N-syndecan and HB-GAM in neural migration and differentiation : Modulation of growth factor activity in brain

The juvenile sea squirt wanders through the sea searching for a suitable rock or hunk of coral to cling to and make its home for life. For this task it has a rudimentary nervous system. When it finds its spot and takes root, it doesn't need its brain any more so it eats it. It's rather like getting tenure. Daniel C. Dennett (from Consciousness Explained, 1991) The little sea squirt needs its brain for a task that is very simple and short. When the task is completed, the sea squirt starts a new life in a vegetative state, after having a nourishing meal. The little brain is more tightly structured than our massive primate brains. The number of neurons is exact, no leeway in neural proliferation is tolerated. Each neuroblast migrates exactly to the correct position, and only a certain number of connections with the right companions is allowed. In comparison, growth of a mammalian brain is a merry mess. The reason is obvious: Squirt brain needs to perform only a few, predictable functions, before becoming waste. The more mobile and complex mammals engage their brains in tasks requiring quick adaptation and plasticity in a constantly changing environment. Although the regulation of nervous system development varies between species, many regulatory elements remain the same. For example, all multicellular animals possess a collection of proteoglycans (PG); proteins with attached, complex sugar chains called glycosaminoglycans (GAG). In development, PGs participate in the organization of the animal body, like in the construction of parts of the nervous system. The PGs capture water with their GAG chains, forming a biochemically active gel at the surface of the cell, and in the extracellular matrix (ECM). In the nervous system, this gel traps inside it different molecules: growth factors and ECM-associated proteins. They regulate the proliferation of neural stem cells (NSC), guide the migration of neurons, and coordinate the formation of neuronal connections. In this work I have followed the role of two molecules contributing to the complexity of mammalian brain development. N-syndecan is a transmembrane heparan sulfate proteoglycan (HSPG) with cell signaling functions. Heparin-binding growth-associated molecule (HB-GAM) is an ECM-associated protein with high expression in the perinatal nervous system, and high affinity to HS and heparin. N-syndecan is a receptor for several growth factors and for HB-GAM. HB-GAM induces specific signaling via N-syndecan, activating c-Src, calcium/calmodulin-dependent serine protein kinase (CASK) and cortactin. By studying the gene knockouts of HB-GAM and N-syndecan in mice, I have found that HB-GAM and N-syndecan are involved as a receptor-ligand-pair in neural migration and differentiation. HB-GAM competes with the growth factors fibriblast growth factor (FGF)-2 and heparin-binding epidermal growth factor (HB-EGF) in HS-binding, causing NSCs to stop proliferation and to differentiate, and affects HB-EGF-induced EGF receptor (EGFR) signaling in neural cells during migration. N-syndecan signaling affects the motility of young neurons, by boosting EGFR-mediated cell migration. In addition, these two receptors form a complex at the surface of the neurons, probably creating a motility-regulating structure.

