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Academic literature on the topic 'Tcjr'

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Published: 26 July 2024

Last updated: 27 July 2024

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Journal articles on the topic "Tcjr"

1

Tibbetts, Randal S., Jennifer L. Jensen, Cheryl L. Olson, Fred D. Wang, and David M. Engman. "The DnaJ family of protein chaperones in Trypanosoma cruzi1Note: Nucleotide sequence data reported in this paper have been submitted to the GenBank™ data base with the following accession numbers: tcj1, L42541; tcj2, L42549; tcj3, L46818; tcj4, L46819.1." Molecular and Biochemical Parasitology 91, no. 2 (March 1998): 319–26. http://dx.doi.org/10.1016/s0166-6851(97)00214-4.

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Dilchert, Janine, Martin Hofmann, Felix Unverdorben, Roland Kontermann, and Sebastian Bunk. "Mammalian Display Platform for the Maturation of Bispecific TCR-Based Molecules." Antibodies 11, no. 2 (May 10, 2022): 34. http://dx.doi.org/10.3390/antib11020034.

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Bispecific T cell receptor (TCR)-based molecules capable of redirecting and activating T cells towards tumor cells represent a novel and promising class of biotherapeutics for the treatment of cancer. Usage of TCRs allows for targeting of intracellularly expressed and highly selective cancer antigens, but also requires a complex maturation process to increase the naturally low affinity and stability of TCRs. Even though TCR domains can be matured via phage and yeast display, these techniques share the disadvantages of non-human glycosylation patterns and the need for a later reformatting into the final bispecific format. Here, we describe the development and application of a Chinese Hamster Ovary (CHO) display for affinity engineering of TCRs in the context of the final bispecific TCR format. The recombinase-mediated cassette exchange (RCME)-based system allows for stable, single-copy integration of bispecific TCR molecules with high efficiency into a defined genetic locus of CHO cells. We used the system to isolate affinity-increased variants of bispecific T cell engaging receptor (TCER) molecules from a library encoding different CDR variants of a model TCR targeting preferentially expressed antigen in melanoma (PRAME). When expressed as a soluble protein, the selected TCER molecules exhibited strong reactivity against PRAME-positive tumor cells associated with a pronounced cytokine release from activated T cells. The obtained data support the usage of the CHO display-based maturation system for TCR affinity maturation in the context of the final bispecific TCER format.

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Bunk, Sebastian, Martin Hofmann, Felix Unverdorben, Meike Hutt, Gabriele Pszolla, Frank Schwöbel, Claudia Wagner, et al. "Effective Targeting of PRAME-Positive Tumors with Bispecific T Cell-Engaging Receptor (TCER®) Molecules." Blood 134, Supplement_1 (November 13, 2019): 3368. http://dx.doi.org/10.1182/blood-2019-129958.

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T cell receptors (TCRs) naturally recognize human leukocyte antigen (HLA)-bound peptides derived from foreign and endogenous proteins regardless of their extracellular or intracellular location. Preferentially expressed antigen in melanoma (PRAME) has been shown to be expressed at high levels in a variety of cancer cells while being absent or present only at very low levels in normal adult tissues except testis. In contrast to most other cancer/testis antigens, PRAME is expressed not only in solid tumors but also in leukemia and myeloma cells. Immunotherapy with bispecific T cell engagers has emerged as a novel and promising treatment modality for malignant diseases, however, antibody-based approaches (ie. blinatumomab) are restricted to few surface antigens such as CD19 or BCMA. Immatics has developed bispecific T cell-engaging receptors (TCER®) that are fusion proteins consisting of an affinity-maturated TCR and a humanized T cell-recruiting antibody with an effector function-silenced IgG1 Fc part. TCER® molecules confer extended half-life together with antibody-like stability and manufacturability characteristics. The molecular design allows for effective redirection of T cells towards target peptide-HLA selectively expressed in tumor tissues. Here we present proof-of-concept data from a TCER® program targeting a PRAME-derived peptide bound to HLA-A*02:01. We confirmed the abundant presence of the target peptide-HLA in several cancer indications and its absence in relevant human normal tissues by using the XPRESIDENT® target discovery engine, which combines quantitative mass spectrometry, transcriptomics and bioinformatics. Yeast surface display technology was used to maturate the stability and affinity of a parental human TCR recognizing PRAME with high functional avidity and specificity. During maturation we applied XPRESIDENT®-guided off-target toxicity screening, incorporating the world's largest normal tissue immunopeptidome database, to deselect cross-reactive candidate TCRs. The maturated TCRs were engineered into the TCER® scaffold and production in Chinese hamster ovary (CHO) cells generated highly stable molecules with low tendency for aggregation as confirmed during stress studies. Following TCR maturation, the TCER® molecules exhibited an up to 10,000-fold increased binding affinity towards PRAME when compared to the parental TCR. The high affinity correlated with potent in vitro anti-tumor activity requiring only low picomolar concentrations of TCER® molecules to induce half-maximal lysis of tumor cells expressing the target at physiological levels. Furthermore, using a tumor xenograft model in immunodeficient NOG mice, we could demonstrate significant growth inhibition of established tumors upon intravenous injection of TCER® molecules. Pharmacokinetic profiling in NOG mice determined a terminal half-life of more than 4 days, compatible with a once weekly dosing regimen in patients. For the safety assessment, we measured killing of more than 20 different human normal tissue cell types derived from high risk organs. Notably, we could confirm a favorable safety window for selected TCER® molecules, which induced killing of most normal tissue cells only at significantly higher concentrations than required for killing of tumor cells. To further support safety of TCER® molecules, we also performed a comprehensive characterization of potential off-target peptides selected from the XPRESIDENT® normal tissue database based on its high similarity to the sequence of the target peptide or based on data from alternative screening approaches. In summary, the efficacy, safety and manufacturability data to be presented provide preclinical proof-of-concept for a novel bispecific T cell-engaging receptor (TCER®) molecule targeting PRAME for treatment of various malignant diseases. Disclosures Bunk: Immatics: Employment. Hofmann:Immatics: Employment. Unverdorben:Immatics: Employment. Hutt:Immatics: Employment. Pszolla:Immatics: Employment. Schwöbel:Immatics: Employment. Wagner:Immatics: Employment. Yousef:Immatics: Employment. Schuster:Immatics: Employment. Missel:Immatics: Employment. Schoor:Immatics: Employment. Weinschenk:Immatics: Employment, Equity Ownership. Singh-Jasuja:Immatics: Employment, Equity Ownership. Maurer:Immatics: Employment. Reinhardt:Immatics: Employment, Equity Ownership.

