Title |
Plasma miRNA as Biomarkers for Assessment of Total-Body Radiation Exposure Dosimetry
|
---|---|
Published in |
PLOS ONE, August 2011
|
DOI | 10.1371/journal.pone.0022988 |
Pubmed ID | |
Authors |
Wanchang Cui, Jinfang Ma, Yulei Wang, Shyam Biswal |
Abstract |
The risk of radiation exposure, due to accidental or malicious release of ionizing radiation, is a major public health concern. Biomarkers that can rapidly identify severely-irradiated individuals requiring prompt medical treatment in mass-casualty incidents are urgently needed. Stable blood or plasma-based biomarkers are attractive because of the ease for sample collection. We tested the hypothesis that plasma miRNA expression profiles can accurately reflect prior radiation exposure. We demonstrated using a murine model that plasma miRNA expression signatures could distinguish mice that received total body irradiation doses of 0.5 Gy, 2 Gy, and 10 Gy (at 6 h or 24 h post radiation) with accuracy, sensitivity, and specificity of above 90%. Taken together, these data demonstrate that plasma miRNA profiles can be highly predictive of different levels of radiation exposure. Thus, plasma-based biomarkers can be used to assess radiation exposure after mass-casualty incidents, and it may provide a valuable tool in developing and implementing effective countermeasures. |
X Demographics
Geographical breakdown
Country | Count | As % |
---|---|---|
United States | 2 | 29% |
Australia | 1 | 14% |
Unknown | 4 | 57% |
Demographic breakdown
Type | Count | As % |
---|---|---|
Members of the public | 6 | 86% |
Scientists | 1 | 14% |
Mendeley readers
Geographical breakdown
Country | Count | As % |
---|---|---|
United States | 3 | 3% |
Turkey | 1 | 1% |
India | 1 | 1% |
Germany | 1 | 1% |
Unknown | 81 | 93% |
Demographic breakdown
Readers by professional status | Count | As % |
---|---|---|
Researcher | 24 | 28% |
Student > Ph. D. Student | 13 | 15% |
Student > Bachelor | 9 | 10% |
Professor > Associate Professor | 7 | 8% |
Student > Postgraduate | 6 | 7% |
Other | 17 | 20% |
Unknown | 11 | 13% |
Readers by discipline | Count | As % |
---|---|---|
Agricultural and Biological Sciences | 30 | 34% |
Biochemistry, Genetics and Molecular Biology | 17 | 20% |
Medicine and Dentistry | 12 | 14% |
Physics and Astronomy | 4 | 5% |
Veterinary Science and Veterinary Medicine | 2 | 2% |
Other | 9 | 10% |
Unknown | 13 | 15% |