Biology subjects

Vachiraarunwong, A.

Publications and source records attributed to Vachiraarunwong, A..

3 recordsLinked to original sources

bioRxiv2025

Construction of a novel 3D urinary bladder mucosa model and its application in toxicity assessment of arsenicals

The urinary bladder is a major target organ for environmental toxicants, including arsenic. The objects of this study were two-fold. First, we constructed a novel 3D urinary bladder mucosa model that incorporated an overlying epithelium and a supporting subepithelial layer, referred to as the 3D-UBMM. Primary human bladder urothelial and fibroblast cells were immortalized by introducing the human CDK4R24C and TERT genes. The subsequent construction of the 3D-UBMM involved incorporating the immortalized fibroblast cells into a collagen raft, while the immortalized urothelial cells were cultured at the air-liquid interface of the raft. This 3D-UBMM closely resembles the human urinary bladder epithelium in terms of morphology and marker protein expression, including uroplakin 1b, P63, and cytokeratin 5. Second, using the 3D-UBMM we investigated the cytotoxicity of sodium arsenite (iAsIII) and dimethylarsenic acid (DMAV). Exposure to iAsIII and DMAV resulted in increased urothelial cell necrosis and increased {gamma}-H2AX-positive cells along with a reduction of P63-positive cells, and each of these effects was induced in a dose-response manner. These findings affirm that this novel 3D-UBMM closely resembles the human urinary bladder epithelial layer, offering a practical in vitro model for the evaluation of the toxicity of arsenic and other bladder carcinogens and the role of cancer-related genes in bladder carcinogenicity. In addition, by identifying mechanisms of carcinogenesis this model will aid in hazard identification and risk assessment of potential bladder carcinogens.

pharmacology and toxicology↗

bioRxiv2025

Developing a Novel In Vitro Toxicity Assay for Predicting Inhalation Toxicity in Rats

The development of alternative in vitro methods for assessing acute inhalation toxicity is a critical step toward reducing animal testing and aligns with the principles of the 3Rs (replacement, reduction, and refinement). In this study, we developed and optimized a neutral red uptake (NRU) assay using human lung adenocarcinoma cells (A549) as a predictive model (A549-NRU) for acute inhalation toxicity. To improve assay efficiency and robustness, we introduced two key modifications: the incubation time was reduced to 15 minutes to enable rapid and high-throughput screening, and for chemicals reactive with polystyrene 6-well glass plates were used to prevent chemical-induced degradation and ensure assay consistency. LC50 values were determined for 49 chemicals and compared with reported LC50 values from 4-hour rat inhalation studies. A significant positive correlation was observed between A549-NRU-derived LC50 values and in vivo LC50 values for water-soluble compounds and chemicals containing aldehyde, ketone, alcohol, ether, and epoxide functional groups, suggesting that in vivo LC50 values may be predictable using the A549-NRU assay. Additionally, A549-NRU LC50 values showed significant negative correlations with molecular weight and octanol-water partition coefficients, indicating that chemicals with higher values tended to be less cytotoxic in vitro. Importantly, the A549-NRU assay demonstrated stronger correlation with in vivo LC50 values than the conventional NRU assay using mouse 3T3 fibroblast cells. These findings support the use of the A549-NRU assay to estimate starting doses for in vivo studies, and potentially as an in vitro alternative for predicting acute inhalation toxicity. Impact statementThe optimized A549-NRU assay demonstrates predictive potential for inhalation toxicity while reducing reliance on animal testing. This model serves as a human-relevant alternative for estimating starting doses for in vivo inhalation toxicity studies.

pharmacology and toxicology↗

bioRxiv2024

A Novel Support Vector Machine-Based One-Day, Single-Dose Prediction Model of Genotoxic Hepatocarcinogenicity in Rats

The development of a rapid and accurate model for determining the genotoxicity and carcinogenicity of chemicals is crucial for effective cancer risk assessment, and it also contributes to cancer prevention. This study aims to develop a one-day, single-dose model for identifying genotoxic hepatocarcinogens (GHCs) in rats. Microarray gene expression data from the livers of rats administered a single dose of 58 compounds, including 5 GHCs, was obtained from the Open TG-GATEs database and used for the identification of marker genes and the construction of a predictive classifier to identify GHCs in rats. We identified 10 gene markers commonly responsive to all 5 GHCs and used them to construct a support vector machine-based predictive classifier. This classifier effectively distinguishes GHCs from other compounds, demonstrating 100% sensitivity and over 96% specificity. To further assess the models effectiveness and reliability, we conducted multi-institutional one-day single oral administration studies on rats. These studies examined 64 compounds, including 23 GHCs, with gene expression data of the marker genes obtained via quantitative PCR (qPCR) 24 hours after a single oral administration. Our results demonstrate that qPCR analysis is an effective alternative to microarray analysis. The GHC predictive model showed high accuracy and reliability, achieving a sensitivity of 91% (21/23) and a specificity of 93% (38/41) across multiple validation studies in three institutions. In conclusion, the present one-day single oral administration model proves to be a reliable and highly sensitive tool for identifying GHCs and is anticipated to be a valuable tool in identifying and screening potential GHCs.

pharmacology and toxicology↗