Resting respiratory tract dendritic cells preferentially stimulate T helper cell type 2 (Th2) responses and require obligatory cytokine signals for induction of Th1 immunity

Consistent with their role in host defense, mature dendritic cells (DCs) from central lymphoid organs preferentially prime for T helper cell type 1 (Th1)-polarized immunity. However, the "default" T helper response at mucosal surfaces demonstrates Th2 polarity, which is reflected in the cytokine profiles of activated T cells from mucosal lymph nodes. This study on rat respiratory tract DCs (RTDCs) provides an explanation for this paradox. We demonstrate that freshly isolated RTDCs are functionally immature as defined in vitro, being surface major histocompatibility complex (MHC) II lo, endocytosishi, and mixed lymphocyte reactionlo, and these cells produce mRNA encoding interleukin (IL)-10. After ovalbumin (OVA)-pulsing and adoptive transfer, freshly isolated RTDCs preferentially stimulated Th2-dependent OVA-specific immunoglobulin (Ig)G1 responses, and antigen-stimulated splenocytes from recipient animals produced IL-4 in vitro. However, preculture with granulocyte/macrophage colony stimulating factor increased their in vivo IgG priming capacity by 2-3 logs, inducing production of both Th1- and Th2-dependent IgG subclasses and high levels of IFN-gamma by antigen-stimulated splenocytes. Associated phenotypic changes included upregulation of surface MHC II and B7 expression and IL-12 p35 mRNA, and downregulation of endocytosis, MHC II processing- associated genes, and IL-10 mRNA expression. Full expression of IL-12 p40 required additional signals, such as tumor necrosis factor alpha or CD40 ligand. These results suggest that the observed Th2 polarity of the resting mucosal immune system may be an inherent property of the resident DC population, and furthermore that mobilization of Th1 immunity relies absolutely on the provision of appropriate microenvironmental costimuli.     

Chemotherapy in non-small cell lung cancer: a review

Lung cancer, of which non-small cell carcinoma is the most common, has been a significant therapeutic challenge for decades and will remain so for decades to come. Despite its prevalence, progress in the management of non-small cell lung cancer has been relatively slow. This is in part due to the pessimism of most physicians treating this disease, which has resulted in a relatively lackadaisical attitude with regards to clinical trials when compared to other solid tumours like breast or colorectal cancers. Nevertheless, the past decade has seen significant progress, specifically with regards to the management of locally advanced disease. Chemotherapy, though shown to be biologically active in non-small cell lung cancer, is considered an ineffective palliative tool in the setting of metastatic disease due to its toxicities and the "less than encouraging" response rates generated by the cisplatin-based combination regimen which is generally considered to be the most active currently available. The advent of new active agents such as paclitaxel and vinorelbine which are potentially less toxic may change this view. Conversely, the response rate of locally advanced disease to chemotherapy is significantly higher and this has resulted in numerous multimodality trials of neoadjuvant chemotherapy prior to surgery and/or radiation. To date, a number of randomised trials have shown that this approach can result in significant survival benefit for patients with locally advanced disease. An alternative approach makes use of the potential synergism between certain chemotherapeutic agents (such as cisplatin) and radiation when used concurrently. However, data on concurrent chemoradiotherapy in locally advanced disease have been largely based on single-arm studies and are inconclusive. Three randomised trials on concurrent chemoradiotherapy have been shown benefit for the use of combined modality in locally advanced disease. Hence, treatment of locally advanced disease should include chemotherapy as part of the combined modality approach. However, the optimal sequencing of these modalities would require well-designed randomised trials to determine.     

Spatial and temporal variability of macrophyte cover and productivity in the eastern Amazon floodplain: A remote sensing approach

Herbaceous aquatic macrophytes cover extensive areas on the floodplains of the Amazon basin and are an important habitat and input of organic carbon. These communities have large intra- and inter-annual variability, and characterization of this variability is necessary to quantify the role of macrophytes in the ecology and biogeochemistry of the floodplain. A novel approach for mapping the temporal evolution of aquatic vegetation in the Amazon floodplain, which could be adapted to other spatially and temporally changing environments, is presented. Macrophyte cover varied seasonally and inter-annually, ranging between 104 and 198 km² for the floodplain examined (total area, 984 km²). The observed evolution of plant distribution indicated a spatial and temporal partition of macrophyte communities into short-lived and annual groups. A simulation of macrophyte net primary production (NPP) based on the mapping results indicated that at least 3% of NPP could be attributed to the short-lived communities. The present results suggest that significant changes in the macrophyte's contribution to carbon cycling in the Amazon floodplain could occur as a result of the predicted increase in frequency of drought years for the Amazon system due to climate change.     

Numerical study of the mixture formation process in a four-stroke GDI engine for two-wheel applications

Guidelines for managing the mixture formation process in a high-performance four-stroke Gasoline Direct Injection (GDI) engine for two-wheel applications are discussed, as derived from a multidimensional modelling of the in-cylinder processes. Gasoline adduction from a multi-hole injector is simulated by resorting to a properly developed model that accounts for the dependence of the initial droplets size distribution upon injection pressure. The model portability is preliminary demonstrated by comparison with experimental measurements carried out on sprays entering a confined vessel at controlled conditions.The simulation of different engine operating conditions highlights the capability to work under the so-called “mixed mode” boosting with spray guided mixture formation.     

