Proof-of-concept of pressure-ulcer-associated VOC biomarkers’ detection using a nanocomposite-based quantum resistive vapour sensor array
Abstract
Pressure ulcers (PU), commonly referred to as bedsores, are a major health problem for which early detection remains challenging. Volatile organic compounds (VOC) released from pressure-affected skin have been proposed as potential biomarkers, providing a complementary approach to conventional visual and pressure-based monitoring. In this study, a cross-reactive electronic nose (e-nose) comprising nine quantum resistive vapour sensors (vQRS) was evaluated for the detection of three VOC previously associated with pressure-ulcer-related skin emissions: benzyl alcohol, pentadecane and 1-tetradecene. The vQRS transducers consisted of carbon nanotube (CNT) networks functionalized with different polymer matrices, namely poly (vinylpyrrolidone), poly (vinyl acetate), poly (lactic acid), poly (ethylene glycol), poly (caprolactone), poly (methyl methacrylate), poly (styrene-co-acrylonitrile), polystyrene and sulfonated poly (ether ether ketone). The individual sensors were first evaluated using benzyl alcohol and water vapour at concentrations ranging from approximately 100 ppb to 1 ppm. A measurable response was obtained at 100 ppb, with signal-to-noise ratios exceeding five for six vQRS. Water vapour modified the response amplitude and apparent sensitivity to benzyl alcohol, highlighting the importance of humidity effects under skin-relevant conditions. The sensor array was subsequently exposed to synthetic mixtures containing the selected biomarkers in a complex VOC background with controlled water vapour content. Principal component analysis (PCA) of the sensor responses enabled discrimination between the different biomarker-containing mixtures, their concentrations, and the background mixture. Combining the maximum response amplitude with the integrated response area further improved separation in the PCA score space compared with amplitude alone. PCA was used as an exploratory visualization tool; no supervised classification or cross-validation was performed, and the data were obtained from synthetic mixtures and a single background donor. These results demonstrate the feasibility of using a cross-reactive CNT/polymer vQRS array to detect pressure-ulcer-associated VOC signatures under controlled laboratory conditions. The study illustrates the possible recognition of synthetic blends of three candidate VOC added to a healthy-skin background (one donor, four skin sites). Further studies using real skin emissions from individuals will target the discrimination between healthy and patients with pressure ulcers to assess the robustness and clinical diagnostic value of the approach.
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BibTeX
@article{tran2026proofofconcept,
title = {{Proof-of-concept of pressure-ulcer-associated VOC biomarkers’ detection using a nanocomposite-based quantum resistive vapour sensor array}},
author = {Manh Trung Tran and Abhishek Sachan and Mickaël Castro and Jean-François Feller},
journal = {Journal of Nanotheranostics},
year = {2026},
month = oct,
doi = {10.3390/jnt7040025},
url = {https://hal.science/hal-05848781v1},
note = {CC BY 4.0},
}
RIS
TY - JOUR
TI - Proof-of-concept of pressure-ulcer-associated VOC biomarkers’ detection using a nanocomposite-based quantum resistive vapour sensor array
AU - Manh Trung Tran
AU - Abhishek Sachan
AU - Mickaël Castro
AU - Jean-François Feller
PY - 2026
DA - 2026/10/26
JO - Journal of Nanotheranostics
DO - 10.3390/jnt7040025
UR - https://hal.science/hal-05848781v1
AB - Pressure ulcers (PU), commonly referred to as bedsores, are a major health problem for which early detection remains challenging. Volatile organic compounds (VOC) released from pressure-affected skin have been proposed as potential biomarkers, providing a complementary approach to conventional visual and pressure-based monitoring. In this study, a cross-reactive electronic nose (e-nose) comprising nine quantum resistive vapour sensors (vQRS) was evaluated for the detection of three VOC previously associated with pressure-ulcer-related skin emissions: benzyl alcohol, pentadecane and 1-tetradecene. The vQRS transducers consisted of carbon nanotube (CNT) networks functionalized with different polymer matrices, namely poly (vinylpyrrolidone), poly (vinyl acetate), poly (lactic acid), poly (ethylene glycol), poly (caprolactone), poly (methyl methacrylate), poly (styrene-co-acrylonitrile), polystyrene and sulfonated poly (ether ether ketone). The individual sensors were first evaluated using benzyl alcohol and water vapour at concentrations ranging from approximately 100 ppb to 1 ppm. A measurable response was obtained at 100 ppb, with signal-to-noise ratios exceeding five for six vQRS. Water vapour modified the response amplitude and apparent sensitivity to benzyl alcohol, highlighting the importance of humidity effects under skin-relevant conditions. The sensor array was subsequently exposed to synthetic mixtures containing the selected biomarkers in a complex VOC background with controlled water vapour content. Principal component analysis (PCA) of the sensor responses enabled discrimination between the different biomarker-containing mixtures, their concentrations, and the background mixture. Combining the maximum response amplitude with the integrated response area further improved separation in the PCA score space compared with amplitude alone. PCA was used as an exploratory visualization tool; no supervised classification or cross-validation was performed, and the data were obtained from synthetic mixtures and a single background donor. These results demonstrate the feasibility of using a cross-reactive CNT/polymer vQRS array to detect pressure-ulcer-associated VOC signatures under controlled laboratory conditions. The study illustrates the possible recognition of synthetic blends of three candidate VOC added to a healthy-skin background (one donor, four skin sites). Further studies using real skin emissions from individuals will target the discrimination between healthy and patients with pressure ulcers to assess the robustness and clinical diagnostic value of the approach.
SN - 2624-845X
ER -