Witt, Hannes

[["dc.bibliographiccitation.firstpage","18"],["dc.bibliographiccitation.issue","1"],["dc.bibliographiccitation.journal","METHODS OF INFORMATION IN MEDICINE"],["dc.bibliographiccitation.lastpage","28"],["dc.bibliographiccitation.volume","48"],["dc.contributor.author","Witte, H."],["dc.contributor.author","Ungureanu, M."],["dc.contributor.author","Ligges, C."],["dc.contributor.author","Hemmelmann, D."],["dc.contributor.author","Wuestenberg, Torsten"],["dc.contributor.author","Reichenbach, J."],["dc.contributor.author","Astolfi, L."],["dc.contributor.author","Babiloni, F."],["dc.contributor.author","Leistritz, L."],["dc.date.accessioned","2018-11-07T08:35:07Z"],["dc.date.available","2018-11-07T08:35:07Z"],["dc.date.issued","2009"],["dc.description.abstract","Objectives: The main objective is to show current topics and future trends in the field of medical signal processing which are derived from current research concepts. Signal processing as an integrative concept within the scope of medical informatics is demonstrated, Methods: For all examples time-variant multivariate autoregressive models were used. Based on this modeling, the concept of Granger causality in terms of the time-variant Granger causality index and the time-variant partial directed coherence was realized to investigate directed information transfer between different brain regions. Results: Signal informatics encompasses several diverse domains including: processing steps, methodologies, levels and subject fields, and applications. Five trends can be recognized and in order to illustrate these trends, three analysis strategies derived from current neuroscientific studies are presented. These examples comprise high-dimensional fMRI and EEG data. In the first example, the quantification of time-variant-directed information transfer between activated brain regions on the basis of fast-fMRI data is introduced and discussed. The second example deals with the investigation of differences in word processing between dyslexic and normal reading children. Different dynamic neural networks of the directed information transfer are identified on the basis of event-related potentials. The third example shows time-variant cortical connectivity networks derived from a source model. Conclusions: These examples strongly emphasize the integrative nature of signal informatics, encompassing processing steps, methodologies, levels and subject fields, and applications."],["dc.identifier.doi","10.3414/ME9133"],["dc.identifier.isi","000262991700004"],["dc.identifier.pmid","19151880"],["dc.identifier.uri","https://resolver.sub.uni-goettingen.de/purl?gro-2/17983"],["dc.notes.status","zu prüfen"],["dc.notes.submitter","Najko"],["dc.publisher","Schattauer Gmbh-verlag Medizin Naturwissenschaften"],["dc.relation.issn","0026-1270"],["dc.title","Signal Informatics as an Advanced Integrative Concept in the Framework of Medical Informatics New Trends Demonstrated by Examples Derived from Neuroscience"],["dc.type","journal_article"],["dc.type.internalPublication","yes"],["dc.type.peerReviewed","yes"],["dc.type.status","published"],["dspace.entity.type","Publication"]]

[["dc.bibliographiccitation.journal","European Biophysics Journal"],["dc.contributor.author","Witt, Hannes"],["dc.contributor.author","Savić, Filip"],["dc.contributor.author","Verbeek, Sarah"],["dc.contributor.author","Dietz, Jörn"],["dc.contributor.author","Tarantola, Gesa"],["dc.contributor.author","Oelkers, Marieelen"],["dc.contributor.author","Geil, Burkhard"],["dc.contributor.author","Janshoff, Andreas"],["dc.date.accessioned","2021-04-14T08:29:19Z"],["dc.date.available","2021-04-14T08:29:19Z"],["dc.date.issued","2021"],["dc.identifier.doi","10.1007/s00249-020-01490-5"],["dc.identifier.uri","https://resolver.sub.uni-goettingen.de/purl?gro-2/82863"],["dc.language.iso","en"],["dc.notes.intern","DOI Import GROB-399"],["dc.relation.eissn","1432-1017"],["dc.relation.issn","0175-7571"],["dc.title","Membrane fusion studied by colloidal probes"],["dc.type","journal_article"],["dc.type.internalPublication","yes"],["dspace.entity.type","Publication"]]

