Infectivity of Lactobacillus rhamnosus and Lactobacillus paracasei isolates in a rat model of experimental endocarditis.

The potential pathogenicity of selected (potentially) probiotic and clinical isolates of Lactobacillus rhamnosus and Lactobacillus paracasei was investigated in a rat model of experimental endocarditis. In addition, adhesion properties of the lactobacilli for fibrinogen, fibronectin, collagen and laminin, as well as the killing activity of the platelet-microbicidal proteins fibrinopeptide A (FP-A) and connective tissue activating peptide 3 (CTAP-3), were assessed. The 90 % infective dose (ID(90)) of the L. rhamnosus endocarditis isolates varied between 10(6) and 10(7) c.f.u., whereas four of the six (potentially) probiotic L. rhamnosus isolates showed an ID(90) that was at least 10-fold higher (10(8) c.f.u.) (P<0.001). In contrast, the two other probiotic L. rhamnosus isolates exhibited an ID(90) (10(6) and 10(7) c.f.u.) comparable to the ID(90) of the clinical isolates of this species investigated (P>0.05). Importantly, these two probiotic isolates shared the same fluorescent amplified fragment length polymorphism cluster type as the clinical isolate showing the lowest ID(90) (10(6) c.f.u.). L. paracasei tended to have a lower infectivity than L. rhamnosus (ID(90) of 10(7) to > or =10(8) c.f.u.). All isolates had comparable bacterial counts in cardiac vegetations (P>0.05). Except for one L. paracasei strain adhering to all substrates, all tested lactobacilli adhered only weakly or not at all. The platelet peptide FP-A did not show any microbicidal activity against the tested lactobacilli, whereas CTAP-3 killed the majority of the isolates. In general, these results indicate that probiotic lactobacilli display a lower infectivity in experimental endocarditis compared with true endocarditis pathogens. However, the difference in infectivity between L. rhamnosus endocarditis and (potentially) probiotic isolates could not be explained by differences in adherence or platelet microbicidal protein susceptibility. Other disease-promoting factors may exist in these organisms and warrant further investigation.

Extension of Murray's law using a non-Newtonian model of blood flow.

BACKGROUND: So far, none of the existing methods on Murray's law deal with the non-Newtonian behavior of blood flow although the non-Newtonian approach for blood flow modelling looks more accurate. MODELING: In the present paper, Murray's law which is applicable to an arterial bifurcation, is generalized to a non-Newtonian blood flow model (power-law model). When the vessel size reaches the capillary limitation, blood can be modeled using a non-Newtonian constitutive equation. It is assumed two different constraints in addition to the pumping power: the volume constraint or the surface constraint (related to the internal surface of the vessel). For a seek of generality, the relationships are given for an arbitrary number of daughter vessels. It is shown that for a cost function including the volume constraint, classical Murray's law remains valid (i.e. SigmaR(c) = cste with c = 3 is verified and is independent of n, the dimensionless index in the viscosity equation; R being the radius of the vessel). On the contrary, for a cost function including the surface constraint, different values of c may be calculated depending on the value of n. RESULTS: We find that c varies for blood from 2.42 to 3 depending on the constraint and the fluid properties. For the Newtonian model, the surface constraint leads to c = 2.5. The cost function (based on the surface constraint) can be related to entropy generation, by dividing it by the temperature. CONCLUSION: It is demonstrated that the entropy generated in all the daughter vessels is greater than the entropy generated in the parent vessel. Furthermore, it is shown that the difference of entropy generation between the parent and daughter vessels is smaller for a non-Newtonian fluid than for a Newtonian fluid.

Respiratory failure in a mouse model of myotonic dystrophy does not correlate with the CTG repeat length.

Myotonic dystrophy (DM1) is a multisystemic disease caused by an expansion of CTG repeats in the region of DMPK, the gene encoding DM protein kinase. The severity of muscle disability in DM1 correlates with the size of CTG expansion. As respiratory failure is one of the main causes of death in DM1, we investigated the correlation between respiratory impairment and size of the (CTG)n repeat in DM1 animal models. Using pressure plethysmography the respiratory function was assessed in control and transgenic mice carrying either 600 (DM600) or >1300 CTG repeats (DMSXL). The statistical analysis of respiratory parameters revealed that both DM1 transgenic mice sub-lines show respiratory impairment compared to control mice. In addition, there is no significant difference in breathing functions between the DM600 and DMSXL mice. In conclusion, these results indicate that respiratory impairment is present in both transgenic mice sub-lines, but the severity of respiratory failure is not related to the size of the (CTG)n expansion.

