Poonia Monika, Witte Spencer A, Woodward Mallard, Yadav Prasant, Puri Sapna, Santhanam Ramasamy, Jacob Naduparambil K, Schultz Zachary D
Department of Chemistry and Biochemistry, The Ohio State University, Columbus, OH 43210, USA.
Department of Radiation Oncology, College of Medicine, The Ohio State University, Columbus, OH 43210, USA.
PNAS Nexus. 2025 Apr 8;4(4):pgaf108. doi: 10.1093/pnasnexus/pgaf108. eCollection 2025 Apr.
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.
确定核事件中非预期暴露的电离辐射影响需要识别相关生物标志物,并开发回顾性估计吸收剂量的方法。黑色素是毛发中一种具有重要生物学意义的天然色素,有望作为评估潜在辐射暴露的生物标志物。我们研究了拉曼光谱法,这是一种快速且非侵入性的技术,用于评估C57BL/6小鼠毛发中黑色素对0至4 Gy伽马辐射的变化。采用两个激发波长(532和785 nm)来探测黑色素对辐射暴露变化的响应。拉曼特征中激发波长依赖性变化表明存在共振拉曼效应,其中785 nm激发对伽马辐射的影响更敏感。黑色素特异性拉曼特征被确定为伽马辐射暴露的潜在生物标志物,并用于区分受辐照和未受辐照的小鼠。暴露的偏最小二乘判别分析模型在785 nm激发下对辐照表现出更高的敏感性,灵敏度为88%,特异性为83%。在已知时间点,小鼠在第7天之前的分类灵敏度和特异性均为100%。辐照后>7天,特异性和分类准确性的下降与黑色素光谱的变化相关。拉曼光谱的回归模型在已知暴露时间点确定暴露剂量的精度<1 Gy。这种非侵入性方法在辐射生物剂量测定和医学监测方面具有广阔的应用前景,能够回顾性检测临床相关剂量的伽马辐射暴露。