[["dc.bibliographiccitation.firstpage","722"],["dc.bibliographiccitation.issue","3"],["dc.bibliographiccitation.journal","NeuroImage"],["dc.bibliographiccitation.lastpage","737"],["dc.bibliographiccitation.volume","45"],["dc.contributor.author","Hemmelmann, D."],["dc.contributor.author","Ungureanu, M."],["dc.contributor.author","Hesse, W."],["dc.contributor.author","Wuestenberg, Torsten"],["dc.contributor.author","Reichenbach, Juergen R."],["dc.contributor.author","Witte, Otto-Wilhelm"],["dc.contributor.author","Witte, H."],["dc.contributor.author","Leistritz, L."],["dc.date.accessioned","2018-11-07T08:30:47Z"],["dc.date.available","2018-11-07T08:30:47Z"],["dc.date.issued","2009"],["dc.description.abstract","Time-variant Granger Causality Index (tvGCI) was applied to simulated and measured BOLD signals to investigate the reliability of time-variant analysis approaches for the identification of directed interrelations between brain areas on the basis of fMRI data. Single-shot fMRI data of a single image slice with short repetition times (200 ms, 16000 frames/subject, 64x64 voxels) were acquired from 5 healthy subjects during an externally-driven, self-paced finger-tapping paradigm (57-59 single taps for each subject). BOLD signals were derived from the pre-supplementary motor area (preSMA), the supplementary motor area (SMA), and the primary motor cortex (M1). The simulations were carried out by means of a Dynamic Causal Modelling (DCM) approach. The tvGCI as well as time-variant Partial Directed Coherence (tvPDC) were used to identify the modelled connectivity network (connectivity structure - CS - of the DCM). Different CSs were applied by using dynamic systems (Generalized Dynamic Neural Network - GDNN) and trivariate autoregressive (AR) processes. The influence of the low-pass characteristics of the simulated hemodynamic response (Balloon model) and of the measuring noise was tested. Additionally, our modelling strategy considered \"spontaneous\" BOLD fluctuations before, during, and after the appearance of the event-related BOLD component. Couplings which were extracted from the simulated signals were statistically evaluated (tvGCI for shuffled data, confidence tubes for tvGCI courses). We demonstrate that connections of our CS models can be correctly identified during the event-related BOLD component and with signal-to-noise-ratios corresponding to those of the measured data. The results based on simulations can be used to examine the reliability of connectivity identification based on BOLD signals by means of time-variant as well as time-invariant connectivity measures and enable a better interpretation of the analysis results using fMRI data. A readiness-BOLD response was only detected in one subject. However, in two subjects a strong time-variant connection (tvGCI) from preSMA to SMA was observed 3 s before the tapping was executed. This connection was accompanied by a weaker rise of the tvGCI from preSMA to M1. These preceding interrelations were confirmed in the other subjects by the dynamics of tvGCI courses. Based on the results of tvGCI analysis, the time-evolution of an individual connectivity network is shown for each subject. (C) 2009 Published by Elsevier Inc."],["dc.identifier.doi","10.1016/j.neuroimage.2008.12.065"],["dc.identifier.isi","000264378400010"],["dc.identifier.pmid","19280694"],["dc.identifier.uri","https://resolver.sub.uni-goettingen.de/purl?gro-2/16973"],["dc.notes.status","zu prüfen"],["dc.notes.submitter","Najko"],["dc.publisher","Academic Press Inc Elsevier Science"],["dc.relation.issn","1053-8119"],["dc.title","Modelling and analysis of time-variant directed interrelations between brain regions based on BOLD-signals"],["dc.type","journal_article"],["dc.type.internalPublication","yes"],["dc.type.peerReviewed","yes"],["dc.type.status","published"],["dspace.entity.type","Publication"]]

