84 research outputs found

    Analysis of the Binding of Cytokines to Highly Charged Polymer Networks

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    We present a model describing the binding of biological signaling proteins to highly charged polymer networks. The networks are formed by polyelectrolyte chains for which the distance between two charges at the chain is smaller than the Bjerrum length. Counterion condensation on such highly charged chains immobilizes a part of the counterions which do no more contribute to the osmotic pressure. The Donnan-equilibrium between the polymer network and the aqueous solution with salt concentration csb is used to calculate the salt concentration of the co- and counterions csg entering the network. Two factors lead to adsorption of proteins to charged polymer networks: i) The electrostatic interaction between the network and the protein is given by the Donnan-potential of the network and the net charge of the protein. In addition to this leading term, a second term describes the change of the Born-energy of the proteins when entering the network. ii) The interaction of the protein with the highly charged chains within the network is governed by counterion release: Patches of positive charge at the protein become multivalent counterions of the polyelectrolyte chains thus releasing a concomitant number of condensed counterions. The model is compared to experimental data obtained on a set of biohybrid polymer networks composed of crosslinked glycosaminoglycan chains that interact with a mixture of key signaling proteins. The analysis of the experimental binding constants reveals that the counterion release mechanism is decisive for protein adsorption to the network at physiological salt concentration

    Chemokine‐Capturing Wound Contact Layer Rescues Dermal Healing

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    Excessive inflammation often impedes the healing of chronic wounds. Scavenging of chemokines by multiarmed poly(ethylene glycol)-glycosaminoglycan (starPEG-GAG) hydrogels has recently been shown to support regeneration in a diabetic mouse chronic skin wound model. Herein, a textile-starPEG-GAG composite wound contact layer (WCL) capable of selectively sequestering pro-inflammatory chemokines is reported. Systematic variation of the local and integral charge densities of the starPEG-GAG hydrogel component allows for tailoring its affinity profile for biomolecular signals of the wound milieu. The composite WCL is subsequently tested in a large animal (porcine) model of human wound healing disorders. Dampening excessive inflammatory signals without affecting the levels of pro-regenerative growth factors, the starPEG-GAG hydrogel-based WCL treatment induced healing with increased granulation tissue formation, angiogenesis, and deposition of connective tissue (collagen fibers). Thus, this biomaterials technology expands the scope of a new anti-inflammatory therapy toward clinical use

    Modellierung und Simulation flexibler Körper in alaska-Softwareprodukten

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    Im Vortrag werden die Möglichkeiten der Modellierung und Verwendung flexibler Körper in Produkten der alaska-Softwarefamilie, die am Institut für Mechatronik e.V. entwickelt werden, vorgestellt. Die alaska-Softwarefamilie umfasst neben dem alaska/ModellerStudio, einer Mehrkörperdynamik-Simulationsumgebung für die allgemeine Verwendung, auch anwendungsspezifische Simulationswerkzeuge mit Fokussierung auf eng begrenzte Einsatzgebiete. Im Interesse realitätsnaher Simulationsergebnisse werden in der Mehrkörperdynamik neben starren Körpern und idealen Gelenken verstärkt elastisch verformbare Körper und nachgiebige Gelenke verwendet. Je nach Einsatzgebiet und Simulationsziel (hohe Genauigkeit, hohe Performance) kommen unterschiedliche Verfahren der Beschreibung flexibler Körper zum Einsatz. Diese werden im Vortrag diskutiert, präsentierte Anwendungsbeispiele illustrieren die Verwendung

    Heparin modified polyethylene glycol microparticle aggregates for focal cancer chemotherapy

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    Focal cancer therapy can improve clinical outcomes. Here, we evaluated injectable heparin-containing hydrogel material loaded with doxorubicin as a focal breast cancer therapy. We utilized a binary heparin/polyethylene glycol (PEG) hydrogel that was processed post synthesis into hydrogel microparticle aggregates to yield a readily injectable hydrogel. When loaded with doxorubicin, the injectable hydrogel microparticle aggregates had excellent short- and long-term anticancer activity against human breast cancer cells in vitro. Efficacy as a focal anticancer therapy was also evaluated in vivo by local injection of the doxorubicin-loaded PEG-heparin hydrogel microparticle aggregates into mice with established human orthotopic breast tumours. Animals showed significant antitumour responses by reduction in both primary tumour growth and metastasis when compared to animals which received the equivalent doxorubicin dose via an intravenous bolus injection. Overall, PEG-heparin hydrogel microparticle aggregates are emerging as a potential anticancer drug delivery system for focal therapy

