Potential role of NF-kappaB in adult neural stem cells: the underrated steersman?

Neural stem cells are precursors of neurons and glial cells. During brain development, these cells proliferate, migrate and differentiate into specific lineages. Recently neural stem cells within the adult central nervous system were identified. Informations are now emerging about regulation of stem cell proliferation, migration and differentiation by numerous soluble factors such as chemokines and cytokines. However, the signal transduction mechanisms downstream of these factors are less clear. Here, we review potential evidences for a novel central role of the transcription factor nuclear factor kappa B (NF-kappaB) in these crucial signal transduction processes. NF-kappaB is an inducible transcription factor detected in neurons, glia and neural stem cells. NF-kappaB was discovered by David Baltimore's laboratory as a transcription factor in lymphocytes. NF-kappaB is involved in many biological processes such as inflammation and innate immunity, development, apoptosis and anti-apoptosis. It has been recently shown that members of the NF-kappaB family are widely expressed by neurons, glia and neural stem cells. In the nervous system, NF-kappaB plays a crucial role in neuronal plasticity, learning, memory consolidation, neuroprotection and neurodegeneration. Recent data suggest an important role of NF-kappaB on proliferation, migration and differentiation of neural stem cells. NF-kappaB is composed of three subunits: two DNA-binding and one inhibitory subunit. Activation of NF-kappaB takes place in the cytoplasm and results in degradation of the inhibitory subunit, thus enabling the nuclear import of the DNA-binding subunits. Within the nucleus, several target genes could be activated. In this review, we suggest a model explaining the multiple action of NF-kappaB on neural stem cells. Furthermore, we discuss the potential role of NF-kappaB within the so-called brain cancer stem cells.

Mathematical model for NF-kappaB-driven proliferation of adult neural stem cells

Neural stem cells (NSCs) are early precursors of neuronal and glial cells. NSCs are capable of generating identical progeny through virtually unlimited numbers of cell divisions (cell proliferation), producing daughter cells committed to differentiation. Nuclear factor kappa B (NF-kappaB) is an inducible, ubiquitous transcription factor also expressed in neurones, glia and neural stem cells. Recently, several pieces of evidence have been provided for a central role of NF-kappaB in NSC proliferation control. Here, we propose a novel mathematical model for NF-kappaB-driven proliferation of NSCs. We have been able to reconstruct the molecular pathway of activation and inactivation of NF-kappaB and its influence on cell proliferation by a system of nonlinear ordinary differential equations. Then we use a combination of analytical and numerical techniques to study the model dynamics. The results obtained are illustrated by computer simulations and are, in general, in accordance with biological findings reported by several independent laboratories. The model is able to both explain and predict experimental data. Understanding of proliferation mechanisms in NSCs may provide a novel outlook in both potential use in therapeutic approaches, and basic research as well.

Highly efficient neural differentiation of human somatic stem cells, isolated by minimally invasive periodontal surgery

Neural stem cells (NSCs) are potential sources for cell therapy of neurodegenerative diseases and for drug screening. Despite their potential benefits, ethical and practical considerations limit the application of NSCs derived from human embryonic stem cells (ES) or adult brain tissue. Thus, alternative sources are required to satisfy the criteria of ready accessibility, rapid expansion in chemically defined media and reliable induction to a neuronal fate. We isolated somatic stem cells from the human periodontium that were collected during minimally invasive periodontal access flap surgery as part of guided tissue regeneration therapy. These cells could be propagated as neurospheres in serum-free medium, which underscores their cranial neural crest cell origin. Culture in the presence of epidermal growth factor (EGF) and fibroblast growth factor-2 (FGF-2) under serum-free conditions resulted in large numbers of nestin-positive/Sox-2-positive NSCs. These periodontium-derived (pd) NSCs are highly proliferative and migrate in response to chemokines that have been described as inducing NSC migration. We used immunocytochemical techniques and RT-PCR analysis to assess neural differentiation after treatment of the expanded cells with a novel induction medium. Adherence to substrate, growth factor deprivation, and retinoic acid treatment led to the acquisition of neuronal morphology and stable expression of markers of neuronal differentiation by more than 90% of the cells. Thus, our novel method might provide nearly limitless numbers of neuronal precursors from a readily accessible autologous adult human source, which could be used as a platform for further experimental studies and has potential therapeutic implications.

