Pub Date : 2025-12-31DOI: 10.1016/j.snb.2025.139414
Guangying Zhou , Bin Tang , Bingsheng Du , Zipei Chen , Le Chen , Haifeng Xiong , Peng Cheng , Yong He
Accurate detection of low-concentration acetone in humid environments remains a critical challenge for non-invasive disease diagnosis. This study proposes a co-design strategy combining a phosphate-functionalized metal oxide sensor with a novel CBAM-GSABP neural network to achieve robust ppb-level acetone detection under varying humidity. The sensitivity of the sensor toward acetone is enhanced via phosphate-modified surface interactions, while the lightweight neural network integrates a channel attention mechanism (CBAM) and genetic simulated annealing (GSA) optimization to adaptively suppress humidity interference and optimize hyperparameters. Experimental results demonstrate that the phosphate-functionalized WO3 gas sensor achieves an enhanced gas sensitivity, with a response of 90 % and a response time of 159 s to 200 ppb acetone. The CBAM-GSABP model achieves excellent performance in acetone detection in a variable humidity environment, with an average R² of 0.9834, RMSE of 5.7226 ppb, and MAE of 3.4878 ppb. This work provides a reliable and efficient solution for trace gas detection and proposes a new idea for small sample modeling tasks in practical applications.
{"title":"Phosphate-functionalized MOS gas sensor for parts per billion-level acetone detection: A CBAM-GSABP neural network approach overcoming humidity interference","authors":"Guangying Zhou , Bin Tang , Bingsheng Du , Zipei Chen , Le Chen , Haifeng Xiong , Peng Cheng , Yong He","doi":"10.1016/j.snb.2025.139414","DOIUrl":"10.1016/j.snb.2025.139414","url":null,"abstract":"<div><div>Accurate detection of low-concentration acetone in humid environments remains a critical challenge for non-invasive disease diagnosis. This study proposes a co-design strategy combining a phosphate-functionalized metal oxide sensor with a novel CBAM-GSABP neural network to achieve robust ppb-level acetone detection under varying humidity. The sensitivity of the sensor toward acetone is enhanced via phosphate-modified surface interactions, while the lightweight neural network integrates a channel attention mechanism (CBAM) and genetic simulated annealing (GSA) optimization to adaptively suppress humidity interference and optimize hyperparameters. Experimental results demonstrate that the phosphate-functionalized WO<sub>3</sub> gas sensor achieves an enhanced gas sensitivity, with a response of 90 % and a response time of 159 s to 200 ppb acetone. The CBAM-GSABP model achieves excellent performance in acetone detection in a variable humidity environment, with an average R² of 0.9834, RMSE of 5.7226 ppb, and MAE of 3.4878 ppb. This work provides a reliable and efficient solution for trace gas detection and proposes a new idea for small sample modeling tasks in practical applications.</div></div>","PeriodicalId":425,"journal":{"name":"Sensors and Actuators B: Chemical","volume":"451 ","pages":"Article 139414"},"PeriodicalIF":3.7,"publicationDate":"2025-12-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145881065","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"化学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2025-12-30DOI: 10.1016/j.snb.2025.139411
Zhiqing Wen , Wenyuan Jiang , Long Yu , Jia Liu , Ziqing Liu , Xin Yang , Qiushuo Zheng , Xin Li , Yuning Wang , Suhua Wang
Uranium’s radioactive and chemical toxicity poses serious risks to the environment and human health. This study introduces a rapid, sensitive in situ detection method for uranyl ions (UO22 +) in complex samples using a dual-emission ratiometric fluorescent probe based on urea-functionalized metal-organic frameworks (MOFs). The probe employs the inner filter effect (IFE) and fluorescence enhancement of uranyl-phosphate complexes for accurate ratiometric detection. Selective recognition of UO22+ in Britton–Robinson buffer is achieved through dual-channel optical signals, with blue-light quenching at 428 nm and green-light enhancement at 521 nm. The detection limit is 24.6 μg/L, below the WHO drinking water standard of 30 μg/L, with a linear range of 10–90 μM. The probe shows strong selectivity against more than 20 coexisting ions and excellent stability. Furthermore, a lightweight dual-task deep learning model built on the Keras framework decodes fluorescence color signals, improving both accuracy and visualization. This strategy significantly enhances overall performance. In conclusion, the probe offers a low-cost and efficient platform for uranium monitoring, water screening, and resource management, showing broad potential in environmental pollution detection and public health protection.
