Inhibition of platelet aggregation and 5-HT release by extracts of Australian plants used traditionally as headache treatments

To identify potential migraine therapeutics, extracts of eighteen plants were screened to detect plant constituents affecting ADP induced platelet aggregation and [14C]5-hydroxytryptamine (5-HT) release. Extracts of the seven plants exhibiting significant inhibition of platelet function were reanalysed in the presence of polyvinyl pyrrolidone (PVP) to remove polyphenolic tannins that precipitate proteins. Two of these extracts no longer exhibited inhibition of platelet activity after removal of tannins. However, extracts of Crataegus monogyna, Ipomoea pes-caprae, Eremophila freelingii, Eremophila longifolia, and Asteromyrtus symphyocarpa still potently inhibited ADP induced human platelet [14C]5-HT release in vitro, with levels ranging from 62 to 95% inhibition. I. pes-caprae, and C. monogyna also caused significant inhibition of ADP induced platelet aggregation. All of these plants have been previously used as traditional headache treatments, except for C. monogyna which is used primarily for protective effects on the cardiovascular system. Further studies elucidating the compounds that are responsible for these anti-platelet effects are needed to determine their exact mechanism of action.

Distinguishing between mechanisms of cell aggregation using pair-correlation functions

Many cell types form clumps or aggregates when cultured in vitro through a variety of mechanisms including rapid cell proliferation, chemotaxis, or direct cell-to-cell contact. In this paper we develop an agent-based model to explore the formation of aggregates in cultures where cells are initially distributed uniformly, at random, on a two-dimensional substrate. Our model includes unbiased random cell motion, together with two mechanisms which can produce cell aggregates: (i) rapid cell proliferation, and (ii) a biased cell motility mechanism where cells can sense other cells within a finite range, and will tend to move towards areas with higher numbers of cells. We then introduce a pair-correlation function which allows us to quantify aspects of the spatial patterns produced by our agent-based model. In particular, these pair-correlation functions are able to detect differences between domains populated uniformly at random (i.e. at the exclusion complete spatial randomness (ECSR) state) and those where the proliferation and biased motion rules have been employed - even when such differences are not obvious to the naked eye. The pair-correlation function can also detect the emergence of a characteristic inter-aggregate distance which occurs when the biased motion mechanism is dominant, and is not observed when cell proliferation is the main mechanism of aggregate formation. This suggests that applying the pair-correlation function to experimental images of cell aggregates may provide information about the mechanism associated with observed aggregates. As a proof of concept, we perform such analysis for images of cancer cell aggregates, which are known to be associated with rapid proliferation. The results of our analysis are consistent with the predictions of the proliferation-based simulations, which supports the potential usefulness of pair correlation functions for providing insight into the mechanisms of aggregate formation.

Hydrogel microwell arrays allow the assessment of protease-associated enhancement of cancer cell aggregation and survival

Current routine cell culture techniques are only poorly suited to capture the physiological complexity of tumor microenvironments, wherein tumor cell function is affected by intricate three-dimensional (3D), integrin-dependent cell-cell and cell-extracellular matrix (ECM) interactions. 3D cell cultures allow the investigation of cancer-associated proteases like kallikreins as they degrade ECM proteins and alter integrin signaling, promoting malignant cell behaviors. Here, we employed a hydrogel microwell array platform to probe using a high-throughput mode how ovarian cancer cell aggregates of defined size form and survive in response to the expression of kallikreins and treatment with paclitaxel, by performing microscopic, quantitative image, gene and protein analyses dependent on the varying microwell and aggregate sizes. Paclitaxel treatment increased aggregate formation and survival of kallikrein-expressing cancer cells and levels of integrins and integrin-related factors. Cancer cell aggregate formation was improved with increasing aggregate size, thereby reducing cell death and enhancing integrin expression upon paclitaxel treatment. Therefore, hydrogel microwell arrays are a powerful tool to screen the viability of cancer cell aggregates upon modulation of protease expression, integrin engagement and anti-cancer treatment providing a micro-scaled yet high-throughput technique to assess malignant progression and drug-resistance.