A web-based formative assessment tool for Masters students: A pilot study

The use of web-based learning and assessment tools is growing in tertiary institutions around the world. To date, very few papers have reported the development and evaluation of a web-based formative assessment tool for postgraduate students. The aim of the present paper was to report on the development and evaluation of an online formative assessment tool for this student group. The web-based formative assessment tool was evaluated by a sample of undergraduate students, postgraduate students and academic staff within a psychology department in order to determine the suitability and sensitivity of the tool. The results of this pilot test suggest that the development of such a tool is both appropriate and feasible for Masters students studying psychology.     

A computational model for developing semantic web-based educational systems

Recently, some initiatives to start the so-called semantic web-based educational systems (SWBES) have emerged in the field of artificial intelligence in education (AIED). The main idea is to incorporate semantic web resources to the design of AIED systems aiming to update their architectures to provide more adaptability, robustness and richer learning environments. However, the construction of such systems is highly complex and faces several challenges in terms of software engineering and artificial intelligence aspects. This paper presents a computational model for developing SWBES focusing on the problem of how to make the development easier and more useful for both developers and authors. In order to illustrate the features of the proposed model, a case study is presented. Furthermore, a discussion about the results regarding the computational model construction is available.     

Skill Memory in Biped Locomotion

Robots must be able to adapt their motor behavior to unexpected situations in order to safely move among humans. A necessary step is to be able to predict failures, which result in behavior abnormalities and may cause irrecoverable damage to the robot and its surroundings, i.e. humans. In this paper we build a predictive model of sensor traces that enables early failure detection by means of a skill memory. Specifically, we propose an architecture based on a biped locomotion solution with improved robustness due to sensory feedback, and extend the concept of Associative Skill Memories (ASM) to periodic movements by introducing several mechanisms into the training workflow, such as linear interpolation and regression into a Dynamical Motion Primitive (DMP) system such that representation becomes time invariant and easily parameterizable. The failure detection mechanism applies statistical tests to determine the optimal operating conditions. Both training and failure testing were conducted on a DARwIn-OP inside a simulation environment to assess and validate the failure detection system proposed. Results show that the system performance in terms of the compromise between sensitivity and specificity is similar with and without the proposed mechanism, while achieving a significant data size reduction due to the periodic approach taken.     

Relational Learning with GPUs: Accelerating Rule Coverage

Relational learning algorithms mine complex databases for interesting patterns. Usually, the search space of patterns grows very quickly with the increase in data size, making it impractical to solve important problems. In this work we present the design of a relational learning system, that takes advantage of graphics processing units (GPUs) to perform the most time consuming function of the learner, rule coverage. To evaluate performance, we use four applications: a widely used relational learning benchmark for predicting carcinogenesis in rodents, an application in chemo-informatics, an application in opinion mining, and an application in mining health record data. We compare results using a single and multiple CPUs in a multicore host and using the GPU version. Results show that the GPU version of the learner is up to eight times faster than the best CPU version.     

Spatial data warehouses and spatial OLAP come towards the cloud: design and performance

Cloud computing systems handle large volumes of data by using almost unlimited computational resources, while spatial data warehouses (SDWs) are multidimensional databases that store huge volumes of both spatial data and conventional data. Cloud computing environments have been considered adequate to host voluminous databases, process analytical workloads and deliver database as a service, while spatial online analytical processing (spatial OLAP) queries issued over SDWs are intrinsically analytical. However, hosting a SDW in the cloud and processing spatial OLAP queries over such database impose novel obstacles. In this article, we introduce novel concepts as cloud SDW and spatial OLAP as a service, and afterwards detail the design of novel schemas for cloud SDW and spatial OLAP query processing over cloud SDW. Furthermore, we evaluate the performance to process spatial OLAP queries in cloud SDWs using our own query processor aided by a cloud spatial index. Moreover, we describe the cloud spatial bitmap index to improve the performance to process spatial OLAP queries in cloud SDWs, and assess it through an experimental evaluation. Results derived from our experiments revealed that such index was capable to reduce the query response time from 58.20 up to 98.89 %.     

Visually impaired people and the emerging connected TV: a comparative study of TV and Web applications’ accessibility

With the TV signal digitization and the current market growth of connected TVs, the authors envision the appearance of accessibility barriers to visually impaired persons. The paper addresses the following hypothesis: (1) visually impaired users want to extend their TV usage to explore new TV features; (2) TV applications are in less conformance with accessibility guidelines compared to their Desktop versions. Additionally, the authors wanted to assess whether guideline conformance reflected real TV accessibility problems experienced by users. The methods used for this study included surveys aimed at characterizing the interest of the visually impaired population regarding the use of TV, and specifically of Web applications on TV, an automated accessibility evaluation to compare TV and Desktop versions of the same Web application, to understand their conformance with accessibility guidelines, and a user study where participants with visual impairments were asked to perform some tasks on both versions. From the survey, we confirmed that people with visual disabilities are interested in extra features on their TV. Results from the automated accessibility evaluation show that TV applications are in a significantly better level of conformance with accessibility guidelines. The user study has illustrated that users were unable to complete any task using the TV versions of the applications. The results from these studies demonstrated that the new features that come with connected TVs still have a long way to go in order to be accessible by all. Furthermore, they lead us to concur with other works that automated evaluations are not enough to assess the accessibility of a Web page.