Differentiation of neural stem cells in fragile X syndrome

Multipotent stem cells can self-renew and give rise to multiple cell types. One type of mammalian multipotent stem cells are neural stem cells (NSC)s, which can generate neurons, astrocytes and oligodendrocytes. NSCs are likely involved in learning and memory, but their exact role in cognitive function in the developing and adult brain is unclear. We have studied properties of NSCs in fragile X syndrome (FXS), which is the most common form of inherited mental retardation. FXS is caused by the lack of functional fragile X mental retardation protein (FMRP). FMRP is involved in the regulation of postsynaptic protein synthesis in a group I metabotropic glutamate receptor 5 (mGluR5)-dependent manner. In the absence of functional FMRP, the formation of functional synapses is impaired in the forebrain which results in alterations in synaptic plasticity. In our studies, we found that FMRP-deficient NSCs generated more neurons and less glia than control NSCs. The newborn neurons derived from FMRP-deficient NSCs showed an abnormally immature morphology. Furthermore, FMRP-deficient NSCs exhibited aberrant oscillatory Ca2+ responses to glutamate, which were specifically abolished by an antagonist of the mGluR5 receptor. The data suggested alterations in glutamatergic differentiation of FMRP-deficient NSCs and were further supported by an accumulation of cells committed to glutamatergic lineage in the subventricular zone of the embryonic Fmr1-knockout (Fmr1-KO) neocortex. Postnatally, the aberrant cells likely contributed to abnormal formation of the neocortex. The findings suggested a defect in the differentiation of distinct glutamatergic mGluR5 responsive cells in the absence of functional FMRP. Furthermore, we found that in the early postnatal Fmr1-KO mouse brain, the expression of mRNA for regulator of G-protein signalling-4 (RGS4) was decreased which was in line with disturbed G-protein signalling in NSCs lacking FMRP. Brain derived neurotrophic factor (BDNF) promotes neuronal differentiation of NSCs as the absence of FMRP was shown to do. This led us to study the effect of impaired BDNF/TrkB receptor signaling on NSCs by overexpression of TrkB.T1 receptor isoform. We showed that changes in the relative expression levels of the full-length and truncated TrkB isoforms influenced the replication capacity of NSCs. After the differentiation, the overexpression of TrkB.T1 increased neuronal turnover. To summarize, FMRP and TrkB signaling are involved in normal differentiation of NSCs in the developing brain. Since NSCs might have potential for therapeutic interventions in a variety of neurological disorders, our findings may be useful in the design of pharmacological interventions in neurological disorders of learning and memory.

From neural stem cells to precursors : Molecular regulation of self-renewal and differentiation

Stem cells are responsible for tissue turnover throughout lifespan. Only highly controlled specific environment, the stem cell niche , can sustain undifferentiated stem cell-pool. The balance between maintenance and differentiation is crucial for individual s health: uncontrolled stem cell self-renewal or proliferation can lead to hyperplasia and mutations that further provoke malignant transformation of the cells. On the other hand, uninhibited differentiation may result in diminished stem cell population, which is unable to maintain tissue turnover. The mechanisms that control the switch from maintenance to differentiation in stem cells are not well known. The same mechanisms that direct the self-renewal and proliferation in normal stem cells are likely to be also involved in maintenance of cancer stem cell . Cancer stem cells exhibit stem cell like properties such as self-renewal- and differentiation capacity and they can also regenerate the tumor tissue. In this thesis, I have investigated the effect of classical oncogenes E6/E7 and c-Myc, tumor suppressors p53 and retinoblastoma (pRb) family, and vascular endothelial growth factor (VEGF) subfamily and glial cell line-derived neurothropic factor (GDNF) family ligands on behavior of embryonic neural stem cells (NSCs) and progenitors. The study includes also the characterization of cytoskeletal tumor suppressor neurofibromatosis 2 (NF2) protein merlin and ezrin-radixin-moesin (ERM) protein ezrin expression in neural progenitors cells and their progeny. This study reveals some potential mechanisms regarding to NSCs maintenance. In summary, the studied molecules are able to shift the balance either towards stem cell maintenance or differentiation; tumor suppressor p53 represses whereas E6/E7 oncogenes and c-Myc increase the proportion of self-renewing and proliferating NSCs or progenitors. The data suggests that active MEK-ERK signaling is critical for self-renewal of normal and oncogene expressing NSCs. In addition, the results indicate that expression of cytoskeletal tumor suppressor merlin and ERM protein ezrin in central nervous system (CNS) tissue and progenitors indicates their role in cell differentiation. Furthermore, the data suggests that VEGF-C a factor involved in lymphatic system development, angiogenesis, neovascularization and metastasis but also in maintenance of some neural populations in brain is a novel thropic factor for progenitors in early sympathetic nervous system (SNS). It seems that VEGF-C dose dependently through ERK-pathway supports the proliferation and survival of early sympathetic progenitor cells, and the effect is comparable to that of GDNF family ligands.

