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1.
Huan Jing Ke Xue ; 44(8): 4334-4343, 2023 Aug 08.
Article in Chinese | MEDLINE | ID: mdl-37694628

ABSTRACT

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.


Subject(s)
Microbiota , Water , Wastewater , Water Pollution , Sulfides
2.
Huan Jing Ke Xue ; 40(12): 5550-5560, 2019 Dec 08.
Article in Chinese | MEDLINE | ID: mdl-31854628

ABSTRACT

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.


Subject(s)
Metals, Heavy , Microbiota , Soil Microbiology , Soil Pollutants , Mining , Soil
3.
Fa Yi Xue Za Zhi ; 30(1): 36-40, 2014 Feb.
Article in English | MEDLINE | ID: mdl-24804382

ABSTRACT

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.


Subject(s)
Brain Injuries/complications , Brain Injuries/psychology , Psychotic Disorders/etiology , Humans , Risk , Syndrome
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