Weighted Shape-based Averaging with Neighborhood Prior Model for Multiple Atlas Fusion-based Medical Image Segmentation

In medical imaging, merging automated segmentations obtained from multiple atlases has become a standard practice for improving the accuracy. In this letter, we propose two new fusion methods: "Global Weighted Shape-Based Averaging" (GWSBA) and "Local Weighted Shape-Based Averaging" (LWSBA). These methods extend the well known Shape-Based Averaging (SBA) by additionally incorporating the similarity information between the reference (i.e., atlas) images and the target image to be segmented. We also propose a new spatially-varying similarity-weighted neighborhood prior model, and an edge-preserving smoothness term that can be used with many of the existing fusion methods. We first present our new Markov Random Field (MRF) based fusion framework that models the above mentioned information. The proposed methods are evaluated in the context of segmentation of lymph nodes in the head and neck 3D CT images, and they resulted in more accurate segmentations compared to the existing SBA.

Sex-biased dispersal in a migratory bat: a characterization using sex-specific demographic parameters.

We studied the noctule bat (Nyctalus noctula), in which the mitochondrial F(ST) is about 10 times that revealed by nuclear markers, to address two questions. We first verified whether random dispersal of one sex is compatible with highly contrasted mitochondrial and nuclear population structures. Using computer simulations, we then assessed the power of multilocus population differentiation tests when the expected population structure departs only slightly from panmixia. Using an island model with sex-specific demographic parameters, we found that random male dispersal is consistent with the population structure observed in the noctule. However, other parameter combinations are also compatible with the data. We computed the minimum sex bias in dispersal (at least 69% of the dispersing individuals are males), a result that would not be available if we had used more classical population genetic models. The power of multilocus population differentiation tests was unexpectedly high, the tests being significant in almost 100% of the replicates, although the observed population structure infered from nuclear markers was extremely low (F(ST) = 0.6%).

A generalized mechanistic codon model.

Models of codon evolution have attracted particular interest because of their unique capabilities to detect selection forces and their high fit when applied to sequence evolution. We described here a novel approach for modeling codon evolution, which is based on Kronecker product of matrices. The 61 × 61 codon substitution rate matrix is created using Kronecker product of three 4 × 4 nucleotide substitution matrices, the equilibrium frequency of codons, and the selection rate parameter. The entities of the nucleotide substitution matrices and selection rate are considered as parameters of the model, which are optimized by maximum likelihood. Our fully mechanistic model allows the instantaneous substitution matrix between codons to be fully estimated with only 19 parameters instead of 3,721, by using the biological interdependence existing between positions within codons. We illustrate the properties of our models using computer simulations and assessed its relevance by comparing the AICc measures of our model and other models of codon evolution on simulations and a large range of empirical data sets. We show that our model fits most biological data better compared with the current codon models. Furthermore, the parameters in our model can be interpreted in a similar way as the exchangeability rates found in empirical codon models.

Flow-R, a model for susceptibility mapping of debris flows and other gravitational hazards at a regional scale

The development of susceptibility maps for debris flows is of primary importance due to population pressure in hazardous zones. However, hazard assessment by processbased modelling at a regional scale is difficult due to the complex nature of the phenomenon, the variability of local controlling factors, and the uncertainty in modelling parameters. A regional assessment must consider a simplified approach that is not highly parameter dependant and that can provide zonation with minimum data requirements. A distributed empirical model has thus been developed for regional susceptibility assessments using essentially a digital elevation model (DEM). The model is called Flow-R for Flow path assessment of gravitational hazards at a Regional scale (available free of charge under www.flow-r.org) and has been successfully applied to different case studies in various countries with variable data quality. It provides a substantial basis for a preliminary susceptibility assessment at a regional scale. The model was also found relevant to assess other natural hazards such as rockfall, snow avalanches and floods. The model allows for automatic source area delineation, given user criteria, and for the assessment of the propagation extent based on various spreading algorithms and simple frictional laws.We developed a new spreading algorithm, an improved version of Holmgren's direction algorithm, that is less sensitive to small variations of the DEM and that is avoiding over-channelization, and so produces more realistic extents. The choices of the datasets and the algorithms are open to the user, which makes it compliant for various applications and dataset availability. Amongst the possible datasets, the DEM is the only one that is really needed for both the source area delineation and the propagation assessment; its quality is of major importance for the results accuracy. We consider a 10m DEM resolution as a good compromise between processing time and quality of results. However, valuable results have still been obtained on the basis of lower quality DEMs with 25m resolution.

