957 resultados para biological models


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Hox genes are essential for the patterning of the axial skeleton. Hox group 10 has been shown to specify the lumbar domain by setting a rib-inhibiting program in the presomitic mesoderm (PSM). We have now produced mice with ribs in every vertebra by ectopically expressing Hox group 6 in the PSM, indicating that Hox genes are also able to specify the thoracic domain. We show that the information provided by Hox genes to specify rib-containing and rib-less areas is first interpreted in the myotome through the regional-specific control of Myf5 and Myf6 expression. This information is then transmitted to the sclerotome by a system that includes FGF and PDGF signaling to produce vertebrae with or without ribs at different axial levels. Our findings offer a new perspective of how Hox genes produce global patterns in the axial skeleton and support a redundant nonmyogenic role of Myf5 and Myf6 in rib formation.

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"UIUCDCS-R-73-616"

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Several levels of complexity are available for modelling of wastewater treatment plants. Modelling local effects rely on computational fluid dynamics (CFD) approaches whereas activated sludge models (ASM) represent the global methodology. By applying both modelling approaches to pilot plant and full scale systems, this paper evaluates the value of each method and especially their potential combination. Model structure identification for ASM is discussed based on a full-scale closed loop oxidation ditch modelling. It is illustrated how and for what circumstances information obtained via CFD (computational fluid dynamics) analysis, residence time distribution (RTD) and other experimental means can be used. Furthermore, CFD analysis of the multiphase flow mechanisms is employed to obtain a correct description of the oxygenation capacity of the system studied, including an easy implementation of this information in the classical ASM modelling (e.g. oxygen transfer). The combination of CFD and activated sludge modelling of wastewater treatment processes is applied to three reactor configurations, a perfectly mixed reactor, a pilot scale activated sludge basin (ASB) and a real scale ASB. The application of the biological models to the CFD model is validated against experimentation for the pilot scale ASB and against a classical global ASM model response. A first step in the evaluation of the potential of the combined CFD-ASM model is performed using a full scale oxidation ditch system as testing scenario.

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Spatial disease ecology is emerging as a new field that requires the integration of complementary approaches to address how the distribution and movements of hosts and parasites may condition the dynamics of their interactions. In this context, migration, the seasonal movement of animals to different zones of their distribution, is assumed to play a key role in the broad scale circulation of parasites and pathogens. Nevertheless, migration is not the only type of host movement that can influence the spatial ecology, evolution, and epidemiology of infectious diseases. Dispersal, the movement of individuals between the location where they were born or bred to a location where they breed, has attracted attention as another important type of movement for the spatial dynamics of infectious diseases. Host dispersal has notably been identified as a key factor for the evolution of host-parasite interactions as it implies gene flow among local host populations and thus can alter patterns of coevolution with infectious agents across spatial scales. However, not all movements between host populations lead to dispersal per se. One type of host movement that has been neglected, but that may also play a role in parasite spread is prospecting, i.e., movements targeted at selecting and securing new habitat for future breeding. Prospecting movements, which have been studied in detail in certain social species, could result in the dispersal of infectious agents among different host populations without necessarily involving host dispersal. In this article, we outline how these various types of host movements might influence the circulation of infectious disease agents and discuss methodological approaches that could be used to assess their importance. We specifically focus on examples from work on colonial seabirds, ticks, and tick-borne infectious agents. These are convenient biological models because they are strongly spatially structured and involve relatively simple communities of interacting species. Overall, this review emphasizes that explicit consideration of the behavioral and population ecology of hosts and parasites is required to disentangle the relative roles of different types of movement for the spread of infectious diseases.

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Desde el inicio de las organizaciones han existido modelos de control rígidos como los sistemas mecanicistas y formales en donde la perspectiva racional sobresale y no se tienen en cuenta los aspectos humanos en el diseño de los sistemas. Estos modelos de control rígidos, estandarizados y centralizados suponen un problema para el adecuado desarrollo estratégico y operativo de las organizaciones. Sin embargo, desde los sistemas biológicos se pueden observar aportes de autores que destacan la ausencia de control y su consecuente funcionamiento armónico a través de propiedades como la auto-organización y la emergencia. De esta forma, este artículo de revisión tiene como objetivo identificar las aproximaciones teóricas que se han realizado en torno a los principales aportes que los modelos biológicos han hecho a la gestión administrativa y específicamente al control organizacional mediante el análisis de la producción bibliográfica realizada en los últimos 10 años.

