Examination of the spatially heterogeneous electroactivity of boron-doped diamond microarray electrodes

Spatial variations in the electrical and electrochemical activity of microarray electrodes, fabricated entirely from diamond, have been investigated. The arrays contain approximately 50-mum-diameter boron-doped diamond (BDD) disks spaced 250 mum apart (center to center) in insulating intrinsic diamond supports, such that the BDD regions are coplanar with the intrinsic diamond. Atomic force microscopy (AFM) imaging of the surface reveals a roughness of no more than +/-10 nm over the array. Each BDD microdisk within the array contains polycrystalline BDD with a variety of different grains exposed. Using conducting-AFM, the conductivity of the different grains was found to vary within a BDD microdisk. Electrochemical imaging of the electroactivity of the microdisk electrodes using scanning electrochemical microscopy operating in substrate generation-tip collection mode revealed that, under apparently diffusion-limited steady-state conditions, there was a small variation in the response between electrodes. However, the majority of electrodes in the array appeared to show predominantly metallic behavior. For the electrodes that showed a lower activity, all grains within the microdisk supported electron transfer, albeit at different rates, as evidenced by studies on the electrodeposition of metallic silver, at potentials far negative of the flat band potential of oxygen-terminated polycrystalline diamond. The possibility of using these array electrodes for steady-state diffusion-limited measurements in electroanalytical applications is far-reaching. However, caution should be exercised in the kinetic analysis of voltammetric measurements, since wide variations in the electroactivity of individual grains are apparent when the potential is below the diffusion-limited value.     

Targeted profiling: quantitative analysis of 1H NMR metabolomics data

Extracting meaningful information from complex spectroscopic data of metabolite mixtures is an area of active research in the emerging field of "metabolomics", which combines metabolism, spectroscopy, and multivariate statistical analysis (pattern recognition) methods. Chemometric analysis and comparison of 1H NMR1 spectra is commonly hampered by intersample peak position and line width variation due to matrix effects (pH, ionic strength, etc.). Here a novel method for mixture analysis is presented, defined as "targeted profiling". Individual NMR resonances of interest are mathematically modeled from pure compound spectra. This database is then interrogated to identify and quantify metabolites in complex spectra of mixtures, such as biofluids. The technique is validated against a traditional "spectral binning" analysis on the basis of sensitivity to water suppression (presaturation, NOESY-presaturation, WET, and CPMG), relaxation effects, and NMR spectral acquisition times (3, 4, 5, and 6 s/scan) using PCA pattern recognition analysis. In addition, a quantitative validation is performed against various metabolites at physiological concentrations (9 microM-8 mM). "Targeted profiling" is highly stable in PCA-based pattern recognition, insensitive to water suppression, relaxation times (within the ranges examined), and scaling factors; hence, direct comparison of data acquired under varying conditions is made possible. In particular, analysis of metabolites at low concentration and overlapping regions are well suited to this analysis. We discuss how targeted profiling can be applied for mixture analysis and examine the effect of various acquisition parameters on the accuracy of quantification.     

A novel nanostructured composite formed by interaction of copper octa(3-aminopropyl)octasilsesquioxane with azide ligands: Preparation, characterization and a voltammetric application

This study presents the preparation, characterization and application of copper octa(3-aminopropyl)octasilsesquioxane following its subsequent reaction with azide ions (ASCA). The precursor (AC) and the novel compound (ASCA) were characterized by Fourier transform infrared spectra (FTIR), nuclear magnetic resonance (NMR), electron paramagnetic resonance (EPR), scanning electronic microscopy (SEM), X-ray diffraction (XRD), Thermogravimetric analyses and voltammetric technique. The cyclic voltammogram of the modified graphite paste electrode with ASCA (GPE-ASCA), showed one redox couple with formal potential () = 0.30 V and an irreversible process at 1.1 V (vs. Ag/AgCl; NaCl 1.0 M; v=20 mV s−1). The material is very sensitive to nitrite concentrations. The modified graphite paste electrode (GPE-ASCA) gives a linear range from 1.0 × 10⁻⁴ to 4.0 × 10⁻³ mol L⁻¹ for the determination of nitrite, with a detection limit of 2.1 × 10⁻⁴ mol L⁻¹ and the amperometric sensitivity of 8.04 mA/mol L⁻¹.     

