Evaluating the influence of spatial uncertainty in locality points for species distributional modeling

1. Species distribution modelling is used increasingly in both applied and theoretical research to predict how species are distributed and to understand attributes of species' environmental requirements. In species distribution modelling, various statistical methods are used that combine species occurrence data with environmental spatial data layers to predict the suitability of any site for that species. While the number of data sharing initiatives involving species' occurrences in the scientific community has increased dramatically over the past few years, various data quality and methodological concerns related to using these data for species distribution modelling have not been addressed adequately. 2. We evaluated how uncertainty in georeferences and associated locational error in occurrences influence species distribution modelling using two treatments: (1) a control treatment where models were calibrated with original, accurate data and (2) an error treatment where data were first degraded spatially to simulate locational error. To incorporate error into the coordinates, we moved each coordinate with a random number drawn from the normal distribution with a mean of zero and a standard deviation of 5 km. We evaluated the influence of error on the performance of 10 commonly used distributional modelling techniques applied to 40 species in four distinct geographical regions. 3. Locational error in occurrences reduced model performance in three of these regions; relatively accurate predictions of species distributions were possible for most species, even with degraded occurrences. Two species distribution modelling techniques, boosted regression trees and maximum entropy, were the best performing models in the face of locational errors. The results obtained with boosted regression trees were only slightly degraded by errors in location, and the results obtained with the maximum entropy approach were not affected by such errors. 4. Synthesis and applications. To use the vast array of occurrence data that exists currently for research and management relating to the geographical ranges of species, modellers need to know the influence of locational error on model quality and whether some modelling techniques are particularly robust to error. We show that certain modelling techniques are particularly robust to a moderate level of locational error and that useful predictions of species distributions can be made even when occurrence data include some error.

Dynamical modeling and analysis of large cellular regulatory networks.

The dynamical analysis of large biological regulatory networks requires the development of scalable methods for mathematical modeling. Following the approach initially introduced by Thomas, we formalize the interactions between the components of a network in terms of discrete variables, functions, and parameters. Model simulations result in directed graphs, called state transition graphs. We are particularly interested in reachability properties and asymptotic behaviors, which correspond to terminal strongly connected components (or "attractors") in the state transition graph. A well-known problem is the exponential increase of the size of state transition graphs with the number of network components, in particular when using the biologically realistic asynchronous updating assumption. To address this problem, we have developed several complementary methods enabling the analysis of the behavior of large and complex logical models: (i) the definition of transition priority classes to simplify the dynamics; (ii) a model reduction method preserving essential dynamical properties, (iii) a novel algorithm to compact state transition graphs and directly generate compressed representations, emphasizing relevant transient and asymptotic dynamical properties. The power of an approach combining these different methods is demonstrated by applying them to a recent multilevel logical model for the network controlling CD4+ T helper cell response to antigen presentation and to a dozen cytokines. This model accounts for the differentiation of canonical Th1 and Th2 lymphocytes, as well as of inflammatory Th17 and regulatory T cells, along with many hybrid subtypes. All these methods have been implemented into the software GINsim, which enables the definition, the analysis, and the simulation of logical regulatory graphs.

Schistosomiasis vaccine development: approaches and prospects

Mounting evidence for acquired immunity to schistosomiasis in humans supports the case for immunological intervention. On the other hand, rapid reinfection poses a threat to younger age groups due to the slow maturation of natural resistance. However, rational approaches, based on advances in immunology and molecular biology, have substantially increased the odds of producing an effective vaccine. Since the parasite cannot replicate in the human host and serious morbidity generally occurs only after a relatively long period of heavy worm burden, complete protection against infection is not essential. The chances of success would increase if more than one of the various host/parasite interphases were targeted, for example reducing morbidity through decreased worm loads as well as through suppression of egg production. Several promising schistosome antigens have now reached an advanced phase of development and are currently undergoing independent confirmatory testing according to a standardized protocol. A few molecules are being contemplated for scaled-up production but, so far, only one has reached the stage of industrial manufacture and safety testing. Since schistosomiasis cannot realistically be controlled by a single approach, vaccination is envisaged to be implemented in conjunction with other means of control, notably chemotherapy.

