Microchip-based purification of DNA from biological samples

A microchip solid-phase extraction method for purification of DNA from biological samples, such as blood, is demonstrated. Silica beads were packed into glass microchips and the beads immobilized with sol-gel to provide a stable and reproducible solid phase onto which DNA could be adsorbed. Optimization of the DNA loading conditions established a higher DNA recovery at pH 6.1 than 7.6. This lower pH also allowed for the flow rate to be increased, resulting in a decrease in extraction time from 25 min to less than 15 min. Using this procedure, template genomic DNA from human whole blood was purified on the microchip platform with the only sample preparation being mixing of the blood with load buffer prior to loading on the microchip device. Comparison between the microchip SPE (microchipSPE) procedure and a commercial microcentrifuge method showed comparable amounts of PCR-amplifiable DNA could be isolated from cultures of Salmonella typhimurium. The greatest potential of the microchipSPE device was illustrated by purifying DNA from spores from the vaccine strain of Bacillus anthracis, where eventual integration of SPE, PCR, and separation on a single microdevice could potentially enable complete detection of the infectious agent in less than 30 min.     

Thorium in the workplace: results from a European-based measurement comparison project

A Series of comparisons were conducted to test the capabilities of a range of metrological techniques and analytical laboratories engaged in the assay of thorium in the workplace. The results of these exercises are presented together with the decision criteria used to determine whether results are significantly different from the true value. The discussion highlights those aspects which warrant closer and further attention.     

Globally Optimal Training of Unit Boundaries in Unit Selection Text-to-Speech Synthesis

The level of quality that can be achieved by modern concatenative text-to-speech synthesis heavily depends on a judicious composition of the unit inventory used in the unit selection process. Unit boundary optimization, in particular, can make a huge difference in the users' perception of the concatenated acoustic waveform. This paper considers the iterative refinement of unit boundaries based on a data-driven feature extraction framework separately optimized for each boundary region. This guarantees a globally optimal cut point between any two matching units in the underlying inventory. The associated boundary training procedure is objectively characterized, first in terms of convergence behavior, and then by comparing the distributions in inter-unit discontinuity obtained before and after training. Experimental results underscore the viability of this approach for unit boundary optimization. Listening evidence also qualitatively exemplifies a noticeable reduction in the perception of discontinuity between concatenated acoustic units     

Strength prediction of multi-layer plain weave textile composites using the direct micromechanics method

Previously developed micromechanical methods for stiffness and strength prediction are adapted for analysis of multi-layer plain weave textile composites. Utilizing the direct micromechanics method (DMM) via finite element modeling, three methods are presented: (a) direct simulation of a multi-layer plain weave textile composite; (b) micromechanical analysis of a single layer of interest from the force and moment resultants acting on that layer; and (c) application of the previously developed quadratic stress-gradient failure theory to the layer of interest. In comparison to direct modeling, the other two techniques show only 5% difference over a number of random test cases. Several practical design examples of strength prediction are included to illustrate the importance and accuracy of method implementation.     

CONTROL OF DEAD-TIME SYSTEMS USING HYBRID ANT COLONY OPTIMIZATION

This paper introduces two improved forms of the ant colony optimization (ACO) algorithm applied to a proportional integral derivative (PID) controller and Smith predictor design. Derivative free optimization methods, namely simplex derivative based pattern search (SDPS) and implicit filtering (IMF), are used to intensify the search mechanism in the ACO algorithm with improved convergence over the original ACO. The effectiveness of the controller schemes using the proposed algorithms, namely SDPS-ACO, and IMF-ACO, is demonstrated using unit step set point response for a class of dead-time systems, and the results are compared with some existing methods of controller tuning.     

In vitro interactions between DMSA-coated maghemite nanoparticles and human fibroblasts: A physicochemical and cyto-genotoxical study

Although the current production of oxide nanoparticles may be modest, the wide range of proposed applications and forecasted growth in production has raised questions about the potential impact of these nanoparticles on the environment and human health. Iron oxide nanoparticles have been proposed for an increasing number of biomedical applications although in vitro toxicity depending on the particles coating has been evidenced. The aim of this study was to examine the potential in vitro cyto- and genotoxicity on human dermal fibroblasts of DMSA-coated maghemite nanoparticles (NmDMSA) as a function of well-defined physicochemical states. Well-stabilized NmDMSA produced weak cytotoxic and no genotoxic effects. This is attributed in part to the DMSA coating, which serves as a barrier for a direct contact between nano-oxide and fibroblasts, inhibiting a potential toxic effect.     