{"title":"Intelligent visual recognition of UO₂²⁺ ions using a machine learning-based metal-organic framework ratiometric fluorescent probe","authors":"Zhiqing Wen , Wenyuan Jiang , Long Yu , Jia Liu , Ziqing Liu , Xin Yang , Qiushuo Zheng , Xin Li , Yuning Wang , Suhua Wang","doi":"10.1016/j.snb.2025.139411","DOIUrl":"10.1016/j.snb.2025.139411","url":null,"abstract":"<div><div>Uranium’s radioactive and chemical toxicity poses serious risks to the environment and human health. This study introduces a rapid, sensitive in situ detection method for uranyl ions (UO<sub>2</sub><sup>2 +</sup>) in complex samples using a dual-emission ratiometric fluorescent probe based on urea-functionalized metal-organic frameworks (MOFs). The probe employs the inner filter effect (IFE) and fluorescence enhancement of uranyl-phosphate complexes for accurate ratiometric detection. Selective recognition of UO<sub>2</sub><sup>2+</sup> in Britton–Robinson buffer is achieved through dual-channel optical signals, with blue-light quenching at 428 nm and green-light enhancement at 521 nm. The detection limit is 24.6 μg/L, below the WHO drinking water standard of 30 μg/L, with a linear range of 10–90 μM. The probe shows strong selectivity against more than 20 coexisting ions and excellent stability. Furthermore, a lightweight dual-task deep learning model built on the Keras framework decodes fluorescence color signals, improving both accuracy and visualization. This strategy significantly enhances overall performance. In conclusion, the probe offers a low-cost and efficient platform for uranium monitoring, water screening, and resource management, showing broad potential in environmental pollution detection and public health protection.</div></div>","PeriodicalId":425,"journal":{"name":"Sensors and Actuators B: Chemical","volume":"451 ","pages":"Article 139411"},"PeriodicalIF":3.7,"publicationDate":"2025-12-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145895142","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"化学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2025-12-30DOI: 10.1016/j.snb.2025.139410
Longyu Ren, Yuhang Du, Ya Wang, Jinan Li, Ruojin Zhang, Jiliang Yuan, Hongyan Xu
In2O3, as a traditional metal oxide semiconductor substrate material, responds to various toxic and harmful gases but with poor selectivity. This paper uses the hydrothermal method to grow dense and uniform In2O3 nanorods vertically on a ceramic tube, and then covers them with ZIF-71. By adjusting the type of solvent used to synthesize ZIF-71, the morphology and properties of the material can be changed. The pores and large specific surface area of ZIF-71 are utilized to sieve large molecular gases, providing more adsorption sites for NO2 gas. And it forms heterostructure with In2O3 to enhance the response to NO2. The optimized gas sensor In2O3@ZIF-71(CH3OH) shows superior response (185, S=Rg/Ra) and selectivity of 50 ppm triethylamine as an interfering gas (7.23, S=Ra/Rg) to 50 ppm NO2 compared to pure In2O3 nanorods. Molecular dynamics simulation is used to study the gas adsorption performance of ZIF-71 and theoretical simulation of the adsorption behavior of NO2 on the In2O3 substrate is conducted through density functional theory. The simulation results show that the ZIF-71 molecular sieve can reduce the response to large molecule TEA gas through the dual effects of pore size adsorption and blocking, thereby improving the selectivity of the material. Indium oxide (In2O3) has an adsorption effect on nitrogen dioxide (NO2), with an adsorption heat of 0.499 electron volts, and its adsorption effect is relatively stable.
{"title":"Enhanced selectivity and response performance of the NO2 sensor composed of ZIF-71-coated In2O3 nanorods grown vertically on ceramic tubes","authors":"Longyu Ren, Yuhang Du, Ya Wang, Jinan Li, Ruojin Zhang, Jiliang Yuan, Hongyan Xu","doi":"10.1016/j.snb.2025.139410","DOIUrl":"10.1016/j.snb.2025.139410","url":null,"abstract":"<div><div>In<sub>2</sub>O<sub>3</sub>, as a traditional metal oxide semiconductor substrate material, responds to various toxic and harmful gases but with poor selectivity. This paper uses the hydrothermal method to grow dense and uniform In<sub>2</sub>O<sub>3</sub> nanorods vertically on a ceramic tube, and then covers them with ZIF-71. By adjusting the type of solvent used to synthesize ZIF-71, the morphology and properties of the material can be changed. The pores and large specific surface area of ZIF-71 are utilized to sieve large molecular gases, providing more adsorption sites for NO<sub>2</sub> gas. And it forms heterostructure with In<sub>2</sub>O<sub>3</sub> to enhance the response to NO<sub>2</sub>. The optimized gas sensor In<sub>2</sub>O<sub>3</sub>@ZIF-71(CH<sub>3</sub>OH) shows superior response (185, <em>S=R</em><sub>g</sub>/<em>R</em><sub>a</sub>) and selectivity of 50 ppm triethylamine as an interfering gas (7.23, <em>S=R</em><sub>a</sub>/<em>R</em><sub>g</sub>) to 50 ppm NO<sub>2</sub> compared to pure In<sub>2</sub>O<sub>3</sub> nanorods. Molecular dynamics simulation is used to study the gas adsorption performance of ZIF-71 and theoretical simulation of the adsorption behavior of NO<sub>2</sub> on the In<sub>2</sub>O<sub>3</sub> substrate is conducted through density functional theory. The simulation results show that the ZIF-71 molecular sieve can reduce the response to large molecule TEA gas through the dual effects of pore size adsorption and blocking, thereby improving the selectivity of the material. Indium oxide (In<sub>2</sub>O<sub>3</sub>) has an adsorption effect on nitrogen dioxide (NO<sub>2</sub>), with an adsorption heat of 0.499 electron volts, and its adsorption effect is relatively stable.