270 research outputs found

    Study of metals in leached soils of a municipal dumpsite in Tampico, Tamaulipas, Mexico: preliminary results

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    The Zapote dumpsite measures 420000 m 2 and is 28 years old; an estimated 2.5 millions tons of waste have accumulated on the site (household waste, clinical waste, commercial waste). The thickness of the waste is 3 to 9 meters. Since operations began, no control regulations have existed on the residues received. The Zapote dumpsite is located within a salt-marsh between a system of channels and river lagoons of brackish water, located in a tropical sedimentary environment in the urban zone of Tampico, Tamaulipas, Mexico. Recently, the Zapote has been closed and work is presently underway in its rehabilitation since a geo-environmental perspective. The present investigation integrates information of preliminary results of metals (Pb, Ni, Cd, Cu, Mg, Fe and Al) contained in sediments that underlie the Zapote dumpsite. In laboratory research the metals of the sediment were correlated with the metals contained in samples of leachate from the Zapote dumpsite. The concentration of metals Pb, Ni, Cd, Cu, Mg, Fe and Al were analyzed in samples of sediments that underlie the body of the dumpsite in layers of 10 cm, reaching a depth of 1.5 m under the interface waste-soil. The results denote high concentrations of metals in layers that are in contact with waste that decreased until reaching 60 to 80 cm of depth. The proportions of the concentrations of metals studied in the soil are comparable with that leached, until layers of 60 to 80 cm of depth are reached, and are then lost in the deepest layers. The high plastic characteristics of clay layers have stood in the way of metallic contaminants in sub layers of the Zapote dumpsite. The results were correlated with metal concentrations of natural and anthropogenic sediments of the region

    Modelling of spectral properties and population kinetics studies of inertial fusión and laboratory astrophysical plasmas

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    Fundamental research and modelling in plasma atomic physics continue to be essential for providing basic understanding of many different topics relevant to high-energy-density plasmas. The Atomic Physics Group at the Institute of Nuclear Fusion has accumulated experience over the years in developing a collection of computational models and tools for determining the atomic energy structure, ionization balance and radiative properties of, mainly, inertial fusion and laser-produced plasmas in a variety of conditions. In this work, we discuss some of the latest advances and results of our research, with emphasis on inertial fusion and laboratory-astrophysical applications

    Flower Development as an Interplay between Dynamical Physical Fields and Genetic Networks

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    In this paper we propose a model to describe the mechanisms by which undifferentiated cells attain gene configurations underlying cell fate determination during morphogenesis. Despite the complicated mechanisms that surely intervene in this process, it is clear that the fundamental fact is that cells obtain spatial and temporal information that bias their destiny. Our main hypothesis assumes that there is at least one macroscopic field that breaks the symmetry of space at a given time. This field provides the information required for the process of cell differentiation to occur by being dynamically coupled to a signal transduction mechanism that, in turn, acts directly upon the gene regulatory network (GRN) underlying cell-fate decisions within cells. We illustrate and test our proposal with a GRN model grounded on experimental data for cell fate specification during organ formation in early Arabidopsis thaliana flower development. We show that our model is able to recover the multigene configurations characteristic of sepal, petal, stamen and carpel primordial cells arranged in concentric rings, in a similar pattern to that observed during actual floral organ determination. Such pattern is robust to alterations of the model parameters and simulated failures predict altered spatio-temporal patterns that mimic those described for several mutants. Furthermore, simulated alterations in the physical fields predict a pattern equivalent to that found in Lacandonia schismatica, the only flowering species with central stamens surrounded by carpels

    The logic of the floral transition: reverse-engineering the switch controlling the identity of lateral organs

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    Much laboratory work has been carried out to determine the gene regulatory network (GRN) that results in plant cells becoming flowers instead of leaves. However, this also involves the spatial distribution of different cell types, and poses the question of whether alternative networks could produce the same set of observed results. This issue has been addressed here through a survey of the published intercellular distribution of expressed regulatory genes and techniques both developed and applied to Boolean network models. This has uncovered a large number of models which are compatible with the currently available data. An exhaustive exploration had some success but proved to be unfeasible due to the massive number of alternative models, so genetic programming algorithms have also been employed. This approach allows exploration on the basis of both data-fitting criteria and parsimony of the regulatory processes, ruling out biologically unrealistic mechanisms. One of the conclusions is that, despite the multiplicity of acceptable models, an overall structure dominates, with differences mostly in alternative fine-grained regulatory interactions. The overall structure confirms the known interactions, including some that were not present in the training set, showing that current data are sufficient to determine the overall structure of the GRN. The model stresses the importance of relative spatial location, through explicit references to this aspect. This approach also provides a quantitative indication of how likely some regulatory interactions might be, and can be applied to the study of other developmental transitions

