The pharmacokinetics and neurotoxicity of paraquat dichloride (PQ) were assessed following once weekly administration to C57BL/6J male mice by intraperitoneal injection for 1, 2 or 3 weeks at doses of 10, 15 or 25 mg/kg/week. Approximately 0.3% of the administered dose was taken up by the brain and was slowly eliminated, with a half-life of approximately 3 weeks. PQ did not alter the concentration of dopamine (DA), homovanillic acid (HVA) or 3,4-dihydroxyphenylacetic acid (DOPAC), or increase dopamine turnover in the striatum. There was inconsistent stereological evidence of a loss of DA neurons, as identified by chromogenic or fluorescent-tagged antibodies to tyrosine hydroxylase in the substantia nigra pars compacta (SNpc). There was no evidence that PQ induced neuronal degeneration in the SNpc or degenerating neuronal processes in the striatum, as indicated by the absence of uptake of silver stain or reduced immunolabeling of tyrosine-hydroxylase-positive (TH(+)) neurons. There was no evidence of apoptotic cell death, which was evaluated using TUNEL or caspase 3 assays. Microglia (IBA-1 immunoreactivity) and astrocytes (GFAP immunoreactivity) were not activated in PQ-treated mice 4, 8, 16, 24, 48, 96 or 168 h after 1, 2 or 3 doses of PQ. In contrast, mice dosed with the positive control substance, 1-methyl-4-phenyl-1,2,3,6-tetrahydropyridine (MPTP; 10mg/kg/dose×4 doses, 2 h apart), displayed significantly reduced DA and DOPAC concentrations and increased DA turnover in the striatum 7 days after dosing. The number of TH(+) neurons in the SNpc was reduced, and there were increased numbers of degenerating neurons and neuronal processes in the SNpc and striatum. MPTP-mediated cell death was not attributed to apoptosis. MPTP activated microglia and astrocytes within 4 h of the last dose, reaching a peak within 48 h. The microglial response ended by 96 h in the SNpc, but the astrocytic response continued through 168 h in the striatum. These results bring into question previous published stereological studies that report loss of TH(+) neurons in the SNpc of PQ-treated mice. This study also suggests that even if the reduction in TH(+) neurons reported by others occurs in PQ-treated mice, this apparent phenotypic change is unaccompanied by neuronal cell death or by modification of dopamine levels in the striatum.

The neurotoxicity of paraquat dichloride (PQ) was assessed in two inbred strains of 9- or 16-week old male C57BL/6 mice housed in two different laboratories and compared to the effects of 1-methyl-4-phenyl-1,2,3,6-tetrahydropyridine (MPTP). PQ was administered by intraperitoneal injections; either once (20 mg/kg) or twice (10 mg/kg) weekly for 3 weeks, while MPTP-HCl was injected 4 times on a single day (20 mg/kg/dose). Brains were collected 8, 16, 24, 48, 96 or 168 hours after the last PQ treatment, and 48 or 168 hours after MPTP treatment. Dopamine neurons in the substantia nigra pars compacta (SNpc) were identified by antibodies to tyrosine hydroxylase (TH+) and microglia were identified using Iba-1 immunoreactivity. The total number of TH+ neurons and the number of resting and activated microglia in the SNpc at 168 hours after the last dose were estimated using model- or design-based stereology, with investigators blinded to treatment. In a further analysis, a pathologist, also blinded to treatment, evaluated the SNpc and/or striatum for loss of TH+ neurons (SNpc) or terminals (striatum), cell death (as indicated by amino cupric silver uptake, TUNEL and/or caspase 3 staining) and neuroinflammation (as indicated by Iba-1 and/or GFAP staining). PQ, administered either once or twice weekly to 9- or 16-week old mice from two suppliers, had no effect on the number of TH+ neurons or microglia in the SNpc, as assessed by two groups, each blinded to treatment, using different stereological methods. PQ did not induce neuronal cell loss or degeneration in the SNpc or striatum. Additionally, there was no evidence of apoptosis, microgliosis or astrogliosis. In MPTP-treated mice, the number of TH+ neurons in the SNpc was significantly decreased and the number of activated microglia increased. Histopathological assessment found degenerating neurons/terminals in the SNpc and striatum but no evidence of apoptotic cell death. MPTP activated microglia in the SNpc and increased the number of astrocytes in the SNpc and striatum.

