The occipital lateral plate mesoderm - a novel source for vertebrate neck musculature

In vertebrates, body musculature originates from somites, whereas head muscles originate from the cranial mesoderm. Neck muscles are located in the transition between these regions. We show that the chick occipital lateral plate mesoderm has myogenic capacity and gives rise to large muscles located in the neck and thorax. We present molecular and genetic evidence to show that these muscles not only have a unique origin, but additionally display a distinct temporal development, forming later than any other muscle group described to date. We further report that these muscles, found in the body of the animal, develop like head musculature rather than deploying the programme used by the trunk muscles. Using mouse genetics we reveal that these muscles are formed in trunk muscle mutants but are absent in head muscle mutants. In concordance with this conclusion, their connective tissue is neural crest in origin. Finally, we provide evidence that the mechanism by which these neck muscles develop is conserved in vertebrates.

The occipital lateral plate mesoderm is a novel source for vertebrate neck musculature

In vertebrates, body musculature originates from somites, whereas head muscles originate from the cranial mesoderm. Neck muscles are located in the transition between these regions. We show that the chick occipital lateral plate mesoderm has myogenic capacity and gives rise to large muscles located in the neck and thorax. We present molecular and genetic evidence to show that these muscles not only have a unique origin, but additionally display a distinct temporal development, forming later than any other muscle group described to date. We further report that these muscles, found in the body of the animal, develop like head musculature rather than deploying the programme used by the trunk muscles. Using mouse genetics we reveal that these muscles are formed in trunk muscle mutants but are absent in head muscle mutants. In concordance with this conclusion, their connective tissue is neural crest in origin. Finally, we provide evidence that the mechanism by which these neck muscles develop is conserved in vertebrates.

Schwann cells can be reprogrammed to multipotency by culture

Adult neural crest related-stem cells persist in adulthood, making them an ideal and easily accessible source of multipotent cells for potential clinical use. Recently, we reported the presence of neural crest-related stem cells within adult palatal ridges, thus raising the question of their localization in their endogenous niche. Using immunocytochemistry, reverse transcription-polymerase chain reaction, and correlative fluorescence and transmission electron microscopy, we identified myelinating Schwann cells within palatal ridges as a putative neural crest stem cell source. Palatal Schwann cells expressed nestin, p75(NTR), and S100. Correlative fluorescence and transmission electron microscopy revealed the exclusive nestin expression within myelinating Schwann cells. Palatal neural crest stem cells and nestin-positive Schwann cells isolated from adult sciatic nerves were able to grow under serum-free conditions as neurospheres in presence of FGF-2 and EGF. Spheres of palatal and sciatic origin showed overlapping expression pattern of neural crest stem cell and Schwann cell markers. Expression of the pluripotency factors Sox2, Klf4, c-Myc, Oct4, the NF-κB subunits p65, p50, and the NF-κB-inhibitor IκB-β were up-regulated in conventionally cultivated sciatic nerve Schwann cells and in neurosphere cultures. Finally, neurospheres of palatal and sciatic origin were able to differentiate into ectodermal, mesodermal, and endodermal cell types emphasizing their multipotency. Taken together, we show that nestin-positive myelinating Schwann cells can be reprogrammed into multipotent adult neural crest stem cells under appropriate culture conditions.

Generation of Schwann cell-derived multipotent neurospheres isolated from intact sciatic nerve

Schwann cells (SCs) are the supporting cells of the peripheral nervous system and originate from the neural crest. They play a unique role in the regeneration of injured peripheral nerves and have themselves a highly unstable phenotype as demonstrated by their unexpectedly broad differentiation potential. Thus, SCs can be considered as dormant, multipotent neural crest-derived progenitors or stem cells. Upon injury they de-differentiate via cellular reprogramming, re-enter the cell cycle and participate in the regeneration of the nerve. Here we describe a protocol for efficient generation of neurospheres from intact adult rat and murine sciatic nerve without the need of experimental in vivo pre-degeneration of the nerve prior to Schwann cell isolation. After isolation and removal of the connective tissue, the nerves are initially plated on poly-D-lysine coated cell culture plates followed by migration of the cells up to 80% confluence and a subsequent switch to serum-free medium leading to formation of multipotent neurospheres. In this context, migration of SCs from the isolated nerve, followed by serum-free cultivation of isolated SCs as neurospheres mimics the injury and reprograms fully differentiated SCs into a multipotent, neural crest-derived stem cell phenotype. This protocol allows reproducible generation of multipotent Schwann cell-derived neurospheres from sciatic nerve through cellular reprogramming by culture, potentially marking a starting point for future detailed investigations of the de-differentiation process.

Origin and regenerative potential of vertebrate mechanoreceptor-associated stem cells

Meissner corpuscles and Merkel cell neurite complexes are highly specialized mechanoreceptors present in the hairy and glabrous skin, as well as in different types of mucosa. Several reports suggest that after injury, such as after nerve crush, freeze injury, or dissection of the nerve, they are able to regenerate, particularly including reinnervation and repopulation of the mechanoreceptors by Schwann cells. However, little is known about mammalian cells responsible for these regenerative processes. Here we review cellular origin of this plasticity in the light of newly described adult neural crest-derived stem cell populations. We also discuss further potential multipotent stem cell populations with the ability to regenerate disrupted innervation and to functionally recover the mechanoreceptors. These capabilities are discussed as in context to cellularly reprogrammed Schwann cells and tissue resident adult mesenchymal stem cells.

Improved method for ex ovo-cultivation of developing chicken embryos for human stem cell xenografts

The characterization of human stem cells for the usability in regenerative medicine is particularly based on investigations regarding their differentiation potential in vivo. In this regard, the chicken embryo model represents an ideal model organism. However, the access to the chicken embryo is only achievable by windowing the eggshell resulting in limited visibility and accessibility in subsequent experiments. On the contrary, ex ovo-culture systems avoid such negative side effects. Here, we present an improved ex ovo-cultivation method enabling the embryos to survive 13 days in vitro. Optimized cultivation of chicken embryos resulted in a normal development regarding their size and weight. Our ex ovo-approach closely resembles the development of chicken embryos in ovo, as demonstrated by properly developed nervous system, bones, and cartilage at expected time points. Finally, we investigated the usability of our method for trans-species transplantation of adult stem cells by injecting human neural crest-derived stem cells into late Hamburger and Hamilton stages (HH26-HH28/E5-E6) of ex ovo-incubated embryos. We demonstrated the integration of human cells allowing experimentally easy investigation of the differentiation potential in the proper developmental context. Taken together, this ex ovo-method supports the prolonged cultivation of properly developing chicken embryos enabling integration studies of xenografted mammalian stem cells at late developmental stages.

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.

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.