To investigate environmental impacts upon colorectal carcinogenesis (CRC) by diet, we assessed two western diet food contaminants: 4-hydroxynonenal (HNE), a major lipid peroxidation product neoformed during digestion, and a mixture of pesticides. We used human colonic cell lines ectopically eliciting varied genetic susceptibilities to CRC: the non-transformed human epithelial colonic cells (HCECs) and their five isogenic cell lines with the loss of (Adenomatous polyposis coli) and (Tumor protein 53) and/or ectopic expression of mutated (Kristen-ras). These cell lines have been exposed for either for a short time (2-24 h) or for a long period (3 weeks) to 1 µM HNE and/or 10 µM pesticides. After acute exposure, we did not observe any cytotoxicity or major DNA damage. However, long-term exposure to pesticides alone and in mixture with HNE induced clonogenic transformation in normal HCECs, as well as in cells representing later stages of carcinogenesis. It was associated with genotoxic and non-genomic mechanisms (cell growth, metabolic reprogramming, cell mobility and epithelial-mesenchymal transition) depending on genetic susceptibility. This study demonstrated a potential initiating and promoting effect of food contaminants on CRC after long-term exposure. It supports that these contaminants can accelerate carcinogenesis when mutations in oncogenes or tumor suppressor genes occur.
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http://dx.doi.org/10.3390/cancers13174337 | DOI Listing |
Biodegradation
December 2024
Department of Civil engineering, Islamic Azad university, Mashhad Branch, Iran.
The widespread use of pesticides, including diazinon, poses an increased risk of environmental pollution and detrimental effects on biodiversity, food security, and water resources. In this study, we investigated the impact of Potentially Toxic Elements (PTE) including Zn, Cd, V, and Mn on the degradation of diazinon in three different soils. We investigated the capability and performance of four machine learning models to predict residual pesticide concentration, including adaptive neuro-fuzzy inference system (ANFIS), support vector regression (SVR), radial basis function (RBF), and multi-layer perceptron (MLP).
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December 2024
Department of Microbiology and Parasitology, Faculty of Science, University of Buea, Box 63, Buea, Cameroon.
Objectives: Methicillin-resistant Staphylococcus aureus (MRSA) is a zoonotic pathogen that poses a serious threat to veterinary and public health worldwide. We investigated mastitis milk samples for contamination with MRSA and also characterized the MRSA isolates by investigating antimicrobial resistance and virulence factors.
Result: We confirmed MRSA in 69 of 201 (34.
Mikrochim Acta
December 2024
State Key Laboratory of Food Science and Resources, Jiangnan University, Wuxi, 214122, China.
A dual-signal aptamer-based assay utilizing colorimetric and fluorescence techniques was developed for the determination of zearalenone (ZEN). The CdTe quantum dots, serving as the fluorescent signal source, were surface-modified onto FeO@SiO and subsequently functionalized with the aptamer. The COF-Au was modified with complementary chain, which possessed peroxide (POD)-like enzyme properties, and could catalyze the peroxidation of 3,3',5,5'-tetramethylbenzidine (TMB) to ox TMB, resulting in the generation of colorimetric signals.
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December 2024
College of Agriculture and Biotechnology, Zhejiang University, Hangzhou, 310058, China.
Crop plants are severely affected by heavy metals (HMs), leading to food scarcity and economical loss. Lead (Pb) is outsourced by use of lead-based fertilizers, batteries, mining, smelting and metal processing. It significantly reduces growth, development and yield of crops cultivated on contaminated sites.
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December 2024
Department of Agricultural Entomology, Tamil Nadu Agricultural University, Coimbatore, 641003, India.
An efficient modified QuEChERS procedure was established for the simultaneous determination of 37 pesticide residues in fresh and processed edible button mushroom by employing GC/ GC-MS and LC-MS/MS. The effectiveness, reliability and accuracy of the method were assessed through validation parameters such as linearity, LOD, LOQ, precision, accuracy, uncertainty, and matrix effect. The linearity calibration for all the selected pesticides at standard concentrations (0.
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