Randomized observation periods for the compound Poisson risk model: Dividends

In the framework of the classical compound Poisson process in collective risk theory, we study a modification of the horizontal dividend barrier strategy by introducing random observation times at which dividends can be paid and ruin can be observed. This model contains both the continuous-time and the discrete-time risk model as a limit and represents a certain type of bridge between them which still enables the explicit calculation of moments of total discounted dividend payments until ruin. Numerical illustrations for several sets of parameters are given and the effect of random observation times on the performance of the dividend strategy is studied.

A double layer model of the gas bubble/water interface

Zeta potential is a physico-chemical parameter of particular importance to describe sorption of contaminants at the surface of gas bubbles. Nevertheless, the interpretation of electrophoretic mobilities of gas bubbles is complex. This is due to the specific behavior of the gas at interface and to the excess of electrical charge at interface, which is responsible for surface conductivity. We developed a surface complexation model based on the presence of negative surface sites because the balance of accepting and donating hydrogen bonds is broken at interface. By considering protons adsorbed on these sites followed by a diffuse layer, the electrical potential at the head-end of the diffuse layer is computed and considered to be equal to the zeta potential. The predicted zeta potential values are in very good agreement with the experimental data of H-2 bubbles for a broad range of pH and NaCl concentrations. This implies that the shear plane is located at the head-end of the diffuse layer, contradicting the assumption of the presence of a stagnant diffuse layer at the gas/water interface. Our model also successfully predicts the surface tension of air bubbles in a KCl solution. (c) 2012 Elsevier Inc. All rights reserved.

The influence of Bone Morphogenic Protein-2 on the consolidation phase in a distraction osteogenesis model.

We asked whether locally applied recombinant-Bone Morphogenic Protein-2 (rh-BMP-2) with an absorbable Type I collagen sponge (ACS) carrier could enhance the consolidation phase in a callotasis model. We performed unilateral transverse osteotomy of the tibia in 21 immature male rabbits. After a latency period of 7 days, a 3-weeks distraction was begun at a rate of 0.5mm/12h. At the end of the distraction period (Day 28) animals were randomly divided into three groups and underwent a second surgical procedure: 6 rabbits in Group I (Control group; the callus was exposed and nothing was added), 6 rabbits in Group II (ACS group; receiving the absorbable collagen sponge soaked with saline) and 9 rabbits in Group III (rh-BMP-2/ACS group; receiving the ACS soaked with 100μg/kg of rh-BMP-2, Inductos(®), Medtronic). Starting at Day 28 we assessed quantitative and qualitative radiographic parameters as well as densitometric parameters every two weeks (Days 28, 42, 56, 70 and 84). Animals were sacrificed after 8 weeks of consolidation (Day 84). Qualitative radiographic evaluation revealed hypertrophic calluses in the Group III animals. The rh-BMP-2/ACS also influenced the development of the cortex of the calluses as shown by the modified radiographic patterns in Group III when compared to Groups I and II. Densitometric analysis revealed the bone mineral content (BMC) was significantly higher in the rh-BMP-2/ACS treated animals (Group III).

Detection of Optimal Models in Parameter Space with Support Vector Machines

The paper proposes an approach aimed at detecting optimal model parameter combinations to achieve the most representative description of uncertainty in the model performance. A classification problem is posed to find the regions of good fitting models according to the values of a cost function. Support Vector Machine (SVM) classification in the parameter space is applied to decide if a forward model simulation is to be computed for a particular generated model. SVM is particularly designed to tackle classification problems in high-dimensional space in a non-parametric and non-linear way. SVM decision boundaries determine the regions that are subject to the largest uncertainty in the cost function classification, and, therefore, provide guidelines for further iterative exploration of the model space. The proposed approach is illustrated by a synthetic example of fluid flow through porous media, which features highly variable response due to the parameter values' combination.

Effects of rat anti-VEGF antibody in a rat model of corneal graft rejection by topical and subconjunctival routes.

PURPOSE: To compare the effect of a rat anti-VEGF antibody, administered either by topical or subconjunctival (SC) routes, on a rat model of corneal transplant rejection.METHODS: Twenty-four rats underwent corneal transplantation and were randomized into four treatment groups (n=6 in each group). G1 and G2 received six SC injections (0.02 ml 10 µg/ml) of denatured (G1) or active (G2) anti-VEGF from Day 0 to Day 21 every third day. G3 and G4 were instilled three times a day with denatured (G3) or active (G4) anti-VEGF drops (10 µg/ml) from Day 0 to Day 21. Corneal mean clinical scores (MCSs) of edema (E), transparency (T), and neovessels (nv) were recorded at Days 3, 9, 15, and 21. Quantification of neovessels was performed after lectin staining of vessels on flat mounted corneas.RESULTS: Twenty-one days after surgery, MCSs differed significantly between G1 and G2, but not between G3 and G4, and the rejection rate was significantly reduced in rats receiving active antibodies regardless of the route of administration (G2=50%, G4=66.65% versus G1 and G3=100%; p<0.05). The mean surfaces of neovessels were significantly reduced in groups treated with active anti-VEGF (G2, G4). However, anti-VEGF therapy did not completely suppress corneal neovessels.CONCLUSIONS: Specific rat anti-VEGF antibodies significantly reduced neovascularization and subsequent corneal graft rejection. The SC administration of the anti-VEGF antibody was more effective than topical instillation.

