Most fish contain some kinds of organoarsenic compounds. To assess the health risk for the chronic effects due to intake of these compounds, it is necessary to quantify the concentration of each chemical form, since the toxicity is difference depending on the form. We developed and validated the LC-MS/MS method to determine the concentration of monomethylarsonic acid (MMA), dimethylarsinic acid (DMA), trimethylarsine oxide (TMAO), tetramethylarsonium (TeMA), arsenobetaine (AB), and arsenocholine (AC) in fish. Using this method, we quantified the concentration of each organoarsenic compounds and total arsenic in 50 fish samples from across 10 groups. Total arsenic concentration ranged from 0.53 to 25 mg/kg in all samples, except for in thread-sail filefish where the concentration ranged from 8.3 to 25 mg/kg. With the exception of sardines, in all samples AB was found at the highest level in relation to the total arsenic concentration. In sardines, the concentration of DMA was higher than that of AB, accounting for 16 to 24% of total arsenic. In red sea bream, concentrations of total arsenic, AB, and AC in farm-raised fish were lower than those in wild-caught fish.
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http://dx.doi.org/10.3358/shokueishi.61.86 | DOI Listing |
J Hazard Mater
January 2025
Third World Center (TWC) for Science and Technology, H.E.J. Research Institute of Chemistry, International Center for Chemical and Biological Sciences, University of Karachi, Karachi 75270, Pakistan; H.E.J. Research Institute of Chemistry, International Center for Chemical and Biological Sciences, University of Karachi, Karachi 75270, Pakistan. Electronic address:
Groundwater contamination is a growing global concern. The objective of the present study is to assess the groundwater quality of Khairpur district, Sindh, Pakistan-a region which is emblematic of broad environmental and public health challenges prevalent in South Asian countries. The study also aims to comprehend the impact of arsenic (As), fluoride (F), and nitrate (NO) dynamics and its health implications.
View Article and Find Full Text PDFJ Hazard Mater
January 2025
Research Institute for Environmental Innovation (Binhai, Tianjin), Tianjin 300450, PR China. Electronic address:
The speciation and mobility of arsenic (As) in waters are largely influenced by the colloids; however, the impacts of colloids with different molecular weights (MWs) in water fractions remain largely unknown. Herein, the surface water was fractionated into three colloidal fractions and truly dissolved fraction via cross-flow ultrafiltration. Total As (As(T)) presented mainly as As(V) and existed primarily in the truly dissolved fraction.
View Article and Find Full Text PDFSci Total Environ
January 2025
Institute of Plant Nutrition, Resources and Environment, Beijing Academy of Agriculture and Forestry Sciences, Beijing 100097, China. Electronic address:
Composting urban and rural wastes into organic fertilizers for land application is considered the best way to dispose of and recycle waste resources. However, there are some concerns about the long-term effects of applying various organic fertilizers on soils, food safety, and health risks derived from heavy metal(loid)s (HMs). A long-term field experiment was conducted to evaluate the effects of continuous application of chicken manure compost (CM), sewage sludge compost (SSC), and domestic waste compost (DWC) for wheat on the accumulation, transfer, and health risks of HMs.
View Article and Find Full Text PDFBiol Trace Elem Res
January 2025
Departamento de Biologia Geral, Universidade Federal de Viçosa, Viçosa, Minas Gerais, Brasil.
Arsenic in drinking water has been associated with an increased risk of health concerns. This metalloid is ingested and distributed throughout the body, accumulating in several organs, including the testis. In this organ, arsenic disturbs steroidogenesis and spermatogenesis and affects male fertility.
View Article and Find Full Text PDFEnviron Geochem Health
January 2025
School of Environmental Science and Engineering, Shandong University, Qingdao, 266237, China.
Groundwater arsenic (As), contamination is a significant issue worldwide including China and Pakistan, particularly in canal command areas. In this study, 131 groundwater samples were collected, and three machine learning models [Random Forest (RF), Logistic Regression (LR), and Artificial Neural Network (ANN)] were employed to predict As concentration. Descriptive statistics helped to conclude that all of the samples were inside the permitted limit of WHO for pH, Ca, Mg, Turbidity, Cl, K, Na, SO, NO, F and beyond limit of WHO for EC, HCO, TDS, and As.
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