| Chapter title |
Transcriptional Regulatory Networks for CD4 T Cell Differentiation.
|
|---|---|
| Chapter number | 372 |
| Book title |
Transcriptional Control of Lineage Differentiation in Immune Cells
|
| Published in |
Current topics in microbiology and immunology, May 2014
|
| DOI | 10.1007/82_2014_372 |
| Pubmed ID | |
| Book ISBNs |
978-3-31-907394-1, 978-3-31-907395-8
|
| Authors |
Darah Christie, Jinfang Zhu |
| Abstract |
CD4(+) T cells play a central role in controlling the adaptive immune response by secreting cytokines to activate target cells. Naïve CD4(+) T cells differentiate into at least four subsets, Th1Th1 , Th2Th2 , Th17Th17 , and inducible regulatory T cellsregulatory T cells , each with unique functions for pathogen elimination. The differentiation of these subsets is induced in response to cytokine stimulation, which is translated into Stat activation, followed by induction of master regulator transcription factorstranscription factors . In addition to these factors, multiple other transcription factors, both subset specific and shared, are also involved in promoting subset differentiation. This review will focus on the network of transcription factors that control CD4(+) T cell differentiation. |
X Demographics
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Unknown | 2 | 100% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Members of the public | 1 | 50% |
| Science communicators (journalists, bloggers, editors) | 1 | 50% |
Mendeley readers
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Germany | 2 | 3% |
| Greece | 1 | 1% |
| Canada | 1 | 1% |
| Unknown | 75 | 95% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Student > Ph. D. Student | 21 | 27% |
| Student > Bachelor | 13 | 16% |
| Researcher | 13 | 16% |
| Student > Master | 9 | 11% |
| Other | 4 | 5% |
| Other | 5 | 6% |
| Unknown | 14 | 18% |
| Readers by discipline | Count | As % |
|---|---|---|
| Agricultural and Biological Sciences | 19 | 24% |
| Immunology and Microbiology | 16 | 20% |
| Biochemistry, Genetics and Molecular Biology | 16 | 20% |
| Medicine and Dentistry | 8 | 10% |
| Engineering | 2 | 3% |
| Other | 1 | 1% |
| Unknown | 17 | 22% |