What is he best known for?
The fields of study he is best known for:
- Gene
- Immune system
- T cell
Jeffrey A. Bluestone mainly investigates Immunology, T cell, IL-2 receptor, Antigen and CD28.
His Immunology study is mostly concerned with Autoimmunity, FOXP3, Autoimmune disease, NOD mice and Immune tolerance.
His research in T cell intersects with topics in Interleukin 2, In vivo and Cell biology.
His study on IL-2 receptor also encompasses disciplines like
- Interleukin 21 which intersects with area such as Molecular biology, Interleukin 12 and Lymphokine,
- Islet, which have a strong connection to Transplantation.
His Antigen study combines topics in areas such as Diabetes mellitus, Endocrinology, Antibody and Internal medicine.
His CD28 research includes themes of Peripheral, Blockade and Antigen presentation.
His most cited work include:
- CD28/B7 SYSTEM OF T CELL COSTIMULATION (2453 citations)
- Loss of CTLA-4 leads to massive lymphoproliferation and fatal multiorgan tissue destruction, revealing a critical negative regulatory role of CTLA-4 (2297 citations)
- CD127 expression inversely correlates with FoxP3 and suppressive function of human CD4+ T reg cells (2139 citations)
What are the main themes of his work throughout his whole career to date?
Jeffrey A. Bluestone focuses on Immunology, T cell, Cell biology, Immune system and Antigen.
His study involves Autoimmunity, T-cell receptor, IL-2 receptor, Immune tolerance and Immunotherapy, a branch of Immunology.
His work in IL-2 receptor addresses subjects such as FOXP3, which are connected to disciplines such as Regulatory T cell and Transcription factor.
His T cell study incorporates themes from Molecular biology, Cytotoxic T cell, T lymphocyte and CD8.
His Molecular biology research focuses on Monoclonal antibody and how it connects with In vivo.
His study ties his expertise on Antibody together with the subject of Antigen.
He most often published in these fields:
- Immunology (57.09%)
- T cell (29.05%)
- Cell biology (19.43%)
What were the highlights of his more recent work (between 2013-2021)?
- Immunology (57.09%)
- Immune system (18.75%)
- Autoimmunity (14.02%)
In recent papers he was focusing on the following fields of study:
Jeffrey A. Bluestone spends much of his time researching Immunology, Immune system, Autoimmunity, Immunotherapy and Cell biology.
His Immunology study which covers Disease that intersects with Phenotype.
Jeffrey A. Bluestone combines subjects such as Cancer, Cytokine and Antigen with his study of Immune system.
His biological study spans a wide range of topics, including Adoptive cell transfer, Nod, Type 1 diabetes and Transplantation.
His study in Immunotherapy is interdisciplinary in nature, drawing from both Cancer research, Clinical trial, Bioinformatics and Cell therapy.
Jeffrey A. Bluestone has included themes like CD28, CD8 and Gene targeting in his Cell biology study.
Between 2013 and 2021, his most popular works were:
- Pathogenic conversion of Foxp3+ T cells into TH17 cells in autoimmune arthritis. (583 citations)
- Type 1 diabetes immunotherapy using polyclonal regulatory T cells (454 citations)
- Generation of knock-in primary human T cells using Cas9 ribonucleoproteins. (450 citations)
In his most recent research, the most cited papers focused on:
- Gene
- Immune system
- Cancer
His scientific interests lie mostly in Immunology, Immune system, Autoimmunity, Immunotherapy and FOXP3.
In his study, Phenotype is strongly linked to Disease, which falls under the umbrella field of Immunology.
His work on T-cell receptor and CD28 as part of general Immune system research is often related to Mechanism, thus linking different fields of science.
His Autoimmunity research is multidisciplinary, incorporating elements of Cancer, Immunity, Transplant rejection, Transplantation and Effector.
His Immunotherapy research is multidisciplinary, relying on both Encephalomyelitis, T cell, Adoptive cell transfer and Heel.
His work deals with themes such as Peripheral tolerance and Regulatory T cell, IL-2 receptor, which intersect with FOXP3.
This overview was generated by a machine learning system which analysed the scientist’s
body of work. If you have any feedback, you can
contact us
here.
