The rainbow trout gill cell line (RTgill-W1), via test guideline 249 of the Organisation for Economic Co-operation and Development, has been established as a promising New Approach Methodology, although to advance confidence in the method more case studies are needed that: 1) expand our understanding of applicability domains (chemicals with diverse properties); 2) increase methodological throughput (96-well format); and 3) demonstrate biological relevance (in vitro to in vivo comparisons; gill vs. other cells). Accordingly, the objective of our study was to characterize the cytotoxicity of 19 pesticides against RTgill-W1 cells, and also liver (RTL-W1) and gut epithelial (RTgutGC) cell lines, and then to compare the in vitro and in vivo data. Of the 19 pesticides tested, 11, 9, and 8 were cytotoxic to the RTgill-W1, RTL-W1, and RTgutGC cells, respectively. Six pesticides (carbaryl, chlorothalonil, chlorpyrifos, dimethenamid-P, metolachlor, and S-metolachlor) were cytotoxic to all three cell lines. Aminomethylphosphonic acid, chlorantraniliprole, dicamba, diquat, imazethapyr, and permethrin exhibited cell-line-specific toxicity. No cytotoxic responses were observed for three herbicides (atrazine, glyphosate, and metribuzin) and four insecticides (clothianidin, diazinon, imidacloprid, and thiamethoxam). When cytotoxicity was measured, there was a strong correlation (r = 0.9, p < 0.0001) between in vitro median effect concentration (EC50) values (based on predicted concentrations using the In Vitro Mass Balance Model Equilibrium Partitioning (IV-MBM EQP) Ver. 2.1) derived from RTgill-W1 and RTL-W1 cells with in vivo median lethal concentration (LC50) values from 96-h acute toxicity studies with trout. In all 28 cases, the in vitro EC50 was within 18-fold of the in vivo LC50. These data help increase our understanding of the ecotoxicological domains of applicability for in vitro studies using cultured rainbow trout cells, while also demonstrating that these assays performed well in a 96-well format and have promise to yield data of biological relevance. Environ Toxicol Chem 2024;00:1-13. © 2023 The Authors. Environmental Toxicology and Chemistry published by Wiley Periodicals LLC on behalf of SETAC.
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Eur J Epidemiol
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Department of Neurobiology, Care Sciences and Society, Division of Family Medicine and Primary Care, Karolinska Institutet, Stockholm, Sweden.
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View Article and Find Full Text PDFSci Rep
January 2025
School of Medicine, Nankai University, Tianjin, 300071, China.
Cholangiocarcinoma (CCA), a highly aggressive form of cancer, is known for its high mortality rate. A Disintegrin and Metalloprotease Domain-like Protein Decysin-1 (ADAMDEC1) can promote the development and metastasis in various tumors by degrading the extracellular matrix. However, its regulatory mechanism in CCA remains unclear.
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Department of Hematology, Navy Medical Center of PLA, Naval Medical University, No. 338 West Huaihai Road, Changning District, Shanghai, 200052, China.
Multiple myeloma(MM) remains incurable with high relapse and chemoresistance rates. Differentially expressed genes(DEGs) between newly diagnosed myeloma and secondary plasma cell leukemia(sPCL) were subjected to a weighted gene co-expression network analysis(WGCNA). Drug resistant myeloma cell lines were established.
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January 2025
School of Physics, Engineering and Technology, University of York, Heslington, York, YO10 5DD, UK.
Prostate cancer is a disease which poses an interesting clinical question: Should it be treated? Only a small subset of prostate cancers are aggressive and require removal and treatment to prevent metastatic spread. However, conventional diagnostics remain challenged to risk-stratify such patients; hence, new methods of approach to biomolecularly sub-classify the disease are needed. Here we use an unsupervised self-organising map approach to analyse live-cell Raman spectroscopy data obtained from prostate cell-lines; our aim is to exemplify this method to sub-stratify, at the single-cell-level, the cancer disease state using high-dimensional datasets with minimal preprocessing.
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