Statistical shape and appearance models for fast and automated estimation of proximal femur fracture load using 2D finite element models

Estimating the risk of osteoporotic fractures is an important diagnostic step that needs to be taken before medicinal treatment. Densitometry-based criteria are normally used in clinical practice for this purpose. However, densitometry-based techniques could not explain all low-energy fractures. As patient-specific finite element (FE) models allow for consideration of other parameters (e.g. load conditions) that are known to be associated with fracture, they are considered promising candidates for more accurate fracture risk estimation. Nevertheless, they are often time consuming, expensive, and complex to build and may need the type of expertise that is not normally available in clinical settings. In this study, we report the development of an automated platform for estimating proximal femur fracture loads using patient-specific 2D FE models generated using dual-energy x-ray absorptiometry (DXA) scans. First, a statistical shape and appearance model (SSAM) is built using DXA scans of patients screened for osteoporosis following a low energy fracture. SSAM is then used together with Active Appearance Models (AAM) for automated segmentation of the proximal femur from new unseen DXA scans. The mean point-to-curve error of the automated procedure, i.e. 1.2–1.4 mm, is shown to be only slightly larger than the intra-observer variability of manual segmentation, i.e. 1.0 mm. Moreover, the developed platform automatically meshes the segmented shape, assigns density-based mechanical properties, assigns loads and boundary conditions, submits the 2D FE model for solution, and performs post-processing of the 2D FE simulation data to determine fracture loads. The fracture loads predicted using the manually generated and automatically generated 2D FE models are shown to be very close with a mean difference of around 8.8%. Repeated measures ANOVA showed no significant differences between the fracture loads calculated using FE models manually generated by three independent observers and those calculated using the automatically generated FE models (p>0.05).     

Reducing variability of crossvalidation for smoothing-parameter choice

One of the attractions of crossvalidation, as a tool for smoothing-parameterchoice, is its applicability to a wide variety of estimatortypes and contexts. However, its detractors comment adverselyon the relatively high variance of crossvalidatory smoothingparameters, noting that this compromises the performance ofthe estimators in which those parameters are used. We show thatthe variability can be reduced simply, significantly and reliablyby employing bootstrap aggregation or bagging. We establishthat in theory, when bagging is implemented using an adaptivelychosen resample size, the variability of crossvalidation canbe reduced by an order of magnitude. However, it is arguablymore attractive to use a simpler approach, based for exampleon half-sample bagging, which can reduce variability by approximately50%.     

The Effect of Recombination on the Accuracy of Phylogeny Estimation

Phylogenetic studies based on DNA sequences typically ignore the potential occurrence of recombination, which may produce different alignment regions with different evolutionary histories. Traditional phylogenetic methods assume that a single history underlies the data. If recombination is present, can we expect the inferred phylogeny to represent any of the underlying evolutionary histories? We examined this question by applying traditional phylogenetic reconstruction methods to simulated recombinant sequence alignments. The effect of recombination on phylogeny estimation depended on the relatedness of the sequences involved in the recombinational event and on the extent of the different regions with different phylogenetic histories. Given the topologies examined here, when the recombinational event was ancient, or when recombination occurred between closely related taxa, one of the two phylogenies underlying the data was generally inferred. In this scenario, the evolutionary history corresponding to the majority of the positions in the alignment was generally recovered. Very different results were obtained when recombination occurred recently among divergent taxa. In this case, when the recombinational breakpoint divided the alignment in two regions of similar length, a phylogeny that was different from any of the true phylogenies underlying the data was inferred.     

A RESIDENT POPULATION OF INDO-PACIFIC BOTTLENOSE DOLPHINS (TURSIOPS ADUNCUS) IN AMAKUSA, WESTERN KYUSHU, JAPAN

Residency patterns and population size were examined for Indo-Pacific bottlenose dolphins ( Tursiops aduncus ) in the coastal waters of Amakusa-Shimoshima Island, western Kyushu, Japan, from summer 1994 to fall 1998. A total of 203 individuals were identified. The number of newly identified individuals barely increased after the first 1.5 yr. The identified individuals in one season were frequently resighted with percentages of mostly over 60% during the subsequent seasons. Most of the dolphins off Amakusa were yearround residents, although the total range of their habitat was unknown. The population size estimated by the mark-recapture technique was 218 individuals with a CV of 5.41% in 1995–1997. The group commonly consisted of more than 100 individuals. The large group size was thought to be a response to feeding on schooling fishes.     

