In-vitro study of the spontaneous calcification of PHEMA-based hydrogels in simulated body fluid

In-vitro calcification of poly(2-hydroxyethyl methacrylate) (PHEMA)-based hydrogels in simulated body fluid (SBF) under a steady/batch system without agitation or stirring the solutions has been investigated. It was noted that the formation of calcium phosphate (CaP) deposits primarily proceeded through spontaneous precipitation. The CaP deposits were found both on the surface and inside the hydrogels. It appears that the effect of chemical structure or reducing the relative number of oxygen atoms in the copolymers on the degree of calcification was only important at the early stage of calcification. The morphology of the CaP deposits was observed to be spherical aggregates with a thickness of the CaP layer less than 0.5 mu m. Additionally, the CaP deposits were found to be poorly crystalline or to have nano-size crystals, or to exist mostly as an amorphous phase. Characterization of the CaP phases in the deposits revealed that the deposits were comprised mainly of whitlockite [Ca9MgH(PO4)(7)] type apatite and DCPD (CaHPO4 center dot 2H(2)O) as the precursors of hydroxyapatite [Ca-10(PO4)(6)(OH)(2)]. The presence of carbonate in the deposits was also detected during the calcification of PHEMA based hydrogels in SBF solution.

Morphology, characterization, and distribution of retinal photoreceptors in the Australian lungfish Neoceratodus forsteri (Krefft, 1870)

The Australian lungfish Neoceratodus forsteri (Dipnoi) is an ancient fish that has a unique phylogenetic relationship among the basal Sarcopterygii. Here we examine the ultrastructure, histochemistry, and distribution of the retinal photoreceptors using a combination of light and electron microscopy in order to determine the characteristics of the photoreceptor layer in this living fossil. Similar proportions of rods (53%) and cones (47%) reveal that N. forsteri optimizes both scotopic and photopic sensitivity according to its visual demands. Scotopic sensitivity is optimized by a tapetum lucidum and extremely large rods (18.62 +/- 2.68 mu m ellipsoid diameter). Photopic sensitivity is optimized with a theoretical spatial resolving power of 3.28 +/- 0.66 cycles degree(-1), which is based on the spacing of at least three different cone types: a red cone containing a red oil droplet, a yellow cone containing a yellow ellipsoidal pigment, and a colorless cone containing multiple clear oil droplets. Topographic analysis reveals a heterogeneous distribution of all photoreceptor types, with peak cone densities predominantly found in temporal retina (6,020 rods MM 2, 4,670 red cones mm(-2), 900 yellow cones mm(-2), and 320 colorless cones mm(-2)), but ontogenetic changes in distribution are revealed. Spatial resolving power and the diameter of all photoreceptor types (except yellow cones) increases linearly with growth. The presence of at least three morphological types of cones provides the potential for color vision, which could play a role in the clearer waters of its freshwater environment.

Mathematical Morphology: Star/Galaxy Differentiation & Galaxy Morphology Classication

We present an application of Mathematical Morphology (MM) for the classification of astronomical objects, both for star/galaxy differentiation and galaxy morphology classification. We demonstrate that, for CCD images, 99.3 +/- 3.8% of galaxies can be separated from stars using MM, with 19.4 +/- 7.9% of the stars being misclassified. We demonstrate that, for photographic plate images, the number of galaxies correctly separated from the stars can be increased using our MM diffraction spike tool, which allows 51.0 +/- 6.0% of the high-brightness galaxies that are inseparable in current techniques to be correctly classified, with only 1.4 +/- 0.5% of the high-brightness stars contaminating the population. We demonstrate that elliptical (E) and late-type spiral (Sc-Sd) galaxies can be classified using MM with an accuracy of 91.4 +/- 7.8%. It is a method involving fewer 'free parameters' than current techniques, especially automated machine learning algorithms. The limitation of MM galaxy morphology classification based on seeing and distance is also presented. We examine various star/galaxy differentiation and galaxy morphology classification techniques commonly used today, and show that our MM techniques compare very favourably.