[["dc.bibliographiccitation.firstpage","643"],["dc.bibliographiccitation.issue","6"],["dc.bibliographiccitation.journal","METHODS OF INFORMATION IN MEDICINE"],["dc.bibliographiccitation.lastpage","650"],["dc.bibliographiccitation.volume","45"],["dc.contributor.author","Leistritz, L."],["dc.contributor.author","Hesse, W."],["dc.contributor.author","Wuestenberg, Torsten"],["dc.contributor.author","Fitzek, C."],["dc.contributor.author","Reichenbach, Juergen R."],["dc.contributor.author","Witte, H."],["dc.date.accessioned","2018-11-07T10:38:26Z"],["dc.date.available","2018-11-07T10:38:26Z"],["dc.date.issued","2006"],["dc.description.abstract","Objectives: Image sequences with time-varying information content need appropriate analysis strategies. The exploration of directed information transfer (interactions) between neuronal assemblies is one of the most important aims of current functional MRI (fMRI) analysis. Additionally, we examined perfusion maps in dynamic contrast agent MRI sequences of stroke patients. In this investigation, the focus centres on distinguishing between brain areas with normal and reduced perfusion on the basis of the dynamics of contrast agent flow and washout. Methods: Fast fMRI sequences were analyzed with time-varient autoregressive model and is used for the quantification of the directed information transfer between activated brain areas. Generalized Dynamic Neural Networks (GDNN) with time-varient weights were applied on dynamic contrast agent MRI sequences as a nonlinear operator in order to enhance differences in the signal courses of pixels of normal and injured tissues. Results: A simple motor task (self-paced finger tapping) is used in an fMRI design to investigate directed interactions between defined brain areas. A significant information transfer can be determined for the direction primary motor cortex to supplementary motor area during a short time period of about five seconds after stimulus. The analysis of dynamic contrast agent MRI sequences demonstrates that the trained GDNN enables a reliable tissue classification. Three classes of interest: normal tissue, tissue at risk for death, and dead tissue. Conclusions: The time-varient multivariate analysis of directed information transfer derived from fMRI sequences and the computation of perfusion maps by GDNN demonstrate that dynamic analysis methods are essential tools for 4D image analysis."],["dc.identifier.isi","000242859600009"],["dc.identifier.pmid","17149506"],["dc.identifier.uri","https://resolver.sub.uni-goettingen.de/purl?gro-2/45812"],["dc.notes.status","zu prüfen"],["dc.notes.submitter","Najko"],["dc.publisher","Schattauer Gmbh-verlag Medizin Naturwissenschaften"],["dc.relation.issn","0026-1270"],["dc.title","Time-variant analysis of fast-fMRI and dynamic contrast agent MRI sequences as examples of 4-dimensional image analysis"],["dc.type","journal_article"],["dc.type.internalPublication","yes"],["dc.type.peerReviewed","yes"],["dc.type.status","published"],["dspace.entity.type","Publication"]]

[["dc.bibliographiccitation.firstpage","2278"],["dc.bibliographiccitation.issue","15"],["dc.bibliographiccitation.journal","Biochemistry"],["dc.bibliographiccitation.lastpage","2288"],["dc.bibliographiccitation.volume","57"],["dc.contributor.author","Seiwert, Dennis"],["dc.contributor.author","Witt, Hannes"],["dc.contributor.author","Ritz, Sandra"],["dc.contributor.author","Janshoff, Andreas"],["dc.contributor.author","Paulsen, Harald"],["dc.date.accessioned","2020-12-10T15:22:31Z"],["dc.date.available","2020-12-10T15:22:31Z"],["dc.date.issued","2018"],["dc.identifier.doi","10.1021/acs.biochem.8b00118"],["dc.identifier.eissn","1520-4995"],["dc.identifier.issn","0006-2960"],["dc.identifier.uri","https://resolver.sub.uni-goettingen.de/purl?gro-2/73430"],["dc.language.iso","en"],["dc.notes.intern","DOI Import GROB-354"],["dc.title","The Nonbilayer Lipid MGDG and the Major Light-Harvesting Complex (LHCII) Promote Membrane Stacking in Supported Lipid Bilayers"],["dc.type","journal_article"],["dc.type.internalPublication","yes"],["dspace.entity.type","Publication"]]

