Culture bag systems for clinical applications of adult human neural crest-derived stem cells

Introduction Facing the challenging treatment of neurodegenerative diseases as well as complex craniofacial injuries such as those common after cancer therapy, the field of regenerative medicine increasingly relies on stem cell transplantation strategies. Here, neural crest-derived stem cells (NCSCs) offer many promising applications, although scale up of clinical-grade processes prior to potential transplantations is currently limiting. In this study, we aimed to establish a clinical-grade, cost-reducing cultivation system for NCSCs isolated from the adult human nose using cGMP-grade Afc-FEP bags. Methods We cultivated human neural crest-derived stem cells from inferior turbinate (ITSCs) in a cell culture bag system using Afc-FEP bags in human blood plasma-supplemented medium. Investigations of viability, proliferation and expression profile of bag-cultured ITSCs were followed by DNA-content and telomerase activity determination. Cultivated ITSCs were introduced to directed in vitro differentiation assays to assess their potential for mesodermal and ectodermal differentiation. Mesodermal differentiation was determined using an enzyme activity assay (alkaline phosphatase, ALP), respective stainings (Alizarin Red S, Von Kossa and Oil Red O), and RT-PCR, while immunocytochemistry and synaptic vesicle recycling were applied to assay neuroectodermal differentiation of ITSCs. Results When cultivated within Afc-FEP bags, ITSCs grew three-dimensionally in a human blood plasma-derived matrix, thereby showing unchanged morphology, proliferation capability, viability and expression profile in comparison to three dimensionally-cultured ITSCs growing in standard cell culture plastics. Genetic stability of bag-cultured ITSCs was further accompanied by unchanged telomerase activity. Importantly, ITSCs retained their potential to differentiate into mesodermal cell types, particularly including ALP-active, Alizarin Red S-, and Von Kossa-positive osteogenic cell types, as well as adipocytes positive in Oil Red O assays. Bag culture further did not affect the potential of ITSCs to undergo differentiation into neuroectodermal cell types coexpressing β-III-tubulin and MAP2 and exhibiting the capability for synaptic vesicle recycling. Conclusions Here, we report for the first time the successful cultivation of human NCSCs within cGMP-grade Afc-FEP bags using a human blood plasma-supplemented medium. Our findings particularly demonstrate the unchanged differentiation capability and genetic stability of the cultivated NCSCs, suggesting the great potential of this culture system for future medical applications in the field of regenerative medicine.

Interaction of adult human neural crest-derived stem cells with a nanoporous titanium surface is sufficient to induce their osteogenic differentiation

Osteogenic differentiation of various adult stem cell populations such as neural crest-derived stem cells is of great interest in the context of bone regeneration. Ideally, exogenous differentiation should mimic an endogenous differentiation process, which is partly mediated by topological cues. To elucidate the osteoinductive potential of porous substrates with different pore diameters (30 nm, 100 nm), human neural crest-derived stem cells isolated from the inferior nasal turbinate were cultivated on the surface of nanoporous titanium covered membranes without additional chemical or biological osteoinductive cues. As controls, flat titanium without any topological features and osteogenic medium was used. Cultivation of human neural crest-derived stem cells on 30 nm pores resulted in osteogenic differentiation as demonstrated by alkaline phosphatase activity after seven days as well as by calcium deposition after 3 weeks of cultivation. In contrast, cultivation on flat titanium and on membranes equipped with 100 nm pores was not sufficient to induce osteogenic differentiation. Moreover, we demonstrate an increase of osteogenic transcripts including Osterix, Osteocalcin and up-regulation of Integrin β1 and α2 in the 30 nm pore approach only. Thus, transplantation of stem cells pre-cultivated on nanostructured implants might improve the clinical outcome by support of the graft adherence and acceleration of the regeneration process.

