ArticlePNAS nexus2025
Raman investigation of in vivo radiation exposure on melanin in murine hair.
Article in PNAS nexus, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.
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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.
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Who cites it
1 citing paper in PubMed.
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Authors and funding
8 authors.
Funding
Abstract
Determining the effects of ionizing radiation from unintended exposure in a nuclear event requires the identification of relevant biomarkers and development of methods to retrospectively estimate the absorbed dose. Melanin, a biologically important natural pigment found in hair, shows promise as a biomarker to assess potential radiation exposure. We investigated Raman spectroscopy as a rapid and noninvasive technique to assess changes in melanin from the hair of C57BL/6 mice to gamma radiation between 0 and 4 Gy. Two excitation wavelengths (532 and 785 nm) were employed to probe the melanin response for changes with radiation exposure. Excitation wavelength-dependent variation in Raman features indicates resonance Raman effects, where a 785-nm excitation is more sensitive to the effects of gamma radiation. Melanin-specific Raman features were identified as potential biomarkers for gamma-radiation exposure and used to distinguish between irradiated and nonirradiated mice. Partial least square discriminant analysis models of exposure exhibited enhanced sensitivity to irradiation at 785 nm excitation and yielded a sensitivity of 88% and a specificity of 83%. Mice were classified with 100% sensitivity and specificity up to day 7 at a known time point. A decline in specificity and classification accuracy correlated with alterations in melanin's spectra after >7 days following irradiation. Regression models of the Raman spectrum determined the exposed dose with a precision of <1 Gy at a known exposure time point. This noninvasive approach offers promising applications in radiation biodosimetry and medical monitoring, providing retrospective detection of gamma-radiation exposure at clinically relevant doses.
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