Pub Date : 2026-03-05DOI: 10.1021/acssensors.5c04529
Jiaxin Fu,Yupei Zhao,Rui Hu,Tao Liang,Dan Song,Zhen Li
Parkinson's disease (PD) is a complex neurodegenerative disorder. Currently, the early diagnosis and treatment of PD are often hindered by significant subjectivity in clinical assessments from both patients and physicians. Hypochlorous acid (HClO), a representative reactive oxygen species, has been widely recognized as closely linked to the pathological mechanisms underlying PD. Thus, we developed a HClO-activated NIR-IIb fluorescent probe, SQ6-RENPs, which is functionalized with the VHP peptide to enable blood-brain barrier (BBB) crossing for monitoring cerebral HClO levels associated with PD progression. The small-molecule SQ6, exhibiting strong absorption at approximately 808 nm, was rationally designed to modulate the NIR-IIb emission of rare-earth nanoparticles (RENPs) via an absorption competition-induced emission (ACIE) mechanism. The probe exhibited excellent sensitivity toward HClO, high selectivity over other analytes, and remarkable stability under physiological conditions. Furthermore, SQ6-RENPs can effectively cross the BBB and accumulate in brain parenchyma through specific binding of the VHP peptide to receptors on brain endothelial cells. These properties render the probe highly suitable for in vivo imaging of cerebral HClO. As expected, SQ6-RENPs successfully revealed the severity of PD and evaluated the therapeutic efficacy of clinically used drugs by real-time monitoring of HClO levels in the brains of PD model mice. This probe offers a promising objective and accurate approach for PD diagnosis and provides a faster strategy for drug evaluation in preclinical research.
{"title":"Activatable NIR-IIb Nanosensor for Visualizing Brain HClO to Monitor Parkinson's Disease.","authors":"Jiaxin Fu,Yupei Zhao,Rui Hu,Tao Liang,Dan Song,Zhen Li","doi":"10.1021/acssensors.5c04529","DOIUrl":"https://doi.org/10.1021/acssensors.5c04529","url":null,"abstract":"Parkinson's disease (PD) is a complex neurodegenerative disorder. Currently, the early diagnosis and treatment of PD are often hindered by significant subjectivity in clinical assessments from both patients and physicians. Hypochlorous acid (HClO), a representative reactive oxygen species, has been widely recognized as closely linked to the pathological mechanisms underlying PD. Thus, we developed a HClO-activated NIR-IIb fluorescent probe, SQ6-RENPs, which is functionalized with the VHP peptide to enable blood-brain barrier (BBB) crossing for monitoring cerebral HClO levels associated with PD progression. The small-molecule SQ6, exhibiting strong absorption at approximately 808 nm, was rationally designed to modulate the NIR-IIb emission of rare-earth nanoparticles (RENPs) via an absorption competition-induced emission (ACIE) mechanism. The probe exhibited excellent sensitivity toward HClO, high selectivity over other analytes, and remarkable stability under physiological conditions. Furthermore, SQ6-RENPs can effectively cross the BBB and accumulate in brain parenchyma through specific binding of the VHP peptide to receptors on brain endothelial cells. These properties render the probe highly suitable for in vivo imaging of cerebral HClO. As expected, SQ6-RENPs successfully revealed the severity of PD and evaluated the therapeutic efficacy of clinically used drugs by real-time monitoring of HClO levels in the brains of PD model mice. This probe offers a promising objective and accurate approach for PD diagnosis and provides a faster strategy for drug evaluation in preclinical research.","PeriodicalId":24,"journal":{"name":"ACS Sensors","volume":"8 1","pages":""},"PeriodicalIF":8.9,"publicationDate":"2026-03-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147359286","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 : 2026-03-05DOI: 10.1021/acssensors.5c03424
Sanghyeon Noh,Cheulmin Joe,Hye Ri Kim,Ee Taek Hwang,Man Bock Gu,Byoung Chan Kim
Current culture-based bioaerosol monitoring fails to provide the species-specificity and real-time capabilities essential for indoor air quality and disease surveillance. We developed a culture-free electrochemical aptasensor for rapid, species-specific detection of airborne bacteria. Targeting Moraxella osloensis, a prevalent indoor species identified through next-generation sequencing, we generated a high-affinity aptamer (Kd = 118.9 nM) for M. osloensis and immobilized it on screen-printed gold electrodes. The label-free electrochemical impedance spectroscopy-based sensor achieved near single-cell sensitivity (5.6 CFU/μL detection limit), log-linear quantification (R2 = 0.98), and robust selectivity against six nontarget species, maintaining stability under PM2.5-equivalent dust loads (15-75 μg/m3). In aerosol chamber tests, the sensor successfully quantified airborne M. osloensis with signals correlating to delivered cell numbers and plate counts, demonstrating specificity even in complex microbial and dust conditions. This platform reduces detection time from days to minutes, enabling multiplexed, field-deployable bioaerosol surveillance for indoor air quality and infectious disease monitoring.
