Inference of gene regulatory networks from time series by Tsallis entropy

Background: The inference of gene regulatory networks (GRNs) from large-scale expression profiles is one of the most challenging problems of Systems Biology nowadays. Many techniques and models have been proposed for this task. However, it is not generally possible to recover the original topology with great accuracy, mainly due to the short time series data in face of the high complexity of the networks and the intrinsic noise of the expression measurements. In order to improve the accuracy of GRNs inference methods based on entropy (mutual information), a new criterion function is here proposed. Results: In this paper we introduce the use of generalized entropy proposed by Tsallis, for the inference of GRNs from time series expression profiles. The inference process is based on a feature selection approach and the conditional entropy is applied as criterion function. In order to assess the proposed methodology, the algorithm is applied to recover the network topology from temporal expressions generated by an artificial gene network (AGN) model as well as from the DREAM challenge. The adopted AGN is based on theoretical models of complex networks and its gene transference function is obtained from random drawing on the set of possible Boolean functions, thus creating its dynamics. On the other hand, DREAM time series data presents variation of network size and its topologies are based on real networks. The dynamics are generated by continuous differential equations with noise and perturbation. By adopting both data sources, it is possible to estimate the average quality of the inference with respect to different network topologies, transfer functions and network sizes. Conclusions: A remarkable improvement of accuracy was observed in the experimental results by reducing the number of false connections in the inferred topology by the non-Shannon entropy. The obtained best free parameter of the Tsallis entropy was on average in the range 2.5 <= q <= 3.5 (hence, subextensive entropy), which opens new perspectives for GRNs inference methods based on information theory and for investigation of the nonextensivity of such networks. The inference algorithm and criterion function proposed here were implemented and included in the DimReduction software, which is freely available at http://sourceforge.net/projects/dimreduction and http://code.google.com/p/dimreduction/.

Feature selection environment for genomic applications

Background: Feature selection is a pattern recognition approach to choose important variables according to some criteria in order to distinguish or explain certain phenomena (i.e., for dimensionality reduction). There are many genomic and proteomic applications that rely on feature selection to answer questions such as selecting signature genes which are informative about some biological state, e. g., normal tissues and several types of cancer; or inferring a prediction network among elements such as genes, proteins and external stimuli. In these applications, a recurrent problem is the lack of samples to perform an adequate estimate of the joint probabilities between element states. A myriad of feature selection algorithms and criterion functions have been proposed, although it is difficult to point the best solution for each application. Results: The intent of this work is to provide an open-source multiplataform graphical environment for bioinformatics problems, which supports many feature selection algorithms, criterion functions and graphic visualization tools such as scatterplots, parallel coordinates and graphs. A feature selection approach for growing genetic networks from seed genes ( targets or predictors) is also implemented in the system. Conclusion: The proposed feature selection environment allows data analysis using several algorithms, criterion functions and graphic visualization tools. Our experiments have shown the software effectiveness in two distinct types of biological problems. Besides, the environment can be used in different pattern recognition applications, although the main concern regards bioinformatics tasks.

Characterization of global transcription profile of normal and HPV-immortalized keratinocytes and their response to TNF treatment

Background: Persistent infection by high risk HPV types (e.g. HPV-16, -18, -31, and -45) is the main risk factor for development of cervical intraepithelial neoplasia and cervical cancer. Tumor necrosis factor (TNF) is a key mediator of epithelial cell inflammatory response and exerts a potent cytostatic effect on normal or HPV16, but not on HPV18 immortalized keratinocytes. Moreover, several cervical carcinoma-derived cell lines are resistant to TNF anti-proliferative effect suggesting that the acquisition of TNF-resistance may constitute an important step in HPV-mediated carcinogenesis. In the present study, we compared the gene expression profiles of normal and HPV16 or 18 immortalized human keratinocytes before and after treatment with TNF for 3 or 60 hours. Methods: In this study, we determined the transcriptional changes 3 and 60 hours after TNF treatment of normal, HPV16 and HPV18 immortalized keratinocytes by microarray analysis. The expression pattern of two genes observed by microarray was confirmed by Northern Blot. NF-kappa B activation was also determined by electrophoretic mobility shift assay (EMSA) using specific oligonucleotides and nuclear protein extracts. Results: We observed the differential expression of a common set of genes in two TNF-sensitive cell lines that differs from those modulated in TNF-resistant ones. This information was used to define genes whose differential expression could be associated with the differential response to TNF, such as: KLK7 (kallikrein 7), SOD2 (superoxide dismutase 2), 100P (S100 calcium binding protein P), PI3 (protease inhibitor 3, skin-derived), CSTA (cystatin A), RARRES1 (retinoic acid receptor responder 1), and LXN (latexin). The differential expression of the KLK7 and SOD2 transcripts was confirmed by Northern blot. Moreover, we observed that SOD2 expression correlates with the differential NF-kappa B activation exhibited by TNF-sensitive and TNF-resistant cells. Conclusion: This is the first in depth analysis of the differential effect of TNF on normal and HPV16 or HPV18 immortalized keratinocytes. Our findings may be useful for the identification of genes involved in TNF resistance acquisition and candidate genes which deregulated expression may be associated with cervical disease establishment and/or progression.

