Mild Hypoxia Enhances Proliferation and Multipotency of Human Neural Stem Cells

Neural stem cells (NSCs) represent an optimal tool for studies and therapy of neurodegenerative diseases. We recently established a v-myc immortalized human NSC (IhNSC) line, which retains stem properties comparable to parental cells. Oxygen concentration is one of the most crucial environmental conditions for cell proliferation and differentiation both in vitro and in vivo. In the central nervous system, physiological concentrations of oxygen range from 0.55 to 8% oxygen. In particular, in the in the subventricular zone niche area, it's estimated to be 2.5 to 3%.We investigated in vitro the effects of 1, 2.5, 5, and 20% oxygen concentrations on IhNSCs both during proliferation and differentiation. The highest proliferation rate, evaluated through neurosphere formation assay, was obtained at 2.5 and 5% oxygen, while 1% oxygen was most noxious for cell survival. The differentiation assays showed that the percentages of β-tubIII+ or MAP2+ neuronal cells and of GalC+ oligodendrocytes were significantly higher at 2.5% compared with 1, 5, or 20% oxygen at 17 days in vitro. Mild hypoxia (2.5 to 5% oxygen) promoted differentiation into neuro-oligodendroglial progenitors as revealed by the higher percentage of MAP2+/Ki67+ and GalC+/Ki67+ residual proliferating progenitors, and enhanced the yield of GABAergic and slightly of glutamatergic neurons compared to 1% and 20% oxygen where a significant percentage of GFAP+/nestin+ cells were still present at 17 days of differentiation.These findings raise the possibility that reduced oxygen levels occurring in neuronal disorders like cerebral ischemia transiently lead to NSC remaining in a state of quiescence. Conversely, mild hypoxia favors NSC proliferation and neuronal and oligodendroglial differentiation, thus providing an important advance and a useful tool for NSC-mediated therapy of ischemic stroke and neurodegenerative diseases like Parkinson's disease, multiple sclerosis, and Alzheimer's disease

Hierarchical classification of complex landscape with VHR pan-sharpened satellite data and OBIA techniques

Land-cover/land-use thematic maps are a major need in urban and country planning. This paper demonstrates the capabilities of Object Based Image Analysis in multi-scale thematic classification of a complex sub-urban landscape with simultaneous presence of agricultural, residential and industrial areas using pan-sharpened very high resolution satellite imagery. The classification process was carried out step by step through the creation of different hierarchical segmentation levels and exploiting spectral, geometric and relational features. The framework returned a detailed land-cover/land-use map with a Cohen’s kappa coefficient of 0.84 and an overall accuracy of 85%

A Knowledge Brokering Framework for Integrated Landscape Management

Sustainable land management is at the heart of some of the most intractable challenges facing humanity in the 21st century. It is critical for tackling biodiversity loss, land degradation, climate change and the decline of ecosystem services. It underpins food production, livelihoods, dietary health, social equity, climate change adaptation, and many other outcomes. However, interdependencies, trade-offs, time lags, and non-linear responses make it difficult to predict the combined effects of land management decisions. Policy decisions also have to be made in the context of conflicting interests, values and power dynamics of those living on the land and those affected by the consequences of land use decisions. This makes designing and coordinating effective land management policies and programmes highly challenging. The difficulty is exacerbated by the scarcity of reliable data on the impacts of land management on the environment and livelihoods. This poses a challenge for policymakers and practitioners in governments, development banks, non-governmental organisations, and other institutions. It also sets demands for researchers, who are under ever increasing pressure from funders to demonstrate uptake and impact of their work. Relatively few research methods exist that can address such questions in a holistic way. Decision makers and researchers need to work together to help untangle, contextualise and interpret fragmented evidence through systems approaches to make decisions in spite of uncertainty. Individuals and institutions acting as knowledge brokers can support these interactions by facilitating the co-creation and use of scientific and other knowledge. Given the patchy nature of data and evidence, particularly in developing countries, it is important to draw on the full range of available models, tools and evidence. In this paper we review the use of evidence to inform multiple-objective integrated landscape management policies and programmes, focusing on how to simultaneously achieve different sustainable development objectives in diverse landscapes. We set out key success factors for evidence-based decision-making, which are summarised into 10 key principles for integrated landscape management knowledge brokering in integrated landscape management and 12 key skills for knowledge brokers. We finally propose a decision-support framework to organise evidence that can be used to tackle different types of land management policy decision

Transplantation of clinical-grade human neural stem cells reduces neuroinflammation, prolongs survival and delays disease progression in the SOD1 rats.

