Supplementary Materials and Methods, Figures 1 - 13, Table 1 from Activating and Propagating Polyclonal Gamma Delta T Cells with Broad Specificity for Malignancies
openalex(2023)
Abstract
PDF file - 1405KB, Supplementary Materials and Methods. Supplementary Figures - (1) Tumor cell line culture conditions and media formulations (2) Co-culture conditions for gamma/delta T cells and designer aAPC (3) Intracellular cytokine production, Luminex, and neutralizing antibody cytolysis assays (4) Lentivirus packaging and transduction of CAOV3 cells Contents of the Supplemental Data include figures: (1) An example of the gating strategy for gamma/delta T-cell analyses (2) Schematic of DNA plasmid pLVU3G-effLuc-T2A-mKateS158A used to co-express enhanced firefly luciferase (effLuc) and mKate (3) Expression of activation markers CD38 and CD95 on propagated gamma/delta T cells (4) aAPC developed for co-culture with gamma/delta T cells to determine the impact of introduced co-stimulatory molecules (5) Expansion of UCB-derived gamma/delta T cells on aAPC with IL-2 and IL-21 (6) Surface expression of TCRdelta1 and TCRdelta2 chains on gamma/delta T cells derived from PBMC prior to propagation (7) Abundance of Vdelta and Vgamma mRNA species in gamma/delta T cells prior to ex vivo numeric expansion (8) Surface expression of TCRdelta1 and TCRdelta2 chains on gamma/delta T cells derived from UCB and propagated on aAPC with IL-2 and IL-21 (9) mRNA expression of shared Valpha/Vdelta alleles in gamma/delta T cells separated and then propagated on aAPC, IL-2, and IL-21 (10) Abundance of mRNA species coding for Vgamma chains in gamma/delta T-cell subsets (11) In vitro lysis of tumor cell line panel by polyclonal gamma/delta T cells (12) Specific lysis of hematological and solid tumor cells by Vdelta T-cell subsets (13) Immunophenotypes associated with PBMC-derived Vdelta T-cell subsets expanded on aAPC/IL-2/IL-21. Supplemental Table 1 - details the antibodies used in this study, where they were purchased, and their hybridoma clone.
MoreTranslated text
Key words
Antigen Presentation
PDF
View via Publisher
AI Read Science
AI Summary
AI Summary is the key point extracted automatically understanding the full text of the paper, including the background, methods, results, conclusions, icons and other key content, so that you can get the outline of the paper at a glance.
Example
Background
Key content
Introduction
Methods
Results
Related work
Fund
Key content
- Pretraining has recently greatly promoted the development of natural language processing (NLP)
- We show that M6 outperforms the baselines in multimodal downstream tasks, and the large M6 with 10 parameters can reach a better performance
- We propose a method called M6 that is able to process information of multiple modalities and perform both single-modal and cross-modal understanding and generation
- The model is scaled to large model with 10 billion parameters with sophisticated deployment, and the 10 -parameter M6-large is the largest pretrained model in Chinese
- Experimental results show that our proposed M6 outperforms the baseline in a number of downstream tasks concerning both single modality and multiple modalities We will continue the pretraining of extremely large models by increasing data to explore the limit of its performance
Try using models to generate summary,it takes about 60s
Must-Reading Tree
Example

Generate MRT to find the research sequence of this paper
Data Disclaimer
The page data are from open Internet sources, cooperative publishers and automatic analysis results through AI technology. We do not make any commitments and guarantees for the validity, accuracy, correctness, reliability, completeness and timeliness of the page data. If you have any questions, please contact us by email: report@aminer.cn
Chat Paper
去 AI 文献库 对话