Towards grey-zone reliability in CA19-9 nanobiosensing: an AI-integrated molecular interface design-to-decision framework.

Authors

Ziyi Shang, Linya Shan, Che Liu, Dandan Zheng, Wantong Huang, Dan Li

Published in

Chemical communications (Cambridge, England). Aug 10, 2026. Epub Aug 10, 2026.

Abstract

Mildly elevated CA19-9 levels (typically 37-300 U mL^-1) define a diagnostic grey zone that fuels both patient anxiety and overdiagnosis, yet many nanobiosensing works continue to prioritise ever-lower detection limits over clinical reliability in this ambiguous interval. In this review, we argue for a use-case-specific shift from sensitivity-only reporting to reliability-centred translational nanobiosensing. An integrated "grey-zone reliability metrology" framework that unifies antifouling interface engineering, high-affinity molecular recognition, signal amplification, and AI-assisted interpretation as a single co-dependent system is proposed. Through interference-aware denoising, longitudinal trajectory modelling, and patient-specific baseline inference, borderline CA19-9 signals can be qualified and contextualised for clinical interpretation. The proposed design-to-decision logic may be adaptable to other grey-zone biomarkers, such as cardiac troponins and circulating tumour DNA, offering a cautious transferable framework for next-generation diagnostics that balance sensitivity with decision reliability. The framework is intended to qualify analytical uncertainty in an already measurable interval rather than to resolve the intrinsic disease-specific limitations of CA19-9 itself.

PMID:
42574111
Bibliographic data and abstract were imported from PubMed on 11 Aug 2026.

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