Specialization in pyramidal cell structure in the sensory-motor cortex of the vervet monkey (Cercopethicus pygerythrus)

Recent studies have revealed systematic differences in the pyramidal cell structure between functionally related cortical areas of primates. Trends for a parallel in pyramidal cell structure and functional complexity have been reported in visual, somatosensory, motor, cingulate and prefrontal cortex in the macaque monkey cortex. These specializations in structure have been interpreted as being fundamental in determining cellular and systems function, endowing circuits in these different cortical areas with different computational power. In the present study we extend our initial finding of systematic specialization of pyramidal cell structure in sensory-motor cortex in the macaque monkey [Cereb Cortex 12 (2002) 1071] to the vervet monkey. More specifically, we investigated pyramidal cell structure in somatosensory and motor areas 1/2, 5, 7, 4 and 6. Neurones in fixed, flat-mounted, cortical slices were injected intracellularly with Lucifer Yellow and processed for a light-stable 3,3'-diaminobenzidine reaction product. The size of, number of branches in, and spine density of the basal dendritic arbors varied systematically such that there was a trend for increasing complexity in arbor structure with progression through 1/2, 5 and 7. In addition, cells in area 6 were larger, more branched, and more spinous than those in area 4. (c) 2005 IBRO. Published by Elsevier Ltd. All rights reserved.

Effect of mutual coupling on the interference rejection capabilities of linear and circular arrays in CDMA systems

This paper is concerned with assessing the interference rejection capabilities of linear and circular array of dipoles that can be part of a base station of a code-division multiple-access cellular communication system. The performance criteria for signal-to-interference ratio (SIR) improvement employed in this paper is the spatial interference suppression coefficient. We first derive an expression for this figure of merit and then analyze and compare the SIR performance of the two types of arrays. For a linear array, we quantitatively assess the degradation in SIR performance, as we move from array broadside to array end-fire direction. In addition, the effect of mutual coupling is taken into account.

A multi-scaled approach for simulating chemical reaction systems

In this paper we give an overview of some very recent work, as well as presenting a new approach, on the stochastic simulation of multi-scaled systems involving chemical reactions. In many biological systems (such as genetic regulation and cellular dynamics) there is a mix between small numbers of key regulatory proteins, and medium and large numbers of molecules. In addition, it is important to be able to follow the trajectories of individual molecules by taking proper account of the randomness inherent in such a system. We describe different types of simulation techniques (including the stochastic simulation algorithm, Poisson Runge–Kutta methods and the balanced Euler method) for treating simulations in the three different reaction regimes: slow, medium and fast. We then review some recent techniques on the treatment of coupled slow and fast reactions for stochastic chemical kinetics and present a new approach which couples the three regimes mentioned above. We then apply this approach to a biologically inspired problem involving the expression and activity of LacZ and LacY proteins in E. coli, and conclude with a discussion on the significance of this work.

Semliki Forest virus and Kunjin virus RNA replicons elicit comparable cellular immunity but distinct humoral immunity

RNA replicons offer a number of qualities which make them attractive as vaccination vectors. Both alphavirus and flavivirus replicon vaccines have been investigated in preclinical models yet there has been little direct comparison of the two vector systems. To determine whether differences in the biology of the two vectors influence immunogenicity, we compared two prototypic replicon vectors based on Semliki Forest virus (SFV) (alphavirus) and Kunjin virus (KUN) (flavivirus). Both vectors when delivered as naked RNAs elicited comparable CD8+ T cell responses but the SFV vectors elicited greater humoral responses to an encoded cytoplasmic antigen beta-galactosidase. Studies in MHC class II-deficient mice revealed that neither vector could overcome the dependence of CD4+ T cell help in the development of humoral and cellular responses following immunization. These studies indicate that the distinct biology of the two replicon systems may differentially impact the adaptive immune response and this may need to be considered when designing vaccination strategies. (c) 2005 Elsevier Ltd. All rights reserved.

Inorganic nanoparticles as carriers for efficient cellular delivery

Cellular delivery involving the transfer of various drugs and bio-active molecules (peptides, proteins and DNAs, etc.) through the cell membrane into cells has attracted increasing attention because of its importance in medicine and drug delivery. This topic has been extensively reviewed. The direct delivery of drugs and biomolecules, however, is generally inefficient and suffering from problems such as enzymic degradation of DNAs. Therefore, searching for efficient and safe transport vehicles (carriers) to delivery genes or drugs into cells has been challenging yet exciting area of research. In past decades, many carriers have been developed and investigated extensively which can be generally classified into four major groups: viral carriers, organic cationic compounds, recombinant protiens and inorganic nanoparticles. Many inorganic materials, such as calcium phosphate, gold, carbon materials, silicon oxide, iron oxide and layered double hydroxide (LDH), have been studied. Inorganic nanoparticles show low toxicity and promise for controlled delivery properties, thus presenting a new alternative to viral carriers and cationic carriers. Inorganic nanoparticles generally possess versatile properties suitable for cellular delivery, including wide availability, rich functionality, good biocompatibility, potential capability of targeted delivery (e.g. selectively destroying cancer cells but sparing normal tissues) and controlled release of carried drugs. This paper reviews the latest advances in inorganic nanoparticle applications as cellular delivery carriers and highlights some key issues in efficient cellular delivery using inorganic nanoparticles. Critical proper-ties of inorganic nanoparticles, surface functionalisation (modification), uptake of biomolecules, the driving forces for delivery, and release of biomolecules will be reviewed systematically. Selected examples of promising inorganic nanoparticle delivery systems, including gold, fullerences and carbon nanotubes, LDH and various oxide nanoparticles in particular their applications for gene delivery will be discussed. The fundamental understanding of properties of inorganic nanoparticles in relation to cellular delivery efficiency as the most paramount issue will be highlighted. (c) 2005 Elsevier Ltd. All rights reserved.

Parallel implementation of stochastic simulation for large scale cellular processes

Experimental and theoretical studies have shown the importance of stochastic processes in genetic regulatory networks and cellular processes. Cellular networks and genetic circuits often involve small numbers of key proteins such as transcriptional factors and signaling proteins. In recent years stochastic models have been used successfully for studying noise in biological pathways, and stochastic modelling of biological systems has become a very important research field in computational biology. One of the challenge problems in this field is the reduction of the huge computing time in stochastic simulations. Based on the system of the mitogen-activated protein kinase cascade that is activated by epidermal growth factor, this work give a parallel implementation by using OpenMP and parallelism across the simulation. Special attention is paid to the independence of the generated random numbers in parallel computing, that is a key criterion for the success of stochastic simulations. Numerical results indicate that parallel computers can be used as an efficient tool for simulating the dynamics of large-scale genetic regulatory networks and cellular processes