Time Course of Remote Neuropathology Following Diffuse Traumatic Brain Injury in the Male Rat

Traumatic brain injury (TBI) can affect different regions throughout the brain. Regions near the site of impact are the most vulnerable to injury. However, damage to distal regions occurs. We investigated progressive neuropathology in the dorsal hippocampus (near the impact) and cerebellum (distal to the impact) after diffuse TBI. Adult male rats were subjected to midline fluid percussion injury or sham injury. Brain tissue was stained by the amino cupric silver stain. Neuropathology was quantified in sub-regions of the dorsal hippocampus at 1, 7, and 28 days post-injury (DPI) and coronal cerebellar sections at 1, 2, and 7 DPI. The highest observed neuropathology in the dentate gyrus occurred at 7 DPI which attenuated by 28 DPI, whereas the highest observed neuropathology was at 1 DPI in the CA3 region. There was no significant neuropathology in the CA1 region at any time point. Neuropathology was increased at 7 DPI in the cerebellum compared to shams and stripes of pathology were observed in the molecular layer perpendicular to the cerebellar cortical surface. Together these data show that diffuse TBI can result in neuropathology across the brain. By describing the time course of pathology in response to TBI, it is possible to build the temporal profile of disease progression.

On the use of fractional polynomial [FP] models to assess preventive aspect of variables: an example in prevention of mortality following HIV infection

Identification of disease risk factors can help in the prevention of diseases. In assessing the predictive value of continuous variables, a routine procedure is to categorize the factors. This yield to inability to detect non-linear relationship, if exist. Multivariate fractional polynomial [MFP] modeling is a flexible method to reveal non-linear associations. We aim to demonstrate the impact of choice of risk function on the significance of variables. We selected 6508 HIV-infected persons registered in the Australia National HIV Registry between 1980 and 2003 to assess the predictors associated with the risk of death after HIV infection prior to AIDS. First, CD4 count as a categorical factor with three other categorical variables [age, sex, and HIV exposure category] was entered into the Cox regression model. Second, CD4 counts as a continuous variable along with other categorical variables were entered into the fractional polynomial [FP] model. Both the Cox and FP models showed age >/= 40 years and hemophiliac patients were significantly associated with increased risk of death. In the categorized model, the CD4 variable did not reach the significance level. However, this variable was highly significant in the MFP model. The FP model showed slightly better performance in terms of discrimination ability and goodness of fit. The FP model is a flexible method in detecting the predictive effect of continuous variables. This method enhances the ability to assess the predictive ability of variables and improves model performance