy, transmission electron microscopy (HRTEM), and photoluminescence spectra, which reveals that they all have high surface area, uniformity in the mesostructure. The resulting materials (BSTC-SBA-15 and BSTC/SBA-15) exhibit regular uniform microstructures, and no phase separation happened for the organic and the inorganic compounds was covalently linked through Si–O bonds via a self-assemble process. Furthermore, the two materials have different luminescence range: BSTC/SBA-15 presents the strong dominant green luminescence, while BSTC-functionalized material BSTC-SBA-15 shows the dominant blue emission

Wettability of amorphous and nanocrystalline Fe78B13Si9 substrates by molten Sn and Bi

The wettability of amorphous and annealing-induced nanocrystalline Fe78B13Si9 ribbons by molten Sn and Bi at 600 K was measured using an improved sessile drop method. The results demonstrate that the structural relaxation and crystallization in the amorphous substrates do not substantially change the wettability with molten Bi because of their invariable physical interaction, but remarkably deteriorate the wettability and interfacial bonding with molten Sn as a result of changing a chemical interaction to a physical one for the atoms at the interface

Critical Role of NADPH Oxidase in Neuronal Oxidative Damage and Microglia Activation following Traumatic Brain Injury

BACKGROUND: Oxidative stress is known to play an important role in the pathology of traumatic brain injury. Mitochondria are thought to be the major source of the damaging reactive oxygen species (ROS) following TBI. However, recent work has revealed that the membrane, via the enzyme NADPH oxidase can also generate the superoxide radical (O(2)(-)), and thereby potentially contribute to the oxidative stress following TBI. The current study thus addressed the potential role of NADPH oxidase in TBI. METHODOLOGY/PRINCIPAL FINDINGS: The results revealed that NADPH oxidase activity in the cerebral cortex and hippocampal CA1 region increases rapidly following controlled cortical impact in male mice, with an early peak at 1 h, followed by a secondary peak from 24-96 h after TBI. In situ localization using oxidized hydroethidine and the neuronal marker, NeuN, revealed that the O(2)(-) induction occurred in neurons at 1 h after TBI. Pre- or post-treatment with the NADPH oxidase inhibitor, apocynin markedly inhibited microglial activation and oxidative stress damage. Apocynin also attenuated TBI-induction of the Alzheimer's disease proteins β-amyloid and amyloid precursor protein. Finally, both pre- and post-treatment of apocynin was also shown to induce significant neuroprotection against TBI. In addition, a NOX2-specific inhibitor, gp91ds-tat was also shown to exert neuroprotection against TBI. CONCLUSIONS/SIGNIFICANCE: As a whole, the study demonstrates that NADPH oxidase activity and superoxide production exhibit a biphasic elevation in the hippocampus and cortex following TBI, which contributes significantly to the pathology of TBI via mediation of oxidative stress damage, microglial activation, and AD protein induction in the brain following TBI

Acetylation of the Pro-Apoptotic Factor, p53 in the Hippocampus following Cerebral Ischemia and Modulation by Estrogen

Recent studies demonstrate that acetylation of the transcription factor, p53 on lysine(373) leads to its enhanced stabilization/activity and increased susceptibility of cells to stress. However, it is not known whether acetylation of p53 is altered in the hippocampus following global cerebral ischemia (GCI) or is regulated by the hormone, 17β-estradiol (17β-E(2)), and thus, this study examined these issues.The study revealed that Acetyl p53-Lysine(373) levels were markedly increased in the hippocampal CA1 region after GCI at 3 h, 6 h and 24 h after reperfusion, an effect strongly attenuated by 17β-E(2). 17β-E(2) also enhanced interaction of p53 with the ubiquitin ligase, Mdm2, increased ubiquitination of p53, and induced its down-regulation, as well as attenuated elevation of the p53 transcriptional target, Puma. We also observed enhanced acetylation of p53 at a different lysine (Lys(382)) at 3 h after reperfusion, and 17β-E(2) also markedly attenuated this effect. Furthermore, administration of an inhibitor of CBP/p300 acetyltransferase, which acetylates p53, was strongly neuroprotective of the CA1 region following GCI. In long-term estrogen deprived (LTED) animals, the ability of 17β-E(2) to attenuate p53 acetylation was lost, and intriguingly, Acetyl p53-Lysine(373) levels were markedly elevated in sham (non-ischemic) LTED animals. Finally, intracerebroventricular injections of Gp91ds-Tat, a specific NADPH oxidase (NOX2) inhibitor, but not the scrambled tat peptide control (Sc-Tat), attenuated acetylation of p53 and reduced levels of Puma following GCI.The studies demonstrate that p53 undergoes enhanced acetylation in the hippocampal CA1 region following global cerebral ischemia, and that the neuroprotective agent, 17β-E(2), markedly attenuates the ischemia-induced p53 acetylation. Furthermore, following LTED, the suppressive effect of 17β-E(2) on p53 acetylation is lost, and p53 acetylation increases in the hippocampus, which may explain previous reports of increased sensitivity of the hippocampus to ischemic stress following LTED

Validation and refinement of two interpretable models for coronavirus disease 2019 prognosis prediction

Objective: To validate two proposed coronavirus disease 2019 (COVID-19) prognosis models, analyze the characteristics of different models, consider the performance of models in predicting different outcomes, and provide new insights into the development and use of artificial intelligence (AI) predictive models in clinical decision-making for COVID-19 and other diseases. Materials and Methods: We compared two proposed prediction models for COVID-19 prognosis that use a decision tree and logistic regression modeling. We evaluated the effectiveness of different model-building strategies using laboratory tests and/or clinical record data, their sensitivity and robustness to the timings of records used and the presence of missing data, and their predictive performance and capabilities in single-site and multicenter settings. Results: The predictive accuracies of the two models after retraining were improved to 93.2% and 93.9%, compared with that of the models directly used, with accuracies of 84.3% and 87.9%, indicating that the prediction models could not be used directly and require retraining based on actual data. In addition, based on the prediction model, new features obtained by model comparison and literature evidence were transferred to integrate the new models with better performance. Conclusions: Comparing the characteristics and differences of datasets used in model training, effective model verification, and a fusion of models is necessary in improving the performance of AI models