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2026年9月，麻省理工学院研究人员结合光学检测、空间基因分析和人工智能，尝试为衰老细胞建立可识别的特征组合。团队先用拉曼显微技术读取细胞的化学组成，再与组织中基因活动的空间分布对应，寻找既能反映衰老状态、又适合光学识别的信号。

研究比较了年轻与高龄小鼠的皮肤和肺组织，发现老年细胞中脂质合成和积累出现明显变化，不同组织还呈现各自的基因通路特征。研究人员把较有区分力的光谱峰和基因信号组合成类似条形码的指标，希望未来仅靠少数关键光学特征，就能更温和地定位衰老细胞。与需要消耗样本的分析方法相比，拉曼检测提供了保留细胞的可能。研究同时强调，细胞衰老并非只有负面作用，它也参与正常发育和组织修复。因此，新工具主要帮助理解和追踪细胞状态，不能把所有带有衰老特征的细胞都视为应被清除的目标，相关功能仍需逐项研究。

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