A dynamic model for stem cell homeostasis and patterning in Arabidopsis meristems.

Plants maintain stem cells in their meristems as a source for new undifferentiated cells throughout their life. Meristems are small groups of cells that provide the microenvironment that allows stem cells to prosper. Homeostasis of a stem cell domain within a growing meristem is achieved by signalling between stem cells and surrounding cells. We have here simulated the origin and maintenance of a defined stem cell domain at the tip of Arabidopsis shoot meristems, based on the assumption that meristems are self-organizing systems. The model comprises two coupled feedback regulated genetic systems that control stem cell behaviour. Using a minimal set of spatial parameters, the mathematical model allows to predict the generation, shape and size of the stem cell domain, and the underlying organizing centre. We use the model to explore the parameter space that allows stem cell maintenance, and to simulate the consequences of mutations, gene misexpression and cell ablations.

A coherent neurobiological framework for functional neuroimaging provided by a model integrating compartmentalized energy metabolism.

Functional neuroimaging has undergone spectacular developments in recent years. Paradoxically, its neurobiological bases have remained elusive, resulting in an intense debate around the cellular mechanisms taking place upon activation that could contribute to the signals measured. Taking advantage of a modeling approach, we propose here a coherent neurobiological framework that not only explains several in vitro and in vivo observations but also provides a physiological basis to interpret imaging signals. First, based on a model of compartmentalized energy metabolism, we show that complex kinetics of NADH changes observed in vitro can be accounted for by distinct metabolic responses in two cell populations reminiscent of neurons and astrocytes. Second, extended application of the model to an in vivo situation allowed us to reproduce the evolution of intraparenchymal oxygen levels upon activation as measured experimentally without substantially altering the initial parameter values. Finally, applying the same model to functional neuroimaging in humans, we were able to determine that the early negative component of the blood oxygenation level-dependent response recorded with functional MRI, known as the initial dip, critically depends on the oxidative response of neurons, whereas the late aspects of the signal correspond to a combination of responses from cell types with two distinct metabolic profiles that could be neurons and astrocytes. In summary, our results, obtained with such a modeling approach, support the concept that both neuronal and glial metabolic responses form essential components of neuroimaging signals.

Tc-99m-MAA SPECT-derived tumor-to-normal liver ratios for partition model dosimetry in selective internal radiation therapy (SIRT)

Aim: When planning SIRT using 90Y microspheres, the partition model is used to refine the activity calculated by the body surface area (BSA) method to potentially improve the safety and efficacy of treatment. For this partition model dosimetry, accurate determination of mean tumor-to-normal liver ratio (TNR) is critical since it directly impacts absorbed dose estimates. This work aimed at developing and assessing a reliable methodology for the calculation of 99mTc-MAA SPECT/CT-derived TNR ratios based on phantom studies. Materials and methods: IQ NEMA (6 hot spheres) and Kyoto liver phantoms with different hot/background activity concentration ratios were imaged on a SPECT/CT (GE Infinia Hawkeye 4). For each reconstruction with the IQ phantom, TNR quantification was assessed in terms of relative recovery coefficients (RC) and image noise was evaluated in terms of coefficient of variation (COV) in the filled background. RCs were compared using OSEM with Hann, Butterworth and Gaussian filters, as well as FBP reconstruction algorithms. Regarding OSEM, RCs were assessed by varying different parameters independently, such as the number of iterations (i) and subsets (s) and the cut-off frequency of the filter (fc). The influence of the attenuation and diffusion corrections was also investigated. Furthermore, both 2D-ROIs and 3D-VOIs contouring were compared. For this purpose, dedicated Matlab© routines were developed in-house for automatic 2D-ROI/3D-VOI determination to reduce intra-user and intra-slice variability. Best reconstruction parameters and RCs obtained with the IQ phantom were used to recover corrected TNR in case of the Kyoto phantom for arbitrary hot-lesion size. In addition, we computed TNR volume histograms to better assess uptake heterogeneityResults: The highest RCs were obtained with OSEM (i=2, s=10) coupled with the Butterworth filter (fc=0.8). Indeed, we observed a global 20% RC improvement over other OSEM settings and a 50% increase as compared to the best FBP reconstruction. In any case, both attenuation and diffusion corrections must be applied, thus improving RC while preserving good image noise (COV<10%). Both 2D-ROI and 3D-VOI analysis lead to similar results. Nevertheless, we recommend using 3D-VOI since tumor uptake regions are intrinsically 3D. RC-corrected TNR values lie within 17% around the true value, substantially improving the evaluation of small volume (<15 mL) regions. Conclusions: This study reports the multi-parameter optimization of 99mTc MAA SPECT/CT images reconstruction in planning 90Y dosimetry for SIRT. In phantoms, accurate quantification of TNR was obtained using OSEM coupled with Butterworth and RC correction.