An active strain electromechanical model for cardiac tissue

We propose a finite element approximation of a system of partial differential equations describing the coupling between the propagation of electrical potential and large deformations of the cardiac tissue. The underlying mathematical model is based on the active strain assumption, in which it is assumed that a multiplicative decomposition of the deformation tensor into a passive and active part holds, the latter carrying the information of the electrical potential propagation and anisotropy of the cardiac tissue into the equations of either incompressible or compressible nonlinear elasticity, governing the mechanical response of the biological material. In addition, by changing from an Eulerian to a Lagrangian configuration, the bidomain or monodomain equations modeling the evolution of the electrical propagation exhibit a nonlinear diffusion term. Piecewise quadratic finite elements are employed to approximate the displacements field, whereas for pressure, electrical potentials and ionic variables are approximated by piecewise linear elements. Various numerical tests performed with a parallel finite element code illustrate that the proposed model can capture some important features of the electromechanical coupling, and show that our numerical scheme is efficient and accurate.

A semi-grand canonical Monte Carlo simulation model for ion binding to ionizable surfaces: Proton binding of carboxylated latex particles as a case study

In this paper, we present a computer simulation study of the ion binding process at an ionizable surface using a semi-grand canonical Monte Carlo method that models the surface as a discrete distribution of charged and neutral functional groups in equilibrium with explicit ions modelled in the context of the primitive model. The parameters of the simulation model were tuned and checked by comparison with experimental titrations of carboxylated latex particles in the presence of different ionic strengths of monovalent ions. The titration of these particles was analysed by calculating the degree of dissociation of the latex functional groups vs. pH curves at different background salt concentrations. As the charge of the titrated surface changes during the simulation, a procedure to keep the electroneutrality of the system is required. Here, two approaches are used with the choice depending on the ion selected to maintain electroneutrality: counterion or coion procedures. We compare and discuss the difference between the procedures. The simulations also provided a microscopic description of the electrostatic double layer (EDL) structure as a function of pH and ionic strength. The results allow us to quantify the effect of the size of the background salt ions and of the surface functional groups on the degree of dissociation. The non-homogeneous structure of the EDL was revealed by plotting the counterion density profiles around charged and neutral surface functional groups. © 2011 American Institute of Physics.

Optimal capital structure: a trade-off model and its empirical testing

In the present research we have set forth a new, simple, Trade-Off model that would allow us to calculate how much debt and, by default, how much equity a company should have, using easily available information and calculating the cost of debt dynamically on the basis of the effect that the capital structure of the company has on the risk of bankruptcy; in an attempt to answer this question. The proposed model has been applied to the companies that make up the Dow Jones Industrial Average (DJIA) in 2007. We have used consolidated financial data from 1996 to 2006, published by Bloomberg. We have used simplex optimization method to find the debt level that maximizes firm value. Then, we compare the estimated debt with real debt of companies using statistical nonparametric Mann-Whitney. The results indicate that 63% of companies do not show a statistically significant difference between the real and the estimated debt.

Technical Note: Dissolved organic matter fluorescence a finite mixture approach to deconvolve excitation-emission matrices

The analysis of the shape of excitation-emission matrices (EEMs) is a relevant tool for exploring the origin, transport and fate of dissolved organic matter (DOM) in aquatic ecosystems. Within this context, the decomposition of EEMs is acquiring a notable relevance. A simple mathematical algorithm that automatically deconvolves individual EEMs is described, creating new possibilities for the comparison of DOM fluorescence properties and EEMs that are very different from each other. A mixture model approach is adopted to decompose complex surfaces into sub-peaks. The laplacian operator and the Nelder-Mead optimisation algorithm are implemented to individuate and automatically locate potential peaks in the EEM landscape. The EEMs of a simple artificial mixture of fluorophores and DOM samples collected in a Mediterranean river are used to describe the model application and to illustrate a strategy that optimises the search for the optimal output.

Neutron skin thickness in the droplet model with surface width dependence: Indications of softness of the nuclear symmetry energy

We analyze the neutron skin thickness in finite nuclei with the droplet model and effective nuclear interactions. The ratio of the bulk symmetry energy J to the so-called surface stiffness coefficient Q has in the droplet model a prominent role in driving the size of neutron skins. We present a correlation between the density derivative of the nuclear symmetry energy at saturation and the J/Q ratio. We emphasize the role of the surface widths of the neutron and proton density profiles in the calculation of the neutron skin thickness when one uses realistic mean-field effective interactions. Next, taking as experimental baseline the neutron skin sizes measured in 26 antiprotonic atoms along the mass table, we explore constraints arising from neutron skins on the value of the J/Q ratio. The results favor a relatively soft symmetry energy at subsaturation densities. Our predictions are compared with the recent constraints derived from other experimental observables. Though the various extractions predict different ranges of values, one finds a narrow window L∼45-75 MeV for the coefficient L that characterizes the density derivative of the symmetry energy that is compatible with all the different empirical indications.

