1,330 research outputs found
Stem cell therapy for white matter disorders: don’t forget the microenvironment!
White matter disorders (WMDs) are a major source of handicap at all ages. They often lead to progressive neurological dysfunction and early death. Although causes are highly diverse, WMDs share the property that glia (astrocytes and oligodendrocytes) are among the cells primarily affected, and that myelin is either not formed or lost. Many WMDs might benefit from cell replacement therapies. Successful preclinical studies in rodent models have already led to the first clinical trials in humans using glial or oligodendrocyte progenitor cells aiming at (re)myelination. However, myelin is usually not the only affected structure. Neurons, microglia, and astrocytes are often also affected and are all important partners in creating the right conditions for proper white matter repair. Composition of the extracellular environment is another factor to be considered. Cell transplantation therapies might therefore require inclusion of non-oligodendroglial cell types and target more than only myelin repair. WMD patients would likely benefit from multimodal therapy approaches involving stem cell transplantation and microenvironment-targeting strategies to alter the local environment to a more favorable state for cell replacement. Furthermore most proof-of-concept studies have been performed with human cells in rodent disease models. Since human glial cells show a larger regenerative capacity than their mouse counterparts in the host mouse brain, microenvironmental factors affecting white matter recovery might be overlooked in rodent studies. We would like to stress that cell replacement therapy is a highly promising therapeutic option for WMDs, but a receptive microenvironment is crucia
Violence Defied? A Review of Prevention of Violence in the Public and Semi-public Domain
This report provides a synthesis of 48 studies of the effects of the
prevention of violence in the public and semi-public domain
Magnetic coupling in superconducting spin valves with strong ferromagnets
Quantum Matter and Optic
solQTL: a tool for QTL analysis, visualization and linking to genomes at SGN database
BACKGROUND: A common approach to understanding the genetic basis of complex traits is through identification of associated quantitative trait loci (QTL). Fine mapping QTLs requires several generations of backcrosses and analysis of large populations, which is time-consuming and costly effort. Furthermore, as entire genomes are being sequenced and an increasing amount of genetic and expression data are being generated, a challenge remains: linking phenotypic variation to the underlying genomic variation. To identify candidate genes and understand the molecular basis underlying the phenotypic variation of traits, bioinformatic approaches are needed to exploit information such as genetic map, expression and whole genome sequence data of organisms in biological databases. DESCRIPTION: The Sol Genomics Network (SGN, http://solgenomics.net) is a primary repository for phenotypic, genetic, genomic, expression and metabolic data for the Solanaceae family and other related Asterids species and houses a variety of bioinformatics tools. SGN has implemented a new approach to QTL data organization, storage, analysis, and cross-links with other relevant data in internal and external databases. The new QTL module, solQTL, http://solgenomics.net/qtl/, employs a user-friendly web interface for uploading raw phenotype and genotype data to the database, R/QTL mapping software for on-the-fly QTL analysis and algorithms for online visualization and cross-referencing of QTLs to relevant datasets and tools such as the SGN Comparative Map Viewer and Genome Browser. Here, we describe the development of the solQTL module and demonstrate its application. CONCLUSIONS: solQTL allows Solanaceae researchers to upload raw genotype and phenotype data to SGN, perform QTL analysis and dynamically cross-link to relevant genetic, expression and genome annotations. Exploration and synthesis of the relevant data is expected to help facilitate identification of candidate genes underlying phenotypic variation and markers more closely linked to QTLs. solQTL is freely available on SGN and can be used in private or public mode
Approach for Predicting Production Scenarios Focused on Cross Impact Analysis
AbstractOne of the most consistent challenges in business is anticipating what the future holds and what impact it may have on current production systems. The scenario technique is a well-established method for developing and forecasting multiple future development paths for companies. However, this method is mostly employed to develop and to support strategic long-term decisions. The core idea of the approach introduced in this paper is to convey the future impact of today's decisions on production systems to employees involved in production planning processes. With the help of immersive visualization, performed in virtual reality (VR) systems, planning participants can perceive how the factory must adapt to fit future demands.In this paper, the focus is on the fourth phase of the scenario technique – so called scenario development – and, in particular, the cross impact analysis. With this methodology, the interrelations, or cross impacts of the different basic elements are determined. The cross impact analysis results serve as a basis for the development of a standardized tool that can be used to create probable production scenarios out of given production systems. This standardized tool will facilitate the usage of the scenario technique for factory planning projects, as it focuses the immense diversity of future uncertainties companies are faced with on the factory level
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