Matrix and Tensor Factorization Methods for Toxicogenomic Modeling and Prediction

Peer reviewe

Hypofibrinolysis in diabetes: a therapeutic target for the reduction of cardiovascular risk

An enhanced thrombotic environment and premature atherosclerosis are key factors for the increased cardiovascular risk in diabetes. The occlusive vascular thrombus, formed secondary to interactions between platelets and coagulation proteins, is composed of a skeleton of fibrin fibres with cellular elements embedded in this network. Diabetes is characterised by quantitative and qualitative changes in coagulation proteins, which collectively increase resistance to fibrinolysis, consequently augmenting thrombosis risk. Current long-term therapies to prevent arterial occlusion in diabetes are focussed on anti-platelet agents, a strategy that fails to address the contribution of coagulation proteins to the enhanced thrombotic milieu. Moreover, antiplatelet treatment is associated with bleeding complications, particularly with newer agents and more aggressive combination therapies, questioning the safety of this approach. Therefore, to safely control thrombosis risk in diabetes, an alternative approach is required with the fibrin network representing a credible therapeutic target. In the current review, we address diabetes-specific mechanistic pathways responsible for hypofibrinolysis including the role of clot structure, defects in the fibrinolytic system and increased incorporation of anti-fibrinolytic proteins into the clot. Future anti-thrombotic therapeutic options are discussed with special emphasis on the potential advantages of modulating incorporation of the anti-fibrinolytic proteins into fibrin networks. This latter approach carries theoretical advantages, including specificity for diabetes, ability to target a particular protein with a possible favourable risk of bleeding. The development of alternative treatment strategies to better control residual thrombosis risk in diabetes will help to reduce vascular events, which remain the main cause of mortality in this condition

extraction parameters and mass transfer modeling

Supercritical carbon dioxide (SC-CO2) extraction of flaxseed oil was performed and effects of process parameters including particle size (mean particle diameter <0.85-0.92 mm), solvent flow rate (2-4 g/min), pressure (40-60 MPa) and temperature (50-70 degrees C) were investigated. The broken and intact cells (BIC) model was used for mass transfer modeling of the extraction of flaxseed oil with SC-CO2 successfully. Extraction of flaxseed oil was divided into two periods as first (fast) and second (slow) extraction periods. Great part of the flaxseed oil was extracted in the first period and a very small amount was extracted in the second period. Decreasing the particle size increased the amount of released (free) oil. Increasing the pressure, temperature and flow rate also caused slight increases in the released oil amounts. Increase in the solvent flow rate, pressure and temperature increased the extraction rate in the first period within the range of experiments. The fluid phase mass transfer coefficient (k(f)a) varied between 0.38 and 2.32 min(-1) and the solid phase mass transfer coefficient (k(s)a) varied between 0.5 x 10(-3) and 6.7 x 10(-3) min(-1). (C) 2016 Elsevier B.V. All rights reserved

The solubility of apricot kernel oil in supercritical carbon dioxide

The solubility of kernel oil from apricots (Prunus armeniaca L.) in supercritical carbon dioxide at 313.15, 323.15 and 333.15 K and at 15, 30, 45, 52.5 and 60 MPa was determined. Appropriate models were fitted to the data and the crossover pressure of apricot kernel oil was found to be between 20 and 30 MPa. Crossover pressure is a pressure value at which the effect of temperature on the solubility changes. Solubility increased as the temperature increased above the crossover pressure but decreased when temperature increased below the crossover pressure. It increased with an increase in pressure over all of the temperature range. The solubility data were well represented by models based on density but the best was found to be the Adachi & Lu equation. An empirical model that did not require density data for CO2 was proposed to relate solubility to temperature and pressure and it was found equally successful to the Adachi & Lu equation

Sensory evoked and event related oscillations in Alzheimer’s disease: a short review

Diagnosis and treatment of Alzheimer’s disease (AD) depend on clinical evaluation and there is a strong need for an objective tool as a biomarker. Our group has investigated brain oscillatory responses in a small group of AD subjects. We found that the de novo (untreated) AD group differs from both the cholinergically-treated AD group and aged-matched healthy controls in theta and delta responses over left frontal-central areas after cognitive stimulation. On the contrary, the difference observed in AD groups upon a sensory visual stimulation includes response increase over primary or secondary visual sensorial areas compared to controls. These findings imply at least two different neural networks, depending on type of stimulation (i.e. cognitive or sensory). The default mode defined as activity in resting state in AD seems to be affected electrophysiologically. Coherences are also very valuable in observing the group differences, especially when a cognitive stimulus is applied. In healthy controls, higher coherence values are elicited after a cognitive stimulus than after a sensory task. Our findings support the notion of disconnectivity of cortico-cortical connections in AD. The differences in comparison of oscillatory responses upon sensory and cognitive stimulations and their role as a biomarker in AD await further investigation in series with a greater number of subjects