Electrical characteristics of lateral heterostructure organic field-effect bipolar transistors

We describe and discuss the unique electrical characteristics of an organic field-effect transistor in which the active layer consists of a type II lateral heterojunction located approximately midway between the source and drain. The two active semiconductors on either side of the junction transport only one carrier type each, with the other becoming trapped, which leads to devices that operate in only the steady state when there is balanced electron and hole injections from the drain and source. We describe the unique transfer characteristics of such devices in two material systems.

A rating aggregation method for generating product reputations

Many websites offer the opportunity for customers to rate items and then use customers' ratings to generate items reputation, which can be used later by other users for decision making purposes. The aggregated value of the ratings per item represents the reputation of this item. The accuracy of the reputation scores is important as it is used to rank items. Most of the aggregation methods didn't consider the frequency of distinct ratings and they didn't test how accurate their reputation scores over different datasets with different sparsity. In this work we propose a new aggregation method which can be described as a weighted average, where weights are generated using the normal distribution. The evaluation result shows that the proposed method outperforms state-of-the-art methods over different sparsity datasets.

Muramidases found in the foregut microbiome of the Tammar wallaby can direct cell aggregation and biofilm formation

We describe here the role of muramidases present in clones of metagenomic DNA that result in cell aggregation and biofilm formation by Escherichia coli. The metagenomic clones were obtained from uncultured Lachnospiraceae-affiliated bacteria resident in the foregut microbiome of the Tammar wallaby. One of these fosmid clones (p49C2) was chosen for more detailed studies and a variety of genetic methods were used to delimit the region responsible for the phenotype to an open reading frame of 1425 bp. Comparative sequence analysis with other fosmid clones giving rise to the same phenotype revealed the presence of muramidase homologues with the same modular composition. Phylogenetic analysis of the fosmid sequence data assigned these fosmid inserts to recently identified, but uncultured, phylogroups of Lachnospiraceae believed to be numerically dominant in the foregut microbiome of the Tammar wallaby. The muramidase is a modular protein containing putative N-acetylmuramoyl--alanine amidase and an endo-β-N-acetylglucosaminidase catalytic module, with a similar organization and functional properties to some Staphylococcal autolysins that also confer adhesive properties and biofilm formation. We also show here that the cloned muramidases result in the production of extracellular DNA, which appears to be the key for biofilm formation and autoaggregation. Collectively, these findings suggest that biofilm formation and cell aggregation in gut microbiomes might occur via the concerted action of carbohydrate-active enzymes and the production of extracellular DNA to serve as a biofilm scaffold.

Health states for schizophrenia and bipolar disorder within the Global Burden of Disease 2010 Study

A comprehensive revision of the Global Burden of Disease (GBD) study is expected to be completed in 2012. This study utilizes a broad range of improved methods for assessing burden, including closer attention to empirically derived estimates of disability. The aim of this paper is to describe how GBD health states were derived for schizophrenia and bipolar disorder. These will be used in deriving health state-specific disability estimates. A literature review was first conducted to settle on a parsimonious set of health states for schizophrenia and bipolar disorder. A second review was conducted to investigate the proportion of schizophrenia and bipolar disorder cases experiencing these health states. These were pooled using a quality-effects model to estimate the overall proportion of cases in each state. The two schizophrenia health states were acute (predominantly positive symptoms) and residual (predominantly negative symptoms). The three bipolar disorder health states were depressive, manic, and residual. Based on estimates from six studies, 63% (38%-82%) of schizophrenia cases were in an acute state and 37% (18%-62%) were in a residual state. Another six studies were identified from which 23% (10%-39%) of bipolar disorder cases were in a manic state, 27% (11%-47%) were in a depressive state, and 50% (30%-70%) were in a residual state. This literature review revealed salient gaps in the literature that need to be addressed in future research. The pooled estimates are indicative only and more data are required to generate more definitive estimates. That said, rather than deriving burden estimates that fail to capture the changes in disability within schizophrenia and bipolar disorder, the derived proportions and their wide uncertainty intervals will be used in deriving disability estimates.

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.