[["dc.bibliographiccitation.firstpage","13244"],["dc.bibliographiccitation.issue","44"],["dc.bibliographiccitation.journal","Langmuir"],["dc.bibliographiccitation.lastpage","13250"],["dc.bibliographiccitation.volume","36"],["dc.contributor.author","Witt, Hannes"],["dc.contributor.author","Yandrapalli, Naresh"],["dc.contributor.author","Sari, Merve"],["dc.contributor.author","Turco, Laura"],["dc.contributor.author","Robinson, Tom"],["dc.contributor.author","Steinem, Claudia"],["dc.date.accessioned","2021-04-14T08:31:54Z"],["dc.date.available","2021-04-14T08:31:54Z"],["dc.date.issued","2020"],["dc.identifier.doi","10.1021/acs.langmuir.0c02175"],["dc.identifier.uri","https://resolver.sub.uni-goettingen.de/purl?gro-2/83745"],["dc.language.iso","en"],["dc.notes.intern","DOI Import GROB-399"],["dc.relation.eissn","1520-5827"],["dc.relation.issn","0743-7463"],["dc.title","Precipitation of Calcium Carbonate Inside Giant Unilamellar Vesicles Composed of Fluid-Phase Lipids"],["dc.type","journal_article"],["dc.type.internalPublication","yes"],["dspace.entity.type","Publication"]]

[["dc.bibliographiccitation.firstpage","22504"],["dc.bibliographiccitation.issue","47"],["dc.bibliographiccitation.journal","Nanoscale"],["dc.bibliographiccitation.lastpage","22519"],["dc.bibliographiccitation.volume","10"],["dc.contributor.author","Kamprad, Nadine"],["dc.contributor.author","Witt, Hannes"],["dc.contributor.author","Schröder, Marcel"],["dc.contributor.author","Kreis, Christian Titus"],["dc.contributor.author","Bäumchen, Oliver"],["dc.contributor.author","Janshoff, Andreas"],["dc.contributor.author","Tarantola, Marco"],["dc.date.accessioned","2020-12-10T18:11:24Z"],["dc.date.available","2020-12-10T18:11:24Z"],["dc.date.issued","2018"],["dc.description.abstract","Dictyostelium discoideum cells rely on two different mechanisms for adhesion: wetting through conventional colloidal forces and stochastic nanocluster dynamics."],["dc.description.abstract","Biological adhesion is essential for all motile cells and generally limits locomotion to suitably functionalized substrates displaying a compatible surface chemistry. However, organisms that face vastly varying environmental challenges require a different strategy. The model organism Dictyostelium discoideum ( D.d. ), a slime mould dwelling in the soil, faces the challenge of overcoming variable chemistry by employing the fundamental forces of colloid science. To understand the origin of D.d. adhesion, we realized and modified a variety of conditions for the amoeba comprising the absence and presence of the specific adhesion protein Substrate Adhesion A ( sadA ), glycolytic degradation, ionic strength, surface hydrophobicity and strength of van der Waals interactions by generating tailored model substrates. By employing AFM-based single cell force spectroscopy we could show that experimental force curves upon retraction exhibit two regimes. The first part up to the critical adhesion force can be described in terms of a continuum model, while the second regime of the curve beyond the critical adhesion force is governed by stochastic unbinding of individual binding partners and bond clusters. We found that D.d. relies on adhesive interactions based on EDL-DLVO (Electrical Double Layer-Derjaguin–Landau–Verwey–Overbeek) forces and contributions from the glycocalix and specialized adhesion molecules like sadA . This versatile mechanism allows the