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4

Fontenot, Andrew P., Michael T. Falta, Brian M. Freed, Lee S. Newman, and Brian L. Kotzin. "Identification of Pathogenic T Cells in Patients with Beryllium-Induced Lung Disease." Journal of Immunology 163, no. 2 (July 15, 1999): 1019–26. http://dx.doi.org/10.4049/jimmunol.163.2.1019.

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Abstract Chronic beryllium disease (CBD) is caused by beryllium exposure and is characterized by granulomatous inflammation with accumulation of CD4+ T cells in the lung. We analyzed TCR β-chain and α-chain genes expressed by these CD4+ T cells. In the lungs of individual patients, as well as among four of five CBD patients studied, different oligoclonal expansions within the Vβ3 subset were found to express homologous or even identical CDR3 amino acid sequences. These related expansions were specific for CBD patients, were compartmentalized to lung, and persisted at high frequency in patients with active disease. Limiting dilution cloning and analysis of coexpressed TCR α-chain genes confirmed that these TCRs were selectively expanded by a common Ag involving beryllium. Overall, homologous TCR β- and α-chains showed identical V regions and invariant charged residues within the CDR3 but considerable variability in TCRJ usage. Remarkably, CBD patients expressing nearly identical TCRs did not share common HLA-DRB1 or DQ alleles. These results implicate particular CD4+ cells in the pathogenesis of CBD and provide insight into how beryllium is recognized in human disease.

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Abdulazim, Amr, Nora Prochnow, and Tara Taeihagh. "TCR or Not TCR?" Journal of Oral and Maxillofacial Surgery 69, no. 10 (October 2011): 2483–84. http://dx.doi.org/10.1016/j.joms.2011.05.028.

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6

Khangura, R. K., and D. W. Wright. "First Report of Club Root Caused by Plasmodiophora brassicae on Canola in Australia." Plant Disease 96, no. 7 (July 2012): 1075. http://dx.doi.org/10.1094/pdis-11-11-1006-pdn.

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In 2009, a disease survey was conducted in 97 commercial canola (Brassica napus L.) fields in Western Australia by the Department of Agriculture and Food, Western Australia (DAFWA). In about 20% of the fields from the northern agricultural region of Western Australia, small patches were observed where canola plants showed symptoms of stunting and wilting. These plants were collected and roots of affected plants were washed thoroughly and examined for the presence of root disease. Small galls and clublike structures were observed on the secondary roots and sometimes on the main root of the affected plants. Examination of thin free hand sections from the root galls revealed that several cortical cells were enlarged and full of resting spores. The diameter of resting spores ranged between 2.5 and 3.0 μm. Plasmodia and zoosporangia were also observed in the root hairs. The identity of Plasmodiophora brassicae Woronin was confirmed by PCR using a modified method of Cao et al. 2007 (1). DNA from spores and slices of the galls of 14 different samples were extracted using DNeasy plant mini kit (QIAGEN Australia) as per manufacturer's instructions. Samples were disrupted by placing them into MPBIO tube A and placed in the Fast Prep machine at speed of 6 ms–1 for 40 s. This was repeated twice. The species-specific primers TC1F (5′-GTGGTCGAACTTCATTAAATTTGGGCTCTT-3′)/TC1R (5′-TTCACCTACGGAACGTATATGTGCATGTGA-3′) and TC2F (5′-AAACAACGAGTCAGCTTGAATGCTAGTGTG-3′)/TC2R (5′-CTTTAGTTGTGTTTCGGCTAGGATGGTTCG-3′) were used (1). The primers TC1F and TC1R failed to produce a PCR product of 548-bp size but using the primers TC2F and TC2R the PCR reaction resulted in a 519- bp fragment. Seven out of 14 samples gave positive results for P. brassicae with primers TC2F and TC2R. This indicates that the P. brassicae pathotype from Western Australia may be different than the one found in Alberta, Canada. However, pathotypes of P. brassicae from brassica vegetables from Australia have been found similar to the populations of P. brassicae present in the United States (2). Pathogenicity of P. brassicae was tested by dipping roots of five 10-day-old canola plants var. Cobbler in a spore suspension (1 × 106 resting spores/ml). Roots of five control plants were dipped in sterile water. Five weeks after inoculation, small galls were observed on the roots of three inoculated plants and the control plants remained symptomless. Resting spores were recovered from the galls developed on the roots of affected plants. Presence of P. brassicae in the affected roots was further confirmed by PCR using the method described above. To our knowledge, this is the first report of club root of canola in Australia. Club root is reported from vegetable brassicas and white mustard (Sinapis alba L.) in Australia. Club root has become a serious disease of canola in Canada since its detection in Alberta in 2006 (3). The resting spores of the fungus can survive for several years in soil, and therefore, this disease could pose a significant threat to canola production in Western Australia. References: (1) Cao et al. Plant Dis. 91:80, 2007. (2) Donald et al. Ann. App. Biol. 148:239, 2006. (3) S. Streklov et al. Can. J. Plant Pathol. 28:467, 2006.