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The damaging of buildings and monuments by biological contamination is a cause of serious concern. Biocides based on chemical toxic compounds have been used to mitigate this problem. However, in the past decade many of the most effective biocides have been banned due to their environmental and health hazards. Therefore, proper remediation actions for microbiologically contaminated historic materials based on environmentally safe solution is of vital importance. Bacillus species are emerging as a promising alternative for built heritage treatment. They produce a great diversity of secondary metabolites with biological activity, well known to possess antagonistic activities against many fungal pathogens. In order to evaluate the antifungal activity of the novel biocides produced in our laboratory by cultures of selected bacterial strains, liquid interaction assays using four biodeteriogenic fungi were achieved, revealing a nearly 100% of inhibitory capacity to fungal proliferation. To confirm their effective safe toxicological properties, in vivo tests using two different biological models were performed. The lyophilized supernatant of the Bacillus culture broth showed no lethality against brine shrimp and also no toxicological effects in Swiss mice through administration of acute dose of 5000 mg/kg by oral gavage. In fact, the bioactive compounds were no lethal at the tested dose unlike Preventol® (commercial biocide) that induced acute toxicity with 10 times minor concentration dose administrated in the same conditions. Therefore, the new bioactive compounds that suppress growth of biodeteriogenic fungi on historical artworks, presenting at the same time no toxicity against other living organisms, constituting an efficient and green safe solution for biodegradation/biodeterioration treatment of Cultural Heritage.

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Inverse problems based on using experimental data to estimate unknown parameters of a system often arise in biological and chaotic systems. In this paper, we consider parameter estimation in systems biology involving linear and non-linear complex dynamical models, including the Michaelis–Menten enzyme kinetic system, a dynamical model of competence induction in Bacillus subtilis bacteria and a model of feedback bypass in B. subtilis bacteria. We propose some novel techniques for inverse problems. Firstly, we establish an approximation of a non-linear differential algebraic equation that corresponds to the given biological systems. Secondly, we use the Picard contraction mapping, collage methods and numerical integration techniques to convert the parameter estimation into a minimization problem of the parameters. We propose two optimization techniques: a grid approximation method and a modified hybrid Nelder–Mead simplex search and particle swarm optimization (MH-NMSS-PSO) for non-linear parameter estimation. The two techniques are used for parameter estimation in a model of competence induction in B. subtilis bacteria with noisy data. The MH-NMSS-PSO scheme is applied to a dynamical model of competence induction in B. subtilis bacteria based on experimental data and the model for feedback bypass. Numerical results demonstrate the effectiveness of our approach.

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Travelling wave phenomena are observed in many biological applications. Mathematical theory of standard reaction-diffusion problems shows that simple partial differential equations exhibit travelling wave solutions with constant wavespeed and such models are used to describe, for example, waves of chemical concentrations, electrical signals, cell migration, waves of epidemics and population dynamics. However, as in the study of cell motion in complex spatial geometries, experimental data are often not consistent with constant wavespeed. Non-local spatial models have successfully been used to model anomalous diffusion and spatial heterogeneity in different physical contexts. In this paper, we develop a fractional model based on the Fisher-Kolmogoroff equation and analyse it for its wavespeed properties, attempting to relate the numerical results obtained from our simulations to experimental data describing enteric neural crest-derived cells migrating along the intact gut of mouse embryos. The model proposed essentially combines fractional and standard diffusion in different regions of the spatial domain and qualitatively reproduces the behaviour of neural crest-derived cells observed in the caecum and the hindgut of mouse embryos during in vivo experiments.

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This paper addresses the problem of determining optimal designs for biological process models with intractable likelihoods, with the goal of parameter inference. The Bayesian approach is to choose a design that maximises the mean of a utility, and the utility is a function of the posterior distribution. Therefore, its estimation requires likelihood evaluations. However, many problems in experimental design involve models with intractable likelihoods, that is, likelihoods that are neither analytic nor can be computed in a reasonable amount of time. We propose a novel solution using indirect inference (II), a well established method in the literature, and the Markov chain Monte Carlo (MCMC) algorithm of Müller et al. (2004). Indirect inference employs an auxiliary model with a tractable likelihood in conjunction with the generative model, the assumed true model of interest, which has an intractable likelihood. Our approach is to estimate a map between the parameters of the generative and auxiliary models, using simulations from the generative model. An II posterior distribution is formed to expedite utility estimation. We also present a modification to the utility that allows the Müller algorithm to sample from a substantially sharpened utility surface, with little computational effort. Unlike competing methods, the II approach can handle complex design problems for models with intractable likelihoods on a continuous design space, with possible extension to many observations. The methodology is demonstrated using two stochastic models; a simple tractable death process used to validate the approach, and a motivating stochastic model for the population evolution of macroparasites.

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Climate matching software (CLIMEX) was used to prioritise areas to explore for biological control agents in the native range of cat's claw creeper Macfadyena unguis-cati (Bignoniaceae), and to prioritise areas to release the agents in the introduced ranges of the plant. The native distribution of cat's claw creeper was used to predict the potential range of climatically suitable habitats for cat's claw creeper in its introduced ranges. A Composite Match Index (CMI) of cat's claw creeper was determined with the 'Match Climates' function in order to match the ranges in Australia and South Africa where the plant is introduced with its native range in South and Central America. This information was used to determine which areas might yield climatically-adapted agents. Locations in northern Argentina had CMI values which best matched sites with cat's claw creeper infestations in Australia and South Africa. None of the sites from where three currently prioritised biological control agents for cat's claw creeper were collected had CMI values higher than 0.8. The analysis showed that central and eastern Argentina, south Brazil, Uruguay and parts of Bolivia and Paraguay should be prioritised for exploration for new biological control agents for cat's claw creeper to be used in Australia and South Africa.