Morphology–elasticity relationships using decreasing fabric information of human trabecular bone from three major anatomical locations

With improving clinical CT scanning technology, the accuracy of CT-based finite element (FE) models of the human skeleton may be ameliorated by an enhanced description of apparent level bone mechanical properties. Micro-finite element (μFE) modeling can be used to study the apparent elastic behavior of human cancellous bone. In this study, samples from the femur, radius and vertebral body were investigated to evaluate the predictive power of morphology–elasticity relationships and to compare them across different anatomical regions. μFE models of 701 trabecular bone cubes with a side length of 5.3 mm were analyzed using kinematic boundary conditions. Based on the FE results, four morphology–elasticity models using bone volume fraction as well as full, limited or no fabric information were calibrated for each anatomical region. The 5 parameter Zysset–Curnier model using full fabric information showed excellent predictive power with coefficients of determination ( r2adj ) of 0.98, 0.95 and 0.94 of the femur, radius and vertebra data, respectively, with mean total norm errors between 14 and 20%. A constant orthotropy model and a constant transverse isotropy model, where the elastic anisotropy is defined by the model parameters, yielded coefficients of determination between 0.90 and 0.98 with total norm errors between 16 and 25%. Neglecting fabric information and using an isotropic model led to r2adj between 0.73 and 0.92 with total norm errors between 38 and 49%. A comparison of the model regressions revealed minor but significant (p<0.01) differences for the fabric–elasticity model parameters calibrated for the different anatomical regions. The proposed models and identified parameters can be used in future studies to compute the apparent elastic properties of human cancellous bone for homogenized FE models.

Inheritance of equine sarcoid disease in Franches-Montagnes horses.

The mode of inheritance for susceptibility to equine sarcoid disease (ES) remains unknown. The objectives of this study were to analyse a large sample of the Franches-Montagnes (FM) horse population and investigate the heritability and mode of inheritance for susceptibility to ES. Horses were clinically examined for the presence of sarcoid tumours. A standardized examination protocol and client questionnaire were used and a pedigree- and subsequent segregation-analysis for the ES trait performed. To investigate the mode of inheritance, five models were evaluated and compared in a hierarchical way. The analyses reveal that variation in susceptibility to ES is best explained by a model incorporating polygenic variation. The possible effect of a major gene, such as specific equine leukocyte antigen alleles, is unlikely, but cannot be ruled-out entirely. The heritability of the phenotype on the observation scale for the trait 'affected with ES' was estimated to be 8%. A corrected value for the heritability on a liability scale was estimated at 21% and it is therefore possible to estimate breeding values for ES. The arguments against the practical implementation of an estimated breeding value in a multifactorial condition like ES are discussed.

High-resolution mineral dust and sea ice proxy records from the Talos Dome ice core

In this study we report on new non-sea salt calcium (nssCa2+, mineral dust proxy) and sea salt sodium (ssNa+, sea ice proxy) records along the East Antarctic Talos Dome deep ice core in centennial resolution reaching back 150 thousand years (ka) before present. During glacial conditions nssCa2+ fluxes in Talos Dome are strongly related to temperature as has been observed before in other deep Antarctic ice core records, and has been associated with synchronous changes in the main source region (southern South America) during climate variations in the last glacial. However, during warmer climate conditions Talos Dome mineral dust input is clearly elevated compared to other records mainly due to the contribution of additional local dust sources in the Ross Sea area. Based on a simple transport model, we compare nssCa2+ fluxes of different East Antarctic ice cores. From this multi-site comparison we conclude that changes in transport efficiency or atmospheric lifetime of dust particles do have a minor effect compared to source strength changes on the large-scale concentration changes observed in Antarctic ice cores during climate variations of the past 150 ka. Our transport model applied on ice core data is further validated by climate model data. The availability of multiple East Antarctic nssCa2+ records also allows for a revision of a former estimate on the atmospheric CO2 sensitivity to reduced dust induced iron fertilisation in the Southern Ocean during the transition from the Last Glacial Maximum to the Holocene (T1). While a former estimate based on the EPICA Dome C (EDC) record only suggested 20 ppm, we find that reduced dust induced iron fertilisation in the Southern Ocean may be responsible for up to 40 ppm of the total atmospheric CO2 increase during T1. During the last interglacial, ssNa+ levels of EDC and EPICA Dronning Maud Land (EDML) are only half of the Holocene levels, in line with higher temperatures during that period, indicating much reduced sea ice extent in the Atlantic as well as the Indian Ocean sector of the Southern Ocean. In contrast, Holocene ssNa+ flux in Talos Dome is about the same as during the last interglacial, indicating that there was similar ice cover present in the Ross Sea area during MIS 5.5 as during the Holocene.

