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Updated: Aug 24, 2026

NiO Nanoflowers for Non-Enzymatic Amperometric Detection of Glucose
Published on: December 30, 2025
β‑Anomeric Mannopentaose-Based Nonenzymatic NIR Glucose Sensor Enabling Cost-Effective Continuous Monitoring
Sayantan Tripathy1,2, Diana Al Husseini1,2, Carolina I Martinez2,3
1Department of Biomedical Engineering, Texas A&M University, 600 Discovery Drive, College Station, Texas 77840-3006, United States.
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In this study, we present a novel, fully injectable, nonenzymatic glucose biosensing platform that uses NIR fluorescence from a PEGylated-ConA and Cy5.5-β-mannopentaose complex to achieve highly sensitive and stable detection. The proof-of-concept assay is designed for high sensitivity, long-term stability, a small size to permit injectability or minimal invasiveness, suitability across all skin tones, and cost-effectiveness. As a control, an analogous assay was prepared with the α-anomeric form (i.e., Cy5.5-α-mannopentaose), which is 10X costlier. Using fluorescence anisotropy, a computational model was developed to optimize the concentration ratios of assay components for sensitive glucose detection within the physiological range. Both conjugates demonstrated comparable responsiveness across physiological glucose concentrations, with Cy5.5-β-mannopentaose exhibiting a broader dynamic range (25-400 mg/dL) in buffer and comparable binding affinity. In addition, performance was validated in artificial interstitial fluid with Cy5.5-β-mannopentaose showing reproducible solvatochromism across the full blood glucose range (25-400 mg/dL), with strong responsiveness maintained within the physiologically relevant subcutaneous window. To further validate its ability to be housed in a membrane carrier, the Cy5.5-β-mannopentaose solution was placed in the cavity of a hollow hydrogel rod with known antifouling properties and mesh size, and >94% was retained over a 7-day period. These results establish β-mannopentaose as a promising low-cost ligand for ConA-based glucose sensing systems and support its potential use in the future development of minimally invasive and scalable glucose sensing approaches.

