10,184 research outputs found
Hindered magnetic order from mixed dimensionalities in CuPO
We present a combined experimental and theoretical study of the spin-1/2
compound CuPO that features a network of two-dimensional (2D)
antiferromagnetic (AFM) square planes, interconnected via one-dimensional (1D)
AFM spin chains. Magnetic susceptibility, high-field magnetization, and
electron spin resonance (ESR) data, as well as microscopic density-functional
band-structure calculations and subsequent quantum Monte-Carlo simulations,
show that the coupling 40 K in the layers is an order of magnitude
larger than 4 K in the chains. Below 8 K, CuPO
develops long-range order (LRO), as evidenced by a weak net moment on the 2D
planes induced by anisotropic magnetic interactions of Dzyaloshinsky-Moriya
type. A striking feature of this 3D ordering transition is that the 1D moments
grow significantly slower than the ones on the 2D layers, which is evidenced by
the persistent paramagnetic ESR signal below . Compared to typical
quasi-2D magnets, the ordering temperature of CuPO 0.2
is unusually low, showing that weakly coupled spins sandwiched between 2D
magnetic units effectively decouple these units and impede the long-range
ordering.Comment: 11 pages, 12 figures, 1 table; published version with few additional
citations added and misprints fixe
On the Nature and Shape of Tubulin Trails: Implications on Microtubule Self-Organization
Microtubules, major elements of the cell skeleton are, most of the time, well
organized in vivo, but they can also show self-organizing behaviors in time
and/or space in purified solutions in vitro. Theoretical studies and models
based on the concepts of collective dynamics in complex systems,
reaction-diffusion processes and emergent phenomena were proposed to explain
some of these behaviors. In the particular case of microtubule spatial
self-organization, it has been advanced that microtubules could behave like
ants, self-organizing by 'talking to each other' by way of hypothetic (because
never observed) concentrated chemical trails of tubulin that are expected to be
released by their disassembling ends. Deterministic models based on this idea
yielded indeed like-looking spatio-temporal self-organizing behaviors.
Nevertheless the question remains of whether microscopic tubulin trails
produced by individual or bundles of several microtubules are intense enough to
allow microtubule self-organization at a macroscopic level. In the present
work, by simulating the diffusion of tubulin in microtubule solutions at the
microscopic scale, we measure the shape and intensity of tubulin trails and
discuss about the assumption of microtubule self-organization due to the
production of chemical trails by disassembling microtubules. We show that the
tubulin trails produced by individual microtubules or small microtubule arrays
are very weak and not elongated even at very high reactive rates. Although the
variations of concentration due to such trails are not significant compared to
natural fluctuations of the concentration of tubuline in the chemical
environment, the study shows that heterogeneities of biochemical composition
can form due to microtubule disassembly. They could become significant when
produced by numerous microtubule ends located in the same place. Their possible
formation could play a role in certain conditions of reaction. In particular,
it gives a mesoscopic basis to explain the collective dynamics observed in
excitable microtubule solutions showing the propagation of concentration waves
of microtubules at the millimeter scale, although we doubt that individual
microtubules or bundles can behave like molecular ants
Dynamics of protein-protein encounter: a Langevin equation approach with reaction patches
We study the formation of protein-protein encounter complexes with a Langevin
equation approach that considers direct, steric and thermal forces. As three
model systems with distinctly different properties we consider the pairs
barnase:barstar, cytochrome c:cytochrome c peroxidase and p53:MDM2. In each
case, proteins are modeled either as spherical particles, as dipolar spheres or
as collection of several small beads with one dipole. Spherical reaction
patches are placed on the model proteins according to the known experimental
structures of the protein complexes. In the computer simulations, concentration
is varied by changing box size. Encounter is defined as overlap of the reaction
patches and the corresponding first passage times are recorded together with
the number of unsuccessful contacts before encounter. We find that encounter
frequency scales linearly with protein concentration, thus proving that our
microscopic model results in a well-defined macroscopic encounter rate. The
number of unsuccessful contacts before encounter decreases with increasing
encounter rate and ranges from 20-9000. For all three models, encounter rates
are obtained within one order of magnitude of the experimentally measured
association rates. Electrostatic steering enhances association up to 50-fold.
If diffusional encounter is dominant (p53:MDM2) or similarly important as
electrostatic steering (barnase:barstar), then encounter rate decreases with
decreasing patch radius. More detailed modeling of protein shapes decreases
encounter rates by 5-95 percent. Our study shows how generic principles of
protein-protein association are modulated by molecular features of the systems
under consideration. Moreover it allows us to assess different coarse-graining
strategies for the future modelling of the dynamics of large protein complexes
The role of malignant tissue on the thermal distribution of cancerous breast
The present work focuses on the integration of analytical and numerical strategies to investigate the thermal distribution of cancerous breasts. Coupled stationary bioheat transfer equations are considered for the glandular and heterogeneous tumor regions, which are characterized by different thermophysical properties. The cross-section of the cancerous breast is identified by a homogeneous glandular tissue that surrounds the heterogeneous tumor tissue, which is assumed to be a two-phase periodic composite with non-overlapping circular inclusions and a square lattice distribution, wherein the constituents exhibit isotropic thermal conductivity behavior. Asymptotic periodic homogenization method is used to find the effective properties in the heterogeneous region. The tissue effective thermal conductivities are computed analytically and then used in the homogenized model, which is solved numerically. Results are compared with appropriate experimental data reported in the literature. In particular, the tissue scale temperature profile agrees with experimental observations. Moreover, as a novelty result we find that the tumor volume fraction in the heterogeneous zone influences the breast surface temperature
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