Alternative generation of CNS neural stem cells and PNS derivatives from neural crest-derived peripheral stem cells

Neural crest-derived stem cells (NCSCs) from the embryonic peripheral nervous system (PNS) can be reprogrammed in neurosphere (NS) culture to rNCSCs that produce central nervous system (CNS) progeny, including myelinating oligodendrocytes. Using global gene expression analysis we now demonstrate that rNCSCs completely lose their previous PNS characteristics and acquire the identity of neural stem cells derived from embryonic spinal cord. Reprogramming proceeds rapidly and results in a homogenous population of Olig2-, Sox3-, and Lex-positive CNS stem cells. Low-level expression of pluripotency inducing genes Oct4, Nanog, and Klf4 argues against a transient pluripotent state during reprogramming. The acquisition of CNS properties is prevented in the presence of BMP4 (BMP NCSCs) as shown by marker gene expression and the potential to produce PNS neurons and glia. In addition, genes characteristic for mesenchymal and perivascular progenitors are expressed, which suggests that BMP NCSCs are directed toward a pericyte progenitor/mesenchymal stem cell (MSC) fate. Adult NCSCs from mouse palate, an easily accessible source of adult NCSCs, display strikingly similar properties. They do not generate cells with CNS characteristics but lose the neural crest markers Sox10 and p75 and produce MSC-like cells. These findings show that embryonic NCSCs acquire a full CNS identity in NS culture. In contrast, MSC-like cells are generated from BMP NCSCs and pNCSCs, which reveals that postmigratory NCSCs are a source for MSC-like cells up to the adult stage.

Intrastriatal transplantation of adult human neural crest-derived stem cells improves functional outcome in parkinsonian rats

Parkinson's disease (PD) is considered the second most frequent and one of the most severe neurodegenerative diseases, with dysfunctions of the motor system and with nonmotor symptoms such as depression and dementia. Compensation for the progressive loss of dopaminergic (DA) neurons during PD using current pharmacological treatment strategies is limited and remains challenging. Pluripotent stem cell-based regenerative medicine may offer a promising therapeutic alternative, although the medical application of human embryonic tissue and pluripotent stem cells is still a matter of ethical and practical debate. Addressing these challenges, the present study investigated the potential of adult human neural crest-derived stem cells derived from the inferior turbinate (ITSCs) transplanted into a parkinsonian rat model. Emphasizing their capability to give rise to nervous tissue, ITSCs isolated from the adult human nose efficiently differentiated into functional mature neurons in vitro. Additional successful dopaminergic differentiation of ITSCs was subsequently followed by their transplantation into a unilaterally lesioned 6-hydroxydopamine rat PD model. Transplantation of predifferentiated or undifferentiated ITSCs led to robust restoration of rotational behavior, accompanied by significant recovery of DA neurons within the substantia nigra. ITSCs were further shown to migrate extensively in loose streams primarily toward the posterior direction as far as to the midbrain region, at which point they were able to differentiate into DA neurons within the locus ceruleus. We demonstrate, for the first time, that adult human ITSCs are capable of functionally recovering a PD rat model.

Neural population models and cortical field theory: overview

The term neural population models (NPMs) is used here as catchall for a wide range of approaches that have been variously called neural mass models, mean field models, neural field models, bulk models, and so forth. All NPMs attempt to describe the collective action of neural assemblies directly. Some NPMs treat the densely populated tissue of cortex as an excitable medium, leading to spatially continuous cortical field theories (CFTs). An indirect approach would start by modelling individual cells and then would explain the collective action of a group of cells by coupling many individual models together. In contrast, NPMs employ collective state variables, typically defined as averages over the group of cells, in order to describe the population activity directly in a single model. The strength and the weakness of his approach are hence one and the same: simplification by bulk. Is this justified and indeed useful, or does it lead to oversimplification which fails to capture the pheno ...

