Nanocrystalline SnO2-based, UVB-activated, colourimetric oxygen indicator

Nanocrystalline SnO2, ncSnO(2), is used as a photosensitiser in a colourimetric O-2 indicator that comprises a sacrificial electron donor, glycerol, a redox dye, methylene blue (MB), and an encapsulating polymer, hydroxyethyl cellulose (HEC). Upon exposure to a burst of UVB light the indicator is activated (photo-bleached) as the MB is photoreduced by the ncSnO(2) particles. In the absence of oxygen, the film stays bleached, but recovers its original colour upon exposure to oxygen. Unlike its TiO2-based predecessor, the HEC/glycerol/MB/ncSnO(2) O-2 indicator is not activated by UVA light from white fluorescent lamps, but is by UVB light. This feature provides much greater control in the activation of the indicator. Other work shows the rate of activation depends upon I-0.75, where I is the UVB irradiance, indicating a partial dependence upon the electron-hole recombination process. The half-life of the recovery of the original colour of a UV-activated film, t(50), is directly proportional to the ambient level of oxygen. The advantages of using this indicator in modified atmosphere packaging as a possible quality assurance indicator are discussed briefly. (c) 2008 Elsevier B.V. All rights reserved.

Novel UV-activated colorimetric oxygen indicator

The results of a detailed characterization study of a novel UV-activated colorimetric oxygen indicator are described. The indicator uses nanoparticles of titania to photosensitize the reduction of methylene blue by triethanolamine in a polymer encapsulation medium, using UVA light. Upon UV irradiation, the indicator bleaches and remains in this colorless state in the dark, unless and until it is exposed to oxygen, whereupon its original color is restored. The indicator is reusable and irreversible. The rate of color recovery is proportional to the level of oxygen present. A layer of PET (poly(ethylene terephthalate)), of thickness b, placed on top of the indicator film slows down its response, and the 90% recovery time is proportional to b.

Potentiation of Inflammatory CXCL8 Signalling Sustains Cell Survival in PTEN-deficient Prostate Carcinoma

Background: Inflammation and genetic instability are enabling characteristics of prostate carcinoma (PCa). Inactivation of the tumour suppressor gene phosphatase and tensin homolog (PTEN) is prevalent in early PCa. The relationship of PTEN deficiency to inflammatory signalling remains to be characterised.

Objective: To determine how loss of PTEN functionality modulates expression and efficacy of clinically relevant, proinflammatory chemokines in PCa.

Design, setting and participants: Experiments were performed in established cell-based PCa models, supported by pathologic analysis of chemokine expression in prostate tissue harvested from PTEN heterozygous (Pten(+/-)) mice harbouring inactivation of one PTEN allele.

Interventions: Small interfering RNA (siRNA)- or small hairpin RNA (shRNA)-directed strategies were used to repress PTEN expression and resultant interleukin-8 (CXCL8) signalling, determined under normal and hypoxic culture conditions.

Outcome measurements and statistical analysis: Changes in chemokine expression in PCa cells and tissue were analysed by real-time polymerase chain reaction (PCR), immunoblotting, enzyme-linked immunosorbent assay (ELISA), and immunohistochemistry; effects of chemokine signalling on cell function were assessed by cell cycle analysis, apoptosis, and survival assays.

Results and limitations: Transient (siRNA) or prolonged (shRNA) PTEN repression increased expression of CXCL8 and its receptors, chemokine (C-X-C motif) receptor (CXCR) 1 and CXCR2, in PCa cells. Hypoxia-induced increases in CXCL8, CXCR1, and CXCR2 expression were greater in magnitude and duration in PTEN-depleted cells. Autocrine CXCL8 signalling was more efficacious in PTEN-depleted cells, inducing hypoxia-inducible factor-1 (HIF-1) and nuclear factor kappa-light-chain-enhancer of activated B cells (NF-?B) transcription and regulating genes involved in survival and angiogenesis. Increased expression of the orthologous chemokine KC was observed in regions displaying atypical cytologic features in Pten(+/-) murine prostate tissue relative to normal epithelium in wild-type PTEN (Pten(WT)) glands. Attenuation of CXCL8 signalling decreased viability of PCa cells harbouring partial or complete PTEN loss through promotion of G1 cell cycle arrest and apoptosis. The current absence of clinical validation is a limitation of the study.

Conclusions: PTEN loss induces a selective upregulation of CXCL8 signalling that sustains the growth and survival of PTEN-deficient prostate epithelium.