Complementarities between mathematical and computational modeling: the case of the repeated Prisoners' Dilemma

We study the properties of the well known Replicator Dynamics when applied to a finitely repeated version of the Prisoners' Dilemma game. We characterize the behavior of such dynamics under strongly simplifying assumptions (i.e. only 3 strategies are available) and show that the basin of attraction of defection shrinks as the number of repetitions increases. After discussing the difficulties involved in trying to relax the 'strongly simplifying assumptions' above, we approach the same model by means of simulations based on genetic algorithms. The resulting simulations describe a behavior of the system very close to the one predicted by the replicator dynamics without imposing any of the assumptions of the mathematical model. Our main conclusion is that mathematical and computational models are good complements for research in social sciences. Indeed, while computational models are extremely useful to extend the scope of the analysis to complex scenarios hard to analyze mathematically, formal models can be useful to verify and to explain the outcomes of computational models.

Experimental approaches in the targeting of photodynamic therapeutics

RÉSUMÉ : Chez l'homme, le manque de sélectivité des agents thérapeutiques représente souvent une limitation pour le traitement des maladies. Le ciblage de ces agents pour un tissu défini pourrait augmenter leur sélectivité et ainsi diminuer les effets secondaires en comparaison d'agents qui s'accumuleraient dans tout le corps. Cela pourrait aussi améliorer l'efficacité des traitements en permettant d'avoir une concentration localisée plus importante. Le ciblage d'agents thérapeutiques est un champ de recherche très actif. Les stratégies sont généralement basées sur les différences entre cellules normales et malades. Ces différences peuvent porter soit sur l'expression des molécules à leurs surfaces comme des récepteurs ou des transporteurs, soit sur les activités enzymatiques exprimées. Le traitement thérapeutique choisi ici est la thérapie photodynamique et est déjà utilisé pour le traitement de certains cancers. Cette thérapie repose sur l'utilisation de molécules qui réagissent à la lumière, les photosensibilisants. Elles absorbent l'énergie lumineuse et réagissent avec l'oxygène pour former des radicaux toxiques pour les cellules. Les photosensibilisants utilisés ici sont de deux natures : (i) soit ils sont tétrapyroliques (comme les porphyrines et chlorines), c'est à dire qu'ils sont directement activables par la lumière ; (ii) soit ce sont des prodrogues de photosensibilisants comme l'acide 5aminolévulinique (ALA) qui est transformé dans la cellule en protoporphyrine IX photosensibilisante. Dans le but d'augmenter la sélectivité des photosensibilisants, nous avons utilisé deux stratégies différentes : (i) le photosensibilisant est modifié par le greffage d'un agent de ciblage ; (ii) le photosensibilisant est incorporé dans des structures moléculaires de quelques centaines de nanomètres. Les sucres et l'acide folique sont des agents de ciblage largement établis et ont été utilisés ici car leurs récepteurs sont surexprimés à la surface de nombreuses cellules malades. Ainsi, des dérivés sucres ou acide folique de l'ALA ont été synthétisés et évalués in vitro sur de nombreuses lignées cellulaires cancéreuses. La stratégie utilisant l'acide folique est apparue incompatible avec l'utilisation de l'ALA puisque aucune photosensibilité n'a été induite par le composé. La stratégie utilisant les sucres a, par ailleurs, provoquée de bonnes photosensibilités mais pas d'augmentation de sélectivité. En parallèle, la combinaison entre les propriétés anticancéreuses des complexes métalliques au ruthénium avec les propriétés photosensibilisantes des porphyrines, a été évaluée. En effet, les thérapies combinées ont émergé il y a une dizaine d'années et représentent aujourd'hui de bonnes alternatives aux monothérapies classiques. Des ruthenium(I1)-arènes complexés avec la tetrapyridylporphyrine ont ainsi présenté de bonnes cytotoxicités et de bonnes phototoxicités pour des cellules de mélanomes. Des porphyrines ont aussi été compléxées avec des noyaux de diruthénium et ce type de dérivé a présenté de bonnes phototoxicités et une bonne sélectivité pour les cellules cancéreuses de l'appareil reproducteur féminin. L'incorporation de photosensibilisants tétrapyroliques a finalement été effectuée en utilisant des nanoparticules (NP) biocompatibles composées de chitosan et de hyaluronate. L'effet de ces NP a été évalué pour le traitement de la polyarthrite rhumatoïde (PR). Les NP ont d'abord été testées in vitro avec des macrophages de souris et les résultats ont mis en évidence de