Overexpression of glial cell line-derived neurotrophic factor induces genes regulating migration and differentiation of neuronal progenitor cells

The glial cell line-derived neurotrophic factor (GDNF) is involved in the development and maintenance of neural tissues. Mutations in components of its signaling pathway lead to severe migration deficits of neuronal crest stem cells, tumor formation, or ablation of the urinary system. In animal models of Parkinson's disease, GDNF has been recognized to be neuroprotective and to improve motor function when delivered into the cerebral ventricles or into the substantia nigra. Here, we characterize the network of 43 genes induced by GDNF overproduction of neuronal progenitor cells (ST14A), which mainly regulate migration and differentiation of neuronal progenitor cells. GDNF down-regulates doublecortin, Paf-ah1b (Lis1), dynamin, and alpha-tubulin, which are involved in neocortical lamination and cytoskeletal reorganization. Axonal guidance depends on cell-surface molecules and extracellular matrix proteins. Laminin, Mpl3, Alcam, Bin1, Id1, Id2, Id3, neuregulin1, the ephrinB2-receptor, neuritin, focal adhesion kinase (FAK), Tc10, Pdpk1, clusterin, GTP-cyclooxygenase1, and follistatin are genes up-regulated by GDNF overexpression. Moreover, we found four key enzymes of the cholesterol-synthesis pathway to be down-regulated leading to decreased farnesyl-pyrophospate production. Many proteins are anchored by farnesyl-derivates at the cell membrane. The identification of these GDNF-regulated genes may open new opportunities for directly influencing differentiation and developmental processes of neurons.     

Dynamic cellular automata: an alternative approach to cellular simulation

A wide variety of approaches, ranging from Petri nets to systems of partial differential equations, have been used to model very specific aspects of cellular or biochemical functions. Here we describe how an agent-based or dynamic cellular automata (DCA) approach can be used as a very simple, yet very general method to model many different kinds of cellular or biochemical processes. Specifically, using simple pairwise interaction rules coupled with random object moves to simulate Brownian motion, we show how the DCA approach can be used to easily and accurately model diffusion, viscous drag, enzyme rate processes, metabolism (the Kreb's cycle), and complex genetic circuits (the repressilator). We also demonstrate how DCA approaches are able to accurately capture the stochasticity of many biological processes. The success and simplicity of this technique suggests that many other physical properties and significantly more complicated aspects of cellular behavior could be modeled using DCA methods. An easy-to-use, graphically-based computer program, called SimCell, was developed to perform the DCA simulations described here. It is available at http://wishart.biology.ualberta.ca/SimCell/.     

Roll Compaction and Tableting of High Loaded Metformin Formulations Using Efficient Binders

Metformin has a poor tabletability and flowability. Therefore, metformin is typically wet granulated with a binder before tableting. To save production costs, it would be desirable to implement a roll compaction/dry granulation (RCDG) process for metformin instead of using wet granulation. In order to implement RCDG, the efficiency of dry binders is crucial to ensure a high drug load and suitable properties of dry granules and tablets. This study evaluates dry granules manufactured by RCDG and subsequently tableting of high metformin content formulations (≥?87.5%). Based on previous results, fine particle grades of hydroxypropylcellulose and copovidone in different fractions were compared as dry binders. The formulations are suitable for RCDG and tableting. Furthermore, results can be connected to in-die and out-of-die compressibility analysis. The addition of 7% of dry binder is a good compromise to generate sufficient mechanical properties on the one hand, but also to save resources and ensure a high metformin content on the other hand. Hydroxypropylcellulose was more efficient in terms of granule size, tensile strength and friability. Three percent croscarmellose was added to reach the specifications of the US Pharmacopeia regarding dissolution. The final formulation has a metformin content of 87.5%. A loss in tabletability does not occur for granules compressed at different specific compaction forces, which displays a robust tensile strength of tablets independent of the granulation process.     

Rapid and reliable protein structure determination via chemical shift threading

Protein structure determination using nuclear magnetic resonance (NMR) spectroscopy can be both time-consuming and labor intensive. Here we demonstrate how chemical shift threading can permit rapid, robust, and accurate protein structure determination using only chemical shift data. Threading is a relatively old bioinformatics technique that uses a combination of sequence information and predicted (or experimentally acquired) low-resolution structural data to generate high-resolution 3D protein structures. The key motivations behind using NMR chemical shifts for protein threading lie in the fact that they are easy to measure, they are available prior to 3D structure determination, and they contain vital structural information. The method we have developed uses not only sequence and chemical shift similarity but also chemical shift-derived secondary structure, shift-derived super-secondary structure, and shift-derived accessible surface area to generate a high quality protein structure regardless of the sequence similarity (or lack thereof) to a known structure already in the PDB. The method (called E-Thrifty) was found to be very fast (often?<?10 min/structure) and to significantly outperform other shift-based or threading-based structure determination methods (in terms of top template model accuracy)—with an average TM-score performance of 0.68 (vs. 0.50–0.62 for other methods). Coupled with recent developments in chemical shift refinement, these results suggest that protein structure determination, using only NMR chemical shifts, is becoming increasingly practical and reliable. E-Thrifty is available as a web server at http://ethrifty.ca.     

Theory of initial current density in membrane voltage-clamp experiments

Herein we show that the voltage-clamp current density at zero time calculated from electrodiffusion equations is linear in the clamping voltage for a simple membrane (no charge structure) and for a membrae with fixed charges. Such membranes are nonexcitable. Excitable membranes can be represented by a homogeneous membrane with dipole layers at the surface. In this case the initial current density will be linear in the clamping voltage if a critical field for a dipole layer reorientation is not passed through in changing from holding to clamping potential. Otherwise, deviation from nonlinearity may occur. This is in agreement with experimental data for the squid giant axon.