Optimisation of time/temperature treatment, for heat treated soft wheat flour

Chlorination of wheat flour in the EU countries has been replaced in recent years, to some extent, by heat treated flour which is used to produce high ratio cakes. Heat treated flour allows high ratio recipes to be developed which generate products with longer shelf life, finer texture, moist crumb and sweeter taste. The mechanism by which heat treatment improves the flour is not fully understood, but it is known that during the heat treatment process, protein denaturation and partial gelatinisation of the starch granules occurs, as well as an increase in batter viscosity. Therefore, it is important to optimize the flour heat treatment process, in order to enhance baking quality. Laboratory preparation of heat treated base wheat flour (culinary, soft, low protein) was carried out in a fluidised bed drier using a range of temperatures and times. The gluten was extracted from the final product and its quality was tested, to obtain objective and comparative information on the extent of protein denaturation. The results indicated that heat treatment of flour decreases gluten extensibility and partial gelatinisation of the starch granules occurred. After heat treatment the gluten appeared to retain moisture. The optimum time/temperature for the heat treatment of base flour was 120-130°C for 30 min with moisture content of ˜12.5%.© 2012 Elsevier Ltd. All rights reserved.

Time-dependent density functional theory study of charge transfer in collisions

We study the charge transfer between colliding ions, atoms, or molecules, within time-dependent density functional theory. Two particular cases are presented, the collision between a proton and a Helium atom, and between a gold atom and a butane molecule. In the first case, proton kinetic energies between 16 keV and 1.2 MeV are considered, with impact parameters between 0.31 and 1.9 angstrom. The partial transfer of charge is monitored with time. The total cross-section is obtained as a function of the proton kinetic energy. In the second case, we analyze one trajectory and discuss spin-dependent charge transfer between the different fragments.

Complement expression in retinal pigment epithelial cells is modulated by activated macrophages

Complement activation is involved in a variety of retinal diseases. We have shown previously that a number of complement components and regulators can be produced locally in the eye, and that retinal pigment epithelial (RPE) cells are the major source of complement expression at the retina-choroidal interface. The expression of complement components by RPE cells is regulated by inflammatory cytokines. Under aging or inflammatory conditions, microglia and macrophages accumulate in the subretinal space, where they are in close contact with RPE cells. In this study, we investigated the effect of activated macrophages on complement expression by RPE cells. Mouse RPE cells were treated with the supernatants from un-activated bone marrow-derived macrophages (BM-DMs), the classically activated BM-DMs (M1) and different types of the alternatively activated BM-DMs (M2a by IL-4, M2b by immune complex and lipopolysaccharide (LPS), M2c by IL-10). The expression of inflammatory cytokines and complement genes by RPE cells were determined by real-time RT-PCR. The protein expression of CFB, C3, C1INH, and C1r was examined by Western blot. Our results show that un-stimulated RPE cells express a variety of complement-related genes, and that the expression levels of complement regulators, including C1r, factor H (CFH), DAF1, CD59, C1INH, Crry, and C4BP genes are significantly higher than those of complement component genes (C2, C4, CFB, C3, and C5). Macrophage supernatants increased inflammatory cytokine (IL-1ß, IL-6, iNOS), chemokine (CCL2) and complement expression in RPE cells. The supernatants from M0, M2a and M2c macrophages mildly up-regulated (2~3.5-fold) CFB, CFH and C3 gene expression in RPE cells, whereas the supernatants from M1 and M2b macrophages massively increased (10~30-fold) CFB and C3 gene expression in RPE cells. The expression of other genes, including C1r, C2, C4, CFH, Masp1, C1INH, and C4BP in RPE cells was also increased by the supernatants of M1 and M2b macrophages; however, the increment levels were significantly lower than CFB and C3 genes. M1 and M2b macrophage supernatants enhanced CFB (Bb fragment) protein expression and C3 secretion by RPE cells. M1 macrophages may affect complement expression in RPE cells through the STAT1 pathway. Our results suggest that under inflammatory conditions, activated macrophages could promote the alternative pathway of complement activation in the retina via induction of RPE cell CFB and C3 expression.