Alkyl nitrates in outflow from North America over the North Atlantic during Intercontinental Transport of Ozone and Precursors 2004

This paper is based on alkyl nitrate measurements made over the North Atlantic as part of the International Consortium for Research on Atmospheric Transport and Transformation (ICARTT). The focus is on the analysis of air samples collected on the UK BAe-146 aircraft during the Intercontinental Transport of Ozone and Precursors (ITOP) project, but air samples collected on board the NASA DC-8 and NOAA WP-3D aircraft as part of a Lagrangian experiment are also used. The ratios between the alkyl nitrates and their parent hydrocarbons are compared with those expected from chemical theory. Further, a box model is run to investigate the temporal evolution of the alkyl nitrates in three Lagrangian case studies and compared to observations. The air samples collected during ITOP do not appear to be strongly influenced by oceanic sources, but rather are influenced by emissions from the N.E. United States and from Alaskan fires. There also appears to be a widespread common source of ethyl nitrate and 1-propyl nitrate other than from their parent hydrocarbons. The general agreement between the alkyl nitrate data and photochemical theory suggests that during the first few days of transport from the source region, photochemical production of alkyl nitrates, and thus ozone, had taken place. The observations in the more photochemically processed air masses are consistent with the alkyl nitrate production reactions no longer dominating the peroxy radical self/cross reactions. Further, the results also suggest that the rates of photochemical processing in the Alaskan smoke plumes were small.

Real-Time software control of neural stimulation in a closed loop Animat system

A recent area for investigation into the development of adaptable robot control is the use of living neuronal networks to control a mobile robot. The so-called Animat paradigm comprises a neuronal network (the ‘brain’) connected to an external embodiment (in this case a mobile robot), facilitating potentially robust, adaptable robot control and increased understanding of neural processes. Sensory input from the robot is provided to the neuronal network via stimulation on a number of electrodes embedded in a specialist Petri dish (Multi Electrode Array (MEA)); accurate control of this stimulation is vital. We present software tools allowing precise, near real-time control of electrical stimulation on MEAs, with fast switching between electrodes and the application of custom stimulus waveforms. These Linux-based tools are compatible with the widely used MEABench data acquisition system. Benefits include rapid stimulus modulation in response to neuronal activity (closed loop) and batch processing of stimulation protocols.

Detection of Parkinson’s disease tremor-onset with a frequency analysing artificial neural network

Deep Brain Stimulator devices are becoming widely used for therapeutic benefits in movement disorders such as Parkinson's disease. Prolonging the battery life span of such devices could dramatically reduce the risks and accumulative costs associated with surgical replacement. This paper demonstrates how an artificial neural network can be trained using pre-processing frequency analysis of deep brain electrode recordings to detect the onset of tremor in Parkinsonian patients. Implementing this solution into an 'intelligent' neurostimulator device will remove the need for continuous stimulation currently used, and open up the possibility of demand-driven stimulation. Such a methodology could potentially decrease the power consumption of a deep brain pulse generator.

Geochemical precursors to volcanic activity at Mount St. Helens, USA

The importance of the interplay between degassing and crystallization before and after the eruption of Mount St. Helens (Washington, USA) in 1980 is well established. Here, we show that degassing occurred over a period of decades to days before eruptions and that the manner of degassing, as deduced from geochemicai signatures within the magma, was characteristic of the eruptive style. Trace element (lithium) and short-lived radioactive isotope (lead-210 and radium-226) data show that ascending magma stalled within the conduit, leading to the accumulation of volatiles and the formation of lead-210 excesses, which signals the presence of degassing magma at depth.

