Natriuretic Peptides, Diagnostic and Prognostic Biomarkers

In humans, the natriuretic peptide family consists of three different types of peptides: atrial natriuretic peptide (synonym: atrial natriuretic factor), B-type natriuretic peptide (synonym: brain natriuretic peptide) and C-natriuretic peptide.1 Atrial natriuretic peptide (ANP) was the fi rst natriuretic peptide to be discovered and in humans ANP is predominantly formed in the cardiomyocytes of the atria.2 B-type natriuretic peptide (BNP) was fi rst discovered in porcine brain hence its original name brain natriuretic peptide.3 In humans, the majority of BNP is formed in ventricular cardiomyocytes, and mRNA levels in brain are negligible. Therefore, brain natriuretic peptide is now recognized as B-type natriuretic peptide. C-type natriuretic peptide (CNP) is basically a neuropeptide, found in brain and vascular endothelial cells

Changes within bursts during learning in dissociated neural networks

We have studied the effect of imprinting a new stimulus-response (SR) relationship into a neuronal network cultured on a multi electrode array (MEA). We have used the Conditional Repetitive Stimulation (CRS) algorithm introduced by Shahaf et al in 2004. In this algorithm focal electrical stimulation is delivered at a low rate (≪1 Hz) and is withdrawn when a desired response is observed. We confirmed that CRS could train the network to strengthen an initially weak SR relationship. With the acquisition of a new SR relationship, we studied its effect on network activity. Specifically, spontaneously occurring network bursts measured before, during and after training were analyzed. The total firing rate within bursts was estimated with a temporal resolution of milliseconds (burst profiles). We have shown earlier that these profiles change shape on a time base of several hours during spontaneous development. We show that the rate of change of the profiles during training (i.e. CRS) was higher than when no stimulation was applied

Legal, Economic, and Cultural Aspects of file sharing

This contribution seeks to identify the short- and long-term economic and cultural effects of file sharing on music, films and games, while taking into account the legal context and policy developments. The short-term implications examined concern direct costs and benefits to society, whereas the long-term impact concerns changes in the industry’s business models as well as in cultural diversity and the accessibility of content. It observes that the proliferation of digital distribution networks combined with the availability of digital technology among consumers has broken the entertainment industries’ control over the access to their products. Only part of the decline in music sales can be attributed to file sharing. Despite the losses for the music industry, the increased accessibillity of culture renders the overall welfare effects of file sharing robustly positive. As a consequence the entertainment industries, particularly the music industry, have to explore new models to sustain their busines.filesharing, downloading/uploading, entertainment industry, cultural analysis, economic analysis, legal and policy analysis.

Orexin A in cortical cultures: expression and effect on synaptogenesis during development

Orexin-A (OXA) is an excitatory hypothalamic neurotransmitter and ligand for Orexin Receptor-1 (OR1), isolated from a small group of hypothalamic neurons. OXA orchestrates different brain functions, and at the cognitive level some of the effects of insufficiency of OXA are well-known, for example in Parkinson’s disease. It is widely assumed that deteriorated cognitive processes are related to impaired network connectivity. However, little is known about the effects of OXA in network connectivity and synaptogenesis. Therefore, to obtain insight into this problem we designed experiments with two groups of networks of dissociated cortical neurons: one group incubated in a plain medium and another chronically treated with OXA. After one, two, three or four weeks in vitro we applied immunocytochemistry for detection of OXA, OR1 and synaptic marker synaptophysin. Shortly after plating, 91±8% of the neurons cultivated in a plain medium expressed OXA-immunoreactivity, which does normally not occur in vivo indicating that neurons may change their phenotype under non-natural culture conditions to develop synaptically coupled networks. The fraction of orexinergic neurons decreased to 33±21% after 4 weeks in vitro. OXA expression was highest in the first week of network formation, the period of maximum synaptogenesis, and then decreased and stabilized in the weeks thereafter. Our hypothesis that OXA plays a role in the network development as a synaptogenic factor was supported by higher levels, earlier onset, and sustained increase of synaptophysin-expression in experiments with chronic OXA application to the culture medium

Analysis of Cultured Neuronal Networks Using Intraburst Firing Characteristics

It is an open question whether neuronal networks, cultured on multielectrode arrays, retain any capability to usefully process information (learning and memory). A necessary prerequisite for learning is that stimulation can induce lasting changes in the network. To observe these changes, one needs a method to describe the network in sufficient detail, while stable in normal circumstances. We analyzed the spontaneous bursting activity that is encountered in dissociated cultures of rat neocortical cells. Burst profiles (BPs) were made by estimating the instantaneous array-wide firing frequency. The shape of the BPs was found to be stable on a time scale of hours. Spatiotemporal detail is provided by analyzing the instantaneous firing frequency per electrode. The resulting phase profiles (PPs) were estimated by aligning BPs to their peak spiking rate over a period of 15 min. The PPs reveal a stable spatiotemporal pattern of activity during bursts over a period of several hours, making them useful for plasticity and learning studies. We also show that PPs can be used to estimate conditional firing probabilities. Doing so, yields an approach in which network bursting behavior and functional connectivity can be studied

Investigating membrane breakdown of neuronal cells exposed to nonuniform electric fields by finite-element modeling and experiments

High electric field strengths may induce high cell membrane potentials. At a certain breakdown level the membrane potential becomes constant due to the transition from an insulating state into a high conductivity and high permeability state. Pores are thought to be created through which molecules may be transported into and out of the cell interior. Membrane rupture may follow due to the expansion of pores or the creation of many small pores across a certain part of the membrane surface. In nonuniform electric fields, it is difficult to predict the electroporated membrane area. Therefore, in this study the induced membrane potential and the membrane area where this potential exceeds the breakdown level is investigated by finite-element modeling. Results from experiments in which the collapse of neuronal cells was detected were combined with the computed field strengths in order to investigate membrane breakdown and membrane rupture. It was found that in nonuniform fields membrane rupture is position dependent, especially at higher breakdown levels. This indicates that the size of the membrane site that is affected by electroporation determines rupture

Context-free Coalgebras

In this article, we provide a coalgebraic account of parts of the mathematical theory underlying context-free languages. We characterize context-free languages, and power series and streams generalizing or corresponding to the context-free languages, by means of systems of behavioural differential equations; and prove a number of results, some of which are new, and some of which are new proofs of existing theorems, using the techniques of bisimulation and bisimulation up to linear combinations. Furthermore, we establish a link between automatic sequences and these systems of equations, allowing us to, given an automaton generating an automatic sequence, easily construct a system of behavioural differential equations yielding this sequence as a context-free stream