Material and Structural Aspects of Bone in Osteogenesis Imperfecta

Bone fragility is a fundamental problem in individuals with osteogenesis imperfecta (OI). The mechanisms behind this fragility, however, are not yet well understood. Multiple factors appear to contribute to the increased fracture risk in OI. At the structural level, bone mass deficiency can result in increased stress levels within bones. The underlying mineral and collagen abnormalities that define OI are also believed to result in compromised material-level properties. The variability of collagen biochemical irregularities causing OI and the corresponding heterogeneity of disease severity result in abnormalities that are not easily generalized within the OI population. The aims of this chapter are to introduce basic mechanical notions pertaining to the strength of structures and materials, and to present a synthesis of existing literature regarding the mechanical properties of bones in OI

Simulating interventions in graphical chain models for longitudinal data

Simulating the outcome of an intervention is a central problem in many fields as this allows decision-makers to quantify the effect of any given strategy and, hence, to evaluate different schemes of actions. Simulation is particularly relevant in very large systems where the statistical model involves many variables that, possibly, interact with each other. In this case one usually has a large number of parameters whose interpretation becomes extremely difficult. Furthermore, in a real system, although one may have a unique target variable, there may be a number of variables which might, and often should, be logically considered predictors of the target outcome and, at the same time, responses of other variables of the system. An intervention taking place on a given variable, therefore, may affect the outcome either directly and indirectly though the way in which it affects other variables within the system. Graphical chain models are particularly helpful in depicting all of the paths through which an intervention may affect the final outcome. Furthermore, they identify all of the relevant conditional distributions and therefore they are particularly useful in driving the simulation process. Focussing on binary variables, we propose a method to simulate the effect of an intervention. Our approach, however, can be easily extended to continuous and mixed responses variables. We apply the proposed methodology to assess the effect that a policy intervention may have on poorer health in early adulthood using prospective data provided by the 1970 British Birth Cohort Study (BCS70).chain graph, conditional approach, Gibbs Sampling, Simulation of interventions, age at motherhood, mental health

Methods of calculating ionization energies of multielectron (five or more) isoelectronic atomic ions

We have previously used simple empirical equations to reproduce the literature values of the ionization energies of isoelectronic sequences of up to four electrons which gave very good agreement. We reproduce here a kinetic energy expression with corrections for relativity and Lamb shift effects which give excellent agreement with the literature values. These equations become more complex as the number of electrons in the system increases. Alternative simple quadratic expressions for calculating ionization energies of multielectron ions are discussed. A set of coefficients when substituted into a simple expression produces very good agreement with the literature values. Our work shows that Slater's rules are not appropriate for predicting trends or screening constants. This work provides very strong evidence that ionization energies are not functions of complete squares, and when calculating ionization energies electron transition/relaxation has to be taken into account. We demonstrate clearly that for particular isoelectronic sequences, the ionizing electrons may occupy different orbitals and in such cases more than one set of constants are needed to calculate the ionization energies

Micro-CT Characterization of Human Trabecular Bone in Osteogenesis Imperfecta

Osteogenesis imperfecta (OI) is a genetic syndrome affecting collagen synthesis and assembly. Its symptoms vary widely but commonly include bone fragility, reduced stature, and bone deformity. Because of the small size and paucity of human specimens, there is a lack of biomechanical data for OI bone. Most literature has focused on histomorphometric analyses, which rely on assumptions to extrapolate 3-D properties. In this study, a micro-computed tomography (μCT) system was used to directly measure structural and mineral properties in pediatric OI bone collected during routine surgical procedures. Surface renderings suggested a poorly organized, plate-like orientation. Patients with a history of bone-augmenting drugs exhibited increased bone volume fraction (BV/TV), trabecular number (Tb.N), and connectivity density (Eu.Conn.D). The latter two parameters appeared to be related to OI severity. Structural results were consistently higher than those reported in a previous histomorphometric study, but these differences can be attributed to factors such as specimen collection site, drug therapy, and assumptions associated with histomorphometry. Mineral testing revealed strong correlations with several structural parameters, highlighting the importance of a dual approach in trabecular bone testing. This study reports some of the first quantitative μCT data of human OI bone, and it suggests compelling possibilities for the future of OI bone assessment

BENEFIT COST ANALYSIS OF THE 2002 EQIP FARM BILL PROVISIONS

Benefit and cost estimates for the Environmental Quality Incentives Program (EQIP) are given. The 2002 Farm Bill increased EQIP funding five fold and allows a broader scope of participation. Estimates for seven classes of environmental benefits and the sensitivity of those estimates to program implementation alternatives are included.Agricultural and Food Policy,

Quantitative Assessment of Children with Osteogenesis Imperfecta

Assessments of children with Osteogenesis Imperfecta (OI) are typically limited to a physical exam and observations from a clinician during a hospital visit. Often quantitative information such as bone mineral density and outcome questionnaires is obtained, but with the increasing prevalence of motion analysis and other performance type laboratories, there are many other tools available, which could be beneficial to this patient population. These laboratories can provide date supplementary to morphologic and radiographic data that is helpful in tracking changes in the patient’s functional abilities, recover from fracture, and treatment outcomes. This chapter will cover some useful evaluation methods for children with the most commonly seen types of OI and provide some examples of their test results