</div></div>","PeriodicalId":425,"journal":{"name":"Sensors and Actuators B: Chemical","volume":"451 ","pages":"Article 139410"},"PeriodicalIF":3.7,"publicationDate":"2025-12-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145881067","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"化学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2025-12-30DOI: 10.1016/j.snb.2025.139376
Raji V. Nair , Saju Pillai , Reny Thankam Thomas
Surface Enhanced Raman Scattering (SERS) is a powerful technique for detecting trace-level analytes including drug residues, explosives, and environmental pollutants. However, high-cost, non-reusable conventional substrates fabricated under cleanroom conditions limit widespread deployment. Here, we present a scalable and cost-effective strategy to fabricate large-area periodic polymeric photonic–plasmonic platforms using the breath figure (BF) method combined with controlled silver (Ag) nanostructure integration for enhanced SERS applications. The BF process generates highly ordered hexagonal pore arrays that confine Ag nanoparticles (AgNPs), creating dense electromagnetic hotspots. AgNPs were incorporated via in-situ chemical reduction, achieving detection limits of 1 fM for omethoate (OM) and methylene blue (MB). Additionally, ex-situ deposition with plasma activation and vertical infiltration further enhanced nanoparticle confinement and hotspot density, reaching detection limits as low as 0.1 fM. Vibrational signatures remained well-resolved, supported by analytical enhancement factors of ∼107. The substrates retained over 92 % of initial Raman intensity after five weeks and exhibited high batch-to-batch reproducibility (RSD 4.2 %), demonstrating scalable reliability. TiO2-assisted UV photocatalytic cleaning enabled 93–95 % SERS signal recovery after five reuse cycles, confirming structural robustness and efficient analyte removal. XPS analyses revealed a decrease in defect-related O 1 s components and the formation of Ag–O–Ti interfacial species, indicating a charge-transfer mediated regeneration mechanism. Sensitive detection of OM in spiked river water and vegetable extracts yielded > 90 % recovery, demonstrating real-sample applicability. Overall, the TiO2-coated Ag–BF platform integrates ultrasensitivity, structural robustness, reproducibility, and reusability in a single low-cost system, highlighting its potential for field-deployable sensing, environmental monitoring, and analytical diagnostics.
{"title":"Large-area periodic silver nanostructures on polymeric substrates via the breath figure method for ultrasensitive and reusable SERS applications","authors":"Raji V. Nair , Saju Pillai , Reny Thankam Thomas","doi":"10.1016/j.snb.2025.139376","DOIUrl":"10.1016/j.snb.2025.139376","url":null,"abstract":"<div><div>Surface Enhanced Raman Scattering (SERS) is a powerful technique for detecting trace-level analytes including drug residues, explosives, and environmental pollutants. However, high-cost, non-reusable conventional substrates fabricated under cleanroom conditions limit widespread deployment. Here, we present a scalable and cost-effective strategy to fabricate large-area periodic polymeric photonic–plasmonic platforms using the breath figure (BF) method combined with controlled silver (Ag) nanostructure integration for enhanced SERS applications. The BF process generates highly ordered hexagonal pore arrays that confine Ag nanoparticles (AgNPs), creating dense electromagnetic hotspots. AgNPs were incorporated via in-situ chemical reduction, achieving detection limits of 1 fM for omethoate (OM) and methylene blue (MB). Additionally, ex-situ deposition with plasma activation and vertical infiltration further enhanced nanoparticle confinement and hotspot density, reaching detection limits as low as 0.1 fM. Vibrational signatures remained well-resolved, supported by analytical enhancement factors of ∼10<sup>7</sup>. The substrates retained over 92 % of initial Raman intensity after five weeks and exhibited high batch-to-batch reproducibility (RSD 4.2 %), demonstrating scalable reliability. TiO<sub>2</sub>-assisted UV photocatalytic cleaning enabled 93–95 % SERS signal recovery after five reuse cycles, confirming structural robustness and efficient analyte removal. XPS analyses revealed a decrease in defect-related O 1 s components and the formation of Ag–O–Ti interfacial species, indicating a charge-transfer mediated regeneration mechanism. Sensitive detection of OM in spiked river water and vegetable extracts yielded > 90 % recovery, demonstrating real-sample applicability. Overall, the TiO<sub>2</sub>-coated Ag–BF platform integrates ultrasensitivity, structural robustness, reproducibility, and reusability in a single low-cost system, highlighting its potential for field-deployable sensing, environmental monitoring, and analytical diagnostics.