Sensitive targeted multiple protein quantification based on elemental detection of Quantum Dots

A generic strategy based on the use of CdSe/ZnS Quantum Dots (QDs) as elemental labels for protein quantification, using immunoassays with elemental mass spectrometry (ICP-MS), detection is presented. In this strategy, streptavidin modified QDs (QDs-SA) are bioconjugated to a biotinylated secondary antibody (b-Ab₂). After a multi-technique characterization of the synthesized generic platform (QDs-SA-b-Ab₂) it was applied to the sequential quantification of five proteins (transferrin, complement C3, apolipoprotein A1, transthyretin and apolipoprotein A4) at different concentration levels in human serum samples. It is shown how this generic strategy does only require the appropriate unlabeled primary antibody for each protein to be detected. Therefore, it introduces a way out to the need for the cumbersome and specific bioconjugation of the QDs to the corresponding specific recognition antibody for every target analyte (protein). Results obtained were validated with those obtained using UV–vis spectrophotometry and commercial ELISA Kits.     

Concurrent multiresponse non-linear screening: Robust profiling of webpage performance

Profiling engineered data with robust mining methods continues attracting attention in knowledge engineering systems. The purpose of this article is to propose a simple technique that deals with non-linear multi-factorial multi-characteristic screening suitable for knowledge discovery studies. The method is designed to proactively seek and quantify significant information content in engineered mini-datasets. This is achieved by deploying replicated fractional-factorial sampling schemes. Compiled multi-response data are converted to a single master-response effectuated by a series of distribution-free transformations and multi-compressed data fusions. The resulting amalgamated master response is deciphered by non-linear multi-factorial stealth stochastics intended for saturated schemes. The stealth properties of our method target processing datasets which might be overwhelmed by a lack of knowledge about the nature of reference distributions at play. Stealth features are triggered to overcome restrictions regarding the data normality conformance, the effect sparsity assumption and the inherent collapse of the ‘unexplainable error’ connotation in saturated arrays. The technique is showcased by profiling four ordinary controlling factors that influence webpage content performance by collecting data from a commercial browser monitoring service on a large scale web host. The examined effects are: (1) the number of Cascading Style Sheets files, (2) the number of JavaScript files, (3) the number of Image files, and (4) the Domain Name System Aliasing. The webpage performance level was screened against three popular characteristics: (1) the time to first visual, (2) the total loading time, and (3) the customer satisfaction. Our robust multi-response data mining technique is elucidated for a ten-replicate run study dictated by an L₉(3⁴) orthogonal array scheme where any uncontrolled noise embedded contribution has not been necessarily excluded.     

Design and investigation of UV image detectors

The results of investigation of optical image detectors designed for the largest problem, near-VUV, range of the spectrum are presented. The possibility of using a dual-stage image detection system to appreciably lower the sensitivity threshold and make computer data processing feasible is considered. The integration of a UV module into a wideband image detector is studied.