{"title":"Electrochemical Aptasensing Platform for Culture-Free, Selective Detection of Airborne Bacterial Species.","authors":"Sanghyeon Noh,Cheulmin Joe,Hye Ri Kim,Ee Taek Hwang,Man Bock Gu,Byoung Chan Kim","doi":"10.1021/acssensors.5c03424","DOIUrl":"https://doi.org/10.1021/acssensors.5c03424","url":null,"abstract":"Current culture-based bioaerosol monitoring fails to provide the species-specificity and real-time capabilities essential for indoor air quality and disease surveillance. We developed a culture-free electrochemical aptasensor for rapid, species-specific detection of airborne bacteria. Targeting Moraxella osloensis, a prevalent indoor species identified through next-generation sequencing, we generated a high-affinity aptamer (Kd = 118.9 nM) for M. osloensis and immobilized it on screen-printed gold electrodes. The label-free electrochemical impedance spectroscopy-based sensor achieved near single-cell sensitivity (5.6 CFU/μL detection limit), log-linear quantification (R2 = 0.98), and robust selectivity against six nontarget species, maintaining stability under PM2.5-equivalent dust loads (15-75 μg/m3). In aerosol chamber tests, the sensor successfully quantified airborne M. osloensis with signals correlating to delivered cell numbers and plate counts, demonstrating specificity even in complex microbial and dust conditions. This platform reduces detection time from days to minutes, enabling multiplexed, field-deployable bioaerosol surveillance for indoor air quality and infectious disease monitoring.","PeriodicalId":24,"journal":{"name":"ACS Sensors","volume":"48 1","pages":"XXX"},"PeriodicalIF":8.9,"publicationDate":"2026-03-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147350808","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}
Hydrogen (H2) sensors capable of sub-ppm detection are vital for safety in hydrogen energy and electrical equipment diagnostics. This work presents a high-performance resistive hydrogen sensor based on a PdAu alloy, achieved through the synergistic optimization of material microstructure and device architecture. We discover that annealing at 250 °C forms a partially alloyed, compositionally graded structure-a Au-enriched surface atop a Pd-rich bulk-which simultaneously enhances sensitivity and poisoning resistance. Coupled with an optimized parallel electrode configuration of 2 μm linewidth, this design ensures uniform current distribution and maximizes the edge-to-volume ratio, drastically improving hydrogen diffusion kinetics. The resulting sensor (P2-250) exhibits an exceptional detection limit of 0.1 ppm H2 at room temperature, a response magnitude 70.6% higher than its series counterpart, excellent selectivity against interferents (e.g., CO), and stable operation over 60 days. Furthermore, the sensor successfully demonstrated the capability for in situ detection of dissolved hydrogen in insulating oil. This study provides a multifaceted optimization strategy encompassing annealing, electrode design, and feature size for developing high-performance PdAu-based resistive hydrogen sensors for sub-ppm applications.