Human mesenchymal stem cells retain multilineage differentiation capacity including neural marker expression after extended in vitro expansion

The suitability of human mesenchymal stem cells (hMSCs) in regenerative medicine relies on retention of their proliferative expansion potential in conjunction with the ability to differentiate toward multiple lineages. Successful utilisation of these cells in clinical applications linked to tissue regeneration requires consideration of biomarker expression, time in culture and donor age, as well as their ability to differentiate towards mesenchymal (bone, cartilage, fat) or non-mesenchymal (e.g., neural) lineages. To identify potential therapeutic suitability we examined hMSCs after extended expansion including morphological changes, potency (stemness) and multilineage potential. Commercially available hMSC populations were expanded in vitro for > 20 passages, equating to > 60 days and > 50 population doublings. Distinct growth phases (A-C) were observed during serial passaging and cells were characterised for stemness and lineage markers at representative stages (Phase A: P+5, approximately 13 days in culture; Phase B: P+7, approximately 20 days in culture; and Phase C: P+13, approximately 43 days in culture). Cell surface markers, stem cell markers and lineage-specific markers were characterised by FACS, ICC and Q-PCR revealing MSCs maintained their multilineage potential, including neural lineages throughout expansion. Co-expression of multiple lineage markers along with continued CD45 expression in MSCs did not affect completion of osteogenic and adipogenic specification or the formation of neurospheres. Improved standardised isolation and characterisation of MSCs may facilitate the identification of biomarkers to improve therapeutic efficacy to ensure increased reproducibility and routine production of MSCs for therapeutic applications including neural repair.

Cell surface heparan sulfate proteoglycans as novel markers of human neural stem cell fate determination

Multipotent neural stem cells (NSCs) provide a model to investigate neurogenesis and develop mechanisms of cell transplantation. In order to define improved markers of stemness and lineage specificity, we examined self-renewal and multi-lineage markers during long-term expansion and under neuronal and astrocyte differentiating conditions in human ESC-derived NSCs (hNSC H9 cells). In addition, with proteoglycans ubiquitous to the neural niche, we also examined heparan sulfate proteoglycans (HSPGs) and their regulatory enzymes. Our results demonstrate that hNSC H9 cells maintain self-renewal and multipotent capacity during extended culture and express HS biosynthesis enzymes and several HSPG core protein syndecans (SDCs) and glypicans (GPCs) at a high level. In addition, hNSC H9 cells exhibit high neuronal and a restricted glial differentiative potential with lineage differentiation significantly increasing expression of many HS biosynthesis enzymes. Furthermore, neuronal differentiation of the cells upregulated SDC4, GPC1, GPC2, GPC3 and GPC6 expression with increased GPC4 expression observed under astrocyte culture conditions. Finally, downregulation of selected HSPG core proteins altered hNSC H9 cell lineage potential. These findings demonstrate an involvement for HSPGs in mediating hNSC maintenance and lineage commitment and their potential use as novel markers of hNSC and neural cell lineage specification.

An adaptive drug delivery design using neural networks for effective treatment of infectious diseases: A simulation study

An adaptive drug delivery design is presented in this paper using neural networks for effective treatment of infectious diseases. The generic mathematical model used describes the coupled evolution of concentration of pathogens, plasma cells, antibodies and a numerical value that indicates the relative characteristic of a damaged organ due to the disease under the influence of external drugs. From a system theoretic point of view, the external drugs can be interpreted as control inputs, which can be designed based on control theoretic concepts. In this study, assuming a set of nominal parameters in the mathematical model, first a nonlinear controller (drug administration) is designed based on the principle of dynamic inversion. This nominal drug administration plan was found to be effective in curing "nominal model patients" (patients whose immunological dynamics conform to the mathematical model used for the control design exactly. However, it was found to be ineffective in curing "realistic model patients" (patients whose immunological dynamics may have off-nominal parameter values and possibly unwanted inputs) in general. Hence, to make the drug delivery dosage design more effective for realistic model patients, a model-following adaptive control design is carried out next by taking the help of neural networks, that are trained online. Simulation studies indicate that the adaptive controller proposed in this paper holds promise in killing the invading pathogens and healing the damaged organ even in the presence of parameter uncertainties and continued pathogen attack. Note that the computational requirements for computing the control are very minimal and all associated computations (including the training of neural networks) can be carried out online. However it assumes that the required diagnosis process can be carried out at a sufficient faster rate so that all the states are available for control computation.

