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).     

Plasmodium relictum (lineage SGS1) and Plasmodium ashfordi (lineage GRW2): the effects of the co-infection on experimentally infected passerine birds

The effects of avian malaria parasites of the genus Plasmodium on their hosts are insufficiently understood. This is particularly true for malarial co-infections, which predominant in many bird populations. We investigated effects of primary co-infection of Plasmodium relictum (lineage SGS1) and Plasmodium ashfordi (GRW2) on experimentally infected naive juveniles of siskin Spinus spinus, crossbill Loxia curvirostra and starling Sturnus vulgaris. All siskins and crossbills were susceptible but starlings resistant to both these infections. A general pattern of the co-infections was that heavy parasitemia (over 35% during peaks) of both parasites developed in both susceptible host species. There were no significant effects of the co-infections on mean body mass of the majority of infected birds. Mean haematocrit value decreased approximately 1.5 and 3 times in siskins and crossbills at the peak of parasitemia, respectively. Mortality was recorded among infected crossbills. We conclude that co-infections of P. relictum and P. ashfordi are highly virulent and act synergetically during primary infections in some but not all passerine birds.     

Docking and scoring with alternative side-chain conformations

We describe a scoring and modeling procedure for docking ligands into protein models that have either modeled or flexible side-chain conformations. Our methodical contribution comprises a procedure for generating new potentials of mean force for the ROTA scoring function which we have introduced previously for optimizing side-chain conformations with the tool IRECS. The ROTA potentials are specially trained to tolerate small-scale positional errors of atoms that are characteristic of (i) side-chain conformations that are modeled using a sparse rotamer library and (ii) ligand conformations that are generated using a docking program. We generated both rigid and flexible protein models with our side-chain prediction tool IRECS and docked ligands to proteins using the scoring function ROTA and the docking programs FlexX (for rigid side chains) and FlexE (for flexible side chains). We validated our approach on the forty screening targets of the DUD database. The validation shows that the ROTA potentials are especially well suited for estimating the binding affinity of ligands to proteins. The results also show that our procedure can compensate for the performance decrease in screening that occurs when using protein models with side chains modeled with a rotamer library instead of using X-ray structures. The average runtime per ligand of our method is 168 seconds on an Opteron V20z, which is fast enough to allow virtual screening of compound libraries for drug candidates.     

Heterocyst patterns without patterning proteins in cyanobacterial filaments

We have quantitatively modeled heterocyst differentiation after fixed nitrogen step-down in the filamentous cyanobacterium Anabaena sp. PCC 7120 without lateral inhibition due to the patterning proteins PatS or HetN. We use cell growth and division together with fixed-nitrogen dynamics and allow heterocysts to differentiate upon the local exhaustion of available fixed nitrogen. Slow transport of fixed nitrogen along a shared periplasmic space allows for fast growing cells to differentiate ahead of their neighbors. Cell-to-cell variability in growth rate determines the initial heterocyst pattern. Early release of fixed nitrogen from committed heterocysts allows a significant fraction of vegetative cells to be retained at later times. We recover the experimental heterocyst spacing distributions and cluster size distributions of Khudyakov and Golden [Khudyakov, I.Y., Golden, J.W., 2004. Different functions of HetR, a master regulator of heterocyst differentiation in Anabaena sp PCC 7120, can be separated by mutation. Proc. Natl. Acad. Sci. U. S. A. 101, 16040-16045].     

Investigation of PDE5/PDE6 and PDE5/PDE11 selective potent tadalafil-like PDE5 inhibitors using combination of molecular modeling approaches,molecular fingerprint-based virtual screening protocols and structure-based pharmacophore development