</div></div>","PeriodicalId":425,"journal":{"name":"Sensors and Actuators B: Chemical","volume":"451 ","pages":"Article 139376"},"PeriodicalIF":3.7,"publicationDate":"2025-12-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145881088","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"化学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2025-12-30DOI: 10.1016/j.snb.2025.139401
Tao Wen , Rongshuai Che , Haiyan Chen , Chenchen Jin , Haibo Wang , Ke-Jing Huang , Kaisheng Diao , Xuecai Tan
To address the limitations of conventional methods in plant pathogen detection, we develop an intelligent detection platform that ingeniously integrates entropy-driven DNA amplification, nanozyme catalysis, and machine learning. This system employs functionalized Au@Cu2O nanozymes as versatile signal transducers, which simultaneously generate electrochemical, colorimetric, and photothermal readouts in response to the target pathogen, establishing an intrinsic triple-modal detection mechanism. The innovation of this work lies in the application of machine learning (Ridge Regression) to fuse these triple-modal signals. This integration creates a self-validating feedback loop that cross-checks the outputs from different modalities, significantly enhancing reliability by minimizing false positives/negatives. Furthermore, the machine learning (ML) model enables predictive analysis, allowing for accurate quantification beyond the conventional calibration curve. The platform achieved a remarkable detection limit of 0.22 fM within a broad linear range (1 fM - 100 nM), along with excellent reproducibility and stability. When applied to the detection of Fusarium sacchariin real sugarcane samples, the results showed high consistency with qPCR (recovery rates: 91.6–107.5 %). This work not only provides a robust tool for early plant disease diagnosis but also establishes a novel paradigm of intelligent, self-validating biosensing for agricultural applications.
为了解决传统方法在植物病原体检测中的局限性，我们开发了一个智能检测平台，巧妙地集成了熵驱动的DNA扩增，纳米酶催化和机器学习。该系统采用功能化Au@Cu2O纳米酶作为多功能信号换能器，可以同时产生电化学、比色和光热读数，以响应目标病原体，建立内在的三模态检测机制。这项工作的创新之处在于应用机器学习（Ridge Regression）来融合这些三模态信号。这种集成创建了一个自我验证的反馈回路，可以交叉检查来自不同模式的输出，通过最大限度地减少误报/误报来显著提高可靠性。此外，机器学习（ML）模型支持预测分析，允许超越传统校准曲线的准确量化。该平台在宽线性范围内（1 fM - 100 nM）的检出限为0.22 fM，具有良好的重现性和稳定性。将该方法应用于实际甘蔗样品中糖精镰刀菌的检测，结果与qPCR的一致性较高（回收率为91.6 ~ 107.5 %）。这项工作不仅为早期植物病害诊断提供了一个强大的工具，而且为农业应用建立了智能、自我验证的生物传感新范式。
{"title":"An intelligent nanozyme-enhanced triple-modal detection platform integrated with machine learning for self-validating pathogen monitoring","authors":"Tao Wen , Rongshuai Che , Haiyan Chen , Chenchen Jin , Haibo Wang , Ke-Jing Huang , Kaisheng Diao , Xuecai Tan","doi":"10.1016/j.snb.2025.139401","DOIUrl":"10.1016/j.snb.2025.139401","url":null,"abstract":"<div><div>To address the limitations of conventional methods in plant pathogen detection, we develop an intelligent detection platform that ingeniously integrates entropy-driven DNA amplification, nanozyme catalysis, and machine learning. This system employs functionalized Au@Cu<sub>2</sub>O nanozymes as versatile signal transducers, which simultaneously generate electrochemical, colorimetric, and photothermal readouts in response to the target pathogen, establishing an intrinsic triple-modal detection mechanism. The innovation of this work lies in the application of machine learning (Ridge Regression) to fuse these triple-modal signals. This integration creates a self-validating feedback loop that cross-checks the outputs from different modalities, significantly enhancing reliability by minimizing false positives/negatives. Furthermore, the machine learning (ML) model enables predictive analysis, allowing for accurate quantification beyond the conventional calibration curve. The platform achieved a remarkable detection limit of 0.22 fM within a broad linear range (1 fM - 100 nM), along with excellent reproducibility and stability. When applied to the detection of Fusarium sacchariin real sugarcane samples, the results showed high consistency with qPCR (recovery rates: 91.6–107.5 %). This work not only provides a robust tool for early plant disease diagnosis but also establishes a novel paradigm of intelligent, self-validating biosensing for agricultural applications.</div></div>","PeriodicalId":425,"journal":{"name":"Sensors and Actuators B: Chemical","volume":"451 ","pages":"Article 139401"},"PeriodicalIF":3.7,"publicationDate":"2025-12-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145881014","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"化学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2025-12-30DOI: 10.1016/j.snb.2025.139397
