1,720,974 research outputs found
Abstract 3648: Targeting glypican-2 in neuroblastoma via single domain antibody-based immunotoxins and chimeric antigen receptor T cells
No full textAbstract
Neuroblastoma is the most common extracranial solid tumor in children. Approximately 45% of patients receiving standard therapy relapse and ultimately succumb to metastatic disease. One of the major challenges in the treatment of neuroblastoma and other pediatric cancers is the lack of effective targets. As such, there is an urgent need for a new therapeutic target. Here we demonstrate that glypican-2 (GPC2) protein is highly expressed in nearly half of neuroblastoma cases. High GPC2 expression has been correlated with poor overall survival when compared to patients with low GPC2 expression. The reduction of GPC2 expression inhibits neuroblastoma cell growth and induces tumor cell apoptosis through downregulation of Wnt/β-catenin signaling. We have discovered a group of human single domain antibodies specific for GPC2 and have used them to make two forms of antibody therapeutics, antibody-toxin conjugates (immunotoxins) and chimeric antigen receptor (CAR) T cells. Treatment with the immunotoxin inhibits proliferation of GPC2-positive neuroblastoma cells in vitro and mouse models. The CAR T cells targeting GPC2 suppress the growth of neuroblastoma xenograft tumors and eradicate disseminated neuroblastomas in mice. Our study establishes GPC2 as a new target of antibody-based cancer therapy and demonstrates that single domain-based antibody therapeutics can be used in the treatment of neuroblastoma.
Citation Format: Nan Li, Haiying Fu, Stephen Hewitt, Dimiter Dimitrov, Javed Khan, Mitchell Ho. Targeting glypican-2 in neuroblastoma via single domain antibody-based immunotoxins and chimeric antigen receptor T cells [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2017; 2017 Apr 1-5; Washington, DC. Philadelphia (PA): AACR; Cancer Res 2017;77(13 Suppl):Abstract nr 3648. doi:10.1158/1538-7445.AM2017-3648</jats:p
Evolving Intelligent Systems, eIS
Full text linkThe basic concept, formulation, background, and a panoramic view over the recent research results and open problems in the newly emerging area of research that is on the crossroads of computational intelligence and cybernetics is compressed in this short communication. Intelligent systems can be defined as systems that incorporate some form of reasoning that is typical for humans. Fuzzy Systems are well known for being able to formalize the approximate reasoning that still separates humans from machines. Artificial neural networks have proven to be a useful form of parallel processing of information that employs principles from the organization of the brain. Finally, the evolution is a phenomenon that was initially used to solve optimization problems inspired by the so called 'genetic algorithms' due to D. E. Goldberg and 'genetic programming' due to J. Koza. These types of evolutionary algorithms are mimicking the natural selection that takes place in populations of living creatures over generations. More recently, the evolution of individual systems within their life-span (self-organization, learning through experience, and self-developing) has attracted the attention. These systems called 'evolving' came as a result of the research into the development of practical on-line algorithms that work in real-time and are close to the theoretically optimal, analytical solutions, suitable for non-stationary, non-linear problems of modeling, control, prediction, classification, clustering, signal processing. Due to the limited space and the specific purpose of this communication only the basic elements of the concept will be outlined. This concept represents, in fact, a higher level adaptation that concerns model structure as well as model parameters. It can also be considered as an extension of the multi-model concept known from the control theory, and of the on-line identification of fixed structure fuzzy rule-based models. It can also be considered as an extension of the learning neural networks methods in direction of on-line applications with a structure that can grow and shrink. This new concept of 'evolving intelligent systems' can also be treated in the framework of the knowledge and data integration. Evolutionary, population/generation based computation, can be applied to optimize parameters and features of an individual system, that learns incrementally from incoming data. The specific of this paper lays in the generalization of the recent advances in the development of evolving fuzzy and neuro-fuzzy models and the more analytical angle of consideration through the prism of knowledge evolution as opposed to the usually used data-centred approach. This powerful new concept has been recently introduced by the authors in a series of parallel works and is still under intensive development. It forms the conceptual basis for the development of the truly intelligent systems. A number of applications of this technique to a range of industrial and benchmark processes have been recently reported. Due to the lack of space only some of them will be mentioned primarily with illustrative purpose
Going Beyond Counting First Authors in Author Co-citation Analysis
Full text linkThe present study examines one of the fundamental aspects of author co-citation analysis (ACA) - the way co-citation
counts are defined. Co-citation counting provides the data on which all subsequent statistical analyses and mappings
are based, and we compare ACA results based on two different types of co-citation counting - the traditional type that
only counts the first one among a cited work's authors on the one hand and a non-traditional type that takes into
account the first 5 authors of a cited work on the other hand. Results indicate that the picture produced through this non-traditional author co-citation counting contains more coherent author groups and is therefore considerably clearer. However, this picture represents fewer specialties in the research field being studied than that produced through the traditional first-author co-citation counting when the same number of top-ranked authors is selected and analyzed. Reasons for these effects are discussed
Variations on the Author
Full text link“Variations on the Author” discusses two of Eduardo Coutinho’s recent films (Um Dia na Vida, from 2010, and Últimas Conversas, posthumously released in 2015) and their contribution to the general question of documentary authorship. The director’s filmography is characterized by a consistent yet self-effacing form of authorial self-inscription: Coutinho often features as an interviewer that rather than express opinions propels discourses; an interviewer that is good at listening. This mode of self-inscription characterizes him as an author who is not expressive but who is nonetheless markedly present on the screen. In Um Dia na Vida, however, Coutinho is completely absent form the image, while Últimas Conversas, on the contrary, includes a confessional prologue that moves the director from the margins to the center of his films. This article examines the ways in which these works stand out in the filmography of a director who offers new insights into the notion of cinematic authorship
Appropriate Similarity Measures for Author Cocitation Analysis
Full text linkWe provide a number of new insights into the methodological discussion about author cocitation analysis. We first argue that the use of the Pearson correlation for measuring the similarity between authors’ cocitation profiles is not very satisfactory. We then discuss what kind of similarity measures may be used as an alternative to the Pearson correlation. We consider three similarity measures in particular. One is the well-known cosine. The other two similarity measures have not been used before in the bibliometric literature. Finally, we show by means of an example that our findings have a high practical relevance.information science;Pearson correlation;cosine;similarity measure;author cocitation analysis
Dispelling the Myths Behind First-author Citation Counts
Full text linkWe conducted a full-scale evaluative citation analysis study of scholars in the XML research field to explore just how different from each other author rankings resulting from different citation counting methods actually are, and to demonstrate the capability of emerging data and tools on the Web in supporting more realistic citation counting methods. Our results contest some common arguments for the continued
use of first-author citation counts in the evaluation of scholars, such as high correlations between author rankings by first-author citation counts and other citation
counting methods, and high costs of using more realistic citation counting methods that are not well-supported by the ISI databases. It is argued that increasingly available digital full text research papers make it possible for citation analysis studies to go beyond what the ISI databases have directly supported and to employ more
sophisticated methods
koamabayili/VECTRON-author-checklist: VECTRON author checklist
No full textWe have done our best to complete the author checklist relating to the use of animals in the hut study. Note that the objective for the hut study was to evaluate the IRS treatment applications for residual efficacy against Anopheles mosquitoes, including the local An. coluzzii mosquito population. Cows were only used to attract mosquitoes into the huts and no tests were carried out directly on the cows. The author checklist is intended for use with studies where experiments are carried out on animals, which is why we have had such difficulty in completing this for the hut study, as many of the questions do not relate to how the cows were used
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