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Trop, Sébastien, Michele Rhodes, David L. Wiest, Patrice Hugo, and Juan Carlos Zúñiga-Pflücker. "Competitive Displacement of pTα by TCR-α During TCR Assembly Prevents Surface Coexpression of Pre-TCR and αβ TCR." Journal of Immunology 165, no. 10 (November 15, 2000): 5566–72. http://dx.doi.org/10.4049/jimmunol.165.10.5566.

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8

Dempsey, Laurie A. "TCR tuning." Nature Immunology 13, no. 6 (May 18, 2012): 533. http://dx.doi.org/10.1038/ni.2335.

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9

Bell, Elaine. "TCR docking." Nature Reviews Immunology 2, no. 9 (September 2002): 626. http://dx.doi.org/10.1038/nri898.

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10

Jones, Daniel S., Peter Reichardt, Mandy L. Ford, Lindsay J. Edwards, and Brian D. Evavold. "TCR Antagonism by Peptide Requires High TCR Expression." Journal of Immunology 181, no. 3 (July 18, 2008): 1760–66. http://dx.doi.org/10.4049/jimmunol.181.3.1760.

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Dissertations / Theses on the topic "Tcjr"

1

Groves, Tim C. "Pre-TCR and TCR-Ãß signaling during T cell development." Thesis, National Library of Canada = Bibliothèque nationale du Canada, 1997. http://www.collectionscanada.ca/obj/s4/f2/dsk2/ftp03/NQ27657.pdf.

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2

Currie, James. "Stochastic modelling of TCR binding." Thesis, University of Leeds, 2012. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.590430.

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A fundamental process in the immune response to infection is the activation of T cells following contact with antigen presenting cells. This activation occurs after T cell receptors on the surface of T cells bind to immunogenic peptides expressed on the surface of antigen presenting cells. The binding of T cell receptors to ligands not only leads to the activation of T cells, it is also key to T cell selection in the thymus and the maintenance of a diverse T cell receptor repertoire. T cell receptor bindings are converted into a signal which activates a T cell but there is no universal theory which governs this process. There is experimental evidence to suggest that receptor-ligand bindings must be sufficiently long to elicit a T cell response. and that counting devices in the T cell work to allow signal accumulation, decoding and translation into biological responses. In view of these results, this thesis uses mathematical models to explore the timescales associated with T cell responses. A stochastic criterion that T cell responses occur after N receptor-ligand complexes have been bound for at least a dwell time, T, each, is used. The first model of receptor-ligand binding, in conjunction with the stochastic criterion, supports the affinity threshold hypothesis for thymic selection and agrees with the experimentally established ligand hierarchy for thymic negative selection. The initial model of ligand-receptor binding is then extended to include feedback responses, bivalent receptor binding and ligand diffusion through the immunological synapse. By including these mechanisms, the models agree with an array of experimental hypotheses which include: T cells exhibit a digital response to ligand. bivalent T cell receptor engagement stabilises receptor-ligand bindings and one ligand is sufficient to elicit a T cell response.

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3

Lacroix, France. "T cell receptor (TCR) for antigen: A comparative study between the TCR alpha/beta and TCR gamma/delta subsets in noninfected and HIV infected individuals." Thesis, University of Ottawa (Canada), 1993. http://hdl.handle.net/10393/6937.

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HIV infection is associated with characteristic quantitative changes in T-lymphocyte subsets: progressive depletion of the CD4$\sp{+}$ T-lymphocytes and an increased number of the CD8$\sp{+}$ T-lymphocyte. In this study, I report the results of a flow cytometric analysis of the expression of CD3, CD4, CD8, TCR$\alpha$/$\beta$, and TCR$\gamma$/$\delta$ antigens. I observed that CD8$\sp{+}$TCR$\alpha$/$\beta\sp{+}$ cells increased early in HIV disease (p 0.01) whereas the frequency of CD4$\sp{+}$TCR$\alpha$/$\beta\sp{+}$ cells was relatively unchanged. The frequency of TCR$\gamma$/$\delta\sp{+}$ cells remained unchanged. However, the mean fluorescence intensity (MFI), reflecting surface antigenic density, varied and allowed a clear distinction among different stages of infection. The expression of three activation markers (HLA-DR, CD38, CD57) was clearly increased in HIV infected individuals. The TCR$\alpha$/$\beta$ subset showed more substantial variation for activation markers. In the TCR$\gamma$/$\delta$ subset, the CD57 antigen seemed to be the most affected by the state of the disease and showed the greatest increase (p 0.01). (Abstract shortened by UMI.)

