Machine learning-enhanced surface- enhanced spectroscopic detection of polycyclic aromatic hydrocarbons in the human placenta

• 成果类型: Article
• 署名作者: Neumann, Oara; Ju, Yilong; Alvarado, Andres B. Sanchez -; Zhou, Guodong; Jiang, Weiwu; Moorthy, Bhagavatula; Suter, Melissa A.; Patel, Ankit; Nordlander, Peter; Halas, Naomi J.
• 署名单位: Rice University; Rice University; Rice University; Rice University; Baylor College of Medicine; Baylor College of Medicine; Baylor College of Medicine; Rice University
• 刊物名称: PROCEEDINGS OF THE NATIONAL ACADEMY OF SCIENCES OF THE UNITED STATES OF AMERICA
• ISSN/ISSBN: 0027-11288
• DOI: 10.1073/pnas.2422537122
• 发表日期: 2025-02-18
• 关键词: p-32 postlabeling assay; dna-adducts; maternal smoking; mainstream smoke; cell-cycle; expression; induction; exposure; pahs; differentiation

摘要

The detection and identification of polycyclic aromatic hydrocarbons (PAHs) and their derivatives, polycyclic aromatic compounds (PACs), are essential for environmental and health monitoring, for assessing toxicological exposure and their associated health risks. PAHs/PACs are the most dangerous chemicals found in tobacco smoke, and cigarette use during pregnancy can convey these molecules to the developing fetus through the placenta. This exposure is associated with many negative health outcomes, from premature birth to sudden infant death syndrome and adverse neurodevelopmental disorders. This absorption spectroscopies for direct detection of PAHs/PACs in human placental tissue. Extraction (CaPE) and Characteristic Peak Similarity (CaPSim), to identify the specific pregnancy compared to spectra of the placenta from self- reported nonsmokers. CaPE verification was accomplished by detecting PAH- DNA and PAC- DNA adducts in the the streamlined detection of hazardous environmental compounds in human tissues, suggesting broader applications in clinical diagnostics and public health surveillance.