With the growing rate of traumatic brain injury (TBI), there is an increasing interest in validated tools to predict and prevent brain injuries. Finite element models (FEM) are valuable tools to estimate tissue responses, predict probability of TBI, and guide the development of safety equipment. In this study, we developed and validated an anisotropic pig brain multi-scale FEM by explicitly embedding the axonal tract structures and utilized the model to simulate experimental TBI in piglets undergoing dynamic head rotations. Binary logistic regression, survival analysis with Weibull distribution, and receiver operating characteristic curve analysis, coupled with repeated k-fold cross-validation technique, were used to examine 12 FEM-derived metrics related to axonal/brain tissue strain and strain rate for predicting the presence or absence of traumatic axonal injury (TAI). All 12 metrics performed well in predicting of TAI with prediction accuracy rate of 73-90%. The axonal-based metrics outperformed their rival brain tissue-based metrics in predicting TAI. The best predictors of TAI were maximum axonal strain times strain rate (MASxSR) and its corresponding optimal fraction-based metric (AF-MASxSR 7.5) that represents the fraction of axonal fibers exceeding MASxSR of 7.5 s −1. The thresholds compare favorably with tissue tolerances found in in-vitro/in-vivo measurements in the literature. In addition, the damaged volume fractions (DVF) predicted using the axonal-based metrics, especially MASxSR (DVF = 0.05-4.5%), were closer to the actual DVF obtained from histopathology (AIV = 0.02-1.65%) in comparison with the DVF predicted using the brain-related metrics (DVF = 0.11-41.2%). The methods and the results from this study can be used to improve model prediction of TBI in humans.

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Dissolved trace elements and heavy metals in the Dan River drainage basin, which is the drinking water source area of South-to-North Water Transfer Project (China), affect large numbers of people and should therefore be carefully monitored. To investigate the distribution, sources, and quality of river water, this study integrating catchment geology and multivariate statistical techniques was carried out in the Dan River drainage from 99 river water samples collected in 2013. The distribution of trace metal concentrations in the Dan River drainage was similar to that in the Danjiangkou Reservoir, indicating that the reservoir was significantly affected by the Dan River drainage. Moreover, our results suggested that As, Sb, Cd, Mn, and Ni were the major pollutants. We revealed extremely high concentrations of As and Sb in the Laoguan River, Cd in the Qingyou River, Mn, Ni, and Cd in the Yinhua River, As and Sb in the Laojun River, and Sb in the Dan River. According to the water quality index, water in the Dan River drainage was suitable for drinking; however, an exposure risk assessment model suggests that As and Sb in the Laojun and Laoguan rivers could pose a high risk to humans in terms of adverse health and potential non-carcinogenic effects.

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