The distribution of the coalescence time and the number of pairwise nucleotide differences in a model of population divergence or speciation with an initial period of gene flow

This paper is concerned with a model of “isolation with an initial period of migration”, where a panmictic ancestral population split into n descendant populations which exchanged migrants symmetrically at a constant rate for a period of time and subsequently became completely isolated. In the limit as the population split occurred an infinitely long time ago, the model becomes an “isolation after migration” model, describing completely isolated descendant populations which arose from a subdivided ancestral population. The probability density function of the coalescence time of a pair of genes and the probability distribution of the number of pairwise nucleotide differences are derived for both models. Whilst these are theoretical results of interest in their own right, they also give an exact analytical expression for the likelihood, for data consisting of the numbers of nucleotide differences between pairs of DNA sequences where each pair is at a different, independent locus. The behaviour of the distribution of the number of pairwise nucleotide differences under these models is illustrated and compared to the corresponding distributions under the “isolation with migration” and “complete isolation” models. It is shown that the distribution of the number of nucleotide differences between a pair of DNA sequences from different descendant populations in the model of “isolation with an initial period of migration” can be quite different from that under the “isolation with migration model”, even if the average migration rate over time (and hence the total number of migrants) is the same in both scenarios. It is also illustrated how the results can be extended to other demographic scenarios that can be described by a combination of isolated panmictic populations and “symmetric island” models.     

On estimating mortalities from osteological age data

A statistical method (based on the maximum likelihood principle) for estimating mortalities of skeletal populations is presented. The method can be applied both when osteological age groups are not overlapping as well as when they are. The results are presented as point estimates and as confidence intervals around these. The method is applied to two series from the Middle Ages: Westerhus and Helgeandsholmen.     

Integrating Prior Knowledge in Multiple Testing under Dependence with Applications to Detecting Differential DNA Methylation

Summary DNA methylation has emerged as an important hallmark of epigenetics. Numerous platforms including tiling arrays and next generation sequencing, and experimental protocols are available for profiling DNA methylation. Similar to other tiling array data, DNA methylation data shares the characteristics of inherent correlation structure among nearby probes. However, unlike gene expression or protein DNA binding data, the varying CpG density which gives rise to CpG island, shore and shelf definition provides exogenous information in detecting differential methylation. This article aims to introduce a robust testing and probe ranking procedure based on a nonhomogeneous hidden Markov model that incorporates the above‐mentioned features for detecting differential methylation. We revisit the seminal work of Sun and Cai (2009, Journal of the Royal Statistical Society: Series B (Statistical Methodology) 71 , 393–424) and propose modeling the nonnull using a nonparametric symmetric distribution in two‐sided hypothesis testing. We show that this model improves probe ranking and is robust to model misspecification based on extensive simulation studies. We further illustrate that our proposed framework achieves good operating characteristics as compared to commonly used methods in real DNA methylation data that aims to detect differential methylation sites.     

Diversification of low dispersal crustaceans through mountain uplift: a case study of Gammarus (Amphipoda: Gammaridae) with descriptions of four novel species

Lineages with low dispersal ability are geographically restricted. We used freshwater Gammarus to test this hypothesis. Sequences of two mitochondrial (cytochrome c oxidase subunit I and 16S) and two nuclear (28S and cytosolic heat‐shock protein) genes were obtained for seven species distributed in 28 localities along the Lüliang and Taihang mountains in China. Phylogenetic analyses showed that Gammarus species were grouped into two clades, one from the Lüliang range and the other from the Taihang range. Each clade was further divided into three or four species, showing a congruent pattern with geographical vicariance. Divergence time estimation indicated that the split between the two clades coincided with the uplift of the Taihang Mountains at the boundary of Oligocene/Miocene. Most speciation events may have been driven by massive uplifting of the Lüliang and Taihang mountains from the late Miocene to early Pliocene. Additionally, four new species are described: G ammarus incoercitus sp. nov. , G ammarus benignus sp. nov. , G ammarus monticellus sp. nov. , and G ammarus pisinnus sp. nov. The new species are compared with related species in this area and a key to these species is provided. © 2014 The Linnean Society of London