Phosphomolybdic Acid Catalysis of Cellulose Hydrolysis

Renewable sources such as cellulose derived biofuels are sought after in order to replace fossil fuel sources that are currently used to meet energy demands. Cellulose is a biological polymer composed of a chain of glucose molecules. Hydrolysis of cellulosic materials then has potential to serve as a source of renewable energy in the form of biofuels. The crystalline structure of cellulose is very stable, and current methods of catalyzed hydrolysis are inefficient for industrial application. This project explores the use of phosphomolybdic acid (PMA) in water to catalyze hydrolysis of microcrystalline cellulose. Temperature of hydrolysis was varied from 40 °C – 100 °C. The amount of soluble hydrolysis product was determined through wet oxidative total organic carbon analysis using a Hach method kit. Total organic carbon content is compared between equimolar amounts of PMA and sulfuric acid, the current industry preference. The yield of total organic carbon in parts per thousand (ppt) is directly correlated to increasing temperatures. Across these temperatures, PMA is more efficient than sulfuric acid in hydrolysis of cellulosic materials. Work is ongoing for glucose-specific product detection as well as evaluating the recyclability of the catalyst

A Study of Socialism in the Contemporary British Novel

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Secure Mobile Support of Independent Sales Agencies

Sales agents depend on mobile support systems for their daily work. Independent sales agencies, however, are not able to facilitate this kind of mobile support on their own due to their small size and lack of the necessary funds. Since their processes correlate with confidential information and include the initiation and alteration of legally binding transactions they have a high need for security. In this contribution we first propose an IT-artifact consisting of a service platform that supports multi-vendor sales processes based on previous work. We then analyze use cases of sales representatives of independent sales agencies using this system and derive their security requirements. We then propose a security extension to the IT-artifact and evaluate this extension by comparing it to existing solutions. Our results show that the proposed artifact extension provides a more convenient and secure solution than already existing approaches

A multiscale hybrid model for pro-angiogenic calcium signals in a vascular endothelial cell

Cytosolic calcium machinery is one of the principal signaling mechanisms by which endothelial cells (ECs) respond to external stimuli during several biological processes, including vascular progression in both physiological and pathological conditions. Low concentrations of angiogenic factors (such as VEGF) activate in fact complex pathways involving, among others, second messengers arachidonic acid (AA) and nitric oxide (NO), which in turn control the activity of plasma membrane calcium channels. The subsequent increase in the intracellular level of the ion regulates fundamental biophysical properties of ECs (such as elasticity, intrinsic motility, and chemical strength), enhancing their migratory capacity. Previously, a number of continuous models have represented cytosolic calcium dynamics, while EC migration in angiogenesis has been separately approached with discrete, lattice-based techniques. These two components are here integrated and interfaced to provide a multiscale and hybrid Cellular Potts Model (CPM), where the phenomenology of a motile EC is realistically mediated by its calcium-dependent subcellular events. The model, based on a realistic 3-D cell morphology with a nuclear and a cytosolic region, is set with known biochemical and electrophysiological data. In particular, the resulting simulations are able to reproduce and describe the polarization process, typical of stimulated vascular cells, in various experimental conditions.Moreover, by analyzing the mutual interactions between multilevel biochemical and biomechanical aspects, our study investigates ways to inhibit cell migration: such strategies have in fact the potential to result in pharmacological interventions useful to disrupt malignant vascular progressio

Translating genome-wide association findings into new therapeutics for psychiatry

Genome-wide association studies (GWAS) in psychiatry, once they reach sufficient sample size and power, have been enormously successful. The Psychiatric Genomics Consortium (PGC) aims for mega-analyses with sample sizes that will grow to (cumulatively) >1 million individuals in the next 5 years. This should lead to hundreds of new findings for common genetic variants across nine psychiatric disorders studied by the PGC. The new targets discovered by GWAS have the potential to restart largely stalled psychiatric drug development pipelines, and the translation of GWAS findings into the clinic is a key aim of the recently funded phase 3 of the PGC. This is not without considerable technical challenges. These approaches complement the other main aim of GWAS studies on risk prediction approaches for improving detection, differential diagnosis, and clinical trial design. This paper outlines the motivations, technical and analytical issues, and the plans for translating PGC3 findings into new therapeutics

