Could NCOA5 a novel candidate gene for multiple sclerosis susceptibility?

BACKGROUND: Multiple sclerosis (MS) is an inflammatory immune-mediated demyelinating disease that causes a challenging and disabling condition. Environmental and genetic factors play a role in appearing the state of the disease. Recent studies have shown that nuclear cofactor genes may play a role in the pathogenesis of MS. NCOA5 is a nuclear receptor coactivator independent of AF2 that modulates ERa-mediated transcription. This gene is involved in the pathogenesis of diseases such as psoriasis, Behcet's disease, and cancer. METHODS AND RESULTS: We investigated the relationship between the rs2903908 polymorphism of the NCOA5 gene and MS among 157 unrelated MS patients and 160 healthy controls by RT-PCR. The frequencies of the CC, CT, and TT genotypes were 19.87%, 37.82%, and 42.31%, respectively, for the MS group and 5.63%, 43.75%, and 50.62%, respectively, for the control group. The CC genotype and the C allele were found to be significantly higher in the patient group (the p values were 0.0002 and 0.003, respectively). CONCLUSIONS: The fact that the CC genotype was found to be significantly higher in the patient group compared to the control group (p = 0.0002) and that it had a statistically significantly higher OR value (OR, 95% CI = 4.16, 1.91-9.05) suggests that the C allele may recessively predispose to MS for this polymorphism. These results suggest for the first time that the NCOA5 gene may have an effect on the occurrence of MS through different molecular pathways, which are discussed in the manuscript.

Comparison of Oleo- vs Petro-Sourcing of Fatty Alcohols via Cradle-to-Gate Life Cycle Assessment.

Alcohol ethoxylates surfactants are produced via ethoxylation of fatty alcohol (FA) with ethylene oxide. The source of FA could be either palm kernel oil (PKO) or petrochemicals. The study aimed to compare the potential environmental impacts for PKO-derived FA (PKO-FA) and petrochemicals-derived FA (petro-FA). Cradle-to-gate life cycle assessment has been performed for this purpose because it enables understanding of the impacts across the life cycle and impact categories. The results show that petro-FA has overall lower average greenhouse gas (GHG) emissions (~2.97 kg CO2e) compared to PKO-FA (~5.27 kg CO2e). (1) The practices in land use change for palm plantations, (2) end-of-life treatment for palm oil mill wastewater effluent and (3) end-of-life treatment for empty fruit bunches are the three determining factors for the environmental impacts of PKO-FA. For petro-FA, n-olefin production, ethylene production and thermal energy production are the main factors. We found the judicious decisions on land use change, effluent treatment and solid waste treatment are key to making PKO-FA environmentally sustainable. The sensitivity results show the broad distribution for PKO-FA due to varying practices in palm cultivation. PKO-FA has higher impacts on average for 12 out of 18 impact categories evaluated. For the base case, when accounted for uncertainty and sensitivity analyses results, the study finds that marine eutrophication, agricultural land occupation, natural land occupation, fossil depletion, particulate matter formation, and water depletion are affected by the sourcing decision. The sourcing of FA involves trade-offs and depends on the specific practices through the PKO life cycle from an environmental impact perspective.

Maximum likelihood estimation of the kinetics of receptor-mediated adhesion.

Adhesion flow assays are commonly employed to characterize the kinetics and force-dependence of receptor-ligand interactions. As transient cellular adhesion events are often mediated by a small number of receptor-ligand complexes (tether bonds) their durations are highly variable, which in turn presents obstacles to standard methods of analysis. In this paper, we employ the stochastic approach to chemical kinetics to construct the pause time distribution. Using this distribution, we develop a robust maximum likelihood (ML) approach to the robust estimation of rate constants associated with receptor-mediated transient adhesion and their confidence intervals. We then formulate robust estimators of the parameters of models for the force-dependence of the off-rate. Lastly, we develop a robust method of elucidation of the force-dependence of the off-rate using Akaike's information criterion (AIC). Our findings conclusively demonstrate that ML estimators of adhesion kinetics are substantial improvements over more conventional approaches, and when combined with Fisher information, they may be used to objectively and reproducibly distinguish the kinetics of different receptor-ligand complexes. Software for the implementation of these methods with experimental data is publicly available as for download at http://www.laurenzi.net.