Bothrops jararaca Peptide with Anti-Hypertensive Action Normalizes Endothelium Dysfunction Involved in Physiopathology of Preeclampsia

Preeclampsia, a pregnancy-specific syndrome characterized by hypertension, proteinuria and edema, is a major cause of fetal and maternal morbidity and mortality especially in developing countries. Bj-PRO-10c, a proline-rich peptide isolated from Bothrops jararaca venom, has been attributed with potent anti-hypertensive effects. Recently, we have shown that Bj-PRO-10c-induced anti-hypertensive actions involved NO production in spontaneous hypertensive rats. Using in vitro studies we now show that Bj-PRO-10c was able to increase NO production in human umbilical vein endothelial cells from hypertensive pregnant women (HUVEC-PE) to levels observed in HUVEC of normotensive women. Moreover, in the presence of the peptide, eNOS expression as well as argininosuccinate synthase activity, the key rate-limiting enzyme of the citrulline-NO cycle, were enhanced. In addition, excessive superoxide production due to NO deficiency, one of the major deleterious effects of the disease, was inhibited by Bj-PRO-10c. Bj-PRO-10c induced intracellular calcium fluxes in both, HUVEC-PE and HUVEC, which, however, led to activation of eNOS expression only in HUVEC-PE. Since Bj-PRO-10c promoted biological effects in HUVEC from patients suffering from the disorder and not in normotensive pregnant women, we hypothesize that Bj-PRO-10c induces its anti-hypertensive effect in mothers with preeclampsia. Such properties may initiate the development of novel therapeutics for treating preeclampsia.

Thermo-solvatochromism in binary mixtures of water and ionic liquids: on the relative importance of solvophobic interactions

The thermo-solvatochromism of 2,6-dibromo-4-[(E)-2-(1-methylpyridinium-4-yl)ethenyl] phenolate, MePMBr(2), has been studied in mixtures of water, W, with ionic liquids, ILs, in the temperature range of 10 to 60 degrees C, where feasible. The objectives of the study were to test the applicability of a recently introduced solvation model, and to assess the relative importance of solute-solvent solvophobic interactions. The ILs were 1-allyl-3-alkylimidazolium chlorides, where the alkyl groups are methyl, 1-butyl, and 1-hexyl, respectively. The equilibrium constants for the interaction of W and the ILs were calculated from density data; they were found to be linearly dependent on N(C), the number of carbon atoms of the alkyl group; van't Hoff equation (log K versus 1/T) applied satisfactorily. Plots of the empirical solvent polarities, E(T) (MePMBr(2)) in kcal mol(-1), versus the mole fraction of water in the binary mixture, chi(w), showed non-linear, i.e., non-ideal behavior. The dependence of E(T) (MePMBr(2)) on chi(w), has been conveniently quantified in terms of solvation by W, IL, and the ""complex"" solvent IL-W. The non-ideal behavior is due to preferential solvation by the IL and, more efficiently, by IL-W. The deviation from linearity increases as a function of increasing N(C) of the IL, and is stronger than that observed for solvation of MePMBr(2) by aqueous 1-propanol, a solvent whose lipophilicity is 12.8 to 52.1 times larger than those of the ILs investigated. The dependence on N(C) is attributed to solute-solvent solvophobic interactions, whose relative contribution to solvation are presumably greater than that in mixtures of water and 1-propanol.

