Red-emissive carbon nanostructure-anchored molecularly imprinted Er-BTC MOF: a biosensor for visual anthrax monitoring.
Solmaz NorouziKheibar DashtianFereshteh AmouriziRouholah Zare-DorabeiPublished in: The Analyst (2023)
Investigating effective fluorescence strategies for real-time monitoring of dipicolinic acid (DPA) is of paramount importance in safeguarding human health. Herein, we present the design of a desirable red-emissive carbon nanostructure anchoring a molecularly imprinted Er-BTC MOF as a fluorescence biosensor for the visual determination of DPA. DPA is a biomarker of Bacillus anthracis , a subcategory of serious infectious diseases and bioweapons. We introduce a paper test strip sensitized with the aforementioned nanostructure, which is integrated with online UV excitation and smartphone digital imaging, resulting in a DPA signal-off sensing platform. The proposed fluorometric visual paper-based biosensor demonstrates wide linear ranges for DPA (10-125 μM) with a LOQ and LOD of 4.32 and 1.28 μM, respectively. The designed platform exhibits impressive emission properties and adaptable surface functional groups, which confirm its desirable selective sensing capabilities against other biological molecules and DPA isomers. As a proof of concept, DPA monitoring is successfully applied to real samples of tap water and urine. This integrated selective paper-based nano-biosensor, coupled with smartphone signal recording, holds great promise for state-of-the-art practical applications including fluorometric/colorimetric detection in healthcare and environmental monitoring, food safety analysis, and point-of-care testing.
Keyphrases
- molecularly imprinted
- human health
- solid phase extraction
- gold nanoparticles
- label free
- sensitive detection
- healthcare
- risk assessment
- quantum dots
- infectious diseases
- single molecule
- high resolution
- high throughput
- energy transfer
- climate change
- nitric oxide
- social media
- breast cancer cells
- loop mediated isothermal amplification
- metal organic framework
- machine learning
- health insurance
- fluorescent probe
- neural network
- bacillus subtilis