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A portable and versatile rGO-Co₃O₄-Pt Nanocomposite-based Electrochemical Sensor for In Vitro and In Vivo Cardiac Stress Monitoring

Sima Singh, Stefania Melini, Ada Raucci, Arshid Numan, Mohammad Khalid, Rosaria Meli, Claudio Pirozzi, Stefano Cinti

ChemRxiv, 2025

Abstract

Excessive reactive oxygen species (ROS) under pathophysiological conditions primarily initiate oxidative stress, which contributes to the development of atherosclerosis and other cardiovascular diseases. Hydrogen peroxide (H2O2) is a crucial oxidative stress biomarker due to its stability and significant role in signaling pathways linked to cellular damage. Hence, H₂O₂ detection is crucial for early disease diagnosis, understanding oxidative stress mechanisms, and therapeutic intervention, especially in cardiac health, where oxidative damage is significant. However, efficient, highly selective & sensitive, quick, and accurate H₂O₂ detection remains a challenge in the protracted battle against oxidative stress-related diseases. The study presents a fast, portable, low-cost, and versatile oxidative stress detection platform using a rGO-Co₃O₄-Pt nanocomposites electrochemical sensor platform, which can be remotely controlled. The sensors offer ultrasensitive, versatile cardiac stress monitoring, with H2O2 detection up to 2.50 µM, low LOD (0.16 µM) and LOQ (0.50 µM), with anti-interference capability and biocompatibility, indicating the possibility of real-sample analysis. Furthermore, we conducted studies on doxorubicin (DOX)-induced cardiotoxicity in vitro (HL-1 cell lines) and in vivo (adult C57BL/6J mice model). The study indicates that the rGO-Co₃O₄-Pt nanocomposite electrochemical sensor platform can efficiently and accurately detect diseases. This work provides direct…

How strong is the evidence?

Evidence Hub reads this as a preprint, done in animal and cell cultures (in vitro), not in people. Its evidence level is 5 of 5 (Very low · case / narrative / animal / in vitro / in silico). Case reports, narrative reviews, and animal, cell or computer-model studies give the weakest evidence for human health.

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