Single breath-hold 3D measurement of left atrial volume using compressed sensing cardiovascular magnetic resonance and a non-model-based reconstruction approach.

BACKGROUND: Left atrial (LA) dilatation is associated with a large variety of cardiac diseases. Current cardiovascular magnetic resonance (CMR) strategies to measure LA volumes are based on multi-breath-hold multi-slice acquisitions, which are time-consuming and susceptible to misregistration. AIM: To develop a time-efficient single breath-hold 3D CMR acquisition and reconstruction method to precisely measure LA volumes and function. METHODS: A highly accelerated compressed-sensing multi-slice cine sequence (CS-cineCMR) was combined with a non-model-based 3D reconstruction method to measure LA volumes with high temporal and spatial resolution during a single breath-hold. This approach was validated in LA phantoms of different shapes and applied in 3 patients. In addition, the influence of slice orientations on accuracy was evaluated in the LA phantoms for the new approach in comparison with a conventional model-based biplane area-length reconstruction. As a reference in patients, a self-navigated high-resolution whole-heart 3D dataset (3D-HR-CMR) was acquired during mid-diastole to yield accurate LA volumes. RESULTS: Phantom studies. LA volumes were accurately measured by CS-cineCMR with a mean difference of -4.73 ± 1.75 ml (-8.67 ± 3.54%, r2 = 0.94). For the new method the calculated volumes were not significantly different when different orientations of the CS-cineCMR slices were applied to cover the LA phantoms. Long-axis "aligned" vs "not aligned" with the phantom long-axis yielded similar differences vs the reference volume (-4.87 ± 1.73 ml vs. -4.45 ± 1.97 ml, p = 0.67) and short-axis "perpendicular" vs. "not-perpendicular" with the LA long-axis (-4.72 ± 1.66 ml vs. -4.75 ± 2.13 ml; p = 0.98). The conventional bi-plane area-length method was susceptible for slice orientations (p = 0.0085 for the interaction of "slice orientation" and "reconstruction technique", 2-way ANOVA for repeated measures). To use the 3D-HR-CMR as the reference for LA volumes in patients, it was validated in the LA phantoms (mean difference: -1.37 ± 1.35 ml, -2.38 ± 2.44%, r2 = 0.97). Patient study: The CS-cineCMR LA volumes of the mid-diastolic frame matched closely with the reference LA volume (measured by 3D-HR-CMR) with a difference of -2.66 ± 6.5 ml (3.0% underestimation; true LA volumes: 63 ml, 62 ml, and 395 ml). Finally, a high intra- and inter-observer agreement for maximal and minimal LA volume measurement is also shown. CONCLUSIONS: The proposed method combines a highly accelerated single-breathhold compressed-sensing multi-slice CMR technique with a non-model-based 3D reconstruction to accurately and reproducibly measure LA volumes and function.

Thermodynamic stability of nanosized multicomponent bubbles/droplets: The square gradient theory and the capillary approach

Formation of nanosized droplets/bubbles from a metastable bulk phase is connected to many unresolved scientific questions. We analyze the properties and stability of multicomponent droplets and bubbles in the canonical ensemble, and compare with single-component systems. The bubbles/droplets are described on the mesoscopic level by square gradient theory. Furthermore, we compare the results to a capillary model which gives a macroscopic description. Remarkably, the solutions of the square gradient model, representing bubbles and droplets, are accurately reproduced by the capillary model except in the vicinity of the spinodals. The solutions of the square gradient model form closed loops, which shows the inherent symmetry and connected nature of bubbles and droplets. A thermodynamic stability analysis is carried out, where the second variation of the square gradient description is compared to the eigenvalues of the Hessian matrix in the capillary description. The analysis shows that it is impossible to stabilize arbitrarily small bubbles or droplets in closed systems and gives insight into metastable regions close to the minimum bubble/droplet radii. Despite the large difference in complexity, the square gradient and the capillary model predict the same finite threshold sizes and very similar stability limits for bubbles and droplets, both for single-component and two-component systems.