Neurogenesis Drives Stimulus Decorrelation in a Model of the Olfactory Bulb

The reshaping and decorrelation of similar activity patterns by neuronal networks can enhance their discriminability, storage, and retrieval. How can such networks learn to decorrelate new complex patterns, as they arise in the olfactory system? Using a computational network model for the dominant neural populations of the olfactory bulb we show that fundamental aspects of the adult neurogenesis observed in the olfactory bulb -- the persistent addition of new inhibitory granule cells to the network, their activity-dependent survival, and the reciprocal character of their synapses with the principal mitral cells -- are sufficient to restructure the network and to alter its encoding of odor stimuli adaptively so as to reduce the correlations between the bulbar representations of similar stimuli. The decorrelation is quite robust with respect to various types of perturbations of the reciprocity. The model parsimoniously captures the experimentally observed role of neurogenesis in perceptual learning and the enhanced response of young granule cells to novel stimuli. Moreover, it makes specific predictions for the type of odor enrichment that should be effective in enhancing the ability of animals to discriminate similar odor mixtures

A Bayesian approach to modelling heterogeneous calcium responses in cell populations

Calcium responses have been observed as spikes of the whole-cell calcium concentration in numerous cell types and are essential for translating extracellular stimuli into cellular responses. While there are several suggestions for how this encoding is achieved, we still lack a comprehensive theory. To achieve this goal it is necessary to reliably predict the temporal evolution of calcium spike sequences for a given stimulus. Here, we propose a modelling framework that allows us to quantitatively describe the timing of calcium spikes. Using a Bayesian approach, we show that Gaussian processes model calcium spike rates with high fidelity and perform better than standard tools such as peri-stimulus time histograms and kernel smoothing. We employ our modelling concept to analyse calcium spike sequences from dynamically-stimulated HEK293T cells. Under these conditions, different cells often experience diverse stimuli time courses, which is a situation likely to occur in vivo. This single cell variability and the concomitant small number of calcium spikes per cell pose a significant modelling challenge, but we demonstrate that Gaussian processes can successfully describe calcium spike rates in these circumstances. Our results therefore pave the way towards a statistical description of heterogeneous calcium oscillations in a dynamic environmen

TrpC3 Regulates Hypertrophy-Associated Gene Expression without Affecting Myocyte Beating or Cell Size

Pathological cardiac hypertrophy is associated with an increased risk of heart failure and cardiovascular mortality. Calcium (Ca2+) -regulated gene expression is essential for the induction of hypertrophy, but it is not known how myocytes distinguish between the Ca2+ signals that regulate contraction and those that lead to cardiac hypertrophy. We used in vitro neonatal rat ventricular myocytes to perform an RNA interference (RNAi) screen for ion channels that mediate Ca2+-dependent gene expression in response to hypertrophic stimuli. We identified several ion channels that are linked to hypertrophic gene expression, including transient receptor potential C3 (TrpC3). RNAi-mediated knockdown of TrpC3 decreases expression of hypertrophy-associated genes such as the A- and B-type natriuretic peptides (ANP and BNP) in response to numerous hypertrophic stimuli, while TrpC3 overexpression increases BNP expression. Furthermore, stimuli that induce hypertrophy dramatically increase TrpC3 mRNA levels. Importantly, whereas TrpC3-knockdown strongly reduces gene expression associated with hypertrophy, it has a negligible effect on cell size and on myocyte beating. These results suggest that Ca2+ influx through TrpC3 channels increases transcription of genes associated with hypertrophy but does not regulate the signaling pathways that control cell size or contraction. Thus TrpC3 may represent an important therapeutic target for the treatment of cardiac hypertrophy and heart failure

Differential Gene Expression Regulated by Oscillatory Transcription Factors

Cells respond to changes in the internal and external environment by a complex regulatory system whose end-point is the activation of transcription factors controlling the expression of a pool of ad-hoc genes. Recent experiments have shown that certain stimuli may trigger oscillations in the concentration of transcription factors such as NF-B and p53 influencing the final outcome of the genetic response. In this study we investigate the role of oscillations in the case of three different well known gene regulatory mechanisms using mathematical models based on ordinary differential equations and numerical simulations. We considered the cases of direct regulation, two-step regulation and feed-forward loops, and characterized their response to oscillatory input signals both analytically and numerically. We show that in the case of indirect two-step regulation the expression of genes can be turned on or off in a frequency dependent manner, and that feed-forward loops are also able to selectively respond to the temporal profile of oscillating transcription factors