Centric diatom morphogenesis: a model based on a DLA algorithm investigating the potential role of microtubules

AbstractDiatoms are single-celled algae which possess characteristic rigid cell walls (frustules) composed of amorphous silica. Frustule formation occurs within a specialised organelle termed the silica deposition vesicle (SDV). During diatom morphogenesis, silica particles are transported to the SDV by silica transport vesicles. Once released within the SDV, the particles are then thought to diffuse until they encounter part of the growing aggregate upon which they adhere. The particles may then undergo a further period of surface relocalisation (sintering) which leads to a smoothing of the surface. A number of computer simulations based on a modified diffusion-limited aggregation (DLA) algorithm, have been undertaken to investigate the potential role of microtubules (which are known to be associated with the periphery of the SDV) in localising deposition of new siliceous material. Based on our findings, we present a new model of diatom morphogenesis which is able to account for many morphological features of diatoms including the influence of environmental effects such as changes in pH and salinity, and the formation of a regular branched pattern

Investigation of growth rate dispersion in lactose crystallisation by AFM

α-Lactose monohydrate crystals have been reported to exhibit growth rate dispersion (GRD). Variation in surface dislocations has been suggested as the cause of GRD, but this has not been further investigated to date. In this study, growth rate dispersion and the change in morphology were investigated in situ and via bottle roller experiments. The surfaces of the (0 1 0) faces of crystals were examined with Atomic Force Microscopy. Smaller, slow growing crystals tend to have smaller (0 1 0) faces with narrow bases and displayed a single double spiral in the centre of the crystal with 2 nm high steps. Additional double spirals in other crystals resulted in faster growth rates. Large, fast growing crystals were observed to have larger (0 1 0) faces with fast growth in both the a and b directions (giving a broader crystal base) with macro steps parallel to the (c direction). The number and location of spirals or existence of macro steps appears to influence the crystal morphology, growth rates and growth rate dispersion in lactose crystals

The role of biosensors in the detection of emerging infectious diseases

Global biosecurity threats such as the spread of emerging infectious diseases (i.e., avian influenza, SARS, Hendra, Nipah, etc.) and bioterrorism have generated significant interest in recent years. There is considerable effort directed towards understanding and negating the proliferation of infectious diseases. Biosensors are an attractive tool which have the potential to detect the outbreak of a virus and/or disease. Although there is a host of technologies available, either commercially or in the scientific literature, the development of biosensors for the detection of emerging infectious diseases (EIDs) is still in its infancy. There is no doubt that the glucose biosensor, the gene chip, the protein chip, etc. have all played and are still playing a significant role in monitoring various biomolecules. Can biosensors play an important role for the detection of emerging infectious diseases? What does the future hold and which biosensor technology platform is suitable for the real-time detection of infectious diseases? These and many other questions will be addressed in this review. The purpose of this review is to present an overview of biosensors particularly in relation to EIDs. It provides a synopsis of the various types of biosensor technologies that have been used to detect EIDs, and describes some of the technologies behind them in terms of transduction and bioreceptor principles

An electron microscopy study of b-FeOOH (akaganeite) nanorods and nanotubes

High-resolution TEM images reveal that samples of b-FeOOH (akaganeite) prepared by quenching of a condensed ferrihydrite gel contain a mixture of rod-like particles and tubes. The tubular particles are usually about 10-15 nm in diameter with a central void that is typically 1/3 of the particle diameter. Dark-field STEM images show that the tubular particles are made up of single crystals that extend across the whole tube diameter, but only rarely extend along the whole length of the tube. Both the solid rods and the tubes appear to be based on subunits of approximately 3-4 nm in diameter, and it is proposed that formation of the akaganeite particles, both tubes and rods, results from secondary nucleation of these subunits at sites on particle edges, followed by rapid linear growth along the c-direction of the akaganeite structure

Zinc sulfide as a solid phase additive for improving the processing characteristics of ferrihydrite residues

The effect of ZnS powders as additives for improving the physical and chemical properties of ferrihydrite residues has been studied in both kinetic and batch experiments. Four ZnS samples were compared: two industrial ZnS concentrates, high purity ZnS pieces, and a sample of synthetic ZnS nanoparticles. The industrial ZnS concentrates were found to be the most effective for promoting the transformation of ferrihydrite to hematite, and this effect was found to be due to their lower surface charge at pH 3, which promotes formation of mixed ZnS/ferrihydrite aggregates. For the high purity ZnS samples, aggregation was not favoured, and only goethite formation was promoted. The effect of particle size of the ZnS additive was also studied, and it was found that samples of smaller average particle size were more effective in promoting phase transformation. Measurement of filtration times and moisture content of ferrihydrite residues precipitated in the presence of ZnS showed only minor improvement in physical handling and indicated that better control of surface properties of the additive would be needed to optimise its effect on phase transformation

Bayesian Calibrated Significance Levels Applied to the Spectral Tilt and Hemispherical Asymmetry

Bayesian model selection provides a formal method of determining the level of support for new parameters in a model. However, if there is not a specific enough underlying physical motivation for the new parameters it can be hard to assign them meaningful priors, an essential ingredient of Bayesian model selection. Here we look at methods maximizing the prior so as to work out what is the maximum support the data could give for the new parameters. If the maximum support is not high enough then one can confidently conclude that the new parameters are unnecessary without needing to worry that some other prior may make them significant. We discuss a computationally efficient means of doing this which involves mapping p-values onto upper bounds of the Bayes factor (or odds) for the new parameters. A p-value of 0.05 ($1.96\sigma$) corresponds to odds less than or equal to 5:2 which is below the `weak' support at best threshold. A p-value of 0.0003 ($3.6\sigma$) corresponds to odds of less than or equal to 150:1 which is the `strong' support at best threshold. Applying this method we find that the odds on the scalar spectral index being different from one are 49:1 at best. We also find that the odds that there is primordial hemispherical asymmetry in the cosmic microwave background are 9:1 at best.Comment: 5 pages. V2: clarifying comments added in response to referee report. Matches version to appear in MNRA