The Experts below are selected from a list of 298470 Experts worldwide ranked by ideXlab platform

Didier Lucor - One of the best experts on this subject based on the ideXlab platform.

  • Uncertainty quantification of inflow boundary condition and proximal arterial stiffness coupled effect on pulse wave propagation in a vascular Network
    2017
    Co-Authors: Auguste Brault, Didier Lucor, Lena Wiechert, Andrew Comerford, Wolfgang A. Wall, L. Dumas, Sophie Rausch
    Abstract:

    SUMMARY This work aims at quantifying the effect of inherent uncertainties from cardiac output on the sensitivity of a human compliant arterial Network Response based on stochastic simulations of a reduced-order pulse wave propagation model. A simple pulsatile output form is utilized to reproduce the most relevant cardiac features with a minimum number of parameters associated with left ventricle dynamics. Another source of critical uncertainty is the spatial heterogeneity of the aortic compliance which plays a key role in the propagation and damping of pulse waves generated at each cardiac cycle. A continuous representation of the aortic stiffness in the form of a generic random field of prescribed spatial correlation is then considered. Resorting to a stochastic sparse pseudospectral method, we investigate the spatial sensitivity of the pulse pressure and waves reflection magnitude with respect to the different model uncertainties. Results indicate that uncertainties related to the shape and magnitude of the prescribed inlet flow in the proximal aorta can lead to potent variation of both the mean value and standard deviation of blood flow velocity and pressure dynamics due to the interaction of different wave propagation and reflection features. These results have potential physiological and pathological implications. They will provide some guidance in clinical data acquisition and future coupling of arterial pulse wave propagation reduced-order model with more complex beating heart models.

  • uncertainty quantification of inflow boundary condition and proximal arterial stiffness coupled effect on pulse wave propagation in a vascular Network
    International Journal for Numerical Methods in Biomedical Engineering, 2017
    Co-Authors: Antoine Brault, L. Dumas, Didier Lucor
    Abstract:

    This work aims at quantifying the effect of inherent uncertainties from cardiac output on the sensitivity of a human compliant arterial Network Response based on stochastic simulations of a reduced-order pulse wave propagation model. A simple pulsatile output form is used to reproduce the most relevant cardiac features with a minimum number of parameters associated with left ventricle dynamics. Another source of significant uncertainty is the spatial heterogeneity of the aortic compliance, which plays a key role in the propagation and damping of pulse waves generated at each cardiac cycle. A continuous representation of the aortic stiffness in the form of a generic random field of prescribed spatial correlation is then considered. Making use of a stochastic sparse pseudospectral method, we investigate the sensitivity of the pulse pressure and waves reflection magnitude over the arterial tree with respect to the different model uncertainties. Results indicate that uncertainties related to the shape and magnitude of the prescribed inlet flow in the proximal aorta can lead to potent variation of both the mean value and standard deviation of blood flow velocity and pressure dynamics due to the interaction of different wave propagation and reflection features. Lack of accurate knowledge in the stiffness properties of the aorta, resulting in uncertainty in the pulse wave velocity in that region, strongly modifies the statistical Response, with a global increase in the variability of the quantities of interest and a spatial redistribution of the regions of higher sensitivity. These results will provide some guidance in clinical data acquisition and future coupling of arterial pulse wave propagation reduced-order model with more complex beating heart models.

Vassily Hatzimanikatis - One of the best experts on this subject based on the ideXlab platform.

  • constraint based metabolic control analysis for rational strain engineering
    Metabolic Engineering, 2021
    Co-Authors: Sofia Tsouka, Meric Ataman, Tuure Hameri, Ljubisa Miskovic, Vassily Hatzimanikatis
    Abstract:

    The advancements in genome editing techniques over the past years have rekindled interest in rational metabolic engineering strategies. While Metabolic Control Analysis (MCA) is a well-established method for quantifying the effects of metabolic engineering interventions on flows in metabolic Networks and metabolite concentrations, it does not consider the physiological limitations of the cellular environment and metabolic engineering design constraints. We report here a constraint-based framework, Network Response Analysis (NRA), for rational genetic strain design. NRA is cast as a Mixed-Integer Linear Programming problem that integrates MCA, Thermodynamically-based Flux Analysis (TFA), biologically relevant constraints, as well as genome editing restrictions into a comprehensive platform for identifying metabolic engineering targets. We show that the NRA formulation and its core constraints are equivalent to the ones of Flux Balance Analysis (FBA) and TFA, which allows it to be used for a wide range of optimization criteria and with various physiological constraints. We also show how the parametrization and introduction of biological constraints enhance the NRA formulation compared to the classical MCA approach, and we demonstrate its features and its ability to generate multiple alternative optimal strategies given several user-defined boundaries and objectives. In summary, NRA is a sophisticated alternative to classical MCA for rational metabolic engineering that accommodates the incorporation of physiological data at metabolic flux, metabolite concentration, and enzyme expression levels.