bonnes sélectivités et photosensibilités pour ces cellules. In vivo chez un modèle marin de la PR, l'utilisation de ces NP a révélé un plus grand temps de résidence des NP dans le genou de la souris en comparaison du temps obtenu avec le photosensibilisant seul. Le traitement par PDT a aussi démontré une bonne efficacité par ailleurs égale à celle obtenue avec les corticoïdes utilisés en clinique. Pour finir, les NP ont aussi démontré une bonne efficacité sur les myelomonocytes phagocytaires humains et sur les cellules contenues dans le liquide synovial de patients présentant une PR. Tous ces résultats suggèrent que les deux stratégies de ciblage peuvent être efficaces pour les agents thérapeutiques. Afm d'obtenir de bons résultats, il est toutefois nécessaire de réaliser une analyse minutieuse de la cible et du mode d'action de l'agent thérapeutique. Concernant les perspectives, la combinaison des deux stratégies c'est à dire incorporer des agents thérapeutiques dans des nanostructures porteuses d'agents de ciblage, représente probablement une solution très prometteuse. SUMMARY : In humans, the lack of selectivity of drugs and their high effective concentrations often represent limitations for the treatment of diseases. Targeting the therapeutical agents to a defined tissue could enhance their selectivity and then diminish their side effects when compared to drugs that accumulate in the entire body and could also improve treatment efûciency by allowing a localized high concentration of the agents. Targeting therapeutics to defined cells in human pathologies is a main challenge and a very active field of research. Strategies are generally based on the different behaviors and patterns of expression of diseased cells compared to normal cells such as receptors, proteases or trans-membrane carriers. The therapeutic treatment chosen here is the photodynamic therapy and is already used in the treatment of many cancers. This therapy relies on the administration of a photosensitizer (PS) which will under light, react with oxygen and induce formation of reactive oxygen species which are toxic for cells. The PSs used here are either tetrapyrolic (i. e. porphyries and chlorins) or prodrugs of PS (5-aminolevulinic acid precursor of the endogenous protoporphyrin Imo. In order to improve PS internalization and selectivity, we have used two different strategies: the modification of the PSs with diseased cell-targeting agents as well as their encapsulation into nanostructures. Sugars and folic acid are well established as targeting entities for diseased cells and were used here since their transporters are overexpressed on the surface of many cancer cells. Therefore sugar- and folic acid-derivatives of 5-aminolevulinic acid (ALA) were synthesized and evaluated in vitro in several cancer cell lines. The folic acid strategy appeared to be incompatible with ALA since no photosensitivity was induced while the strategy with sugars induced good photosensitivites but no increase of selectivity. Alternatively, the feasibility of combining the antineoplastic properties of ruthenium complexes with the porphyrin's photosensitizing properties, was evaluated since combined therapies have emerged as good alternatives to classical treatments. Tetrapyridylporphyrins complexed to ruthenium (I17 arenes presented good cytotoxicities and good phototoxicities toward melanoma cells. Porphyries were also complexed to diruthenium cores and this type of compound presented good phototoxicities and good selectivity for female reproductive cancer cells. The encapsulation of tetrapyrolic PSs was finally investigated using biocompatible nanogels composed of chitosan and hyaluronate. The behavior of these nanoparticles was evaluated for the treatment of rheumatoid arthritis (RA). They were first tested in vitro in mouse macrophages and results revealed good selectivities and phototoxicities toward these cells. In vivo in mice model of RA, the use of such nanoparticles instead of free PS showed longer time of residence in mice knees. Photodynamic protocols also demonstrated good efficiency of the treatment comparable to the corticoid injection used in the clinic. Finally our system was also efficient in human cells using phagocytic myelomonocytes or using cells of synovial fluids taken from patients with RA. Altogether, these results revealed that both strategies of modification or encapsulation of drugs can be successful in the targeting of diseased cells. However, a careful analysis of the target and of the mode of action of the drug, are needed in order to obtain good results. Looking ahead to the future, the combination of the two strategies (i.e. drugs loaded into nanostructures bearing the targeting agents) would represent probably the best solution.