Outdoor grazing of dairy cows on pasture versus indoor feeding on total mixed ration: Effects on gross composition and mineral content of milk during lactation

The influence of feeding system and lactation period on the gross composition, macroelements (Ca, P, Mg, and Na), and trace elements (Zn, Fe, Cu, Mo, Mn, Se, and Co) of bovine milk was investigated. The feeding systems included outdoor grazing on perennial ryegrass pasture (GRO), outdoor grazing on perennial ryegrass and white clover pasture (GRC), and indoors offered total mixed ration (TMR). Sixty spring-calving Holstein Friesian dairy cows were assigned to 3 herds, each consisting of 20 cows, and balanced with respect to parity, calving date, and pre-experimental milk yield and milk solids yield. The herds were allocated to 1 of the 3 feeding systems from February to November. Milk samples were collected on 10 occasions over the period June 17 to November 26, at 2 or 3 weekly intervals, when cows were on average 119 to 281 d in lactation (DIL). The total lactation period was arbitrarily sub-divided into 2 lactation periods based on DIL, namely mid lactation, June 17 to September 9 when cows were 119 to 203 DIL; and late lactation, September 22 to November 26 when cows were 216 to 281 DIL. With the exception of Mg, Na, Fe, Mo, and Co, all other variables were affected by feeding system. The GRO milk had the highest mean concentrations of total solids, total protein, casein, Ca, and P. The TMR milk had the highest concentrations of lactose, Cu, and Se, and lowest level of total protein. The GRC milk had levels of lactose, Zn, and Cu similar to those of GRO milk, and concentrations of TS, Ca, and P similar to those of TMR milk. Lactation period affected all variables, apart from the concentrations of Fe, Cu, Mn, and Se. On average, the proportion (%) of total Ca, P, Zn, Mn, or Se that sedimented with the casein on high-speed ultracentrifugation at 100,000 × g was ≥60%, whereas that of Na, Mg, or Mo was ≤45% total. The results demonstrate how the gross composition and elemental composition of milk can be affected by different feeding systems.     

The cost-benefit of genomic testing of heifers and using sexed semen in pasture-based dairy herds

Recent improvements in dairy cow fertility and female reproductive technologies offer an opportunity to apply greater selection pressure to females. This means there may be greater incentive to obtain genomic breeding values for females. We modeled the impact of changes to key parameters on the net benefit from genomic testing of heifer calves with and without usage of sexed semen. This paper builds on earlier cost-benefit studies but uses parameters relevant to pasture-based systems. A deterministic model was used to evaluate the effect on net benefit due to changes in (1) reproduction rate, (2) genomic test costs, (3) availability of parent-derived breeding values (EBV_PA), and (4) replacement rate. When the use of sexed semen was included, we also considered (1) the proportion of heifers and cows mated to sexed semen, (2) decreases in conception rate in inseminations with sexed semen, and (3) the marginal return for surplus heifers. Scenarios with lower replacement rates and no availability of EBV_PA had the largest net benefits. Under current Australian parameters, the net benefit of genomic testing realized over the lifetime of genotyped heifers is expected to range from A$204 to A$1,124 per 100 cows for a herd with median reproductive performance. The cost of a genomic test, a perceived barrier to many farmers, had only a small effect on net benefit. Genomic testing alone was always more profitable than using sexed semen and genomic testing together if the only benefit considered was increased genetic gain in heifer replacements. When other benefits (i.e., the higher sale price of a surplus heifer compared with a male calf) were considered, there were combinations of parameters where net benefit from using sexed semen and genomic testing was higher than the equivalent scenario with genomic testing only. Using sexed semen alongside genomic testing is most likely to be profitable when (1) used in heifers, (2) the marginal return for selling surplus heifers (sale price minus rearing costs) is greater than A$400, and (3) conception rates of no more than 10 percentage points lower than those achieved using conventional semen can be realized. Net benefit was highly dependent on the marginal return. Demonstrating that the initial investment in genomic testing can be recouped within the lifetime of the heifers tested may assist in the development of extension messages to explain the value of genomic testing females at the herd level.     

