Plasmon enhanced upconversion luminescence of NaYF(4):Yb,Er@SiO(2)@Ag core-shell nanocomposites for cell imaging

NaYF(4):Yb,Er@SiO(2)@Ag core-shell nanocomposites were prepared to investigate metal-enhanced upconversion luminescence. Two sizes (15 and 30 nm) of Ag nanoparticles were used. The emission intensity of the upconversion nanocrystals was found to be strongly modulated by the presence of Ag nanoparticles (NPs) on the outer shell layer of the nanocomposites. The extent of modulation depended on the separation distance between Ag NPs and upconversion nanocrystals. The optimum upconversion luminescence enhancement was observed at a separation distance of 10 nm for Ag NPs with two different sizes (15 and 30 nm). A maximum upconversion luminescence enhancement of 14.4-fold was observed when 15 nm Ag nanoparticles were used and 10.8-fold was observed when 30 nm Ag NPs were used. The separation distance dependent emission intensity is ascribed to the competition between energy transfer and enhanced radiative decay rates. The biocompatibility of the nanocomposites was significantly improved by surface modification with DNA. The biological imaging capabilities of these nanocomposites were demonstrated using B16F0 cells.     

Antagonism of microRNA function in zebrafish embryos by using locked nucleic acid enzymes (LNAzymes)

MicroRNAs (miRNAs) have crucial functions in many cellular processes, such as differentiation, proliferation and apoptosis; aberrant expression of miRNAs has been linked to human diseases, including cancer. Tools that allow specific and efficient knockdown of miRNAs would be of immense importance for exploring miRNA function. Zebrafish serves as an excellent vertebrate model system to understand the functions of miRNAs involved in a variety of biological processes. We designed and employed a strategy based on locked nucleic acid enzymes (LNAzymes) for in vivo knockdown of miRNA in zebrafish embryos. We demonstrate that LNAzyme can efficiently knockdown miRNAs with minimal toxicity to the zebrafish embryos.     

Molecular rotors image intracellular viscosity

This review describes a new method for quantitative measurement and spatial imaging of microviscosity within individual domains of live cells. The method is based on fluorescence detection from small synthetic molecules termed 'molecular rotors', which are characterised by a strong response of fluorescence lifetimes or spectra to the viscosity of their immediate environment. We have demonstrated that the quantitative determination of viscosity is possible using lifetime-based molecular rotors and ratiometric molecular rotors. The ratiometric imaging of viscosity benefits from a very fast signal acquisition. We have illustrated this advantage by monitoring changes in intracellular viscosity during photodynamic therapy, which is a clinically utilised modality for the treatment of neoplastic disease.     

Chick Chorioallantoic Membrane (CAM) Assay as an In Vivo Model to Study the Effect of Newly Identified Molecules on Ovarian Cancer Invasion and Metastasis

The majority of ovarian cancer patients present with advanced disease and despite aggressive treatment, prognosis remains poor. Significant improvement in ovarian cancer survival will require the development of more effective molecularly targeted therapeutics. Commonly, mouse models are used for the in vivo assessment of potential new therapeutic targets in ovarian cancer. However, animal models are costly and time consuming. Other models, such as the chick embryo chorioallantoic membrane (CAM) assay, are therefore an attractive alternative. CAM assays have been widely used to study angiogenesis and tumor invasion of colorectal, prostate and brain cancers. However, there have been limited studies that have used CAM assays to assess ovarian cancer invasion and metastasis. We have therefore developed a CAM assay protocol to monitor the metastatic properties of ovarian cancer cells (OVCAR-3, SKOV-3 and OV-90) and to study the effect of potential therapeutic molecules in vivo. The results from the CAM assay are consistent with cancer cell motility and invasion observed in in vitro assays. Our results demonstrate that the CAM assay is a robust and cost effective model to study ovarian cancer cell metastasis. It is therefore a very useful in vivo model for screening of potential novel therapeutics.     