  • constraint based metabolic control analysis for rational strain engineering
    bioRxiv, 2020
    Co-Authors: Sofia Tsouka, Meric Ataman, Tuure Hameri, Ljubisa Miskovic, Vassily Hatzimanikatis
    Abstract:

    The advancements in genome editing techniques over the past years have rekindled interest in rational metabolic engineering strategies. While Metabolic Control Analysis (MCA) is a well-established method for quantifying the effects of metabolic engineering interventions on flows in metabolic Networks and metabolic concentrations, it fails to account for the physiological limitations of the cellular environment and metabolic engineering design constraints. We report here a constraint-based framework based on MCA, Network Response Analysis (NRA), for the rational genetic strain design that incorporates biologically relevant constraints, as well as genome editing restrictions. The NRA core constraints being similar to the ones of Flux Balance Analysis, allow it to be used for a wide range of optimization criteria and with various physiological constraints. We show how the parametrization and introduction of biological constraints enhance the NRA formulation compared to the classical MCA approach, and we demonstrate its features and its ability to generate multiple alternative optimal strategies given several user-defined boundaries and objectives. In summary, NRA is a sophisticated alternative to classical MCA for rational metabolic engineering that accommodates the incorporation of physiological data at metabolic flux, metabolite concentration, and enzyme expression levels.

J E Frodin - One of the best experts on this subject based on the ideXlab platform.

  • humoral anti idiotypic and anti anti idiotypic immune Response in cancer patients treated with monoclonal antibody 17 1a
    Cancer Immunology Immunotherapy, 1996
    Co-Authors: Jan Fagerberg, Peter Ragnhammar, Maria Liljefors, A L Hjelm, Hakan Mellstedt, J E Frodin
    Abstract:

    A group of 96 patients with advanced colorectal carcinoma were treated with the mouse (m) or chimeric (c) (mouse variable regions × human IgG1 constant regions) monoclonal antibody (mAb) 17-1A recognizing the tumour-associated antigen GA733-2. Eighty-two of the 83 patients treated with mmAb17-1A and 69% of the patients given cmAb17-1A (n = 13) developed anti-idiotypic antibodies (ab2). Auto-antibodies binding to tumour cells expressing GA733-2 were found in 7% of the patients. In a further 38 patients (40%) antitumour-cell antibodies, i.e. anti-anti-idiotypic antibodies (ab3), were induced by the mAb17-1A therapy. Patients with detectable ab3 after treatment had significantly higher ab2 levels than those not developing ab3. Addition of granulocyte/macrophage-colony-stimulating factor (GM-CSF) to mmAb17-1A significantly enhanced the induction of ab2 as well as induction of anti-anti-idiotypic antibodies (ab3), compared to mmAb17-1A alone. Patients with a high increase in antitumour-cell antibodies (ab3) induced by the therapy lived significantly longer than patients with no or a low level of induction of ab3 (P = 0.016). The results indicate that induction of an idiotypic Network Response might be an important effector mechanism in mAb therapy.

  • tumor regression in monoclonal antibody treated patients correlates with the presence of anti idiotype reactive t lymphocytes
    Cancer Research, 1995
    Co-Authors: Jan Fagerberg, Peter Ragnhammar, J E Frodin, Annalena Hjelm, Hans Wigzell, Hakan Mellstedt
    Abstract:

    Treatment of cancer patients with unconjugated mAbs directed against tumor-associated antigens is considered passive immunotherapy due to the main suggested effector mechanisms: antibody-dependent cellular cytotoxicity, complement-dependent cytolysis, and apoptosis. The therapeutic antibody (ab1) may, however, also give rise to an idiotypic Network Response, i.e. , an immunizing effect. Induced anti-idiotypic antibodies (ab2) mimicking the epitope that ab1 recognizes might subsequently induce an anti-anti-idiotypic humoral (ab3) and T-cell (T3) Response recognizing the nominal tumor-associated antigen. Twenty-four patients with metastatic colorectal carcinoma were treated with MAb17-1A against the tumor associated antigen GA733-2 and were analyzed for the induction of T3 cells. Five of the patients responded to mAb therapy with tumor regression. These five patients all had T cells specifically recognizing human ab2 (DNA synthesis) after treatment, while all nonresponding patients lacked such T cells. Four of the five patients with ab2-reactive T cells also showed induction of T cells recognizing GA733-2. The association between T3 cells and tumor regression was highly significant ( P = 0.0005). Thus, induction of T3 cells might be an important secondary antitumor effector function of therapy with unconjugated mAbs. Antibody therapy may therefore also be considered active specific immunotherapy.

Jan Fagerberg - One of the best experts on this subject based on the ideXlab platform.

