Terrorism using radiological dirty bombs or improvised nuclear devices is recognized as a major threat to both public health and national security. In the event of a radiological or nuclear disaster, rapid and accurate biodosimetry of thousands of potentially affected individuals will be essential for effective medical management to occur. Currently, health care providers lack an accurate, high-throughput biodosimetric assay which is suitable for the triage of large numbers of radiation injury victims. Here, we describe the development of a biodosimetric assay based on the analysis of irradiated mice, ex vivo-irradiated human peripheral blood (PB) and humans treated with total body irradiation (TBI). Interestingly, a gene expression profile...
The risk of a large-scale event leading to acute radiation exposure necessitates the development of ...
Introduction: In case of a large-scale radiation accident with involvement of individuals without ph...
Background: Gene signatures derived from transcriptomic data using machine learning methods have sho...
<div><p>Terrorism using radiological dirty bombs or improvised nuclear devices is recognized as a ma...
Terrorism using radiological dirty bombs or improvised nuclear devices is recognized as a major thre...
In the event of a terrorist-mediated attack in the United States using radiological or improvised nu...
BACKGROUND: The capacity to assess environmental inputs to biological phenotypes is limited by metho...
The capacity to assess environmental inputs to biological phenotypes is limited by methods that can ...
Molecular biodosimetry tools are a valuable asset for life-saving medical triage and patient managem...
Previous work has demonstrated the potential for peripheral blood (PB) gene expression profiling for...
Introduction: In case of a large-scale radiation accident with involvement of individuals without ph...
Purpose: In order to ensure efficient use of medical resources following a radiological incident, th...
<p>A) A Minority of Murine Radiation Response Genes Are Expressed in Humans. The scatterplot shows –...
Biodosimetry, the measurement of radiation damage in a biologic sample, is a reliable tool for incre...
<div><p>Purpose</p><p>To compile a list of genes that have been reported to be affected by external ...
The risk of a large-scale event leading to acute radiation exposure necessitates the development of ...
Introduction: In case of a large-scale radiation accident with involvement of individuals without ph...
Background: Gene signatures derived from transcriptomic data using machine learning methods have sho...
<div><p>Terrorism using radiological dirty bombs or improvised nuclear devices is recognized as a ma...
Terrorism using radiological dirty bombs or improvised nuclear devices is recognized as a major thre...
In the event of a terrorist-mediated attack in the United States using radiological or improvised nu...
BACKGROUND: The capacity to assess environmental inputs to biological phenotypes is limited by metho...
The capacity to assess environmental inputs to biological phenotypes is limited by methods that can ...
Molecular biodosimetry tools are a valuable asset for life-saving medical triage and patient managem...
Previous work has demonstrated the potential for peripheral blood (PB) gene expression profiling for...
Introduction: In case of a large-scale radiation accident with involvement of individuals without ph...
Purpose: In order to ensure efficient use of medical resources following a radiological incident, th...
<p>A) A Minority of Murine Radiation Response Genes Are Expressed in Humans. The scatterplot shows –...
Biodosimetry, the measurement of radiation damage in a biologic sample, is a reliable tool for incre...
<div><p>Purpose</p><p>To compile a list of genes that have been reported to be affected by external ...
The risk of a large-scale event leading to acute radiation exposure necessitates the development of ...
Introduction: In case of a large-scale radiation accident with involvement of individuals without ph...
Background: Gene signatures derived from transcriptomic data using machine learning methods have sho...