55 research outputs found

    Leukaemia stem cells: hit or miss?

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    Population Based Model of Human Embryonic Stem Cell (hESC) Differentiation during Endoderm Induction

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    The mechanisms by which human embryonic stem cells (hESC) differentiate to endodermal lineage have not been extensively studied. Mathematical models can aid in the identification of mechanistic information. In this work we use a population-based modeling approach to understand the mechanism of endoderm induction in hESC, performed experimentally with exposure to Activin A and Activin A supplemented with growth factors (basic fibroblast growth factor (FGF2) and bone morphogenetic protein 4 (BMP4)). The differentiating cell population is analyzed daily for cellular growth, cell death, and expression of the endoderm proteins Sox17 and CXCR4. The stochastic model starts with a population of undifferentiated cells, wherefrom it evolves in time by assigning each cell a propensity to proliferate, die and differentiate using certain user defined rules. Twelve alternate mechanisms which might describe the observed dynamics were simulated, and an ensemble parameter estimation was performed on each mechanism. A comparison of the quality of agreement of experimental data with simulations for several competing mechanisms led to the identification of one which adequately describes the observed dynamics under both induction conditions. The results indicate that hESC commitment to endoderm occurs through an intermediate mesendoderm germ layer which further differentiates into mesoderm and endoderm, and that during induction proliferation of the endoderm germ layer is promoted. Furthermore, our model suggests that CXCR4 is expressed in mesendoderm and endoderm, but is not expressed in mesoderm. Comparison between the two induction conditions indicates that supplementing FGF2 and BMP4 to Activin A enhances the kinetics of differentiation than Activin A alone. This mechanistic information can aid in the derivation of functional, mature cells from their progenitors. While applied to initial endoderm commitment of hESC, the model is general enough to be applicable either to a system of adult stem cells or later stages of ESC differentiation

    PET and MRI for the evaluation of regional myocardial perfusion and wall thickening after myocardial infarction

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    Deterioration of left ventricular (LV) function after myocardial infarction (MI) is a major cause of heart failure. Myocardial perfusion performance may play an important role in deterioration or improvement in LV function after MI. The aim of this study was to evaluate the myocardial perfusion reserve (MPR) and stress perfusion in deteriorating and non-deteriorating LV segments in patients after MI by PET and MRI, respectively. Regional wall thickening of 352 segments in 22 patients was assessed at 4 and 24 months after MI by cardiac MRI. PET was performed to evaluate MPR and adenosine stress N-13-ammonia perfusion 24 months after MI. Segments were divided into four groups according to deterioration or improvement in wall thickening. Normal functional segments at 4 months after MI that remained stable had a significantly higher mean MPR and mean stress perfusion PET value than deteriorated segments (p < 0.001). Furthermore, dysfunctional segments that improved had a significantly higher mean stress perfusion PET value than dysfunctional segments that remained dysfunctional (p < 0.001). This study demonstrated the additional value of myocardial perfusion assessment in relation to the functional integrity of the injured myocardium. Segmental functional LV improvement after MI was associated with better regional myocardial perfusion characteristics. Furthermore, the amount of wall thickening reduction was associated with regional myocardial perfusion abnormalities in patients after MI

    Cell Lineages and the Logic of Proliferative Control

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    It is widely accepted that the growth and regeneration of tissues and organs is tightly controlled. Although experimental studies are beginning to reveal molecular mechanisms underlying such control, there is still very little known about the control strategies themselves. Here, we consider how secreted negative feedback factors (“chalones”) may be used to control the output of multistage cell lineages, as exemplified by the actions of GDF11 and activin in a self-renewing neural tissue, the mammalian olfactory epithelium (OE). We begin by specifying performance objectives—what, precisely, is being controlled, and to what degree—and go on to calculate how well different types of feedback configurations, feedback sensitivities, and tissue architectures achieve control. Ultimately, we show that many features of the OE—the number of feedback loops, the cellular processes targeted by feedback, even the location of progenitor cells within the tissue—fit with expectations for the best possible control. In so doing, we also show that certain distinctions that are commonly drawn among cells and molecules—such as whether a cell is a stem cell or transit-amplifying cell, or whether a molecule is a growth inhibitor or stimulator—may be the consequences of control, and not a reflection of intrinsic differences in cellular or molecular character

    Noise-Driven Stem Cell and Progenitor Population Dynamics

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    BACKGROUND: The balance between maintenance of the stem cell state and terminal differentiation is influenced by the cellular environment. The switching between these states has long been understood as a transition between attractor states of a molecular network. Herein, stochastic fluctuations are either suppressed or can trigger the transition, but they do not actually determine the attractor states. METHODOLOGY/PRINCIPAL FINDINGS: We present a novel mathematical concept in which stem cell and progenitor population dynamics are described as a probabilistic process that arises from cell proliferation and small fluctuations in the state of differentiation. These state fluctuations reflect random transitions between different activation patterns of the underlying regulatory network. Importantly, the associated noise amplitudes are state-dependent and set by the environment. Their variability determines the attractor states, and thus actually governs population dynamics. This model quantitatively reproduces the observed dynamics of differentiation and dedifferentiation in promyelocytic precursor cells. CONCLUSIONS/SIGNIFICANCE: Consequently, state-specific noise modulation by external signals can be instrumental in controlling stem cell and progenitor population dynamics. We propose follow-up experiments for quantifying the imprinting influence of the environment on cellular noise regulation.Engineering and Applied SciencesOther Research Uni

    Novel probes for pH and dissolved oxygen measurements in cultivations from millilitre to benchtop scale

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    Erworben im Rahmen der Schweizer Nationallizenzen (http://www.nationallizenzen.ch)pH value and the concentration of dissolved oxygen (DO) are key parameters to monitor and control cell growth in cultivation studies. Reliable, robust and accurate methods to measure these parameters in cultivation systems in real time guarantee high product yield and quality. This mini-review summarises the current state of the art of pH and DO sensors that are applied to bioprocesses from millilitre to benchtop scale by means of a short introduction on measuring principles and selected applications. Special emphasis is placed on single-use bioreactors, which have been increasingly employed in bioprocess development and production in recent years. Working principles, applications and the particular requirements of sensors in these cultivation systems are given. In such processes, optical sensors for pH and DO are often preferred to electrochemical probes, as they allow semi-invasive measurements and can be miniaturised to micrometre scale or lower. In addition, selected measuring principles of novel sensing technologies for pH and DO are discussed. These include solid-state sensors and miniaturised devices that are not yet commercially available, but show promising characteristics for possible use in bioprocesses in the near future
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