A label-free nanoparticle aggregation assay for protein complex/aggregate detection and study

The detection, analysis, and understanding of protein complexes/aggregates and their formation process are extremely important for biomolecular research, diagnosis, and biopharmaceutical development. Unfortunately, techniques that can be used conveniently for protein complex/aggregate detection and analysis are very limited. Using gold nanoparticle immunoprobes coupled with dynamic light scattering (DLS), we developed a label-free nanoparticle aggregation immunoassay (NanoDLSay) for protein aggregate detection and study. Glyceraldehyde 3-phosphate dehydrogenase (GAPDH), a protein target used routinely in Western blot as a loading control, is demonstrated here as an example. Through this study, we discovered that GAPDH has a strong tendency to form large aggregates in certain buffer solutions at a concentration range of 10-25 μg/ml. The strong light scattering property of gold nanoparticles immunoprobes greatly enhanced the sensitivity of the dynamic light scattering for protein complex/aggregate detection. In contrast to fluorescence techniques for protein complex and aggregation study, the protein targets do not need to be labeled with fluorescent probe molecules in NanoDLSay. NanoDLSay is a very convenient and sensitive tool for protein complex/aggregate detection and study.     

Regret‐Regression for Optimal Dynamic Treatment Regimes

Summary We consider optimal dynamic treatment regime determination in practice. Model building, checking, and comparison have had little or no attention so far in this literature. Motivated by an application on optimal dosage of anticoagulants, we propose a modeling and estimation strategy that incorporates the regret functions of Murphy (2003, Journal of the Royal Statistical Society, Series B 65, 331–366) into a regression model for observed responses. Estimation is quick and diagnostics are available, meaning a variety of candidate models can be compared. The method is illustrated using simulation and the anticoagulation application.     

沈阳城市绿地系统的景观生态评价

运用景观生态学原理和方法,选取多样性指数、均匀度指数、破碎度指数、分离度指数、分维度指数、连通性指数等8个景观格局指数对沈阳市城市绿地系统的景观格局进行分析。结果表明:沈阳城市绿地景观总体表现为绿地率较低,绿地斑块分布不均衡,景观结构不合理,破碎度较高,分维数较低,景观类型较齐全,均匀度较低,景观分离度较小。针对存在的问题,提出了沈阳城市绿地景观生态规划建议。     

Dynamic Model of the Process of Protein Synthesis in Eukaryotic Cells

Protein synthesis is the final step of gene expression in all cells. In order to understand the regulation of this process, it is important to have an accurate model that incorporates the regulatory steps. The model presented in this paper is composed of set of differential equations which describe the dynamics of the initiation process and its control, as well as peptide elongation, starting with the amino acids available for peptide creation. A novel approach for modeling the elongation process permits useful prediction of protein production and consumption of energy and amino acids, as well as ribosome loading rate and ribosome spacing on the mRNA. An erratum to this article can be found at     

Chromatin reorganization and endogenous auxin/cytokinin dynamic activity during somatic embryogenesis of cultured cotton cell

We conducted a systematic assessment and comparative study on the biochemical and cellular characteristics of cultured cotton cells during the entire process of somatic embryogenesis (SE). All staged cultures were widely investigated in this assay. Cell and tissue ectogenesis manipulation combined with flow cytometry (FCM) was employed to cellular study during the whole totipotency process of dedifferentiation and redifferentiation. We identified two phases of chromatin decondensation during the dedifferentiation and redifferentiation. At the same time, sharp increase in the ratio of indoleacetic acid (IAA), isopentenyladenosine group (iPAs) at the same stage of cell dedifferentiation and redifferentiation process serve as distinct biochemical maker of dedifferentiation and SE initiation with the unique feature. Our results suggest the two phases of chromatin reorganization associated with endogenous auxin/cytokinin dynamic activity may underlie dedifferentiation and redifferentiation during the entire SE process in cotton.     

Heterogeneity in dynamic species abundance models: the selective effect of extinction processes

There is often large variation in traits across the species of a community. In particular, variation in life history traits affecting population dynamics is likely to affect the species abundance distribution. Applying a dynamic and heterogeneous species abundance model we study how differences in extinction time for species in a community act as a force changing the distribution of dynamic parameters across species. This process may generate communities that are more heterogeneous then the heterogeneity measured as the species enter the community. Analytical results for some versions of the lognormal and gamma species abundance model are given as exemplifications of this process, together with stochastic simulations demonstrating the temporal changes in number of species and community heterogeneity through time.     

