Analytic approximations for the broadening of the spectral lines of hydrogen-like ions

Broadband approximate expressions for calculating the broadening of the spectral lines of hydrogen-like ions in a multicomponent plasma are derived taking into account both the influence of the interaction between plasma particles on the distribution function of the plasma microfield and the effect of the microfield dynamics on the broadening of the central component of the spectral line. With the approximate expressions proposed, the calculation of the shape of a given spectral line of a certain ion in a plasma with a given ion composition requires only a few seconds of computer time. The approximate expressions provide a good computational accuracy not only for the central component of the spectral line but also for the spectral line wings.     

Microfield model of quasi-independent particles and nonideal plasma

An original model of a plasma microfield constructed from first principles is much more advantageous than the earlier ones. The validity of the model is confirmed by optical measurements. The thermodynamics of a gaseous plasma is qualitatively described by a new ionization equilibrium model in which the interaction between charged particles is accounted for by means of a self-consistent plasma microfield. Numerical simulations show that, in this new model, nonideal effects are insignificant even at high plasma densities, and there are no phase transitions in a gaseous plasma, a conclusion that agrees with experimental data. The model is tested against the popular models of nonideal plasma and the SESAM database.     

Maximum-entropy determination of self-association distribution functions; daunorubicin and ATP.

In the present paper we show how one can use the perturbation of some molecular optical property (for example circular dichroism or chemical shift) as a function of concentration to construct cluster distribution functions describing the self-association of molecules in solution. The optical data are first converted into data giving the variation of the average extent of clustering as a function of the total concentration and then, using straightforward thermodynamics, a set of moments of the cluster distribution function can be obtained. Utilizing the maximum-entropy method, the moments are then used to calculate approximate distribution functions, where the more moments that are used the better the approximation obtained. Given the probability distribution for clusters of different sizes one can then calculate the equilibrium constant for each stage of association. Thus one converts average degree of association into equilibrium constants without having to use any specific model. By this method one can clearly tell whether the equilibrium constants remain constant, increase, or decrease with the number of molecules in a cluster. We apply the method to literature data for two systems, namely daunorubicin, which has a strong tendency to cluster in solution, and Mg(ATP)(2-) which forms weaker clusters. We find that the successive equilibrium constants for adding a monomer to a cluster are approximately constant for daunorubicin but clearly decrease as a function of increasing cluster size for Mg(ATP)(2-).     

A program for the application of the radial distribution function to cluster analysis in cell biology

The radial distribution function g(r) is one measure of spatialpattern commonly used in statistical physics to analyze thestructure of liquids and has been used in several cellular systems.The graphs of the radial distribution function present threedifferent functional forms. The first form indicates a randomdistribution; in the second form the graph is characteristicof the cluster distribution; and the third type is characteristicof substantial order. The Funct_G program uses the coordinates(x,y) of each point on m photographs to calculate the radialdistribution function g(r) and produce a histogram to analyzegraphically this function and to define the distribution model.     

Ironing out the distribution of [2Fe-2S] motifs in ferrochelatases

Heme, a near ubiquitous cofactor, is synthesized by most organisms. The essential step of insertion of iron into the porphyrin macrocycle is mediated by the enzyme ferrochelatase. Several ferrochelatases have been characterized, and it has been experimentally shown that a fraction of them contain [2Fe-2S] clusters. It has been suggested that all metazoan ferrochelatases have such clusters, but among bacteria, these clusters have been most commonly identified in Actinobacteria and a few other bacteria. Despite this, the function of the [2Fe-2S] cluster remains undefined. With the large number of sequenced genomes currently available, we comprehensively assessed the distribution of putative [2Fe-2S] clusters throughout the ferrochelatase protein family. We discovered that while rare within the bacterial ferrochelatase family, this cluster is prevalent in a subset of phyla. Of note is that genomic data show that the cluster is not common in Actinobacteria, as is currently thought based on the small number of actinobacterial ferrochelatases experimentally examined. With available physiological data for each genome included, we identified a correlation between the presence of the microbial cluster and aerobic metabolism. Additionally, our analysis suggests that Firmicute ferrochelatases are the most ancient and evolutionarily preceded the Alphaproteobacterial precursor to eukaryotic mitochondria. These findings shed light on distribution and evolution of the [2Fe-2S] cluster in ferrochelatases and will aid in determining the function of the cluster in heme synthesis.     