Peitao Dong , Siyue Xiong , Yujie Gong , Chengxuan Wang , Xun Li , Xuezhong Wu
Acute myocardial infarction (AMI) is a common cardiovascular disease with extremely high clinical mortality rates. Globally, more than one million deaths occur annually due to AMI; rapid diagnosis and early intervention can significantly reduce mortality and improve patient prognosis. The creatine kinase MB isoenzyme (CK-MB) is associated with AMI recurrence and infarct size and is recognized as an essential cardiac biomarker for early AMI diagnosis. Therefore, point-of-care testing (POCT) of CK-MB is important for the early diagnosis of AMI. In this study, we selected CK-MB as the target analyte. We proposed a pump-free microfluidic chip sensor based on surface-enhanced Raman scattering (SERS) technology, which was designed to achieve ultrahigh-sensitivity POCT for CK-MB. The sensor uses a sandwich-type immunoassay system constructed with gold-shelled magnetic particles (AuMNPs), CK-MB, and SERS tags. During operation, the test samples were transported through microchannels by capillary action, enabling the formation of immunocomplexes. The complexes were subsequently magnetically separated and enriched in the detection chamber for SERS signal measurement. This design significantly streamlines operational procedures without external pumps, achieving a very low limit of detection (LOD) (1 pg/mL). The integrated sensor delivers exceptional portability, ultrasensitivity, and rapid analysis (<15 min), establishing a high-performance POCT solution for timely and precise diagnosis of AMI.
{"title":"SERS-based pump-free microfluidic chip sensor for immunoassays of the myocardial injury marker CK-MB","authors":"Peitao Dong , Siyue Xiong , Yujie Gong , Chengxuan Wang , Xun Li , Xuezhong Wu","doi":"10.1016/j.snb.2025.139397","DOIUrl":"10.1016/j.snb.2025.139397","url":null,"abstract":"<div><div>Acute myocardial infarction (AMI) is a common cardiovascular disease with extremely high clinical mortality rates. Globally, more than one million deaths occur annually due to AMI; rapid diagnosis and early intervention can significantly reduce mortality and improve patient prognosis. The creatine kinase MB isoenzyme (CK-MB) is associated with AMI recurrence and infarct size and is recognized as an essential cardiac biomarker for early AMI diagnosis. Therefore, point-of-care testing (POCT) of CK-MB is important for the early diagnosis of AMI. In this study, we selected CK-MB as the target analyte. We proposed a pump-free microfluidic chip sensor based on surface-enhanced Raman scattering (SERS) technology, which was designed to achieve ultrahigh-sensitivity POCT for CK-MB. The sensor uses a sandwich-type immunoassay system constructed with gold-shelled magnetic particles (AuMNPs), CK-MB, and SERS tags. During operation, the test samples were transported through microchannels by capillary action, enabling the formation of immunocomplexes. The complexes were subsequently magnetically separated and enriched in the detection chamber for SERS signal measurement. This design significantly streamlines operational procedures without external pumps, achieving a very low limit of detection (LOD) (1 pg/mL). The integrated sensor delivers exceptional portability, ultrasensitivity, and rapid analysis (<15 min), establishing a high-performance POCT solution for timely and precise diagnosis of AMI.</div></div>","PeriodicalId":425,"journal":{"name":"Sensors and Actuators B: Chemical","volume":"451 ","pages":"Article 139397"},"PeriodicalIF":3.7,"publicationDate":"2025-12-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145881017","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"化学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2025-12-29DOI: 10.1016/j.snb.2025.139399
Jing-Lin He , Bing Li , Yingying Dong , Shudan Zou, Dan Li, Zhong Cao
A green and biocompatible strategy for synthesizing MnO2 nanoflowers is reported using Tremella fuciformis as a natural reductant and structural template. The resulting MnO2 was employed as a redox-responsive carrier for constructing a multifunctional DNA nanodevice (X-DMNF) integrating tumor-cell imaging, dual-gene regulation, and photodynamic activity. The X-DNA scaffold incorporated miR-21 recognition elements, Mn2 + -activated DNAzymes targeting EGR-1 and Survivin mRNA, and a Ce6 photosensitizer. Upon cellular internalization, endogenous glutathione (GSH) triggered MnO2 degradation, releasing Mn2+ and restoring fluorescence for miRNA detection. The released DNAzymes catalyzed selective mRNA cleavage, while Ce6 generated singlet oxygen under laser irradiation. In vitro experiments demonstrated efficient miRNA recognition, gene silencing, reactive oxygen species generation, and synergistic cytotoxicity in MCF-7 cells, with minimal off-target effects on normal cells. This work establishes a green and modular approach for constructing GSH-responsive DNA-MnO2 nanodevices and provides a promising platform for cell-level cancer diagnostics and mechanistic therapeutic studies, pending future in vivo validation.