cells to adhere to a large variety of natural surfaces under various conditions."],["dc.description.abstract","Dictyostelium discoideum cells rely on two different mechanisms for adhesion: wetting through conventional colloidal forces and stochastic nanocluster dynamics."],["dc.description.abstract","Biological adhesion is essential for all motile cells and generally limits locomotion to suitably functionalized substrates displaying a compatible surface chemistry. However, organisms that face vastly varying environmental challenges require a different strategy. The model organism Dictyostelium discoideum ( D.d. ), a slime mould dwelling in the soil, faces the challenge of overcoming variable chemistry by employing the fundamental forces of colloid science. To understand the origin of D.d. adhesion, we realized and modified a variety of conditions for the amoeba comprising the absence and presence of the specific adhesion protein Substrate Adhesion A ( sadA ), glycolytic degradation, ionic strength, surface hydrophobicity and strength of van der Waals interactions by generating tailored model substrates. By employing AFM-based single cell force spectroscopy we could show that experimental force curves upon retraction exhibit two regimes. The first part up to the critical adhesion force can be described in terms of a continuum model, while the second regime of the curve beyond the critical adhesion force is governed by stochastic unbinding of individual binding partners and bond clusters. We found that D.d. relies on adhesive interactions based on EDL-DLVO (Electrical Double Layer-Derjaguin–Landau–Verwey–Overbeek) forces and contributions from the glycocalix and specialized adhesion molecules like sadA . This versatile mechanism allows the cells to adhere to a large variety of natural surfaces under various conditions."],["dc.identifier.doi","10.1039/C8NR07107A"],["dc.identifier.eissn","2040-3372"],["dc.identifier.issn","2040-3364"],["dc.identifier.uri","https://resolver.sub.uni-goettingen.de/purl?gro-2/73995"],["dc.language.iso","en"],["dc.notes.intern","DOI Import GROB-354"],["dc.relation.eissn","2040-3372"],["dc.relation.issn","2040-3364"],["dc.rights.uri","http://creativecommons.org/licenses/by/3.0/"],["dc.title","Adhesion strategies of Dictyostelium discoideum – a force spectroscopy study"],["dc.type","journal_article"],["dc.type.internalPublication","yes"],["dspace.entity.type","Publication"]]

[["dc.bibliographiccitation.firstpage","33516"],["dc.bibliographiccitation.issue","30"],["dc.bibliographiccitation.journal","ACS Applied Materials & Interfaces"],["dc.bibliographiccitation.lastpage","33529"],["dc.bibliographiccitation.volume","12"],["dc.contributor.author","Kim, Hyejeong"],["dc.contributor.author","Witt, Hannes"],["dc.contributor.author","Oswald, Tabea A."],["dc.contributor.author","Tarantola, Marco"],["dc.date.accessioned","2020-11-05T15:08:09Z"],["dc.date.available","2020-11-05T15:08:09Z"],["dc.date.issued","2020"],["dc.identifier.doi","10.1021/acsami.0c09166"],["dc.identifier.uri","https://resolver.sub.uni-goettingen.de/purl?gro-2/68477"],["dc.language.iso","en"],["dc.notes.intern","DOI Import GROB-352.7"],["dc.relation.eissn","1944-8252"],["dc.relation.issn","1944-8244"],["dc.title","Adhesion of Epithelial Cells to PNIPAm Treated Surfaces for Temperature-Controlled Cell-Sheet Harvesting"],["dc.type","journal_article"],["dc.type.internalPublication","unknown"],["dspace.entity.type","Publication"]]