Biotic and abiotic interactions in aquatic microcosms determine fate and toxicity of Ag nanoparticles: part 2-toxicity and Ag speciation

To study the effects of complex environmental media on silver nanoparticle (AgNP) toxicity, AgNPs were added to microcosms with freshwater sediments and two species of aquatic plants (Potamogeton diversifolius and Egeria densa), followed by toxicity testing with microcosm surface water. Microcosms were designed with four environmental matrices in order to determine the contribution of each environmental compartment to changes in toxicity: water only (W), water + sediment (WS), water + plants (WP), and water + plants + sediment (WPS). Silver treatments included AgNPs with two different coatings, gum arabic (GA-AgNPs) or polyvinylpyrollidone (PVP-AgNPs), as well as AgNO(3). Water samples taken from the microcosms at 24 h postdosing were used in acute toxicity tests with two standard model organisms, early life stage zebrafish (Danio rerio) and Daphnia magna. Speciation of Ag in these samples was analyzed using Ag L3-edge X-ray absorption near edge spectroscopy (XANES). Silver speciation patterns for the nanoparticle treatments varied significantly by coating type. While PVP-AgNPs were quite stable and resisted transformation across all matrices (>92.4% Ag(0)), GA-AgNP speciation patterns suggest significantly higher transformation rates, especially in treatments with plants (<69.2% and <58.8% Ag(0) in WP and WPS, respectively) and moderately increased transformation with sediments (<85.6% Ag(0)). Additionally, the presence of plants in the microcosms (with and without sediments) reduced both the concentration of Ag in the water column and toxicity for all Ag treatments. Reductions in toxicity may have been related to decreased water column concentrations as well as changes in the surface chemistry of the particles induced by organic substances released from the plants.     

A multiscale parallel computing architecture for automated segmentation of the brain connectome

Several groups in neurobiology have embarked into deciphering the brain circuitry using large-scale imaging of a mouse brain and manual tracing of the connections between neurons. Creating a graph of the brain circuitry, also called a connectome, could have a huge impact on the understanding of neurodegenerative diseases such as Alzheimer's disease. Although considerably smaller than a human brain, a mouse brain already exhibits one billion connections and manually tracing the connectome of a mouse brain can only be achieved partially. This paper proposes to scale up the tracing by using automated image segmentation and a parallel computing approach designed for domain experts. We explain the design decisions behind our parallel approach and we present our results for the segmentation of the vasculature and the cell nuclei, which have been obtained without any manual intervention.     

Monitoring the transesterification reaction with laser spectroscopy

The production of biodiesel is rapidly expanding around the world, making it more important to produce this fuel with more energy efficiency. In this paper, we observed a series of transesterification reactions of soy bean oil and methyl alcohol catalyzed by potassium hydroxide. The observations were made using a non-invasive optical technique. This technique is useful to indicate the endpoint of a transesterification reaction or to determine when this reaction is reaching the state of chemical equilibrium. This study made it possible to improve the follow-up of the transesterification reaction, by optimizing the reaction time with a better monitoring system.     

The Comparison of Woven Fabrics by Reference to Their Tightness

The paper outlines a method for comparing the tightness of two woven fabrics. The tightness of a woven fabric is determined with reference to the nearest maximum-sett fabric to the given fabric. The purpose is not to categorise woven fabrics in terms of their tightness but to enable fabrics to be designed with reference to other known fabrics, tightness being used as the basis for comparison.