Estimation of molecular averages and equilibrium fluctuations in lipid bilayer systems from the excess heat capacity function

It is demonstrated that the bilayer partition function can be numerically obtained from scanning calorimetric data without assuming a particular model for the gel-liquid crystalline transition. From this partition function, the enthalpy, entropy and volume changes accompanying the transition can be calculated. In the limit of very large systems, the method of the grand partition function allows calculation of cluster model distribution functions from which average sizes of gel and liquid-crystal clusters, cluster densities and equilibrium fluctuations are obtained. These results indicate that the main transition in phospholipid bilayers proceeds through the formation of clusters and that these clusters are not static domains but highly fluctuating entities. These fluctuations in cluster size are approximately equal to the average cluster size and give rise to localized density and volume fluctuations. The magnitude of these fluctuations is affected by the radius of curvature of the bilayer and by the addition of small molecular weight compounds to the system.     

A model for early death caused by radiation pneumonitis and pulmonary fibrosis after inhaling insoluble radioactive particles

Large radiation doses to the lung can cause early death from cardiopulmonary insufficiency resulting from radiation pneumonitis and pulmonary fibrosis. A model for early death following inhalation of insoluble radioactive particles is propose. The model is based on three assumptions: (1) early death results from damage to a cluster of cells from a large number of cell clusters at risk, (2) the dose that causes early death depends on how the radiation is delivered in time and (3) the cell clusters at risk to damage are equally sensitive ro radiation. Results from asymptotic theory of extreme values, along with biophysical considerations, suggest that the cumultive distribution function for the absorbed radiation dose to the production of pulmonary injury sufficient to cause early death is best estimated by the third asymptotic distribution without a threshold. This distribution function is identical to the Weibull cumulative distribution function. Data for Beagle dogs after inhaling relatively insoluble forms of alpha- or beta-gamma-emitting particles are shown to support the Weibull model.     

Temperature and heat production patterns inside organism clusters

Clustering of organisms under cold air temperature conditions is modelled with a finite-difference method. Metabolic functions of temperature are used to simulate completely ectothermic, completely endothermic, and other organisms. To adequately match real conditions, the core temperature is kept constant at a high level, while the periphery of the organism cluster is assigned a lower temperature representing the cold conditions under which clustering is observed for organisms. The numerical model reasonably predicts the observed temperature distribution in honeybee clusters. The results do not support suggestions that organisms could overheat in the core of a cluster if they do not use thermoregulatory mechanisms to cool down. Endothermic organisms are not as efficient as ectothermic ones in heating a cluster core temperature to a given level. The general ectothermic metabolic rate function exhibited one of the highest efficiencies for heating the cluster.     

Microtubule dynamics and the regulation by microtubule-associated proteins (MAPs).

Individual microtubules (MTs) repeat alternating phases of polymerization and depolymerization, a process known as "dynamic instability." The dynamic instability is regulated by various protein factors according to the requirement of cellular conditions. Heat-stable MAPs regulate the dynamic instability by increasing the rescue frequency. To explore the influence of MAP2, a heat-stable MAPs abundant in neuron, on in vitro MT dynamics, the distribution of MAP2 on individual MTs was correlated with the dynamic phase changes of the same MTs by optical microscopy. MAP2 distributed inhomogeneously along the length of MTs by forming high-density regions, clusters. Stops of depolymerization were always found to occur only at the cluster sites. Every cluster did not stop depolymerization, but depolymerization did always stop at a cluster site. We suggest that mode of distribution along MT is an important factor of the function of heat-stable MAPs.     

广东爬行动物地理分布的聚类分析

对广东省83种爬行动物的地理分布进行了聚类研究。将各种爬行动物在广东4个动物地理省(粤北、粤东、粤西、沿海)分布的有或无作为二元性状,用联合系数来表征每两个动物地理省爬行动物组成的相似程度,以类平均法进行聚类分析,结果表明爬行类在广东各动物地理省的分布受地形明显影响,论述了广东省爬行动物地理分布的特点,并对聚类结果与动物地理区划进行了比较。     

Diagnostics of a current-sheet plasma with the use of helium spectral lines with forbidden components

Results are presented from the first measurements of the profiles of the HeI 447.1-nm and HeI 492.2-nm neutral helium spectral lines emitted by the plasma of a current sheet formed in the CS-3D experimental device. A theoretical analysis of these profiles is performed with the model microfield method. A comparison of the theoretical and experimental profiles shows that the electron density in the peripheral regions of the current sheets amounts to (1.0–2.0)×10¹⁵ cm^?3.     

