Voriconazole-Induced Inhibition of the Fungicidal Activity of Amphotericin B in Candida Strains with Reduced Susceptibility to Voriconazole: an Effect Not Predicted by the MIC Value Alone.

An antagonistic effect of voriconazole on the fungicidal activity of sequential doses of amphotericin B has previously been demonstrated in Candida albicans strains susceptible to voriconazole. Because treatment failure and the need to switch to other antifungals are expected to occur more often in infections that are caused by resistant strains, it was of interest to study whether the antagonistic effect was still seen in Candida strains with reduced susceptibility to voriconazole. With the hypothesis that antagonism will not occur in voriconazole-resistant strains, C. albicans strains with characterized mechanisms of resistance against voriconazole, as well as Candida glabrata and Candida krusei strains with differences in their degrees of susceptibility to voriconazole were exposed to voriconazole or amphotericin B alone, to both drugs simultaneously, or to voriconazole followed by amphotericin B in an in vitro kinetic model. Amphotericin B administered alone or simultaneously with voriconazole resulted in fungicidal activity. When amphotericin B was administered after voriconazole, its activity was reduced (median reduction, 61%; range, 9 to 94%). Levels of voriconazole-dependent inhibition of amphotericin B activity differed significantly among the strains but were not correlated with the MIC values (correlation coefficient, -0.19; P = 0.65). Inhibition was found in C. albicans strains with increases in CDR1 and CDR2 expression but not in the strain with an increase in MDR1 expression. In summary, decreased susceptibility to voriconazole does not abolish voriconazole-dependent inhibition of the fungicidal activity of amphotericin B in voriconazole-resistant Candida strains. The degree of interaction could not be predicted by the MIC value alone.

Lipid composition of fingermark residue and donor classification using GC/MS

Lipids available in fingermark residue represent important targets for enhancement and dating techniques. While it is well known that lipid composition varies among fingermarks of the same donor (intra-variability) and between fingermarks of different donors (inter-variability), the extent of this variability remains uncharacterised. Thus, this worked aimed at studying qualitatively and quantitatively the initial lipid composition of fingermark residue of 25 different donors. Among the 104 detected lipids, 43 were reported for the first time in the literature. Furthermore, palmitic acid, squalene, cholesterol, myristyl myristate and myristyl myristoleate were quantified and their correlation within fingermark residue was highlighted. Ten compounds were then selected and further studied as potential targets for dating or enhancement techniques. It was shown that their relative standard deviation was significantly lower for the intra-variability than for the inter-variability. Moreover, the use of data pretreatments could significantly reduce this variability. Based on these observations, an objective donor classification model was proposed. Hierarchical cluster analysis was conducted on the pre-treated data and the fingermarks of the 25 donors were classified into two main groups, corresponding to "poor" and "rich" lipid donors. The robustness of this classification was tested using fingermark replicates of selected donors. 86% of these replicates were correctly classified, showing the potential of such a donor classification model for research purposes in order to select representative donors based on compounds of interest.

A two-compartment mathematical model of neuroglial metabolism using [1-(11)C] acetate.

The purpose of this study was to develop a two-compartment metabolic model of brain metabolism to assess oxidative metabolism from [1-(11)C] acetate radiotracer experiments, using an approach previously applied in (13)C magnetic resonance spectroscopy (MRS), and compared with an one-tissue compartment model previously used in brain [1-(11)C] acetate studies. Compared with (13)C MRS studies, (11)C radiotracer measurements provide a single uptake curve representing the sum of all labeled metabolites, without chemical differentiation, but with higher temporal resolution. The reliability of the adjusted metabolic fluxes was analyzed with Monte-Carlo simulations using synthetic (11)C uptake curves, based on a typical arterial input function and previously published values of the neuroglial fluxes V(tca)(g), V(x), V(nt), and V(tca)(n) measured in dynamic (13)C MRS experiments. Assuming V(x)(g)=10 × V(tca)(g) and V(x)(n)=V(tca)(n), it was possible to assess the composite glial tricarboxylic acid (TCA) cycle flux V(gt)(g) (V(gt)(g)=V(x)(g) × V(tca)(g)/(V(x)(g)+V(tca)(g))) and the neurotransmission flux V(nt) from (11)C tissue-activity curves obtained within 30 minutes in the rat cortex with a beta-probe after a bolus infusion of [1-(11)C] acetate (n=9), resulting in V(gt)(g)=0.136±0.042 and V(nt)=0.170±0.103 μmol/g per minute (mean±s.d. of the group), in good agreement with (13)C MRS measurements.

