GFP–Margatoxin,a Genetically Encoded Fluorescent Ligand to Probe Affinity of Kv1.3 Channel Blockers

Peptide pore blockers and their fluorescent derivatives are useful molecular probes to study the structure and functions of the voltage-gated potassium Kv1.3 channel, which is considered as a pharmacological target in the treatment of autoimmune and neurological disorders. We present Kv1.3 fluorescent ligand, GFP–MgTx, constructed on the basis of green fluorescent protein (GFP) and margatoxin (MgTx), the peptide, which is widely used in physiological studies of Kv1.3. Expression of the fluorescent ligand in E. coli cells resulted in correctly folded and functionally active GFP–MgTx with a yield of 30 mg per 1 L of culture. Complex of GFP–MgTx with the Kv1.3 binding site is reported to have the dissociation constant of 11 ± 2 nM. GFP–MgTx as a component of an analytical system based on the hybrid KcsA–Kv1.3 channel is shown to be applicable to recognize Kv1.3 pore blockers of peptide origin and to evaluate their affinities to Kv1.3. GFP–MgTx can be used in screening and pre-selection of Kv1.3 channel blockers as potential drug candidates.     

Therapeutic Effects of Hypoxic and Pro-Inflammatory Priming of Mesenchymal Stem Cell-Derived Extracellular Vesicles in Inflammatory Arthritis

Mesenchymal stem cells (MSCs) immunomodulate inflammatory responses through paracrine signalling, including via secretion of extracellular vesicles (EVs) in the cell secretome. We evaluated the therapeutic potential of MSCs-derived small EVs in an antigen-induced model of arthritis (AIA). EVs isolated from MSCs cultured normoxically (21% O₂, 5% CO₂), hypoxically (2% O₂, 5% CO₂) or with a pro-inflammatory cytokine cocktail were applied into the AIA model. Disease pathology was assessed post-arthritis induction through swelling and histopathological analysis of synovial joint structure. Activated CD4+ T cells from healthy mice were cultured with EVs or MSCs to assess deactivation capabilities prior to application of standard EVs in vivo to assess T cell polarisation within the immune response to AIA. All EVs treatments reduced knee-joint swelling whilst only normoxic and pro-inflammatory primed EVs improved histopathological outcomes. In vitro culture with EVs did not achieve T cell deactivation. Polarisation towards CD4+ helper cells expressing IL17a (Th17) was reduced when normoxic and hypoxic EV treatments were applied in vitro. Normoxic EVs applied into the AIA model reduced Th17 polarisation and improved Regulatory T cell (Treg):Th17 homeostatic balance. Normoxic EVs present the optimal strategy for broad therapeutic benefit. EVs present an effective novel technology with the potential for cell-free therapeutic translation.     

Fibrosis Protein-Protein Interactions from Google Matrix Analysis of MetaCore Network

Protein–protein interactions is a longstanding challenge in cardiac remodeling processes and heart failure. Here, we use the MetaCore network and the Google matrix algorithms for prediction of protein–protein interactions dictating cardiac fibrosis, a primary cause of end-stage heart failure. The developed algorithms allow identification of interactions between key proteins and predict new actors orchestrating fibroblast activation linked to fibrosis in mouse and human tissues. These data hold great promise for uncovering new therapeutic targets to limit myocardial fibrosis.     

Synthesis of the glycidyl aniline adduct and its crosslinking

Synthesis of the adduct of aniline and glycidyl methacrylate and its polymerization and copolymerization with two diisocyanates are presented. Hexyl diisocyanate representing aliphatic compounds and toluene diisocyanate as the aromatic compound were used. UV and thermal initiations were applied. The curing process was controlled by FTIR analysis. Thermomechanical properties of the compositions cured at different temperatures were compared. © 2004 Wiley Periodicals, Inc. J Appl Polym Sci 95: 524–528, 2005     