{"title":"Tremella-derived MnO2 nanoflowers for tumor-cell-responsive imaging and combined gene-photodynamic actions in vitro","authors":"Jing-Lin He , Bing Li , Yingying Dong , Shudan Zou, Dan Li, Zhong Cao","doi":"10.1016/j.snb.2025.139399","DOIUrl":"10.1016/j.snb.2025.139399","url":null,"abstract":"<div><div>A green and biocompatible strategy for synthesizing MnO<sub>2</sub> nanoflowers is reported using <em>Tremella fuciformis</em> as a natural reductant and structural template. The resulting MnO<sub>2</sub> was employed as a redox-responsive carrier for constructing a multifunctional DNA nanodevice (X-DMNF) integrating tumor-cell imaging, dual-gene regulation, and photodynamic activity. The X-DNA scaffold incorporated miR-21 recognition elements, Mn<sup>2 +</sup> -activated DNAzymes targeting EGR-1 and Survivin mRNA, and a Ce6 photosensitizer. Upon cellular internalization, endogenous glutathione (GSH) triggered MnO<sub>2</sub> degradation, releasing Mn<sup>2+</sup> and restoring fluorescence for miRNA detection. The released DNAzymes catalyzed selective mRNA cleavage, while Ce6 generated singlet oxygen under laser irradiation. In vitro experiments demonstrated efficient miRNA recognition, gene silencing, reactive oxygen species generation, and synergistic cytotoxicity in MCF-7 cells, with minimal off-target effects on normal cells. This work establishes a green and modular approach for constructing GSH-responsive DNA-MnO<sub>2</sub> nanodevices and provides a promising platform for cell-level cancer diagnostics and mechanistic therapeutic studies, pending future in vivo validation.</div></div>","PeriodicalId":425,"journal":{"name":"Sensors and Actuators B: Chemical","volume":"451 ","pages":"Article 139399"},"PeriodicalIF":3.7,"publicationDate":"2025-12-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145939467","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"化学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2025-12-29DOI: 10.1016/j.snb.2025.139400
Xue Deng , Wei Zhou , Yuxuan Fan , Xingyu Wang , Yanyuan Huang , Wenqiang Zhang
Inspired by the distinctive micro- and nanostructural features observed on the pistil of Viola philippica Cav., we developed a flexible and bionic surface-enhanced Raman scattering (SERS) substrate with improved sensitivity. The “pistil-inspired” substrate was produced by chemically etching a composite film consisting of silver nanowires (AgNWs) embedded within a polydimethylsiloxane (PDMS) matrix. Careful optimization of the etching concentration and reaction duration significantly enhanced the Raman signal intensity of Rhodamine 6 G (R6G). To further augment performance, gold nanoparticles were introduced through a self-assembly process, thereby forming a hierarchical multi-scale bionic architecture. This dual-scale structural design enabled a remarkable detection limit for R6G, reaching concentrations as low as 10−10 mol/L. Moreover, to bridge the gap between laboratory research and field application, the substrate was integrated with a portable Raman spectrometer. Despite the typically lower resolution of handheld devices, the high enhancement factor of our substrate enabled the reliable detection of paraquat at 0.1 ng/mL with a relative standard deviation (RSD) of 5.39 %. Collectively, these findings validate the platform’s capability for rapid, on-site food safety monitoring using portable instrumentation.