BackgroundDue to recent advances in data storage and sharing for further data processing in predictive toxicology, there is an increasing need for flexible data representations, secure and consistent data curation and automated data quality checking. Toxicity prediction involves multidisciplinary data. There are hundreds of collections of chemical, biological and toxicological data that are widely dispersed, mostly in the open literature, professional research bodies and commercial companies. In order to better manage and make full use of such large amount of toxicity data, there is a trend to develop functionalities aiming towards data governance in predictive toxicology to formalise a set of processes to guarantee high data quality and better data management. In this paper, data quality mainly refers in a data storage sense (e.g. accuracy, completeness and integrity) and not in a toxicological sense (e.g. the quality of experimental results).ResultsThis paper reviews seven widely used predictive toxicology data sources and applications, with a particular focus on their data governance aspects, including: data accuracy, data completeness, data integrity, metadata and its management, data availability and data authorisation. This review reveals the current problems (e.g. lack of systematic and standard measures of data quality) and desirable needs (e.g. better management and further use of captured metadata and the development of flexible multi-level user access authorisation schemas) of predictive toxicology data sources development. The analytical results will help to address a significant gap in toxicology data quality assessment and lead to the development of novel frameworks for predictive toxicology data and model governance.ConclusionsWhile the discussed public data sources are well developed, there nevertheless remain some gaps in the development of a data governance framework to support predictive toxicology. In this paper, data governance is identified as the new challenge in predictive toxicology, and a good use of it may provide a promising framework for developing high quality and easy accessible toxicity data repositories. This paper also identifies important research directions that require further investigation in this area.

Abstract-Diquat dibromide (6,7-dihydrodipyrido [1,2-a:2Ј,1Ј-c] pyrazinediium dibromide; diquat) is one of the few herbicides registered for direct application to water systems in the United States to control noxious aquatic weeds. The dissipation of diquat dibromide in aquatic environments is highly dependent on the hydrodynamic and physicochemical characteristics of the receiving water body. Computer simulations (EXAMSII) were conducted to evaluate the variability of diquat cation dissipation in farm ponds, lakes, and canals following applications to control aquatic weeds across the United States. Within each scenario, probabilities were assigned to varying values for physical properties (velocity, dispersion, suspended sediment concentrations, bed sediment properties, and plant biomass) using a joint probability method, and the results were expressed as spatially and temporally explicit cumulative probability distributions by water-body type on a regional scale. The results showed that the dissipation of diquat cation in water was very rapid, with the highest exposure concentrations (90th percentile) predicted to be 0.194 mg/L diquat cation 1 h after treatment and typically reaching 0.01 mg/L by 96 h.

Estimates of potential aquatic exposure concentrations arising from the use of pyrethroid insecticides on cotton produced using conventional procedures outlined by the U.S. Environmental Protection Agency's Office of Pesticide Programs Environmental Fate and Effects Division seem unrealistically high. Accordingly, the assumptions inherent in the pesticide exposure assessment modeling scenarios were examined using remote sensing of a significant Mississippi, USA, cotton-producing county. Image processing techniques and a geographic information system were used to investigate the number and size of the water bodies in the county and their proximity to cotton. Variables critical to aquatic exposure modeling were measured for approximately 600 static water bodies in the study area. Quantitative information on the relative spatial orientation of cotton and water, regional soil texture and slope, and the detailed nature of the composition of physical buffers between agricultural fields and water bodies was also obtained. Results showed that remote sensing and geographic information systems can be used cost effectively to characterize the agricultural landscape and provide verifiable data to refine conservative model assumptions. For example, 68% of all ponds in the region have no cotton within 360 m and 92% of the ponds have no cotton within 60 m. Only 2% of ponds have cotton present in all directions around the ponds and within 120 m. These are significant modifications to conventional pesticide risk assessment exposure modeling assumptions and exemplify the importance of using landscape-level risk assessments to better describe the Mississippi cotton agricultural landscape. Incorporating spatially characterized landscape information into pesticide aquatic exposure scenarios is likely to have greater impact on the model output than many other refinements.