A FRET-based aptasensor exploiting the multiple functions of zirconium-based bimetallic organic frameworks for the quantitative determination of sulfadimethoxine.

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Title: A FRET-based aptasensor exploiting the multiple functions of zirconium-based bimetallic organic frameworks for the quantitative determination of sulfadimethoxine.
Authors: Esmaelpourfarkhani, Masoomeh1,2 (AUTHOR), Sumar, Mahshid Olfati2 (AUTHOR), Ramezani, Mohammad1 (AUTHOR), Alibolandi, Mona1 (AUTHOR), Abnous, Khalil1,2 (AUTHOR) abnouskh@mums.ac.ir, Taghdisi, Seyed Mohammad3,4 (AUTHOR) taghdisihm@mums.ac.ir
Source: Microchimica Acta. Jun2025, Vol. 192 Issue 6, p1-14. 14p.
Subjects: Fluorescence resonance energy transfer, Single-stranded DNA, Fluorescence quenching, Detection limit, Catalytic activity
Abstract: A novel fluorescent aptasensor was introduced for the assessment of sulfadimethoxine (SDM) using multiple functions of ZrFe metal–organic framework (MOF). This sensing strategy exploits the ZrFe MOF features including the peroxidase-mimicking feature, fluorescence characteristics, single-stranded DNA adsorption on its surface, and the change in its catalytic activity. In the detection mechanism, ferrofluid was used as separation agent and the peroxidized product quenched the fluorescence intensity of the ZrFe MOF through the fluorescence resonance energy transfer (FRET) effect. In this FRET-based approach, the existence or absence of SDM affects the attendance or non-attendance of complementary strand of aptamer (CS) in supernatant solution, which subsequently alters the peroxidase-like behavior of ZrFe MOF. Thus, the discrepancy in fluorescence intensity is caused by the variation in the amount of produced peroxidation product. Employing this sensing platform, a detection limit of 3 pM was achieved. Furthermore, the suggested sensing platform, leveraging the specificity of the aptamer for its target, demonstrated a significant potential to mitigate the influence of other interfering substances. The aptasensor has the capability to quantitatively detect SDM content in human serum samples. Therefore, it is well-suited for use in intricate matrices. [ABSTRACT FROM AUTHOR]
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  Data: A FRET-based aptasensor exploiting the multiple functions of zirconium-based bimetallic organic frameworks for the quantitative determination of sulfadimethoxine.
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  Data: <searchLink fieldCode="JN" term="%22Microchimica+Acta%22">Microchimica Acta</searchLink>. Jun2025, Vol. 192 Issue 6, p1-14. 14p.
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  Data: A novel fluorescent aptasensor was introduced for the assessment of sulfadimethoxine (SDM) using multiple functions of ZrFe metal–organic framework (MOF). This sensing strategy exploits the ZrFe MOF features including the peroxidase-mimicking feature, fluorescence characteristics, single-stranded DNA adsorption on its surface, and the change in its catalytic activity. In the detection mechanism, ferrofluid was used as separation agent and the peroxidized product quenched the fluorescence intensity of the ZrFe MOF through the fluorescence resonance energy transfer (FRET) effect. In this FRET-based approach, the existence or absence of SDM affects the attendance or non-attendance of complementary strand of aptamer (CS) in supernatant solution, which subsequently alters the peroxidase-like behavior of ZrFe MOF. Thus, the discrepancy in fluorescence intensity is caused by the variation in the amount of produced peroxidation product. Employing this sensing platform, a detection limit of 3 pM was achieved. Furthermore, the suggested sensing platform, leveraging the specificity of the aptamer for its target, demonstrated a significant potential to mitigate the influence of other interfering substances. The aptasensor has the capability to quantitatively detect SDM content in human serum samples. Therefore, it is well-suited for use in intricate matrices. [ABSTRACT FROM AUTHOR]
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  Data: <i>Copyright of Microchimica Acta is the property of Springer Nature and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract.</i> (Copyright applies to all Abstracts.)
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              Text: Jun2025
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