Evidence map›Paper›PMID 25485227›Full record

ArticleEPJ techniques and instrumentation2014

Method for validating radiobiological samples using a linear accelerator.

Muriel Brengues, David Liu, Ronald Korn, Frederic Zenhausern

Open access · goldAbstract read
In one paragraph

Article in EPJ techniques and instrumentation, 2014. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing papers in PubMed
1.4field-weighted citation impact, top 16% of its field
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

2 citing papers in PubMed, 4 citations in OpenAlex.

  1. Article
  2. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

4 authors at 2 institutions in 1 country.

Muriel BrenguesCenter for Applied NanoBioscience and Medicine, The University of Arizona College of Medicine, 425 N. 5th Street, Phoenix, AZ 85004, USA.
David LiuScottsdale Clinical Research Institute, Scottsdale Healthcare, 10510 N. 92nd Street, Scottsdale, AZ 85258.
Ronald KornScottsdale Clinical Research Institute, Scottsdale Healthcare, 10510 N. 92nd Street, Scottsdale, AZ 85258.
Frederic ZenhausernCenter for Applied NanoBioscience and Medicine, The University of Arizona College of Medicine, 425 N. 5th Street, Phoenix, AZ 85004, USA ; Scottsdale Clinical Research Institute, Scottsdale Healthcare, 10510 N. 92nd Street, Scottsdale, AZ 85258.
Clinical Research Institute · USUniversity of Arizona · US

Funding

Sample Engineering CoreU19AI067773 · NIAID · COLUMBIA UNIVERSITY HEALTH SCIENCES · PI FORNACE, ALBERT J · 2005 to 2024
$105.4M
NIAID NIH HHS U19 AI067773
6 · The paper itself

Abstract

There is an immediate need for rapid triage of the population in case of a large scale exposure to ionizing radiation. Knowing the dose absorbed by the body will allow clinicians to administer medical treatment for the best chance of recovery for the victim. In addition, today's radiotherapy treatment could benefit from additional information regarding the patient's sensitivity to radiation before starting the treatment. As of today, there is no system in place to respond to this demand. This paper will describe specific procedures to mimic the effects of human exposure to ionizing radiation creating the tools for optimization of administered radiation dosimetry for radiotherapy and/or to estimate the doses of radiation received accidentally during a radiation event that could pose a danger to the public. In order to obtain irradiated biological samples to study ionizing radiation absorbed by the body, we performed

Indexed as

BiodosimetryBlood samplesGene expressionLinac accelerator

Identifiers

PMID25485227
PMCPMC4257133
OpenAlexW2139253841

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.