A new approach for in vitro bioassay to measure tannin biological effects based on a gas production technique

The aim of this paper was to study a method based on gas production technique to measure the biological effects of tannins on rumen fermentation. Six feeds were used as fermentation substrates in a semi-automated gas method: feed A - aroeira (Astronium urundeuva); feed B - jurema preta (Mimosa hostilis), feed C - sorghum grains (Sorghum bicolor); feed D - Tifton-85 (Cynodon sp.); and two others prepared mixing 450 g sorghum leaves, 450 g concentrate (maize and soybean meal) and 100 g either of acacia (Acacia mearnsii) tannin extract (feed E) or quebracho (Schinopsis lorentzii) tannin extract (feed F) per kg (w:w). Three assays were carried out to standardize the bioassay for tannins. The first assay compared two binding agents (polyethylene glycol - PEG - and polyvinyl polypirrolidone - PVPP) to attenuate the tannin effects. The complex formed by PEG and tannins showed to be more stable than PVPP and tannins. Then, in the second assay, PEG was used as binding agent, and this assay was done to evaluate levels of PEG (0, 500, 750, 1000 and 1250 mg/g DM) to minimize the tannin effect. All the tested levels of PEG produced a response to evaluate tannin effects but the best response was for dose of 1000 mg/g DM. Using this dose of PEG, the final assay was carried out to test three compounds (tannic acid, quebracho extract and acacia extract) to establish a curve of biological equivalent effect of tannins. For this, five levels of each compound were added to I g of a standard feed (Lucerne hay). The equivalent effect showed not to be directly related to the chemical analysis for tannins. It was shown that different sources of tannins had different activities or reactivities. The curves of biological equivalence can provide information about tannin reactivity and its use seems to be important as an additional factor for chemical analysis. (C) 2007 Elsevier B.V. All rights reserved.

Effect of some essential oils on in vitro methane emission

The objectives of this study were to characterise four essential oils (EO) chemically and to evaluate their effect on ruminal fermentation and methane emission in vitro. The investigated EO were isolated from Achillea santolina, Artemisia judaica, Schinus terebinthifolius and Mentha microphylla, and supplemented at four levels (0, 25, 50 and 75 l) to 75ml of buffered rumen fluid plus 0.5 g of substrate. The main components of the EO were piperitone (49.1%) and camphor (34.5%) in A. judaica, 16-dimethyl 15-cyclooactdaiene (60.5%) in A. santolina, piperitone oxide (46.7%) and cis-piperitone oxide (28%) in M. microphylla, and -muurolene (45.3%) and -thujene (16.0%) in S. terebinthifolius. The EO from A. santolina (at 25 and 50 l), and all levels of A. judaica increased the gas production significantly, but S. terebinthifolius (at 50 and 75 l), A. santolina (at 75 l) and all levels of M. microphylla decreased the gas production significantly in comparison with the control. The highest levels of A. santolina and A. judaica, and all doses from M. microphylla EO inhibited the methane production along with a significant reduction in true degradation of dry matter and organic matter, protozoa count and NH3-N concentration. It is concluded that the evaluated EO have the potential to affect ruminal fermentation efficiency and the EO from M. microphylla could be a promising methane mitigating agent.

Fertilizers applied to certified organic tomato culture

The tomato culture demands large quantities of mineral nutrients, which are supplied by synthetic fertilizers in the conventional cultivation system. In the organic cultivation system only alternative fertilizers are allowed by the certifiers and accepted as safe for humans and environment. The chemical composition of rice bran, oyster flour, cattle manure and ground charcoal, as well as soils and tomato fruits were evaluated by instrumental neutron activation analysis (INAA). The potential contribution of organic fertilizers to the enrichment of chemical elements in soil and their transfer to fruits was investigated using concentration ratios for fertilizer and soil samples, and also for soil and tomato. Results evidenced that these alternative fertilizers could be taken as important sources of Br, Ca, Ce, K, Na and Zn for the organic tomato culture.