The stabilizing effects of the acquired immunity on the schistosomiasis transmission modeling - the sensitivity Analysis

A mathematical model is proposed to analyze the effects of acquired immunity on the transmission of schistosomiasis in the human host. From this model the prevalence curve dependent on four parameters can be obtained. These parameters were estimated fitting the data by the maximum likelihood method. The model showed a good retrieving capacity of real data from two endemic areas of schistosomiasis: Touros, Brazil (Schistosoma mansoni) and Misungwi, Tanzania (S. haematobium). Also, the average worm burden per person and the dispersion of parasite per person in the community can be obtained from the model. In this paper, the stabilizing effects of the acquired immunity assumption in the model are assessed in terms of the epidemiological variables as follows. Regarded to the prevalence curve, we calculate the confidence interval, and related to the average worm burden and the worm dispersion in the community, the sensitivity analysis (the range of the variation) of both variables with respect to their parameters is performed.

Different approaches to modelling the cost-effectiveness of schistosomiasis control

This paper reviews three different approaches to modelling the cost-effectiveness of schistosomiasis control. Although these approaches vary in their assessment of costs, the major focus of the paper is on the evaluation of effectiveness. The first model presented is a static economic model which assesses effectiveness in terms of the proportion of cases cured. This model is important in highlighting that the optimal choice of chemotherapy regime depends critically on the level of budget constraint, the unit costs of screening and treatment, the rates of compliance with screening and chemotherapy and the prevalence of infection. The limitations of this approach is that it models the cost-effectiveness of only one cycle of treatment, and effectiveness reflects only the immediate impact of treatment. The second model presented is a prevalence-based dynamic model which links prevalence rates from one year to the next, and assesses effectiveness as the proportion of cases prevented. This model was important as it introduced the concept of measuring the long-term impact of control by using a transmission model which can assess reduction in infection through time, but is limited to assessing the impact only on the prevalence of infection. The third approach presented is a theoretical framework which describes the dynamic relationships between infection and morbidity, and which assesses effectiveness in terms of case-years prevented of infection and morbidity. The use of this model in assessing the cost-effectiveness of age-targeted treatment in controlling Schistosoma mansoni is explored in detail, with respect to varying frequencies of treatment and the interaction between drug price and drug efficacy.

Histoarchitecture of schistosomal granuloma development and involution: morphogenetic and biomechanical approaches

The authors present morphogenetic and biomechanical approaches on the concept of the Schistosoma mansoni granulomas, considering them as organoid structures that depend on cellular adhesion and sorting, forming rearrangement into hierarchical concentric layers, creating tension-dependent structures, aiming to acquire round form, since this is the minimal energy form, in which opposing forces pull in equally from all directions and are in balance. From the morphogenetic point of view, the granulomas function as little organs, presenting maturative and involutional stages in their development with final disappearance (pre-granulomatous stages, subdivided in: weakly and/or initial reactive and exudative; granulomatous stages: exudative-productive, productive and involutional). A model for the development of granulomas was suggested, according to the following stages: encapsulating, focal histolysis, fiber production, orientation and compacting and involution and desintegration. The authors concluded that schistosomal granuloma is not a tangled web of individual cells and fibers, but an organized structure composed by host and parasite components, which is not formed to attack the miracidia, but functions as an hybrid interface between two different phylogenetic beings.

