Methodological assessment of PDMS passive sampling for skin VOC collection across body sites
Kobara, S.; Huang, M.; Ilhamsyah, R.; Struk, D.; Dimandja, J.; Hesketh, P. J.; Arrubla, D. C.; Fensore, C.; Polito, C.; Kamaleswaran, R.; Esper, A.
Show abstract
Background/ObjectivesPolydimethylsiloxane (PDMS) is a non-invasive and versatile material often used for non-invasive collection of skin-emitted volatile organic compounds (VOCs), with potential applicability in acute and pre-critical care settings. However, most existing PDMS-based methodologies rely on extensive sample preparation and environmental control, limiting their feasibility in time-sensitive clinical contexts. MethodsWe conducted a proof-of-concept pilot study in four healthy volunteers to evaluate whether a simplified skin-contact PDMS sampling procedure can capture detectable VOCs and preserve individual-level variation. PDMS strips were applied directly to the skin with minimal preparation, and collected VOCs were analyzed using gas chromatography-mass spectrometry. Donor-associated variability was assessed using Bray-Curtis dissimilarity, and variability in VOC detection was evaluated across body sites. ResultsSkin-contact PDMS sampling detected 160 VOCs across four participants. The mean within-donor Bray-Curtis dissimilarity was 0.308, compared with a mean between-donor dissimilarity of 0.347. Preliminary permutation testing showed distinguishable donor profiles (p-value = 0.004). VOC detection variability differed across body sites, with lower coefficients of variation at the forehead, neck, and wrist than at the ankle. ConclusionsUnder simplified sampling conditions, skin-contact PDMS captured individual-associated VOC profiles with lower within-donor variability than between-donor variability. These findings support the feasibility of PDMS-based skin VOC sampling in minimally controlled settings. Further validation in larger and clinically relevant cohorts is warranted to assess the utility of PDMS-sampled skin VOCs as potential biomarkers for early disease detection.
Matching journals
The top 8 journals account for 50% of the predicted probability mass.
Similar papers in this journal
- High-Quality and Easy-to-Regenerate Personal Filter 93%
- Air-liquid interface exposure of A549 human lung cells to characterize the hazard potential of a gaseous bio-hybrid fuel blend 93%
- Feasibility of Integrating Canine Olfaction with Chemical and Microbial Profiling of Urine to Detect Lethal Prostate Cancer 93%
Similar papers in this journal
- Machine learning identifies phenotypic profile alterations of human dopaminergic neurons exposed to bisphenols and perfluoroalkyls 92%
- Chemical and Sensory Analyses of Cultivated Pork Fat Tissue as a Flavor Enhancer for Meat Alternatives 91%
- Evaluation of at-home methods for N95 filtering facepiece respirator decontamination 91%
Similar papers in this journal
- Generation of false positive SARS-CoV-2 antigen results with testing conditions outside manufacturer recommendations: A scientific approach to pandemic misinformation 91%
- Machine-learning based detection of adventitious microbes in T-cell therapy cultures using long read sequencing 89%
- Investigating sensitivity of nasal or throat (ISNOT): A combination of both swabs increases sensitivity of SARS-CoV-2 rapid antigen tests 89%
"Similar papers" are the closest papers from that journal in the model's embedding space. They show what the match is built on, but the ranking comes mostly from a classifier over the whole training set, not from these examples alone.