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In order to explore the status and sources of soil heavy metal pollution around typical industrial parks in the upper reaches of the Yellow River, 377 surface soil samples were systematically collected from an important industrial park in Zhongwei area, Ningxia Hui Autonomous Region, and the content characteristics of the eight heavy metal elements As, Hg, Cr, Ni, Pb, Cd, Co, and Mn in the soil were analyzed. Single-factor pollution index, ground accumulation index, Nemerow index, pollution load index, and potential ecological risk index were used to comprehensively evaluate the soil heavy metal pollution level and potential ecological risk in the study area. Multivariate statistical analysis and the absolute principal component multiple linear regression (APCS-MLR) model were employed to quantitatively identify the sources of heavy metals in the soil. The results showed that the content of heavy metals in soil decreased from southwest to northeast. The average contents of Hg, Cr, Pb, Cd, and Mn were higher than the background values of soil from Ningxia Hui Autonomous Region. The spatial distribution of Hg and Cd was different, and they were significantly affected by human activities. The soil was slightly polluted and presented a medium ecological risk level in the study area. The content of Hg and Cd in the soil was relatively high, which were the main elements causing soil pollution. The results of APCS-MLR modelling showed that the dominant sources of heavy metals were natural sources (50.6%), industrial sources and fossil fuel combustion combined sources (27.9%), and agricultural sources (21.5%). The findings can provide important basis for soil pollution control and land use optimization in the region and serve the national strategy of ecological protection and high-quality development in the Yellow River Basin.
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http://dx.doi.org/10.13227/j.hjkx.202404210 | DOI Listing |
Top Curr Chem (Cham)
September 2025
Center for Advanced Materials Research, Research Institute of Sciences and Engineering, University of Sharjah, 27272, Sharjah, United Arab Emirates.
Controlling the size of gold nanoparticles (AuNPs) has been critical in diagnostics, biomolecular sensing, targeted therapy, wastewater treatment, catalysis, and sensing applications. Ultrasmall AuNPs (uAuNPs), with sizes Ranging from 2 to 5 nm, and gold nanoclusters (AuNCs), with sizes less than 2 nm, are often dealt with interchangeably in the literature, making it challenging to review them separately. Although they are grouped in our discussion, their chemical and physical properties differ significantly, partly due to their electronic properties.
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Shobhaben Pratapbhai Patel School of Pharmacy and Technology Management, SVKM's Narsee Monjee Institute of Management Studies, Mumbai, 56, India.
Zebrafish models have been used to research Alzheimer's disease and other neurodegenerative disorders because of their similarities to the human genetic composition and behavior. Researchers have detected iron accumulation in the post-mortem brain sections of neurodegenerative disorder patients. Therefore, the development an animal model to simulate these clinical pathological findings is important.
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October 2025
Laboratory of Experimental Physiopathology, Program of postgraduate in Science of Health, Universidade do Extremo Sul Catarinense, Criciúma, Santa Catarina state, Brazil.
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Department of Occupational Health (Key Laboratory of Electromagnetic Radiation Protection, Ministry of Education), Army Medical University (Third Military Medical University), Chongqing, 400038, China.
Cadmium (Cd) is a heavy metal that exhibits strong carcinogenic properties and promotes breast cancer (BC) progression. Autophagic flux dysfunction is involved in Cd-induced BC progression, but the underlying molecular mechanisms remain unclear. Here, it is observed that impaired autophagic flux and metabolic reprogramming are notable features related to Cd-induced proliferation, migration, and invasion in BC cell lines, including T-47D and MCF-7 cells.
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Institute of Marine and Environmental Technology, University of Maryland Center for Environmental Science, Baltimore, MD 21202 USA.
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