{"title":"Sub-ppm Hydrogen Sensing via PdAu Alloy: Optimized Annealing and Electrode Structures from Experimental and Calculation Studies.","authors":"Shuai Wang,Haibao Mu,Yunfeng Wang,Jiazhuo Jian,Siyu Deng,Maoqun Shen,Zekai Lai,Guanjun Zhang","doi":"10.1021/acssensors.5c04207","DOIUrl":"https://doi.org/10.1021/acssensors.5c04207","url":null,"abstract":"Hydrogen (H2) sensors capable of sub-ppm detection are vital for safety in hydrogen energy and electrical equipment diagnostics. This work presents a high-performance resistive hydrogen sensor based on a PdAu alloy, achieved through the synergistic optimization of material microstructure and device architecture. We discover that annealing at 250 °C forms a partially alloyed, compositionally graded structure-a Au-enriched surface atop a Pd-rich bulk-which simultaneously enhances sensitivity and poisoning resistance. Coupled with an optimized parallel electrode configuration of 2 μm linewidth, this design ensures uniform current distribution and maximizes the edge-to-volume ratio, drastically improving hydrogen diffusion kinetics. The resulting sensor (P2-250) exhibits an exceptional detection limit of 0.1 ppm H2 at room temperature, a response magnitude 70.6% higher than its series counterpart, excellent selectivity against interferents (e.g., CO), and stable operation over 60 days. Furthermore, the sensor successfully demonstrated the capability for in situ detection of dissolved hydrogen in insulating oil. This study provides a multifaceted optimization strategy encompassing annealing, electrode design, and feature size for developing high-performance PdAu-based resistive hydrogen sensors for sub-ppm applications.","PeriodicalId":24,"journal":{"name":"ACS Sensors","volume":"61 1","pages":"XXX"},"PeriodicalIF":8.9,"publicationDate":"2026-03-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147350602","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}
Sensitive, point-of-care detection of salivary miRNA-31 holds considerable potential for the early, noninvasive screening and diagnosis of oral squamous cell carcinoma (OSCC). This study reports the first development of a sensitive, portable biosensor that integrates an autocycling primer extension reaction (ACPER) with a bioinspired photonic-crystal (PC) microchip for quantitative analysis of miRNA-31 in saliva. The high amplification efficiency of ACPER enables sensitive detection of miRNA-31 in saliva. Meanwhile, due to the fluorescence-enhancing properties of the PC microchip, the fluorescence signal generated by the ACPER on the PC microchip can be directly visualized and captured through a smartphone imaging system under ultraviolet-light illumination. The fluorescence intensity values are subsequently extracted via image processing software for quantification analysis. This approach obviates the need for bulky instrumentation and mitigates errors arising from subjective interpretation of color depth by the naked eyes, thereby significantly enhancing detection accuracy. Preliminary clinical feasibility assessment demonstrated that this newly developed biosensor can differentiate between cancer patients and healthy individuals in clinical samples with good accuracy (area under the curve = 1), providing a novel paradigm for the early, noninvasive, and sensitive diagnosis of OSCC.
