A normal-distribution based rating aggregation method for generating product reputations

With the extensive use of rating systems in the web, and their significance in decision making process by users, the need for more accurate aggregation methods has emerged. The Naïve aggregation method, using the simple mean, is not adequate anymore in providing accurate reputation scores for items [6 ], hence, several researches where conducted in order to provide more accurate alternative aggregation methods. Most of the current reputation models do not consider the distribution of ratings across the different possible ratings values. In this paper, we propose a novel reputation model, which generates more accurate reputation scores for items by deploying the normal distribution over ratings. Experiments show promising results for our proposed model over state-of-the-art ones on sparse and dense datasets.

Vascular endothelial growth factor is an autocrine growth factor, signaling through neuropilin-1 in non-small cell lung cancer

Background The VEGF pathway has become an important therapeutic target in lung cancer, where VEGF has long been established as a potent pro-angiogenic growth factor expressed by many types of tumors. While Bevacizumab (Avastin) has proven successful in increasing the objective tumor response rate and in prolonging progression and overall survival in patients with NSCLC, the survival benefit is however relatively short and the majority of patients eventually relapse. The current use of tyrosine kinase inhibitors alone and in combination with chemotherapy has been underwhelming, highlighting an urgent need for new targeted therapies. In this study, we examined the mechanisms of VEGF-mediated survival in NSCLC cells and the role of the Neuropilin receptors in this process. Methods NSCLC cells were screened for expression of VEGF and its receptors. The effects of recombinant VEGF and its blockade on lung tumor cell proliferation and cell cycle were examined. Phosphorylation of Akt and Erk1/2 proteins was examined by high content analysis and confocal microscopy. The effects of silencing VEGF on cell proliferation and survival signaling were also assessed. A Neuropilin-1 stable-transfected cell line was generated. Cell growth characteristics in addition to pAkt and pErk1/2 signaling were studied in response to VEGF and its blockade. Tumor growth studies were carried out in nude mice following subcutaneous injection of NP1 over-expressing cells. Results Inhibition of the VEGF pathway with anti-VEGF and anti-VEGFR-2 antibodies or siRNA to VEGF, NP1 and NP2 resulted in growth inhibition of NP1 positive tumor cell lines associated with down-regulation of PI3K and MAPK kinase signaling. Stable transfection of NP1 negative cells with NP1 induced proliferation in vitro, which was further enhanced by exogenous VEGF. In vivo, NP1 over-expressing cells significantly increased tumor growth in xenografts compared to controls. Conclusions Our data demonstrate that VEGF is an autocrine growth factor in NSCLC signaling, at least in part, through NP1. Targeting this VEGF receptor may offer potential as a novel therapeutic approach and also support the evaluation of the role of NP1 as a biomarker predicting sensitivity or resistance to VEGF and VEGFR-targeted therapies in the clinical arena.

The tumour-promoting receptor tyrosine kinase, EphB4, regulates expression of Integrin-β8 in prostate cancer cells

Background The EphB4 receptor tyrosine kinase is overexpressed in many cancers including prostate cancer. The molecular mechanisms by which this ephrin receptor influences cancer progression are complex as there are tumor-promoting ligand-independent mechanisms in place as well as ligand-dependent tumor suppressive pathways. Methods We employed transient knockdown of EPHB4 in prostate cancer cells, coupled with gene microarray analysis, to identify genes that were regulated by EPHB4 and may represent linked tumor-promoting factors. We validated target genes using qRT-PCR and employed functional assays to determine their role in prostate cancer migration and invasion. Results We discovered that over 500 genes were deregulated upon EPHB4 siRNA knockdown, with integrin β8 (ITGB8) being the top hit (29-fold down-regulated compared to negative non-silencing siRNA). Gene ontology analysis found that the process of cell adhesion was highly deregulated and two other integrin genes, ITGA3 and ITGA10, were also differentially expressed. In parallel, we also discovered that over-expression of EPHB4 led to a concomitant increase in ITGB8 expression. In silico analysis of a prostate cancer progression microarray publically available in the Oncomine database showed that both EPHB4 and ITGB8 are highly expressed in prostatic intraepithelial neoplasia, the precursor to prostate cancer. Knockdown of ITGB8 in PC-3 and 22Rv1 prostate cancer cells in vitro resulted in significant reduction of cell migration and invasion. Conclusions These results reveal that EphB4 regulates integrin β8 expression and that integrin β8 plays a hitherto unrecognized role in the motility of prostate cancer cells and thus targeting integrin β8 may be a new treatment strategy for prostate cancer.