Robust Estimates of the Negative Binomial Model

We consider robust parametric procedures for univariate discrete distributions, focusing on the negative binomial model. The procedures are based on three steps: ?First, a very robust, but possibly inefficient, estimate of the model parameters is computed. ?Second, this initial model is used to identify outliers, which are then removed from the sample. ?Third, a corrected maximum likelihood estimator is computed with the remaining observations. The final estimate inherits the breakdown point (bdp) of the initial one and its efficiency can be significantly higher. Analogous procedures were proposed in [1], [2], [5] for the continuous case. A comparison of the asymptotic bias of various estimates under point contamination points out the minimum Neyman's chi-squared disparity estimate as a good choice for the initial step. Various minimum disparity estimators were explored by Lindsay [4], who showed that the minimum Neyman's chi-squared estimate has a 50% bdp under point contamination; in addition, it is asymptotically fully efficient at the model. However, the finite sample efficiency of this estimate under the uncontaminated negative binomial model is usually much lower than 100% and the bias can be strong. We show that its performance can then be greatly improved using the three step procedure outlined above. In addition, we compare the final estimate with the procedure described in

Mergers and difference-in-difference estimator : why firms do not increase prices?

Difference-in-Difference (DiD) methods are being increasingly used to analyze the impact of mergers on pricing and other market equilibrium outcomes. Using evidence from an exogenous merger between two retail gasoline companies in a specific market in Spain, this paper shows how concentration did not lead to a price increase. In fact, the conjectural variation model concludes that the existence of a collusive agreement before and after the merger accounts for this result, rather than the existence of efficient gains. This result may explain empirical evidence reported in the literature according to which mergers between firms do not have significant effects on prices.

A model of gender prejudice, power, and discrimination: How hierarchy-enhancing factors predominate over hierarchy-attenuating factors

Gender inequalities remain an issue in our society and particularly in the workplace. Several factors can explain this gender difference in top-level managerial positions such as career ambitions but also biases against women. In our chapter, we propose a model explaining why gender inequalities and particularly discrimination against women is still present in our societies despite social norms and existing legislation on gender equality. To this purpose, we review research on discrimination through two different approaches, (a) a prejudice approach through the justification-suppression model developed by Crandall and Eshleman (2003) and (b) a power approach through the social dominance theory (Pratto, Sidanius, Stallworth, & Malle, 1994; Sidanius & Pratto, 1999). In our work, we integrate these two approaches and propose a model of gender prejudice, power and discrimination. The integration of these two approaches contributes to a better understanding of how discrimination against women is formed and maintained over time.

Why Women Rarely Rise to the Top: A Social Identity Model of Leader Prototypes.

Purpose We propose a social identity model of leader prototypes to address why the maleness of leader prototypes is more pronounced among men than among women (e.g., Schein, 2001). Specifically, we argue that individuals project their ingroup prototype (e.g., a male prototype) onto a valued other category (e.g., leaders) (e.g., Wenzel, Mummendey, Weber, & Waldzus, 2003) in order to maintain a positive ingroup (e.g., gender) identity. We hypothesized that both women and men engage in ingroup projection of their gender prototype on their leader prototype, and we expected this effect to be stronger for men than women. We also investigated intelligence as a moderator of ingroup projection. Methodology Participants (276 students, University of Lausanne) assessed to what extent attributes on a list of gender traits were characteristic of a successful leader. We computed relative ingroup similarity scores (e.g., Waldzus & Mummendey, 2004) representing the difference between how characteristic ingroup traits are for a successful leader, and how characteristic outgroup traits are for a successful leader. Results Results showed that men engaged in ingroup projection while women engaged in outgroup projection, and that men engaged in ingroup projection to a greater extent. We also found a small, but positive effect of intelligence on ingroup projection among men. Limitations The use of a student sample might limit the external validity of our findings. Implications Our findings contribute to research on the under-representation of women in managerial roles, and introduce intelligence as a predictor of ingroup projection. Value Our study allows for a more fine-grained understanding of the cognitive representations of leaders of men and women.

A feed-forward spiking model of shape-coding by IT cells

The ability to recognize a shape is linked to figure-ground (FG) organization. Cell preferences appear to be correlated across contrast-polarity reversals and mirror reversals of polygon displays, but not so much across FG reversals. Here we present a network structure which explains both shape-coding by simulated IT cells and suppression of responses to FG reversed stimuli. In our model FG segregation is achieved before shape discrimination, which is itself evidenced by the difference in spiking onsets of a pair of output cells. The studied example also includes feature extraction and illustrates a classification of binary images depending on the dominance of vertical or horizontal borders.