Emergence of spatially heterogeneous burst suppression in a neural field model of electrocortical activity

Burst suppression in the electroencephalogram (EEG) is a well-described phenomenon that occurs during deep anesthesia, as well as in a variety of congenital and acquired brain insults. Classically it is thought of as spatially synchronous, quasi-periodic bursts of high amplitude EEG separated by low amplitude activity. However, its characterization as a “global brain state” has been challenged by recent results obtained with intracranial electrocortigraphy. Not only does it appear that burst suppression activity is highly asynchronous across cortex, but also that it may occur in isolated regions of circumscribed spatial extent. Here we outline a realistic neural field model for burst suppression by adding a slow process of synaptic resource depletion and recovery, which is able to reproduce qualitatively the empirically observed features during general anesthesia at the whole cortex level. Simulations reveal heterogeneous bursting over the model cortex and complex spatiotemporal dynamics during simulated anesthetic action, and provide forward predictions of neuroimaging signals for subsequent empirical comparisons and more detailed characterization. Because burst suppression corresponds to a dynamical end-point of brain activity, theoretically accounting for its spatiotemporal emergence will vitally contribute to efforts aimed at clarifying whether a common physiological trajectory is induced by the actions of general anesthetic agents. We have taken a first step in this direction by showing that a neural field model can qualitatively match recent experimental data that indicate spatial differentiation of burst suppression activity across cortex.

RE1 silencing transcription factor/neuron-restrictive silencing factor regulates expansion of adult mouse subventricular zone-derived neural stem/progenitor cells in vitro

Adult neural stem cell (aNSC) activity is tuned by external stimuli through the recruitment of transcription factors. This study examines the RE1 silencing transcription factor (REST) in neural stem/progenitor cells isolated from the subventricular zone of adult mouse brain and provides the first extensive characterization of REST-mediated control of the cellular and molecular properties. This study shows that REST knockdown affects the capacity of progenitor cells to generate neurospheres, reduces cell proliferation, and triggers cell differentiation despite the presence of growth factors. Genome- and transcriptome-wide analyses show that REST binding sites are significantly enriched in genes associated with synaptic transmission and nervous system development and function. Seeking candidate regulators of aNSC function, this study identifies a member of the bone morphogenetic protein (BMP) family, BMP6, the mRNA and protein of which increased after REST knockdown. The results of this study extend previous findings, demonstrating a reciprocal control of REST expression by BMPs. Administration of exogenous BMP6 inhibits aNSC proliferation and induces the expression of the astrocytic marker glial fibrillary acidic protein, highlighting its antimitogenic and prodifferentiative effects. This study suggests that BMP6 produced in a REST-regulated manner together with other signals can contribute to regulation of NSC maintenance and fate. © 2015 Wiley Periodicals, Inc.

B-spline neural network based single-carrier frequency domain equalisation for Hammerstein channels

A practical single-carrier (SC) block transmission with frequency domain equalisation (FDE) system can generally be modelled by the Hammerstein system that includes the nonlinear distortion effects of the high power amplifier (HPA) at transmitter. For such Hammerstein channels, the standard SC-FDE scheme no longer works. We propose a novel Bspline neural network based nonlinear SC-FDE scheme for Hammerstein channels. In particular, we model the nonlinear HPA, which represents the complex-valued static nonlinearity of the Hammerstein channel, by two real-valued B-spline neural networks, one for modelling the nonlinear amplitude response of the HPA and the other for the nonlinear phase response of the HPA. We then develop an efficient alternating least squares algorithm for estimating the parameters of the Hammerstein channel, including the channel impulse response coefficients and the parameters of the two B-spline models. Moreover, we also use another real-valued B-spline neural network to model the inversion of the HPA’s nonlinear amplitude response, and the parameters of this inverting B-spline model can be estimated using the standard least squares algorithm based on the pseudo training data obtained as a byproduct of the Hammerstein channel identification. Equalisation of the SC Hammerstein channel can then be accomplished by the usual one-tap linear equalisation in frequency domain as well as the inverse Bspline neural network model obtained in time domain. The effectiveness of our nonlinear SC-FDE scheme for Hammerstein channels is demonstrated in a simulation study.