Frequency-Dependent Selection Predicts Patterns of Radiations and Biodiversity

Most empirical studies support a decline in speciation rates through time, although evidence for constant speciation rates also exists. Declining rates have been explained by invoking pre-existing niches, whereas constant rates have been attributed to non-adaptive processes such as sexual selection and mutation. Trends in speciation rate and the processes underlying it remain unclear, representing a critical information gap in understanding patterns of global diversity. Here we show that the temporal trend in the speciation rate can also be explained by frequency-dependent selection. We construct a frequency-dependent and DNA sequence-based model of speciation. We compare our model to empirical diversity patterns observed for cichlid fish and Darwin's finches, two classic systems for which speciation rates and richness data exist. Negative frequency-dependent selection predicts well both the declining speciation rate found in cichlid fish and explains their species richness. For groups like the Darwin's finches, in which speciation rates are constant and diversity is lower, speciation rate is better explained by a model without frequency-dependent selection. Our analysis shows that differences in diversity may be driven by incipient species abundance with frequency-dependent selection. Our results demonstrate that genetic-distance-based speciation and frequency-dependent selection are sufficient to explain the high diversity observed in natural systems and, importantly, predict decay through time in speciation rate in the absence of pre-existing niches.

Bone Volume Fraction and Fabric Anisotropy Are Better Determinants of Trabecular Bone Stiffness than Other Morphological Variables

As our population ages, more individuals suffer from osteoporosis. This disease leads to impaired trabecular architecture and increased fracture risk. It is essential to understand how morphological and mechanical properties of the cancellous bone are related. Morphologyelasticity relationships based on bone volume fraction (BV/TV) and fabric anisotropy explain up to 98% of the variation in elastic properties. Yet, other morphological variables such as individual trabeculae segmentation (ITS) and trabecular bone score (TBS) could improve the stiffness predictions. A total of 743 micro-computed tomography reconstructions of cubic trabecular bone samples extracted from femur, radius, vertebrae and iliac crest were analysed. Their morphology was assessed via 25 variables and their stiffness tensor (inline image) was computed from six independent load cases using micro finite element analyses. Variance inflation factors were calculated to evaluate collinearity between morphological variables and decide upon their inclusion in morphology-elasticity relationships. The statistically admissible morphological variables were included in a multi-linear regression modelling the dependent variable inline image. The contribution of each independent variable was evaluated (ANOVA). Our results show that BV/TV is the best determinant of inline image (inline image=0.889), especially in combination with fabric (inline image=0.968). Including the other independent predictors hardly affected the amount of variance explained by the model (inline image=0.975). Across all anatomical sites, BV/TV explained 87% of the variance of the bone elastic properties. Fabric further described 10% of the bone stiffness, but the improvement in variance explanation by adding other independent factors was marginal (<1%). These findings confirm that BV/TV and fabric are the best determinants of trabecular bone stiffness and show, against common belief, that other morphological variables do not bring any further contribution. These overall conclusions remain to be confirmed for specific bone diseases and post-elastic properties.

Evidence for Emergency Vaccination Having Played a Crucial Role to Control the 1965/66 Foot-and-Mouth Disease Outbreak in Switzerland.

