Beta, Carsten

[["dc.bibliographiccitation.issue","9"],["dc.bibliographiccitation.journal","PMC Biophysics"],["dc.bibliographiccitation.lastpage","15"],["dc.bibliographiccitation.volume","3"],["dc.contributor.author","Westendorf, Christian"],["dc.contributor.author","Bae, Albert J."],["dc.contributor.author","Erlenkamper, Christoph"],["dc.contributor.author","Galland, Edouard"],["dc.contributor.author","Franck, Carl"],["dc.contributor.author","Bodenschatz, Eberhard"],["dc.contributor.author","Beta, Carsten"],["dc.date.accessioned","2019-07-09T11:52:49Z"],["dc.date.available","2019-07-09T11:52:49Z"],["dc.date.issued","2010"],["dc.description.abstract","Eukaryotic cell flattening is valuable for improving microscopic observations, ranging from bright field (BF) to total internal reflection fluorescence (TIRF) microscopy. Fundamental processes, such as mitosis and in vivo actin polymerization, have been investigated using these techniques. Here, we review the well known agar overlayer protocol and the oil overlay method. In addition, we present more elaborate microfluidics-based techniques that provide us with a greater level of control. We demonstrate these techniques on the social amoebae Dictyostelium discoideum, comparing the advantages and disadvantages of each method. PACS Codes: 87.64.-t, 47.61.-k, 87.80.Ek"],["dc.identifier.doi","10.1186/1757-5036-3-9"],["dc.identifier.pmid","20403171"],["dc.identifier.purl","https://resolver.sub.uni-goettingen.de/purl?gs-1/6028"],["dc.identifier.uri","https://resolver.sub.uni-goettingen.de/purl?gro-2/60285"],["dc.language.iso","en"],["dc.notes.intern","Merged from goescholar"],["dc.relation.orgunit","Fakultät für Physik"],["dc.rights","Goescholar"],["dc.rights.uri","https://goedoc.uni-goettingen.de/licenses"],["dc.subject.ddc","530"],["dc.title","Live cell flattening -traditional and novel approaches"],["dc.type","journal_article"],["dc.type.internalPublication","yes"],["dc.type.version","published_version"],["dspace.entity.type","Publication"]]

[["dc.bibliographiccitation.artnumber","e37213"],["dc.bibliographiccitation.issue","5"],["dc.bibliographiccitation.journal","PLoS ONE"],["dc.bibliographiccitation.volume","7"],["dc.contributor.author","Amselem, Gabriel"],["dc.contributor.author","Theves, Matthias"],["dc.contributor.author","Bae, Albert J."],["dc.contributor.author","Bodenschatz, Eberhard"],["dc.contributor.author","Beta, Carsten"],["dc.date.accessioned","2018-11-07T09:10:15Z"],["dc.date.available","2018-11-07T09:10:15Z"],["dc.date.issued","2012"],["dc.description.abstract","Chemotaxis, the directed motion of a cell toward a chemical source, plays a key role in many essential biological processes. Here, we derive a statistical model that quantitatively describes the chemotactic motion of eukaryotic cells in a chemical gradient. Our model is based on observations of the chemotactic motion of the social ameba Dictyostelium discoideum, a model organism for eukaryotic chemotaxis. A large number of cell trajectories in stationary, linear chemoattractant gradients is measured, using microfluidic tools in combination with automated cell tracking. We describe the directional motion as the interplay between deterministic and stochastic contributions based on a Langevin equation. The functional form of this equation is directly extracted from experimental data by angle-resolved conditional averages. It contains quadratic deterministic damping and multiplicative noise. In the presence of an external gradient, the deterministic part shows a clear angular dependence that takes the form of a force pointing in gradient direction. With increasing gradient steepness, this force passes through a maximum that coincides with maxima in both speed and directionality of the cells. The stochastic part, on the other hand, does not depend on the orientation of the directional cue and remains independent of the gradient magnitude. Numerical simulations of our probabilistic model yield quantitative agreement with the experimental distribution functions. Thus our model captures well the dynamics of chemotactic cells and can serve to quantify differences and similarities of different chemotactic eukaryotes. Finally, on the basis of our model, we can characterize the heterogeneity within a population of chemotactic cells."],["dc.description.sponsorship","Deutsche Forschungsgemeinschaft (DFG) [BE 3978/3-1]"],["dc.identifier.doi","10.1371/journal.pone.0037213"],["dc.identifier.isi","000305342300029"],["dc.identifier.pmid","22662138"],["dc.identifier.purl","https://resolver.sub.uni-goettingen.de/purl?gs-1/7898"],["dc.identifier.uri","https://resolver.sub.uni-goettingen.de/purl?gro-2/26447"],["dc.notes","CB acknowledges financial support by the Deutsche Forschungsgemeinschaft (DFG BE 3978/3-1), www.dfg.de."],["dc.notes.intern","Merged from goescholar"],["dc.notes.status","zu prüfen"],["dc.notes.submitter","Najko"],["dc.publisher","Public Library Science"],["dc.relation.issn","1932-6203"],["dc.relation.orgunit","Fakultät für Physik"],["dc.title","A Stochastic Description of Dictyostelium Chemotaxis"],["dc.type","journal_article"],["dc.type.internalPublication","yes"],["dc.type.peerReviewed","yes"],["dc.type.status","published"],["dc.type.version","published_version"],["dspace.entity.type","Publication"]]