Exploration of the neural correlates of cerebral palsy for sensorimotor BCI control

Cerebral palsy (CP) includes a broad range of disorders, which can result in impairment of posture and movement control. Brain-computer interfaces (BCIs) have been proposed as assistive devices for individuals with CP. Better understanding of the neural processing underlying motor control in affected individuals could lead to more targeted BCI rehabilitation and treatment options. We have explored well-known neural correlates of movement, including event-related desynchronization (ERD), phase synchrony, and a recently-introduced measure of phase dynamics, in participants with CP and healthy control participants. Although present, significantly less ERD and phase locking were found in the group with CP. Additionally, inter-group differences in phase dynamics were also significant. Taken together these findings suggest that users with CP exhibit lower levels of motor cortex activation during motor imagery, as reflected in lower levels of ongoing mu suppression and less functional connectivity. These differences indicate that development of BCIs for individuals with CP may pose additional challenges beyond those faced in providing BCIs to healthy individuals.

Automated identification of neural correlates of continuous variables

Background: The electroencephalogram (EEG) may be described by a large number of different feature types and automated feature selection methods are needed in order to reliably identify features which correlate with continuous independent variables. New method: A method is presented for the automated identification of features that differentiate two or more groups inneurologicaldatasets basedupona spectraldecompositionofthe feature set. Furthermore, the method is able to identify features that relate to continuous independent variables. Results: The proposed method is first evaluated on synthetic EEG datasets and observed to reliably identify the correct features. The method is then applied to EEG recorded during a music listening task and is observed to automatically identify neural correlates of music tempo changes similar to neural correlates identified in a previous study. Finally,the method is applied to identify neural correlates of music-induced affective states. The identified neural correlates reside primarily over the frontal cortex and are consistent with widely reported neural correlates of emotions. Comparison with existing methods: The proposed method is compared to the state-of-the-art methods of canonical correlation analysis and common spatial patterns, in order to identify features differentiating synthetic event-related potentials of different amplitudes and is observed to exhibit greater performance as the number of unique groups in the dataset increases. Conclusions: The proposed method is able to identify neural correlates of continuous variables in EEG datasets and is shown to outperform canonical correlation analysis and common spatial patterns.

Neural correlates of emotional responses to music: an EEG study

This paper presents an EEG study into the neural correlates of music-induced emotions. We presented participants with a large dataset containing musical pieces in different styles, and asked them to report on their induced emotional responses. We found neural correlates of music-induced emotion in a number of frequencies over the pre-frontal cortex. Additionally, we found a set of patterns of functional connectivity, defined by inter-channel coherence measures,to be significantly different between groups of music-induced emotional responses.

Adaptive B-spline neural network based nonlinear equalization for high-order QAM systems with nonlinear transmit high power amplifier

High bandwidth-efficiency quadrature amplitude modulation (QAM) signaling widely adopted in high-rate communication systems suffers from a drawback of high peak-toaverage power ratio, which may cause the nonlinear saturation of the high power amplifier (HPA) at transmitter. Thus, practical high-throughput QAM communication systems exhibit nonlinear and dispersive channel characteristics that must be modeled as a Hammerstein channel. Standard linear equalization becomes inadequate for such Hammerstein communication systems. In this paper, we advocate an adaptive B-Spline neural network based nonlinear equalizer. Specifically, during the training phase, an efficient alternating least squares (LS) scheme is employed to estimate the parameters of the Hammerstein channel, including both the channel impulse response (CIR) coefficients and the parameters of the B-spline neural network that models the HPA’s nonlinearity. In addition, another B-spline neural network is used to model the inversion of the nonlinear HPA, and the parameters of this inverting B-spline model can easily be estimated using the standard LS algorithm based on the pseudo training data obtained as a natural byproduct of the Hammerstein channel identification. Nonlinear equalisation of the Hammerstein channel is then accomplished by the linear equalization based on the estimated CIR as well as the inverse B-spline neural network model. Furthermore, during the data communication phase, the decision-directed LS channel estimation is adopted to track the time-varying CIR. Extensive simulation results demonstrate the effectiveness of our proposed B-Spline neural network based nonlinear equalization scheme.