Evidence map›Paper›PMID 31797975›Full record

ArticleScientific reports2019

Transcriptomic responses in mouse blood during the first week after in vivo gamma irradiation.

Sunirmal Paul, Norman J Kleiman, Sally A Amundson

Open access · goldAbstract read
In one paragraph

Article in Scientific reports, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 12 papers.

0numbers the graph read from it
0cells of the map it votes in
12citing papers in PubMed
1.9field-weighted citation impact, top 14% 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

12 citing papers in PubMed, 17 citations in OpenAlex.

  1. Review
  2. Article
  3. Validation and Derivation of miRNA-Based Germline Signatures Predicting Radiation Toxicity in Prostate Cancer.Clinical cancer research : an official journal of the American Association for Cancer Research · 2025
    Article
  4. Article
  5. Article
  6. Review
  7. Transcriptomics for radiation biodosimetry: progress and challenges.International journal of radiation biology · 2023
    Review
  8. Article
  9. The transcriptomic revolution and radiation biology.International journal of radiation biology · 2022
    Article
  10. Article
  11. Article
  12. 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

3 authors at 2 institutions in 1 country.

Sunirmal PaulCenter for Radiological Research, Vagelos College of Physicians and Surgeons, Columbia University Irving Medical Center, New York, NY, 10032, USA.
Norman J KleimanDepartment of Environmental Health Sciences, Mailman School of Public Health, Columbia University Irving Medical Center, New York, NY, 10032, USA.ORCID http://orcid.org/0000-0002-4725-998X
Sally A AmundsonCenter for Radiological Research, Vagelos College of Physicians and Surgeons, Columbia University Irving Medical Center, New York, NY, 10032, USA. saa2108@cumc.columbia.edu.ORCID http://orcid.org/0000-0001-9992-8818
Columbia University Irving Medical Center · USColumbia University · US

Funding

Sample Engineering CoreU19AI067773 · NIAID · COLUMBIA UNIVERSITY HEALTH SCIENCES · PI FORNACE, ALBERT J · 2005 to 2024
$105.4M
NIAID NIH HHS U19 AI067773U.S. Department of Health & Human Services | Biomedical Advanced Research and Development Authority (BARDA) HHS01201000008C
6 · The paper itself

Abstract

Due to limitations of available human models for development of gene expression based radiation biodosimetry, many such studies have made use of mouse models. To provide a broad view of the gene expression response to irradiation in the mouse, we have exposed male C57BL/6 mice to 0, 1.5, 3, 6 or 10 Gy of gamma rays, sacrificing groups of the mice at 1, 2, 3, 5, or 7 days after exposure. We then profiled global gene expression in blood from individual mice using Agilent microarrays. In general, we found increasing numbers of genes differentially expressed with increasing dose, with more prolonged responses after the higher doses. Gene ontology analysis showed a similar pattern, with more biological processes enriched among the genes responding to higher doses, and at later times after exposure. Clustering the timecourse expression data using maSigPro identified four broad patterns of response, representing different gene ontology functions. The largest of these clusters included genes with initially decreased expression followed by increased expression at later times, a pattern of expression previously reported for several genes following neutron exposure. Another gene cluster showing consistent down regulation suggests genes useful for biodosimetry throughout the first week after exposure can be identified.

Indexed as

Oligonucleotide Array Sequence AnalysisAnimalsCluster AnalysisDisease Models, AnimalGamma RaysGene Expression RegulationGene OntologyHumansMiceNeutronsRadiation DosageTranscriptome

Identifiers

PMID31797975
PMCPMC6893039
OpenAlexW2993170826

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.