Does the diurnal cycle of cortisol explain the relationship between physical performance and cognitive function in older adults?

Background Regular physical activity is a promising strategy to treat and prevent cognitive decline. The mechanisms that mediate these benefits are not fully clear but physical activity is thought to attenuate the harmful effects of chronic psychological stress and hypercortisolism on cognition. However, the circadian pattern of cortisol secretion is complex and it is not known which aspects are most closely associated with increased cognitive function and better physical performance. This is the first study to simultaneously measure cognitive function, the diurnal cycle of salivary cortisol and physical performance in older adults, without cognitive impairment (n = 30) and with amnestic Mild Cognitive Impairment (aMCI) (n = 30). Results Regression analysis showed that better cognitive function was associated with better physical performance. A greater variance in cortisol levels across the day from morning to evening was associated with better cognitive function and physical performance. Conclusions The results support the idea that a more dynamic cortisol secretion pattern is associated with better cognitive function and physical performance even in the presence of cognitive impairment, but our results could not confirm a mediating role in this relationship

Q-Data: Using Deductive Database Technology to Improve Data Quality

This chapter discusses an extended deductive database prototype system, Q-Data, developed by Bellcore to improve data quality through data validation and cleanup. The key technology component of Q-Data is the extended deductive database system LDL++, developed at MCC. We discuss the issues of data quality improvement, the relevance of the deductive database technology such as the LDL++ system to data quality improvement tasks, and the system architecture of the prototype. Furthermore, we describe our experiences using the deductive database technology in an on-going Q-Data trial attacking a real-world problem with test data from operational systems. Experiences related to engineering aspects of both the deductive database system and other component technologies, as well as pragmatic aspects of the implementation of Q-Data as a distributed system, are discussed