Simulating the effects of N availability, straw particle size and location in soil on C and N mineralization

Predicting the C and N mineralization of straw added to soil is important for forecasting subsequent soil N availability during and between crop growth cycles. The decomposition module of the STICS model, parameterized under optimal conditions, was used to predict straw decomposition in sub-optimal conditions, i.e. when contact between soil and residue was poor (due to large size residues or surface placement) or when mineral N availability was restricted. The data used in the simulations were obtained from published studies of effects of residue size, location and N availability on C and N mineralization from straw under controlled laboratory conditions. We selected studies in which the dynamics of C and N mineralization were measured simultaneously. The dynamics of straw mineralization could be well predicted by the model under optimal conditions with standard parameter values as derived from measured C/N ratios of the residues, but not under sub-optimal conditions which required a new parameterization. A good fit could be obtained on these treatments by a marked reduction in the rate constants of residue and microbial biomass decomposition and a marked increase in the microbial biomass C/N ratio. Our results show the need to include in decomposition models routines for simulating effects of spatial heterogeneity of residue distribution, different particle sizes and limiting N availability.     

A critical evaluation of the conformational requirements of fusogenic peptides in membranes

It is generally assumed that fusogenic peptides would require a certain conformation, which triggers or participates in the rate-determining step of membrane fusion. Previous structure analyses of the viral fusion peptide from gp41 of HIV-1 have yielded contradictory results, showing either an α-helical or a β-stranded conformation under different conditions. To find out whether either of these conformations is relevant in the actual fusion process, we have placed sterically demanding substitutions into the fusion peptide FP23 to prevent or partially inhibit folding and self-assembly. A single substitution of either D- or L-CF₃-phenylglycine was introduced in different positions of the sequence, and the capability of these peptide analogues to fuse large unilamellar vesicles was monitored by lipid mixing and dynamic light scattering. If fusion proceeds via a β-stranded oligomer, then the D- and L-epimers are expected to differ systematically in their activity, since the D-epimers should be unable to form β-structures due to sterical hindrance. If an α-helical conformation is relevant for fusion, then the D-epimers would be slightly disfavoured compared to the L-forms, hence a small systematic difference in fusion activity should be observed. Interestingly, we find that (1) all D- and L-epimers are fusogenically active, though to different extents compared to the wild type, and – most importantly – (ii) there is no systematic preference for either the D- or L-forms. We therefore suggest that a well-structured α-helical peptide conformation or a β-stranded oligomeric assembly can be excluded as the rate-determining state. Instead, fusion appears to involve conformationally disordered peptides with a pronounced structural plasticity. Dedicated to Prof. K. Arnold on the occasion of this 65th birthday.     

Factors influencing route choice by avian migrants: a dynamic programming model of Pacific brant migration

We used stochastic dynamic programming to investigate a spectacular migration strategy in the black brant Branta bernicla nigricans, a species of goose. Black brant migration is well suited for theoretical analysis since there are a number of existing strategies that easily can be compared. In early autumn, almost the entire population of the black brant gathers at Izembek Lagoon on the Alaska Peninsula to stage and refuel before the southward migration. There are at least three distinct strategies, with most geese making a spectacular direct migration more than 5000km across the Gulf of Alaska to their wintering grounds in southern Baja California or mainland Mexico. This is a potentially dangerous strategy since foraging is not possible during the overseas passage. Some individuals instead use shorter flights to make a detour along the coast, a longer route that all individuals use for northwards migration in spring. Since flight costs accelerate with increasing body mass, migration by short flights is energetically cheaper than long-distance flights. A small but increasing part of the population has recently begun to winter at Izembek. We investigated this migration under two different suppositions using a dynamic state variable model. First, if the geese are free to make a strategic choice, under what assumptions should they prefer direct migration and under what assumptions should they prefer detour migration/winter residency? Second, provided that the dominating direct migration strategy is optimal, what conditions will force the geese to go for detour migration/winter residency? In the second case the geese may try to follow an optimal direct migration strategy, but stochastic events may force them to choose a suboptimal policy. We also simulated possible effects of global warming. The model suggests that the fuel level at arrival in Izembek and fuel gain rates are key factors and that tail winds must have been reliable in the past, otherwise direct migration could not have evolved. It also suggests that a change to milder winters may promote an unexpectedly abrupt change from long-distance to short-distance migration or winter residency. Finally, it produced a number of predictions that might be testable in the field.     

Heterogeneous communities with lognormal species abundance distribution: Species-area curves and sustainability

Heterogeneous species abundance models are models in which the dynamics differ between species, described by variation among parameters defining the dynamics. Using a dynamic and heterogeneous species abundance model generating the lognormal species abundance distribution it is first shown that different degrees of heterogeneity may result in equivalent species abundance distributions. An alternative to Preston's canonical lognormal model is defined by assuming that reduction in resources, for example reduction in available area, increases the density regulation of each species. This leads to species-individual curves and species-area curves that are approximately linear in a double logarithmic plot. Preston's canonical parameter gamma varies little along these curves and takes values in the neighborhood of one. Quite remarkably, the curves, which define the sensitivity of the community to area reductions, are independent of the heterogeneity among species for this model. As a consequence, the curves can be estimated from a single sample from the community using the Poisson lognormal distribution. It is shown how to perform sensitivity analysis with respect to over-dispersion in sampling relative to the Poisson distribution as well as sampling intensity, that is, the fraction of the community sampled. The method is exemplified by analyzing three simulated data sets.