Perceived controllability modulates the neural response to pain

The response to painful stimulation depends not only on peripheral nociceptive input but also on the cognitive and affective context in which pain occurs. One contextual variable that affects the neural and behavioral response to nociceptive stimulation is the degree to which pain is perceived to be controllable. Previous studies indicate that perceived controllability affects pain tolerance, learning and motivation, and the ability to cope with intractable pain, suggesting that it has profound effects on neural pain processing. To date, however, no neuroimaging studies have assessed these effects. We manipulated the subjects' belief that they had control over a nociceptive stimulus, while the stimulus itself was held constant. Using functional magnetic resonance imaging, we found that pain that was perceived to be controllable resulted in attenuated activation in the three neural areas most consistently linked with pain processing: the anterior cingulate, insular, and secondary somatosensory cortices. This suggests that activation at these sites is modulated by cognitive variables, such as perceived controllability, and that pain imaging studies may therefore overestimate the degree to which these responses are stimulus driven and generalizable across cognitive contexts. [References: 28]

A reconfigurable neural environment on active networks

This paper proposes the deployment of a neural network computing environment on Active Networks. Active Networks are packet-switched computer networks in which packets can contain code fragments that are executed on the intermediate nodes. This feature allows the injection of small pieces of codes to deal with computer network problems directly into the network core, and the adoption of new computing techniques to solve networking problems. The goal of our project is the adoption of a distributed neural network for approaching tasks which are specific of the computer network environment. Dynamically reconfigurable neural networks are spread on an experimental wide area backbone of active nodes (ABone) to show the feasibility of the proposed approach.

Chess Endgames and Neural Networks

The existence of endgame databases challenges us to extract higher-grade information and knowledge from their basic data content. Chess players, for example, would like simple and usable endgame theories if such holy grail exists: endgame experts would like to provide such insights and be inspired by computers to do so. Here, we investigate the use of artificial neural networks (NNs) to mine these databases and we report on a first use of NNs on KPK. The results encourage us to suggest further work on chess applications of neural networks and other data-mining techniques.

Validation of improved TAMANN neural network for operational satellite-derived rainfall estimation in Africa

Real-time rainfall monitoring in Africa is of great practical importance for operational applications in hydrology and agriculture. Satellite data have been used in this context for many years because of the lack of surface observations. This paper describes an improved artificial neural network algorithm for operational applications. The algorithm combines numerical weather model information with the satellite data. Using this algorithm, daily rainfall estimates were derived for 4 yr of the Ethiopian and Zambian main rainy seasons and were compared with two other algorithms-a multiple linear regression making use of the same information as that of the neural network and a satellite-only method. All algorithms were validated against rain gauge data. Overall, the neural network performs best, but the extent to which it does so depends on the calibration/validation protocol. The advantages of the neural network are most evident when calibration data are numerous and close in space and time to the validation data. This result emphasizes the importance of a real-time calibration system.

Studies on particulate matter (PM10) and its precursors over urban environment of Reading, UK

The extent to which airborne particles penetrate into the human respiratory system is determined mainly by their size, with possible health effects. The research over the scientific evidence of the role of airborne particles in adverse health effects has been intensified in recent years. In the present study, seasonal variations of PM10 and its relation with anthropogenic activities have been studied by using the data from UK National Air Quality Archive over Reading, UK. The diurnal variation of PM10 shows a morning peak during 7:00-10:00 LT and an evening peak during 19:00-22:00 LT. 3 The variation between 12:00 and 17:00 LT remains more or less steady for PM10 with the minimum value of similar to 16 mu g m(-3). PM10 and black smoke (BS) concentrations during weekdays were found to be high compared to weekends. A reduction in the concentration of PM10 has been found during the Christmas holidays compared to normal days during December. Seasonal variations of PM10 showed high values during spring compared to other seasons. A linear relationship has been found between PM10 and NO, during March, July, November and December suggesting that most of the PM10 is due to local traffic exhaust emissions. PM10 and SO2 concentrations showed positive correlation with the correlation coefficient of R-2 = 0.65 over the study area. Seasonal variations of SO2 and NOx showed high concentrations during winter and low concentrations during spring. Fraction of BS in PM10 has been found to be 50% during 2004 over the study area. (C) 2005 Elsevier Ltd. All rights reserved.