Electron traps on high-temperature oxidized SIMOX buried oxides

Photo-injection was used to study the charge trapping properties of high-temperature oxidation (HITOX) SIMOX buried oxides (BOX), provided by two independent vendors. After electron injection, from a 5 eV mercury light source, the electron trapping per area for both HITOX material sources was found to be larger than their respective standard (control) separation by implantation of oxygen (SIMOX) structures. This increase has been attributed to the HITOX's process influence on the formation of the HITOX/BOX oxide     

Enzyme-amplified aequorin-based bioluminometric hybridization assays

The sensitivity of aequorin-based bioluminometric hybridization assays was enhanced by introducing, enzymically, multiple aequorin labels per DNA hybrid. The target DNA was hybridized in microtiter wells with an immobilized capture probe and a digoxigenin-labeled detection probe. The hybrids were reacted with an anti-digoxigenin antibody conjugated to horseradish peroxidase. Peroxidase catalyzed the oxidation of digoxigenin-tyramine by hydrogen peroxide, resulting in the attachment of multiple digoxigenin moieties to the solid phase. Aequorin-labeled anti-digoxigenin antibody was then allowed to bind to the immobilized digoxigenins. The bound aequorin was determined by its characteristic Ca2+-triggered bioluminescence. As low as 20 fmol/L (1 amol/ well) target DNA was detected with a signal-to-background ratio of 2.7. A hybridization assay that used only aequorin-labeled anti-digoxigenin antibody without the peroxidase amplification step gave a signal-to-background ratio of 2 for 160 fmol/L target DNA. The signal enhancement of the amplified assay was in the range of 14-38 times. The analytical range of the amplified assay extended up to 2600 fmol/L. The CVs were in the range of 5.5-7.3%.     

Multi-platform data integration in microarray analysis

An increasing number of studies have profiled gene expressions in tumor specimens using distinct microarray platforms and analysis techniques. One challenging task is to develop robust statistical models in order to integrate multi-platform findings. We compare some methodologies on the field with respect to estrogen receptor (ER) status, and focus on a unified-among-platforms scale implemented by Shen et al. in 2004, which is based on a Bayesian mixture model. Under this scale, we study the ER intensity similarities between four breast cancer datasets derived from various platforms. We evaluate our results with an independent dataset in terms of ER sample classification, given the derived gene ER signatures of the integrated data. We found that integrated multi-platform gene signatures and fold-change variability similarities between different platform measurements can assist the statistical analysis of independent microarray datasets in terms of ER classification.     

Preparation and properties of fully esterified erythritol

Pure tetraesters of erythritol with C₁₀, C₁₂, C₁₄, C₁₆, C₁₈ saturated, and C_18:1 unsaturated (oleoyl) fatty acyl chains have been prepared for the first time and characterized using the acylating systems fatty acid/N,N′‐dicyclohexylcarbodiimide/4‐dimethylaminopyridine (DMAP), fatty acid anhydride/DMAP, fatty acyl chloride/pyridine, and fatty acyl chloride/boron trifluoride etherate. For the first three systems the yields were in the range of 80–90% while the fatty acyl chloride/pyridine system has the advantage of lower cost. The fatty acyl chloride/boron trifluoride etherate system gave lower (ca 70%) yields of the tetraesters. The tetraesters of erythritol may have applications analogues to those of triglycerides. In addition, new applications can be envisaged for these compounds, as a result of their differences in physical, chemical, and biochemical properties compared to triglycerides. Practical applications: The tetraesters of erythritol with saturated fatty acyl chains may have applications analogous to those of saturated triglycerides. However, tetraesters with unsaturated fatty acid chains may have greater prospects of having industrial uses after doing chemistry on the carbon–carbon double bonds.     

A nanoparticle-based sensor for visual detection of multiple mutations

Disposable dipstick-type DNA biosensors in the form of lateral flow strips are particularly useful for genotyping in a small laboratory or for field testing due to their simplicity, low cost and portability. Their unique advantage is that they enable visual detection in?minutes without the use of instruments. In addition, the dry-reagent format minimizes the pipetting, incubation and washing steps. In this work, we significantly enhance the multiplexing capabilities of lateral flow strip biosensors without compromising their simplicity. Multiplex genotyping is carried out by polymerase chain reaction (PCR) followed by a single primer extension reaction for all target alleles, in which a primer is extended and biotin is incorporated only if it is perfectly complementary to the target. Multiallele detection is achieved by multiple test spots on the membrane of the sensor, each comprising a suspension of polystyrene microspheres functionalized with capture probes. The products of the primer extension reaction hybridize, through specific sequence tags, to the capture probes and are visualized by using antibiotin-conjugated gold nanoparticles. This design enables accommodation of multiple spots in a small area because the microspheres are trapped in the fibres of the membrane and remain fixed in site without any diffusion. Furthermore, the detectability is improved because the hybrids are exposed on the surface of the trapped microspheres rather than inside the pores of the membrane. We demonstrate the specificity and performance of the biosensor for multiallele genotyping.     

Neural network approach to retrieve the inherent optical properties of the ocean from observations of MODIS

Retrieving the inherent optical properties of water from remote sensing multispectral reflectance measurements is difficult due to both the complex nature of the forward modeling and the inherent nonlinearity of the inverse problem. In such cases, neural network (NN) techniques have a long history in inverting complex nonlinear systems. The process we adopt utilizes two NNs in parallel. The first NN is used to relate the remote sensing reflectance at available MODIS-visible wavelengths (except the 678 nm fluorescence channel) to the absorption and backscatter coefficients at 442 nm (peak of chlorophyll absorption). The second NN separates algal and nonalgal absorption components, outputting the ratio of algal-to-nonalgal absorption. The resulting synthetically trained algorithm is tested using both the NASA Bio-Optical Marine Algorithm Data Set (NOMAD), as well as our own field datasets from the Chesapeake Bay and Long Island Sound, New York. Very good agreement is obtained, with R2 values of 93.75%, 90.67%, and 86.43% for the total, algal, and nonalgal absorption, respectively, for the NOMAD. For our field data, which cover absorbing waters up to about 6 m?1, R2 is 91.87% for the total measured absorption.