    Deep Learning Methods for Partial Differential Equations and Related Parameter Identification Problems

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    Recent years have witnessed a growth in mathematics for deep learning--which seeks a deeper understanding of the concepts of deep learning with mathematics and explores how to make it more robust--and deep learning for mathematics, where deep learning algorithms are used to solve problems in mathematics. The latter has popularised the field of scientific machine learning where deep learning is applied to problems in scientific computing. Specifically, more and more neural network architectures have been developed to solve specific classes of partial differential equations (PDEs). Such methods exploit properties that are inherent to PDEs and thus solve the PDEs better than standard feed-forward neural networks, recurrent neural networks, or convolutional neural networks. This has had a great impact in the area of mathematical modeling where parametric PDEs are widely used to model most natural and physical processes arising in science and engineering. In this work, we review such methods as well as their extensions for parametric studies and for solving the related inverse problems. We equally proceed to show their relevance in some industrial applications

    Three dimensional in-vitro models for studying cancer angiogenesis

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    Introduction Hydrogels prepared from star-shaped poly(ethylene glycol) (PEG) and maleimide-functionalized heparin provide a potential matrix for use in developing three dimensional (3D) models. We have previously demonstrated that these hydrogels support the cultivation of human umbilical vein endothelial cells (HUVECs). We extend this body of work to study the ability to create an extracellular matrix (ECM)-like model to study breast and prostate cancer cell growth in 3D. Also, we investigate the ability to produce a tri-culture mimicking tumour angiogenesis with cancer spheroids, HUVECs and mesenchymal stem cells (MSCs). Materials and Methods The breast cancer cell lines, MCF-7 and MDA-MB-231, and prostate cancer cell lines, LNCaP and PC3, were seeded into starPEG-heparin hydrogels and grown for 14 Days to analyze the effects of varying hydrogel stiffness on spheroid development. Resulting hydrogel constructs were analyzed via proliferation assays, light microscopy, and immunostaining. Cancer cell lines were then seeded into starPEG-heparin hydrogels functionalized with growth factors as spheroids with HUVECs and MSCs and grown as a tri-culture. Cultures were analyzed via immunostaining and observed using confocal microscopy. Results Cultures prepared in MMP-cleavable starPEG-heparin hydrogels display spheroid formation in contrast to adherent growth on tissue culture plastic. Small differences were visualized in cancer spheroid growth between different gel stiffness across the range of cell lines. Cancer cell lines were able to be co-cultivated with HUVECs and MSC. Interaction was visualized between tumours and HUVECs via confocal microscopy. Further studies intend to further optimize and mimic the ECM environment of in-situ tumour angiogenesis. Discussion Our results confirm the suitability of hydrogels constructed from starPEG-heparin for HUVEC and MSC co-cultivation with cancer cell lines to study cell-cell and cell-matrix interactions in a 3D environment. This represents a step forward in the development of 3D culture models to study the pathomechanisms of breast and prostate cancer

    Cryogel-supported stem cell factory for customized sustained release of bispecific antibodies for cancer immunotherapy

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    Combining stem cells with biomaterial scaffolds provides a promising strategy for the development of drug delivery systems. Here we propose an innovative immunotherapeutic organoid by housing human mesenchymal stromal cells (MSCs), gene-modified for the secretion of an anti-CD33-anti-CD3 bispecific antibody (bsAb), in a small biocompatible star-shaped poly(ethylene glycol)-heparin cryogel scaffold as a transplantable and low invasive therapeutic machinery for the treatment of acute myeloid leukemia (AML). The macroporous biohybrid cryogel platform displays effectiveness in supporting proliferation and survival of bsAb-releasing-MSCs overtime in vitro and in vivo, avoiding cell loss and ensuring a constant release of sustained and detectable levels of bsAb capable of triggering T-cell-mediated anti-tumor responses and a rapid regression of CD33 + AML blasts. This therapeutic device results as a promising and safe alternative to the continuous administration of short-lived immunoagents and paves the way for effective bsAb-based therapeutic strategies for future tumor treatments
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