Validation of density–elasticity relationships for finite element modeling of human pelvic bone by modal analysis

In total hip arthroplasty and particularly in revision surgery, computer assisted pre-operative prediction of the best possible anchorage strategy for implant fixation would be a great help to the surgeon. Computer simulation relies on validated numerical models. In the current study, three density–elasticity relationships (No. 1–3) from the literature for inhomogeneous material parameter assignment from CT data in automated finite element (FE) modeling of long bones were evaluated for their suitability for FE modeling of human pelvic bone. Numerical modal analysis was conducted on 10 FE models of hemipelvic bone specimens and compared to the gold standard provided by experimental modal analysis results from a previous in-vitro study on the same specimens. Overall, calculated resonance frequencies came out lower than measured values. Magnitude of mean relative deviation of numerical resonance frequencies with regard to measured values is lowest for the density–elasticity relationship No. 3 (−15.9%) and considerably higher for both density–elasticity relationships No. 1 (−41.1%) and No. 2 (−45.0%). Mean MAC values over all specimens amount to 77.8% (No. 1), 78.5% (No. 2), and 83.0% (No. 3). MAC results show, that mode shapes are only slightly influenced by material distribution. Calculated resonance frequencies are generally lower than measured values, which indicates, that numerical models lack stiffness. Even when using the best suited (No. 3) out of three investigated density–elasticity relationships, in FE modeling of pelvic bone a considerable underestimation of model stiffness has to be taken into account.     

Deducing Underlying Mechanisms from Protein Recruitment Data

By using fluorescent labelling techniques, the distribution and dynamics of proteins can be measured within living cells, allowing to study in vivo the response of cells to a triggering event, such as DNA damage. In order to evaluate the reaction rate constants and to identify the proteins and reactions that are essential for the investigated process, mechanistic models are used, which often contain many proteins and associated parameters and are therefore underdetermined by the data. In order to establish criteria for assessing the significance of a model, we present here a systematic investigation of the information that can be reliably deduced from protein recruitment data, assuming that the complete set of reactions that affect the data of the considered protein species is not known. To this purpose, we study in detail models where one or two proteins that influence each other are recruited to a substrate. We show that in many cases the kind of interaction between the proteins can be deduced by analyzing the shape of the recruitment curves of one protein. Furthermore, we discuss in general in which cases it is possible to discriminate between different models and in which cases it is impossible based on the data. Finally, we argue that if different models fit experimental data equally well, conducting experiments with different protein concentrations would allow discrimination between the alternative models in many cases.     

Angelman syndrome and severe infections in a patient with de novo 15q11.2–q13.1 deletion and maternally inherited 2q21.3 microdeletion

Angelman syndrome is a neurodevelopmental disorder characterized by mental retardation, severe speech disorder, facial dysmorphism, secondary microcephaly, ataxia, seizures, and abnormal behaviors such as easily provoked laughter. It is most frequently caused by a de novo maternal deletion of chromosome 15q11–q13 (about 70–90%), but can also be caused by paternal uniparental disomy of chromosome 15q11–q13 (3–7%), an imprinting defect (2–4%) or in mutations in the ubiquitin protein ligase E3A gene UBE3A mostly leading to frame shift mutation. In addition, for patients with overlapping clinical features (Angelman-like syndrome), mutations in methyl-CpG binding protein 2 gene MECP2 and cyclin-dependent kinase-like 5 gene CDKL5 as well as a microdeletion of 2q23.1 including the methyl-CpG binding domain protein 5 gene MBD5 have been described. Here, we describe a patient who carries a de novo 5 Mb-deletion of chromosome 15q11.2–q13.1 known to be associated with Angelman syndrome and a further, maternally inherited deletion 2q21.3 (~ 364 kb) of unknown significance. In addition to classic features of Angelman syndrome, she presented with severe infections in the first year of life, a symptom that has not been described in patients with Angelman syndrome. The 15q11.2–q13.1 deletion contains genes critical for Prader–Willi syndrome, the Angelman syndrome causing genes UBE3A and ATP10A/C, and several non-imprinted genes: GABRB3 and GABRA5 (both encoding subunits of GABA A receptor), GOLGA6L2, HERC2 and OCA2 (associated with oculocutaneous albinism II). The deletion 2q21.3 includes exons of the genes RAB3GAP1 (associated with Warburg Micro syndrome) and ZRANB3 (not disease-associated). Despite the normal phenotype of the mother, the relevance of the 2q21.3 microdeletion for the phenotype of the patient cannot be excluded, and further case reports will need to address this point.     

Relation between complexity and stability in food webs with adaptive behavior

We investigate the influence of functional responses (Lotka-Volterra or Holling type), initial topological web structure (randomly connected or niche model), adaptive behavior (adaptive foraging and predator avoidance) and the type of constraints on the adaptive behavior (linear or nonlinear) on the stability and structure of food webs. Two kinds of stability are considered: one is the network robustness (i.e., the proportion of species surviving after population dynamics) and the other is the species deletion stability. When evaluating the network structure, we consider link density as well as the trophic level structure. We show that the types of functional responses and initial web structure do not have a large effect on the stability of food webs, but foraging behavior has a large stabilizing effect. It leads to a positive complexity-stability relationship whenever higher "complexity" implies more potential prey per species. The other type of adaptive behavior, predator avoidance behavior, makes food webs only slightly more stable. The observed link density after population dynamics depends strongly on the presence or absence of adaptive foraging, and on the type of constraints used. We also show that the trophic level structure is preserved under population dynamics with adaptive foraging.     

