ArticleScientific reports2020
Urine metabolomics based prediction model approach for radiation exposure.
Article in Scientific reports, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 20 papers.
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Who cites it
20 citing papers in PubMed.
- Polymeric sorbent phase sorptive extraction for radiation metabolomics.RSC advances · 2026Article
- The role of macrophages in radiation-induced lung injury: from pathological mechanisms to therapeutic targets.Frontiers in immunology · 2026Review
- Cancer Management Using Photodynamic Therapy: Fundamentals, Mechanism and Advances.Current pharmaceutical design · 2026Review
- Plasma and Fecal Metabolites Combined with Gut Microbiome Reveal Systemic Metabolic Shifts inMetabolites · 2025Article
- Effects of 4.9 GHz Radiofrequency Field Exposure on Brain Metabolomic and Proteomic Characterization in Mice.Biology · 2024Article
- Impact of Partial Body Shielding from Very High Dose Rates on Untargeted Metabolomics in Biodosimetry.ACS omega · 2024Article
- Article
- Unraveling biomarkers of exposure for tenuazonic acid through urinary metabolomics.Food and chemical toxicology : an international journal published for the British Industrial Biological Research Association · 2023Article
- Metabolomics and transcriptomics based multi-omics integration reveals radiation-induced altered pathway networking and underlying mechanism.NPJ systems biology and applications · 2023Article
- Variable Dose Rates in Realistic Radiation Exposures: Effects on Small Molecule Markers of Ionizing Radiation in the Murine Model.Radiation research · 2023Article
- Statistical methods and resources for biomarker discovery using metabolomics.BMC bioinformatics · 2023Review
- Review
- Applications of photodynamic therapy in extramammary Paget's disease.American journal of cancer research · 2023Review
- Exploration of urinary metabolite dynamicity for early detection of pregnancy in water buffaloes.Scientific reports · 2022Article
- Urinary metabolic modulation in human participants residing in Siachen: a 1H NMR metabolomics approach.Scientific reports · 2022Article
- Metabolomics as a valid analytical technique in environmental exposure research: application and progress.Metabolomics : Official journal of the Metabolomic Society · 2022Review
- The Association of Urine Creatinine With Kidney Stone Prevalence in US Adults: Data From NHANES 2009-2018.Frontiers in medicine · 2022Article
- Article
- Biofluid Metabolomics of Mice Exposed to External Low-Dose Rate Radiation in a Novel Irradiation System, the Variable Dose-Rate ExternalJournal of proteome research · 2021Article
- Radiation exposure induces cross-species temporal metabolic changes that are mitigated in mice by amifostine.Scientific reports · 2021Article
Corrections and comments
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4 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
The radiological incidents and terrorism have demanded the need for the development of rapid, precise, and non-invasive technique for detection and quantification of exposed dose of radiation. Though radiation induced metabolic markers have been thoroughly investigated, but reproducibility still needs to be elucidated. The present study aims at assessing the reliability and reproducibility of markers using nuclear magnetic resonance (NMR) spectroscopy and further deriving a logistic regression model based on these markers. C57BL/6 male mice (8-10 weeks) whole body γ-irradiated and sham irradiated controls were used. Urine samples collected at 24 h post dose were investigated using high resolution NMR spectroscopy and the datasets were analyzed using multivariate analysis. Fifteen distinguishable metabolites and 3 metabolic pathways (TCA cycle, taurine and hypotaurine metabolism, primary bile acid biosynthesis) were found to be amended. ROC curve and logistic regression was used to establish a diagnostic model as Logit (p) = log (p/1 - p) = -0.498 + 13.771 (tau) - 3.412 (citrate) - 34.461 (α-KG) + 515.183 (fumarate) with a sensitivity and specificity of 1.00 and 0.964 respectively. The findings demonstrate the proof of concept and the potential of NMR based metabolomics to establish a prediction model that can be implemented as a promising mass screening tool during triage.
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