Signaling through three chemokine receptors triggers the migration of transplanted neural precursor cells in a model of multiple sclerosis

AbstractMultiple sclerosis (MS) is a multifocal disease, and precursor cells need to migrate into the multiple lesions in order to exert their therapeutic effects. Therefore, cell migration is a crucial element in regenerative processes in MS, dictating the route of delivery, when cell transplantation is considered. We have previously shown that inflammation triggers migration of multi-potential neural precursor cells (NPCs) into the white matter of experimental autoimmune encephalomyelitis (EAE) rodents, a widely used model of MS. Here we investigated the molecular basis of this attraction.NPCs were grown from E13 embryonic mouse brains and transplanted into the lateral cerebral ventricles of EAE mice. Transplanted NPC migration was directed by three tissue-derived chemokines. Stromal cell-derived factor-1α, monocyte chemo-attractant protein-1 and hepatocyte growth factor were expressed in the EAE brain and specifically in microglia and astrocytes. Their cognate receptors, CXCR4, CCR2 or c-Met were constitutively expressed on NPCs. Selective blockage of CXCR4, CCR2 or c-Met partially inhibited NPC migration in EAE brains. Blocking all three receptors had an additive effect and resulted in profound inhibition of NPC migration, as compared to extensive migration of control NPCs. The inflammation-triggered NPC migration into white matter tracts was dependent on a motile NPC phenotype. Specifically, depriving NPCs from epidermal growth factor (EGF) prevented the induction of glial commitment and a motile phenotype (as indicated by an in vitro motility assay), hampering their response to neuroinflammation.In conclusion, signaling via three chemokine systems accounts for most of the inflammation-induced, tissue-derived attraction of transplanted NPCs into white matter tracts during EAE

DNA damage in mammalian cells and its relevance to lethality

From fourth symposium on microdosimetry; Pallanza, Italy (24 Sep 1973). Cell killing (loss of proliferative capacity) is a principal end point in all radiation effects contingent upon cell viability. DNA, the molecular carrier of the genetic inheritance, affects the affairs of a cell because the properties and characteristics of a cell are dictated by the DNA -- RNA -- protein axis of information storage, flow, and expression. Thus, the mutagenic and chromosome- breaking properties of radiation, the biological amplification available to a lesion in DNA, and the fact that DNA molecularly constitutes a very large radiation target, aH make DNA the principal target relative to many radiation effects. An indirect approach may be useful in studies of the sensitive targets in a mammalian cell. This stems from the fact that to kill cells with low LET radiation; sublethal damage must be accumulated and cells can repair this damage. Thus, focussing on DNA, and repair processes in DNA, while indirect, is supporied in the instance of cell killing by extensive experimental evidence. The status of damage registered directly in DNA may be assessed by examining changes in the sedimentation of DNA from irradiated cells. Along with measurements of cell survival, sedimentation data are discussed relative to their bearing on cell killing and their ability to help us understand the organization and replication of DNA in mammalian cells. (CH

Turing machines can be efficiently simulated by the General Purpose Analog Computer

The Church-Turing thesis states that any sufficiently powerful computational model which captures the notion of algorithm is computationally equivalent to the Turing machine. This equivalence usually holds both at a computability level and at a computational complexity level modulo polynomial reductions. However, the situation is less clear in what concerns models of computation using real numbers, and no analog of the Church-Turing thesis exists for this case. Recently it was shown that some models of computation with real numbers were equivalent from a computability perspective. In particular it was shown that Shannon's General Purpose Analog Computer (GPAC) is equivalent to Computable Analysis. However, little is known about what happens at a computational complexity level. In this paper we shed some light on the connections between this two models, from a computational complexity level, by showing that, modulo polynomial reductions, computations of Turing machines can be simulated by GPACs, without the need of using more (space) resources than those used in the original Turing computation, as long as we are talking about bounded computations. In other words, computations done by the GPAC are as space-efficient as computations done in the context of Computable Analysis

Scale-free energy dissipation and dynamic phase transition in stochastic sandpiles

We study numerically scaling properties of the distribution of cumulative energy dissipated in an avalanche and the dynamic phase transition in a stochastic directed cellular automaton [B. Tadi\'c and D. Dhar, Phys. Rev. Lett. {\bf 79}, 1519 (1997)] in d=1+1 dimensions. In the critical steady state occurring for the probability of toppling $p\ge p^\star$= 0.70548, the dissipated energy distribution exhibits scaling behavior with new scaling exponents $\tau_E$ and D_E for slope and cut-off energy, respectively, indicating that the sandpile surface is a fractal. In contrast to avalanche exponents, the energy exponents appear to be p- dependent in the region $p^\star \le p <1$, however the product $(\tau_E-1)D_E$ remains universal. We estimate the roughness exponent of the transverse section of the pile as $\chi =0.44\pm 0.04$. Critical exponents characterizing the dynamic phase transition at $p^\star$ are obtained by direct simulation and scaling analysis of the survival probability distribution and the average outflow current. The transition belongs to a new universality class with the critical exponents $\nu_\| =\gamma =1.22 \pm 0.02$, $\beta =0.56\pm 0.02$ and $\nu_\bot = 0.761 \pm 0.029$, with apparent violation of hyperscaling. Generalized hyperscaling relation leads to $\beta + \beta ^\prime = (d-1)\nu_\bot$, where $\beta ^\prime = 0.195 \pm 0.012$ is the exponent governed by the ultimate survival probability