Foot-and-mouth disease (FMD) is a highly contagious disease that caused several large outbreaks in Europe in the last century. The last important outbreak in Switzerland took place in 1965/66 and affected more than 900 premises and more than 50,000 animals were slaughtered. Large-scale emergency vaccination of the cattle and pig population has been applied to control the epidemic. In recent years, many studies have used infectious disease models to assess the impact of different disease control measures, including models developed for diseases exotic for the specific region of interest. Often, the absence of real outbreak data makes a validation of such models impossible. This study aimed to evaluate whether a spatial, stochastic simulation model (the Davis Animal Disease Simulation model) can predict the course of a Swiss FMD epidemic based on the available historic input data on population structure, contact rates, epidemiology of the virus, and quality of the vaccine. In addition, the potential outcome of the 1965/66 FMD epidemic without application of vaccination was investigated. Comparing the model outcomes to reality, only the largest 10% of the simulated outbreaks approximated the number of animals being culled. However, the simulation model highly overestimated the number of culled premises. While the outbreak duration could not be well reproduced by the model compared to the 1965/66 epidemic, it was able to accurately estimate the size of the area infected. Without application of vaccination, the model predicted a much higher mean number of culled animals than with vaccination, demonstrating that vaccination was likely crucial in disease control for the Swiss FMD outbreak in 1965/66. The study demonstrated the feasibility to analyze historical outbreak data with modern analytical tools. However, it also confirmed that predicted epidemics from a most carefully parameterized model cannot integrate all eventualities of a real epidemic. Therefore, decision makers need to be aware that infectious disease models are useful tools to support the decision-making process but their results are not equal valuable as real observations and should always be interpreted with caution.

Rotating dust particles in the coma of comet 67P/Churyumov-Gerasimenko

Context. During September and October 2014, the OSIRIS cameras onboard the ESA Rosetta mission detected millions of single particles. Many of these dust particles appear as long tracks (due to both the dust proper motion and the spacecraft motion during the exposure time) with a clear brightness periodicity. Aims. We interpret the observed periodic features as a rotational and translational motion of aspherical dust grains. Methods. By counting the peaks of each track, we obtained statistics of a rotation frequency. We compared these results with the rotational frequency predicted by a model of aspherical dust grain dynamics in a model gas flow. By testing many possible sets of physical conditions and grain characteristics, we constrained the rotational properties of dust grains. Results. We analyzed on the motion of rotating aspherical dust grains with different cross sections in flow conditions corresponding to the coma of 67P/Churyumov-Gerasimenko qualitatively and quantitatively. Based on the OSIRIS observations, we constrain the possible physical parameters of the grains.

Lake-effect snow as the dominant control of mesic-forest distribution in Michigan, USA

1Recent studies demonstrated the sensitivity of northern forest ecosystems to changes in the amount and duration of snow cover at annual to decadal time scales. However, the consequences of snowfall variability remain uncertain for ecological variables operating at longer time scales, especially the distributions of forest communities. 2The Great Lakes region of North America offers a unique setting to examine the long-term effects of variable snowfall on forest communities. Lake-effect snow produces a three-fold gradient in annual snowfall over tens of kilometres, and dramatic edaphic variations occur among landform types resulting from Quaternary glaciations. We tested the hypothesis that these factors interact to control the distributions of mesic (dominated by Acer saccharum, Tsuga canadensis and Fagus grandifolia) and xeric forests (dominated by Pinus and Quercus spp.) in northern Lower Michigan. 3We compiled pre-European-settlement vegetation data and overlaid these data with records of climate, water balance and soil, onto Landtype Association polygons in a geographical information system. We then used multivariate adaptive regression splines to model the abundance of mesic vegetation in relation to environmental controls. 4Snowfall is the most predictive among five variables retained by our model, and it affects model performance 29% more than soil texture, the second most important variable. The abundance of mesic trees is high on fine-textured soils regardless of snowfall, but it increases with snowfall on coarse-textured substrates. Lake-effect snowfall also determines the species composition within mesic forests. The weighted importance of A. saccharum is significantly greater than of T. canadensis or F. grandifolia within the lake-effect snowbelt, whereas T. canadensis is more plentiful outside the snowbelt. These patterns are probably driven by the influence of snowfall on soil moisture, nutrient availability and fire return intervals. 5Our results imply that a key factor dictating the spatio-temporal patterns of forest communities in the vast region around the Great Lakes is how the lake-effect snowfall regime responds to global change. Snowfall reductions will probably cause a major decrease in the abundance of ecologically and economically important species, such as A. saccharum.