Descripción: Osmolarity not only plays a key role in celluar homeostasis but also challenges cell survival. The molecular understanding of osmosis has not yet been completely achieved, and the discovery of aquaporins as molecular entities involved in water transport has caused osmosis to again become a focus of research. The main questions that need to be answered are the mechanism underlying the osmotic permeability coefficients and the extent to which aquaporins change our understanding of osmosis. Here, attempts to answer these questions are discussed. Critical aspects of the state of the state of knowledge on osmosis, a topic that has been studied since 19th century, are reviewed and integrated with the available information provided by in vivo, in vitro and in silico approaches. © 2012 Federation of European Biochemical Societies. Published by Elsevier B.V. All rights reserved.

Descripción: Background: Alzheimer's disease (AD) is characterized by a neurodegenerative progression that alters cognition. On a phenotypical level, cognition is evaluated by means of the MiniMental State Examination (MMSE) and the post-morten examination of Neurofibrillary Tangle count (NFT) helps to confirm an AD diagnostic. The MMSE evaluates different aspects of cognition including orientation, short-term memory (retention and recall), attention and language. As there is a normal cognitive decline with aging, and death is the final state on which NFT can be counted, the identification of brain gene expression biomarkers from these phenotypical measures has been elusive. Methodology/Principal Findings: We have reanalysed a microarray dataset contributed in 2004 by Blalock et al. of 31 samples corresponding to hippocampus gene expression from 22 AD subjects of varying degree of severity and 9 controls. Instead of only relying on correlations of gene expression with the associated MMSE and NFT measures, and by using modern bioinformatics methods based on information theory and combinatorial optimization, we uncovered a 1,372-probe gene expression signature that presents a high-consensus with established markers of progression in AD. The signature reveals alterations in calcium, insulin, phosphatidylinositol and wnt-signalling. Among the most correlated gene probes with AD severity we found those linked to synaptic function, neurofilament bundle assembly and neuronal plasticity. Conclusions/Significance: A transcription factors analysis of 1,372-probe signature reveals significant associations with the EGR/KROX family of proteins, MAZ, and E2F1. The gene homologous of EGR1, zif268, Egr-1 or Zenk, together with other members of the EGR family, are consolidating a key role in the neuronal plasticity in the brain. These results indicate a degree of commonality between putative genes involved in AD and prion-induced neurodegenerative processes that warrants further investigation. © 2010 Go ́mez Ravetti et al.

Descripción: Alternative splicing plays a key role in generating protein diversity. Transfections with minigenes revealed coordination between two distant, alternatively spliced exons in the same gene. Mutations that either inhibit or stimulate inclusion of the upstream alternative exon deeply affect inclusion of the downstream one. However, similar mutations at the downstream alternative exon have little effect on the upstream one. This polar effect is promoter specific and is enhanced by inhibition of transcriptional elongation. Consistently, cells from mutant mice with either constitutive or null inclusion of a fibronectin alternative exon revealed coordination with a second alternative splicing region, located far downstream. Using allele-specific RT-PCR, we demonstrate that this coordination occurs in cis and is also affected by transcriptional elongation rates. Bioinformatics supports the generality of these findings, indicating that 25% of human genes contain multiple alternative splicing regions and identifying several genes with nonrandom distribution of mRNA isoforms at two alternative regions. Copyright ©2005 by Elsevier Inc.

Descripción: Background: The vast computational resources that became available during the past decade enabled the development and simulation of increasingly complex mathematical models of cancer growth. These models typically involve many free parameters whose determination is a substantial obstacle to model development. Direct measurement of biochemical parameters in vivo is often difficult and sometimes impracticable, while fitting them under data-poor onditions may result in biologically implausible values. Results: We discuss different methodological approaches to estimate parameters in complex biological models. We make use of the high computational power of the Blue Gene technology to perform an extensive study of the parameter space in a model of avascular tumor growth. We explicitly show that the landscape of the cost function used to optimize the model to the data has a very rugged surface in parameter space. This cost function has many local minima with unrealistic solutions, including the global minimum corresponding to the best fit. Conclusions: The case studied in this paper shows one example in which model parameters that optimally fit the data are not necessarily the best ones from a biological point of view. To avoid force-fitting a model to a dataset, we propose that the best model parameters should be found by choosing, among suboptimal parameters, those that match criteria other than the ones used to fit the model. We also conclude that the model, data and optimization approach form a new complex system and point to the need of a theory that addresses this problem more generally. © 2010 Fernandez Slezak et al.