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How cells establish and maintain a well-defined size is a fundamental question of cell biology. Here we investigated to what extent the microtubule cytoskeleton can set a predefined cell size, independent of an enclosing cell membrane. We used electropulse-induced cell fusion to form giant multinuclear cells of the social amoeba Dictyostelium discoideum. Based on dual-color confocal imaging of cells that expressed fluorescent markers for the cell nucleus and the microtubules, we determined the subcellular distributions of nuclei and centrosomes in the giant cells. Our two- and three-dimensional imaging results showed that the positions of nuclei in giant cells do not fall onto a regular lattice. However, a comparison with model predictions for random positioning showed that the subcellular arrangement of nuclei maintains a low but still detectable degree of ordering. This can be explained by the steric requirements of the microtubule cytoskeleton, as confirmed by the effect of a microtubule degrading drug.
Massive stars, at least similar to 10 times more massive than the Sun, have two key properties that make them the main drivers of evolution of star clusters, galaxies, and the Universe as a whole. On the one hand, the outer layers of massive stars are so hot that they produce most of the ionizing ultraviolet radiation of galaxies; in fact, the first massive stars helped to re-ionize the Universe after its Dark Ages. Another important property of massive stars are the strong stellar winds and outflows they produce. This mass loss, and finally the explosion of a massive star as a supernova or a gamma-ray burst, provide a significant input of mechanical and radiative energy into the interstellar space. These two properties together make massive stars one of the most important cosmic engines: they trigger the star formation and enrich the interstellar medium with heavy elements, that ultimately leads to formation of Earth-like rocky planets and the development of complex life. The study of massive star winds is thus a truly multidisciplinary field and has a wide impact on different areas of astronomy. In recent years observational and theoretical evidences have been growing that these winds are not smooth and homogeneous as previously assumed, but rather populated by dense "clumps". The presence of these structures dramatically affects the mass loss rates derived from the study of stellar winds. Clump properties in isolated stars are nowadays inferred mostly through indirect methods (i.e., spectroscopic observations of line profiles in various wavelength regimes, and their analysis based on tailored, inhomogeneous wind models). The limited characterization of the clump physical properties (mass, size) obtained so far have led to large uncertainties in the mass loss rates from massive stars. Such uncertainties limit our understanding of the role of massive star winds in galactic and cosmic evolution. Supergiant high mass X-ray binaries (SgXBs) are among the brightest X-ray sources in the sky. A large number of them consist of a neutron star accreting from the wind of a massive companion and producing a powerful X-ray source. The characteristics of the stellar wind together with the complex interactions between the compact object and the donor star determine the observed X-ray output from all these systems. Consequently, the use of SgXBs for studies of massive stars is only possible when the physics of the stellar winds, the compact objects, and accretion mechanisms are combined together and confronted with observations. This detailed review summarises the current knowledge on the theory and observations of winds from massive stars, as well as on observations and accretion processes in wind-fed high mass X-ray binaries. The aim is to combine in the near future all available theoretical diagnostics and observational measurements to achieve a unified picture of massive star winds in isolated objects and in binary systems.
The linear Boltzmann equation approach is generalized to describe fractional superdiffusive transport of the Levy walk type in external force fields. The time distribution between scattering events is assumed to have a finite mean value and infinite variance. It is completely characterized by the two scattering rates, one fractional and a normal one, which defines also the mean scattering rate. We formulate a general fractional linear Boltzmann equation approach and exemplify it with a particularly simple case of the Bohm and Gross scattering integral leading to a fractional generalization of the Bhatnagar, Gross and Krook kinetic equation. Here, at each scattering event the particle velocity is completely randomized and takes a value from equilibrium Maxwell distribution at a given fixed temperature. We show that the retardation effects are indispensable even in the limit of infinite mean scattering rate and argue that this novel fractional kinetic equation provides a viable alternative to the fractional Kramers-Fokker-Planck (KFP) equation by Barkai and Silbey and its generalization by Friedrich et al. based on the picture of divergent mean time between scattering events. The case of divergent mean time is also discussed at length and compared with the earlier results obtained within the fractional KFP. Also a phenomenological fractional BGK equation without retardation effects is proposed in the limit of infinite scattering rates. It cannot be, however, rigorously derived from a scattering model, being rather clever postulated. It this respect, this retardationless equation is similar to the fractional KFP by Barkai and Silbey. However, it corresponds to the opposite, much more physical limit and, therefore, also presents a viable alternative.
