Effects of Weak Electric Fields on the Denitrification Performance of Pseudomonas stutzeri: Insights into Enzymes and Metabolic Pathways.

Enhanced denitrification has been reported under weak electric fields. However, it is difficult to investigate the mechanism of enhanced denitrification due to the complex interspecific interactions of mixed-culture systems. In this study, Pseudomonas stutzeri, capable of denitrification under anaerobic conditions, was selected for treating low COD/N (2.0, ratio between concentration of chemical oxygen demand and NO3--N) artificial wastewater under constant external voltages of 0.2, 0.4, and 0.6 V. The results revealed that P. stutzeri exhibited the highest efficiency in nitrate reduction at 0.2 V. Moreover, the maximum nitrate removal rate was 15.96 mg/(L·h) among the closed-circuit groups, 19.39% higher than that under the open-circuit group. Additionally, a notable reduction in nitrite accumulation was observed under weak electric fields. Enzyme activity analysis showed that the nitrate reductase activities were significantly increased among the closed-circuit groups, while nitrite reductase activities were inhibited. Transcriptomic analysis indicated that amino acid metabolism, carbohydrate metabolism, and energy metabolism were increased, enhancing the resistance of P. stutzeri to environmental stress and the efficiency of carbon source utilization for denitrification. The current study examined the impacts of weak electric fields on enzyme activities and microbial metabolic pathways and offers valuable insights into the mechanism by which denitrification is enhanced by weak electric fields.

[Microbial Community Composition and Diversity in Metal Sulfide Mine Water Systems].

To understand the characteristics of heavy metal pollution and physicochemical properties caused by mining activities in mine water systems and the response of the microbial community to habitats with different contamination levels, this study selected different types of water (mining area wastewater, spoil heap area wastewater, dressing area wastewater, mine seepage water, and pond water) as the variables related to the mining activities in the water system of the Shizishan mining area in Tongling, Anhui Province. The pollution characteristics and physicochemical properties were compared, and the relationship between environmental factors and the microbial communities were analyzed. The results showed that the content of heavy metals, the physicochemical properties, and the structure and diversity of the microbial community of different types of water were significantly different in different mine areas, among which the most seriously polluted areas were the mining area, the spoil heap area, and the dressing area. There were significant differences in microbial community structure among different functional types of wastewaters, and the diversity and abundance of the microbial community in DW with the heaviest heavy metal pollution were weaker than those in the other four regions. PcoA analysis showed that samples of similar water types had similar clustering. Spearman correlation heat map analysis and canonical correlation analysis (CCA) indicated that heavy metal pollution, pH, electrical conductivity (EC), SO2-4, and chemical oxygen demand (COD) had the greatest effect on the microbial communities in the mine water systems. Moreover, this study found that Proteobacteria, Euryarchaeota, and Bacteroidetes dominated in mine water systems, and their potential use could be explored in the future. Our results provide a better understanding of the different types of water pollution characteristics in mine water systems and the key factors that determine the microbial community structure.

Ecological Effects of Heavy Metal Pollution on Soil Microbial Community Structure and Diversity on Both Sides of a River around a Mining Area.

The objectives of this study were to understand the characteristics of heavy metal pollution caused by mining activities on the two sides of the Shun'an river and the response of soil microorganisms to the habitats by different contamination levels and vegetation. This paper selected soil samples from the banks of the Shun'an River near the Shizishan mining area, which is at the left of the river, in Tongling, Anhui Province, China. Using Illumina MiSeq 2500 technology, we analyzed the relationship between environmental factors and microbial communities. As the distance from the mining area increased, the heavy metal comprehensive pollution and potential risk value decreased. Additionally, the pollution severity and risk value of the left bank, where the mining area lies, were generally higher than those of the right bank. Because the symmetric sampling points on both banks of the river had similar planting types, their environmental factors and microbial community structure were similar and clustered. However, under different vegetation, the paddy soils tended to have a higher nutrient content and community richness and diversity than the vegetable fields or the abandoned land. It was found that soil microbial communities in this area were mostly affected by pH and Nemerow pollution index (PN). The pH significantly affected the abundance and structure of most microorganisms. In addition, Proteobacteria, Acidobacteria, and Bacteroidetes had significant tolerance to Zn, Pb, and Cd. By exploring the potential use of these tolerant microorganisms, we seek to provide strains and the theoretical basis for the bioremediation of areas contaminated by heavy metal.

[Effects of Different Land Use Types on Microbial Community Diversity in the Shizishan Mining Area].

Soil microorganisms play an important role in ecosystem function. Soil microbial community structure can be used to feed back the status of heavy metal pollution in soil at different functional areas of mines related to mining activities. Samples of four different land use types (vegetable garden, tailings reservoir, heap mining area, and dressing area) were collected in the Shizishan mining area, Tongling, Anhui Province, to determine the effect of heavy metal pollution on microbial community structure. Soil physical and chemical properties and heavy metal contents of the four different land use types were measured, and soil microbial community abundance and structure diversity were analyzed by Illumina MiSeq high-throughput sequencing technology. The results show that there are significant differences in physical and chemical properties between different regions. The comprehensive pollution index of Nemerow is heap mining area (7.28) > dressing area (6.99) > tailings reservoir (6.55) > vegetable garden (5.92). The distribution of microbial community abundance and structure diversity was tailings reservoir > dressing area > vegetable garden > heap mining area. In addition, principal coordinates analysis (PCoA), canonical correspondence analysis (CCA), and correlation analysis showed that land use type, soil pH and heavy metal content had significant effects on the microbial community. The dominant soil microbial communities at the phylum level were Proteobacteria, Bacteroidetes, Acidobacteria, and Actinobacteria, at the class level were ß-Proteobacteria, α-Proteobacteria, and γ-Proteobacteria, and at the genus level were Flavobacterium, Kaistobacter, and Ramlibacter. The bacteria that are more tolerant to heavy metals are Proteobacteria, Firmicutes, ß-Proteobacteria, and Kaistobacter. These results have deepened our understanding of microbial changes and aggregation patterns in soils of heavy-metal-contaminated mining areas. This study can provide bacterial species and theoretical basis for bioremediation of heavy metal mining areas.

Correlative factors for organic psychotic symptoms in patients following traumatic brain injury.

OBJECTIVE: To investigate the correlative factors for organic psychotic symptoms following traumatic brain injury (TBI). METHODS: In the current study, 391 subjects who had undergone forensic identification of the organic mental disorders due to TBI were included, both the demographic and post-traumatic information collected. The relevant data were statistically analyzed in those confirmed as organic psychotic syndrome according to Chinese Classification of Mental Disorders 3rd version (CCMD-3). RESULTS: Fifty-two subjects (13.3%) were identified as organic psychotic symptoms. The chi-square test showed that the detectable organic psychotic symptoms were associated with the marriage status, damage nature, injury severity and treatment, and the multivariate logistic regression analysis revealed good fitness of treatment and injury severity with the regression model (OR = 0.044, 95% CI: 0.017-0.114; OR = 2.145, 95% CI: 1.201-3.832, respectively). CONCLUSION: The risks of organic psychotic symptoms following TBI can be involved in the alternative of craniotomy for the cases with trauma and moderate brain injury.