Hungarian Academy of Sciences

About: Hungarian Academy of Sciences is a government organization based out in Budapest, Hungary. It is known for research contribution in the topics: Catalysis & Population. The organization has 21510 authors who have published 56712 publications receiving 1612286 citations. The organization is also known as: Magyar Tudományos Akadémia & MTA.

Some new faces of membrane microdomains: a complex confocal fluorescence, differential polarization, and FCS imaging study on live immune cells.

Abstract: Lipid rafts are cholesterol- and glycosphingolipid-rich plasma membrane microdomains, which control signal transduction, cellular contacts, pathogen recognition, and internalization processes. Their stability/lifetime, heterogeneity remained still controversial, mostly due to the high diversity of raft markers and cellular models. The correspondence of the rafts of living cells to liquid ordered (Lo) domains of model membranes and the effect of modulating rafts on the structural dynamics of their bulk membrane environment are also yet unresolved questions. Spatial overlap of various lipid and protein raft markers on live cells was studied by confocal laser scanning microscopy, while fluorescence polarization of DiIC18(3) and Bodipy-phosphatidylcholine was imaged with differential polarization CLSM (DP-CLSM). Mobility of the diI probe under different conditions was assessed by fluorescence correlation spectroscopic (FCS). GM1 gangliosides highly colocalized with GPI-linked protein markers of rafts and a new anti-cholesterol antibody (AC8) in various immune cells. On the same cells, albeit not fully excluded from rafts, diI colocalized much less with raft markers of both lipid and protein nature, suggesting the Lo membrane regions are not equivalents to lipid rafts. The DP-CLSM technique was capable of imaging probe orientation and heterogeneity of polarization in the plasma membrane of live cells, reflecting differences in lipid order/packing. This property—in accordance with diI mobility assessed by FCS—was sensitive to modulation of rafts either through their lipids or proteins. Our complex imaging analysis demonstrated that two lipid probes—GM1 and a new anti-cholesterol antibody—equivocally label the membrane rafts on a variety of cell types, while some raft-associated proteins (MHC-II, CD48, CD59, or CD90) do not colocalize with each other. This indicates the compositional heterogeneity of rafts. Usefulness of the DP-CLSM technique in imaging immune cell surface, in terms of lipid order/packing heterogeneities, was also shown together with its sensitivity to monitor biological modulation of lipid rafts. © 2007 International Society for Analytical Cytology

Consistent estimation of the basic neighborhood of Markov random fields

Abstract: For Markov random fields on Z d with finite state space, we address the statistical estimation of the basic neighborhood, the smallest region that determines the conditional distribution at a site on the condition that the values at all other sites are given. A modification of the Bayesian Information Criterion, replacing likelihood by pseudo-likelihood, is proved to provide strongly consistent estimation from observing a realization of the field on increasing finite regions: the estimated basic neighborhood equals the true one eventually almost surely, not assuming any prior bound on the size of the latter. Stationarity of the Markov field is not required, and phase transition does not affect the results.

CNN dynamics represents a broader class than PDEs

Abstract: The relationship between Cellular Nonlinear Networks (CNNs) and Partial Differential Equations (PDEs) is investigated. The equivalence between discrete-space CNN models and continuous-space PDE models is rigorously defined. The key role of space discretization is explained. The problem of the equivalence is split into two subproblems: approximation and topological equivalence, that can be explicitly studied for any CNN model. It is known that each PDE can be approximated by a space difference scheme, i.e. a CNN model, that presents a similar dynamic behavior. It is shown, through several examples, that there exist CNN models that are not equivalent to any PDEs, either because they do not approximate any PDE models, or because they have a qualitatively different dynamic behavior (i.e. they are not topologically equivalent to the PDE that they approximate). This proves that the spatio-temporal CNN dynamics is broader than that described by PDEs.