The correlation between inbreeding and fitness: does allele size matter?

The availability of highly polymorphic genetic markers, in particular microsatellites, has made it possible to test the effect of inbreeding on fitness in the field and in the absence of pedigree information. It has been suggested that the squared difference in allele size at a locus (d(2)) might be a better indicator of the level of inbreeding than is heterozygosity. Using an elegant new analytical model, Tsitrone et al. now put this idea to the test, and to rest.

Intestinal fibrovascular nodules caused by Schistosoma mansoni infection in Calomys callosus Rengger, 1830 (Rodentia: Cricetidae): a model of concomitant fibrosis and angiogenesis

Human schistosomiasis develops extensive and dense fibrosis in portal space, together with congested new blood vessels. This study demonstrates that Calomys callosus infected with Schistosoma mansoni also develops fibrovascular lesions, which are found in intestinal subserosa. Animals were percutaneously infected with 70 cercariae and necropsied at 42, 45, 55, 80, 90 and 160 days after infection. Intestinal sections were stained for brightfield, polarization microscopy, confocal laser scanning, transmission and scanning electron microscopies. Immunohistological analysis was also performed and some nodules were aseptically collected for cell culture. Numerous intestinal nodules, appearing from 55 up to 160 days after infection, were localized at the interface between external muscular layer and intestinal serosa, consisting of fibrovascular tissue forming a shell about central granuloma(s). Intranodular new vessels were derived from the vasculature of the external vascular layer and were positive for laminin, chondroitin-sulfate, smooth muscle alpha-actin and FVIII-RA. Fibroblastic cells and extracellular matrix components (collagens I, III and VI, fibronectin and tenascin) comprised the stroma. Intermixed with the fibroblasts and vessels there were variable number of eosinophils, macrophages and haemorrhagic foci. In conclusion, the nodules constitute an excellent and accessible model to study fibrogenesis and angiogenesis, dependent on S. mansoni eggs. The fibrogenic activity is fibroblastic and not myofibroblastic-dependent. The angiogenesis is so prominent that causes haemorrhagic ascites.

An empirical hierarchical Bayesian unification of occupational exposure assessment methods.

In occupational exposure assessment of airborne contaminants, exposure levels can either be estimated through repeated measurements of the pollutant concentration in air, expert judgment or through exposure models that use information on the conditions of exposure as input. In this report, we propose an empirical hierarchical Bayesian model to unify these approaches. Prior to any measurement, the hygienist conducts an assessment to generate prior distributions of exposure determinants. Monte-Carlo samples from these distributions feed two level-2 models: a physical, two-compartment model, and a non-parametric, neural network model trained with existing exposure data. The outputs of these two models are weighted according to the expert's assessment of their relevance to yield predictive distributions of the long-term geometric mean and geometric standard deviation of the worker's exposure profile (level-1 model). Bayesian inferences are then drawn iteratively from subsequent measurements of worker exposure. Any traditional decision strategy based on a comparison with occupational exposure limits (e.g. mean exposure, exceedance strategies) can then be applied. Data on 82 workers exposed to 18 contaminants in 14 companies were used to validate the model with cross-validation techniques. A user-friendly program running the model is available upon request.

The demographic benefits of belligerence and bravery: defeated group repopulation or victorious group size expansion?

Intraspecific coalitional aggression between groups of individuals is a widespread trait in the animal world. It occurs in invertebrates and vertebrates, and is prevalent in humans. What are the conditions under which coalitional aggression evolves in natural populations? In this article, I develop a mathematical model delineating conditions where natural selection can favor the coevolution of belligerence and bravery between small-scale societies. Belligerence increases an actor's group probability of trying to conquer another group and bravery increase the actors's group probability of defeating an attacked group. The model takes into account two different types of demographic scenarios that may lead to the coevolution of belligerence and bravery. Under the first, the fitness benefits driving the coevolution of belligerence and bravery come through the repopulation of defeated groups by fission of victorious ones. Under the second demographic scenario, the fitness benefits come through a temporary increase in the local carrying capacity of victorious groups, after transfer of resources from defeated groups to victorious ones. The analysis of the model suggests that the selective pressures on belligerence and bravery are stronger when defeated groups can be repopulated by victorious ones. The analysis also suggests that, depending on the shape of the contest success function, costly bravery can evolve in groups of any size.

