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An anthracene-based hydrogen-bonded organic framework as a bifunctional fluorescent sensor for the detection of γ-aminobutyric acid and nitrofurazone
Inorganic Chemistry Frontiers ( IF 6.1 ) Pub Date : 2022-06-01 , DOI: 10.1039/d2qi00542e Yanhong Liu 1 , Xin Xu 1 , Bing Yan 1
Inorganic Chemistry Frontiers ( IF 6.1 ) Pub Date : 2022-06-01 , DOI: 10.1039/d2qi00542e Yanhong Liu 1 , Xin Xu 1 , Bing Yan 1
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Intelligent fluorescence detection for disease diagnosis has become a research hotspot. In the era of big data, machine learning (ML) for analyzing data and mining will be widely used in drug and biomarker detection. A novel hydrogen-bonded organic framework (HOF) HOF-DBA with good luminescence properties was successfully prepared from aromatic tetracarboxylic acid (4,4′-(anthracene-9,10-diyl)dibenzoic acid) by a solvothermal method. HOF-DBA acted as a fluorescent sensor to quantitatively identify the concentration of nitrofurazone (NFZ) by photo-induced electron transfer (PET) and competitive absorption. The detection limit was lower than 0.002 μg mL−1, with high sensitivity and good reproducibility. HOF-DBA also exhibited highly efficient turn-up fluorescence sensing of γ-aminobutyric acid (GABA osteoporosis biomarker) in aqueous solution and serum. In addition, a back-propagation neural network (BPNN) model based on HOF-DBA and GABA was constructed for the first time. The actual test data showed that BPNN could accurately distinguish GABA concentrations by the maximum depth likelihood method. This work provides new insights into HOF-based sensors and combines fluorescence sensing with deep ML to achieve intelligent fluorescence detection of GABA.
中文翻译：
蒽基氢键有机骨架作为双功能荧光传感器检测γ-氨基丁酸和呋喃西林
用于疾病诊断的智能荧光检测已成为研究热点。在大数据时代，用于分析数据和挖掘的机器学习（ML）将广泛应用于药物和生物标志物检测。以芳香族四羧酸(4,4'-(anthracene-9,10-diyl)dibenzoic acid)为原料，采用溶剂热法成功制备出具有良好发光性能的新型氢键有机骨架(HOF) HOF-DBA。HOF-DBA 作为荧光传感器，通过光诱导电子转移 (PET) 和竞争性吸收来定量识别呋喃西林 (NFZ) 的浓度。检测限低于0.002 μg mL -1，灵敏度高，重现性好。HOF-DBA 还表现出对水溶液和血清中 γ-氨基丁酸（GABA 骨质疏松症生物标志物）的高效荧光检测。此外，首次构建了基于HOF-DBA和GABA的反向传播神经网络（BPNN）模型。实际测试数据表明，BPNN可以通过最大深度似然法准确区分GABA浓度。这项工作为基于 HOF 的传感器提供了新的见解，并将荧光传感与深度 ML 相结合，实现了 GABA 的智能荧光检测。
更新日期：2022-06-01
中文翻译：
蒽基氢键有机骨架作为双功能荧光传感器检测γ-氨基丁酸和呋喃西林
用于疾病诊断的智能荧光检测已成为研究热点。在大数据时代，用于分析数据和挖掘的机器学习（ML）将广泛应用于药物和生物标志物检测。以芳香族四羧酸(4,4'-(anthracene-9,10-diyl)dibenzoic acid)为原料，采用溶剂热法成功制备出具有良好发光性能的新型氢键有机骨架(HOF) HOF-DBA。HOF-DBA 作为荧光传感器，通过光诱导电子转移 (PET) 和竞争性吸收来定量识别呋喃西林 (NFZ) 的浓度。检测限低于0.002 μg mL -1，灵敏度高，重现性好。HOF-DBA 还表现出对水溶液和血清中 γ-氨基丁酸（GABA 骨质疏松症生物标志物）的高效荧光检测。此外，首次构建了基于HOF-DBA和GABA的反向传播神经网络（BPNN）模型。实际测试数据表明，BPNN可以通过最大深度似然法准确区分GABA浓度。这项工作为基于 HOF 的传感器提供了新的见解，并将荧光传感与深度 ML 相结合，实现了 GABA 的智能荧光检测。
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