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4

Sommermeyer, Daniel. "Generation of dual T cell receptor (TCR) T cells by TCR gene transfer for adoptive T cell therapy." Doctoral thesis, Humboldt-Universität zu Berlin, Mathematisch-Naturwissenschaftliche Fakultät I, 2010. http://dx.doi.org/10.18452/16051.

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Die Herstellung von T-Zellen mit definierten Spezifitäten durch den Transfer von T-Zellrezeptor (TCR) Genen ist eine effiziente Methode, um Zellen für eine Immuntherapie bereitzustellen. Eine besondere Herausforderung ist dabei, ein ausreichend hohes Expressionsniveau des therapeutischen TCR zu erreichen. Da T-Zellen mit einem zusätzlichen TCR ausgestattet werden, entsteht eine Konkurrenzsituation zwischen dem therapeutischen und dem endogenen TCR. Bevor diese Arbeit begonnen wurde war nicht bekannt, welche TCR nach einem Gen-Transfer exprimiert werden. Daher haben wir Modelle etabliert, in denen TCR Gene in Maus und humane T-Zellen mit definierten endogenen TCR transferiert wurden. Die Expression beider TCR wurde mithilfe von Antikörpern und MHC-Multimeren analysiert. Diese Modelle haben gezeigt, dass bestimmte TCR andere TCR von der Zelloberfläche verdrängen können. Dies führte in einem Fall zu einer vollständigen Umkehr der Antigenspezifität. Aufgrund dieser Ergebnisse haben wir das Konzept von „starken“ (gut exprimierten) und „schwachen“ (schlecht exprimierten) TCR vorgeschlagen. Zusätzlich wurde die Verdrängung „schwacher“ und „starker“ humaner TCR durch Maus TCR beobachtet. Parallel dazu wurde berichtet, dass die konstanten (C) Regionen von Maus TCR für die erhöhte Expression auf humanen Zellen verantwortlich sind. Dies führte zu einer Strategie zur Verbesserung der Expression humaner TCR, die auf dem Austausch der humanen C-Regionen durch die von Maus TCR basiert (Murinisierung). Ein Problem ist dabei die mögliche Immunogenität dieser hybriden Konstrukte. Deshalb haben wir jene Bereiche der Maus C-Regionen identifiziert, die für die erhöhte Expression verantwortlich sind. In der TCRalpha Kette wurden vier und in der TCRbeta Kette fünf Aminosäuren gefunden, die ausreichend für diesen Effekt waren. Primäre humane T-Zellen mit TCR, die diese neun „Maus“ Aminosäuren enthielten, zeigten eine bessere Funktionalität als T-Zellen mit Wildtyp TCR.
The in vitro generation of T cells with a defined antigen specificity by T cell receptor (TCR) gene transfer is an efficient method to create cells for immunotherapy. One major challenge of this strategy is to achieve sufficiently high expression levels of the therapeutic TCR. As T cells expressing an endogenous TCR are equipped with an additional TCR, there is a competition between therapeutic and endogenous TCR. Before this work was started, it was not known which TCR is present on the cell surface after TCR gene transfer. Therefore, we transferred TCR genes into murine and human T cells and analyzed TCR expression of endogenous and transferred TCR by staining with antibodies and MHC-multimers. We found that some TCR have the capability to replace other TCR on the cell surface, which led to a complete conversion of antigen specificity in one model. Based on these findings we proposed the concept of ‘‘strong’’ (well expressed) and “weak” (poorly expressed) TCR. In addition, we found that a mouse TCR is able to replace both “weak” and “strong” human TCR on human cells. In parallel to this result, it was reported that the constant (C)-regions of mouse TCR were responsible for the improved expression of murine TCR on human cells. This led to a strategy to improve human TCR by exchanging the C-regions by their murine counterparts (murinization). However, a problem of these hybrid constructs is the probable immunogenicity. Therefore, we identified the specific parts of the mouse C-regions which are essential to improve human TCR. In the TCRalpha C-region four and in the TCRbeta C-region five amino acids were identified. Primary human T cells modified with TCR containing these nine “murine” amino acids showed an increased function compared to cells modified with wild type TCR. For TCR gene therapy the utilization of these new C-regions will reduce the amount of foreign sequences and thus the risk of immunogenicity of the therapeutic TCR.

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Mariathasan, Sanjeev. "TCR-mediated signaling in thymocyte selection." Thesis, National Library of Canada = Bibliothèque nationale du Canada, 2001. http://www.collectionscanada.ca/obj/s4/f2/dsk3/ftp05/NQ63683.pdf.

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6

Rivera, Reyes Brenda Mariola. "Regulation of the TCR signaling pathway." Connect to text online, 2006. http://rave.ohiolink.edu/etdc/view?acc%5Fnum=case1132588714.

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7

Barry, A. C. "Regulation of TCR signalling by SOCS." Thesis, Queen's University Belfast, 2008. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.479241.

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8

Mallaun, Michel. "Proximal TCR signaling in self tolerance /." [S.l.] : [s.n.], 2008. http://edoc.unibas.ch/diss/DissB_8729.

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9

Huang, Elizabeth Chi-Fang. "Organisation of, and ligand-independent signalling by, the TCR, with a special emphasis on the pre-TCR." Thesis, University of Oxford, 2017. http://ora.ox.ac.uk/objects/uuid:0c01e3d4-2002-487c-a0b6-09ed20cb223b.

