Physical therapy assessment tools to evaluate disease progression and phenotype variability in Golden Retriever muscular dystrophy

Dogs suffering from Golden Retriever muscular dystrophy (GRMD) present symptoms that are similar to human patients with Duchenne muscular dystrophy (DMD). Phenotypic variability is common in both cases and correlates with disease progression and response to therapy. Physical therapy assessment tools were used to study disease progression and assess phenotypic variability in dogs with GRMD. At 5 (TO), 9 (T1), 13 (T2) and 17 (T3) months of age, the physical features, joint ranges of motion (ROM), limb and thorax circumferences, weight and creatine kinase (CK) levels were assessed in 11 dogs with GRMD. Alterations of physical features were higher at 13 months, and different disease progression rates were observed. Passive ROM decreased until 1 year old, which was followed by a decline of elbow and tarsal ROM. Limb and thorax circumferences, which were corrected for body weight, decreased significantly between TO and T3. These measurements can be used to evaluate disease progression in dogs with GRMD and to help discover new therapies for DMD patients. (C) 2011 Elsevier Ltd. All rights reserved.

Outcomes and indicators, measurement tools, and databases for the National Action Plan for Promotion, Prevention and Early Intervention for Mental Health 2000

This publication is a support and resource document for the "National Action Plan for Promotion, Prevention and Early Intervention for Mental Health 2000". It includes indicators, measurement tools and databases relevant to assessing the implementation of the outcomes and strategies identified in the action plan.

Genetic influence on ERP slow wave measures of working memory

Individual differences in the variance of event-related potential (ERP) slow wave (SW) measures were examined. SW was recorded at prefrontal and parietal sites during memory and sensory trials of a delayed-response task in 391 adolescent twin pairs. Familial resemblance was identified and there was a strong suggestion of genetic influence. A common genetic factor influencing memory and sensory SW was identified at the prefrontal site (accounting for an estimated 35%-37% of the reliable variance) and at the parietal site (51%-52% of the reliable variance). Remaining reliable variance was influenced by unique environmental factors. Measurement error accounted for 24% to 30% of the total variance of each variable. The results show genetic independence for recording site, but not trial type, and suggest that the genetic factors identified relate more directly to brain structures, as defined by the cognitive functions they support, than to the cognitive networks that link them.