The essential biological function of phosphodiesterase (PDE) type enzymes is to regulate the cytoplasmic levels of intracellular second messengers, 3′,5′-cyclic guanosine monophosphate (cGMP) and/or 3′,5′-cyclic adenosine monophosphate (cAMP). PDE targets have 11 isoenzymes. Of these enzymes, PDE5 has attracted a special attention over the years after its recognition as being the target enzyme in treating erectile dysfunction. Due to the amino acid sequence and the secondary structural similarity of PDE6 and PDE11 with the catalytic domain of PDE5, first-generation PDE5 inhibitors (i.e. sildenafil and vardenafil) are also competitive inhibitors of PDE6 and PDE11. Since the major challenge of designing novel PDE5 inhibitors is to decrease their cross-reactivity with PDE6 and PDE11, in this study, we attempt to identify potent tadalafil-like PDE5 inhibitors that have PDE5/PDE6 and PDE5/PDE11 selectivity. For this aim, the similarity-based virtual screening protocol is applied for the “clean drug-like subset of ZINC database” that contains more than 20 million small compounds. Moreover, molecular dynamics (MD) simulations of selected hits complexed with PDE5 and off-targets were performed in order to get insights for structural and dynamical behaviors of the selected molecules as selective PDE5 inhibitors. Since tadalafil blocks hERG1 K channels in concentration dependent manner, the cardiotoxicity prediction of the hit molecules was also tested. Results of this study can be useful for designing of novel, safe and selective PDE5 inhibitors.     

Modeling changes in soil organic matter in Amazon forest to pasture conversion with the Century model

Land use and land cover changes in the Brazilian Amazon region have major implications for regional and even global carbon cycling. We analyzed the effects of the predominant land use change, conversion of tropical forest to pasture, on total soil C and N, using the Century ecosystem model and data collected from the Nova Vida ranch, Western Brazilian Amazon. We estimated equilibrium organic matter levels, plant productivity and residue carbon inputs under native forest conditions, then simulated deforestation following the slash and burn procedure. Soil organic matter dynamics were simulated for pastures established in 1989, 1987, 1983, 1979, 1972, 1951, and 1911. Using input data from the Nova Vida ranch, the Century model predicted that forest clearance and conversion to pasture would cause an initial decline in soil C and N stocks, followed by a slow rise to levels exceeding those under native forest. Simulated soil total C and N levels (2500 g C m^?2 and 245 g N m^?2 in the 0–20 cm layer) prior to conversion to pasture were close to those measured in the native forest. Simulated above‐ and below‐ground biomass for the forest and pasture were comparable with literature values from this region. The model predicted the long‐term changes in soil C and N under pasture inferred from the pasture chronosequence, but there was considerable variation in soil C stocks for pastures <20 years in age. Differences in soil texture between pastures were relatively small and could not account for much of the variability between different pastures of similar ages, in either the measured or simulated data. It is likely that much of the variability in C stocks between pastures of similar ages is related to initial C stocks immediately following deforestation and that this was the largest source of variability in the chronosequence. Internal C cycling processes in Century were evaluated using measurements of microbial biomass and soil δ¹³C. The relative magnitude and long‐term trend in microbial biomass simulated by the model were consistent with measurements. The close fit of simulated to measured values of δ¹³C over time suggests that the relative loss of forest‐derived C and its replacement by pasture‐derived C was accurately predicted by the model. After 80 years, almost 90% of the organic matter in the top 20 cm was pasture derived. While our analysis represents a single ‘case study’ of pasture conversion, our results suggest that modeling studies in these pasture systems can help to evaluate the magnitude of impacts on C and N cycling, and determine the effect of management strategies on pasture sustainability.     

Phytomass change in natural phytocenosis as an indicator of technogenic pollution of soils with heavy metals

This study considered the possibility of using plant community phytomass for the assessment of soil pollution with heavy metals (HM) from industrial wastes. The three-year-long field experiment was run under the regional natural meadow vegetation; the polymetallic galvanic slime was used as an industrial waste contaminant. It is shown that soil contamination primarily causes decrease of phytomass in the growing phytocenosis. The vegetation experiments determined nonlinear dependence of cultivated and wild plant biomass on the level of soil contamination; it is described by the equations of logistic and Gaussian regression. In the absence of permanent contaminants, the soil is self-cleaned over time. It reproduces phytomass mainly due to the productivity increase of the most pollution-tolerant species in the remaining phytocenosis. This phenomenon is defined as environmental hysteresis. Soil pollution by industrial waste leads to the loss of plant biodiversity. The research shows that the study of the HM impact on ecosystems is expedient given the consideration of the “soil–phytocenosis–pollutant” complex in the “dose–response” aspect. The reaction of phytocenosis on HM showing decline in phytomass leads to serious limitations in the choice of accumulating plants, because the adsorbed HM are rejected through phytomass.     