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Understanding how immune signalling is initiated and regulated spatiotemporally is likely to be helped by investigations of receptor stoichiometry. The pre-TCR expressed by thymocytes shares similarities in structure and signalling components with the mature TCR but, in contrast to the TCR, it has no known ligands. This thesis has therefore analysed the stoichiometry of the pre-TCR using mutagenesis- and imaging-based approaches, and explored how ligand-independent signalling might be initiated by both the TCR and pre-TCR. The mutational analysis, which required considerable optimisation because the pre-TCR is very weakly expressed in transfected cells, suggested that only one contiguous surface on pre-Tα needs to be buried in the pre-TCR complex in order for it to reach the cell surface. This comprised the surface buried at the interface with the constant region of TCRβ and therefore was incompatible with previous suggestions that the pre-TCR assembles into a 'head-to-tail' dimer. Unexpectedly, super-resolution imaging experiments combined with cluster analysis, and the method of single-molecule cross-colour coincidence detection were suggestive that, rather than dimers, the pre-TCR forms higher-order oligomers in transfected cells and possibly also in thymocytes. Similar analyses showed that the organisation of the TCR was heterogeneous, depending on the level of expression of the receptor. Overall, technical limitations that emerged in the course of the study highlighted some of the difficulties in studying native receptor stoichiometry on resting cells generally. The final part of the thesis investigated ligand-independent signalling by the TCR, using a novel assay based on the binding of a superagonistic antibody to a non-signalling form of the receptor CD28. Using CRISPR/Cas-mediated gene editing, it was shown that ligand-independent signalling by the mature TCR and pre-TCR was dependent on Lck and Zap70, indicating that it is reliant on the triggering of conventional signalling pathways. Ways in which the pre-TCR might initiate signalling, that could be tolerant of complexes exhibiting a range of stabilities, are also discussed.

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Bunse, Mario. "RNAi-mediated knockdown of the endogenous TCR improves safety of immunotherapy with TCR gene-modified T cells." Doctoral thesis, Humboldt-Universität zu Berlin, Lebenswissenschaftliche Fakultät, 2015. http://dx.doi.org/10.18452/17155.

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Durch den Transfer der Gene des heterodimeren T-Zellrezeptors (TZR) mithilfe viraler Vektoren können T-Zellen programmiert werden, ein ausgewähltes Antigen spezifisch zu erkennen. In klinischen Studien wurden solche T-Zellen bereits mit Erfolg zur Immuntherapie von Krebs und viralen Infektionen eingesetzt. Genmodifizierte T-Zellen unterscheiden sich jedoch von normalen T-Zellen, weil sie neben den beiden zelleigenen auch die zwei übertragenen TZR-Gene exprimieren. Diese Situation erlaubt die Bildung vier verschiedener TZR-Heterodimere: der zelleigene TZR, der übertragene TZR und zwei gemischte TZR, bestehend aus je einer übertragenen und einer zelleigenen TZR-Kette. Gemischte TZR bergen das Risiko von Nebenwirkungen, weil sie durch Zufall gesundes Körpergewebe erkennen und so Autoimmunität auslösen könnten. In dieser Arbeit wurden deshalb virale Vektoren entwickelt, die gleichzeitig mit der Übertragung von neuen TZR-Genen den zelleigenen TZR durch RNA Interferenz (RNAi) unterdrücken. Mikro-RNA (miRNA), die in den Vektor MP71 eingefügt wurden, reduzierten den zelleigenen TZR in Maus-T-Zellen um mehr als 85%. Dies hatte zur Folge, dass beide Ketten des übertragenen P14-TZR in gleicher Menge auf der Zelloberfläche exprimiert wurden und die Bildung von gemischten TZR reduziert wurde. In einem Mausmodell der adoptiven T-Zelltherapie verhinderte die Unterdrückung des zelleigenen TZR die Entstehung von Autoimmunität, die andernfalls durch gemischte TZR verursacht wurde. Im Gegensatz dazu führte die Anwendung von gentechnisch optimierten P14-TZR-Genen weder zur angeglichenen Oberflächenexpression der P14-TZR Ketten noch zu weniger Autoimmunität im Mausmodell. Ein anderes Tierexperiment zeigte, dass die miRNA die Funktion der genmodifizierten T-Zellen nicht beeinträchtigte. Schließlich wurde ein viraler Vektor entwickelt und getestet, der die Expression des zelleigenen TZR in menschlichen T-Zellen effektiv unterdrückte und die Bildung von gemischten TZR reduzieren konnte.
T cells can be genetically modified using viral vectors. The transfer of genes encoding both chains of the heterodimeric T cell receptor (TCR) programs T cells to specifically react towards an antigen of choice. Such TCR gene-modified T cells were already successfully applied in clinical studies to treat cancer and viral infections. However, in contrast to nonmanipulated T cells these cells express the transferred TCR in addition to the endogenous TCR and this situation allows the assembly of four different TCR heterodimers: the endogenous TCR, the transferred TCR, and two mixed TCR dimers, composed of one endogenous and one transferred TCR chain. The formation of mixed TCR dimers represents a safety issue because they may by chance recognize self-antigens and thereby cause autoimmune side effects. To overcome this problem, an RNAi-TCR replacement vector was developed that simultaneously silences the endogenous TCR and expresses an RNAi-resistant therapeutic TCR. The expression of miRNA encoded by a retroviral MP71 vector in transduced mouse T cells reduced the surface levels of the endogenous TCR by more than 85%. The knockdown of the endogenous TCR in turn resulted in equal surface expression levels of both transferred P14 TCR chains and prevented the formation of mixed TCR dimers. Accordingly, the development of lethal mixed TCR dimer-dependent autoimmunity (TI-GVHD) in a mouse model of adoptive T cell therapy was dramatically reduced by the knockdown of the endogenous TCR. In contrast, the usage of genetically optimized TCR genes neither resulted in equal surface levels of both P14 TCR chains nor in reduced autoimmunity. A second mouse model demonstrated that the in vivo functionality of the transduced T cells was not negatively influenced by the expression of the miRNA. Finally, an RNAi-TCR replacement vector for human T cells was developed that effectively reduced the expression of the endogenous TCR and prevented the formation of mixed TCR dimers.