Peripheral eosinophilia as an indicator of meningitic angiostrongyliasis in exposed individuals

The diagnosis of meningitic angiostrongyliasis (MA) is based on clinical criteria. A lumbar puncture is used as a diagnostic tool, but it is an invasive procedure. The blood eosinophil levels are also assessed and used in the diagnosis of this disease. We enrolled 47 patients with serologically proven MA and 131 controls with intestinal parasite infections. An absolute eosinophil count model was found to be the best marker for MA. An eosinophil count of more than 798 cells led to sensitivity, specificity, positive predictive and negative predictive values of 76.6%, 80.2%, 58.1% and 90.5%, respectively. These data support the use of testing for high blood eosinophil levels as a diagnostic tool for MA in individuals that are at risk for this disease.

Infection in a rat model reactivates attenuated virulence after long-term axenic culture of Acanthamoeba spp

Prolonged culturing of many microorganisms leads to the loss of virulence and a reduction of their infective capacity. However, little is known about the changes in the pathogenic strains of Acanthamoeba after long culture periods. Our study evaluated the effect of prolonged culturing on the invasiveness of different isolates of Acanthamoeba in an in vivo rat model. ATCC strains of Acanthamoeba, isolates from the environment and clinical cases were evaluated. The in vivo model was effective in establishing the infection and differentiating the pathogenicity of the isolates and re-isolates. The amoebae cultured in the laboratory for long periods were less virulent than those that were recently isolated, confirming the importance of passing Acanthamoeba strains in animal models.

Integrating human indoor air pollutant exposure within Life Cycle Impact Assessment.

Neglecting health effects from indoor pollutant emissions and exposure, as currently done in Life Cycle Assessment (LCA), may result in product or process optimizations at the expense of workers' or consumers' health. To close this gap, methods for considering indoor exposure to chemicals are needed to complement the methods for outdoor human exposure assessment already in use. This paper summarizes the work of an international expert group on the integration of human indoor and outdoor exposure in LCA, within the UNEP/ SETAC Life Cycle Initiative. A new methodological framework is proposed for a general procedure to include human-health effects from indoor exposure in LCA. Exposure models from occupational hygiene and household indoor air quality studies and practices are critically reviewed and recommendations are provided on the appropriateness of various model alternatives in the context of LCA. A single-compartment box model is recommended for use as a default in LCA, enabling one to screen occupational and household exposures consistent with the existing models to assess outdoor emission in a multimedia environment. An initial set of model parameter values was collected. The comparison between indoor and outdoor human exposure per unit of emission shows that for many pollutants, intake per unit of indoor emission may be several orders of magnitude higher than for outdoor emissions. It is concluded that indoor exposure should be routinely addressed within LCA.

Economic and environmental effects of the CO2 taxation: an input-output analysis for Spain

CO2 emissions induced by human activities are the major cause of climate change; hence, strong environmental policy that limits the growing dependence on fossil fuel is indispensable. Tradable permits and environmental taxes are the usual tools used in CO2 reduction strategies. Such economic tools provide incentives to polluting industries to reduce their emissions through market signals. The aim of this work is to investigate the direct and indirect effects of an environmental tax on Spanish products and services. We apply an environmentally extended input-output (EIO) model to identify CO2 emission intensities of products and services and, accordingly, we estimate the tax proportional to these intensities. The short-term price effects are analyzed using an input-output price model. The effect of tax introduction on consumption prices and its influence on consumers’ welfare are determined. We also quantify the environmental impacts of such taxation in terms of the reduction in CO2 emissions. The results, based on the Spanish economy for the year 2007, show that sectors with relatively poor environmental profile are subjected to high environmental tax rates. And consequently, applying a CO2 tax on these sectors, increases production prices and induces a slight increase in consumer price index and a decrease in private welfare. The revenue from the tax could be used to counter balance the negative effects on social welfare and also to stimulate the increase of renewable energy shares in the most impacting sectors. Finally, our analysis highlights that the environmental and economic goals cannot be met at the same time with the environmental taxation and this shows the necessity of finding other (complementary or alternative) measures to ensure both the economic and ecological efficiencies. Keywords: CO2 emissions; environmental tax; input-output model, effects of environmental taxation.