Abstract Stem cells are emerging as a therapeutic option for incurable diseases, such as Amyotrophic Lateral Sclerosis (ALS). However, critical issues are related to their origin as well as to the need to deepen our knowledge of the therapeutic actions exerted by these cells. Here, we investigate the therapeutic potential of clinical-grade human neural stem cells (hNSCs) that have been successfully used in a recently concluded phase I clinical trial for ALS patients (NCT01640067). The hNSCs were transplanted bilaterally into the anterior horns of the lumbar spinal cord (four grafts each, segments L3–L4) of superoxide dismutase 1 G93A transgenic rats (SOD1 rats) at the symptomatic stage. Controls included untreated SOD1 rats (CTRL) and those treated with HBSS (HBSS). Motor symptoms and histological hallmarks of the disease were evaluated at three progressive time points: 15 and 40 days after transplant (DAT), and end stage. Animals were treated by transient immunosuppression (for 15 days, starting at time of transplantation). Under these conditions, hNSCs integrated extensively within the cord, differentiated into neural phenotypes and migrated rostro-caudally, up to 3.77 ± 0.63 cm from the injection site. The transplanted cells delayed decreases in body weight and deterioration of motor performance in the SOD1 rats. At 40DAT, the anterior horns at L3–L4 revealed a higher density of motoneurons and fewer activated astroglial and microglial cells. Accordingly, the overall survival of transplanted rats was significantly enhanced with no rejection of hNSCs observed. We demonstrated that the beneficial effects observed after stem cell transplantation arises from multiple events that counteract several aspects of the disease, a crucial feature for multifactorial diseases, such as ALS. The combination of therapeutic approaches that target different pathogenic mechanisms of the disorder, including pharmacology, molecular therapy and cell transplantation, will increase the chances of a clinically successful therapy for ALS

Human neural stem cell transplantation in ALS: initial results from a phase I trial

We report the initial results from a phase I clinical trial for ALS. We transplanted GMP-grade, fetal human neural stem cells from natural in utero death (hNSCs) into the anterior horns of the spinal cord to test for the safety of both cells and neurosurgical procedures in these patients. The trial was approved by the Istituto Superiore di Sanit\ue0 and the competent Ethics Committees and was monitored by an external Safety Board

Solitary waves in the Nonlinear Dirac Equation

In the present work, we consider the existence, stability, and dynamics of solitary waves in the nonlinear Dirac equation. We start by introducing the Soler model of self-interacting spinors, and discuss its localized waveforms in one, two, and three spatial dimensions and the equations they satisfy. We present the associated explicit solutions in one dimension and numerically obtain their analogues in higher dimensions. The stability is subsequently discussed from a theoretical perspective and then complemented with numerical computations. Finally, the dynamics of the solutions is explored and compared to its non-relativistic analogue, which is the nonlinear Schr{\"o}dinger equation. A few special topics are also explored, including the discrete variant of the nonlinear Dirac equation and its solitary wave properties, as well as the PT-symmetric variant of the model

Long-Term Survival of Human Neural Stem Cells in the Ischemic Rat Brain upon Transient Immunosuppression

Understanding the physiology of human neural stem cells (hNSCs) in the context of cell therapy for neurodegenerative disorders is of paramount importance, yet large-scale studies are hampered by the slow-expansion rate of these cells. To overcome this issue, we previously established immortal, non-transformed, telencephalic-diencephalic hNSCs (IhNSCs) from the fetal brain. Here, we investigated the fate of these IhNSC's immediate progeny (i.e. neural progenitors; IhNSC-Ps) upon unilateral implantation into the corpus callosum or the hippocampal fissure of adult rat brain, 3 days after global ischemic injury. One month after grafting, approximately one fifth of the IhNSC-Ps had survived and migrated through the corpus callosum, into the cortex or throughout the dentate gyrus of the hippocampus. By the fourth month, they had reached the ipsilateral subventricular zone, CA1-3 hippocampal layers and the controlateral hemisphere. Notably, these results could be accomplished using transient immunosuppression, i.e administering cyclosporine for 15 days following the ischemic event. Furthermore, a concomitant reduction of reactive microglia (Iba1+ cells) and of glial, GFAP+ cells was also observed in the ipsilateral hemisphere as compared to the controlateral one. IhNSC-Ps were not tumorigenic and, upon in vivo engraftment, underwent differentiation into GFAP+ astrocytes, and β-tubulinIII+ or MAP2+ neurons, which displayed GABAergic and GLUTAmatergic markers. Electron microscopy analysis pointed to the formation of mature synaptic contacts between host and donor-derived neurons, showing the full maturation of the IhNSC-P-derived neurons and their likely functional integration into the host tissue. Thus, IhNSC-Ps possess long-term survival and engraftment capacity upon transplantation into the globally injured ischemic brain, into which they can integrate and mature into neurons, even under mild, transient immunosuppressive conditions. Most notably, transplanted IhNSC-P can significantly dampen the inflammatory response in the lesioned host brain. This work further supports hNSCs as a reliable and safe source of cells for transplantation therapy in neurodegenerative disorders

High-resolution SAR and high-resolution optical data integration for sub-urban land-cover classification

This study shows a comparison between pixel-based and object-based approaches in data fusion of high-resolution multispectral GeoEye-1 imagery and high-resolution COSMO-SkyMed SAR data for land-cover/land-use classification. The per-pixel method consisted of a maximum likelihood classification of fused data based on discrete wavelet transform and a classification from optical images alone. Optical and SAR data were then integrated into an object-oriented environment with the addition of texture measurements from SAR and classified with a nearest neighbor approach. Results were compared with the classification of the GeoEye-1 data alone and the outcomes pointed out that per-pixel data fusion did not improve the classification accuracy, while the object-based data integration increased the overall accuracy from 73% to 89%. According to results, an object-based approach with the introduction of adjunctive information layers proved to be more performing in land-cover/land-use classification than standard pixel-based methods