  • humoral anti idiotypic and anti anti idiotypic immune Response in cancer patients treated with monoclonal antibody 17 1a
    Cancer Immunology Immunotherapy, 1996
    Co-Authors: Jan Fagerberg, Peter Ragnhammar, Maria Liljefors, A L Hjelm, Hakan Mellstedt, J E Frodin
    Abstract:

    A group of 96 patients with advanced colorectal carcinoma were treated with the mouse (m) or chimeric (c) (mouse variable regions × human IgG1 constant regions) monoclonal antibody (mAb) 17-1A recognizing the tumour-associated antigen GA733-2. Eighty-two of the 83 patients treated with mmAb17-1A and 69% of the patients given cmAb17-1A (n = 13) developed anti-idiotypic antibodies (ab2). Auto-antibodies binding to tumour cells expressing GA733-2 were found in 7% of the patients. In a further 38 patients (40%) antitumour-cell antibodies, i.e. anti-anti-idiotypic antibodies (ab3), were induced by the mAb17-1A therapy. Patients with detectable ab3 after treatment had significantly higher ab2 levels than those not developing ab3. Addition of granulocyte/macrophage-colony-stimulating factor (GM-CSF) to mmAb17-1A significantly enhanced the induction of ab2 as well as induction of anti-anti-idiotypic antibodies (ab3), compared to mmAb17-1A alone. Patients with a high increase in antitumour-cell antibodies (ab3) induced by the therapy lived significantly longer than patients with no or a low level of induction of ab3 (P = 0.016). The results indicate that induction of an idiotypic Network Response might be an important effector mechanism in mAb therapy.

  • tumor regression in monoclonal antibody treated patients correlates with the presence of anti idiotype reactive t lymphocytes
    Cancer Research, 1995
    Co-Authors: Jan Fagerberg, Peter Ragnhammar, J E Frodin, Annalena Hjelm, Hans Wigzell, Hakan Mellstedt
    Abstract:

    Treatment of cancer patients with unconjugated mAbs directed against tumor-associated antigens is considered passive immunotherapy due to the main suggested effector mechanisms: antibody-dependent cellular cytotoxicity, complement-dependent cytolysis, and apoptosis. The therapeutic antibody (ab1) may, however, also give rise to an idiotypic Network Response, i.e. , an immunizing effect. Induced anti-idiotypic antibodies (ab2) mimicking the epitope that ab1 recognizes might subsequently induce an anti-anti-idiotypic humoral (ab3) and T-cell (T3) Response recognizing the nominal tumor-associated antigen. Twenty-four patients with metastatic colorectal carcinoma were treated with MAb17-1A against the tumor associated antigen GA733-2 and were analyzed for the induction of T3 cells. Five of the patients responded to mAb therapy with tumor regression. These five patients all had T cells specifically recognizing human ab2 (DNA synthesis) after treatment, while all nonresponding patients lacked such T cells. Four of the five patients with ab2-reactive T cells also showed induction of T cells recognizing GA733-2. The association between T3 cells and tumor regression was highly significant ( P = 0.0005). Thus, induction of T3 cells might be an important secondary antitumor effector function of therapy with unconjugated mAbs. Antibody therapy may therefore also be considered active specific immunotherapy.

Deivy Wilson - One of the best experts on this subject based on the ideXlab platform.

  • simultaneous titration of ternary mixtures of pb ii cd ii and cu ii with potentiometric electronic tongue detection
    Electroanalysis, 2015
    Co-Authors: Deivy Wilson, Salvador Alegret, Manel Del Valle
    Abstract:

    An automatic titration method is reported to resolve ternary mixtures of transition metals (Pb2+, Cd2+ and Cu2+) employing electronic tongue detection and a reduced number of pre-defined additions of EDTA titrant. Sensors used were PVC membrane selective electrodes with generic Response to heavy-metals, plus an artificial neural Network Response model. Detection limits obtained were ca. 1 mg L−1 for the three target ions and reproducibilities 3.0 % for Pb2+, 4.1 % for Cd2+ and 5.2 % for Cu2+. The system was applied to contaminated soil samples and high accuracy was obtained for the determination of Pb2+. In the determination Cd2+ and Cu2+, sample matrix showed a significant effect.

  • potentiometric electronic tongue flow injection analysis system for the monitoring of heavy metal biosorption processes
    Talanta, 2012
    Co-Authors: Deivy Wilson, Salvador Alegret, M Del Valle, C Valderrama, A Florido
    Abstract:

    An automated flow injection potentiometric (FIP) system with electronic tongue detection (ET) is used for the monitoring of biosorption processes of heavy metals on vegetable wastes. Grape stalk wastes are used as biosorbent to remove Cu2+ ions in a fixed-bed column configuration. The ET is formed by a 5-sensor array with Cu2+ and Ca2+-selective electrodes and electrodes with generic Response to heavy-metals, plus an artificial neural Network Response model of the sensor's cross-Response. The real-time monitoring of both the Cu2+ and the cation exchanged and released (Ca2+) in the effluent solution is performed by using flow-injection potentiometric electronic tongue system. The coupling of the electronic tongue with automation features of the flow-injection system allows us to accurately characterize the Cu2+ ion-biosorption process, through obtaining its breakthrough curves, and the profile of the Ca2+ ion release. In parallel, fractions of the extract solution are analysed by spectroscopic techniques in order to validate the results obtained with the reported methodology. The sorption performance of grape stalks is also evaluated by means of well-established sorption models.