Population PK-guided simulation study in children exposed to drugs in human milk

Risks of significant infant drug exposure through human milk arepoorly defined due to lack of large-scale PK data. We propose to useBayesian approach based on population PK (popPK)-guided modelingand simulation for risk prediction. As a proof-of-principle study, weexploited fluoxetine milk concentration data from 25 women. popPKparameters including milk-to-plasma ratio (MP ratio) were estimatedfrom the best model. The dose of fluoxetine the breastfed infant wouldreceive through mother's milk, and infant plasma concentrations wereestimated from 1000 simulated mother-infant pairs, using randomassignment of feeding times and milk volume. A conservative estimateof CYP2D6 activity of 20% of the allometrically-adjusted adult valuewas assumed. Derived model parameters, including MP ratio were consistentwith those reported in the literature. Visual predictive check andother model diagnostics showed no signs of model misspecifications.The model simulation predicted that infant exposure levels to fluoxetinevia mother's milk were below 10% of weight-adjusted maternal therapeuticdoses in >99% of simulated infants. Predicted median ratio ofinfant-mother serum levels at steady state was 0.093 (range 0.033-0.31),consistent with literature reported values (mean=0.07; range 0-0.59).Predicted incidence of relatively high infant-mother ratio (>0.2) ofsteady-state serum fluoxetine concentrations was <1.3%. Overall, ourpredictions are consistent with clinical observations. Our approach maybe valid for other drugs, allowing in silico prediction of infant drugexposure risks through human milk. We will discuss application of thisapproach to another drug used in lactating women.

Organisational Values as "Attractors of Chaos": An Emerging Cultural Change to Manage Organisational Complexity

Business organisations are excellent representations of what in physics and mathematics are designated "chaotic" systems. Because a culture of innovation will be vital for organisational survival in the 21st century, the present paper proposes that viewing organisations in terms of "complexity theory" may assist leaders in fine-tuning managerial philosophies that provide orderly management emphasizing stability within a culture of organised chaos, for it is on the "boundary of chaos" that the greatest creativity occurs. It is argued that 21st century companies, as chaotic social systems, will no longer be effectively managed by rigid objectives (MBO) nor by instructions (MBI). Their capacity for self-organisation will be derived essentially from how their members accept a shared set of values or principles for action (MBV). Complexity theory deals with systems that show complex structures in time or space, often hiding simple deterministic rules. This theory holds that once these rules are found, it is possible to make effective predictions and even to control the apparent complexity. The state of chaos that self-organises, thanks to the appearance of the "strange attractor", is the ideal basis for creativity and innovation in the company. In this self-organised state of chaos, members are not confined to narrow roles, and gradually develop their capacity for differentiation and relationships, growing continuously toward their maximum potential contribution to the efficiency of the organisation. In this way, values act as organisers or "attractors" of disorder, which in the theory of chaos are equations represented by unusually regular geometric configurations that predict the long-term behaviour of complex systems. In business organisations (as in all kinds of social systems) the starting principles end up as the final principles in the long term. An attractor is a model representation of the behavioral results of a system. The attractor is not a force of attraction or a goal-oriented presence in the system; it simply depicts where the system is headed based on its rules of motion. Thus, in a culture that cultivates or shares values of autonomy, responsibility, independence, innovation, creativity, and proaction, the risk of short-term chaos is mitigated by an overall long-term sense of direction. A more suitable approach to manage the internal and external complexities that organisations are currently confronting is to alter their dominant culture under the principles of MBV.

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.

A multi-objective model for a multi-period distribution management problem

The problems arising in commercial distribution are complex and involve several players and decision levels. One important decision is relatedwith the design of the routes to distribute the products, in an efficient and inexpensive way.This article deals with a complex vehicle routing problem that can beseen as a new extension of the basic vehicle routing problem. The proposed model is a multi-objective combinatorial optimization problemthat considers three objectives and multiple periods, which models in a closer way the real distribution problems. The first objective is costminimization, the second is balancing work levels and the third is amarketing objective. An application of the model on a small example, with5 clients and 3 days, is presented. The results of the model show the complexity of solving multi-objective combinatorial optimization problems and the contradiction between the several distribution management objective.