Highly accurate detection of ovarian cancer using CA125 but limited improvement with serum matrix-assisted laser desorption/ionization time-of-flight mass spectrometry profiling

Objectives: Our objective was to test the performance of CA125 in classifying serum samples from a cohort of malignant and benign ovarian cancers and age-matched healthy controls and to assess whether combining information from matrix-assisted laser desorption/ionization (MALDI) time-of-flight profiling could improve diagnostic performance. Materials and Methods: Serum samples from women with ovarian neoplasms and healthy volunteers were subjected to CA125 assay and MALDI time-of-flight mass spectrometry (MS) profiling. Models were built from training data sets using discriminatory MALDI MS peaks in combination with CA125 values and tested their ability to classify blinded test samples. These were compared with models using CA125 threshold levels from 193 patients with ovarian cancer, 290 with benign neoplasm, and 2236 postmenopausal healthy controls. Results: Using a CA125 cutoff of 30 U/mL, an overall sensitivity of 94.8% (96.6% specificity) was obtained when comparing malignancies versus healthy postmenopausal controls, whereas a cutoff of 65 U/mL provided a sensitivity of 83.9% (99.6% specificity). High classification accuracies were obtained for early-stage cancers (93.5% sensitivity). Reasons for high accuracies include recruitment bias, restriction to postmenopausal women, and inclusion of only primary invasive epithelial ovarian cancer cases. The combination of MS profiling information with CA125 did not significantly improve the specificity/accuracy compared with classifications on the basis of CA125 alone. Conclusions: We report unexpectedly good performance of serum CA125 using threshold classification in discriminating healthy controls and women with benign masses from those with invasive ovarian cancer. This highlights the dependence of diagnostic tests on the characteristics of the study population and the crucial need for authors to provide sufficient relevant details to allow comparison. Our study also shows that MS profiling information adds little to diagnostic accuracy. This finding is in contrast with other reports and shows the limitations of serum MS profiling for biomarker discovery and as a diagnostic tool

Hydrogen-bond assisted stabilization of the less favored conformation of a tridentate Schiff base ligand in dinuclear nickel(II) complex: an experimental and theoretical study

The Schiff base ligand, HL (2-[1-(3-methylamino-propylimino)-ethyl]-phenol), the 1:1 condensation product of 2-hydroxy acetophenone and N-methyl-1,3-diaminopropane, has been synthesized and characterized by X-ray crystallography as the perchlorate salt [H2L]ClO4 (1). The structure consists of discrete [H2L](+) cations and perchlorate anions. Two dinuclear Ni-II complexes, [Ni2L2(NO2)(2)] (2), [Ni2L2(NO3)(2)] (3) have been synthesized using this ligand and characterized by single crystal X-ray analyses. Complexes 2 and 3 are centrosymmetric dimers in which the Ni-II ions are in distorted fac- and mer-octahedral environments, respectively, bridged by two mu(2)-phenolate ions of deprotonated ligand, L. The plane of the phenyl rings and the Ni2O2 basal plane are nearly coplanar in 2 but almost perpendicular in 3. We have studied and explained this different behavior using high level DFT calculations (RI-BP86/def2-TZVP level of theory). The conformation observed in 3, which is energetically less favorable, is stabilized via intermolecular non-covalent interactions. Under the excitation of ultraviolet light, characteristic fluorescence of compound 1 was observed; by comparison fluorescence intensity decreases in case of compound 3 and completely quenched in compound 2.

Adaptive modelling with tunable RBF network using multi-innovation RLS algorithm assisted by swarm intelligence

In this paper, we propose a new on-line learning algorithm for the non-linear system identification: the swarm intelligence aided multi-innovation recursive least squares (SI-MRLS) algorithm. The SI-MRLS algorithm applies the particle swarm optimization (PSO) to construct a flexible radial basis function (RBF) model so that both the model structure and output weights can be adapted. By replacing an insignificant RBF node with a new one based on the increment of error variance criterion at every iteration, the model remains at a limited size. The multi-innovation RLS algorithm is used to update the RBF output weights which are known to have better accuracy than the classic RLS. The proposed method can produces a parsimonious model with good performance. Simulation result are also shown to verify the SI-MRLS algorithm.

Dissolution rates of earthworm-secreted calcium carbonate

The dissolution of CaCO3 granules secreted by earthworms in soil leaching columns was governed by soil pH and exchange sites available for Ca. Results indicate that granules could last for significant periods of time in soils and that, therefore, granules could be an important source of soil calcite.

Mechanisms of burst release from pH-responsive polymeric microparticles.

