A reliable measure of similarity based on dependency for short time series: an application to gene expression networks

Background: Microarray techniques have become an important tool to the investigation of genetic relationships and the assignment of different phenotypes. Since microarrays are still very expensive, most of the experiments are performed with small samples. This paper introduces a method to quantify dependency between data series composed of few sample points. The method is used to construct gene co-expression subnetworks of highly significant edges. Results: The results shown here are for an adapted subset of a Saccharomyces cerevisiae gene expression data set with low temporal resolution and poor statistics. The method reveals common transcription factors with a high confidence level and allows the construction of subnetworks with high biological relevance that reveals characteristic features of the processes driving the organism adaptations to specific environmental conditions. Conclusion: Our method allows a reliable and sophisticated analysis of microarray data even under severe constraints. The utilization of systems biology improves the biologists ability to elucidate the mechanisms underlying celular processes and to formulate new hypotheses.

Shallow landslide prediction in the Serra do Mar, Sao Paulo, Brazil

Various methods are currently used in order to predict shallow landslides within the catchment scale. Among them, physically based models present advantages associated with the physical description of processes by means of mathematical equations. The main objective of this research is the prediction of shallow landslides using TRIGRS model, in a pilot catchment located at Serra do Mar mountain range, Sao Paulo State, southeastern Brazil. Susceptibility scenarios have been simulated taking into account different mechanical and hydrological values. These scenarios were analysed based on a landslide scars map from the January 1985 event, upon which two indexes were applied: Scars Concentration (SC - ratio between the number of cells with scars, in each class, and the total number of cells with scars within the catchment) and Landslide Potential (LP - ratio between the number of cells with scars, in each class, and the total number of cells in that same class). The results showed a significant agreement between the simulated scenarios and the scar's map. In unstable areas (SF <= 1), the SC values exceeded 50% in all scenarios. Based on the results, the use of this model should be considered an important tool for shallow landslide prediction, especially in areas where mechanical and hydrological properties of the materials are not well known.

Adipose Tissue-Derived Stem Cells from Humans and Mice Differ in Proliferative Capacity and Genome Stability in Long-Term Cultures

Adipose tissue-derived stem cells (ASCs) are among the more attractive adult stem cell options for potential therapeutic applications. Here, we studied and compared the basic biological characteristics of ASCs isolated from humans (hASCs) and mice (mASCs) and maintained in identical culture conditions, which must be examined prior to considering further potential clinical applications. hASCs and mASCs were compared for immunophenotype, differentiation potential, cell growth characteristics, senescence, nuclear morphology, and DNA content. Although both strains of ASCs displayed a similar immunophenotype, the percentage of CD73(+) cells was markedly lower and CD31(+) was higher in mASC than in hASC cultures. The mean population doubling time was 98.08 +/- 6.15 h for hASCs and 52.58 +/- 3.74 h for mASCs. The frequency of nuclear aberrations was noticeably lower in hASCs than in mASCs regardless of the passage number. Moreover, as the cells went through several in vitro passages, mASCs showed changes in DNA content and cell cycle kinetics (frequency of hypodiploid, G0/G1, G2/M, and hyperdiploid cells), whereas all of these parameters remained constant in hASCs. Collectively, these results suggest that mASCs display higher proliferative capacity and are more unstable than hASCs in long-term cultures. These results underscore the need to consider specificities among model systems that may influence outcomes when designing potential human applications.

Evaluating Patellar Kinematics Through Magnetic Resonance Imaging During Open- and Closed-Kinetic-Chain Exercises

Purpose: To evaluate patellar kinematics of volunteers Without knee pain at rest and during isometric contraction in open- and closed-kinetic-chain exercises. Methods: Twenty individuals took part in this study. All were submitted to magnetic resonance imaging (MRI) during rest and voluntary isometric contraction (VIC) in the open anti closed kinetic chain at 15 degrees, 30 degrees, and 45 degrees of knee flexion. Through MRI and using medical e-film software, the following measurements were evaluated: sulcus angle, patellar-tilt angle, and bisect offset. The mixed-effects linear model was used for comparison between knee positions, between rest and isometric contractions, and between (he exercises. Results: Data analysis revealed that the sulcus angle decreased as knee flexion increased and revealed increases with isometric contractions in both the open and closed kinetic chain for all knee-flexion angles. The patellar-tilt angle decreased with isometric contractions in both the open and closed kinetic chain for every knee position. However, in the closed kinetic chain, patellar tilt increased significantly with the knee flexed at 15 degrees. The bisect offset increased with the knee flexed at 15 degrees during isometric contractions and decreased as knee flexion increased during both exercises. Conclusion: VIC in the last degrees of knee extension may compromise patellar dynamics. On the other hand, it is possible to favor patellar stability by performing muscle contractions with the knee flexed at 30 degrees and 45 degrees in either the open or closed kinetic chain.