Abstract

Exhaled breath condensate is an emerging source of inflammatory biomarkers suitable for the noninvasive detection of respiratory disorders. Current gold standard methods are highly invasive and pose challenges in sample collection during airway inflammation monitoring. Cytokine biomarkers are detectable in EBC at increased or decreased concentrations. IL-6, IL-1β, IL-8, and hs-CRP are characteristic biomarkers identified in respiratory disorders. We have demonstrated the promising outcomes of a 16-plexed electrochemical platform - READ 2.0 for the multiplexed detection of characteristic biomarkers in EBC. The sensor demonstrates dynamic ranges of 1-243 pg/mL with a lower detection limit of 1 pg/mL for IL-6 and IL-1β, while the detection range and limit of detection for IL-8 and hs-CRP is 1-150 pg/mL and 3 pg/mL, respectively. The detection accuracies for the biomarkers are in the range of ∼85 ± 15% to ∼100 ± 10%. The sensor shows a nonspecific response to similar cross-reacting biomarkers. Analytical validation of the sensor with ELISA as the standard reference generated a correlation of R2 > 0.96 and mean biases of 10.9, 3.5, 17.4, and 3.9 pg/mL between the two methods for IL-6, IL-1β, IL-8, and hs-CRP, respectively. The precision of the sensor in detecting low biomarker concentrations yields a %CV of <7%. The variation in the sensor's response on repeat EBC sample measurements and within a 6 h duration is less than 10%. The READ 2.0 platform shows a promise that EBC-based biomarker detection can prove to be vital in predicting the severity and survival rates of respiratory disorders and serve as a reference point for monitoring EBC-based biomarkers.

Full Text
Paper version not known

Talk to us

Join us for a 30 min session where you can share your feedback and ask us any queries you have

Schedule a call

Disclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.