Objective: This systematic review aims to synthesize current knowledge on Propylene Oxide (PO) in human exhaled breath, examining its presence across various biological matrices and exploring methodologies for its analysis. It seeks to elucidate the sources of PO in the human body and understand individual variability in detoxification processes. Methods: A comprehensive literature search was conducted across 12 databases and specialized repositories, spanning over 10,000 publications without language restrictions until February 2024. Sixteen AI tools were employed to enhance study identification and analysis, focusing on both direct mentions and indirect evidence of PO behavior and detection in the human body. Assessment tools for risk of bias included SYRCLE's tool for animal studies, the Newcastle-Ottawa Scale for cohort and case-control studies, and the ROBINS-I tool for non-randomized studies. The selection process yielded 88 studies, encompassing a range of research types and species, supplemented by reviews, monographs, and editorials to provide a comprehensive overview. Results: he search revealed limited direct evidence on PO concentrations in exhaled breath, with only one reference providing concrete data (0.083 ppb to 0.3 ppb). However, numerous references offered indirect insights into PO's persistence and detection in the human body, particularly in blood and urine. The review highlights the enzymes involved in PO metabolism, the evolution of analytical methodologies, and the challenges and potentials of employing AI tools in systematic reviews. Conclusions: The scarcity of direct evidence on PO in exhaled breath underscores a significant gap in the literature and indicates variability in environmental compound concentrations influenced by genetics, health status, metabolism, and the microbiome. The review emphasizes the difficulties in synthesizing data on PO effects due to heterogeneous inputs and complex exposure scenarios. It underscores the need for advanced AI capabilities in literature reviews to capture nuanced, indirect evidence more effectively and calls for targeted research and technological innovation in environmental health sciences. This study advocates for the strategic enhancement of AI tools to navigate scientific literature with greater efficacy, leveraging PRISMA guidelines and diverse data sources to minimize bias and enhance reliability.

The authors have declared no competing interest.

https://www.crd.york.ac.uk/PROSPERO/display_record.php?RecordID=397159

This study did not receive any funding

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All data produced are accessible via the Open Science Framework (OSF) repository, which serves as a platform for data sharing and collaborative research.

https://osf.io/w7682/