Abstract

Oxidative-stress-related diseases generate elevated levels of hydrogen peroxide (H2O2) and other redox-active species in exhaled breath condensate (EBC), offering a promising avenue for non-invasive disease assessment. Despite its diagnostic potential, clinical translation of EBC redox species detection has been constrained by bulky analyzers, labor-intensive operation, and limited sensitivity. By harnessing the redox potential, we present a Redox-mediated Optochemical Plasmonic Sensing (ROPS) system, an ultrasensitive platform that enables real- time, easy-to-use, point-of-care quantitative analysis of H2O2_-equivalent reducing capacity in EBC. By coupling H2O2_-triggered gold nanoparticle growth on a phase-modulated plasmonic sensor, the ROPS system based on the phase-modulated interferometry achieved a detection limit of 1.19 pM and a wide dynamic range across 4 orders of magnitude. Moreover, the ROPS system demonstrated excellent reusability, maintaining stable H2O2 sensing performance over 40 reuse cycles. To enable point-of-care applications, we further developed a handheld high-efficiency EBC sampler, which harvested exhaled condensate at 2.49 μL/s and enabled an EBC- ROPS sampling-to-biosensing workflow down to 15 min. Clinical evaluation using EBC samples from lung and esophageal cancer patients and matched controls confirmed reliable quantification of trace H2O2_-equivalent Au (III)-reducing capacity in complex EBC matrices, highlighting the potential of the integrated ROPS platform as a practical tool for point-of-care and non-invasive oxidative stress-related disease assessment.

Fig. 1. Schematic illustration of the ROPS sensing mechanism and the system configuration. a) Reaction pathway of the H2O2-induced AuNI nanoparticle growth for quantitative H2O2 analysis. b) The AuNI chip within the CPSI system with highlighted microfluidic-based sensing cavity for ROPS detection (left). AFM height image of the AuNI chip (right). c) The CPSI platform with designed birefringent crystal and plasmonic sensing flow-cell was employed for optochemical ROPS detection. d) Representative real-time phase sensorgram of the redox-mediated AuNI growth for quantitative H2O2 analysis.

Fig. 2. Mechanistic Characterization and Optimization of H2O2 Detection with ROPS. a) Schematic illustration of the redox reaction mechanism for ROPS detection. b) Overall and c) enlarged view of interferometric LSPR spectra for ROPS analysis. The redshift of the LSPR resonance wavelength was caused by Au- nucleation and growth on the AuNI sensor surface. d) Comparison of the LSPR phase responses in the presence and absence of H2O2 centration at 100 μM. e) Phase sensorgrams for detecting 5 nM H2O2 under different HAuCl4 substrate concentrations at 10 μM and 100 μM. f) The LSPR phase responses toward 0.5 nM and 0.001 nM H2O2, which exhibited distinct deposition dynamics and stabilities.

https://doi.org/10.1016/j.bios.2026.119093