Using chemistry and microfluidics to understand the spatial dynamics of complex biological networks

Understanding the spatial dynamics of biochemical networks is both fundamentally important for understanding life at the systems level and also has practical implications for medicine, engineering, biology, and chemistry. Studies at the level of individual reactions provide essential information about the function, interactions, and localization of individual molecular species and reactions in a network. However, analyzing the spatial dynamics of complex biochemical networks at this level is difficult. Biochemical networks are nonequilibrium systems containing dozens to hundreds of reactions with nonlinear and time-dependent interactions, and these interactions are influenced by diffusion, flow, and the relative values of state-dependent kinetic parameters. To achieve an overall understanding of the spatial dynamics of a network and the global mechanisms that drive its function, networks must be analyzed as a whole, where all of the components and influential parameters of a network are simultaneously considered. Here, we describe chemical concepts and microfluidic tools developed for network-level investigations of the spatial dynamics of these networks. Modular approaches can be used to simplify these networks by separating them into modules, and simple experimental or computational models can be created by replacing each module with a single reaction. Microfluidics can be used to implement these models as well as to analyze and perturb the complex network itself with spatial control on the micrometer scale. We also describe the application of these network-level approaches to elucidate the mechanisms governing the spatial dynamics of two networkshemostasis (blood clotting) and early patterning of the Drosophila embryo. To investigate the dynamics of the complex network of hemostasis, we simplified the network by using a modular mechanism and created a chemical model based on this mechanism by using microfluidics. Then, we used the mechanism and the model to predict the dynamics of initiation and propagation of blood clotting and tested these predictions with human blood plasma by using microfluidics. We discovered that both initiation and propagation of clotting are regulated by a threshold response to the concentration of activators of clotting, and that clotting is sensitive to the spatial localization of stimuli. To understand the dynamics of patterning of the Drosophila embryo, we used microfluidics to perturb the environment around a developing embryo and observe the effects of this perturbation on the expression of Hunchback, a protein whose localization is essential to proper development. We found that the mechanism that is responsible for Hunchback positioning is asymmetric, time-dependent, and more complex than previously proposed by studies of individual reactions. Overall, these approaches provide strategies for simplifying, modeling, and probing complex networks without sacrificing the functionality of the network. Such network-level strategies may be most useful for understanding systems with nonlinear interactions where spatial dynamics is essential for function. In addition, microfluidics provides an opportunity to investigate the mechanisms responsible for robust functioning of complex networks. By creating nonideal, stressful, and perturbed environments, microfluidic experiments could reveal the function of pathways thought to be nonessential under ideal conditions.     

Effects of organic carbon supply rates on uranium mobility in a previously bioreduced contaminated sediment

Bioreduction-based strategies for remediating uranium (U)-contaminated sediments face the challenge of maintaining the reduced status of U for long times. Because groundwater influxes continuously bring in oxidizing terminal electron acceptors (O2, NO3(-)), it is necessary to continue supplying organic carbon (OC) to maintain the reducing environment after U bioreduction is achieved. We tested the influence of OC supply rates on mobility of previously microbial reduced uranium U(IV) in contaminated sediments. We found that high degrees of U mobilization occurred when OC supply rates were high, and when the sediment still contained abundant Fe(III). Although 900 days with low levels of OC supply minimized U mobilization, the sediment redox potential increased with time as did extractable U(VI) fractions. Molecular analyses of total microbial activity demonstrated a positive correlation with OC supply and analyses of Geobacteraceae activity (RT-qPCR of 16S rRNA) indicated continued activity even when the effluent Fe(II) became undetectable. These data support our hypothesis on the mechanisms responsible for remobilization of U under reducing conditions; that microbial respiration caused increased (bi)carbonate concentration and formation of stable uranyl carbonate complexes, thereby shifted U(IV)/U(VI) equilibrium to more reducing potentials. The data also suggested that low OC concentrations could not sustain the reducing condition of the sediment for much longer time. Bioreduced U(IV) is not sustainable in an oxidizing environment for a very long time.     

