Standardised and scalable methods to quantify and characterise MNP in environmental compartments and matrices in the human body (ATHENA)

The ATHENA project - Standardised and scalable methods to quantify and characterise micro- and nanoplastics in environmental compartments and matrices in the human body - was conducted was to strengthen the scientific basis for assessing human health risks of micro- and nanoplastic (MNP) particles. This was achieved by developing and integrating (1) quantitative Quality Assurance/Quality Control (QA/QC) frameworks for literature data, and (2) statistical Probability Density Function (PDF) tools for harmonising heterogeneous exposure and toxicity datasets. The dataset contains results from large-scale literature screenings and AI-assisted data extraction covering over 7,000 exposure and 1,400 effect publications. Approximately 950 exposure studies (air, food, beverages) and 700 effect studies were retained for scoring. QA/QC criteria (13 for exposure; 18–24 for effect studies) evaluated reporting quality in particle characterisation, contamination control, experimental design, and risk-assessment relevance. The repository includes: Processed literature datasets (e.g., Table_S1_Literature Dataset.xlsx, META_SCORE.csv), AI-extracted data for classification, particles, thresholds, and exposure (Gemini_extracted_*.xlsx, GPT_extracted_*.xlsx), Validated concentration datasets for air, food, and beverages (Table_S6–S8.xlsx), Power-law and PDF fitting results (Table_S3_pwr_fitting_result.xlsx), Prompt files defining the modular AI extraction structure, and Human validation files (CHECK_87_upload_YODA.xlsx). Together, these datasets provide a harmonised, quality-ranked foundation for comparing MNP exposure and effect data across media and studies, thereby supporting the first quantitative human health risk assessments for microplastics.ATHENA项目——用于量化和表征环境介质及人体基质中微塑料与纳米塑料（micro- and nanoplastics, MNP）的标准化可扩展方法——旨在为评估微塑料与纳米塑料（MNP）颗粒对人类健康的风险夯实科学基础。该项目通过两大核心模块达成目标：一是构建并整合面向文献数据的量化质量保证/质量控制（Quality Assurance/Quality Control, QA/QC）框架，二是开发统计概率密度函数（Probability Density Function, PDF）工具以统一异质性暴露与毒性数据集。 本数据集涵盖大规模文献筛选与AI辅助数据提取的成果，涉及超过7000篇暴露相关文献与1400篇效应相关文献。最终筛选保留约950项暴露研究（覆盖空气、食品、饮料三类介质）与700项效应研究，并对其进行评分。质量保证/质量控制标准（暴露研究含13项标准，效应研究含18至24项标准）用于评估研究在颗粒表征、污染控制、实验设计及风险评估相关性方面的报告质量。 该数据集仓库包含以下内容： 1. 处理后的文献数据集（如Table_S1_Literature Dataset.xlsx、META_SCORE.csv）； 2. 用于分类、颗粒信息、阈值及暴露场景的AI提取数据（Gemini_extracted_*.xlsx、GPT_extracted_*.xlsx）； 3. 经验证的空气、食品及饮料中微塑料与纳米塑料浓度数据集（Table_S6–S8.xlsx）； 4. 幂律分布与概率密度函数拟合结果（Table_S3_pwr_fitting_result.xlsx）； 5. 定义模块化AI提取框架的提示词文件； 6. 人工验证文件（CHECK_87_upload_YODA.xlsx）。 上述数据集共同构成了一套统一化、按质量分级的研究基础，可用于跨介质与跨研究的微塑料与纳米塑料暴露及效应数据对比，从而为微塑料的首次定量人类健康风险评估提供支撑。