Competitive speciation in quantitative genetic models

We study sympatric speciation due to competition in an environment with a broad distribution of resources. We assume that the trait under selection is a quantitative trait, and that mating is assortative with respect to this trait. Our model alternates selection according to Lotka-Volterra-type competition equations, with reproduction using the ideas of quantitative genetics. The recurrence relations defined by these equations are studied numerically and analytically. We find that when a population enters a new environment, with a broad distribution of unexploited food sources, the population distribution broadens under a variety of conditions, with peaks at the edge of the distribution indicating the formation of subpopulations. After a long enough time period, the population can split into several subpopulations with little gene flow between them.     

Ecological character displacement in quantitative genetic models

We study, both analytically and numerically, models of ecological character displacement for two species that compete for the same set of food sources. These models include quantitative genetics and Lotka-Volterra type competition and are symmetric with respect to the two species. We allow for various shapes of the carrying capacity and the competition function, and we discuss under what general conditions large character displacement can occur. While some of these conditions, like genetic rigidity, or flat and truncated carrying capacity curves, were known before, we also find that slow dynamics of the genetic variance, steep slopes in the interaction function and carrying capacities that are not truncated can lead to large displacements. We interpret these conditions biologically and also give new insights into models which have been previously investigated.     

Emergence of complexity in evolving niche-model food webs

We have analysed mechanisms that promote the emergence of complex structures in evolving model food webs. The niche model is used to determine predator-prey relationships. Complexity is measured by species richness as well as trophic level structure and link density. Adaptive dynamics that allow predators to concentrate on the prey species they are best adapted to lead to a strong increase in species number but have only a small effect on the number and relative occupancy of trophic levels. The density of active links also remains small but a high number of potential links allows the network to adjust to changes in the species composition (emergence and extinction of species). Incorporating effects of body size on individual metabolism leads to a more complex trophic level structure: both the maximum and the average trophic level increase. So does the density of active links. Taking body size effects into consideration does not have a measurable influence on species richness. If species are allowed to adjust their foraging behaviour, the complexity of the evolving networks can also be influenced by the size of the external resources. The larger the resources, the larger and more complex is the food web it can sustain. Body size effects and increasing resources do not change size and the simple structure of the evolving networks if adaptive foraging is prohibited. This leads to the conclusion that in the framework of the niche model adaptive foraging is a necessary but not sufficient condition for the emergence of complex networks. It is found that despite the stabilising effect of foraging adaptation the system displays elements of self-organised critical behaviour.     

A three-species model explaining cyclic dominance of Pacific salmon

The four-year oscillations of the number of spawning sockeye salmon (Oncorhynchus nerka) that return to their native stream within the Fraser River basin in Canada are a striking example of population oscillations. The period of the oscillation corresponds to the dominant generation time of these fish. Various—not fully convincing—explanations for these oscillations have been proposed, including stochastic influences, depensatory fishing, or genetic effects. Here, we show that the oscillations can be explained as an attractor of the population dynamics, resulting from a strong resonance near a Neimark Sacker bifurcation. This explains not only the long-term persistence of these oscillations, but also reproduces correctly the empirical sequence of salmon abundance within one period of the oscillations. Furthermore, it explains the observation that these oscillations occur only in sockeye stocks originating from large oligotrophic lakes, and that they are usually not observed in salmon species that have a longer generation time.     

Tangled Bank dismissed too early

The Tangled Bank hypothesis has been one of the main theories to explain why most organisms reproduce sexually. It was most forcefully defended by Bell, who argued that genetically diverse offspring are able to extract more food from their environment than genetically identical clones. Due to the limited applicability of mathematical models and a lack of evidence that more sib‐competition leads to a larger advantage of sexual reproduction, the Tangled Bank hypothesis has since been abandoned by many authors in favor of the Red Queen hypothesis, which focuses on temporal environmental variation instead of spatial variation. Here, we argue that the rejection of the Tangled Bank hypothesis is based on a lack of appreciation of the importance of resources for determining the mode of reproduction, of the fundamental difference between the role of resources and the role of abiotic conditions, and of the negative feedback between resource consumption and resource availability. This negative feedback in fact leads to an ongoing temporal change in resource usage and thus connects the Tangled Bank concept to the Red Queen concept. We discuss recently introduced models that implement these ideas, and we suggest empirical studies on the relation between invasibility and genetic diversity of communities in order to test the Tangled Bank hypothesis more thoroughly.     

Combined deletion 18q22.2 and duplication/triplication 18q22.1 causes microcephaly,mental retardation and leukencephalopathy

Chromosome 18 abnormalities rank among the most common autosomal anomalies with 18q being the most frequently affected. A deletion of 18q has been attributed to microcephaly, mental retardation, short stature, facial dysmorphism, myelination disorders, limb and genitourinary malformations and congenital aural atresia. On the other hand, duplications of 18q have been associated with the phenotype of Edwards syndrome. Critical chromosomal regions for both phenotypes are contentious. In this report, we describe the first case of an 11-year old male with a combined interstitial duplication 18q22.1, triplication 18q22.1q22.2 and terminal deletion 18q22.2q23 with phenotypic features of isolated 18q deletion syndrome and absence of phenotypic features characteristic of Edwards syndrome despite duplication of the suggested critical region. This report allows for reevaluation of proposed critical intervals for the phenotypes in deletion 18q syndrome and Edwards syndrome.