An anatomical model to determine step height in step testing for estimating aerobic capacity

Physical fitness has been reported to be inversely related to coronary heart disease and other health related problems. One of the most valid means of assessing physical fitness is the test of aerobic capacity. Aerobic capacity is the greatest rate at which the body can consume oxygen and represents the most efficient integration of the various physiological processes which make up the oxygen transport system. However, direct measurement of aerobic capacity requires sophisticated laboratory equipment, and is adversive to subjects. Step tests are widely used to estimate aerobic capacity. Because the biomechanical efficiency and work rate is determined by step height, accommodation of step height to the subject's statute height should provide a better estimation of aerobic capacity. A hip angle of 73.3 degrees, when stepping, was found to give the best relationship of recovery heart rate of a step test to direct measurement of aerobic capacity. Using 73.3 degrees, the following equations were developed for determining the stepping height when using the step test: Hf = 0.189 Ih and Hf = 0.192 Ih for females and males respectively, where hf is the step height and Ih is the statute height of the subject. A correlation coefficient (r) of 0.93 was calculated between various hip angles and calculated foot height of 182 observations of 47 females while a correlation coefficient (r) of 0.96 was calculated from 208 observations of 53 males. Using these equations to determine step height, measurement of 30 females showed a mean hip angle of 73.3 degrees +/- 2.2 and measurement of 30 males showed a mean hip angle of 73.3 degrees +/- 2.1.(ABSTRACT TRUNCATED AT 250 WORDS)     

Acquired Antibody Responses against Plasmodium vivax Infection Vary with Host Genotype for Duffy Antigen Receptor for Chemokines (DARC)

Background

Polymorphism of the Duffy Antigen Receptor for Chemokines (DARC) is associated with susceptibility to and the severity of Plasmodium vivax malaria in humans. P. vivax uses DARC to invade erythrocytes. Individuals lacking DARC are ‘resistant’ to P. vivax erythrocytic infection. However, susceptibility to P. vivax in DARC+ individuals is reported to vary between specific DARC genotypes. We hypothesized that the natural acquisition of antibodies to P. vivax blood stages may vary with the host genotype and the level of DARC expression. Furthermore, high parasitemia has been reported to effect the acquisition of immunity against pre-erythrocytic parasites. We investigated the correlation between host DARC genotypes and the frequency and magnitude of antibodies against P. vivax erythrocytic stage antigens.

Methodology/Findings

We assessed the frequencies and magnitudes of antibody responses against P. vivax and P. falciparum sporozoite and erythrocytic antigens in Colombian donors from malaria-endemic regions. The frequency and level of naturally-acquired antibodies against the P. vivax erythrocytic antigens merozoite surface protein 1 (PvMSP1) and Duffy binding protein (PvDBP) varied with the host DARC genotypes. Donors with one negative allele (FY*B/FY*Bnull and FY*A/FY*Bnull) were more likely to have anti-PvMSP1 and anti-PvDBP antibodies than those with two positive alleles (FY*B/FY*B and FY*A/FY*B). The lower IgG3 and IgG1 components of the total IgG response may account for the decreased responses to P. vivax erythrocytic antigens with FY*A/FY*B and FY*B/FY*B genotypes. No such association was detected with P. falciparum erythrocytic antigens, which does not use DARC for erythrocyte invasion.

Conclusion/Significance

Individuals with higher DARC expression, which is associated with higher susceptibility to P. vivax infection, exhibited low frequencies and magnitudes of P. vivax blood-stage specific antibody responses. This may indicate that one of the primary mechanisms by which P. vivax evades host immunity is through DARC indirectly down-regulating humoral responses against erythrocytic invasion and development.     

Technical approaches for mouse models of human disease

The mouse is the leading organism for disease research. A rich resource of genetic variation occurs naturally in inbred and special strains owing to spontaneous mutations. However, one can also obtain desired gene mutations by using the following processes: targeted mutations that eliminate function in the whole organism or in a specific tissue; forward genetic screens using chemicals or transposons; or the introduction of exogenous transgenes as DNAs, bacterial artificial chromosomes (BACs) or reporter constructs. The mouse is the only mammal that provides such a rich resource of genetic diversity coupled with the potential for extensive genome manipulation, and is therefore a powerful application for modeling human disease. This poster review outlines the major genome manipulations available in the mouse that are used to understand human disease: natural variation, reverse genetics, forward genetics, transgenics and transposons. Each of these applications will be essential for understanding the diversity that is being discovered within the human population.     

Diversity surveys and evolutionary relationships of aoxB genes in aerobic arsenite-oxidizing bacteria

A new primer set was designed to specifically amplify ca. 1,100 bp of aoxB genes encoding the As(III) oxidase catalytic subunit from taxonomically diverse aerobic As(III)-oxidizing bacteria. Comparative analysis of AoxB protein sequences showed variable conservation levels and highlighted the conservation of essential amino acids and structural motifs. AoxB phylogeny of pure strains showed well-discriminated taxonomic groups and was similar to 16S rRNA phylogeny. Alphaproteobacteria-, Betaproteobacteria-, and Gammaproteobacteria-related sequences were retrieved from environmental surveys, demonstrating their prevalence in mesophilic As-contaminated soils. Our study underlines the usefulness of the aoxB gene as a functional marker of aerobic As(III) oxidizers.     

Development of a statistical model of knee kinetics for applications in pre-clinical testing

Pre-clinical computational testing of total knee replacements (TKRs) often only considers a single patient model with simplified applied loads. In studies of multiple patients, most only take into account geometric differences, especially in studies on the knee. Limited availability of kinetic data means that it is difficult to account for inter-patient variability. Principal component analysis (PCA) based statistical models have been used to capture the variation of a set of data and generate new instances of the data. This study presents a method to create a statistical model of kinetic waveform data. A PCA based statistical model was created of the tibiofemoral joint loads for level gait of preoperative TKR patients using data predicted from a musculoskeletal model. A reconstruction test showed that, using principal components (PCs) representing 95% variance, the median root-mean-squared (RMS) error was <0.1 body weight (BW) for the forces and <0.001 BWm for the moments. Leave-one-out tests were also performed and although the median RMS error increased for each load in comparison to the reconstruction error (maximum was 0.2 BW for the axial force and 0.012 BWm for the varus-valgus moment) these were considered within an acceptable limit. The purpose of creating a statistical model is to be able to sample a large set of data representing a population from a small set of clinical data. Such models can potentially be used in population based studies of TKRs incorporating inter-patient variability.