The time taken for the regional distribution of ventilation to stabilise: An investigation using electrical impedance tomography

Electrical impedance tomography is a novel technology capable of quantifying ventilation distribution in the lung in real time during various therapeutic manoeuvres. The technique requires changes to the patient’s position to place the electrical impedance tomography electrodes circumferentially around the thorax. The impact of these position changes on the time taken to stabilise the regional distribution of ventilation determined by electrical impedance tomography is unknown. This study aimed to determine the time taken for the regional distribution of ventilation determined by electrical impedance tomography to stabilise after changing position. Eight healthy, male volunteers were connected to electrical impedance tomography and a pneumotachometer. After 30 minutes stabilisation supine, participants were moved into 60 degrees Fowler’s position and then returned to supine. Thirty minutes was spent in each position. Concurrent readings of ventilation distribution and tidal volumes were taken every five minutes. A mixed regression model with a random intercept was used to compare the positions and changes over time. The anterior-posterior distribution stabilised after ten minutes in Fowler’s position and ten minutes after returning to supine. Left-right stabilisation was achieved after 15 minutes in Fowler’s position and supine. A minimum of 15 minutes of stabilisation should be allowed for spontaneously breathing individuals when assessing ventilation distribution. This time allows stabilisation to occur in the anterior-posterior direction as well as the left-right direction.

Good for the environment good for health

“First do no harm”. This phrase, attributed to the 19th century surgeon, Thomas Inman, 1 reflects an equivalent phrase found in Epidemics, Book I of the Hippocratic School, “Practise two things in your dealings with disease: either help or do not harm the patient”. Pharmacists have played, and continue to play, an important role in reducing patient harm from medication misadventures. Now, they have a new role to play. The delivery of pharmaceutical care contributes to climate change (e.g. through the embedded carbon in the manufacture and distribution of medicines, disposal of waste, and energy and water use),2 which in turn has a negative impact on health. 3,4 This paradox argues a moral and ethical obligation by pharmacists, to deliver pharmaceutical care more sustainably – do no harm. Sustainability “…. is concerned, on one hand, with resources and how we can preserve them, and, on the other hand, with waste products and how we can best reduce or dispose of them.” 5(p.37) It is about preserving and nurturing Earth’s resources and systems for this generation and future generations to enjoy. Pharmacists play an important role in preventative health strategies such as smoking cessation, promotion of healthier lifestyles and vaccination/immunisation programmes and have the potential to also play a significant role in delivering pharmaceutical care more sustainably. Sustainable pharmaceutical care may be considered a virtuous cycle - what is good for the environment is also good for our health. 5 The good news for community pharmacy owners and managers is that implementing sustainability initiatives in the pharmacy can also have significant financial co-benefits.

Study protocol of the YOU CALL - WE CALL TRIAL: Impact of a multimodal support intervention after a "mild" stroke

Background More than 60% of new strokes each year are "mild" in severity and this proportion is expected to rise in the years to come. Within our current health care system those with "mild" stroke are typically discharged home within days, without further referral to health or rehabilitation services other than advice to see their family physician. Those with mild stroke often have limited access to support from health professionals with stroke-specific knowledge who would typically provide critical information on topics such as secondary stroke prevention, community reintegration, medication counselling and problem solving with regard to specific concerns that arise. Isolation and lack of knowledge may lead to a worsening of health problems including stroke recurrence and unnecessary and costly health care utilization. The purpose of this study is to assess the effectiveness, for individuals who experience a first "mild" stroke, of a sustainable, low cost, multimodal support intervention (comprising information, education and telephone support) - "WE CALL" compared to a passive intervention (providing the name and phone number of a resource person available if they feel the need to) - "YOU CALL", on two primary outcomes: unplanned-use of health services for negative events and quality of life. Method/Design We will recruit 384 adults who meet inclusion criteria for a first mild stroke across six Canadian sites. Baseline measures will be taken within the first month after stroke onset. Participants will be stratified according to comorbidity level and randomised to one of two groups: YOU CALL or WE CALL. Both interventions will be offered over a six months period. Primary outcomes include unplanned use of heath services for negative event (frequency calendar) and quality of life (EQ-5D and Quality of Life Index). Secondary outcomes include participation level (LIFE-H), depression (Beck Depression Inventory II) and use of health services for health promotion or prevention (frequency calendar). Blind assessors will gather data at mid-intervention, end of intervention and one year follow up. Discussion If effective, this multimodal intervention could be delivered in both urban and rural environments. For example, existing infrastructure such as regional stroke centers and existing secondary stroke prevention clinics, make this intervention, if effective, deliverable and sustainable.

