Smoke and Mirrors

A combination of spectroscopic techniques and machine learning (ML) has enabled researchers at Rice University and Baylor College of Medicine (BCM) to rapidly and accurately identify toxic chemicals in placental tissue, and distinguish between samples from smokers and non-smokers. 

Using surface-enhanced Raman spectroscopy (SERS) and surface-enhanced infrared absorption spectroscopy (SEIRAS), the team identified polycyclic aromatic hydrocarbons (PAHs) and polycyclic aromatic compounds (PACs) – harmful substances found in tobacco smoke – in smokers’ placential samples. PAHs and PACs have been linked to adverse pregnancy outcomes, including preterm birth, low birth weight, and developmental disorders such as gastroschisis.

"Our work addresses a critical challenge in maternal and fetal health by improving our ability to detect harmful compounds like PAHs and PACs in placenta samples," stated first author Oara Neumann, in the team’s press release.

The researchers employed two ML algorithms to process the spectral data: Characteristic Peak Extraction (CaPE) and Characteristic Peak Similarity (CaPSim). These tools enabled precise identification of PAH and PAC signatures in placental samples from mothers who reported smoking during pregnancy. 

“Picture a noisy and crowded room with lots of people talking at once. We are able to focus our attention on a particular conversation only by tuning out the rest,” explained Ankit Patel, co-author of the study. “In the same way, machine learning is able to parse through the spectral data associated with PAHs and PACs much more effectively than humans can.”

To verify their results, the researchers used 32P-postlabeling assays to detect PAH-DNA and PAC-DNA adducts – both biomarkers of toxic exposure. The presence of these molecular markers in smoker placentas confirmed the spectroscopic findings, validating the method's accuracy.

Co-author Bhagavatula Moorthy concluded that the research “lays the groundwork for expanding ultrasensitive PAH- and PAC-detection technology in biological fluids such as blood and urine as well as in the environmental monitoring of PAHs, PACs, and other hazardous chemicals in air, water and soil, thereby aiding in human risk assessment."