{"title":"Sensitive Point-of-Care Detection of Oral Squamous Cell Carcinoma-Associated Salivary miRNA-31 Enabled by Autocycling Primer Extension Reaction and a Bioinspired Photonic-Crystal Microchip","authors":"Jing Li,Wei Zhang,Yiqi Liu,Ruirui Chang,Yiting Lan,Dengxue Qiu,Caiwang Chang,Jin Huang,Qin Xu","doi":"10.1021/acssensors.5c04078","DOIUrl":"https://doi.org/10.1021/acssensors.5c04078","url":null,"abstract":"Sensitive, point-of-care detection of salivary miRNA-31 holds considerable potential for the early, noninvasive screening and diagnosis of oral squamous cell carcinoma (OSCC). This study reports the first development of a sensitive, portable biosensor that integrates an autocycling primer extension reaction (ACPER) with a bioinspired photonic-crystal (PC) microchip for quantitative analysis of miRNA-31 in saliva. The high amplification efficiency of ACPER enables sensitive detection of miRNA-31 in saliva. Meanwhile, due to the fluorescence-enhancing properties of the PC microchip, the fluorescence signal generated by the ACPER on the PC microchip can be directly visualized and captured through a smartphone imaging system under ultraviolet-light illumination. The fluorescence intensity values are subsequently extracted via image processing software for quantification analysis. This approach obviates the need for bulky instrumentation and mitigates errors arising from subjective interpretation of color depth by the naked eyes, thereby significantly enhancing detection accuracy. Preliminary clinical feasibility assessment demonstrated that this newly developed biosensor can differentiate between cancer patients and healthy individuals in clinical samples with good accuracy (area under the curve = 1), providing a novel paradigm for the early, noninvasive, and sensitive diagnosis of OSCC.","PeriodicalId":24,"journal":{"name":"ACS Sensors","volume":"100 1","pages":""},"PeriodicalIF":8.9,"publicationDate":"2026-03-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147346761","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}
The development of high-performance gas sensors is crucial for ensuring safety and efficiency in the emerging hydrogen economy, particularly for detecting hydrogen (H2) and ammonia (NH3), which are essential for hydrogen storage, transportation, and energy applications. Hydrogen is highly flammable, with a lower explosive limit of 4%, while ammonia is toxic and can cause severe health hazards; thus, their early and accurate detection is critical to prevent accidents and ensure safe handling. However, most hydrogen sensors exhibit cross-sensitivity to ammonia, making it challenging to distinguish between the two gases. Additionally, blends of ammonia and hydrogen are considered as alternative fuels to achieve zero-carbon emissions. Detecting them in mixture form is essential, as the flammability and toxicity limits of the mixture differ from those of the individual gases, requiring precise monitoring for safety, process optimization, and efficient fuel utilization. In this study, we employ palladium (Pd) nanoparticle-decorated electrostatically formed nanowire (Pd-EFN) sensor for the selective detection of H2, NH3, and their mixtures at low concentrations. The EFN sensor, a multiple-gate depletion-mode field-effect transistor (FET) fabricated using complementary metal-oxide-semiconductor (CMOS)-compatible processes, provides unique multigate electrostatic control, enabling enhanced sensitivity and selectivity. Experimental results demonstrate a highly reversible response, with distinct “electrostatic fingerprints” observed across different back-gate voltages, allowing for improved gas differentiation. Using supervised machine learning techniques including Linear and Kernel Support Vector Machine, AdaBoost, Gradient Boosting, Extra Trees, Random Forest, Decision Tree, Linear Discriminant Analysis, and K-Nearest Neighbors, we achieved up to 94% classification accuracy in distinguishing H2 vs NH3 and H2 vs (NH3 + H2), respectively. Additionally, adopting a transfer learning approach using the VGG-19 neural network and leveraging sensor response maps as inputs, further improved accuracy to approximately 97 and 96%, respectively. Furthermore, the ability to discern the individual gases and the mixture (H2/NH3/(NH3 + H2)) was improved from 77 to 87% with the use of transfer learning. The ability to selectively identify individual gases and their mixtures using a single sensor with high accuracy, without the need for sensor arrays, paves the way for advanced, miniaturized, and cost-effective gas sensing platforms, demonstrating potential for real-world applications in hydrogen safety and environmental monitoring.