受堇菜雌蕊独特的微观和纳米结构特征的启发。我们开发了一种柔性和仿生表面增强拉曼散射（SERS）衬底，具有更高的灵敏度。“雌蕊启发”的衬底是通过化学蚀刻一层由银纳米线（AgNWs）组成的复合膜，该复合膜嵌入聚二甲基硅氧烷（PDMS）基质中。精心优化蚀刻浓度和反应时间，显著增强罗丹明6 G （R6G）的拉曼信号强度。为了进一步提高性能，通过自组装过程引入金纳米颗粒，从而形成分层的多尺度仿生结构。这种双尺度结构设计使R6G的检测限显着提高，浓度低至10−10 mol/L。此外，为了弥合实验室研究和现场应用之间的差距，衬底集成了便携式拉曼光谱仪。尽管手持设备的分辨率通常较低，但我们的底物的高增强因子使百草枯在0.1 ng/mL的水平上可靠检测，相对标准偏差（RSD）为5.39 %。总的来说，这些发现验证了该平台使用便携式仪器进行快速现场食品安全监测的能力。
{"title":"Bionic pistil-inspired nanostructure based on silver nanowires for rapid SERS detection","authors":"Xue Deng , Wei Zhou , Yuxuan Fan , Xingyu Wang , Yanyuan Huang , Wenqiang Zhang","doi":"10.1016/j.snb.2025.139400","DOIUrl":"10.1016/j.snb.2025.139400","url":null,"abstract":"<div><div>Inspired by the distinctive micro- and nanostructural features observed on the pistil of <em>Viola philippica Cav</em>., we developed a flexible and bionic surface-enhanced Raman scattering (SERS) substrate with improved sensitivity. The “pistil-inspired” substrate was produced by chemically etching a composite film consisting of silver nanowires (AgNWs) embedded within a polydimethylsiloxane (PDMS) matrix. Careful optimization of the etching concentration and reaction duration significantly enhanced the Raman signal intensity of Rhodamine 6 G (R6G). To further augment performance, gold nanoparticles were introduced through a self-assembly process, thereby forming a hierarchical multi-scale bionic architecture. This dual-scale structural design enabled a remarkable detection limit for R6G, reaching concentrations as low as 10<sup>−10</sup> mol/L. Moreover, to bridge the gap between laboratory research and field application, the substrate was integrated with a portable Raman spectrometer. Despite the typically lower resolution of handheld devices, the high enhancement factor of our substrate enabled the reliable detection of paraquat at 0.1 ng/mL with a relative standard deviation (RSD) of 5.39 %. Collectively, these findings validate the platform’s capability for rapid, on-site food safety monitoring using portable instrumentation.</div></div>","PeriodicalId":425,"journal":{"name":"Sensors and Actuators B: Chemical","volume":"451 ","pages":"Article 139400"},"PeriodicalIF":3.7,"publicationDate":"2025-12-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145939466","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"化学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2025-12-28DOI: 10.1016/j.snb.2025.139398
Yuxin Chen , Yuanshou Zhu , Wenbao Qi , Zhuoyun Jiang , Yanjing Chen , Xitian Xu , Mengyuan Huang , Ziyang Yin , Jingru Liu , Lu Feng , Kangyongjie Sun , Lihong Huang , Zifeng Wang , Sheng-ce Tao , Zhigang Zhu
African swine fever virus (ASFV) has a large, highly variable genome; single-gene assays therefore risk false-negative results, and a field-deployable, multi-target nucleic acid test is urgently needed. Here we present DeepLAMP, a platform that combines a hive-shaped microfluidic chip, gold-nanoparticle-enhanced colorimetric loop-mediated isothermal amplification (LAMP), and smartphone-based deep-learning analysis to synchronously detect four conserved ASFV genes (B646L, Q706L, P1192R and B475L). The AuNP-catalyzed micro‑environment markedly boosts amplification efficiency, lowering limits of detection to 5 copies µL⁻¹ for B646L and P1192R, and to 25 and 50 copies µL⁻¹ for Q706L and B475L, respectively; the full assay is completed within 60 min. An optimized ConvNeXt deep learning model classifies six chip image categories with 98.6 % overall accuracy, automatically quantifying color shifts imperceptible to the naked eye. DeepLAMP correctly identified clinical ASFV samples and showed no cross reactivity with CSFV, PRRSV or PRV, demonstrating high specificity and robustness. Requiring neither centrifugation nor costly instrumentation, the workflow delivers “sample-to-answer” operation in pig farms and other resource-limited settings, offering a versatile point-of-care platform readily extendable to multi-gene diagnostics of other zoonotic and emerging pathogens.