The phylogeny of persistence in DNA

We continue our study, Poland [Biophysical Chemistry 110 (2004) 59-2], of the distribution of C or G (C-G for short) in the DNA of select organisms, in particular, the tendency for C-G to cluster on all scales with respect to the number of bases considered. We previously found that if we counted the number of C-G bases in consecutive, nonoverlapping boxes containing a total of m bases, then the width of the distribution function describing how many C-G bases are in a box increases with respect to m dramatically relative to the width expected for a random distribution. The relative width of the C-G composition distribution function was found to vary accurately as a power law with respect to m, the size of the box, over a very wide range of m values. We express the power law in terms of a characteristic exponent gamma, that is, the relative widths of the distributions vary as m(gamma). The enhanced relative width of the distribution functions is a direct consequence of the tendency for boxes of similar composition to follow one another. This tendency represents persistence in composition from box to box and hence we refer to gamma as the persistence exponent. The occurrence of a power law means that the tendency for C-G to cluster is present on all scales of sequence length (box size) up to the total length of the chromosome which for bacteria is the entire genome. The persistence exponent gamma that characterizes the power law is thus an important parameter describing the distribution of C-G on all scales from individual base pairs up to the total length of the DNA sample considered. In the present paper, we determine the characteristic exponent gamma and the associated fractal dimension of DNA samples for a selection of species representing all of the major types of organism, that is, we explore the phylogeny of the exponent gamma. Here we treat six prokaryotes and six eukaryotes which, together with the species we have previously treated, brings the total number of species we have examined to 15. We find the power law form for the C-G distribution for all of the species treated and hence this behavior seems to be ubiquitous. The values of the characteristic exponent gamma that we find tend to cluster around the value gamma=0.20 with no obvious pattern with respect to phylogeny. The extreme values that we obtain are gamma=0.057 (yeast) and gamma=0.386 (human). We conclude by showing that the persistence of C-G clustering on the scale of the length of a chromosome is dramatically illustrated by interpreting the C-G distribution as a random walk.     

Positioning of chemosensory clusters in E. coli and its relation to cell division

Chemotaxis receptors and associated signalling proteins in Escherichia coli form clusters that consist of thousands of molecules and are the largest native protein complexes described to date in bacteria. Clusters are located at the cell poles and laterally along the cell body, and play an important role in signal transduction. Much work has been done to study the structure and function of receptor clusters, but the significance of their positioning and the underlying mechanisms are not understood. Here, we used fluorescence imaging to study cluster distribution and follow cluster dynamics during cell growth. Our data show that lateral clusters localise to specific periodic positions along the cell body, which mark future division sites and are involved in the localisation of the replication machinery. The chemoreceptor cluster positioning is thus intricately related to the overall structure and division of an E. coli cell.     

Role of H(abc) domain in membrane trafficking and targeting of syntaxin 1A

Membrane syntaxin plays essential roles in exocytosis in eukaryotic cells. The conservative H(abc) domain in plasma membrane syntaxins implies important roles for syntaxin targeting and function. Our previous study showed H(abc) domain was necessary for the trafficking and cluster distribution of syntaxin 1A on the plasma membrane. Here we identified which of the three domains (H(a), H(b) and H(c)) was essential for Stx1A trafficking and clustering. We found that, in INS-1 cells, the mutant truncated with either H(a), H(b) or H(c) domain could be sorted to the cell surface by a different mechanism compared to that of whole H(abc) truncated mutant. In contrast to wild type Stx1A, none of the mutants showed cluster distribution at the functional sites, suggesting that the physiological localization of Stx1A relies on intact H(abc) domain. Furthermore Munc18-1 is found not to be essential for Stx1A cluster distribution, despite important role in stabilizing membrane delivery of Stx1A.     

The role of mitochondria in anchoring dynein to the cell cortex extends beyond clustering the anchor protein

Organelle distribution is regulated over the course of the cell cycle to ensure that each of the cells produced at the completion of division inherits a full complement of organelles. In yeast, the protein Num1 functions in the positioning and inheritance of two essential organelles, mitochondria and the nucleus. Specifically, Num1 anchors mitochondria as well as dynein to the cell cortex, and this anchoring activity is required for proper mitochondrial distribution and dynein-mediated nuclear inheritance. The assembly of Num1 into clusters at the plasma membrane is critical for both of its anchoring functions. We have previously shown that mitochondria drive the assembly of Num1 clusters and that these mitochondria-assembled Num1 clusters serve as cortical attachment sites for dynein. Here we further examine the role for mitochondria in dynein anchoring. Using a GFP-αGFP nanobody targeting system, we synthetically clustered Num1 on eisosomes to bypass the requirement for mitochondria in Num1 cluster formation. Utilizing this system, we found that mitochondria positively impact the ability of synthetically clustered Num1 to anchor dynein and support dynein function even when mitochondria are no longer required for cluster formation. Thus, the role of mitochondria in regulating dynein function extends beyond simply concentrating Num1; mitochondria likely promote an arrangement of Num1 within a cluster that is competent for dynein anchoring. This functional dependency between mitochondrial and nuclear positioning pathways likely serves as a mechanism to order and integrate major cellular organization systems over the course of the cell cycle.     

