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  • 1
    ISSN: 1460-9568
    Source: Blackwell Publishing Journal Backfiles 1879-2005
    Topics: Medicine
    Notes: We have examined several neurochemical and behavioural parameters related to the function of the mesolimbic dopamine (DA) pathway in animals treated with nicotine following three modes of drug administration, i.e. systemic intraperitoneal injection, intra-accumbens (Acb) infusion or intraventral tegmental area (intra-VTA) microinjection. The present modes of systemic, intra-Acb and intra-VTA nicotine administration elicited comparable acute increases in dialysate DA levels from the Acb. The increase in extracellular DA levels was paralleled by a significant enhancement of locomotion in a habituated environment in the case of systemic or intra-VTA nicotine administration, whereas unilateral or bilateral intra-Acb nicotine infusion was ineffective, showing that accumbal DA increase is not sufficient to elicit locomotion in this experimental paradigm. Intra-VTA, but not systemic or intra-Acb, nicotine administration caused a long-term (at least 24-h) increase in basal dialysate DA levels from the Acb. In addition, significant increases in tyrosine hydroxylase (TH) and GluR1 (but not dopamine transporter or NR1) mRNA levels in the VTA were detected 24 h after intra-VTA nicotine administration. Systemic nicotine injection caused only an increase in TH mRNA levels while intra-Acb infusion did not modify any of the mRNAs tested. The long-term increase in basal DA levels in the Acb and TH, and GluR1 mRNA levels in the VTA upon intra-VTA nicotine microinjection indicates that even a single nicotine injection can induce plastic changes of the mesolimbic DA pathway.
    Type of Medium: Electronic Resource
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  • 2
    ISSN: 1471-4159
    Source: Blackwell Publishing Journal Backfiles 1879-2005
    Topics: Medicine
    Notes: Abstract: In a search for behavioral, neuroanatomical, and metabolic characteristics of Alzheimer's disease that may result from cholinergic malfunction, we used transgenic mice overexpressing acetylcholinesterase (AChE) mRNA and active enzyme in brain neurons. Mapping by in situ hybridization revealed that transgenic and host AChE mRNAs were distributed similarly. In a Morris water maze working memory paradigm, adult transgenic mice did not display the characteristic improvement found in control mice either between or within test days and spent less time than control mice in the platform zone. In 5-week-old transgenic mice, the basilar dendritic trees of layer 5 pyramidal neurons from the frontoparietal cortex were essentially as developed as in age-matched controls. However, branching totally ceased after this age, whereas in control adults it continued up to at least 7 months. Therefore, dendritic arbors became smaller in adult transgenic mice than those of controls. Furthermore, the average number of spines was significantly lower on dendritic branches of 7-month-old but not 5-week-old transgenics as compared with controls. Binding of tritiated hemicholinium-3, a blocker of the high-affinity choline uptake characteristic of active cholinergic terminals, was over twofold enhanced in the brain of transgenic mice. In contrast, no differences were observed in the mRNA and ligand binding levels of several different subtypes of nicotinic and muscarinic acetylcholine receptors. These findings suggest that three different hallmarks associated with Alzheimer's disease—namely, progressive cognitive failure, cessation of dendrite branching and spine formation, and enhanced high-affinity choline uptake—are outcomes of cholinergic malfunction.
    Type of Medium: Electronic Resource
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  • 3
    Abstract: BioModels serves as a central repository of mathematical models representing biological processes. It offers a platform to make mathematical models easily shareable across the systems modelling community, thereby supporting model reuse. To facilitate hosting a broader range of model formats derived from diverse modelling approaches and tools, a new infrastructure for BioModels has been developed that is available at http://www.ebi.ac.uk/biomodels. This new system allows submitting and sharing of a wide range of models with improved support for formats other than SBML. It also offers a version-control backed environment in which authors and curators can work collaboratively to curate models. This article summarises the features available in the current system and discusses the potential benefit they offer to the users over the previous system. In summary, the new portal broadens the scope of models accepted in BioModels and supports collaborative model curation which is crucial for model reproducibility and sharing.
