Biomedical subjects

Dirk Neumann

Publications and source records attributed to Dirk Neumann.

8 recordsLinked to original sources

PubMed2006

Emotional arousal in agenesis of the corpus callosum.

While the processing of verbal and psychophysiological indices of emotional arousal have been investigated extensively in relation to the left and right cerebral hemispheres, it remains poorly understood how both hemispheres normally function together to generate emotional responses to stimuli. Drawing on a unique sample of nine high-functioning subjects with complete agenesis of the corpus callosum (AgCC), we investigated this issue using standardized emotional visual stimuli. Compared to healthy controls, subjects with AgCC showed a larger variance in their cognitive ratings of valence and arousal, and an insensitivity to the emotion category of the stimuli, especially for negatively-valenced stimuli, and especially for their arousal. Despite their impaired cognitive ratings of arousal, some subjects with AgCC showed large skin-conductance responses, and in general skin-conductance responses discriminated emotion categories and correlated with stimulus arousal ratings. We suggest that largely intact right hemisphere mechanisms can support psychophysiological emotional responses, but that the lack of interhemispheric communication between the hemispheres, perhaps together with dysfunction of the anterior cingulate cortex, interferes with normal verbal ratings of arousal, a mechanism in line with some models of alexithymia.

Adult↗

PubMed2005

Tunable retina encoders for retina implants: why and how.

Current research towards retina implants for partial restoration of vision in blind humans with retinal degenerative dysfunctions focuses on implant and stimulation experiments and technologies. In contrast, our approach takes the availability of an epiretinal multi-electrode neural interface for granted and studies the conditions for successful joint information processing of both retinal prosthesis and brain. Our proposed learning retina encoder (RE) includes information processing modules to simulate the complex mapping operation of parts of the 5-layered neural retina and to provide an iterative, perception-based dialog between RE and human subject. Alternative information processing technologies in the learning RE are being described, which allow an individual optimization of the RE mapping operation by means of iterative tuning with learning algorithms in a dialog between implant wearing subject and RE. The primate visual system is modeled by a retina module (RM) composed of spatio-temporal (ST) filters and a central visual system module (VM). RM performs a mapping 1 of an optical pattern P1 in the physical domain onto a retinal output vector R1(t) in a neural domain, whereas VM performs a mapping 2 of R1(t) in a neural domain onto a visual percept P2 in the perceptual domain. Retinal ganglion cell properties represent non-invertible ST filters in RE, which generate ambiguous output signals. VM generates visual percepts only if the corresponding R1(t) is properly encoded, contains sufficient information, and can be disambiguated. Based on the learning RE and the proposed visual system model, a novel retina encoder (RE*) is proposed, which considers both ambiguity removal and miniature eye movements during fixation. Our simulation results suggest that VM requires miniature eye movements under control of the visual system to retrieve unambiguous patterns P2 corresponding to P1. For retina implant applications, RE* can be tuned to generate optimal ganglion cell codes for epiretinal stimulation.

Action Potentials↗

PubMed2005

Isolation and structural analysis of peptide mimotopes for the disialoganglioside GD2, a neuroblastoma tumor antigen.

The disialoganglioside GalAcbeta1-4(NeuAcalpha2-8NeuAcalpha2-3)Galbeta1-4Glcbeta1-1Cer (GD2) is expressed on various tumors, including neuroblastoma, and was defined as a relevant tumor antigen. The monoclonal anti-GD2 antibody 14.18 is widely used for diagnostic purposes in neuroblastoma, and in its mouse/human chimeric form (ch14.18) now enters passive immunotherapeutic regimens in phase II clinical trials. This study aimed to generate structural mimics of the 14.18 epitope of GD2. Therefore, we used the ch14.18 antibody for selecting immunoreactive GD2 peptide mimotopes from a decamer phage display library. In all, 13 GD2 peptide mimics could be determined by biopanning and their specificity was demonstrated by exclusive recognition by the ch14.18 antibody. Furthermore, their nature of being GD2 mimics and their degree of mimicry was confirmed by competition with the natural antigen. When performing a comparative visualization of the GD2 epitope and selected mimotopes using a three-dimensional computer modeling system (BALLView), we demonstrated fitting of the GD2 molecule and the mimotopes in the antigen-binding pouch of a GD2 specific antibody. Moreover, the computer modeling argued for optimal affinity of the GD2 mimotopes. We thus provide evidence that the generation of GD2 peptide mimotopes is successful when using the neuroblastoma antibody ch14.18 for selection, and that this approach might offer a tool to develop a vaccination strategy against this malignant pediatric tumor.

Amino Acid Sequence↗

PubMed2004

Computational modeling of the sugar-lectin interaction.

