ArticleScientific reports2014
Identification of gene expression biomarkers for predicting radiation exposure.
Article in Scientific reports, 2014. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 21 papers, 1 of them a synthesis that pooled 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.
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.
Who cites it
21 citing papers in PubMed, 1 synthesis or guideline pooled it.
- Candidate gene biodosimetry markers of exposure to external ionizing radiation in human blood: A systematic review.PloS one · 2018Pooled it
- Enhanced γ-H2AX Foci Frequency and Altered Gene Expression in Participants Exposed to Ionizing Radiation During I-131 Nuclear Medicine Procedures.Nuclear medicine and molecular imaging · 2024Article
- Comparative Analysis of Driver Mutations and Transcriptomes in Papillary Thyroid Cancer by Region of Residence in South Korea.Endocrinology and metabolism (Seoul, Korea) · 2023Article
- Paper-Based Vertical Flow Immunoassay for the Point-of-Care Multiplex Detection of Radiation Dosimetry Genes.Cytogenetic and genome research · 2023Article
- A Review of Radiation-Induced Alterations of Multi-Omic Profiles, Radiation Injury Biomarkers, and Countermeasures.Radiation research · 2023Review
- Identification of marker genes in Alzheimer's disease using a machine-learning model.Bioinformation · 2021Article
- Radioprotection and Radiomitigation: From the Bench to Clinical Practice.Biomedicines · 2020Review
- Two-miRNA-based finger-stick assay for estimation of absorbed ionizing radiation dose.Science translational medicine · 2020Article
- New Approaches for Quantitative Reconstruction of Radiation Dose in Human Blood Cells.Scientific reports · 2019Article
- Dataset for dose and time-dependent transcriptional response to ionizing radiation exposure.Data in brief · 2019Article
- Ionizing radiation exposure: hazards, prevention, and biomarker screening.Environmental science and pollution research international · 2018Article
- FDXR is a biomarker of radiation exposure in vivo.Scientific reports · 2018Article
- Predicting ionizing radiation exposure using biochemically-inspired genomic machine learning.F1000Research · 2018Article
- Meta-analysis approach as a gene selection method in class prediction: does it improve model performance? A case study in acute myeloid leukemia.BMC bioinformatics · 2017Article
- Comparison of gene expression response to neutron and x-ray irradiation using mouse blood.BMC genomics · 2017Article
- Biomarkers of Ionizing Radiation Exposure: A Multiparametric Approach.Genome integrity · 2017Article
- Gene expression profiling in undifferentiated thyroid carcinoma induced by high-dose radiation.Journal of radiation research · 2016Article
- Development of a prediction model for radiosensitivity using the expression values of genes and long non-coding RNAs.Oncotarget · 2016Article
- Transcriptional profile of immediate response to ionizing radiation exposure.Genomics data · 2016Article
- Radiation-induced alternative transcription and splicing events and their applicability to practical biodosimetry.Scientific reports · 2016Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
5 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
A need for more accurate and reliable radiation dosimetry has become increasingly important due to the possibility of a large-scale radiation emergency resulting from terrorism or nuclear accidents. Although traditional approaches provide accurate measurements, such methods usually require tedious effort and at least two days to complete. Therefore, we provide a new method for rapid prediction of radiation exposure. Eleven microarray datasets were classified into two groups based on their radiation doses and utilized as the training samples. For the two groups, Student's t-tests and resampling tests were used to identify biomarkers, and their gene expression ratios were used to develop a prediction model. The performance of the model was evaluated in four independent datasets, and Ingenuity pathway analysis was performed to characterize the associated biological functions. Our meta-analysis identified 29 biomarkers, showing approximately 90% and 80% accuracy in the training and validation samples. Furthermore, the 29 genes significantly participated in the regulation of cell cycle, and 19 of them are regulated by three well-known radiation-modulated transcription factors: TP53, FOXM1 and ERBB2. In conclusion, this study demonstrates a reliable method for identifying biomarkers across independent studies and high and reproducible prediction accuracy was demonstrated in both internal and external datasets.
Indexed as
Identifiers
What OpenQuestion holds
Registered trials
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.