Niemann-Pick disease type C (NP-C) is an inherited neurodegenerative disorder associated with intracellular cholesterol and glycolipid trafficking defects. Two separate genes, NPC1 and NPC2, have been linked to NP-C. NPC1 encodes a polytopic membrane-bound protein with a putative sterol-sensing domain. NPC2 has been recently identified as epididymal secretory glycoprotein 1. The NPC1 protein functions in the vesicular redistribution of endocytosed lysosomal cargo, but how its inactivation leads to neurodegeneration is not known. The neurological symptoms of NP-C typically appear after a period of normal early development and reflect progressive degeneration of widespread brain regions. Here we have delineated the pattern of neurodegeneration in NP-C mice, whose genetic defect has been shown to be an inactivating mutation of the mouse NPC1 gene. The results reveal a spatially and temporally specific pattern of degeneration of nerve fibers followed by degeneration of neuronal cell bodies beginning as early as day 9 and continuing throughout life. We have recently showed that in the primate brain, the NPC1 protein is localized predominantly within perisynaptic astrocytic processes. The present observations suggest that a functional disturbance in NPC1 could disrupt vesicular transport of cholesterol, glycolipids and possibly other endocytic cargo in glia, which is critical for maintaining the integrity of neurons.

Statistical analysis is an essential technique that enables a medical research practitioner to draw meaningful inference from their data analysis. Improper application of study design and data analysis may render insufficient and improper results and conclusion. Converting a medical problem into a statistical hypothesis with appropriate methodological and logical design and then back-translating the statistical results into relevant medical knowledge is a real challenge. This article explains various sampling methods that can be appropriately used in medical research with different scenarios and challenges.

Background: The purpose of this study was to assess the impact of drug abuse treatment in Peru that used the therapeutic community (TC) model. Program directors and several staff members from all study treatment facilities received two to eight weeks of in-country training on how to implement the TC treatment model prior to the follow-up study.

A social policy experiment is presented that was conducted from 1997 to 2000 in a setting with a high level of readiness for implementing a randomized experiment of therapeutic community (TC) drug treatment training in Peru. Seventy-six drug abuse treatment organizations were randomly assigned into three groups, and data were collected at multiple assessment periods. Staff and directors in organizations assigned to the training groups participated in either 6-week basic training or 8-week basic plus booster training sessions, which were theoretically grounded. Small- to medium-size positive effects were found on increased staff empowerment to use actual tools and principles from the training; medium and large positive effects were found on the implementation of TC methods with fidelity after the training. A follow-up with the funding and training organizations 1 year later showed use of the evaluation results in decision making in both organizations.