The fixation of the cemented femoral component. Effects of stem stiffness, cement thickness and roughness of the cement-bone surface.

After cemented total hip arthroplasty (THA) there may be failure at either the cement-stem or the cement-bone interface. This results from the occurrence of abnormally high shear and compressive stresses within the cement and excessive relative micromovement. We therefore evaluated micromovement and stress at the cement-bone and cement-stem interfaces for a titanium and a chromium-cobalt stem. The behaviour of both implants was similar and no substantial differences were found in the size and distribution of micromovement on either interface with respect to the stiffness of the stem. Micromovement was minimal with a cement mantle 3 to 4 mm thick but then increased with greater thickness of the cement. Abnormally high micromovement occurred when the cement was thinner than 2 mm and the stem was made of titanium. The relative decrease in surface roughness augmented slipping but decreased debonding at the cement-bone interface. Shear stress at this site did not vary significantly for the different coefficients of cement-bone friction while compressive and hoop stresses within the cement increased slightly.

quantiNemo: an individual-based program to simulate quantitative traits with explicit genetic architecture in a dynamic metapopulation.

quantiNemo is an individual-based, genetically explicit stochastic simulation program. It was developed to investigate the effects of selection, mutation, recombination and drift on quantitative traits with varying architectures in structured populations connected by migration and located in a heterogeneous habitat. quantiNemo is highly flexible at various levels: population, selection, trait(s) architecture, genetic map for QTL and/or markers, environment, demography, mating system, etc. quantiNemo is coded in C++ using an object-oriented approach and runs on any computer platform. Availability: Executables for several platforms, user's manual, and source code are freely available under the GNU General Public License at http://www2.unil.ch/popgen/softwares/quantinemo.

The M-Coffee web server: a meta-method for computing multiple sequence alignments by combining alternative alignment methods.

The M-Coffee server is a web server that makes it possible to compute multiple sequence alignments (MSAs) by running several MSA methods and combining their output into one single model. This allows the user to simultaneously run all his methods of choice without having to arbitrarily choose one of them. The MSA is delivered along with a local estimation of its consistency with the individual MSAs it was derived from. The computation of the consensus multiple alignment is carried out using a special mode of the T-Coffee package [Notredame, Higgins and Heringa (T-Coffee: a novel method for fast and accurate multiple sequence alignment. J. Mol. Biol. 2000; 302: 205-217); Wallace, O'Sullivan, Higgins and Notredame (M-Coffee: combining multiple sequence alignment methods with T-Coffee. Nucleic Acids Res. 2006; 34: 1692-1699)] Given a set of sequences (DNA or proteins) in FASTA format, M-Coffee delivers a multiple alignment in the most common formats. M-Coffee is a freeware open source package distributed under a GPL license and it is available either as a standalone package or as a web service from www.tcoffee.org.

Reliable selfing rate estimates from imperfect population genetic data.

Genotypic frequencies at codominant marker loci in population samples convey information on mating systems. A classical way to extract this information is to measure heterozygote deficiencies (FIS) and obtain the selfing rate s from FIS = s/(2 - s), assuming inbreeding equilibrium. A major drawback is that heterozygote deficiencies are often present without selfing, owing largely to technical artefacts such as null alleles or partial dominance. We show here that, in the absence of gametic disequilibrium, the multilocus structure can be used to derive estimates of s independent of FIS and free of technical biases. Their statistical power and precision are comparable to those of FIS, although they are sensitive to certain types of gametic disequilibria, a bias shared with progeny-array methods but not FIS. We analyse four real data sets spanning a range of mating systems. In two examples, we obtain s = 0 despite positive FIS, strongly suggesting that the latter are artefactual. In the remaining examples, all estimates are consistent. All the computations have been implemented in a open-access and user-friendly software called rmes (robust multilocus estimate of selfing) available at http://ftp.cefe.cnrs.fr, and can be used on any multilocus data. Being able to extract the reliable information from imperfect data, our method opens the way to make use of the ever-growing number of published population genetic studies, in addition to the more demanding progeny-array approaches, to investigate selfing rates.