Measurement Errors Should Always Be Incorporated in Phylogenetic Comparative Analysis

The evolution of continuous traits is the central component of comparative analyses in phylogenetics, and the comparison of alternative models of trait evolution has greatly improved our understanding of the mechanisms driving phenotypic differentiation. Several factors influence the comparison of models, and we explore the effects of random errors in trait measurement on the accuracy of model selection. We simulate trait data under a Brownian motion model (BM) and introduce different magnitudes of random measurement error. We then evaluate the resulting statistical support for this model against two alternative models: Ornstein-Uhlenbeck (OU) and accelerating/decelerating rates (ACDC). Our analyses show that even small measurement errors (10%) consistently bias model selection towards erroneous rejection of BM in favour of more parameter-rich models (most frequently the OU model). Fortunately, methods that explicitly incorporate measurement errors in phylogenetic analyses considerably improve the accuracy of model selection. Our results call for caution in interpreting the results of model selection in comparative analyses, especially when complex models garner only modest additional support. Importantly, as measurement errors occur in most trait data sets, we suggest that estimation of measurement errors should always be performed during comparative analysis to reduce chances of misidentification of evolutionary processes.

The ability model of emotional intelligence: Searching for valid measures

Current measures of ability emotional intelligence (EI)--including the well-known Mayer-Salovey-Caruso Emotional Intelligence Test (MSCEIT)--suffer from several limitations, including low discriminant validity and questionable construct and incremental validity. We show that the MSCEIT is largely predicted by personality dimensions, general intelligence, and demographics having multiple R's with the MSCEIT branches up to .66; for the general EI factor this relation was even stronger (Multiple R = .76). As concerns the factor structure of the MSCEIT, we found support for four first-order factors, which had differential relations with personality, but no support for a higher-order global EI factor. We discuss implications for employing the MSCEIT, including (a) using the single branches scores rather than the total score, (b) always controlling for personality and general intelligence to ensure unbiased parameter estimates in the EI factors, and (c) correcting for measurement error. Failure to account for these methodological aspects may severely compromise predictive validity testing. We also discuss avenues for the improvement of ability-based tests.

Interleukin-17 is a critical mediator of vaccine-induced reduction of Helicobacter infection in the mouse model.

BACKGROUND &amp; AIMS: Despite the proven ability of immunization to reduce Helicobacter infection in mouse models, the precise mechanism of protection has remained elusive. This study explores the possibility that interleukin (IL)-17 plays a role in the reduction of Helicobacter infection following vaccination of wild-type animals or in spontaneous reduction of bacterial infection in IL-10-deficient mice. METHODS: In mice, reducing Helicobacter infection, the levels and source of IL-17 were determined and the role of IL-17 in reduction of Helicobacter infection was probed by neutralizing antibodies. RESULTS: Gastric IL-17 levels were strongly increased in mice mucosally immunized with urease plus cholera toxin and challenged with Helicobacter felis as compared with controls (654 +/- 455 and 34 +/- 84 relative units for IL-17 messenger RNA expression [P &lt; .01] and 6.9 +/- 8.4 and 0.02 +/- 0.04 pg for IL-17 protein concentration [P &lt; .01], respectively). Flow cytometry analysis showed that a peak of CD4(+)IL-17(+) T cells infiltrating the gastric mucosa occurred in immunized mice in contrast to control mice (4.7% +/- 0.3% and 1.4% +/- 0.3% [P &lt; .01], respectively). Gastric mucosa-infiltrating CD4(+)IL-17(+) T cells were also observed in IL-10-deficient mice that spontaneously reduced H felis infection (4.3% +/- 2.3% and 2% +/- 0.6% [P &lt; .01], for infected and noninfected IL-10-deficient mice, respectively). In wild-type immunized mice, intraperitoneal injection of anti-IL-17 antibodies significantly inhibited inflammation and the reduction of Helicobacter infection in comparison with control antibodies (1 of 12 mice vs 9 of 12 mice reduced Helicobacter infection [P &lt; .01], respectively). CONCLUSIONS: IL-17 plays a critical role in the immunization-induced reduction of Helicobacter infection from the gastric mucosa.