Generic Sandpile Models Have Directed Percolation Exponents

We study sandpile models with stochastic toppling rules and having sticky grains so that with a non-zero probability no toppling occurs, even if the local height of pile exceeds the threshold value. Dissipation is introduced by adding a small probability of particle loss at each toppling. Generically, for models with a preferred direction, the avalanche exponents are those of critical directed percolation clusters. For undirected models, avalanche exponents are those of directed percolation clusters in one higher dimension.Comment: 4 pages, 4 figures, minor change

Numerical Determination of the Avalanche Exponents of the Bak-Tang-Wiesenfeld Model

We consider the Bak-Tang-Wiesenfeld sandpile model on a two-dimensional square lattice of lattice sizes up to L=4096. A detailed analysis of the probability distribution of the size, area, duration and radius of the avalanches will be given. To increase the accuracy of the determination of the avalanche exponents we introduce a new method for analyzing the data which reduces the finite-size effects of the measurements. The exponents of the avalanche distributions differ slightly from previous measurements and estimates obtained from a renormalization group approach.Comment: 6 pages, 6 figure

Non-monotonic changes in clonogenic cell survival induced by disulphonated aluminum phthalocyanine photodynamic treatment in a human glioma cell line

<p>Abstract</p> <p>Background</p> <p>Photodynamic therapy (PDT) involves excitation of sensitizer molecules by visible light in the presence of molecular oxygen, thereby generating reactive oxygen species (ROS) through electron/energy transfer processes. The ROS, thus produced can cause damage to both the structure and the function of the cellular constituents resulting in cell death. Our preliminary investigations of dose-response relationships in a human glioma cell line (BMG-1) showed that disulphonated aluminum phthalocyanine (AlPcS₂) photodynamically induced loss of cell survival in a concentration dependent manner up to 1 μM, further increases in AlPcS₂concentration (>1 μM) were, however, observed to decrease the photodynamic toxicity. Considering the fact that for most photosensitizers only monotonic dose-response (survival) relationships have been reported, this result was unexpected. The present studies were, therefore, undertaken to further investigate the concentration dependent photodynamic effects of AlPcS₂.</p> <p>Methods</p> <p>Concentration-dependent cellular uptake, sub-cellular localization, proliferation and photodynamic effects of AlPcS₂were investigated in BMG-1 cells by absorbance and fluorescence measurements, image analysis, cell counting and colony forming assays, flow cytometry and micronuclei formation respectively.</p> <p>Results</p> <p>The cellular uptake as a function of extra-cellular AlPcS₂concentrations was observed to be biphasic. AlPcS₂was distributed throughout the cytoplasm with intense fluorescence in the perinuclear regions at a concentration of 1 μM, while a weak diffuse fluorescence was observed at higher concentrations. A concentration-dependent decrease in cell proliferation with accumulation of cells in G₂+M phase was observed after PDT. The response of clonogenic survival after AlPcS₂-PDT was non-monotonic with respect to AlPcS₂concentration.</p> <p>Conclusions</p> <p>Based on the results we conclude that concentration-dependent changes in physico-chemical properties of sensitizer such as aggregation may influence intracellular transport and localization of photosensitizer. Consequent modifications in the photodynamic induction of lesions and their repair leading to different modes of cell death may contribute to the observed non-linear effects.</p

Dynamically Driven Renormalization Group Applied to Sandpile Models

The general framework for the renormalization group analysis of self-organized critical sandpile models is formulated. The usual real space renormalization scheme for lattice models when applied to nonequilibrium dynamical models must be supplemented by feedback relations coming from the stationarity conditions. On the basis of these ideas the Dynamically Driven Renormalization Group is applied to describe the boundary and bulk critical behavior of sandpile models. A detailed description of the branching nature of sandpile avalanches is given in terms of the generating functions of the underlying branching process.Comment: 18 RevTeX pages, 5 figure

The Bak-Tang-Wiesenfeld sandpile model around the upper critical dimension

We consider the Bak-Tang-Wiesenfeld sandpile model on square lattices in different dimensions (D>=6). A finite size scaling analysis of the avalanche probability distributions yields the values of the distribution exponents, the dynamical exponent, and the dimension of the avalanches. Above the upper critical dimension D_u=4 the exponents equal the known mean field values. An analysis of the area probability distributions indicates that the avalanches are fractal above the critical dimension.Comment: 7 pages, including 9 figures, accepted for publication in Physical Review