The clinical use of quantitative ultrasound (QUS) in the detection and management of osteoporosis

For the detection and management of osteoporosis and osteoporosis-related fractures, quantitative ultrasound (QUS) is emerging as a relatively low-cost and readily accessible alternative to dual-energy X-ray absorptiometry (DXA) measurement of bone mineral density (BMD) in certain circumstances. The following is a brief, but thorough review of the existing literature with respect to the use of QUS in 6 settings: 1) assessing fragility fracture risk; 2) diagnosing osteoporosis; 3) initiating osteoporosis treatment; 4) monitoring osteoporosis treatment; 5) osteoporosis case finding; and 6) quality assurance and control. Many QUS devices exist that are quite different with respect to the parameters they measure and the strength of empirical evidence supporting their use. In general, heel QUS appears to be most tested and most effective. Overall, some, but not all, heel QUS devices are effective assessing fracture risk in some, but not all, populations, the evidence being strongest for Caucasian females over 55 years old. Otherwise, the evidence is fair with respect to certain devices allowing for the accurate diagnosis of likelihood of osteoporosis, and generally fair to poor in terms of QUS use when initiating or monitoring osteoporosis treatment. A reasonable protocol is proposed herein for case-finding purposes, which relies on a combined assessment of clinical risk factors (CR.F) and heel QUS. Finally, several recommendations are made for quality assurance and control.

A numeric model to simulate solar individual ultraviolet exposure.

Exposure to solar ultraviolet (UV) light is the main causative factor for skin cancer. UV exposure depends on environmental and individual factors. Individual exposure data remain scarce and development of alternative assessment methods is greatly needed. We developed a model simulating human exposure to solar UV. The model predicts the dose and distribution of UV exposure received on the basis of ground irradiation and morphological data. Standard 3D computer graphics techniques were adapted to develop a rendering engine that estimates the solar exposure of a virtual manikin depicted as a triangle mesh surface. The amount of solar energy received by each triangle was calculated, taking into account reflected, direct and diffuse radiation, and shading from other body parts. Dosimetric measurements (n = 54) were conducted in field conditions using a foam manikin as surrogate for an exposed individual. Dosimetric results were compared to the model predictions. The model predicted exposure to solar UV adequately. The symmetric mean absolute percentage error was 13%. Half of the predictions were within 17% range of the measurements. This model provides a tool to assess outdoor occupational and recreational UV exposures, without necessitating time-consuming individual dosimetry, with numerous potential uses in skin cancer prevention and research.

Comparison and validation of tissue modelization and statistical classification methods in T1-weighted MR brain images.

This paper presents a validation study on statistical nonsupervised brain tissue classification techniques in magnetic resonance (MR) images. Several image models assuming different hypotheses regarding the intensity distribution model, the spatial model and the number of classes are assessed. The methods are tested on simulated data for which the classification ground truth is known. Different noise and intensity nonuniformities are added to simulate real imaging conditions. No enhancement of the image quality is considered either before or during the classification process. This way, the accuracy of the methods and their robustness against image artifacts are tested. Classification is also performed on real data where a quantitative validation compares the methods' results with an estimated ground truth from manual segmentations by experts. Validity of the various classification methods in the labeling of the image as well as in the tissue volume is estimated with different local and global measures. Results demonstrate that methods relying on both intensity and spatial information are more robust to noise and field inhomogeneities. We also demonstrate that partial volume is not perfectly modeled, even though methods that account for mixture classes outperform methods that only consider pure Gaussian classes. Finally, we show that simulated data results can also be extended to real data.

The evolution of judgement bias in indirect reciprocity.