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Books on the topic "Tcjr"

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NA. Effectv Classrm Mangmt& Tchr Tstd& Tchr Prep. Addison Wesley Longman, 2005.

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Pearson. Literacy 21st Century&tchr Prep&wetska Tchr. Pearson, 2009.

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NA. Effctv Classrm Managmt&tchr Testd&tchr Prep. Addison Wesley Longman, 2007.

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Tcar' prizrakov. AST, 2000.

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Tcar' Krov'. AST, 2001.

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NA. Resource Guide Elem&tchr Tstd Clss&tchr Pkg. Addison Wesley Longman, 2005.

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NA. Artifact Case Studies&tchr Tst&tchr Prep Pk. Addison Wesley Longman, 2005.

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NA. Mylabschl Studt Start& Tchr Multi& Tchr Tec Pkg. Addison Wesley Publishing Company, 2004.

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NA. Classrm Managmt SEC Tchr& What Every Tchr Pk. Addison Wesley Publishing Company, 2004.

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NA. Educ Psych: Developg& Tchr Prep A/C& Tchr Pkg. Addison Wesley Longman, 2006.

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Book chapters on the topic "Tcjr"

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Maeurer, Markus J. "TCR Analyses." In Analyzing T Cell Responses, 239–60. Dordrecht: Springer Netherlands, 2005. http://dx.doi.org/10.1007/1-4020-3623-x_14.

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Raghunandan, M. A., Nirmalie Wiratunga, Sutanu Chakraborti, Stewart Massie, and Deepak Khemani. "Evaluation Measures for TCBR Systems." In Lecture Notes in Computer Science, 444–58. Berlin, Heidelberg: Springer Berlin Heidelberg, 2008. http://dx.doi.org/10.1007/978-3-540-85502-6_30.

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Jameson, Stephen C., and Kristin A. Hogquist. "Options for TCR Interactions: TCR Agonists, Antagonists and Partial Agonists." In MHC Molecules: Expression, Assembly and Function, 181–90. Boston, MA: Springer US, 1996. http://dx.doi.org/10.1007/978-1-4684-6462-7_11.

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Raghunandan, M. A., Sutanu Chakraborti, and Deepak Khemani. "Robust Measures of Complexity in TCBR." In Case-Based Reasoning Research and Development, 270–84. Berlin, Heidelberg: Springer Berlin Heidelberg, 2009. http://dx.doi.org/10.1007/978-3-642-02998-1_20.

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Vandenbark, Arthur A., George Hashim, and Halina Offner. "TCR Peptide Therapy in Autoimmunity." In Progress in Immunology Vol. VIII, 635–41. Berlin, Heidelberg: Springer Berlin Heidelberg, 1993. http://dx.doi.org/10.1007/978-3-642-51479-1_82.

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Rhein, Simone, and Neşe Çakmak-Görür. "TCR Gene Therapy for Cancer." In Methods in Molecular Biology, 95–128. New York, NY: Springer US, 2022. http://dx.doi.org/10.1007/978-1-0716-2441-8_6.

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Feng, Yanming, and Chris Rizos. "Geometry-Based TCAR Models and Performance Analysis." In International Association of Geodesy Symposia, 645–53. Berlin, Heidelberg: Springer Berlin Heidelberg, 2009. http://dx.doi.org/10.1007/978-3-540-85426-5_75.

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Palazzi, Eliana, Nazzareno Mandolesi, Philippe Crane, Dennis J. Hegyi, and J. Christopher Blades. "Measurements of Tcbr at 1. 3 MM." In Astronomy, Cosmology and Fundamental Physics, 441–44. Dordrecht: Springer Netherlands, 1989. http://dx.doi.org/10.1007/978-94-009-0965-6_43.

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Hu, Rong, Sarah Jane Delany, and Brian Mac Namee. "EGAL: Exploration Guided Active Learning for TCBR." In Case-Based Reasoning. Research and Development, 156–70. Berlin, Heidelberg: Springer Berlin Heidelberg, 2010. http://dx.doi.org/10.1007/978-3-642-14274-1_13.

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Peruzzi, Benedetta, Sara Bencini, and Roberto Caporale. "TCR Vβ Evaluation by Flow Cytometry." In Methods in Molecular Biology, 99–109. New York, NY: Springer US, 2021. http://dx.doi.org/10.1007/978-1-0716-1311-5_8.

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Conference papers on the topic "Tcjr"

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Bunk, Sebastian, Martin Hofmann, Gabriele Pszolla, Meike Hutt, Felix Unverdorben, Frank Schwoebel, Nadine Aschmoneit, et al. "1319 Next-generation TCR bispecifics (TCER®) targeting peptide-HLA antigens for the treatment of patients with solid tumors." In SITC 37th Annual Meeting (SITC 2022) Abstracts. BMJ Publishing Group Ltd, 2022. http://dx.doi.org/10.1136/jitc-2022-sitc2022.1319.

