Underground coal mining in western China causes heavy land subsidence and alters the soil ecology. However, the effects of land subsidence on soil fertility are not currently known, and the key factors governing its impact remain unclear in sandy land. We investigated the effects of land subsidence induced by underground mining on the soil quality in western China. Soil samples were collected at 0–15 cm and 15–30 cm from control and subsidence areas in three coal mines. The results showed that the soil water content (SWC), clay and silt percentage, total nitrogen (TN), dissolved organic carbon (DOC), ammonia nitrogen (NH4+-N), nitrate nitrogen (NO3--N), available phosphorus (AP), and available potassium (AK) of the subsidence areas were significantly lower than those of the control areas. The saccharase, urease, and alkaline phosphatase activities in the subsidence areas decreased compared to those in the control areas, while the sand percentage of soil tended to increase. Soil nutrient contents, bacterial quantities, and activities of soil enzymes were positively correlated with SWC. Redundancy analysis (RDA) showed that the soil particle size distribution, SWC, and electrical conductivity (EC) were the major environmental factors driving changes in soil properties. These results indicated that land subsidence induced by coal mining caused losses in surface soil water and nutrients, and ultimately led to soil quality degradation. Therefore, the reclamation of mining subsidence land might be necessary, especially in arid and semi-arid areas.

Over the last few years, under the combined effects of climate change and human factors, the ecological environment of coal mining areas has undergone tremendous changes. Therefore, the rapid and accurate quantitative assessments of the temporal and spatial evolution of the ecological environment quality is of great significance for the ecological restoration and development planning of coal mining areas. This study applied the ecological environment index after topographic correction to improve the remote sensing ecological index (RSEI). Based on a series of Landsat images, the ecological environment quality of Yangquan Coal Mine in Shanxi Province from 1987 to 2020 was monitored and evaluated by an improved remote sensing ecological index. The results show that after topographic correction, the topographic effect of the remote sensing ecological index was greatly reduced, and its practicability was improved. From 1987 to 2020, the ecological environment quality of Yangquan Coal Mine was improved, and the mean of the RSEI increased from 0.4294 to 0.6379. The ecological environment quality of the six coal mines in the study area was improved. Among the six coal gangue dumps, the ecological environmental quality of D1, D2, D3, and D4 has improved, and the ecological environment quality of D5 and D6 worsened. The percentages of improved, unchanged, and degraded ecological environment quality in the entire coal mining area were 77.08%, 0.99%, and 21.93%, respectively. The global Moran’s index was between 0.7929 and 0.9057, and it was shown that there was a strong positive correlation between the ecological environmental qualities of the study area, and that its spatial distribution was clustered rather than random. The LISA cluster map showed that the aggregation and dispersion degree of ecological environment quality was mainly high–high clustering and low–low clustering over the whole stage. During the study period, temperature and precipitation had limited impacts on the ecological environment quality of Yangquan Coal Mine, while the coal mining activities and urbanization construction seriously affected the local ecological environment quality and the implementation of ecological restoration policies, regulations, and measures was the main reason for the improvement of the ecological environment quality.

Keloids are a fibroproliferative disorder of the skin resulted from abnormal healing of injured or irritated skin and are characterized by the ability to spread beyond the original boundary of the wound. Here, we tested the effect of gallic acid (GA), a plant polyphenol with selective growth inhibitory effects in cancer, on the proliferation and invasion of keloid fibroblasts (KFs) isolated from patients undergoing surgery. GA inhibited KF proliferation, migration, and invasion in parallel with the downregulation of matrix metalloproteinase-1 and -3 and upregulation of tissue inhibitors of metalloproteinase-1. Flow cytometric analysis showed that GA inhibited cell cycle progression and induced apoptosis. The effects of GA on KFs occurred in parallel with the inhibition of AKT and ERK1/2, suggesting that GA acts by suppressing the AKT/ERK signaling pathway. In ex vivo explant cultures of keloid tissues, GA inhibited the migration of KFs to the wound area and suppressed the expression of angiogenic markers concomitant with the inhibition of collagen deposition. These results identify GA as a potential therapeutic agent for the treatment of keloids and suggest a potential mechanism underlying its protective effect.

Tetraena mongolica is a rare and endangered species unique to China. The total number and density of Tetraena mongolica shrubs in desertification areas have experienced a sharp decrease with increases in coal mining activities. However, available information on the T. mongolica rhizosphere soil quality and microbial properties is scarce. Here, we investigated the effect of coal mining on the soil bacterial community and its response to the soil environment in the T. mongolica region. The results showed that the closer to the coal mining area, the lower the vegetation coverage and species diversity. The electrical conductivity (EC) in the contaminated area increased, while the total nitrogen (TN), available phosphorus (AP), available potassium (AK), and soil organic carbon (SOC) decreased. The activity of β-glucosidase, urease, alkaline phosphatase, and catalase further decreased. In addition, the mining area could alter the soil’s bacterial abundance and diversity. The organic pollutant degradation bacteria such as Sphingomonas, Gemmatimonas, Nocardioides, and Gaiella were enriched in the soil, and the carbon-nitrogen cycle was changed. Canonical correspondence analysis (CCA) and Pearson’s correlation coefficients showed that the change in the bacterial community structure was mainly caused by environmental factors such as water content (SWC) and EC. Taken together, these results suggested that open pit mining led to the salinization of the soil, reduction the soil nutrient content and enzyme activity, shifting the rhizosphere soil microbial community structure, and altering the carbon-nitrogen cycle, and the soil quality declined and the growth of T. mongolica was affected in the end. Therefore, the development of green coal mining technology is of great significance to protect the growth of T. mongolica.

The large-scale development and utilization of coal resources have brought great challenges to the ecological environment of coal-mining areas. Therefore, this paper has used scientific and effective methods to monitor and evaluate whether changes in ecological environment quality in coal-mining areas are helpful to alleviate the contradiction between human and nature and realize the sustainable development of such coal-mining areas. Firstly, in order to quantify the degree of coal dust pollution in coal-mining areas, an index-based coal dust index (ICDI) is proposed. Secondly, based on the pressure-state-response (PSR) framework, a new coal-mine ecological index (CMEI) was established by using the principal component analysis (PCA) method. Finally, the coal-mine ecological index (CMEI) was used to evaluate and detect the temporal and spatial changes of the ecological environment quality of the Ningwu Coalfield from 1987 to 2021. The research shows that ICDI has a strong ability to extract coal dust with an overall accuracy of over 96% and a Kappa coefficient of over 0.9. As a normalized difference index, ICDI can better quantify the pollution degree of coal dust. The effectiveness of CMEI was evaluated by four methods: sample image-based, classification-based, correlation-based, and distance-based. From 1987 to 2021, the ecological environment quality of Ningwu Coalfield was improved, and the mean of CMEI increased by 0.1189. The percentages of improvement and degradation of ecological environment quality were 71.85% and 27.01%, respectively. The areas with obvious degradation were mainly concentrated in coal-mining areas and built-up areas. The ecological environment quality of Pingshuo Coal Mine, Shuonan Coal Mine, Xuangang Coal Mine, and Lanxian Coal Mine also showed improvement. The results of Moran’s Index show that CMEI has a strong positive spatial correlation, and its spatial distribution is clustered rather than random. Coal-mining areas and built-up areas showed low–low clustering (LL), while other areas showed high–high clustering (HH). The utilization and popularization of CMEI provides an important reference for decision makers to formulate ecological protection policies and implement regional coordinated development strategies.