Exclusion of repetitive DNA elements from gnathostome Hox clusters

Despite their homology and analogous function, the Hox gene clusters of vertebrates and invertebrates are subject to different constraints on their structural organization. This is demonstrated by a drastically different distribution of repetitive DNA elements in the Hox cluster regions. While gnathostomes have a strong tendency to exclude repetitive DNA elements from the inside of their Hox clusters, no such trend can be detected in the Hox gene clusters of protostomes. Repeats "invade" the gnathostome Hox clusters from the 5' and 3' ends while the core of the clusters remains virtually free of repetitive DNA. This invasion appears to be correlated with relaxed constraints associated with gene loss after cluster duplications.     

Self Assembly of Bilayers in a Lattice Model of Amphiphile and Solvent Systems

The results of a Metropolis Monte Carlo simulation of a three dimensional lattice model of an amphiphile and solvent mixture are presented. In the model each amphiphile molecule is represented as a connected chain of lattice sites with one site representing the head and the remaining chain sites representing the tail of the molecule. The remaining sites on the lattice represent solvent molecules. The amphiphiles interact through a nearest neighbour potential which includes head-solvent and tail-solvent interactions. No prior assumption is made about the structures which may be observed.

The cluster size distribution and cluster structure is studied as a function of temperature and head-solvent interaction. If the tail-solvent interaction is solvophobic and the head-solvent interaction is solvophilic, a micellar region is observed in the phase diagram. For sufficiently solvophilic head-solvent interactions the low temperature phase exhibits self assembly into castellated bilayer structures.     

Plant nutrient-acquisition strategies change with soil age

Nitrogen (N) tends to limit plant productivity on young soils; phosphorus (P) becomes increasingly limiting in ancient soils because it gradually disappears through leaching and erosion. Plant traits that are regarded as adaptations to N- and P-limited conditions include mycorrhizas and cluster roots. Mycorrhizas 'scavenge' P from solution or 'mine' insoluble organic N. Cluster roots function in severely P-impoverished landscapes, 'mining' P fixed as insoluble inorganic phosphates. The 'scavenging' and 'mining' strategies of mycorrhizal species without and non-mycorrhizal species with cluster roots, respectively, allow functioning on soils that differ markedly in P availability. Based on recent advances in our understanding of these contrasting strategies of nutrient acquisition, we provide an explanation for the distribution of mycorrhizal species on less P-impoverished soils, and for why, globally, cluster-bearing species dominate on severely P-impoverished, ancient soils, where P sensitivity is relatively common.     

The major chemotaxis gene cluster of Rhizobium leguminosarum bv. viciae is essential for competitive nodulation

Rhizobium leguminosarum biovar viciae strain 3841 is a motile alpha-proteobacterium that can establish a nitrogen-fixing symbiosis within the roots of pea plants. In order to determine the contribution of chemotaxis to the lifestyle of R. leguminosarum, we have characterized the function of two chemotaxis gene clusters (che1 and che2) in controlling motility behaviour. We have found that both chemotaxis gene clusters modulate the motility swimming bias of R. leguminosarum cells and that the che1 cluster is the major pathway controlling swimming bias and chemotaxis. The che2 cluster also contributes to swimming bias, but has a minor effect on chemotaxis. Using competitive nodulation assays, we have demonstrated that a functional che1 cluster, but not the che2 cluster, promotes competitive nodulation of the peas. This finding implies that the environmental cue(s) triggering chemotaxis of R. leguminosarum bv. viciae cells towards the roots of pea and facilitating colonization are likely to be processed through the che1 cluster despite the contribution of both che clusters to swimming behaviour. A phylogenetic analysis of the distribution of che1 and che2 orthologues in the alpha-proteobacteria together with our results allow us to propose that che1 homologues are major controllers of chemotaxis and host association in the Rhizobiaceae.     

The Interplay of Structural and Cellular Biophysics Controls Clustering of Multivalent Molecules

Dynamic molecular clusters are assembled through weak multivalent interactions and are platforms for cellular functions, especially receptor-mediated signaling. Clustering is also a prerequisite for liquid-liquid phase separation. It is not well understood, however, how molecular structure and cellular organization control clustering. Using coarse-grained kinetic Langevin dynamics, we performed computational experiments on a prototypical ternary system modeled after membrane-bound nephrin, the adaptor Nck1, and the actin nucleation promoting factor NWASP. Steady-state cluster size distributions favored stoichiometries that optimized binding (stoichiometry matching) but still were quite broad. At high concentrations, the system can be driven beyond the saturation boundary such that cluster size is limited only by the number of available molecules. This behavior would be predictive of phase separation. Domains close to binding sites sterically inhibited clustering much less than terminal domains because the latter effectively restrict access to the cluster interior. Increased flexibility of interacting molecules diminished clustering by shielding binding sites within compact conformations. Membrane association of nephrin increased the cluster size distribution in a density-dependent manner. These properties provide insights into how molecular ensembles function to localize and amplify cell signaling.