Uncertain species distribution: From interpolation to extrapolation

Species distribution models (SDMs) are considered to exemplify Pattern rather than Process based models of a species' response to its environment. Hence when used to map species distribution, the purpose of SDMs can be viewed as interpolation, since species response is measured at a few sites in the study region, and the aim is to interpolate species response at intermediate sites. Increasingly, however, SDMs are also being used to also extrapolate species-environment relationships beyond the limits of the study region as represented by the training data. Regardless of whether SDMs are to be used for interpolation or extrapolation, the debate over how to implement SDMs focusses on evaluating the quality of the SDM, both ecologically and mathematically. This paper proposes a framework that includes useful tools previously employed to address uncertainty in habitat modelling. Together with existing frameworks for addressing uncertainty more generally when modelling, we then outline how these existing tools help inform development of a broader framework for addressing uncertainty, specifically when building habitat models. As discussed earlier we focus on extrapolation rather than interpolation, where the emphasis on predictive performance is diluted by the concerns for robustness and ecological relevance. We are cognisant of the dangers of excessively propagating uncertainty. Thus, although the framework provides a smorgasbord of approaches, it is intended that the exact menu selected for a particular application, is small in size and targets the most important sources of uncertainty. We conclude with some guidance on a strategic approach to identifying these important sources of uncertainty. Whilst various aspects of uncertainty in SDMs have previously been addressed, either as the main aim of a study or as a necessary element of constructing SDMs, this is the first paper to provide a more holistic view.

Information-theoretic analysis of brain white matter fiber orientation distribution functions

We propose a new information-theoretic metric, the symmetric Kullback-Leibler divergence (sKL-divergence), to measure the difference between two water diffusivity profiles in high angular resolution diffusion imaging (HARDI). Water diffusivity profiles are modeled as probability density functions on the unit sphere, and the sKL-divergence is computed from a spherical harmonic series, which greatly reduces computational complexity. Adjustment of the orientation of diffusivity functions is essential when the image is being warped, so we propose a fast algorithm to determine the principal direction of diffusivity functions using principal component analysis (PCA). We compare sKL-divergence with other inner-product based cost functions using synthetic samples and real HARDI data, and show that the sKL-divergence is highly sensitive in detecting small differences between two diffusivity profiles and therefore shows promise for applications in the nonlinear registration and multisubject statistical analysis of HARDI data.

Classic identity negative priming involves accessing semantic representations in the left anterior temporal cortex

Classic identity negative priming (NP) refers to the finding that when an object is ignored, subsequent naming responses to it are slower than when it has not been previously ignored (Tipper, S.P., 1985. The negative priming effect: inhibitory priming by ignored objects. Q. J. Exp. Psychol. 37A, 571-590). It is unclear whether this phenomenon arises due to the involvement of abstract semantic representations that the ignored object accesses automatically. Contemporary connectionist models propose a key role for the anterior temporal cortex in the representation of abstract semantic knowledge (e.g., McClelland, J.L., Rogers, T.T., 2003. The parallel distributed processing approach to semantic cognition. Nat. Rev. Neurosci. 4, 310-322), suggesting that this region should be involved during performance of the classic identity NP task if it involves semantic access. Using high-field (4 T) event-related functional magnetic resonance imaging, we observed increased BOLD responses in the left anterolateral temporal cortex including the temporal pole that was directly related to the magnitude of each individual's NP effect, supporting a semantic locus. Additional signal increases were observed in the supplementary eye fields (SEF) and left inferior parietal lobule (IPL).

Negative priming in naming of categorically related objects: An fMRI study

Ignoring an object slows subsequent naming responses to it, a phenomenon known as negative priming (NP). A central issue in NP research concerns the level of representation at which the effect occurs. As object naming is typically considered to involve access to abstract semantic representations, Tipper 1985 proposed that the NP effect occurred at this level of processing, and other researchers supported this proposal by demonstrating a similar result with categorically related objects (e.g., Allport et al., 1985; Murray, 1995), an effect referred to as semantic NP. However, objects within categories share more physical or structural features than objects from different categories. Consequently, the NP effect observed with categorically related objects might occur at a structural rather than semantic level of representation. We used event related fMRI interleaving overt object naming and image acquisition to demonstrate for the first time that the semantic NP effect activates the left posterior-mid fusiform and insular-opercular cortices. Moreover, both naming latencies and left posterior-mid fusiform cortex responses were influenced by the structural similarity of prime-probe object pairings in the categorically related condition, increasing with the number of shared features. None of the cerebral regions activated in a previous fMRI study of the identity NP effect (de Zubicaray et al., 2006) showed similar activation during semantic NP, including the left anterolateral temporal cortex, a region considered critical for semantic processing. The results suggest that the identity and semantic NP effects differ with respect to their neural mechanisms, and the label "semantic NP" might be a misnomer. We conclude that the effect is most likely the result of competition between structurally similar category exemplars that determines the efficiency of object name retrieval.

