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The Global ETD Search service is a free service for researchers
to find electronic theses and dissertations. This service is
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Networked Digital Library of Theses and Dissertations.
Our metadata is collected from universities around the world. If you manage a university/consortium/country archive and want to be added, details can be found on the NDLTD website.
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Showing 11 to 17 of 17 (0.085 seconds)| 11 |
Les cytokines inflammatoires modulent la prolifération et la différenciation in vitro des cellules souches/progénitrices de la moelle épinièreVaugeois, Alexandre 04 1900 (has links)
No description available.
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CellTrans: An R Package to Quantify Stochastic Cell State TransitionsBuder, Thomas, Deutsch, Andreas, Seifert, Michael, Voss-Böhme, Anja 15 November 2017 (has links) (PDF)
Many normal and cancerous cell lines exhibit a stable composition of cells in distinct states which can, e.g., be defined on the basis of cell surface markers. There is evidence that such an equilibrium is associated with stochastic transitions between distinct states. Quantifying these transitions has the potential to better understand cell lineage compositions. We introduce CellTrans, an R package to quantify stochastic cell state transitions from cell state proportion data from fluorescence-activated cell sorting and flow cytometry experiments. The R package is based on a mathematical model in which cell state alterations occur due to stochastic transitions between distinct cell states whose rates only depend on the current state of a cell. CellTrans is an automated tool for estimating the underlying transition probabilities from appropriately prepared data. We point out potential analytical challenges in the quantification of these cell transitions and explain how CellTrans handles them. The applicability of CellTrans is demonstrated on publicly available data on the evolution of cell state compositions in cancer cell lines. We show that CellTrans can be used to (1) infer the transition probabilities between different cell states, (2) predict cell line compositions at a certain time, (3) predict equilibrium cell state compositions, and (4) estimate the time needed to reach this equilibrium. We provide an implementation of CellTrans in R, freely available via GitHub (https://github.com/tbuder/CellTrans).
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Regenerationspotenzial CD133+-hämatopoetischer Progenitorzellen der humanen Nabelschnur beim Nierendefekt im Mausmodell / Regenerative potential of human umbilical cord blood derived CD133 positive hematopoietic progenitor cells after kidney injury in a mouse modelHoffschulte, Birgit 19 August 2009 (has links)
No description available.
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CellTrans: An R Package to Quantify Stochastic Cell State TransitionsBuder, Thomas, Deutsch, Andreas, Seifert, Michael, Voss-Böhme, Anja 15 November 2017 (has links)
Many normal and cancerous cell lines exhibit a stable composition of cells in distinct states which can, e.g., be defined on the basis of cell surface markers. There is evidence that such an equilibrium is associated with stochastic transitions between distinct states. Quantifying these transitions has the potential to better understand cell lineage compositions. We introduce CellTrans, an R package to quantify stochastic cell state transitions from cell state proportion data from fluorescence-activated cell sorting and flow cytometry experiments. The R package is based on a mathematical model in which cell state alterations occur due to stochastic transitions between distinct cell states whose rates only depend on the current state of a cell. CellTrans is an automated tool for estimating the underlying transition probabilities from appropriately prepared data. We point out potential analytical challenges in the quantification of these cell transitions and explain how CellTrans handles them. The applicability of CellTrans is demonstrated on publicly available data on the evolution of cell state compositions in cancer cell lines. We show that CellTrans can be used to (1) infer the transition probabilities between different cell states, (2) predict cell line compositions at a certain time, (3) predict equilibrium cell state compositions, and (4) estimate the time needed to reach this equilibrium. We provide an implementation of CellTrans in R, freely available via GitHub (https://github.com/tbuder/CellTrans).
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Morfologická a funkční charakterizace střevního epitelu z hlediska exprese proteinu LGR4 / Morphological and functional characterization of intestinal epithelium in the context of LGR4 expressionBurešová, Petra January 2017 (has links)
No description available.
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Veranschaulichung subzellulärer physikalischer Kräfte biochemischen und mechanischen Ursprungs mittels FRET / Insights into the spatiotemporal regulation of the cellular cytoskeleton through applications of FRETMitkovski, Miso 03 November 2005 (has links)
No description available.
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SCF cdc4 regulates msn2 and msn4 dependent gene expression to counteract hog1 induced lethalityVendrell Arasa, Alexandre 16 January 2009 (has links)
L'activació sostinguda de Hog1 porta a una inhibició del creixement cel·lular. En aquest treball, hem observat que el fenotip de letalitat causat per l'activació sostinguda de Hog1 és parcialment inhibida per la mutació del complexe SCFCDC4. La inhibició de la mort causada per l'activació sostinguda de Hog1 depèn de la via d'extensió de la vida. Quan Hog1 s'activa de manera sostinguda, la mutació al complexe SCFCDC4 fa que augmenti l'expressió gènica depenent de Msn2 i Msn4 que condueix a una sobreexpressió del gen PNC1 i a una hiperactivació de la deacetilassa Sir2. La hiperactivació de Sir2 és capaç d'inhibir la mort causada per l'activació sostinguda de Hog1. També hem observat que la mort cel·lular causada per l'activació sostinguda de Hog1 és deguda a una inducció d'apoptosi. L'apoptosi induïda per Hog1 és inhibida per la mutació al complexe SCFCDC4. Per tant, la via d'extensió de la vida és capaç de prevenir l'apoptosi a través d'un mecanisme desconegut. / Sustained Hog1 activation leads to an inhibition of cell growth. In this work, we have observed that the lethal phenotype caused by sustained Hog1 activation is prevented by SCFCDC4 mutants. The prevention of Hog1-induced cell death by SCFCDC4 mutation depends on the lifespan extension pathway. Upon sustained Hog1 activation, SCFCDC4 mutation increases Msn2 and Msn4 dependent gene expression that leads to a PNC1 overexpression and a Sir2 deacetylase hyperactivation. Then, hyperactivation of Sir2 is able to prevent cell death caused by sustained Hog1 activation. We have also observed that cell death upon sustained Hog1 activation is due to an induction of apoptosis. The apoptosis induced by Hog1 is decreased by SCFCDC4 mutation. Therefore, lifespan extension pathway is able to prevent apoptosis by an unknown mechanism.
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