Direct toxicity assessment of toxic chemicals with electrochemical method

Electrochemical measurement of respiratory chain activity is a rapid and reliable screening for the toxicity on microorganisms. Here, we investigated in-vitro effects of toxin on Escherichia coli (E. coli) that was taken as a model microorganism incubated with ferricyanide. The current signal of ferrocyanide effectively amplified by ultramicroelectrode array (UMEA), which was proven to be directly related to the toxicity. Accordingly, a direct toxicity assessment (DTA) based on chronoamperometry was proposed to detect the effect of toxic chemicals on microorganisms. The electrochemical responses to 3,5-dichlorophenol (DCP) under the incubation times revealed that the toxicity reached a stable level at 60 min, and its 50% inhibiting concentration (IC50) was estimated to be 8.0 mg L-1. At 60 min incubation, the IC50 values for KCN and As2O3 in water samples were 4.9 mg L-1 and 18.3 mg L-1, respectively. But the heavy metal ions, such as Cu2+ Pb2+ and Ni2+, showed no obvious toxicity on E. coli.

NMR-based metabonomic study on the subacute toxicity of aristolochic acid in rats

The subacute toxicity of aristolochic acid (AA) was investigated by H-1 NMR spectroscopic and pattern recognition (PR)-based metabonomic methods. Model toxins were used to enable comparisons of the urinary profiles from rats treated with known toxicants and AA at various time intervals. Urinary H-1 NMR spectra were data-processed and analyzed by pattern recognition method. The result of visual comparison of the spectra showed that AA caused a renal proximal tubular and papillary lesion and a slight hepatic impair. Pattern recognition analysis indicated that the renal proximal tubule lesion was the main damage induced by AA, and the renal toxicity induced by AA was a progressive course with the accumulation of dosage by monitoring the toxicological processes from onset, development and part-recovery. These results were also supported by the conventional clinical biochemical parameters.

Three-dimensional structural features and the toxicity of aminobenzenes and phenols

For a QSAR of the toxicity of aminobenzenes in environment and their structures, the projection areas of the molecules in 3D space were calculated. The combinations of the projection areas and quantum chemical as well as topological parameters were performed for the methods of regression analysis and neural network, and much better results than that by using CoMFA were achieved.

A QSAR of the toxicity of amino-benzenes and their structures

The quantum chemical parameters and the topological indices have been calculated for the prediction of the toxicity of amino-benzenes in the environment, and work has been done on the multiple regression and neural networks. The combination of CoMFA with formation heat yields greatly improved results. A good model has been obtained which provides a basis for the studies of the toxic action mechanism.

QUANTITATIVE STRUCTURE-ACTIVITY-RELATIONSHIPS FOR TOXICITY OF PHENOLS USING REGRESSION-ANALYSIS AND COMPUTATIONAL NEURAL NETWORKS

Quantitative structure-toxicity models were developed that directly link the molecular structures of a et of 50 alkYlated and/or halogenated phenols with their polar narcosis toxicity, expressed as the negative logarithm of the IGC50 (50% growth inhibitor