Microencapsulation of drugs into preformed polymers is commonly achieved through solvent evaporation techniques or spray drying. We compared these encapsulation methods in terms of controlled drug release properties of the prepared microparticles and investigated the underlying mechanisms responsible for the “burst release” effect. Using two different pH-responsive polymers with a dissolution threshold of pH 6 (Eudragit L100 and AQOAT AS-MG), hydrocortisone, a model hydrophobic drug, was incorporated into microparticles below and above its solubility within the polymer matrix. Although, spray drying is an attractive approach due to rapid particle production and relatively low solvent waste, the oil-in-oil microencapsulation method is superior in terms of controlled drug release properties from the microparticles. Slow solvent evaporation during the oil-in-oil emulsification process allows adequate time for drug and polymer redistribution in the microparticles and reduces uncontrolled drug burst release. Electron microscopy showed that this slower manufacturing procedure generated non-porous particles whereas thermal analysis and X-ray diffractometry showed that drug loading above the solubility limit of the drug in the polymer generated excess crystalline drug on the surface of the particles. Raman spectral mapping illustrated that drug was homogeneously distributed as a solid solution in the particles when loaded below saturation in the polymer with consequently minimal burst release.

Production and dissolution rates of earthworm-secreted calcium carbonate

Earthworms secrete granules of calcium carbonate. These are potentially important in soil biogeochemical cycles and are routinely recorded in archaeological studies of Quaternary soils. Production rates of calcium carbonate granules by the earthworm Lumbricus terrestris L. were determined over 27 days in a range of soils with differing chemical properties (pH, organic matter content, water holding capacity, bulk composition, cation exchange capacity and exchangeable cations). Production rate varied between soils, lay in the range 0–0.043 mmolCaCO3 (0–4.3 mg) earthworm−1 d−1 with an average rate of 8 × 10−3 mmolCaCO3 (0.8 mg) earthworm−1 d−1 and was significantly correlated (r = 0.68, P ≤ 0.01) with soil pH. In a second experiment lasting 315 days earthworms repeatedly (over periods of 39–57 days) produced comparable masses of granules. Converting individual earthworm granule production rates into fluxes expressed on per hectare of land per year basis depends heavily on estimates of earthworm numbers. Using values of 10–20 L. terrestris m−2 suggests a rate of 18– 3139 molCaCO3 ha−1 yr−1. Data obtained from flow-through dissolution experiments suggest that at near neutral pH, granule geometric surface areanormalised dissolution rates are similar to those for other biogenic and inorganic calcium carbonate. Fits of the data to the dissolution relationship r = k(1 − ˝)n where r = dissolution rate, k = a rate constant, ˝ = relative saturation and n = the reaction order gave values of k = 1.72 × 10−10 mol cm−2 s−1 and n = 1.8 for the geometric surface area-normalised rates and k = 3.51 × 10−13 mol cm−2 s−1 and n = 1.8 for the BET surface area-normalised rates. In 196 day leaching column experiments trends in granule dissolution rate referenced to soil chemistry corresponded to predictions made by the SLIM model for dissolution of limestone in soil. If soil solution approaches saturation with respect to calcium carbonate granule dissolution will slow or even stop and granules be preserved indefinitely. Granules have the potential to be a small but significant component of the biogeochemical cycling of C and Ca in soil.

Kinetic multi-layer model of gas-particle interactions in aerosols and clouds (KM-GAP): linking condensation, evaporation and chemical reactions of organics, oxidants and water

We present a novel kinetic multi-layer model for gas-particle interactions in aerosols and clouds (KM-GAP) that treats explicitly all steps of mass transport and chemical reaction of semi-volatile species partitioning between gas phase, particle surface and particle bulk. KM-GAP is based on the PRA model framework (Pöschl-Rudich-Ammann, 2007), and it includes gas phase diffusion, reversible adsorption, surface reactions, bulk diffusion and reaction, as well as condensation, evaporation and heat transfer. The size change of atmospheric particles and the temporal evolution and spatial profile of the concentration of individual chemical species can be modelled along with gas uptake and accommodation coefficients. Depending on the complexity of the investigated system, unlimited numbers of semi-volatile species, chemical reactions, and physical processes can be treated, and the model shall help to bridge gaps in the understanding and quantification of multiphase chemistry and microphysics in atmo- spheric aerosols and clouds. In this study we demonstrate how KM-GAP can be used to analyze, interpret and design experimental investigations of changes in particle size and chemical composition in response to condensation, evaporation, and chemical reaction. For the condensational growth of water droplets, our kinetic model results provide a direct link between laboratory observations and molecular dynamic simulations, confirming that the accommodation coefficient of water at 270 K is close to unity. Literature data on the evaporation of dioctyl phthalate as a function of particle size and time can be reproduced, and the model results suggest that changes in the experimental conditions like aerosol particle concentration and chamber geometry may influence the evaporation kinetics and can be optimized for eðcient probing of specific physical effects and parameters. With regard to oxidative aging of organic aerosol particles, we illustrate how the formation and evaporation of volatile reaction products like nonanal can cause a decrease in the size of oleic acid particles exposed to ozone.

