Order and membrane organization in chlorhexidine-lipid mixtures /

Formulations of a general bactericidal agent, chlorhexidine, mixed with a phospholipid at different concentrations are investigated using ^H NMR spectroscopy on a chain-deuterated lipid analog. Lipid-chlorhexidine formulation is known to release the drug into an aqueous medium slowly, maintaining a comparable concentration of the drug for up to four times longer than a direct aqueous solution. The NMR data does not support the proposed liposomal entrapment of chlorhexidine in lipid compartments. Complex thermal history of the lipid-chlorhexidine preparations is investigated in detail. In preparation for a counterpart measurement, using ^H NMR of deuterated chlorhexidine mixed with protonated lipid, the synthesis of a deuterated analog of chlorhexidine is performed.

Cognitive Behavior Therapy for Obsessive-Compulsive Behavior in Children with Autism Spectrum Disorder: A Comparison of Hierarchical Linear Modelling and Visual Analysis

Behavioral researchers commonly use single subject designs to evaluate the effects of a given treatment. Several different methods of data analysis are used, each with their own set of methodological strengths and limitations. Visual inspection is commonly used as a method of analyzing data which assesses the variability, level, and trend both within and between conditions (Cooper, Heron, & Heward, 2007). In an attempt to quantify treatment outcomes, researchers developed two methods for analysing data called Percentage of Non-overlapping Data Points (PND) and Percentage of Data Points Exceeding the Median (PEM). The purpose of the present study is to compare and contrast the use of Hierarchical Linear Modelling (HLM), PND and PEM in single subject research. The present study used 39 behaviours, across 17 participants to compare treatment outcomes of a group cognitive behavioural therapy program, using PND, PEM, and HLM on three response classes of Obsessive Compulsive Behaviour in children with Autism Spectrum Disorder. Findings suggest that PEM and HLM complement each other and both add invaluable information to the overall treatment results. Future research should consider using both PEM and HLM when analysing single subject designs, specifically grouped data with variability.