Estimation of the costs of acute gastrointestinal illness in British Columbia, Canada

The costs associated with gastrointestinal infection (GI) in the province of British Columbia, Canada, were estimated using data from a population-based survey in three health service delivery areas, namely Vancouver, East Kootenay and Northern Interior. The number of cases of disease, consequent expenditure of resources and associated economic costs were modeled as probability distributions in a stochastic model. Using 2004 prices, the estimated mean annual cost per capita of gastrointestinal infection was CAN$128.61 (euro207.96), with a mean annual cost per case of CAN$1,342.57 (euro2,170.99). The mean estimate of the overall economic burden to British Columbia was CAN$514.2 million (euro831.5 million) (95% CFI CAN$161.0 million to CAN$5.8 billion; euro260.3 million to euro9.38 billion). The major element of this cost was the loss of productivity associated with time away from paid employment by both the sick and their caregivers. Sensitivity analysis suggested that the uncertainty associated with the base model assumptions did not significantly affect the estimates. The results are comparable to those obtained in an earlier study using a similar analytical framework and data from the city of Hamilton, Ontario, Canada.     

Catalytic oxidation with Al-Ce-Fe-PILC as a post-treatment system for coffee wet processing wastewater

The effluent from the anaerobic biological treatment of coffee wet processing wastewater (CWPW) contains a non-biodegradable compound that must be treated before it is discharged into a water source. In this paper, the wet hydrogen peroxide catalytic oxidation (WHPCO) process using Al-Ce-Fe-PILC catalysts was researched as a post-treatment system for CWPW and tested in a semi-batch reactor at atmospheric pressure and 25 °C. The Al-Ce-Fe-PILC achieved a high conversion rate of total phenolic compounds (70%) and mineralization to CO(2) (50%) after 5 h reaction time. The chemical oxygen demand (COD) of coffee processing wastewater after wet hydrogen peroxide catalytic oxidation was reduced in 66%. The combination of the two treatment methods, biological (developed by Cenicafé) and catalytic oxidation with Al-Ce-Fe-PILC, achieved a 97% reduction of COD in CWPW. Therefore, the WHPCO using Al-Ce-Fe-PILC catalysts is a viable alternative for the post-treatment of coffee processing wastewater.     

Measurement and mathematical modelling of nutrient level and water quality parameters

Physico-chemical water quality parameters and nutrient levels such as water temperature, turbidity, saturated oxygen, dissolved oxygen, pH, chlorophyll-a, salinity, conductivity, total nitrogen and total phosphorus, were measured from April to September 2011 in the Karaj dam area, Iran. Total nitrogen in water was modelled using an artificial neural network system. In the proposed system, water temperature, depth, saturated oxygen, dissolved oxygen, pH, chlorophyll-a, salinity, turbidity and conductivity were considered as input data, and the total nitrogen in water was considered as output. The weights and biases for various systems were obtained by the quick propagation, batch back propagation, incremental back propagation, genetic and Levenberg-Marquardt algorithms. The proposed system uses 144 experimental data points; 70% of the experimental data are randomly selected for training the network and 30% of the data are used for testing. The best network topology was obtained as (9-5-1) using the quick propagation method with tangent transform function. The average absolute deviation percentages (AAD%) are 2.329 and 2.301 for training and testing processes, respectively. It is emphasized that the results of the artificial neural network (ANN) model are compatible with the experimental data.     

Smoothing of pixelated finite element models of cancellous bone structures and the effect on the predicted structural properties of the bone

Many areas of biomedical engineering involve the modelling of biological systems, often using data from medical scanning techniques such as computed microtomography (microCT), and the prediction of the mechanical properties of these systems via finite element models. These models, and also those produced from remodelling simulations on idealized bone structures, are inherently highly pixelated and therefore have a high degree of surface roughness. The purpose of this paper is to demonstrate that this surface roughness need not necessarily have an influence on the predicted properties of the object under examination. To demonstrate this, two-dimensional idealized models of cancellous bone structures were used that were initially depleted and then rebuilt stochastically. A hysteresis effect was observed such that a significant amount of rebuilding beyond the original density was required to regain the initial intact stiffness. To ensure that this effect was not an artefact of the high degree of surface roughness of the rebuilt structures, a two-stage smoothing procedure was applied to assess if this had any effect on the stiffness of the structures. The superpixelation of the structures appeared to have a more profound effect than the smoothing procedures, although the smoothed structures still had stiffness and density values similar to those of the original structures, with a hysteresis effect still evident. This proves that the pixelization of the structures does not have a significant effect on the predicted mechanical properties of the structures. This work has important implications for other models that exhibit a high degree of surface roughness.