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Bajaj, A., S. Monje, C. Ayala, J. Poggi, E. Shaaya, J. Feler, K. Moldovan, C. Doberstein, R. McTaggart, and R. Torabi. "E-019 TCAR." In SNIS 19th Annual Meeting Abstracts. BMA House, Tavistock Square, London, WC1H 9JR: BMJ Publishing Group Ltd., 2022. http://dx.doi.org/10.1136/neurintsurg-2022-snis.130.

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Mao, Yelu, Xiaoyu Shi, Ming-Sheng Shang, and Ying Zhang. "TCR." In the 2018 2nd International Conference. New York, New York, USA: ACM Press, 2018. http://dx.doi.org/10.1145/3234804.3234819.

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Newby, Richard A., Wen-Ching Yang, and Ronald L. Bannister. "Use of Thermochemical Recuperation in Combustion Turbine Power Systems." In ASME 1997 International Gas Turbine and Aeroengine Congress and Exhibition. American Society of Mechanical Engineers, 1997. http://dx.doi.org/10.1115/97-gt-044.

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The performance and practicality of heavy duty combustion turbine power systems incorporating thermochemical recuperation (TCR) of natural gas has been estimated to assess the potential merits of this technology. Process models of TCR combustion turbine power systems based on the Westinghouse 501F combustion turbine were developed to conduct the performance evaluation. Two TCR schemes were assessed — Steam-TCR and Flue Gas-TCR. Compared to conventional combustion turbine power cycles, the TCR power cycles show the potential for significant plant heat rate improvements, but their practicality is an issue. Significant development remains to verify and commercialize TCR for combustion turbine power systems.

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Gelman, Vitaly. "Energy Savings With Reversible Thyristor Controlled Rectifier." In 2009 Joint Rail Conference. ASMEDC, 2009. http://dx.doi.org/10.1115/jrc2009-63013.

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The paper deals with energy savings in Traction Systems available with Thyristor Controlled Rectifiers (TCR) and Reversible TCR (RTCR). TCR provides active voltage control, RTCR in addition has power recuperation into AC line. The energy balance of the TCR and diode rectifier systems are calculated, including losses in the rails, car’s power train and friction losses. The TCR advantages over diode rectifiers: better voltage regulation and fault current limiting allow us to reduce the number of substations and increase their service life. Major energy savings are through recuperation back to AC line using RTCR, with additional savings through increased DC bus voltage. The estimated energy savings depending on the system parameters, train speed profile, etc. can be as high as 50%.

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Balbola, Amr A., Mohammed O. Kayed, and Walied A. Moussa. "Studying the Effect of N-Type Strained Silicon on the Temperature Coefficient of Resistance." In ASME 2017 International Mechanical Engineering Congress and Exposition. American Society of Mechanical Engineers, 2017. http://dx.doi.org/10.1115/imece2017-70039.

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As a step in employing the strained silicon in enhancing a MEMS piezoresistive based 3D stress sensor performance, this paper studies the influence of pre-stretching silicon atoms on the temperature coefficient of resistance (TCR). Extracting accurately the TCR is very influential for the piezoresistive based stress sensor. For this purpose, a piezoresistive sensing rosette was fabricated on strained and unstrained silicon substrates. The pre-strained state was integrated during microfabrication using an intrinsic stress produced by highly compressive plasma enhanced chemical vapor deposition (PECVD) silicon nitride layer, which induces global biaxial tensile pre-strain onto the substrate. Under a stress free thermal loading, the TCR for both strained and unstrained chips were calibrated using an environmental chamber. Comparing the calibration results in both strained and unstrained silicon, the tensile pre-strained silicon has larger TCR than that in unstrained silicon. Moreover, over the surface concentration range used in this work, the strained silicon shows the same unstrained silicon trend, which is, the TCR is increased proportionally with the surface concentration.

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Restrepo, Gustavo A., Andrey N. Krylov, and Eduard D. Sergievskiy. "Heat and Mass Transfer and Kinetic Processes Modeling in a Methane Steam Conversion Facility." In ASME 2009 Heat Transfer Summer Conference collocated with the InterPACK09 and 3rd Energy Sustainability Conferences. ASMEDC, 2009. http://dx.doi.org/10.1115/ht2009-88425.

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This paper deals with one of the most interesting methods of lowering heat losses: thermochemical recuperation (TCR) of waste heat present in high-temperature flue gases via methane steam reforming. An earlier proposed process flow diagram for TCR in a glass production facility was revised and a mathematical model was developed to predict the heat and mass transfer phenomena that take place in the catalytic chemical reactor included in that process. Comparison of data obtained by the new proposed model and published data confirmed the feasibility of using it in the investigation and synthesis of TCR processes. Obtained results also permit to find optimal temperature profile in order to increase the hydrogen rate formation.

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Joseph, Diya, Juan L. Aragon, Joan-Manuel Parcerisa, and Antonio Gonzalez. "TCOR: A Tile Cache with Optimal Replacement." In 2022 IEEE International Symposium on High-Performance Computer Architecture (HPCA). IEEE, 2022. http://dx.doi.org/10.1109/hpca53966.2022.00055.