Apport de la systématique dans l'amélioration de la compréhension des systèmes de prise en compte des risques en entreprise

La gestion des risques est souvent appréhendée par l'utilisation de méthodes linéaires mettant l'accent sur des raisonnements de positionnement et de type causal : à tel événement correspond tel risque et telle conséquence. Une prise en compte des interrelations entre risques est souvent occultée et les risques sont rarement analysés dans leurs dynamiques et composantes non linéaires. Ce travail présente ce que les méthodes systémiques et notamment l'étude des systèmes complexes sont susceptibles d'apporter en matière de compréhension, de management et d'anticipation et de gestion des risques d'entreprise, tant sur le plan conceptuel que de matière appliquée. En partant des définitions relatives aux notions de systèmes et de risques dans différents domaines, ainsi que des méthodes qui sont utilisées pour maîtriser les risques, ce travail confronte cet ensemble à ce qu'apportent les approches d'analyse systémique et de modélisation des systèmes complexes. En mettant en évidence les effets parfois réducteurs des méthodes de prise en compte des risques en entreprise ainsi que les limitations des univers de risques dues, notamment, à des définitions mal adaptées, ce travail propose également, pour la Direction d'entreprise, une palette des outils et approches différentes, qui tiennent mieux compte de la complexité, pour gérer les risques, pour aligner stratégie et management des risques, ainsi que des méthodes d'analyse du niveau de maturité de l'entreprise en matière de gestion des risques. - Risk management is often assessed through linear methods which stress positioning and causal logical frameworks: to such events correspond such consequences and such risks accordingly. Consideration of the interrelationships between risks is often overlooked and risks are rarely analyzed in their dynamic and nonlinear components. This work shows what systemic methods, including the study of complex systems, are likely to bring to knowledge, management, anticipation of business risks, both on the conceptual and the practical sides. Based on the definitions of systems and risks in various areas, as well as methods used to manage risk, this work confronts these concepts with approaches of complex systems analysis and modeling. This work highlights the reducing effects of some business risk analysis methods as well as limitations of risk universes caused in particular by unsuitable definitions. As a result this work also provides chief officers with a range of different tools and approaches which allows them a better understanding of complexity and as such a gain in efficiency in their risk management practices. It results in a better fit between strategy and risk management. Ultimately the firm gains in its maturity of risk management.

Pharmacological Approaches to Antitrypanosomal Chemotherapy

There is an urgent need for new drugs for the chemotherapy of human African trypanosomiasis, Chagas disease and leishmaniasis. Progress has been made in the identification and characterization of novel drug targets for rational chemotherapy and inhibitors of trypanosomatid glycosomal enzymes, trypanothione reductase, ornithine decarboxylase, S-adenosylmethionine decarboxylase, cysteine proteases and of the purine and sterol biosynthetic pathways. However, less attention has been paid to the pharmacological aspects of drug design or to the use of drug delivery systems in the chemotherapy of African trypanosomiasis and Chagas disease. A review of research on pharmacology and drug delivery systems shows that there are new opportunities for improving the chemotherapy of these diseases.

Synchronous versus asynchronous modeling of gene regulatory networks.

MOTIVATION: In silico modeling of gene regulatory networks has gained some momentum recently due to increased interest in analyzing the dynamics of biological systems. This has been further facilitated by the increasing availability of experimental data on gene-gene, protein-protein and gene-protein interactions. The two dynamical properties that are often experimentally testable are perturbations and stable steady states. Although a lot of work has been done on the identification of steady states, not much work has been reported on in silico modeling of cellular differentiation processes. RESULTS: In this manuscript, we provide algorithms based on reduced ordered binary decision diagrams (ROBDDs) for Boolean modeling of gene regulatory networks. Algorithms for synchronous and asynchronous transition models have been proposed and their corresponding computational properties have been analyzed. These algorithms allow users to compute cyclic attractors of large networks that are currently not feasible using existing software. Hereby we provide a framework to analyze the effect of multiple gene perturbation protocols, and their effect on cell differentiation processes. These algorithms were validated on the T-helper model showing the correct steady state identification and Th1-Th2 cellular differentiation process. AVAILABILITY: The software binaries for Windows and Linux platforms can be downloaded from http://si2.epfl.ch/~garg/genysis.html.