Indirect reciprocity is a form of reciprocity where help is given to individuals based on their reputation. In indirect reciprocity, bad acts (such as not helping) reduce an individual's reputation while good acts (such as helping) increase an individual's reputation. Studies of indirect reciprocity assume that good acts and bad acts are weighted equally when assessing the reputation of an individual. As different information can be processed in different ways, this is not likely to be the case, and it is possible that an individual could bias an actor's reputation by putting more weight to acts of defection (not helping) than acts of co-operation (helping) or vice versa. We term this difference 'judgement bias', and build an individual-based model of image scoring to investigate the conditions under which it may evolve. We find that, if the benefits of co-operation are small, judgement bias is weighted towards acts perceived to be bad; if the benefits are high, the reverse is true. Our result is consistent under both scoring and standing strategies, and we find that allowing judgement bias to evolve increases the level of co-operation in the population.

Effect of knotting on polymer shapes and their enveloping ellipsoids.

We simulate freely jointed chains to investigate how knotting affects the overall shapes of freely fluctuating circular polymeric chains. To characterize the shapes of knotted polygons, we construct enveloping ellipsoids that minimize volume while containing the entire polygon. The lengths of the three principal axes of the enveloping ellipsoids are used to define universal size and shape descriptors analogous to the squared radius of gyration and the inertial asphericity and prolateness. We observe that polymeric chains forming more complex knots are more spherical and also more prolate than chains forming less complex knots with the same number of edges. We compare the shape measures, determined by the enveloping ellipsoids, with those based on constructing inertial ellipsoids and explain the differences between these two measures of polymer shape.

The evolution of trans-generational altruism: kin selection meets niche construction.

A cornerstone result of sociobiology states that limited dispersal can induce kin competition to offset the kin selected benefits of altruism. Several mechanisms have been proposed to circumvent this dilemma but all assume that actors and recipients of altruism interact during the same time period. Here, this assumption is relaxed and a model is developed where individuals express an altruistic act, which results in posthumously helping relatives living in the future. The analysis of this model suggests that kin selected benefits can then feedback on the evolution of the trait in a way that promotes altruistic helping at high rates under limited dispersal. The decoupling of kin competition and kin selected benefits results from the fact that by helping relatives living in the future, an actor is helping individuals that are not in direct competition with itself. A direct consequence is that behaviours which actors gain by reducing the common good of present and future generations can be opposed by kin selection. The present model integrates niche-constructing traits with kin selection theory and delineates demographic and ecological conditions under which altruism can be selected for; and conditions where the 'tragedy of the commons' can be reduced.

Use of anisotropic modelling in electrical impedance tomography: description of method and preliminary assessment of utility in imaging brain function in the adult human head.

Electrical Impedance Tomography (EIT) is an imaging method which enables a volume conductivity map of a subject to be produced from multiple impedance measurements. It has the potential to become a portable non-invasive imaging technique of particular use in imaging brain function. Accurate numerical forward models may be used to improve image reconstruction but, until now, have employed an assumption of isotropic tissue conductivity. This may be expected to introduce inaccuracy, as body tissues, especially those such as white matter and the skull in head imaging, are highly anisotropic. The purpose of this study was, for the first time, to develop a method for incorporating anisotropy in a forward numerical model for EIT of the head and assess the resulting improvement in image quality in the case of linear reconstruction of one example of the human head. A realistic Finite Element Model (FEM) of an adult human head with segments for the scalp, skull, CSF, and brain was produced from a structural MRI. Anisotropy of the brain was estimated from a diffusion tensor-MRI of the same subject and anisotropy of the skull was approximated from the structural information. A method for incorporation of anisotropy in the forward model and its use in image reconstruction was produced. The improvement in reconstructed image quality was assessed in computer simulation by producing forward data, and then linear reconstruction using a sensitivity matrix approach. The mean boundary data difference between anisotropic and isotropic forward models for a reference conductivity was 50%. Use of the correct anisotropic FEM in image reconstruction, as opposed to an isotropic one, corrected an error of 24 mm in imaging a 10% conductivity decrease located in the hippocampus, improved localisation for conductivity changes deep in the brain and due to epilepsy by 4-17 mm, and, overall, led to a substantial improvement on image quality. This suggests that incorporation of anisotropy in numerical models used for image reconstruction is likely to improve EIT image quality.