Thermal biology of flight in a butterfly: genotype,flight metabolism,and environmental conditions

Knowledge of the effects of thermal conditions on animal movement and dispersal is necessary for a mechanistic understanding of the consequences of climate change and habitat fragmentation. In particular, the flight of ectothermic insects such as small butterflies is greatly influenced by ambient temperature. Here, variation in body temperature during flight is investigated in an ecological model species, the Glanville fritillary butterfly (Melitaea cinxia). Attention is paid on the effects of flight metabolism, genotypes at candidate loci, and environmental conditions. Measurements were made under a natural range of conditions using infrared thermal imaging. Heating of flight muscles by flight metabolism has been presumed to be negligible in small butterflies. However, the results demonstrate that Glanville fritillary males with high flight metabolic rate maintain elevated body temperature better during flight than males with a low rate of flight metabolism. This effect is likely to have a significant influence on the dispersal performance and fitness of butterflies and demonstrates the possible importance of intraspecific physiological variation on dispersal in other similar ectothermic insects. The results also suggest that individuals having an advantage in low ambient temperatures can be susceptible to overheating at high temperatures. Further, tolerance of high temperatures may be important for flight performance, as indicated by an association of heat‐shock protein (Hsp70) genotype with flight metabolic rate and body temperature at takeoff. The dynamics of body temperature at flight and factors affecting it also differed significantly between female and male butterflies, indicating that thermal dynamics are governed by different mechanisms in the two sexes. This study contributes to knowledge about factors affecting intraspecific variation in dispersal‐related thermal performance in butterflies and other insects. Such information is needed for predictive models of the evolution of dispersal in the face of habitat fragmentation and climate change.     

Modeling the precision and robustness of Hunchback border during Drosophila embryonic development

During anterior-posterior axis specification in the Drosophila embryo, the Hunchback (Hb) protein forms a sharp boundary at the mid-point of the embryo with great positional precision. While Bicoid (Bcd) is a known upstream regulator for hb expression, there is evidence to suggest that Hb effectively filters out “noisy” data received from varied Bcd gradients. We use mathematical models to explore simple regulatory networks which filter out such noise to produce a precise Hb boundary. We find that in addition to Bcd and Hb, at least one freely evolving protein is necessary. An automated search yields a number of examples of three-protein networks exhibiting the desired precision. In all such networks, Hb diffuses much slower than the third protein. In addition, the action of Hb on the third protein is the opposite of the action of the third protein on hb (i.e. if Hb activates the third protein, then the third protein inhibits hb expression, and vice versa). Most of the discovered systems satisfy the known biological properties, that Bcd activates hb, and that Hb activates its own expression. We find that all network topologies satisfying these constraints arise among the networks exhibiting the desired precision. Investigating the dynamics of these networks, we find that under a general class of non-uniform initial conditions, Bcd can be eliminated from the system and the spatiotemporal evolution of these two proteins alone is sufficient to recapture the dynamics. We hypothesize that Bcd is needed only to spatially disturb the gradient of the third protein, and then becomes unnecessary in the further evolution of the Hb border. This provides a possible explanation as to why the Hb dynamics are robust under perturbations of the Bcd gradient. Under this hypothesis, other proteins would be able to assume the role of Bcd in our simulations (possibly in the case of evolutionary divergences or a redundancy in the process), with the only constraint that they act to positively regulate hb.     

Computational study of the putative active form of protein Z (PZa): sequence design and structural modeling

Although protein Z (PZ) has a domain arrangement similar to the essential coagulation proteins FVII, FIX, FX, and protein C, its serine protease (SP)-like domain is incomplete and does not exhibit proteolytic activity. We have generated a trial sequence of putative activated protein Z (PZa) by identifying amino acid mutations in the SP-like domain that might reasonably resurrect the serine protease catalytic activity of PZ. The structure of the activated form was then modeled based on the proposed sequence using homology modeling and solvent-equilibrated molecular dynamics simulations. In silico docking of inhibitors of FVIIa and FXa to the putative active site of equilibrated PZa, along with structural comparison with its homologous proteins, suggest that the designed PZa can possibly act as a serine protease.