Learning Automata from Ordered Examples

Connectionist learning models have had considerable empirical success, but it is hard to characterize exactly what they learn. The learning of finite-state languages (FSL) from example strings is a domain which has been extensively studied and might provide an opportunity to help understand connectionist learning. A major problem is that traditional FSL learning assumes the storage of all examples and thus violates connectionist principles. This paper presents a provably correct algorithm for inferring any minimum-state deterministic finite-state automata (FSA) from a complete ordered sample using limited total storage and without storing example strings. The algorithm is an iterative strategy that uses at each stage a current encoding of the data considered so far, and one single sample string. One of the crucial advantages of our algorithm is that the total amount of space used in the course of learning for encoding any finite prefix of the sample is polynomial in the size of the inferred minimum state deterministic FSA. The algorithm is also relatively efficient in time and has been implemented. More importantly, there is a connectionist version of the algorithm that preserves these properties. The connectionist version requires much more structure than the usual models and has been implemented using the Rochester Connectionist Simulator. We also show that no machine with finite working storage can iteratively identify the FSL from arbitrary presentations.     

Resection margins, extrapleural nodal status, and cell type determine postoperative long-term survival in trimodality therapy of malignant pleural mesothelioma: results in 183 patients

OBJECTIVES: Our aim was to identify prognostic variables for long-term postoperative survival in trimodality management of malignant pleural mesothelioma. METHODS: From 1980 to 1997, 183 patients underwent extrapleural pneumonectomy followed by adjuvant chemotherapy and radiotherapy. RESULTS: Forty-three women and 140 men (age range 31-76 years) had a median follow-up of 13 months. The perioperative mortality rate was 3.8% (7 deaths) and the morbidity, 50%. Survival in the 176 remaining patients was 38% at 2 years and 15% at 5 years (median 19 months). Univariate analysis identified 3 prognostic variables associated with improved survival: epithelial cell type (52% 2-year survival, 21% 5-year survival, 26-month median survival; P =.0001), negative resection margins (44% at 2 years, 25% at 5 years, median 23 months; P =.02), and extrapleural nodes without metastases (42% at 2 years, 17% at 5 years, median 21 months; P =.004). Using the Cox proportional hazards, the relative risk of death was calculated for nonepithelial cell type (OR 3.0, CI 2.0-4.5; P <.0001), positive resection margins (OR 1.7, CI 1.2-2.6; P =.0082), and metastatic extrapleural nodes (OR 2.0, CI 1.3-3.2; P =.0026). Thirty-one patients with 3 positive variables had the best survival (68% 2-year survival, 46% 5-year survival, median 51 months; P =.013). A previously published staging system using these variables stratified survival (P <.05). CONCLUSIONS: (1) Multimodality therapy including extrapleural pneumonectomy is feasible in selected patients with malignant pleural mesotheliomas, (2) pre-resectional evaluation of extrapleural nodes may select patients for radical therapy, (3) microscopic resection margins affect long-term survival, highlighting the need for further investigation of locoregional control, and (4) patients with epithelial, margin-negative, extrapleural node-negative resection had extended survival.     

Comparison of source apportionment and source sensitivity of ozone in a three-dimensional air quality model

The ozone source apportionment technology (OSAT) estimates the contributions of different sources to ozone concentrations using a set of tracers for NOx, total VOCs, and ozone and an indicator that ascribes instantaneous ozone production to NOx or VOCs. These source contributions were compared to first-order sensitivities obtained by the decoupled direct method (DDM) for a three-dimensional simulation of an ozone episode in the Lake Michigan region. The cut-point for the OSAT indicator between VOC- and NOx-sensitive ozone production agrees well with the DDM sensitivities to VOC and NOx. In a ranking of the most important contributors to ozone concentrations >80 ppb, the OSAT and DDM results agreed on four of the top five contributors on average. The spatial distributions of the sensitivities and source contributions are similar, and the OSAT and DDM results for ozone >80 ppb correlate well. However, the source contributions ascribe substantially less relative importance to anthropogenic emissions and greater relative importance to the boundary concentrations than do the sensitivities. In regions where NOx inhibits ozone formation and the sensitivity is negative, the source contribution is small and positive. For the same subdivision of the emissions, the OSAT is 14 times faster than the DDM, but the DDM has greater flexibility in defining which emissions to include and generates results for species other than ozone. The first-order sensitivities explain, on average, 70% of the ozone concentrations.