Microwave-assisted hydrogel synthesis: a new method for crosslinking polymers in aqueous solutions

It has been found that hydrogels may be formed by microwave irradiation of aqueous solutions containing appropriate combinations of polymers. This new method of hydrogel synthesis yields sterile hydrogels without the use of monomers, eliminating the need for the removal of unreacted species from the final product. Results for two particularly successful combinations, poly(vinyl alcohol) with either poly(acrylic acid) or poly(methylvinylether-alt-maleic anhydride), are presented. Irradiation using temperatures of 100–150 °C was found to yield hydrogels with large equilibrium swelling degrees of 500–1000 g g−1. Material leached from both types of hydrogel shows little cytotoxicity towards HT29 cells.

Assisted remote viewing of a teleoperation work cell

Intelligent viewing systems are required if efficient and productive teleoperation is to be applied to dynamic manufacturing environments. These systems must automatically provide remote views to an operator which assist in the completion of the task. This assistance increases the productivity of the teleoperation task if the robot controller is responsive to the unpredictable dynamic evolution of the workcell. Behavioral controllers can be utilized to give reactive 'intelligence.' The inherent complex structure of current systems, however, places considerable time overheads on any redesign of the emergent behavior. In industry, where the remote environment and task frequently change, this continual redesign process becomes inefficient. We introduce a novel behavioral controller, based on an 'ego-behavior' architecture, to command an active camera (a camera mounted on a robot) within a remote workcell. Using this ego-behavioral architecture the responses from individual behaviors are rapidly combined to produce an 'intelligent' responsive viewing system. The architecture is single-layered, each behavior being autonomous with no explicit knowledge of the number, description or activity of other behaviors present (if any). This lack of imposed structure decreases the development time as it allows each behavior to be designed and tested independently before insertion into the architecture. The fusion mechanism for the behaviors provides the ability for each behavior to compete and/or co-operate with other behaviors for full or partial control of the viewing active camera. Each behavior continually reassesses this degree of competition or co-operation by measuring its own success in controlling the active camera against pre-defined constraints. The ego-behavioral architecture is demonstrated through simulation and experimentation.

Kinetic multi-layer model of gas-particle interactions in aerosols and clouds (KM-GAP): linking condensation, evaporation and chemical reactions of organics, oxidants and water

We present a novel kinetic multi-layer model for gas-particle interactions in aerosols and clouds (KMGAP) that treats explicitly all steps of mass transport and chemical reaction of semi-volatile species partitioning between gas phase, particle surface and particle bulk. KMGAP is based on the PRA model framework (P¨oschl-Rudich- Ammann, 2007), and it includes gas phase diffusion, reversible adsorption, surface reactions, bulk diffusion and reaction, as well as condensation, evaporation and heat transfer. The size change of atmospheric particles and the temporal evolution and spatial profile of the concentration of individual chemical species can be modeled along with gas uptake and accommodation coefficients. Depending on the complexity of the investigated system and the computational constraints, unlimited numbers of semi-volatile species, chemical reactions, and physical processes can be treated, and the model shall help to bridge gaps in the understanding and quantification of multiphase chemistry and microphysics in atmospheric aerosols and clouds. In this study we demonstrate how KM-GAP can be used to analyze, interpret and design experimental investigations of changes in particle size and chemical composition in response to condensation, evaporation, and chemical reaction. For the condensational growth of water droplets, our kinetic model results provide a direct link between laboratory observations and molecular dynamic simulations, confirming that the accommodation coefficient of water at 270K is close to unity (Winkler et al., 2006). Literature data on the evaporation of dioctyl phthalate as a function of particle size and time can be reproduced, and the model results suggest that changes in the experimental conditions like aerosol particle concentration and chamber geometry may influence the evaporation kinetics and can be optimized for efficient probing of specific physical effects and parameters. With regard to oxidative aging of organic aerosol particles, we illustrate how the formation and evaporation of volatile reaction products like nonanal can cause a decrease in the size of oleic acid particles exposed to ozone.

PSO assisted NURB Neural Network Identification

A system identification algorithm is introduced for Hammerstein systems that are modelled using a non-uniform rational B-spline (NURB) neural network. The proposed algorithm consists of two successive stages. First the shaping parameters in NURB network are estimated using a particle swarm optimization (PSO) procedure. Then the remaining parameters are estimated by the method of the singular value decomposition (SVD). Numerical examples are utilized to demonstrate the efficacy of the proposed approach.

EU enlargement and consequences for FDI-assisted industrial development

Many of the new member states as well as candidate and accession countries of the EU are confident that membership will result in substantially increased inward foreign direct investment (FDI) in manufacturing. This paper discusses the policy issues and challenges that cohesion and accession countries face, applying lessons that by now have become mainstream in the parallel discussion of FDI-assisted development in the developing economies. We argue that globalisation has attenuated the benefits that accrue from EU membership for latecomers, and they must now compete for FDI not just with other European countries but also with non- EU emerging economies. We posit that they should not base their industrial development strategy on mere passive reliance of FDI flows without considering how to concatenate their industrial development and the nature of the MNE activities they attract.