Developmental Brain Dysfunction: Revival and Expansion of Old Concepts Based on New Genetic Evidence

Neurodevelopmental disorders can be caused by many different genetic abnormalities that are individually rare but collectively common. Specific genetic causes, including certain copy number variants and single-gene mutations, are shared among disorders that are thought to be clinically distinct. This evidence of variability in the clinical manifestations of individual genetic variants and sharing of genetic causes among clinically distinct brain disorders is consistent with the concept of developmental brain dysfunction, a term we use to describe the abnormal brain function underlying a group of neurodevelopmental and neuropsychiatric disorders and to encompass a subset of various clinical diagnoses. Although many pathogenic genetic variants are currently thought to be variably penetrant, we hypothesise that when disorders encompassed by developmental brain dysfunction are considered as a group, the penetrance will approach 100%. The penetrance is also predicted to approach 100% when the phenotype being considered is a specific trait, such as intelligence or autistic-like social impairment, and the trait could be assessed using a continuous, quantitative measure to compare probands with non-carrier family members rather than a qualitative, dichotomous trait and comparing probands with the healthy population. Copyright 2013 Elsevier Ltd. All rights reserved.

A Metric to Evaluate and Synthesize Distributed Compliant Mechanisms

Compliant mechanisms with evenly distributed stresses have better load-bearing ability and larger range of motion than mechanisms with compliance and stresses lumped at flexural hinges. In this paper, we present a metric to quantify how uniformly the strain energy of deformation and thus the stresses are distributed throughout the mechanism topology. The resulting metric is used to optimize cross-sections of conceptual compliant topologies leading to designs with maximal stress distribution. This optimization framework is demonstrated for both single-port mechanisms and single-input single-output mechanisms. It is observed that the optimized designs have lower stresses than their nonoptimized counterparts, which implies an ability for single-port mechanisms to store larger strain energy, and single-input single-output mechanisms to perform larger output work before failure.