Time-Resolved DRIFTS, MS, and Resistance Study of SnO2 Materials: The Role of Surface Hydroxyl Groups in Formation of Donor States

Time-resolved DRIFTS, MS, and resistance measurements were used to study the interaction of undoped and Pd-doped SnO2 with H-2 in air and argon at 300 degrees C. Using first-order kinetics, we compare the time constants for the resistance drop and its partial recovery with those of the surface hydroxyl evolution and water formation in the gas phase upon exposure to hydrogen. In the case of the undoped oxide, resistance and bridging hydroxyls (BOHs) evolve similarly, manifesting a fast main drop followed by recovery at a similar rate. The rate of water formation for this material was found to be much slower than that of the main drop in both the resistance and BOHs. In contrast, the resistance change for SnO2-Pd appeared to be similar to that of water formation, and no correlation was found between the evolution of resistance and surface OHs. Isotopic exchange on both materials revealed that water formation occurs via fast and slow hydrogen transfer to surface oxygen species. While the former originates from just-adsorbed hydrogen, the latter appears to proceed from the preadsorbed OHs. Both surfaces exhibit close interaction between chemisorbed oxygen and existing bridging OH groups, indicating that the latter is an intermediate in the hydrogen oxidation and generation of donor states on the surface.

Decoding semantics across fMRI sessions with different stimulus modalities:a practical MVPA study

Both embodied and symbolic accounts of conceptual organization would predict partial sharing and partial differentiation between the neural activations seen for concepts activated via different stimulus modalities. But cross-participant and cross-session variability in BOLD activity patterns makes analyses of such patterns with MVPA methods challenging. Here, we examine the effect of cross-modal and individual variation on the machine learning analysis of fMRI data recorded during a word property generation task. We present the same set of living and non-living concepts (land-mammals, or work tools) to a cohort of Japanese participants in two sessions: the first using auditory presentation of spoken words; the second using visual presentation of words written in Japanese characters. Classification accuracies confirmed that these semantic categories could be detected in single trials, with within-session predictive accuracies of 80-90%. However cross-session prediction (learning from auditory-task data to classify data from the written-word-task, or vice versa) suffered from a performance penalty, achieving 65-75% (still individually significant at p « 0.05). We carried out several follow-on analyses to investigate the reason for this shortfall, concluding that distributional differences in neither time nor space alone could account for it. Rather, combined spatio-temporal patterns of activity need to be identified for successful cross-session learning, and this suggests that feature selection strategies could be modified to take advantage of this.

Hexavalent Chromium Adsorption by a Novel Activated Carbon Prepared by Microwave Activation

Microwave heating reduces the preparation time and improves the adsorption quality of activated carbon. In this study, activated carbon was prepared by impregnation of palm kernel fiber with phosphoric acid followed by microwave activation. Three different types of activated carbon were prepared, having high surface areas of 872 m2 g-1, 1256 m2 g-1, and 952 m2 g-1 and pore volumes of 0.598 cc g-1, 1.010 cc g-1, and 0.778 cc g-1, respectively. The combined effects of the different process parameters, such as the initial adsorbate concentration, pH, and temperature, on adsorption efficiency were explored with the help of Box-Behnken design for response surface methodology (RSM). The adsorption rate could be expressed by a polynomial equation as the function of the independent variables. The hexavalent chromium adsorption rate was found to be 19.1 mg g-1 at the optimized conditions of the process parameters, i.e., initial concentration of 60 mg L-1, pH of 3, and operating temperature of 50 oC. Adsorption of Cr(VI) by the prepared activated carbon was spontaneous and followed second-order kinetics. The adsorption mechanism can be described by the Freundlich Isotherm model. The prepared activated carbon has demonstrated comparable performance to other available activated carbons for the adsorption of Cr(VI).

Model selection for prognostic time-to-event gene signature discovery with applications in early breast cancer data

Model selection between competing models is a key consideration in the discovery of prognostic multigene signatures. The use of appropriate statistical performance measures as well as verification of biological significance of the signatures is imperative to maximise the chance of external validation of the generated signatures. Current approaches in time-to-event studies often use only a single measure of performance in model selection, such as logrank test p-values, or dichotomise the follow-up times at some phase of the study to facilitate signature discovery. In this study we improve the prognostic signature discovery process through the application of the multivariate partial Cox model combined with the concordance index, hazard ratio of predictions, independence from available clinical covariates and biological enrichment as measures of signature performance. The proposed framework was applied to discover prognostic multigene signatures from early breast cancer data. The partial Cox model combined with the multiple performance measures were used in both guiding the selection of the optimal panel of prognostic genes and prediction of risk within cross validation without dichotomising the follow-up times at any stage. The signatures were successfully externally cross validated in independent breast cancer datasets, yielding a hazard ratio of 2.55 [1.44, 4.51] for the top ranking signature.

