A dual-mode sensing system based on carbon quantum dots and Fe nanozymes for the detection of α-glucosidase and its inhibitors

Lv, Yuntai; Zhou, Chenyu; Li, Meini; Huo, Zejiao; Wei, Zhiyuan; Wang, Nan; Wang, Guannan; Su, Xingguang

doi:10.1016/j.talanta.2023.125328

Cited by 7 publications

(1 citation statement)

References 38 publications

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“…To solve these issues, it is required to construct robust, fast, and efficient analytic platforms for accurate determination of H 2 S. Colorimetric analysis is fast, simple, low-cost, and on-the-spot, − while the electrochemical sensing platform is ultrasensitive and has great adaptability for H 2 S determination. , Notably, the colorimetric-based sensing platform possesses a significant color change, which can achieve the naked-eye readout for semiquantitative analysis . Despite the advanced effort in the rational design of the H 2 S sensing platform, the single signal output can still generate unstable and false results. − Integrating multiple signal analysis, which complements the merits of each sensing platform through different detection mechanisms, can obviously boost accuracy and reliability for H 2 S determination.…”

Section: Introductionmentioning

confidence: 99%

Smartphone Imaging Device for Multimodal Detection of Hydrogen Sulfide Using Cu-Doped MOF Sensors

Shang,

Zhang,

Ding

et al. 2024

ACS Appl. Mater. Interfaces

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Multimodal sensing platforms may offer reliable, fast results, but it is still challenging to incorporate biosensors with high discriminating ability in complex biological samples. Herein, we established a highly sensitive dual colorimetric/electrochemical monitoring approach for the detection of hydrogen sulfide (H 2 S) utilizing Cu-doped In-based metal−organic frameworks (Cu/In-MOFs) combined with a versatile color selector software-based smartphone imaging device. H 2 S can result in the enhancement of the electrochemical signal because of the electroactive substance copper sulfide (Cu x S), the decrease of the colorimetric signal of the characteristic absorption response caused by the strong coordination effect on Cu/In-MOFs, and the obvious changes of red-greenblue (RGB) values of images acquired via an intelligent smartphone. Attractively, the Cu/In-MOFs-based multimodal detection guarantees precise and sensitive detection of H 2 S with triple-signal detection limits of 0.096 μM (electrochemical signals), 0.098 μM (colorimetric signals), and 0.099 μM (smartphone signals) and an outstanding linear response. This analytical toolkit provides an idea for fabricating a robust, sensitive, tolerant matrix and reliable sensing platform for rapidly monitoring H 2 S in clinical disease diagnosis and visual supervision.

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