    Specialization Can Drive the Evolution of Modularity

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    Organismal development and many cell biological processes are organized in a modular fashion, where regulatory molecules form groups with many interactions within a group and few interactions between groups. Thus, the activity of elements within a module depends little on elements outside of it. Modularity facilitates the production of heritable variation and of evolutionary innovations. There is no consensus on how modularity might evolve, especially for modules in development. We show that modularity can increase in gene regulatory networks as a byproduct of specialization in gene activity. Such specialization occurs after gene regulatory networks are selected to produce new gene activity patterns that appear in a specific body structure or under a specific environmental condition. Modules that arise after specialization in gene activity comprise genes that show concerted changes in gene activities. This and other observations suggest that modularity evolves because it decreases interference between different groups of genes. Our work can explain the appearance and maintenance of modularity through a mechanism that is not contingent on environmental change. We also show how modularity can facilitate co-option, the utilization of existing gene activity to build new gene activity patterns, a frequent feature of evolutionary innovations

    Critical Dynamics in Genetic Regulatory Networks: Examples from Four Kingdoms

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    The coordinated expression of the different genes in an organism is essential to sustain functionality under the random external perturbations to which the organism might be subjected. To cope with such external variability, the global dynamics of the genetic network must possess two central properties. (a) It must be robust enough as to guarantee stability under a broad range of external conditions, and (b) it must be flexible enough to recognize and integrate specific external signals that may help the organism to change and adapt to different environments. This compromise between robustness and adaptability has been observed in dynamical systems operating at the brink of a phase transition between order and chaos. Such systems are termed critical. Thus, criticality, a precise, measurable, and well characterized property of dynamical systems, makes it possible for robustness and adaptability to coexist in living organisms. In this work we investigate the dynamical properties of the gene transcription networks reported for S. cerevisiae, E. coli, and B. subtilis, as well as the network of segment polarity genes of D. melanogaster, and the network of flower development of A. thaliana. We use hundreds of microarray experiments to infer the nature of the regulatory interactions among genes, and implement these data into the Boolean models of the genetic networks. Our results show that, to the best of the current experimental data available, the five networks under study indeed operate close to criticality. The generality of this result suggests that criticality at the genetic level might constitute a fundamental evolutionary mechanism that generates the great diversity of dynamically robust living forms that we observe around us

    Prevalence of Anxiety and Depression among Outpatients with Type 2 Diabetes in the Mexican Population

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    Depression and anxiety are common in diabetic patients; however, in recent years the frequency of these symptoms has markedly increased worldwide. Therefore, it is necessary to establish the frequency and factors associated with depression and anxiety, since they can be responsible for premature morbidity, mortality, risk of developing comorbidities, complications, suffering of patients, as well as escalation of costs. We studied the frequency of depression and anxiety in Mexican outpatients with type 2 diabetes and identified the risk factors for depression and anxiety.We performed a study in 820 patients with type 2 diabetes. The prevalence of depression and anxiety was estimated using the Hamilton Depression Rating Scale and the Hamilton Anxiety Rating Scale, respectively. We calculated the proportions for depression and anxiety and, after adjusting for confounding variables, we performed multivariate analysis using multiple logistic regressions to evaluate the combined effect of the various factors associated with anxiety and depression among persons with type 2 diabetes. The rates for depression and anxiety were 48.27% (95% CI: 44.48–52.06) and 55.10% (95% CI: 51.44–58.93), respectively. Occupation and complications in diabetes were the factors associated with anxiety, whereas glucose level and complications in diabetes were associated with depression. Complications in diabetes was a factor common to depression and anxiety (p<0.0001; OR 1.79, 95% CI 1.29–2.4).Our findings demonstrate that a large proportion of diabetic patients present depression and/or anxiety. We also identified a significant association between complications in diabetes with depression and anxiety. Interventions are necessary to hinder the appearance of complications in diabetes and in consequence prevent depression and anxiety

    Continuous-time modeling of cell fate determination in Arabidopsis flowers

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    <p>Abstract</p> <p>Background</p> <p>The genetic control of floral organ specification is currently being investigated by various approaches, both experimentally and through modeling. Models and simulations have mostly involved boolean or related methods, and so far a quantitative, continuous-time approach has not been explored.</p> <p>Results</p> <p>We propose an ordinary differential equation (ODE) model that describes the gene expression dynamics of a gene regulatory network that controls floral organ formation in the model plant <it>Arabidopsis thaliana</it>. In this model, the dimerization of MADS-box transcription factors is incorporated explicitly. The unknown parameters are estimated from (known) experimental expression data. The model is validated by simulation studies of known mutant plants.</p> <p>Conclusions</p> <p>The proposed model gives realistic predictions with respect to independent mutation data. A simulation study is carried out to predict the effects of a new type of mutation that has so far not been made in <it>Arabidopsis</it>, but that could be used as a severe test of the validity of the model. According to our predictions, the role of dimers is surprisingly important. Moreover, the functional loss of any dimer leads to one or more phenotypic alterations.</p
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