Taguchi optimisation approach for production of activated carbon from phosphoric acid impregnated palm kernel shell by microwave heating

Taguchi method was applied to investigate the optimal operating conditions in the preparation of activated carbon using palm kernel shell with quadruple control factors: irradiation time, microwave power, concentration of phosphoric acid as impregnation substance and impregnation ratio between acid and palm kernel shell. The best combination of the control factors as obtained by applying Taguchi method was microwave power of 800 W, irradiation time of 17 min, impregnation ratio of 2, and acid concentration of 85%. The noise factor (particle size of raw material) was considered in a separate outer array, which had no effect on the quality of the activated carbon as confirmed by t-test. Activated carbon prepared at optimum combination of control factors had high BET surface area of 1,473.55 m² g-1 and high porosity. The adsorption equilibrium and kinetic data can satisfactorily be described by the Langmuir isotherm and a pseudo-second-order kinetic model, respectively. The maximum adsorbing capacity suggested by the Langmuir model was 1000 mg g-1.

Experimentally validated partial least squares model for dynamic line rating

This study presents a model based on partial least squares (PLS) regression for dynamic line rating (DLR). The model has been verified using data from field measurements, lab tests and outdoor experiments. Outdoor experimentation has been conducted both to verify the model predicted DLR and also to provide training data not available from field measurements, mainly heavily loaded conditions. The proposed model, unlike the direct measurement based DLR techniques, enables prediction of line rating for periods ahead of time whenever a reliable weather forecast is available. The PLS approach yields a very simple statistical model that accurately captures the physical performance of the conductor within a given environment without requiring a predetermination of parameters as required by many physical modelling techniques. Accuracy of the PLS model has been tested by predicting the conductor temperature for measurement sets other than those used for training. Being a linear model, it is straightforward to estimate the conductor ampacity for a set of predicted weather parameters. The PLS estimated ampacity has proven its accuracy through an outdoor experiment on a piece of the line conductor in real weather conditions.

Partial least squares model for dynamic rating of overhead line in wind intensive areas based on field measurements

This paper presents a statistical model for the thermal behaviour of the line model based on lab tests and field measurements. This model is based on Partial Least Squares (PLS) multi regression and is used for the Dynamic Line Rating (DLR) in a wind intensive area. DLR provides extra capacity to the line, over the traditional seasonal static rating, which makes it possible to defer the need for reinforcement the existing network or building new lines. The proposed PLS model has a number of appealing features; the model is linear, so it is straightforward to use for predicting the line rating for future periods using the available weather forecast. Unlike the available physical models, the proposed model does not require any physical parameters of the line, which avoids the inaccuracies resulting from the errors and/or variations in these parameters. The developed model is compared with physical model, the Cigre model, and has shown very good accuracy in predicting the conductor temperature as well as in determining the line rating for future time periods. 

Performance analysis of switch-and-stay combining in two-way relay systems with analog network coding and time-division broadcast protocols

In this paper, weconsider switch-and-stay combining (SSC) in two-way relay systems with two amplify-and-forward relays, one of which is activated to assist the information exchange between the two sources. The system operates in either analog network coding (ANC) protocol where the communication is only achieved with the help of the active relay or timedivision broadcast (TDBC) protocol where the direct link between two sources can be utilized to exploit more diversity gain. In both cases, we study the outage probability and bit error rate (BER) for Rayleigh fading channels. In particular, we derive closed-form lower bounds for the outage probability and the average BER, which remain tight for different fading conditions. We also present asymptotic analysis for both the outage probability and the average BER at high signalto-noise ratio. It is shown that SSC can achieve the full diversity order in two-way relay systems for both ANC and TDBC protocols with proper switching thresholds. Copyright © 2014 John Wiley & Sons, Ltd.

Alkali Activated Fuel Ash and Slag Mixes:Optimization Study from Mortars to Concrete Building Blocks

Alkali activated binders, based on ash and slag, also known as geopolymers, can play a key role in reducing the carbon footprint of the construction sector by replacing ordinary Portland cement in some concretes. Since 1970s, research effort has been ongoing in many research institutions. In this study, pulverized fuel ash (PFA) from a UK power plant, ground granulated blast furnace slag (GGBS) and combinations of the two have been investigated as geopolymer binders for concrete applications. Activators used were sodium hydroxide and sodium silicate solutions. Mortars with sand/binder ratio of 2.75 with several PFA and GGBS combinations have been mixed and tested. The optimization of alkali dosage (defined as the Na2O/binder mass ratio) and modulus (defined as the Na2O/SiO2 mass ratio) resulted in strengths in excess of 70 MPa for tested mortars. Setting time and workability have been considered for the identification of the best combination of PFA/GGBS and alkali activator dosage for different precast concrete products. Geopolymer concrete building blocks have been replicated in laboratory and a real scale factory trial has been successfully carried out. Ongoing microstructural characterization is aiming to identify reaction products arising from PFA/GGBS combinations.