Classification of Indian meteorological stations using cluster and fuzzy cluster analysis, and Kohonen artificial neural networks

The present study deals with the application of cluster analysis, Fuzzy Cluster Analysis (FCA) and Kohonen Artificial Neural Networks (KANN) methods for classification of 159 meteorological stations in India into meteorologically homogeneous groups. Eight parameters, namely latitude, longitude, elevation, average temperature, humidity, wind speed, sunshine hours and solar radiation, are considered as the classification criteria for grouping. The optimal number of groups is determined as 14 based on the Davies-Bouldin index approach. It is observed that the FCA approach performed better than the other two methodologies for the present study.

Neural mechanisms underlying perilesional transcranial direct current stimulation in aphasia: A feasibility study

Little is known about the neural mechanisms by which transcranial direct current stimulation (tDCS) impacts on language processing in post-stroke aphasia. This was addressed in a proof-of-principle study that explored the effects of tDCS application in aphasia during simultaneous functional magnetic resonance imaging (fMRI). We employed a single subject, cross-over, sham-tDCS controlled design, and the stimulation was administered to an individualized perilesional stimulation site that was identified by a baseline fMRI scan and a picture naming task. Peak activity during the baseline scan was located in the spared left inferior frontal gyrus and this area was stimulated during a subsequent cross-over phase. tDCS was successfully administered to the target region and anodal- vs. sham-tDCS resulted in selectively increased activity at the stimulation site. Our results thus demonstrate that it is feasible to precisely target an individualized stimulation site in aphasia patients during simultaneous fMRI, which allows assessing the neural mechanisms underlying tDCS application. The functional imaging results of this case report highlight one possible mechanism that may have contributed to beneficial behavioral stimulation effects in previous clinical tDCS trials in aphasia. In the future, this approach will allow identifying distinct patterns of stimulation effects on neural processing in larger cohorts of patients. This may ultimately yield information about the variability of tDCS effects on brain functions in aphasia.

Rotorcraft parameter estimation using radial basis function neural network

Increased emphasis on rotorcraft performance and perational capabilities has resulted in accurate computation of aerodynamic stability and control parameters. System identification is one such tool in which the model structure and parameters such as aerodynamic stability and control derivatives are derived. In the present work, the rotorcraft aerodynamic parameters are computed using radial basis function neural networks (RBFN) in the presence of both state and measurement noise. The effect of presence of outliers in the data is also considered. RBFN is found to give superior results compared to finite difference derivatives for noisy data. (C) 2010 Elsevier Inc. All rights reserved.

Search for the Higgs Boson Using Neural Networks in Events with Missing Energy and b-Quark Jets in pp̅ Collisions at √s=1.96 TeV

We report on a search for the standard model Higgs boson produced in association with a $W$ or $Z$ boson in $p\bar{p}$ collisions at $\sqrt{s} = 1.96$ TeV recorded by the CDF II experiment at the Tevatron in a data sample corresponding to an integrated luminosity of 2.1 fb$^{-1}$. We consider events which have no identified charged leptons, an imbalance in transverse momentum, and two or three jets where at least one jet is consistent with originating from the decay of a $b$ hadron. We find good agreement between data and predictions. We place 95% confidence level upper limits on the production cross section for several Higgs boson masses ranging from 110$\gevm$ to 150$\gevm$. For a mass of 115$\gevm$ the observed (expected) limit is 6.9 (5.6) times the standard model prediction.