Circadian Rhythm and Pain: Mathematical Model based on Multiagent Simulation.

The circadian rhythm is responsible for the daily variations in metabolism, and circadian rhythm disorders have direct implications for many diseases, such as obesity and mental disorders. The regulation of sleep time is the most common example of the importance of the circadian rhythm for the functioning of the human body. In this sense, this work aims to study a mathematical and computational model based on multiagent simulation that simulates the synchronization and desynchronization of the circadian rhythm in relation to the pain variables. The results from the multiagent simulation of circadian rhythms show that in relation to pain, sleep, especially its biological rhythms, is directly affected by pain. In this way, our mathematical model was able to show that pain causes changes in the circadian rhythm and it can contribute to the medical field analysis.

The semantic web in translational medicine: current applications and future directions.

Semantic web technologies offer an approach to data integration and sharing, even for resources developed independently or broadly distributed across the web. This approach is particularly suitable for scientific domains that profit from large amounts of data that reside in the public domain and that have to be exploited in combination. Translational medicine is such a domain, which in addition has to integrate private data from the clinical domain with proprietary data from the pharmaceutical domain. In this survey, we present the results of our analysis of translational medicine solutions that follow a semantic web approach. We assessed these solutions in terms of their target medical use case; the resources covered to achieve their objectives; and their use of existing semantic web resources for the purposes of data sharing, data interoperability and knowledge discovery. The semantic web technologies seem to fulfill their role in facilitating the integration and exploration of data from disparate sources, but it is also clear that simply using them is not enough. It is fundamental to reuse resources, to define mappings between resources, to share data and knowledge. All these aspects allow the instantiation of translational medicine at the semantic web-scale, thus resulting in a network of solutions that can share resources for a faster transfer of new scientific results into the clinical practice. The envisioned network of translational medicine solutions is on its way, but it still requires resolving the challenges of sharing protected data and of integrating semantic-driven technologies into the clinical practice.

Enrichment analysis applied to disease prognosis.

: Enrichment analysis is well established in the field of transcriptomics, where it is used to identify relevant biological features that characterize a set of genes obtained in an experiment.This article proposes the application of enrichment analysis as a first step in a disease prognosis methodology, in particular of diseases with a strong genetic component. With this analysis the objective is to identify clinical and biological features that characterize groups of patients with a common disease, and that can be used to distinguish between groups of patients associated with disease-related events. Data mining methodologies can then be used to exploit those features, and assist medical doctors in the evaluation of the patients in respect to their predisposition for a specific event.In this work the disease hypertrophic cardiomyopathy (HCM) is used as a case-study, as a first test to assess the feasibility of the application of an enrichment analysis to disease prognosis. To perform this assessment, two groups of patients have been considered: patients that have suffered a sudden cardiac death episode and patients that have not.The results presented were obtained with genetic data and the Gene Ontology, in two enrichment analyses: an enrichment profiling aiming at characterizing a group of patients (e.g. that suffered a disease-related event) based on their mutations; and a differential enrichment aiming at identifying differentiating features between a sub-group of patients and all the patients with the disease. These analyses correspond to an adaptation of the standard enrichment analysis, since multiple sets of genes are being considered, one for each patient.The preliminary results are promising, as the sets of terms obtained reflect the current knowledge about the gene functions commonly altered in HCM patients, thus allowing their characterization. Nevertheless, some factors need to be taken into consideration before the full potential of the enrichment analysis in the prognosis methodology can be evaluated. One of such factors is the need to test the enrichment analysis with clinical data, in addition to genetic data, since both types of data are expected to be necessary for prognosis purposes.

Two traditional maize inbred lines of contrasting technological abilities are discriminated by the seed flour proteome.

The seed proteome of two traditional maize inbred lines (pb269 and pb369) contrasting in grain hardness and in preferable use for bread-making was evaluated. The pb269 seeds, of flint type (i.e., hard endosperm), are preferably used by manufacturers, while pb369 (dent, soft endosperm) is rejected. The hypothesis that the content and relative amounts of specific proteins in the maize flour are relevant for such discrimination of the inbred lines was tested. The flour proteins were sequentially extracted following the Osborne fractionation (selective solubilization), and the four Osborne fractions were submitted to two-dimensional electrophoresis (2DE). The total amount of protein extracted from the seeds was not significantly different, but pb369 flour exhibited significantly higher proportions of salt-extracted proteins (globulins) and ethanol-extracted proteins (alcohol-soluble prolamins). The proteome analysis allowed discrimination between the two inbred lines, with pb269 demonstrating higher heterogeneity than pb369. From the 967 spots (358 common to both lines, 208 specific to pb269, and 401 specific to pb369), 588 were submitted to mass spectrometry (MS). Through the combined use of trypsin and chymotrypsin it was possible to identify proteins in 436 spots. The functional categorization in combination with multivariate analysis highlighted the most discriminant biological processes (carbohydrate metabolic process, response to stress, chitin catabolic process, oxidation-reduction process) and molecular function (nutrient reservoir activity). The inbred lines exhibited quantitative and qualitative differences in these categories. Differences were also revealed in the amounts, proportions, and distribution of several groups of storage proteins, which can have an impact on the organization of the protein body and endosperm hardness. For some proteins (granule-bound starch synthase-1, cyclophilin, zeamatin), a change in the protein solubility rather than in the total amount extracted was observed, which reveals distinct in vivo associations and/or changes in binding strength between the inbred lines. Our approach produced information that relates protein content, relative protein content, and specific protein types to endosperm hardness and to the preferable use for "broa" bread-making.