Estimating the predictive validity of diabetic animal models in rosiglitazone studies

For therapeutic studies, predictive validity of animal models - arguably the most important feature of animal models in terms of human relevance - can be calculated retrospectively by obtaining data on treatment efficacy from human and animal trials. Using rosiglitazone as a case study, we aim to determine the predictive validity of animal models of diabetes, by analyzing which models perform most similarly to humans during rosiglitazone treatment in terms of changes in standard diabetes diagnosis parameters (glycosylated hemoglobin (HbA1c) and fasting glucose levels). A further objective of this article is to explore the impact of four covariates on the predictive capacity: i) diabetes induction method, ii) drug administration route, iii) sex of animals, and iv) diet during the experiments

The early career researcher's toolkit:translating tissue engineering, regenerative medicine and cell therapy products

Although the importance of translation for the development of tissue engineering, regenerative medicine and cell-based therapies is widely recognized, the process of translation is less well understood. This is particularly the case among some early career researchers who may not appreciate the intricacies of translational research or make decisions early in development which later hinders effective translation. Based on our own research and experiences as early career researchers involved in tissue engineering and regenerative medicine translation, we discuss common pitfalls associated with translational research, providing practical solutions and important considerations which will aid process and product development. Suggestions range from effective project management, consideration of key manufacturing, clinical and regulatory matters and means of exploiting research for successful commercialization

Reduced Slow-Wave Sleep Is Associated with High Cerebrospinal Fluid A beta 42 Levels in Cognitively Normal Elderly

Study Objectives: Emerging evidence suggests a role for sleep in contributing to the progression of Alzheimer disease (AD). Slow wave sleep (SWS) is the stage during which synaptic activity is minimal and clearance of neuronal metabolites is high, making it an ideal state to regulate levels of amyloid beta (Aβ). We thus aimed to examine relationships between concentrations of Aβ42 in the cerebrospinal fluid (CSF) and measures of SWS in cognitively normal elderly subjects. Methods: Thirty-six subjects underwent a clinical and cognitive assessment, a structural MRI, a morning to early afternoon lumbar puncture, and nocturnal polysomnography. Correlations and linear regression analyses were used to assess for associations between CSF Aβ42 levels and measures of SWS controlling for potential confounders. Resulting models were compared to each other using ordinary least squared linear regression analysis. Additionally, the participant sample was dichotomized into “high” and “low” Aβ42 groups to compare SWS bout length using survival analyses. Results: A significant inverse correlation was found between CSF Aβ42 levels, SWS duration and other SWS characteristics. Collectively, total SWA in the frontal lead was the best predictor of reduced CSF Aβ42 levels when controlling for age and ApoE status. Total sleep time, time spent in NREM1, NREM2, or REM sleep were not correlated with CSF Aβ42. Conclusions: In cognitively normal elderly, reduced and fragmented SWS is associated with increases in CSF Aβ42, suggesting that disturbed sleep might drive an increase in soluble brain Aβ levels prior to amyloid deposition