The effects of cocoa on the immune system

Cocoa is a food relatively rich in polyphenols, which makes it a potent antioxidant. Due to its activity as an antioxidant, as well as through other mechanisms, cocoa consumption has been reported to be beneficial for cardiovascular health, brain functions, and cancer prevention. Furthermore, cocoa influences the immune system, in particular the inflammatory innate response and the systemic and intestinal adaptive immune response. Preclinical studies have demonstrated that a cocoa-enriched diet modifies T-cell functions that conduce to a modulation of the synthesis of systemic and gut antibodies. In this regard, it seems that a cocoa diet in rats produces changes in the lymphocyte composition of secondary lymphoid tissues and the cytokines secreted by T cells. These results suggest that it is possible that cocoa could inhibit the function of Th2 cells, and in line with this, the preventive effect of cocoa on IgE synthesis in a rat allergy model has been reported, which opens up new perspectives when considering the beneficial effects of cocoa compounds. On the other hand, cocoa intake modifies the functionality of gut-associated lymphoid tissue by means of modulating IgA secretion and intestinal microbiota. The mechanisms involved in these influences are discussed here. Further research may elucidate the cocoa compounds involved in such an effect and also the possible medical approaches to these repercussions

Classifier combination for in vivo magnetic resonance spectra of brain tumours

In this paper we present a multi-stage classifier for magnetic resonance spectra of human brain tumours which is being developed as part of a decision support system for radiologists. The basic idea is to decompose a complex classification scheme into a sequence of classifiers, each specialising in different classes of tumours and trying to reproducepart of the WHO classification hierarchy. Each stage uses a particular set of classification features, which are selected using a combination of classical statistical analysis, splitting performance and previous knowledge.Classifiers with different behaviour are combined using a simple voting scheme in order to extract different error patterns: LDA, decision trees and the k-NN classifier. A special label named "unknown¿ is used when the outcomes of the different classifiers disagree. Cascading is alsoused to incorporate class distances computed using LDA into decision trees. Both cascading and voting are effective tools to improve classification accuracy. Experiments also show that it is possible to extract useful information from the classification process itself in order to helpusers (clinicians and radiologists) to make more accurate predictions and reduce the number of possible classification mistakes.

Most of the Abundant Protein Fractions of Embryonic Cerebrospinal Fluid are Produced Out of the Brain Anlagen

The microenvironment of the central nervous system is important for neuronal function and development. During the early stages of embryo development the cephalic vesicles are filled by embryonic cerebrospinal fluid, a complex fluid containing different protein fractions, which contributes to the regulation of the survival, proliferation and neurogenesis of neuroectodermal stem cells. The protein content of embryonic cerebrospinal fluid from chick and rat embryos at the start of neurogenesis has already been determined. Most of the identified gene products are thought to be involved in the regulation of developmental processes during embryogenesis. However, due to the crucial roles played by embryonic cerebrospinal fluid during brain development, the embryological origin of the gene products it contains remains an intriguing question. According to the literature most of these products are synthesised in embryonic tissues other than the neuroepithelium. In this study we examined the embryological origin of the most abundant embryonic cerebrospinal fluid protein fractions by means of slot-blot analysis and by using several different embryonic and extraembryonic protein extracts, immunodetected with polyclonal antibodies. This first attempt to elucidate their origin is not based on the proteins identified by proteomic methods, but rather on crude protein fractions detected by SDS-PAGE analysis and to which polyclonal antibodies were specifically generated. Despite some of the limitations of this study, i.e. that one protein fraction may contain more than one gene product, and that a specific gene product may be contained in different protein fractions depending on post-translational modifications, our results show that most of the analysed protein fractions are not produced by the cephalic neuroectoderm but are rather stored in the egg reservoir; furthermore, few are produced by embryo tissues, thus indicating that they must be transported from their production or storage sites to the cephalic cavities, most probably via embryonic serum. These results raise the question as to whether the transfer of proteins from these two embryo compartments is regulated at this early developmental stage.

Reward networks in the brain as captured by connectivity measures

An assortment of human behaviors is thought to be driven by rewards including reinforcement learning, novelty processing, learning, decision making, economic choice, incentive motivation, and addiction. In each case the ventral tegmental area/ventral striatum (nucleus accumbens) (VTAVS) system has been implicated as a key structure by functional imaging studies, mostly on the basis of standard, univariate analyses. Here we propose that standard functional magnetic resonance imaging analysis needs to be complemented by methods that take into account the differential connectivity of the VTAVS system in the different behavioral contexts in order to describe reward based processes more appropriately. We fi rst consider the wider network for reward processing as it emerged from animal experimentation. Subsequently, an example for a method to assess functional connectivity is given. Finally, we illustrate the usefulness of such analyses by examples regarding reward valuation, reward expectation and the role of reward in addiction.

Brain Computer Interface for Virtual Reality Control

A brain-computer interface (BCI) is a new communication channel between the human brain and a computer. Applications of BCI systems comprise the restoration of movements, communication and environmental control. In this study experiments were made that used the BCI system to control or to navigate in virtual environments (VE) just by thoughts. BCI experiments for navigation in VR were conducted so far with synchronous BCI and asynchronous BCI systems. The synchronous BCI analyzes the EEG patterns in a predefined time window and has 2 to 3 degrees of freedom.

Pleiotrophin as a central nervous system neuromodulator, evidences from the hippocampus

Pleiotrophin (PTN) is a secreted growth factor, and also a cytokine, associated with the extracellular matrix, which has recently starting to attract attention as a significant neuromodulator with multiple neuronal functions during development. PTN is expressed in several tissues, where its signals are generally related with cell proliferation, growth, and differentiation by acting through different receptors. In Central Nervous System (CNS), PTN exerts post-developmental neurotrophic and -protective effects, and additionally has been involved in neurodegenerative diseases and neural disorders. Studies in Drosophila shed light on some aspects of the different levels of regulatory control of PTN invertebrate homologs. Specifically in hippocampus, recent evidence from PTN Knock-out (KO) mice involves PTN functioning in learning and memory. In this paper, we summarize, discuss, and contrast the most recent advances and results that lead to proposing a PTN as a neuromodulatory molecule in the CNS, particularly in hippocampus.

Pleiotrophin as a central nervous system neuromodulator, evidences from the hippocampus

Pleiotrophin (PTN) is a secreted growth factor, and also a cytokine, associated with the extracellular matrix, which has recently starting to attract attention as a significant neuromodulator with multiple neuronal functions during development. PTN is expressed in several tissues, where its signals are generally related with cell proliferation, growth, and differentiation by acting through different receptors. In Central Nervous System (CNS), PTN exerts post-developmental neurotrophic and -protective effects, and additionally has been involved in neurodegenerative diseases and neural disorders. Studies in Drosophila shed light on some aspects of the different levels of regulatory control of PTN invertebrate homologs. Specifically in hippocampus, recent evidence from PTN Knock-out (KO) mice involves PTN functioning in learning and memory. In this paper, we summarize, discuss, and contrast the most recent advances and results that lead to proposing a PTN as a neuromodulatory molecule in the CNS, particularly in hippocampus.