Diffusion models for firing of a neuron with varying threshold

A stochastic model for the firing of a neuron with refractory properties is treated analytically. Refractory behavior is modeled by a threshold function θ(t) which is infinite immediately after the neuron fires, as well as during the absolute refractory period, and then decreases monotonically to the quiescent threshold level, θ_∞, during the relative refractory period. Using Wald's identity, input-output relations are derived analytically for the exponential threshold which has a time constant equal to the membrane time constant. A method for computing these relations for a general threshold is presented and is explicitly used for the general exponential threshold and the Hagiwara threshold, θ(t) = θ_∞e^α/t, where a is a constant.     

Evidence in vitro that hepatic lipase reduces the concentration of apolipoprotein A-I in rabbit high-density lipoproteins

Incubation of rabbit plasma in vitro with hepatic lipase resulted in the hydrolysis of triacylglycerol in high-density lipoproteins (HDL) and a reduction in HDL particle size. These changes were accompanied by a decrease in the concentration of apolipoprotein A-I (apo A-I) in the HDL. The loss of apo A-I was demonstrated independently by ultracentrifugation, size exclusion chromatography and gradient gel-immunoblot analysis. It was unrelated to hydrolysis of HDL phospholipids but did correlate with the reduction in HDL particle size. These studies suggest that the concentration of apo A-I in HDL may be influenced by factors which regulate the metabolism of HDL core lipid constituents.     

Impact of chlortetracycline on sequencing batch reactor performance for swine manure treatment

Treatment of aged (500 day, 4 °C stored) chlortetracycline (CTC; 0, 20, 40, 80 mg/L CTC)-amended swine manure using two cycle, 22 day stage anaerobic sequencing batch reactors (SBR) was assessed. Eighty milligrams per liter CTC treatment inhibited SBR treatment efficiencies, although total gas production was enhanced compared to the no-CTC treatment. The 20 and 40 mg/L CTC treatments resulted in either slight or no differences to SBR treatment efficiencies and microbial diversities compared to the no-CTC treatment, and were generally similar to no-CTC treatments upon completion of the first 22 day SBR cycle. All CTC treatments enhanced SBR gas generation, however CH₄ yields were lowest for the 80 mg/L CTC treatment (0.111 L CH₄/g tCOD) upon completion of the second SBR react cycle. After a 22 day acclimation period, the 80 mg/L CTC treatment inhibited methanogenesis due to acetate accumulation, and decreased microbial diversity and CH₄ yield compared to the no-CTC treatment.     

Priority effects within coinfected hosts can drive unexpected population‐scale patterns of parasite prevalence

Organisms are frequently coinfected by multiple parasite strains and species, and interactions between parasites within hosts are known to influence parasite prevalence and diversity, as well as epidemic timing. Importantly, interactions between coinfecting parasites can be affected by the order in which they infect hosts (i.e. within‐host priority effects). In this study, we use a single‐host, two‐pathogen, SI model with environmental transmission to explore how within‐host priority effects scale up to alter host population‐scale infection patterns. Specifically, we ask how parasite prevalence changes in the presence of different types of priority effects. We consider two scenarios without priority effects and four scenarios with priority effects where there is either an advantage or a disadvantage to being the first to infect in a coinfected host. Models without priority effects always predict negative relationships between the prevalences of both parasites. In contrast, models with priority effects can yield unimodal prevalence relationships where the prevalence of a focal parasite is minimized or maximized at intermediate prevalences of a coinfecting parasite. The mechanism behind this pattern is that as the prevalence of the coinfecting parasite increases, most infections of the focal parasite change from occurring as solo infections, to first arrival coinfections, to second arrival coinfections. The corresponding changes in parasite fitness as the focal parasite moves from one infection class to another then map to changes in focal parasite prevalence. Further, we found that even when parasites interact negatively within a host, they still can have positive prevalence relationships at the population scale. These results suggest that within‐host priority effects can change host population‐scale infection patterns in systematic (and initially counterintuitive) ways, and that taking them into account may improve disease forecasting in coinfected populations.     

Understanding variation in salamander ionomes: A nutrient balance approach

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DIDA: Distributed Indexing Dispatched Alignment

One essential application in bioinformatics that is affected by the high-throughput sequencing data deluge is the sequence alignment problem, where nucleotide or amino acid sequences are queried against targets to find regions of close similarity. When queries are too many and/or targets are too large, the alignment process becomes computationally challenging. This is usually addressed by preprocessing techniques, where the queries and/or targets are indexed for easy access while searching for matches. When the target is static, such as in an established reference genome, the cost of indexing is amortized by reusing the generated index. However, when the targets are non-static, such as contigs in the intermediate steps of a de novo assembly process, a new index must be computed for each run. To address such scalability problems, we present DIDA, a novel framework that distributes the indexing and alignment tasks into smaller subtasks over a cluster of compute nodes. It provides a workflow beyond the common practice of embarrassingly parallel implementations. DIDA is a cost-effective, scalable and modular framework for the sequence alignment problem in terms of memory usage and runtime. It can be employed in large-scale alignments to draft genomes and intermediate stages of de novo assembly runs. The DIDA source code, sample files and user manual are available through http://www.bcgsc.ca/platform/bioinfo/software/dida. The software is released under the British Columbia Cancer Agency License (BCCA), and is free for academic use.     

Pullulanase and Starch Synthase III Are Associated with Formation of Vitreous Endosperm in Quality Protein Maize

The opaque-2 (o2) mutation of maize increases lysine content, but the low seed density and soft texture of this type of mutant are undesirable. Lines with modifiers of the soft kernel phenotype (mo2) called “Quality Protein Maize” (QPM) have high lysine and kernel phenotypes similar to normal maize. Prior research indicated that the formation of vitreous endosperm in QPM might involve changes in starch granule structure. In this study, we focused on analysis of two starch biosynthetic enzymes that may influence kernel vitreousness. Analysis of recombinant inbred lines derived from a cross of W64Ao2 and K0326Y revealed that pullulanase activity had significant positive correlation with kernel vitreousness. We also found that decreased Starch Synthase III abundance may decrease the pullulanase activity and average glucan chain length given the same Zpu1 genotype. Therefore, Starch Synthase III could indirectly influence the kernel vitreousness by affecting pullulanase activity and coordinating with pullulanase to alter the glucan chain length distribution of amylopectin, resulting in different starch structural properties. The glucan chain length distribution had strong positive correlation with the polydispersity index of glucan chains, which was positively associated with the kernel vitreousness based on nonlinear regression analysis. Therefore, we propose that pullulanase and Starch Synthase III are two important factors responsible for the formation of the vitreous phenotype of QPM endosperms.