Inductive program synthesis for therapy plan generation

Planning is investigated in an area where classical STRIPS-like approaches usually fail. The application domain is therapy (i.e. repair) for complex dynamic processes. The peculiarities of this domain are discussed in some detail for convincingly developing the characteristics of the inductive planning approach presented. Plans are intended to be run for process therapy. Thus, plans are programs. Because of the unavoidable vagueness and uncertainty of information about complex dynamic processes in the case of disturbance, therapy plan generation turns out to be inductive program synthesis. There is developed a graph-theoretically based approach to inductive therapy plan generation. This approach is investigated from the inductive inference perspective. Particular emphasis is put on consistent and incremental learning of therapy plans. Basic application scenarios are developed and compared to each other. The inductive inference approach is invoked to develop and investigate a couple of planning algorithms. The core versions of these algorithms are successfully implemented in Lisp and Prolog. The work has been partially supported by the German Federal Ministry for Research and Technology (BMFT) within the Joint Project (BMFT-Verbundprojekt)Wiscon onDevelopment of Methods for Intelligent Monitoring and Control under contract no. 413-4001-01 IW 204 B. Additionally, the second author’s work in learning theory received some support from the German Federal Ministry for Research and Technology (BMFT) within the Joint Project (BMFT-Verbundprojekt)Gosler onAlgorithmic Learning for Knowledge-Based Systems under contract no. 413-4001-01 IW 101 A. Oksana Arnold: She graduated from Leipzig University of Technology in 1990 with a Master’s Thesis on a rule interpreter for default reasoning. She received her PhD. in Computer Science in 1996 on therapy control for complex dynamic processes within a knowledge-based process supervision and control system. Recently, She works at the University of Leipzig within a research project on information and communication technologies for virtual enterprises. Her main scientific interest is both in knowledge-based process supervision and control, where she did a pioneering work on therapy plan generation, and in flexible information systems for new generation business applications. Klaus P. Jantke: He graduated from Humboldt University Berlin with a Master’s Thesis in 1975. He received his Ph. D. in Computer Science in 1979 and his Habilitation at Humboldt in 1984. He worked as the Head of a Research Laboratory in Theoretical Computer Science and as a Vice-Director of the Computing Center at Humboldt University. Since 1987, Dr. Jantke is full professor at Leipzig University of Technology. His main research interest is in algorithmic learning theory. Besides this, he contributes to case-based reasoning, where his special interest is in learning issues and in structural similarity, and to knowledge-based process supervision and control, especially to planning. Dr. Jantke is member of the ACM, the EATCS, and the GI.     

Current transfer processes in a hydrated layer localized in a two-layer porous structure of nanosized ZrO2

Journal of Materials Science: Materials in Electronics - The current transfer through a two-layer structure saturated with absorbed water, each layer of which consists of pressed ZrO2 nanoparticles...     

Allelopathic influence ofSorghum bicolor on weeds during germination and early development of seedlings

The allelopathic interaction between sorghum [Sorghum bicolor (L.) Moench] and 10 species of grass and broadleaf weeds was investigated. Germination of weed seeds was slightly inhibited or stimulated, depending on species, when incubated in closed Petri dishes with germinating sorghum. Subsequent radicle and hypocotyl or coleoptile elongation of weeds was significantly inhibited by the germinating sorghum. For weeds interplanted with sorghum and grown under greenhouse conditions. The inhibitory effect on some weed species was still evident after 2 months of growth. Significant differences were found in the dry matter per weed plant grown in pots in proximity to sorghum vs. weeds grown in monoculture. Aqueous leachates from pots planted with sorghum alone or from a system in which sorghum roots protruded into water had strong allelopathic activity. These results indicate that water-soluble allelochemicals are produced by germinating sorghum seeds and that production of these substances continues during seedling growth.Agricultural Research Service, U.S. Department of Agriculture.     

Coding of Experimental Conditions in Microfluidic Droplet Assays Using Colored Beads and Machine Learning Supported Image Analysis

To efficiently exploit the potential of several millions of droplets that can be considered as individual bioreactors in microfluidic experiments, methods to encode different experimental conditions in droplets are needed. The approach presented here is based on coencapsulation of colored polystyrene beads with biological samples. The decoding of the droplets, as well as content quantification, are performed by automated analysis of triggered images of individual droplets in‐flow using bright‐field microscopy. The decoding strategy combines bead classification using a random forest classifier and Bayesian inference to identify different codes and thus experimental conditions. Antibiotic susceptibility testing of nine different antibiotics and the determination of the minimal inhibitory concentration of a specific antibiotic against a laboratory strain of Escherichia coli are presented as a proof‐of‐principle. It is demonstrated that this method allows successful encoding and decoding of 20 different experimental conditions within a large droplet population of more than 10⁵ droplets per condition. The decoding strategy correctly assigns 99.6% of droplets to the correct condition and a method for the determination of minimal inhibitory concentration using droplet microfluidics is established. The current encoding and decoding pipeline can readily be extended to more codes by adding more bead colors or color combinations.