A study of the diffusion of compact particles in polymer solutions using quasi-elastic light scattering

This paper describes an investigation, using quasi-elastic light scattering, of the diffusion of polystyrene spheres through solutions of dextran. The diffusion coefficient, D, of the spheres is shown to vary inversely with the volume fraction, φ, of dextran according to $\text{D =}\text{D}{}_0\text{(1 + νφ + κφ}{}^2\text{)}$. Changes in the molecular weight of dextran are shown to reflect changes in the macromolecular shape parameter, ν, and the interaction parameter, κ. This result differs from previous studies which suggested an $\text{exp}\text{(?}\text{B}\text{φ}{}^{\mathrm{<mtext>1</mtext><mtext>2</mtext>}}\text{)}$ dependence and no molecular weight dependence [8].     

HIV Treatment as Prevention: Optimising the Impact of Expanded HIV Treatment Programmes

Until now, decisions about how to allocate ART have largely been based on maximising the therapeutic benefit of ART for patients. Since the results of the HPTN 052 study showed efficacy of antiretroviral therapy (ART) in preventing HIV transmission, there has been increased interest in the benefits of ART not only as treatment, but also in prevention. Resources for expanding ART in the short term may be limited, so the question is how to generate the most prevention benefit from realistic potential increases in the availability of ART. Although not a formal systematic review, here we review different ways in which access to ART could be expanded by prioritising access to particular groups based on clinical or behavioural factors. For each group we consider (i) the clinical and epidemiological benefits, (ii) the potential feasibility, acceptability, and equity, and (iii) the affordability and cost-effectiveness of prioritising ART access for that group. In re-evaluating the allocation of ART in light of the new data about ART preventing transmission, the goal should be to create policies that maximise epidemiological and clinical benefit while still being feasible, affordable, acceptable, and equitable.     

A Trade-Off between Sample Complexity and Computational Complexity in Learning Boolean Networks from Time-Series Data

A key problem in molecular biology is to infer regulatory relationships between genes from expression data. This paper studies a simplified model of such inference problems in which one or more Boolean variables, modeling, for example, the expression levels of genes, each depend deterministically on a small but unknown subset of a large number of Boolean input variables. Our model assumes that the expression data comprises a time series, in which successive samples may be correlated. We provide bounds on the expected amount of data needed to infer the correct relationships between output and input variables. These bounds improve and generalize previous results for Boolean network inference and continuous-time switching network inference. Although the computational problem is intractable in general, we describe a fixed-parameter tractable algorithm that is guaranteed to provide at least a partial solution to the problem. Most interestingly, both the sample complexity and computational complexity of the problem depend on the strength of correlations between successive samples in the time series but in opposing ways. Uncorrelated samples minimize the total number of samples needed while maximizing computational complexity; a strong correlation between successive samples has the opposite effect. This observation has implications for the design of experiments for measuring gene expression.     

Aquatic insect emergence in two Great Lakes marshes

This study determined total number, biomass, taxa, and seasonal occurrence of adult aquatic insects emerging from four vegetation zones in one diked and one undiked freshwater coastal marsh on hypereutrophic lower Green Bay, Lake Michigan, USA during the summer of 1984. Floating box traps were placed in open water, sparse emergent, dense emergent, and wet meadow vegetation zones in each marsh. Insects were collected during 20 24-hour periods, each four days apart, from June 11 to August 26. Two-way ANOVA was used to test differences in number and biomass of insects between marshes and among vegetation zones. Polynomial regression was used to evaluate seasonal emergence patterns. More insects, insect biomass, and insect taxa were found in the diked marsh, especially during the first half of the sampling period. Damselflies were much more abundant in the diked marsh. Most insects and insect biomass were found in the sparse emergent vegetation zone of both marshes. The emerging insect community in the diked marsh appears enhanced by its separation from the hypereutrophic and turbid waters of lower Green Bay.