We present the PINE (Plasma density in the Inner magnetosphere Neural network‐based Empirical) model ‐ a new empirical model for reconstructing the global dynamics of the cold plasma density distribution based only on solar wind data and geomagnetic indices. Utilizing the density database obtained using the NURD (Neural‐network‐based Upper hybrid Resonance Determination) algorithm for the period of 1 October 2012 to 1 July 2016, in conjunction with solar wind data and geomagnetic indices, we develop a neural network model that is capable of globally reconstructing the dynamics of the cold plasma density distribution for 2≤L≤6 and all local times. We validate and test the model by measuring its performance on independent data sets withheld from the training set and by comparing the model‐predicted global evolution with global images of He+ distribution in the Earth's plasmasphere from the IMAGE Extreme UltraViolet (EUV) instrument. We identify the parameters that best quantify the plasmasphere dynamics by training and comparing multiple neural networks with different combinations of input parameters (geomagnetic indices, solar wind data, and different durations of their time history). The optimal model is based on the 96 h time history of Kp, AE, SYM‐H, and F10.7 indices. The model successfully reproduces erosion of the plasmasphere on the nightside and plume formation and evolution. We demonstrate results of both local and global plasma density reconstruction. This study illustrates how global dynamics can be reconstructed from local in situ observations by using machine learning techniques.
We present an effective dynamical model for the onset of bacterial bioluminescence, one of the most studied quorum sensing-mediated traits. Our model is built upon simple equations that describe the growth of the bacterial colony, the production and accumulation of autoinducer signal molecules, their sensing within bacterial cells, and the ensuing quorum activation mechanism that triggers bioluminescent emission. The model is directly tested to quantitatively reproduce the experimental distributions of photon emission times, previously measured for bacterial colonies of Vibrio jasicida, a luminescent bacterium belonging to the Harveyi clade, growing in a highly drying environment. A distinctive and novel feature of the proposed model is bioluminescence ‘quenching’ after a given time elapsed from activation. Using an advanced fitting procedure based on the simulated annealing algorithm, we are able to infer from the experimental observations the biochemical parameters used in the model. Such parameters are in good agreement with the literature data. As a further result, we find that, at least in our experimental conditions, light emission in bioluminescent bacteria appears to originate from a subtle balance between colony growth and quorum activation due to autoinducers diffusion, with the two phenomena occurring on the same time scale. This finding is consistent with a negative feedback mechanism previously reported for Vibrio harveyi.
In this Letter, we study the role of the donor:acceptor interface nanostructure upon charge separation and recombination in organic photovoltaic devices and blend films, using mixtures of PBTTT and two different fullerene derivatives (PC70BM and ICTA) as models for intercalated and nonintercalated morphologies, respectively. Thermodynamic simulations show that while the completely intercalated system exhibits a large free-energy barrier for charge separation, this barrier is significantly lower in the nonintercalated system and almost vanishes when energetic disorder is included in the model. Despite these differences, both femtosecond-resolved transient absorption spectroscopy (TAS) and time-delayed collection field (TDCF) exhibit extensive first-order losses in both systems, suggesting that geminate pairs are the primary product of photoexcitation. In contrast, the system that comprises a combination of fully intercalated polymer:fullerene areas and fullerene-aggregated domains (1:4 PBTTT:PC70BM) is the only one that shows slow, second-order recombination of free charges, resulting in devices with an overall higher short-circuit current and fill factor. This study therefore provides a novel consideration of the role of the interfacial nanostructure and the nature of bound charges and their impact upon charge generation and recombination.
The lateral diffusion of embedded proteins along lipid membranes in protein-poor conditions has been successfully described in terms of the Saffman-Delbruck (SD) model, which predicts that the protein diffusion coefficient D is weakly dependent on its radius R as D proportional to ln(1/R). However, instead of being protein-poor, native cell membranes are extremely crowded with proteins. On the basis of extensive molecular simulations, we here demonstrate that protein crowding of the membrane at physiological levels leads to deviations from the SD relation and to the emergence of a stronger Stokes-like dependence D proportional to 1/R. We propose that this 1/R law mainly arises due to geometrical factors: smaller proteins are able to avoid confinement effects much better than their larger counterparts. The results highlight that the lateral dynamics in the crowded setting found in native membranes is radically different from protein-poor conditions and plays a significant role in formation of functional multiprotein complexes.
We address the generic problem of random search for a point-like target on a line. Using the measures of search reliability and efficiency to quantify the random search quality, we compare Brownian search with Levy search based on long-tailed jump length distributions. We then compare these results with a search process combined of two different long-tailed jump length distributions. Moreover, we study the case of multiple targets located by a Levy searcher.
How different are the properties of critical adsorption of polyampholytes and polyelectrolytes onto charged surfaces? How important are the details of polyampholyte charge distribution on the onset of critical adsorption transition? What are the scaling relations governing the dependence of critical surface charge density on salt concentration in the surrounding solution? Here, we employ Metropolis Monte Carlo simulations and uncover the scaling relations for critical adsorption for quenched periodic and random charge distributions along the polyampholyte chains. We also evaluate and discuss the dependence of the adsorbed layer width on solution salinity and details of the charge distribution. We contrast our findings to the known results for polyelectrolyte adsorption onto oppositely charged surfaces, in particular, their dependence on electrolyte concentration.