Chemical characterization of agricultural supplies applied to organic tomato cultivation

The agricultural supplies used in the organic system to control pests and diseases as well as to fertilize soil are claimed to be beneficial to plants and innocuous to human health and to the environment. The chemical composition of six agricultural supplies commonly used in the organic tomato culture, was evaluated by instrumental neutron activation analysis (INAA). Results were compared to the maximum limits established by the Environment Control Agency of the Sao Paulo State (CETESB) and the Guidelines for Organic Quality Standard of Instituto Biodinamico (IBD). Concentrations above reference values were found for Co, Cr and Zn in compost, Cr and Zn in cattle manure and Zn in rice bran.

Chemical composition of tomato seeds affected by conventional and organic production systems

Tomato is amongst the most consumed vegetables in the world, not only for its culinary versatility but also for its high nutritional value. In the last years, consumers have shown an increased concern regarding food origin and safety. The organic tomato production has been a promising alternative for the consumer offering a safer food in relation to environmental, social and nutritional aspects. This study assessed the chemical composition of tomato seeds produced in both conventional and organic systems by INAA. The results showed significant differences (P <= 0.05) in the mass fractions of Br, Cs, Eu, Fe, K, Mo, Na, Rb and Sm between both systems, indicating influence of the crop management adopted in the different tomato production systems.

An opinion dynamics model for the diffusion of innovations

We study the dynamics of the adoption of new products by agents with continuous opinions and discrete actions (CODA). The model is such that the refusal in adopting a new idea or product is increasingly weighted by neighbor agents as evidence against the product. Under these rules, we study the distribution of adoption times and the final proportion of adopters in the population. We compare the cases where initial adopters are clustered to the case where they are randomly scattered around the social network and investigate small world effects on the final proportion of adopters. The model predicts a fat tailed distribution for late adopters which is verified by empirical data. (C) 2009 Elsevier B.V. All rights reserved.

Multifractality in the random parameter model for multivariate time series

The Random Parameter model was proposed to explain the structure of the covariance matrix in problems where most, but not all, of the eigenvalues of the covariance matrix can be explained by Random Matrix Theory. In this article, we explore the scaling properties of the model, as observed in the multifractal structure of the simulated time series. We use the Wavelet Transform Modulus Maxima technique to obtain the multifractal spectrum dependence with the parameters of the model. The model shows a scaling structure compatible with the stylized facts for a reasonable choice of the parameter values. (C) 2009 Elsevier B.V. All rights reserved.

Bayesian updating rules in continuous opinion dynamics models

Here, I investigate the use of Bayesian updating rules applied to modeling how social agents change their minds in the case of continuous opinion models. Given another agent statement about the continuous value of a variable, we will see that interesting dynamics emerge when an agent assigns a likelihood to that value that is a mixture of a Gaussian and a uniform distribution. This represents the idea that the other agent might have no idea about what is being talked about. The effect of updating only the first moments of the distribution will be studied, and we will see that this generates results similar to those of the bounded confidence models. On also updating the second moment, several different opinions always survive in the long run, as agents become more stubborn with time. However, depending on the probability of error and initial uncertainty, those opinions might be clustered around a central value.

Continuous opinions and discrete actions in opinion dynamics problems

A model where agents show discrete behavior regarding their actions, but have continuous opinions that are updated by interacting with other agents is presented. This new updating rule is applied to both the voter and Sznajd models for interaction between neighbors, and its consequences are discussed. The appearance of extremists is naturally observed and it seems to be a characteristic of this model.

MODELING SCIENTIFIC AGENTS FOR A BETTER SCIENCE

Science is a fundamental human activity and we trust its results because it has several error-correcting mechanisms. It is subject to experimental tests that are replicated by independent parts. Given the huge amount of information available and the information asymetry between producers and users of knowledge, scientists have to rely on the reports of others. This makes it possible for social effects to influence the scientific community. Here, an Opinion Dynamics agent model is proposed to describe this situation. The influence of Nature through experiments is described as an external field that acts on the experimental agents. We will see that the retirement of old scientists can be fundamental in the acceptance of a new theory. We will also investigate the interplay between social influence and observations. This will allow us to gain insight in the problem of when social effects can have negligible effects in the conclusions of a scientific community and when we should worry about them.