[["dc.contributor.author","Lorenz, Charlotta"],["dc.contributor.author","Forsting, Johanna"],["dc.contributor.author","Schepers, Anna V."],["dc.contributor.author","Kraxner, Julia"],["dc.contributor.author","Bauch, Susanne"],["dc.contributor.author","Witt, Hannes"],["dc.contributor.author","Klumpp, Stefan"],["dc.contributor.author","Köster, Sarah"],["dc.date.accessioned","2020-03-03T08:23:45Z"],["dc.date.available","2020-03-03T08:23:45Z"],["dc.date.issued","2019"],["dc.description.abstract","The cytoskeleton is a composite network of three types of protein filaments, among which in-termediate filaments (IFs) are the most extensible ones. Two very important IFs are keratin and vimentin, which have similar molecular architectures, but different mechanical behaviors. Here we compare the mechanical response of single keratin and vimentin filaments using optical tweezers. We show that the mechanics of vimentin strongly depends on the ionic strength of the buffer and that its force-strain curve suggests a high degree of cooperativity between subunits. Indeed, a computational model indicates that in contrast to keratin, vimentin is characterized by strong lateral subunit coupling of its charged monomers during unfolding of α-helices. We conclude that cells can tune their mechanics by differential use of keratin versus vimentin."],["dc.identifier.doi","10.1101/676197"],["dc.identifier.purl","https://resolver.sub.uni-goettingen.de/purl?gs-1/16475"],["dc.identifier.uri","https://resolver.sub.uni-goettingen.de/purl?gro-2/63071"],["dc.language.iso","en"],["dc.title","Lateral Subunit Coupling Determines Intermediate Filament Mechanics"],["dc.type","preprint"],["dc.type.internalPublication","yes"],["dspace.entity.type","Publication"]]

[["dc.bibliographiccitation.firstpage","13051"],["dc.bibliographiccitation.issue","46"],["dc.bibliographiccitation.journal","PROCEEDINGS OF THE NATIONAL ACADEMY OF SCIENCES OF THE UNITED STATES OF AMERICA"],["dc.bibliographiccitation.lastpage","13056"],["dc.bibliographiccitation.volume","113"],["dc.contributor.author","Oelkers, Marieelen"],["dc.contributor.author","Witt, Hannes"],["dc.contributor.author","Halder, Partho"],["dc.contributor.author","Jahn, Reinhard"],["dc.contributor.author","Janshoff, Andreas"],["dc.date.accessioned","2018-11-07T10:05:44Z"],["dc.date.available","2018-11-07T10:05:44Z"],["dc.date.issued","2016"],["dc.description.abstract","Fusion of lipid bilayers is usually prevented by large energy barriers arising from removal of the hydration shell, formation of highly curved structures, and, eventually, fusion pore widening. Here, we measured the force-dependent lifetime of fusion intermediates using membrane-coated silica spheres attached to cantilevers of an atomic-force microscope. Analysis of time traces obtained from force-clamp experiments allowed us to unequivocally assign steps in deflection of the cantilever to membrane states during the SNARE-mediated fusion with solid-supported lipid bilayers. Force-dependent lifetime distributions of the various intermediate fusion states allowed us to propose the likelihood of different fusion pathways and to assess the main free energy barrier, which was found to be related to passing of the hydration barrier and splaying of lipids to eventually enter either the fully fused state or a long-lived hemifusion intermediate. The results were compared with SNARE mutants that arrest adjacent bilayers in the docked state and membranes in the absence of SNAREs but presence of PEG or calcium. Only with the WT SNARE construct was appreciable merging of both bilayers observed."],["dc.description.sponsorship","Deutsche Forschungsgemeinschaft [GSC 226/2, SFB 803 B06, B08]"],["dc.identifier.doi","10.1073/pnas.1615885113"],["dc.identifier.isi","000388970100058"],["dc.identifier.pmid","27807132"],["dc.identifier.uri","https://resolver.sub.uni-goettingen.de/purl?gro-2/38957"],["dc.notes.status","zu prüfen"],["dc.notes.submitter","Najko"],["dc.publisher","Natl Acad Sciences"],["dc.relation.issn","0027-8424"],["dc.title","SNARE-mediated membrane fusion trajectories derived from force-clamp experiments"],["dc.type","journal_article"],["dc.type.internalPublication","yes"],["dc.type.peerReviewed","yes"],["dc.type.status","published"],["dspace.entity.type","Publication"]]