Streptomyces camelliae sp. nov., isolated from rhizosphere soil of Camellia oleifera Abel

A novel actinobacterium strain, designated HUAS 2-6 T, was isolated from the rhizosphere soil of Camellia oleifera Abel collected from Taoyuan County, Northwestern Hunan Province, South China. This strain was subjected to a polyphasic taxonomic study. Strain HUAS 2-6 T is characterized by morphology typical of members of the genus Streptomyces, with deep purplish vinaceous aerial mycelia and deep dull lavender substrate mycelia. Strain HUAS 2-6 T, based on the full-length 16S rRNA gene sequence analysis, exhibited the highest similarities to S. puniciscabiei S77T (99.31%), S. filipinensis NBRC 12860 T (99.10%), S. yaanensis CGMCC 4.7035 T (99.09%), S. fodineus TW1S1T (99.08%), S. broussonetiae CICC 24819 T (98.76%), S. achromogenes JCM 4121 T (98.69%), S. barringtoniae JA03T (98.69%), and less than 98.70% with other validly species. In phylogenomic tree, strain HUAS 2-6 T was clustered together with S. broussonetiae CICC 24819 T, suggesting that they were closely related to each other. However, average nucleotide identity (ANI) and digital DNA-DNA hybridisation (dDDH) between them were much less than the species cutoff values (ANI 96.7% and dDDH 70%). Moreover, in phenotypic and chemotaxonomic characteristics, strain HUAS 2-6 T is distinct from S. broussonetiae CICC 24819 T. On the basis of the polyphasic data, strain HUAS 2-6 T is proposed to represent a novel species, Streptomyces camelliae sp. nov. (= MCCC 1K04729T = JCM 35918 T).

Changes of mercury and methylmercury content and mercury methylation in Suaeda salsa soil under different salinity

In this paper, we studied the changes of Hg and MeHg contents in Liaohe estuarine Suaeda salsa soils under anaerobic conditions by simulated indoor incubation at constant temperature and whether the changes of salinity (CK, 0.5%, 1.0%, 1.5%, 2.0%) affected SRB and dominated the formation of MeHg. The lowest Hg content is found in the subsurface Suaeda salsa soils at 2.0% salinity. The MeHg content in the soil also showed a general trend of increasing and then decreasing with increasing flooding salinity, and the MeHg content was higher at 0.5-1.0% flooding salinity. SRB was present in the soil under all salinity conditions and reached the maximum value at 15 days of incubation. The SRB content was higher under CK, S1 and S2 conditions, and the soil MeHg content showed a significant positive correlation with the number of SRB bacteria, indicating that the formation of MeHg was related to SRB which is of great significance to the study of estuarine wetlands.

Electroencephalogram based communication system for locked in state person using mentally spelled tasks with optimized network model

Due to growth in population, Individual persons with disabilities are increasing daily. To overcome the disability especially in Locked in State (LIS) due to Spinal Cord Injury (SCI), we planned to design four states moving robot from four imagery tasks signals acquired from three electrode systems by placing the electrodes in three positions namely T1, T3 and FP1. At the time of the study we extract the features from Continuous Wavelet Transform (CWT) and trained with Optimized Neural Network model to analyze the features. The proposed network model showed the highest performances with an accuracy of 93.86 % then that of conventional network model. To confirm the performances we conduct offline test. The offline test also proved that new network model recognizing accuracy was higher than the conventional network model with recognizing accuracy of 97.50 %. To verify our result we conducted Information Transfer Rate (ITR), from this analysis we concluded that optimized network model outperforms the other network models like conventional ordinary Feed Forward Neural Network, Time Delay Neural Network and Elman Neural Networks with an accuracy of 21.67 bits per sec. By analyzing classification performances, recognizing accuracy and Information Transformation Rate (ITR), we concluded that CWT features with optimized neural network model performances were comparably greater than that of normal or conventional neural network model and also the study proved that performances of male subjects was appreciated compared to female subjects.