Roles of the translationally controlled tumour protein (TCTP) and the double-stranded RNA-dependent protein kinase, PKR, in cellular stress responses

Translationally controlled tumour protein (TCTP) is a highly conserved protein present in all eukaryotic organisms. Various cellular functions and molecular interactions have been ascribed to this protein, many related to its growth-promoting and antiapoptotic properties. TCTP levels are highly regulated in response to various cellular stimuli and stresses. We have shown recently that the double-stranded RNA-dependent protein kinase, PKR, is involved in translational regulation of TCTP. Here we extend these studies by demonstrating that TCTP is downregulated in response to various proapoptotic treatments, in particular agents that induce Ca++ stress, in a PKR-dependent manner. This regulation requires phosphorylation of protein synthesis factor eIF2α. Since TCTP has been characterized as an antiapoptotic and Ca++-binding protein, we asked whether it is involved in protecting cells from Ca++-stress-induced apoptosis. Overexpression of TCTP partially protects cells against thapsigargin-induced apoptosis, as measured using caspase-3 activation assays, a nuclear fragmentation assay, using fluorescence-activated cell sorting analysis, and time-lapse video microscopy. TCTP also protects cells against the proapoptotic effects of tunicamycin and etoposide, but not against those of arsenite. Our results imply that cellular TCTP levels influence sensitivity to apoptosis and that PKR may exert its proapoptotic effects at least in part through downregulation of TCTP via eIF2α phosphorylation.

Measurement and prediction of the effect of students activities on airborne particulate concentration in a classroom.

Epidemiological studies have shown links between human exposure to indoor airborne particles and adverse health affects. Several recent studies have also reported that the classroom environment has an impact on students’ health and performance. In this study particle concentration in a university classroom is assessed experimentally for different occupancy periods. The mass concentrations of different particle size ranges (0.3 – 20 µm), and the three particulate matter fractions (PM10, PM2.5, and PM1) were measured simultaneously in a classroom with different occupancy periods including occupied and unoccupied periods in the University of Reading, UK, during the winter period of 2010. The results showed that students’ presence is a significant factor affecting particles concentration for the fractions above PM1 in the measured range of 0.3 to 20 µm. The resuspension of the three PM fractions was also determined in the study.

Platelet endothelial cell adhesion molecule-1 regulates collagen-stimulated platelet function by modulating the association of phosphatidylinositol 3-kinase with Grb-2-associated binding protein-1 and linker for activation of T cells

Background: Platelet activation by collagen depends on signals transduced by the glycoprotein (GP)VI–Fc receptor (FcR)-chain collagen receptor complex, which involves recruitment of phosphatidylinositol 3-kinase (PI3K) to phosphorylated tyrosines in the linker for activation of T cells (LAT). An interaction between the p85 regulatory subunit of PI3K and the scaffolding molecule Grb-2-associated binding protein-1 (Gab1), which is regulated by binding of the Src homology 2 domain-containing protein tyrosine phosphatase-2 (SHP-2) to Gab1, has been shown in other cell types to sustain PI3K activity to elicit cellular responses. Platelet endothelial cell adhesion molecule-1 (PECAM-1) functions as a negative regulator of platelet reactivity and thrombosis, at least in part by inhibiting GPVI–FcR-chain signaling via recruitment of SHP-2 to phosphorylated immunoreceptor tyrosine-based inhibitory motifs in PECAM-1. Objective: To investigate the possibility that PECAM-1 regulates the formation of the Gab1–p85 signaling complexes, and the potential effect of such interactions on GPVI-mediated platelet activation in platelets. Methods: The ability of PECAM-1 signaling to modulate the LAT signalosome was investigated with immunoblotting assays on human platelets and knockout mouse platelets. Results: PECAM-1-associated SHP-2 in collagen-stimulated platelets binds to p85, which results in diminished levels of association with both Gab1 and LAT and reduced collagen-stimulated PI3K signaling. We therefore propose that PECAM-1-mediated inhibition of GPVI-dependent platelet responses result, at least in part, from recruitment of SHP-2–p85 complexes to tyrosine-phosphorylated PECAM-1, which diminishes the association of PI3K with activatory signaling molecules, such as Gab1 and LAT.

Dual-orthogonal radial basis function networks for nonlinear time series prediction

A new structure of Radial Basis Function (RBF) neural network called the Dual-orthogonal RBF Network (DRBF) is introduced for nonlinear time series prediction. The hidden nodes of a conventional RBF network compare the Euclidean distance between the network input vector and the centres, and the node responses are radially symmetrical. But in time series prediction where the system input vectors are lagged system outputs, which are usually highly correlated, the Euclidean distance measure may not be appropriate. The DRBF network modifies the distance metric by introducing a classification function which is based on the estimation data set. Training the DRBF networks consists of two stages. Learning the classification related basis functions and the important input nodes, followed by selecting the regressors and learning the weights of the hidden nodes. In both cases, a forward Orthogonal Least Squares (OLS) selection procedure is applied, initially to select the important input nodes and then to select the important centres. Simulation results of single-step and multi-step ahead predictions over a test data set are included to demonstrate the effectiveness of the new approach.

