Department of Biology, Institute of Science, Giresun University, Giresun, Turkey.
Department of Biology, Faculty of Science and Art, Giresun University, 28200, Giresun, Turkey.
Sci Rep. 2024 Apr 15;14(1):8651. doi: 10.1038/s41598-024-59335-6.
In this study, the multifaceted toxicity induced by high doses of the essential trace element molybdenum in Allium cepa L. was investigated. Germination, root elongation, weight gain, mitotic index (MI), micronucleus (MN), chromosomal abnormalities (CAs), Comet assay, malondialdehyde (MDA), proline, superoxide dismutase (SOD), catalase (CAT) and anatomical parameters were used as biomarkers of toxicity. In addition, detailed correlation and PCA analyzes were performed for all parameters discussed. On the other hand, this study focused on the development of a two hidden layer deep neural network (DNN) using Matlab. Four experimental groups were designed: control group bulbs were germinated in tap water and application group bulbs were germinated with 1000, 2000 and 4000 mg/L doses of molybdenum for 72 h. After germination, root tips were collected and prepared for analysis. As a result, molybdenum exposure caused a dose-dependent decrease (p < 0.05) in the investigated physiological parameter values, and an increase (p < 0.05) in the cytogenetic (except MI) and biochemical parameter values. Molybdenum exposure induced different types of CAs and various anatomical damages in root meristem cells. Comet assay results showed that the severity of DNA damage increased depending on the increasing molybdenum dose. Detailed correlation and PCA analysis results determined significant positive and negative interactions between the investigated parameters and confirmed the relationships of these parameters with molybdenum doses. It has been found that the DNN model is in close agreement with the actual data showing the accuracy of the predictions. MAE, MAPE, RMSE and R2 were used to evaluate the effectiveness of the DNN model. Collective analysis of these metrics showed that the DNN model performed well. As a result, it has been determined once again that high doses of molybdenum cause multiple toxicity in A. cepa and the Allium test is a reliable universal test for determining this toxicity. Therefore, periodic measurement of molybdenum levels in agricultural soils should be the first priority in preventing molybdenum toxicity.
在这项研究中,研究了高剂量必需微量元素钼对洋葱(Allium cepa L.)多方面的毒性。使用发芽、根伸长、增重、有丝分裂指数(MI)、微核(MN)、染色体异常(CAs)、彗星试验、丙二醛(MDA)、脯氨酸、超氧化物歧化酶(SOD)、过氧化氢酶(CAT)和解剖学参数作为毒性的生物标志物。此外,还对所有讨论的参数进行了详细的相关性和 PCA 分析。另一方面,本研究专注于使用 Matlab 开发一个具有两个隐藏层的深度神经网络(DNN)。设计了四个实验组:对照组的鳞茎在自来水中发芽,而应用组的鳞茎在 1000、2000 和 4000mg/L 的钼剂量下发芽 72 小时。发芽后,收集根尖并准备进行分析。结果表明,钼暴露导致研究的生理参数值呈剂量依赖性下降(p<0.05),而细胞遗传学(除 MI 外)和生化参数值呈上升(p<0.05)。钼暴露诱导根尖细胞出现不同类型的 CAs 和各种解剖损伤。彗星试验结果表明,随着钼剂量的增加,DNA 损伤的严重程度增加。详细的相关性和 PCA 分析结果确定了研究参数之间存在显著的正相关和负相关,并证实了这些参数与钼剂量的关系。研究发现,DNN 模型与实际数据非常吻合,表明预测的准确性。MAE、MAPE、RMSE 和 R2 用于评估 DNN 模型的有效性。这些指标的综合分析表明,DNN 模型表现良好。因此,再次确定高剂量的钼会导致洋葱发生多种毒性,而 Allium 测试是一种可靠的通用测试方法,可用于确定这种毒性。因此,定期测量农业土壤中的钼含量应成为预防钼毒性的首要任务。