| Title |
Innate Immune Suppression Enables Frequent Transfection with RNA Encoding Reprogramming Proteins
|
|---|---|
| Published in |
PLOS ONE, July 2010
|
| DOI | 10.1371/journal.pone.0011756 |
| Pubmed ID | |
| Authors |
Matthew Angel, Mehmet Fatih Yanik |
| Abstract |
Generating autologous pluripotent stem cells for therapeutic applications will require the development of efficient DNA-free reprogramming techniques. Transfecting cells with in vitro-transcribed, protein-encoding RNA is a straightforward method of directly expressing high levels of reprogramming proteins without genetic modification. However, long-RNA transfection triggers a potent innate immune response characterized by growth inhibition and the production of inflammatory cytokines. As a result, repeated transfection with protein-encoding RNA causes cell death. |
X Demographics
The data shown below were collected from the profiles of 6 X users who shared this research output. Click here to find out more about how the information was compiled.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| United States | 2 | 33% |
| Unknown | 4 | 67% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Members of the public | 5 | 83% |
| Scientists | 1 | 17% |
Mendeley readers
The data shown below were compiled from readership statistics for 149 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| United States | 4 | 3% |
| Germany | 2 | 1% |
| France | 1 | <1% |
| South Africa | 1 | <1% |
| Italy | 1 | <1% |
| United Kingdom | 1 | <1% |
| Poland | 1 | <1% |
| Unknown | 138 | 93% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Researcher | 41 | 28% |
| Student > Ph. D. Student | 35 | 23% |
| Student > Master | 14 | 9% |
| Student > Bachelor | 10 | 7% |
| Student > Doctoral Student | 7 | 5% |
| Other | 24 | 16% |
| Unknown | 18 | 12% |
| Readers by discipline | Count | As % |
|---|---|---|
| Agricultural and Biological Sciences | 59 | 40% |
| Biochemistry, Genetics and Molecular Biology | 35 | 23% |
| Medicine and Dentistry | 16 | 11% |
| Neuroscience | 5 | 3% |
| Engineering | 4 | 3% |
| Other | 10 | 7% |
| Unknown | 20 | 13% |