Cross-validated sensing platform: Fe-based metal-organic frameworks nanozyme enables electron spin resonance and...

An electron spin resonance (ESR) and colorimetric dual-mode sensor was developed for the detection of cholesterol and hydrogen peroxide (H2O2), utilizing a synthesized iron-based metal-organic framework (Fe-MOFs) as a high-performance peroxidase mimic. This cascade — in which cholesterol is first converted to H2O2 by cholesterol oxidase and subsequently H2O2 is catalytically utilized by Fe-MOFs to oxidize ABTS into detectable ABTS•+ radical— enables dual-mode (ESR and colorimetric) detection. The superior catalytic activity of Fe-MOFs and its underlying •OH-involved mechanism were further verified respectively by enzyme kinetics and ESR spin-trapping experiments. Under optimized conditions, the sensor provided a linear range of up to 150 µmol L− 1 for cholesterol, with limits of detection (LODs) of 0.86 µmol L− 1 (ESR method) and 0.83 µmol L− 1 (colorimetric method). Additionally, a linear response was observed for H2O2, with LODs of 0.40 µmol L− 1 (ESR) and 0.45 µmol L⁻¹ (colorimetric). The method exhibited excellent selectivity against common interferents and was successfully applied to the determination of cholesterol in milk samples, achieving recoveries of 95.2–100.6% (ESR method) and 98.2–98.9% (colorimetric method). Remarkably, the excellent correlation (r = 0.9996) between the analytical results obtained from the ESR and colorimetric methods provides effective cross-validation (i.e. orthogonal signal verification) between these two independent techniques, significantly enhancing the overall reliability of the sensing platform. This dual-signal strategy enables robust mutual verification between colorimetric and ESR measurements. The colorimetric mode provides a simple, cost-effective, and visual semi-quantitative approach for routine analysis, while ESR spectroscopy serves as a reliable complementary tool for mechanistic validation and cross-validation, offering an accurate sensing strategy with promising applications in food analysis and quality control.