Introduction to the Proceedings of the Workshop on User-Focused Service Engineering, Consumption and Aggregation (USECA) 2011

The first User-Focused Service Engineering, Consumption and Aggregation workshop (USECA) in 2011 was held in conjunction with the WISE 2011 conference in Sydney, Australia. Web services and related technology are a widely accepted standard architectural paradigm for application development. The idea of reusing existing software components to build new applications has been well documented and supported for the world of enterprise computing and professional developers. However, this powerful idea has not been transferred to end-users who have limited or no computing knowledge. The current methodologies, models, languages and tools developed for Web service composition are suited to IT professionals and people with years of training in computing technologies. It is still hard to imagine any of these technologies being used by business professionals, as opposed to computing professionals. © 2013 Springer-Verlag.

Defining a developmental subtype of bipolar disorder in a sample of nonreferred adults by age at onset

Objective To test the hypothesis that the age at onset of bipolar disorder would identify a developmental subtype of bipolar disorder in adults characterized by increased levels of irritability, chronic course, rapid cycling, and comorbidity with attention deficit hyperactivity disorder. Methods Forty-four adult subjects diagnosed with bipolar disorder were selected from large family studies of youth with and without attention deficit hyperactivity disorder. These subjects were stratified by the age at onset in childhood (younger than 13 years; n = 8, 18%), adolescence (13–18 years; n = 12, 27%, or adulthood (older than 19 years; n = 24, 55%). All subjects were administered structure diagnostic interviews and a brief cognitive battery. Results In contrast with adult-onset bipolar disorder, child-onset bipolar disorder was associated with a longer duration of illness, more irritability than euphoria, a mixed presentation, a more chronic or rapid-cycling course, and increased comorbidity with childhood disruptive behavior disorders and anxiety disorders. Conclusion Stratification by age at onset of bipolar disorder identified subgroups of adult subjects with differing clinical correlates. This pattern of correlates is consistent with findings documented in children with pediatric bipolar disorder and supports the hypothesis that child-onset bipolar disorder may represent a developmental subtype of the disorder.

Nanoporous Pt with High Surface Area by Reaction-Limited Aggregation of Nanoparticles

Nanoporous structures with high active surface areas are critical for a variety of applications. Here, we present a general templateless strategy to produce such porous structures by controlled aggregation of nanostructured subunits and apply the principles for synthesizing nanoporous Pt for electrocatalytic oxidation of methanol. The nature of the aggregate produced is controlled by tuning the electrostatic interaction between surfactant-free nanoparticles in the solution phase. When the repulsive force between the particles is very large, the particles are stabilized in the solution while instantaneous aggregation leading to fractal-like structures results when the repulsive force is very low. Controlling the repulsive interaction to an optimum, intermediate value results in the formation of compact structures with very large surface areas. In the case of Pt, nanoporous clusters with an extremely high specific surface area (39 m(2)/g) and high activity for methanol oxidation have been produced. Preliminary investigations indicate that the method is general and can be easily extended to produce nanoporous structures of many inorganic materials.

Exceptional adhesive and gelling properties of fibrous nanoscopic tapes of self-assembled bipolar urethane amides of L-phenylalanine

Seven L-phenylalanine based alkyl (monopolar) and alkanediyl (bipolar) derivatives are synthesized; while the bipolar urethane amides form gels and show strong adhesive properties, the monopolar analogues form fibrous nanoscopic cloth-like tapes.

An accurate rating aggregation method for generating item reputation

Many websites presently provide the facility for users to rate items quality based on user opinion. These ratings are used later to produce item reputation scores. The majority of websites apply the mean method to aggregate user ratings. This method is very simple and is not considered as an accurate aggregator. Many methods have been proposed to make aggregators produce more accurate reputation scores. In the majority of proposed methods the authors use extra information about the rating providers or about the context (e.g. time) in which the rating was given. However, this information is not available all the time. In such cases these methods produce reputation scores using the mean method or other alternative simple methods. In this paper, we propose a novel reputation model that generates more accurate item reputation scores based on collected ratings only. Our proposed model embeds statistical data, previously disregarded, of a given rating dataset in order to enhance the accuracy of the generated reputation scores. In more detail, we use the Beta distribution to produce weights for ratings and aggregate ratings using the weighted mean method. Experiments show that the proposed model exhibits performance superior to that of current state-of-the-art models.