{"title":"DeepLAMP: Deep learning-assisted Hive-Chip integrated with AuNP-enhanced colorimetric LAMP for smartphone-based multiplex detection of African swine fever virus","authors":"Yuxin Chen , Yuanshou Zhu , Wenbao Qi , Zhuoyun Jiang , Yanjing Chen , Xitian Xu , Mengyuan Huang , Ziyang Yin , Jingru Liu , Lu Feng , Kangyongjie Sun , Lihong Huang , Zifeng Wang , Sheng-ce Tao , Zhigang Zhu","doi":"10.1016/j.snb.2025.139398","DOIUrl":"10.1016/j.snb.2025.139398","url":null,"abstract":"<div><div>African swine fever virus (ASFV) has a large, highly variable genome; single-gene assays therefore risk false-negative results, and a field-deployable, multi-target nucleic acid test is urgently needed. Here we present DeepLAMP, a platform that combines a hive-shaped microfluidic chip, gold-nanoparticle-enhanced colorimetric loop-mediated isothermal amplification (LAMP), and smartphone-based deep-learning analysis to synchronously detect four conserved ASFV genes (B646L, Q706L, P1192R and B475L). The AuNP-catalyzed micro‑environment markedly boosts amplification efficiency, lowering limits of detection to 5 copies µL⁻¹ for B646L and P1192R, and to 25 and 50 copies µL⁻¹ for Q706L and B475L, respectively; the full assay is completed within 60 min. An optimized ConvNeXt deep learning model classifies six chip image categories with 98.6 % overall accuracy, automatically quantifying color shifts imperceptible to the naked eye. DeepLAMP correctly identified clinical ASFV samples and showed no cross reactivity with CSFV, PRRSV or PRV, demonstrating high specificity and robustness. Requiring neither centrifugation nor costly instrumentation, the workflow delivers “sample-to-answer” operation in pig farms and other resource-limited settings, offering a versatile point-of-care platform readily extendable to multi-gene diagnostics of other zoonotic and emerging pathogens.</div></div>","PeriodicalId":425,"journal":{"name":"Sensors and Actuators B: Chemical","volume":"451 ","pages":"Article 139398"},"PeriodicalIF":3.7,"publicationDate":"2025-12-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145845060","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"化学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2025-12-26DOI: 10.1016/j.snb.2025.139356
Guanwei Tao, Xinping Zhang
Surface-enhanced Raman scattering (SERS) sensors offer high-sensitivity, high-specificity, and high-speed detection of low-concentration molecules with low costs. High stability of the device is a key issue in the design and application of this category of sensors. However, SERS detection with strong and high-contrast Raman signals requires strong laser excitation of the target molecules, which may lead to the damage of the metallic nanostructures on the SERS substrates by photothermal effects, reducing largely the reliability of the detection data. In this study, we present a SERS substrate fabricated by depositing silver nanoparticles (AgNPs) onto the polytetrafluoroethylene (PTFE)-modified carbon paper (CP), which is defined as the CP-PTFE-AgNP sensor. The fabrication parameters were systematically adjusted to optimize the SERS-active nanostructures with significantly improved sensing performance. The fabricated sensor exhibits exceptional photostability, maintaining optimal performance even under high excitation laser intensity. Using R6G as a probe molecule, it demonstrates an ultrahigh enhancement factor of 2.66 × 1012 and a remarkably low detection limit of 10−17 M. Furthermore, the high-sensitivity detection of ciprofloxacin in water and bilirubin in serum implies promising applications of such a design of SERS devices. These experimental results indicate that this highly stable SERS sensor holds great potential for point-of-care testing applications in fields such as environmental monitoring and biomedical diagnostics.
{"title":"Carbon paper stabilized SERS sensor with high excitation laser damage threshold","authors":"Guanwei Tao, Xinping Zhang","doi":"10.1016/j.snb.2025.139356","DOIUrl":"10.1016/j.snb.2025.139356","url":null,"abstract":"<div><div>Surface-enhanced Raman scattering (SERS) sensors offer high-sensitivity, high-specificity, and high-speed detection of low-concentration molecules with low costs. High stability of the device is a key issue in the design and application of this category of sensors. However, SERS detection with strong and high-contrast Raman signals requires strong laser excitation of the target molecules, which may lead to the damage of the metallic nanostructures on the SERS substrates by photothermal effects, reducing largely the reliability of the detection data. In this study, we present a SERS substrate fabricated by depositing silver nanoparticles (AgNPs) onto the polytetrafluoroethylene (PTFE)-modified carbon paper (CP), which is defined as the CP-PTFE-AgNP sensor. The fabrication parameters were systematically adjusted to optimize the SERS-active nanostructures with significantly improved sensing performance. The fabricated sensor exhibits exceptional photostability, maintaining optimal performance even under high excitation laser intensity. Using R6G as a probe molecule, it demonstrates an ultrahigh enhancement factor of 2.66 × 10<sup>12</sup> and a remarkably low detection limit of 10<sup>−17</sup> M. Furthermore, the high-sensitivity detection of ciprofloxacin in water and bilirubin in serum implies promising applications of such a design of SERS devices. These experimental results indicate that this highly stable SERS sensor holds great potential for point-of-care testing applications in fields such as environmental monitoring and biomedical diagnostics.</div></div>","PeriodicalId":425,"journal":{"name":"Sensors and Actuators B: Chemical","volume":"451 ","pages":"Article 139356"},"PeriodicalIF":3.7,"publicationDate":"2025-12-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145838082","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"化学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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