An efficient algorithm for the stochastic simulation of the hybridization of DNA to microarrays.

BACKGROUND: Although oligonucleotide microarray technology is ubiquitous in genomic research, reproducibility and standardization of expression measurements still concern many researchers. Cross-hybridization between microarray probes and non-target ssDNA has been implicated as a primary factor in sensitivity and selectivity loss. Since hybridization is a chemical process, it may be modeled at a population-level using a combination of material balance equations and thermodynamics. However, the hybridization reaction network may be exceptionally large for commercial arrays, which often possess at least one reporter per transcript. Quantification of the kinetics and equilibrium of exceptionally large chemical systems of this type is numerically infeasible with customary approaches. RESULTS: In this paper, we present a robust and computationally efficient algorithm for the simulation of hybridization processes underlying microarray assays. Our method may be utilized to identify the extent to which nucleic acid targets (e.g. cDNA) will cross-hybridize with probes, and by extension, characterize probe robustnessusing the information specified by MAGE-TAB. Using this algorithm, we characterize cross-hybridization in a modified commercial microarray assay. CONCLUSIONS: By integrating stochastic simulation with thermodynamic prediction tools for DNA hybridization, one may robustly and rapidly characterize of the selectivity of a proposed microarray design at the probe and "system" levels. Our code is available at http://www.laurenzi.net.

Kinetics of autocatalysis in small systems.

Autocatalysis is a ubiquitous chemical process that drives a plethora of biological phenomena, including the self-propagation of prions etiological to the Creutzfeldt-Jakob disease and bovine spongiform encephalopathy. To explain the dynamics of these systems, we have solved the chemical master equation for the irreversible autocatalytic reaction A+B-->2A. This solution comprises the first closed form expression describing the probabilistic time evolution of the populations of autocatalytic and noncatalytic molecules from an arbitrary initial state. Grand probability distributions are likewise presented for autocatalysis in the equilibrium limit (A+B <==>2A), allowing for the first mechanistic comparison of this process with chemical isomerization (B<==>A) in small systems. Although the average population of autocatalytic (i.e., prion) molecules largely conforms to the predictions of the classical "rate law" approach in time and the law of mass action at equilibrium, thermodynamic differences between the entropies of isomerization and autocatalysis are revealed, suggesting a "mechanism dependence" of state variables for chemical reaction processes. These results demonstrate the importance of chemical mechanism and molecularity in the development of stochastic processes for chemical systems and the relationship between the stochastic approach to chemical kinetics and nonequilibrium thermodynamics.

Mechanical properties and biocompatibility of plasma-nitrided laser-cut 316L cardiovascular stents.

The effect of surface modification of laser-cut 316L cardiovascular stents by low-T plasma nitriding was evaluated in terms of mechanical properties and biocompatibility of the stents. The plasma nitriding was performed at 400, 450 or 500 degrees C using various ratios of nitrogen-hydrogen gas mixtures. The flexibility and radial strength were measured in crimped and expanded state of the stents, respectively. The mechanical properties could be adjusted and improved by plasma nitriding conducted at temperatures lower than 450 degrees C and/or nitrogen content less than 10% in the treatment gas. An osteoblast cell culture model system was utilized to investigate the effect of plasma nitriding of the stents on the biological response towards the stents, using biological criteria such as cell viability, alkaline phosphatase and nitric oxide production. In terms of cell viability and alkaline phosphatase production, the plasma nitriding procedure did not appear to negatively affect the biocompatibility of the 316L steel stents. However, in terms of nitric oxide production that was slightly increased in the presence of the plasma-nitrided stents, an indirect improvement in the biocompatibility could possibly be expected.