In the last few years numerous experimental studies have shed light onto the details of the lectin-carbohydrate interaction. X-ray crystallography and NMR spectroscopy have been used to elucidate the structures of lectins, sugars, and their complexes. In addition, an increasing number of experimental methods has been employed to determine the thermodynamic and kinetic parameters of the binding process. Based on this experimental data, computational methods have been developed to model and predict these interactions. A plethora of techniques from Molecular Modeling and Computational Chemistry have been applied to the problem and current models achieve high-quality predictions. These successes are based on both new theoretical approaches and reliable experimental data. The aim of the present article is to outline the most relevant computational and experimental methods applied in the field of lectin-carbohydrate interaction and to give an overview of the current state of the art in the modeling of these interactions with a focus on plant lectins.

Carbohydrates↗

PubMed2002

Lectin-sugar interaction. Calculated versus experimental binding energies.

Although a steadily increasing number of protein--ligand docking experiments have been performed successfully, there are only few studies concerning protein--sugar interactions. In this study, we investigate the interaction of wheat germ agglutinin (WGA) with N-acetylglucosamine and a number of its derivatives and predict the binding free energies using flexible docking techniques. To assess the quality of our predictions, we also determined those binding free energies experimentally in cell-binding studies. The predicted binding site, ligand orientation, and details of the binding mode are in perfect agreement with the known crystal structure of WGA with a sialoglycopeptide. Furthermore, we obtained an excellent linear correlation of our predicted binding free energies with both our own data and experimental data from the literature [Monsigny, M., Roche, A.C., Sene, C., Maget Dana, R. & Delmotte, F. (1980) Eur. J. Biochem. 104, 147-153.]. In both cases, predicted energies were within 1.0 kJ x mol(-1) of the experimental value. These results illustrate the usefulness of docking-based methods for the qualitative and quantitative prediction of protein--carbohydrate interactions. The insights gained from such theoretical studies may be used to complement the results from the still scarce crystal structures.

Binding Sites↗

PubMedDate not supplied

A fully computational model for predicting percutaneous drug absorption.

The prediction of transdermal absorption for arbitrary penetrant structures has several important applications in the pharmaceutical industry. We propose a new data-driven, predictive model for skin permeability coefficients k(p) based on an ensemble model using k-nearest-neighbor models and ridge regression. The model was trained and validated with a newly assembled data set containing experimental data and structures for 110 compounds. On the basis of three purely computational descriptors (molecular weight, calculated octanol/water partition coefficient, and solvation free energy), we have developed a model allowing for the reliable, purely computational prediction of skin permeability coefficients. The model is both accurate and robust, as we showed in an extensive validation (correlation coefficient for leave-one-out cross validation: Q = 0.948, mean standard error: 0.2 for log k(p)).

Animals↗

PubMedDate not supplied

SLICK--scoring and energy functions for protein-carbohydrate interactions.

Protein-carbohydrate interactions are increasingly being recognized as essential for many important biomolecular recognition processes. From these, numerous biomedical applications arise in areas as diverse as drug design, immunology, or drug transport. We introduce SLICK, a package containing a scoring and an energy function, which were specifically designed to predict binding modes and free energies of sugars and sugarlike compounds to proteins. SLICK accounts for van der Waals interactions, solvation effects, electrostatics, hydrogen bonds, and CH...pi interactions, the latter being a particular feature of most protein-carbohydrate interactions. Parameters for the empirical energy function were calibrated on a set of high-resolution crystal structures of protein-sugar complexes with known experimental binding free energies. We show that SLICK predicts the binding free energies of predicted complexes (through molecular docking) with high accuracy. SLICK is available as part of our molecular modeling package BALL (www.ball-project.org).

Calibration↗

PubMedDate not supplied

Human vascular endothelial cells in primary cell culture for the evaluation of nanoparticle bioadhesion.

Nanoparticles (NP) are employed in various therapeutic approaches for innovative drug delivery strategies. Among them, there is drug delivery to the brain and sustained release forms for intravenous drug delivery. In order to optimize drug carriers and to elucidate involved mechanisms such as bioadhesion and cellular uptake, NP were surface modified and analyzed for their interaction with human endothelial cells in cell culture. Fluorescently labeled NP of different diameters (50 to 1000 nm) were surface modified either by simple adsorption of chitosan or by covalent binding to the lectin ulex europaeus agglutinin and thereafter applied to human endothelial cells for different incubation periods. After incubation with NP the binding of NP was quantified directly by the fluorescence emission signals from the cell layers. In order to visualize the binding behaviour, NP were localized three-dimensionally in the cell layer by confocal laser scanning microscopy. Cell binding experiments in phosphate buffer were observed to be particle size dependent with the 50 nm NP showing the highest binding percentage over all experiments. Binding decreased with increasing particle diameter and shorter incubation interval. The adhesion was further enhanced by NP surface modifications in the order blank < chitosan < lectin. The presence of plasma proteins enhanced the adhesiveness of chitosan coated NP, while the binding of lectin coated NP was inhibited. Experiments at 4 degrees C indicated the involvement of an active process in the binding of NP to endothelial cells.

Adhesiveness↗