Modulation of pro-survival Akt/protein kinase B and ERK1/2 signaling cascades by quercetin and its in vivo metabolites underlie their action on neuronal viability

Much recent interest has focused on the potential of flavonoids to interact with intracellular signaling pathways such as with the mitogen-activated protein kinase cascade. We have investigated whether the observed strong neurotoxic potential of quercetin in primary cortical neurons may occur via specific and sensitive interactions within neuronal mitogen-activated protein kinase and Akt/protein kinase B (PKB) signaling cascades, both implicated in neuronal apoptosis. Quercetin induced potent inhibition of both Akt/PKB and ERK phosphorylation, resulting in reduced phosphorylation of BAD and a strong activation of caspase-3. High quercetin concentrations (30 microM) led to sustained loss of Akt phosphorylation and subsequent Akt cleavage by caspase-3, whereas at lower concentrations (<10 microM) the inhibition of Akt phosphorylation was transient and eventually returned to basal levels. Lower levels of quercetin also induced strong activation of the pro-survival transcription factor cAMP-responsive element-binding protein, although this did not prevent neuronal damage. O-Methylated quercetin metabolites inhibited Akt/PKB to lesser extent and did not induce such strong activation of caspase-3, which was reflected in the lower amount of damage they inflicted on neurons. In contrast, neither quercetin nor its O-methylated metabolites had any measurable effect on c-Jun N-terminal kinase phosphorylation. The glucuronide of quercetin was not toxic and did not evoke any alterations in neuronal signaling, probably reflecting its inability to enter neurons. Together these data suggest that quercetin and to a lesser extent its O-methylated metabolites may induce neuronal death via a mechanism involving an inhibition of neuronal survival signaling through the inhibition of both Akt/PKB and ERK rather than by an activation of the c-Jun N-terminal kinase-mediated death pathway.

c-Jun N-terminal kinase (JNK)-mediated modulation of brain mitochondria function: new target proteins for JNK signalling in mitochondrion-dependent apoptosis

The molecular mechanisms underlying the initiation and control of the release of cytochrome c during mitochondrion-dependent apoptosis are thought to involve the phosphorylation of mitochondrial Bcl-2 and Bcl-x(L). Although the c-Jun N-terminal kinase (JNK) has been proposed to mediate the phosphorylation of Bcl-2/Bcl-x(L) the mechanisms linking the modification of these proteins and the release of cytochrome c remain to be elucidated. This study was aimed at establishing interdependency between JNK signalling and mitochondrial apoptosis. Using an experimental model consisting of isolated, bioenergetically competent rat brain mitochondria, these studies show that (i) JNK catalysed the phosphorylation of Bcl-2 and Bcl-x(L) as well as other mitochondrial proteins, as shown by two-dimensional isoelectric focusing/SDS/PAGE; (ii) JNK-induced cytochrome c release, in a process independent of the permeability transition of the inner mitochondrial membrane (imPT) and insensitive to cyclosporin A; (iii) JNK mediated a partial collapse of the mitochondrial inner-membrane potential (Deltapsim) in an imPT- and cyclosporin A-independent manner; and (iv) JNK was unable to induce imPT/swelling and did not act as a co-inducer, but as an inhibitor of Ca-induced imPT. The results are discussed with regard to the functional link between the Deltapsim and factors influencing the permeability transition of the inner and outer mitochondrial membranes. Taken together, JNK-dependent phosphorylation of mitochondrial proteins including, but not limited to, Bcl-2/Bcl-x(L) may represent a potential of the modulation of mitochondrial function during apoptosis.

On the utility of input selection and pruning for financial distress prediction models

Analyzes the use of linear and neural network models for financial distress classification, with emphasis on the issues of input variable selection and model pruning. A data-driven method for selecting input variables (financial ratios, in this case) is proposed. A case study involving 60 British firms in the period 1997-2000 is used for illustration. It is shown that the use of the Optimal Brain Damage pruning technique can considerably improve the generalization ability of a neural model. Moreover, the set of financial ratios obtained with the proposed selection procedure is shown to be an appropriate alternative to the ratios usually employed by practitioners.

Ensemble prediction for nowcasting with a convection-permitting model—I: description of the system and the impact of radar-derived surface precipitation rates

A key strategy to improve the skill of quantitative predictions of precipitation, as well as hazardous weather such as severe thunderstorms and flash floods is to exploit the use of observations of convective activity (e.g. from radar). In this paper, a convection-permitting ensemble prediction system (EPS) aimed at addressing the problems of forecasting localized weather events with relatively short predictability time scale and based on a 1.5 km grid-length version of the Met Office Unified Model is presented. Particular attention is given to the impact of using predicted observations of radar-derived precipitation intensity in the ensemble transform Kalman filter (ETKF) used within the EPS. Our initial results based on the use of a 24-member ensemble of forecasts for two summer case studies show that the convective-scale EPS produces fairly reliable forecasts of temperature, horizontal winds and relative humidity at 1 h lead time, as evident from the inspection of rank histograms. On the other hand, the rank histograms seem also to show that the EPS generates too much spread for forecasts of (i) surface pressure and (ii) surface precipitation intensity. These may indicate that for (i) the value of surface pressure observation error standard deviation used to generate surface pressure rank histograms is too large and for (ii) may be the result of non-Gaussian precipitation observation errors. However, further investigations are needed to better understand these findings. Finally, the inclusion of predicted observations of precipitation from radar in the 24-member EPS considered in this paper does not seem to improve the 1-h lead time forecast skill.