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Tsuru, Kazunari, Yutaka Yamada, Tatsuya Ikuta, Takashi Nishiyama, and Koji Takahashi. "Experimental Study on Thermal Contact Resistance of Multi-Walled Carbon Nanotubes." In ASME 2013 4th International Conference on Micro/Nanoscale Heat and Mass Transfer. American Society of Mechanical Engineers, 2013. http://dx.doi.org/10.1115/mnhmt2013-22078.

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Heat transfer at solid-solid interface is very fascinating where no one knows the full mechanism which has a huge impact in many applications in engineering and science. In many kinds of interfaces, we treat a van der Waals contact of perfectly-smooth surfaces by using multi-walled carbon nanotubes (CNTs). Their thermal contact resistance (TCR) is estimated by comparing measured thermal conductivity of CNT specimen and numerical simulation result. The TCR per unit area is estimated as 1.58∼3.33×10−8 m2K/W at room temperature in vacuum, which is much higher than our previous result in air. It was also found that TCR is inversely proportional with the temperature to the 1.92th power different from the simple phonon model represented by the diffuse mismatch model.

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Bahrami, M., J. R. Culham, and M. M. Yovanovich. "A Scale Analysis Approach to Thermal Contact Resistance." In ASME 2003 International Mechanical Engineering Congress and Exposition. ASMEDC, 2003. http://dx.doi.org/10.1115/imece2003-55283.

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A new analytical model is developed for predicting thermal contact resistance (TCR) of non-conforming rough contacts of bare solids in a vacuum. Instead of using probability relationships to model the size and number of microcontacts of Gaussian surfaces, a novel approach by employing the “scale analysis methods” is taken. It is shown that the mean size of the microcontacts is proportional to the surface roughness and inversely proportional to the surface asperity slope. A general relationship for determining TCR is derived by superposition of the macro and the effective micro thermal resistances. The present model allows TCR to be predicted over the entire range of non-conforming rough contacts from conforming rough to smooth Hertzian contacts. It is demonstrated that the geometry of heat sources on a half-space for microcontacts is justifiable and that effective micro thermal resistance is not a function of surface curvature. A comparison of the present model with 604 experimental data points, collected by many researchers during the last forty years, shows good agreement for the entire range of TCR. The data covers a wide range of materials, mechanical and thermophysical properties, micro and macro contact geometries, and similar and dissimilar metal contacts.

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Reports on the topic "Tcjr"

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McDonald, Tia, and Ron Durst. analysis of the effect of sunsetting tax provisions for family farm households. Washington, D.C.: Economic Research Service, U.S. Department of Agriculture, 2024. http://dx.doi.org/10.32747/2024.8327788.ers.

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Two recent laws enacted temporary provisions to the Federal tax code: the American Rescue Plan Act (ARPA) and the Tax Cuts and Jobs Act (TCJA). The authors of this report assess the impact of these sunsetting tax provisions on tax liabilities for farm households. Using data from the USDA, Agricultural Resource Management Survey (2018-21) and the USDA, Economic Research Service's Federal income tax and estate tax models, the authors estimate that the expiration of the temporary provisions of the ARPA and TCJA would increase farm households' Federal income tax liabilities by $8.9 billion and estate tax liabilities by $647 million in the year following expiration.

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Russell, Michael, Vincent Paquit, Luke Scime, and Alka Singh. TCR Data Management Plan. Office of Scientific and Technical Information (OSTI), March 2021. http://dx.doi.org/10.2172/1814318.

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Huning, Alex, and Randall Fair. TCR Postulated Accident and MHA Dose Assessment. Office of Scientific and Technical Information (OSTI), March 2021. http://dx.doi.org/10.2172/1778087.

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Shirvan, Koroush. Validation of Robustness in TCR Design Strategies. Office of Scientific and Technical Information (OSTI), March 2023. http://dx.doi.org/10.2172/1964002.

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Meer, Jonathan, and Benjamin Priday. Tax Prices and Charitable Giving: Projected Changes in Donations Under the 2017 TCJA. Cambridge, MA: National Bureau of Economic Research, November 2019. http://dx.doi.org/10.3386/w26452.

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HANG, THONG, and CHARLES NASH. ZAM MODELING STUDY TO SUPPORT THE TANK CLOSURE CESIUM REMOVAL (TCCR) 1A UNIT. Office of Scientific and Technical Information (OSTI), August 2020. http://dx.doi.org/10.2172/1658845.

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Dehoff, Ryan, and Michael Russell. Quality Procedures for TCR Metal Core Structure Advanced Manufacturing Process. Office of Scientific and Technical Information (OSTI), September 2020. http://dx.doi.org/10.2172/1814370.

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Taylor-Pashow, Kathryn, and Charles Nash. Summary of Expedited Results from Samples Supporting Tank Closure Cesium Removal (TCCR) Batch 3. Office of Scientific and Technical Information (OSTI), July 2020. http://dx.doi.org/10.2172/1643938.

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Hang, T. Modeling Crystalline Silicotitanate Performance to Support TCCR Batch 1 and Batch 1A Operations (U). Office of Scientific and Technical Information (OSTI), March 2019. http://dx.doi.org/10.2172/1510931.

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Schappel, Danny, and Kurt Terrani. Key Material Properties for Thermo-Structural Analysis of TCR Core Components. Office of Scientific and Technical Information (OSTI), August 2019. http://dx.doi.org/10.2172/1558508.

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