Probabilistic multi-tensor estimation using the tensor distribution function

Diffusion weighted magnetic resonance (MR) imaging is a powerful tool that can be employed to study white matter microstructure by examining the 3D displacement profile of water molecules in brain tissue. By applying diffusion-sensitized gradients along a minimum of 6 directions, second-order tensors can be computed to model dominant diffusion processes. However, conventional DTI is not sufficient to resolve crossing fiber tracts. Recently, a number of high-angular resolution schemes with greater than 6 gradient directions have been employed to address this issue. In this paper, we introduce the Tensor Distribution Function (TDF), a probability function defined on the space of symmetric positive definite matrices. Here, fiber crossing is modeled as an ensemble of Gaussian diffusion processes with weights specified by the TDF. Once this optimal TDF is determined, the diffusion orientation distribution function (ODF) can easily be computed by analytic integration of the resulting displacement probability function.

A novel measure of fractional anisotropy based on the tensor distribution function

Fractional anisotropy (FA), a very widely used measure of fiber integrity based on diffusion tensor imaging (DTI), is a problematic concept as it is influenced by several quantities including the number of dominant fiber directions within each voxel, each fiber's anisotropy, and partial volume effects from neighboring gray matter. With High-angular resolution diffusion imaging (HARDI) and the tensor distribution function (TDF), one can reconstruct multiple underlying fibers per voxel and their individual anisotropy measures by representing the diffusion profile as a probabilistic mixture of tensors. We found that FA, when compared with TDF-derived anisotropy measures, correlates poorly with individual fiber anisotropy, and may sub-optimally detect disease processes that affect myelination. By contrast, mean diffusivity (MD) as defined in standard DTI appears to be more accurate. Overall, we argue that novel measures derived from the TDF approach may yield more sensitive and accurate information than DTI-derived measures.

Analyzing multi-fiber reconstruction in high angular resolution diffusion imaging using the tensor distribution function

High-angular resolution diffusion imaging (HARDI) can reconstruct fiber pathways in the brain with extraordinary detail, identifying anatomical features and connections not seen with conventional MRI. HARDI overcomes several limitations of standard diffusion tensor imaging, which fails to model diffusion correctly in regions where fibers cross or mix. As HARDI can accurately resolve sharp signal peaks in angular space where fibers cross, we studied how many gradients are required in practice to compute accurate orientation density functions, to better understand the tradeoff between longer scanning times and more angular precision. We computed orientation density functions analytically from tensor distribution functions (TDFs) which model the HARDI signal at each point as a unit-mass probability density on the 6D manifold of symmetric positive definite tensors. In simulated two-fiber systems with varying Rician noise, we assessed how many diffusionsensitized gradients were sufficient to (1) accurately resolve the diffusion profile, and (2) measure the exponential isotropy (EI), a TDF-derived measure of fiber integrity that exploits the full multidirectional HARDI signal. At lower SNR, the reconstruction accuracy, measured using the Kullback-Leibler divergence, rapidly increased with additional gradients, and EI estimation accuracy plateaued at around 70 gradients.

Provisioning a 3.3 MW PhotoVoltaic generation system onto a distribution authority’s 11 kV rural feeder

This paper describes part of an engineering study that was undertaken to demonstrate that a multi-megawatt Photovoltaic (PV) generation system could be connected to a rural 11 kV feeder without creating power quality issues for other consumers. The paper concentrates solely on the voltage regulation aspect of the study as this was the most innovative part of the study. The study was carried out using the time-domain software package, PSCAD/EMTDC. The software model included real time data input of actual measured load and scaled PV generation data, along with real-time substation voltage regulator and PV inverter reactive power control. The outputs from the model plot real-time voltage, current and power variations throughout the daily load and PV generation variations. Other aspects of the study not described in the paper include the analysis of harmonics, voltage flicker, power factor, voltage unbalance and system losses.

Interplay of MLC, gantry and respiratory motion during DCAT delivery

This study investigated the possible interplay effects arising from the treatment of moving targets using the dynamic conformal arc therapy (DCAT) technique. Dose from a modulated test beam was measured, with and without phantom motion and with and without a 30o arc rotation, using a diode array placed on a sinusoidally moving platform. Measurements were repeated at five different collimator angles (0, 22.5, 45, 67.5 and 90o), at two different dose rates (300 and 600 MU/min). Results showed that the effect of respiratory motion on the measured dose distribution increased slightly when the beams were delivered as arcs, rather than with a static gantry angle, and that this effect increased substantially as the collimator angle was increased from 0o (MLC motion perpendicular to respiratory motion) to 90o (MLC motion parallel to respiratory motion). The dose oscillations arising from interplay between phantom and MLC motion were found to increase in magnitude when the dose rate was increased. These results led to the development of simple recommendations for minimizing the negative effects of motion interplay on DCAT dose distributions