Segments of used drinking water pipes of galvanised steel (GS), cross-linked polyethylene (PEX), copper pipes (Cu) or new medium-density polyethylene (PE) were investigated for the formation of biofilm and survival of E. coli in biofilm and in the water phase. Pipes were filled with water and incubated at 15 degrees C or 35 degrees C under static conditions. Biofilm formation was followed during 32, 40 and 56 (58) d. The most dense biofilm was formed on GS, reaching approximately 4.7 x 10(5) CFU/cm2 measured as heterotrophic plate count (HPC), and at the other materials the density reached 3 x 10(3) CFU/cm2 on PE and PEX and 5 x 10(1) and 5 x 10(2) CFU/cm2 on Cu pipes after 58d at 15 degrees C. Biofilm HPC values were higher at 35 degrees C than at 15 degrees C, with only slightly higher values on the metals, but 100-fold higher on PE and PEX. Adenosine triphosphate (ATP) measurements confirmed the general trends observed by HPC. Higher temperature was seen to be an important factor reducing E. coli survival in the water phase in drinking water pipes. At 15 degrees C E. coli survived more than 4 d in GS and Cu pipes and 8 d in PE pipes, but was not detected after 48 h at 35 degrees C. The E. coli survived longer at both temperatures in the glass control bottles than in the drinking water pipes. Despite the obvious biofilm formation, E. coli was not detected in the biofilm at any of the investigated surfaces.
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http://dx.doi.org/10.2166/wst.2006.447 | DOI Listing |
Viruses
December 2024
Associate Laboratory for Animal and Veterinary Sciences (AL4AnimalS), Interdisciplinary Center for Research in Animal Health (CIISA), Faculty of Veterinary Medicine, University of Lisbon, 1300-477 Lisbon, Portugal.
Rotavirus group A (RVA) is a major cause of pediatric acute gastroenteritis (AGE). Vaccination is an effective public health strategy and Angola implemented it in 2014. This hospital-based study aimed to estimate the prevalence of RVA infection and the severity of AGE in children under five years of age treated at six hospitals in Luanda Province.
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November 2024
Division of Water Supply and Sewerage Research, National Institute of Environmental Research, Incheon 22689, Republic of Korea.
Groundwater is an essential drinking water source for humans. However, improper groundwater management leads to fecal contamination and waterborne diseases caused by viral pathogens. Therefore, this study aimed to investigate norovirus (NoV) contamination by conducting nationwide monitoring over five years (2019-2023).
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December 2024
School of Resource and Environmental Engineering, Inner Mongolia University of Technology, Hohhot 010051, China.
The rapid development of the global chemical industry has led to widespread groundwater contamination, with frequent pollution incidents posing severe threats to water safety. However, there has been insufficient assessment of the health risks posed by chlorinated hydrocarbon contamination in groundwater around chemical industrial parks. This study evaluates the chlorinated hydrocarbon contamination in groundwater at a chemical park and conducts a multi-pathway health risk assessment, identifying the key risk pollutants.
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December 2024
School of Public Health, Baotou Medical College, Inner Mongolia University of Science & Technology, Baotou 014040, China.
Arsenic exposure can induce liver insulin resistance (IR) and diabetes (DM), but the underlying mechanisms are not yet clear. Circular RNAs (circRNAs) are involved in the regulation of the onset of diabetes, especially in the progression of IR. This study aimed to investigate the role of circRNAs in arsenic-induced hepatic IR and its underlying mechanism.
View Article and Find Full Text PDFThis study aimed to evaluate the annual pollution characteristics of trichloromethane (TCM) in Kunshan City's tap water from 2016 to 2022. This research analyzed 566 tap water samples from centralized water supply units, utilizing the GB 5749-2006 Sanitary Standard for Drinking Water as the evaluation benchmark. Data analysis employed non-parametric tests and Spearman's correlation analysis using Excel 2017 and SPSS 26.
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