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Chimeric Antigen Receptors and Regulatory T Cells:The Potential for HLA-Specific Immunosuppression in Transplantation

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Engineering 2022年第3期8卷 30-43页

作者： Sabrina Wright Conor Hennessy Joanna Hester fadi issa Nuffield Department of Surgical Sciences University of OxfordOxford OX39DUUK

Chimeric antigen receptors(CARs)are a breakthrough in genetic engineering that have revolutio nized the field of adoptive cellular therapy(ACT).Cells expressing these receptors are rerouted to a predefined target by the inclusion of an antigen-specific binding region within the synthetic CAR *** advantage of cells with programmed specificity has been demonstrated clinically in the field of oncology,and it is clear that such cells have greater accuracy,potency,and reduced off-target therapeutic effects compared with their unmodified *** contrast to conventional T cells(Tconvs),regulatory T cells(Tregs)play a major role in suppressing immune activation and regulating the host immune *** expression within Tregs has been proposed as a therapy for autoimmune and inflammatory diseases,graft-versus-host disease(GVHD),and organ transplant rejectio *** the latter,they hold immense potential as mediators of immune tolerance for recipients of ***,current research into CAR-Treg engineering is extremely limited,and there is uncertainty regarding optimal design for therapeutic *** review examines the rationale behind the development of CAR-Tregs,their significance for human transplantation,potential designs,safety considerations,and comparisons of CAR-Tregs in transplantation models to date.

关键词： Chimeric antigen receptors T cell Treg Alloimmunity Bioengineering Transplant Autoimmunity

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A dynamic rule-induction method for classification in data mining

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Journal of Management Analytics 2015年第3期2卷 233-253页

作者： issa Qabajeh fadi Thabtah Francisco Chiclana E-Business Department Canadian University of DubaiDubaiUAE Computing and Informatics Department De Montfort UniversityLeicesterUK Centre for Computational Intelligence De Montfort UniversityLeicesterUK

Rule induction(RI)produces classifiers containing simple yet effective‘If–Then’rules for decision *** algorithms normally based on PRISM suffer from a few drawbacks mainly related to rule pruning and rule-sharing items(attribute values)in the training data *** response to the above two issues,a new dynamic rule induction(DRI)method is *** a rule is produced and its related training data instances are discarded,DRI updates the frequency of attribute values that are used to make the next in-line rule to reflect the data ***,the attribute value frequencies are dynamically adjusted each time a rule is generated rather statically as in *** enables DRI to generate near perfect rules and realistic *** results using different University of California Irvine data sets show competitive performance in regards to error rate and classifier size of DRI when compared to other RI algorithms.

关键词： data mining classification rules rule induction expected accuracy

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