Telekommunikationsverhalten im europäischen Forschungsnetzwerk EARN: Ein Prototyp eines dynamischen Modells

Series: Discussion Papers of the Institute for Economic Geography and GIScienc

Isolation and characterisation of neural crest-derived stem cells from adult ovine palatal tissue

Adult mammalian craniofacial tissues contain limited numbers of post-migratory neural crest-derived stem cells. Similar to their embryonic counterparts, these adult multipotent stem cells can undergo multi-lineage differentiation and are capable of contributing to regeneration of mesodermal and ectodermal cells and tissues in vivo. In the present study, we describe for the first time the presence of Nestin-positive neural crest-derived stem cells (NCSCs) within the ovine hard palate. We show that these cells can be isolated from the palatal tissue and are able to form neurospheres. Ovine NCSCs express the typical neural crest markers Slug and Twist, exhibit high proliferative and migratory activity and are able to differentiate into α smooth muscle cells and β-III-tubulin expressing ectodermal cells. Finally, we demonstrate that oNCSCs are capable of differentiating into osteogenic, adipogenic and chondrogenic cells. Taken together, our results suggest that oNCSCs could be used as model cells to assess the efficacy and safety of autologous NCSC transplantation in a large animal model

Pancreatic graft outcome after combined whole pancreas and liver retrieval

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Structural and biophysical characterization of the secreted, β-helical adhesin EtpA of Enterotoxigenic Escherichia coli

DATA AVAILABILITY STATEMENT : All relevant data are within the paper and its Supporting Information files.SUPPORTING INFORMATION : TABLE S1. Plasmids and primers used. FIGURE S1. Schematic representation of full-length EtpA protein. The signal peptide (SP) for localization and processing and the TPS domain for recognition by the transport partner are indicated. The four consecutive repeats (R1, R2, R3 and R4) and the C-terminal tail are also indicated. The numbers represent the start and end of each fragment. The two N-terminal fragments; EtpA1-606 and EtpA67-447 are shown. FIGURE S2. Purification of EtpA67-447. (A) Single-peak ion exchange chromatography profile, (B) Single-peak size exclusion chromatography profile of EtpA67-447 and a single band on SDS-PAGE (insert) matching the 38 kDa size of monomeric EtpA67-447.FIGURE S3. Urea dependent un- and refolding of EtpA1-606. (A-C) CD spectra for untreated (0M urea, black squares), urea treated (1.5 to 4.5Murea, red spheres) and renatured samples (blue triangle). RAW IMAGES S1.Enterotoxigenic Escherichia coli (ETEC) is a diarrhoeal pathogen associated with high morbidity and mortality especially among young children in developing countries. At present, there is no vaccine for ETEC. One candidate vaccine antigen, EtpA, is a conserved secreted adhesin that binds to the tips of flagellae to bridge ETEC to host intestinal glycans. EtpA is exported through a Gram-negative, two-partner secretion system (TPSS, type Vb) comprised of the secreted EtpA passenger (TpsA) protein and EtpB (TpsB) transporter that is integrated into the outer bacterial membrane. TpsA proteins share a conserved, N-terminal TPS domain followed by an extensive C-terminal domain with divergent sequence repeats. Two soluble, N-terminal constructs of EtpA were prepared and analysed respectively including residues 67 to 447 (EtpA67-447) and 1 to 606 (EtpA1-606). The crystal structure of EtpA67- 447 solved at 1.76 Å resolution revealed a right-handed parallel β-helix with two extra-helical hairpins and an N-terminal β-strand cap. Analyses by circular dichroism spectroscopy confirmed the β-helical fold and indicated high resistance to chemical and thermal denaturation as well as rapid refolding. A theoretical AlphaFold model of full-length EtpA largely concurs with the crystal structure adding an extended β-helical C-terminal domain after an interdomain kink. We propose that robust folding of the TPS domain upon secretion provides a template to extend the N-terminal β-helix into the C-terminal domains of TpsA proteins.The National Institute of Allergy and Infectious Diseases and the US Department of Veterans Affairs.https://journals.plos.org/plosone/am2024Biochemistry, Genetics and Microbiology (BGM)SDG-03:Good heatlh and well-bein

Elemental, Morphological, and Corrosion Characterization of Different Surface States of Co-Cr Alloy for Prosthodontic Applications

In this study, four different groups were prepared in a cast model of an arch that received four implants made with a Co-Cr dental alloy. The surface of each group was prepared by four different surface treatments, including sandblasting with Al2O3 grains (SB), conventional finishing with dental burs (CF), milling with a CAD/CAM device (MIL), and electrodischarge machining (EDM). The characterization of the roughness parameters, morphology, elemental composition, and electrochemical properties of a dental Co-Cr alloy in different surface states exposed to an oral environment were reported. The electrochemical properties were tested with open-circuit potential (OCP) and anodic scan in Ringer’s solutions. The results of roughness parameters, elemental composition, OCP, corrosion potential and pitting potential were statistically analyzed by one-way ANOVA and the Tukey-Kramer multiple- comparison test at 95% confidence level. The roughness parameters classified the surfaces from smoothest to roughest according to the following order; CF, MIL, EDM, and SB. The CF group has the best corrosion resistance followed by the EDM, MIL, and SB groups

Modeling Disease Progression In Retinal OCTs With Longitudinal Self-Supervised Learning

Longitudinal imaging is capable of capturing the static ana\-to\-mi\-cal structures and the dynamic changes of the morphology resulting from aging or disease progression. Self-supervised learning allows to learn new representation from available large unlabelled data without any expert knowledge. We propose a deep learning self-supervised approach to model disease progression from longitudinal retinal optical coherence tomography (OCT). Our self-supervised model takes benefit from a generic time-related task, by learning to estimate the time interval between pairs of scans acquired from the same patient. This task is (i) easy to implement, (ii) allows to use irregularly sampled data, (iii) is tolerant to poor registration, and (iv) does not rely on additional annotations. This novel method learns a representation that focuses on progression specific information only, which can be transferred to other types of longitudinal problems. We transfer the learnt representation to a clinically highly relevant task of predicting the onset of an advanced stage of age-related macular degeneration within a given time interval based on a single OCT scan. The boost in prediction accuracy, in comparison to a network learned from scratch or transferred from traditional tasks, demonstrates that our pretrained self-supervised representation learns a clinically meaningful information.Comment: Accepted for publication in the MICCAI 2019 PRIME worksho