    Type of Publication: Journal article published
    PubMed ID: 29106614
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  • 4
    Keywords: INFORMATION ; NEW-YORK ; GENOME ; MICROARRAY DATA ; SPECIFICATION ; PROJECT ; GUIDELINES ; ANNOTATION ; STANDARDS ; USA ; microbiology ; ENGLAND ; biotechnology ; SCIENTIFIC JOURNALS
    Type of Publication: Journal article published
    PubMed ID: 18688244
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  • 5
    Keywords: SIMULATIONS ; CELLS ; CELL ; Germany ; MODEL ; MODELS ; NETWORKS ; SYSTEM ; SYSTEMS ; TOOL ; DISEASE ; DISEASES ; GENE ; TIME ; COMPLEX ; COMPLEXES ; MECHANISM ; mechanisms ; SIMULATION ; BIOLOGY ; ASSOCIATION ; FIELD ; RECOGNITION ; PATTERNS ; DATABASE ; bioinformatics ; SELECTION ; systems biology ; PROJECT ; EUROPE ; PRODUCTS ; RESOURCE ; pattern recognition ; TECHNOLOGY ; RECOMMENDATIONS ; modelling ; mathematical models ; INVESTIGATE
    Abstract: The following report selects and summarises some of the conclusions and recommendations generated throughout a series of workshops and discussions that have lead to the publication of the Science Policy Briefing (SPB) Nr. 35, published by the European Science Foundation. (Large parts of the present text are directly based on the ESF SPB. Detailed recommendations with regard to specific application areas are not given here but can be found in the SPB. Issues related to mathematical modelling, including training and the need for an infrastructure supporting modelling are discussed in greater detail in the present text.) The numerous reports and publications about the advances within the rapidly growing field of systems biology have led to a plethora of alternative definitions for key concepts. Here, with 'mathematical modelling' the authors refer to the modelling and simulation of subcellular, cellular and macro-scale phenomena, using primarily methods from dynamical systems theory. The aim of such models is encoding and testing hypotheses about mechanisms underlying the functioning of cells. Typical examples are models for molecular networks, where the behaviour of cells is expressed in terms of quantitative changes in the levels of transcripts and gene products. Bioinformatics provides essential complementary tools, including procedures for pattern recognition, machine learning, statistical modelling (testing for differences, searching for associations and correlations) and secondary data extracted from databases. Dynamical systems theory is the natural language to investigate complex biological systems demonstrating nonlinear spatio-temporal behaviour. However, the generation of experimental data suitable to parameterise, calibrate and validate such models is often time consuming and expensive or not even possible with the technology available today. In our report, we use the term 'computational model' when mathematical models are complemented with information generated from bioinformatics resources. Hence, 'the model' is, in reality, an integrated collection of data and models from various (possibly heterogeneous) sources. The present report focuses on a selection of topics, which were identified as appropriate case studies for medical systems biology, and adopts a particular perspective which the authors consider important. We strongly believe that mathematical modelling represents a natural language with which to integrate data at various levels and, in doing so, to provide insight into complex diseases: Modelling necessitates the statement of explicit hypotheses, a process which often enhances comprehension of the biological system and can uncover critical points where understanding is lacking. Simulations can reveal hidden patterns and/or counter-intuitive mechanisms in complex systems. Theoretical thinking and mathematical modelling constitute powerful tools to integrate and make sense of the biological and clinical information being generated and, more importantly, to generate new hypotheses that can then be tested in the laboratory. Medical Systems Biology projects carried out recently across Europe have revealed a need for action: While the need for mathematical modelling and interdisciplinary collaborations is becoming widely recognised in the biological sciences, with substantial implications for the training and research funding mechanisms within this area, the medical sciences have yet to follow this lead. To achieve major breakthroughs in Medical Systems Biology, existing academic funding schemes for large-scale projects need to be reconsidered. The hesitant stance of the pharmaceutical industry towards major investment in systems biology research has to be addressed. Leading medical journals should be encouraged to promote mathematical modelling
    Type of Publication: Journal article published
    PubMed ID: 19449974
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  • 6
    Abstract: We created SynSysNet, available online at http://bioinformatics.charite.de/synsysnet, to provide a platform that creates a comprehensive 4D network of synaptic interactions. Neuronal synapses are fundamental structures linking nerve cells in the brain and they are responsible for neuronal communication and information processing. These processes are dynamically regulated by a network of proteins. New developments in interaction proteomics and yeast two-hybrid methods allow unbiased detection of interactors. The consolidation of data from different resources and methods is important to understand the relation to human behaviour and disease and to identify new therapeutic approaches. To this end, we established SynSysNet from a set of approximately 1000 synapse specific proteins, their structures and small-molecule interactions. For two-thirds of these, 3D structures are provided (from Protein Data Bank and homology modelling). Drug-target interactions for 750 approved drugs and 50 000 compounds, as well as 5000 experimentally validated protein-protein interactions, are included. The resulting interaction network and user-selected parts can be viewed interactively and exported in XGMML. Approximately 200 involved pathways can be explored regarding drug-target interactions. Homology-modelled structures are downloadable in Protein Data Bank format, and drugs are available as MOL-files. Protein-protein interactions and drug-target interactions can be viewed as networks; corresponding PubMed IDs or sources are given.
    Type of Publication: Journal article published
    PubMed ID: 23143269
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  • 7
    Publication Date: 2018-09-02
    Description: In patients with asthma or chronic obstructive pulmonary disease, rhinovirus (RV) infections can provoke acute worsening of disease, and limited treatment options exist. Viral replication in the host cell induces significant remodeling of intracellular membranes, but few studies have explored this mechanistically or as a therapeutic opportunity. We performed unbiased lipidomic analysis on human bronchial epithelial cells infected over a 6 h period with the RV-A1b strain of RV to determine changes in 493 distinct lipid species. Through pathway and network analysis, we identified temporal changes in the apparent activities of a number of lipid metabolizing and signaling enzymes. In particular, analysis highlighted FA synthesis and ceramide metabolism as potential anti-rhinoviral targets. To validate the importance of these enzymes in viral replication, we explored the effects of commercially available enzyme inhibitors upon RV-A1b infection and replication. Ceranib-1, D609, and C75 were the most potent inhibitors, which confirmed that FAS and ceramidase are potential inhibitory targets in rhinoviral infections. More broadly, this study demonstrates the potential of lipidomics and pathway analysis to identify novel targets to treat human disorders.
    Print ISSN: 0022-2275
    Electronic ISSN: 1539-7262
    Topics: Biology , Chemistry and Pharmacology , Medicine
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