In an area characterized by the presence of a plant that recycles and refines precious metals the study aims to evaluate the exposure to the plant emissions of the residents in the neighbourhood using human urinary biomarkers, in comparison with those obtained in a reference and in an urban area and with the data concerning dispersions of plant emissions obtained through a specific diffusional model. 153 subjects in the study area, 95 in the urban area and 55 in the reference area, aged 18-60years, answered to a self-administered questionnaire and collected their 24-h urine. Urinary concentrations of antimony, silver, cadmium, cobalt, chromium, mercury, nickel, platinum, creatinine, and the porphyrin patterns were detected. The results for the 3 areas were compared using parametric and non-parametric tests. Significant higher concentrations of mercury, cadmium, silver and nickel are observed in the study area in comparison with the reference area, but no differential distribution was observed by different levels of environmental pollution defined by the study's diffusion model, and no correlation was found between the concentrations of altered urinary porphyrin and metals. Life styles being equal, residents in the study area as well as residents in the urban area have high urinary levels of mercury, silver and nickel in comparison with the reference area, suggesting common environmental pressures probably related to diffuse gold processing activities, suggesting common environmental pressures. The excess of cadmium only in the study area suggests a role played by exposure to plant emissions, even if a differential distribution was not observed by different levels of environmental pollution.
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http://dx.doi.org/10.1016/j.scitotenv.2016.12.178 | DOI Listing |
Arch Immunol Ther Exp (Warsz)
January 2025
Department of Human Physiology, Medical University of Lublin, Lublin, Poland.
Systemic lupus erythematosus (SLE) is an autoimmune disease whose pathogenesis is not fully understood to date. One of the suggested mechanisms for its development is NETosis, which involves the release of a specific network consisting of chromatin, proteins, and enzymes from neutrophils, stimulating the immune system. One of its markers is citrullinated histone H3 (H3Cit).
View Article and Find Full Text PDFJMIR Res Protoc
January 2025
National Radiotherapy, Oncology and Nuclear Medicine Centre, Korle-bu Teaching Hospital, Accra, Ghana.
Background: Cancer is a leading cause of global mortality, accounting for nearly 10 million deaths in 2020. This is projected to increase by more than 60% by 2040, particularly in low- and middle-income countries. Yet, palliative and psychosocial oncology care is very limited in these countries.
View Article and Find Full Text PDFPhys Rev Lett
December 2024
CERN, Geneva, Switzerland.
High-energy nuclear collisions create a quark-gluon plasma, whose initial condition and subsequent expansion vary from event to event, impacting the distribution of the eventwise average transverse momentum [P([p_{T}])]. Disentangling the contributions from fluctuations in the nuclear overlap size (geometrical component) and other sources at a fixed size (intrinsic component) remains a challenge. This problem is addressed by measuring the mean, variance, and skewness of P([p_{T}]) in ^{208}Pb+^{208}Pb and ^{129}Xe+^{129}Xe collisions at sqrt[s_{NN}]=5.
View Article and Find Full Text PDFJ Med Internet Res
January 2025
Department of Nephrology, Hunan Key Laboratory of Kidney Disease and Blood Purification, The Second Xiangya Hospital of Central South University, Changsha, China.
Background: Acute kidney injury (AKI) is a common complication in hospitalized older patients, associated with increased morbidity, mortality, and health care costs. Major adverse kidney events within 30 days (MAKE30), a composite of death, new renal replacement therapy, or persistent renal dysfunction, has been recommended as a patient-centered endpoint for clinical trials involving AKI.
Objective: This study aimed to develop and validate a machine learning-based model to predict MAKE30 in hospitalized older patients with AKI.
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