Ensemble prediction for nowcasting with a convection-permitting model - II: forecast error statistics

A 24-member ensemble of 1-h high-resolution forecasts over the Southern United Kingdom is used to study short-range forecast error statistics. The initial conditions are found from perturbations from an ensemble transform Kalman filter. Forecasts from this system are assumed to lie within the bounds of forecast error of an operational forecast system. Although noisy, this system is capable of producing physically reasonable statistics which are analysed and compared to statistics implied from a variational assimilation system. The variances for temperature errors for instance show structures that reflect convective activity. Some variables, notably potential temperature and specific humidity perturbations, have autocorrelation functions that deviate from 3-D isotropy at the convective-scale (horizontal scales less than 10 km). Other variables, notably the velocity potential for horizontal divergence perturbations, maintain 3-D isotropy at all scales. Geostrophic and hydrostatic balances are studied by examining correlations between terms in the divergence and vertical momentum equations respectively. Both balances are found to decay as the horizontal scale decreases. It is estimated that geostrophic balance becomes less important at scales smaller than 75 km, and hydrostatic balance becomes less important at scales smaller than 35 km, although more work is required to validate these findings. The implications of these results for high-resolution data assimilation are discussed.

Ensemble prediction of transitions of the North Atlantic eddy-driven jet

The consistency of ensemble forecasts from three global medium-range prediction systems with the observed transition behaviour of a three-cluster model of the North Atlantic eddy-driven jet is examined. The three clusters consist of a mid jet cluster taken to represent an undisturbed jet and south and north jet clusters representing southward and northward shifts of the jet. The ensemble forecasts span a period of three extended winters (October–February) from October 2007–February 2010. The mean probabilities of transitions between the clusters calculated from the ensemble forecasts are compared with those calculated from a 23-extended-winter climatology taken from the European Centre for Medium-Range Weather Forecasts 40-Year Re-analysis (ERA40) dataset. No evidence of a drift with increasing lead time of the ensemble forecast transition probabilities towards values inconsistent with the 23-extended-winter climatology is found. The ensemble forecasts of transition probabilities are found to have positive Brier Skill at 15 day lead times. It is found that for the three-extended-winter forecast set, probabilistic forecasts initialized in the north jet cluster are generally less skilful than those initialized in the other clusters. This is consistent with the shorter persistence time-scale of the north jet cluster observed in the ERA40 23-extended-winter climatology. Copyright © 2011 Royal Meteorological Society

Automated tertiary structure prediction with accurate local model quality assessment using the IntFOLD-TS method

The IntFOLD-TS method was developed according to the guiding principle that the model quality assessment would be the most critical stage for our template based modelling pipeline. Thus, the IntFOLD-TS method firstly generates numerous alternative models, using in-house versions of several different sequence-structure alignment methods, which are then ranked in terms of global quality using our top performing quality assessment method – ModFOLDclust2. In addition to the predicted global quality scores, the predictions of local errors are also provided in the resulting coordinate files, using scores that represent the predicted deviation of each residue in the model from the equivalent residue in the native structure. The IntFOLD-TS method was found to generate high quality 3D models for many of the CASP9 targets, whilst also providing highly accurate predictions of their per-residue errors. This important information may help to make the 3D models that are produced by the IntFOLD-TS method more useful for guiding future experimental work

Urban tracer dispersion experiment in London (DAPPLE) 2003: field study and comparison with empirical prediction

The DAPPLE (Dispersion of Air Pollutants and their Penetration into the Local Environment) project seeks to characterise near-field urban atmospheric dispersion using a multidisciplinary approach. In this paper we report on the first tracer dispersion experiment carried out in May 2003. Results of concurrent meteorological measurements are presented. Variations of receptor tracer concentration with time are presented. Meteorological observations suggest that in-street channelling and flow-switching at intersections take place. A comparison between roof top and surface measurements suggest that rapid vertical mixing occurs, and a comparison between a simple dispersion model and maximum concentrations observed are presented

Prediction of the thermal performance of horizontal-coupled ground source heat exchangers

The thermal performance of a horizontal-coupled ground-source heat pump system has been assessed both experimentally and numerically in a UK climate. A numerical simulation of thermal behaviour of the horizontal-coupled heat exchanger for combinations of different ambient air temperatures, wind speeds, refrigerant temperature and soil thermal properties was studied using a validated 2D transient model. The specific heat extraction by the heat exchanger increased with ambient temperature and soil thermal conductivity, however it decreased with increasing refrigerant temperature. The effect of wind speed was negligible.