{"title":"Selective Sensing of Hydrogen and Ammonia Using a Single CMOS-Compatible Sensor and Transfer Learning Methods","authors":"Anwesha Mukherjee,Mohd Salman Siddiqui,Idan ShemTov,Shahar Mahpod,Yossi Rosenwaks","doi":"10.1021/acssensors.5c03498","DOIUrl":"https://doi.org/10.1021/acssensors.5c03498","url":null,"abstract":"The development of high-performance gas sensors is crucial for ensuring safety and efficiency in the emerging hydrogen economy, particularly for detecting hydrogen (H2) and ammonia (NH3), which are essential for hydrogen storage, transportation, and energy applications. Hydrogen is highly flammable, with a lower explosive limit of 4%, while ammonia is toxic and can cause severe health hazards; thus, their early and accurate detection is critical to prevent accidents and ensure safe handling. However, most hydrogen sensors exhibit cross-sensitivity to ammonia, making it challenging to distinguish between the two gases. Additionally, blends of ammonia and hydrogen are considered as alternative fuels to achieve zero-carbon emissions. Detecting them in mixture form is essential, as the flammability and toxicity limits of the mixture differ from those of the individual gases, requiring precise monitoring for safety, process optimization, and efficient fuel utilization. In this study, we employ palladium (Pd) nanoparticle-decorated electrostatically formed nanowire (Pd-EFN) sensor for the selective detection of H2, NH3, and their mixtures at low concentrations. The EFN sensor, a multiple-gate depletion-mode field-effect transistor (FET) fabricated using complementary metal-oxide-semiconductor (CMOS)-compatible processes, provides unique multigate electrostatic control, enabling enhanced sensitivity and selectivity. Experimental results demonstrate a highly reversible response, with distinct “electrostatic fingerprints” observed across different back-gate voltages, allowing for improved gas differentiation. Using supervised machine learning techniques including Linear and Kernel Support Vector Machine, AdaBoost, Gradient Boosting, Extra Trees, Random Forest, Decision Tree, Linear Discriminant Analysis, and K-Nearest Neighbors, we achieved up to 94% classification accuracy in distinguishing H2 vs NH3 and H2 vs (NH3 + H2), respectively. Additionally, adopting a transfer learning approach using the VGG-19 neural network and leveraging sensor response maps as inputs, further improved accuracy to approximately 97 and 96%, respectively. Furthermore, the ability to discern the individual gases and the mixture (H2/NH3/(NH3 + H2)) was improved from 77 to 87% with the use of transfer learning. The ability to selectively identify individual gases and their mixtures using a single sensor with high accuracy, without the need for sensor arrays, paves the way for advanced, miniaturized, and cost-effective gas sensing platforms, demonstrating potential for real-world applications in hydrogen safety and environmental monitoring.","PeriodicalId":24,"journal":{"name":"ACS Sensors","volume":"20 1","pages":""},"PeriodicalIF":8.9,"publicationDate":"2026-03-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147346764","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}
The highly sensitive photoelectric detection of hydrogen (H2) at room temperature (RT) is highly desired, but it is crucial to boost •O2− generation by improving charge transfer and favorable O2 adsorption. Herein, we construct a novel all-organic polydopamine/poly(heptazine imide) (PDA/PHI) nanosheet heterojunction through in situ polymerization for photoelectric H2 detection. The optimized one exhibits high sensitivity (an ultralow detection limit of 500 ppm and a high gas response of 42.8% for 5000 ppm H2), along with good linearity from 500 to 5000 ppm, under 405 nm irradiation at RT based on the dynamic detection process. Moreover, good repeatability in 40 cycles, long-term stability (over 210 days), and high selectivity are confirmed. The outstanding performance is attributed to the efficient Z-scheme charge transfer and the promoted O2 adsorption for facilitating the •O2− species generation. Interestingly, the in situ μs-transient absorption spectra quantitatively reveal that the electron transfer efficiency (ETE) to the adsorbed O2 of the PDA/PHI heterojunction is changed from 68.0% to 31.1% after introducing H2, while the change rate of ETE is more pronounced than that of PHI. This study demonstrates great potential of all-organic heterojunctions for RT photoelectric detection and provides deep insight into the •O2− species and gas sensing property.
{"title":"An All-Organic Polydopamine/Poly(heptazine imide) Heterojunction for High-Sensitivity Photoelectric H2 Detection at Room Temperature","authors":"Rongping Xu,Baihe Sun,Jianhui Sun,Zhuo Li,Peng Li,Zhiyu Ren,Liqiang Jing","doi":"10.1021/acssensors.5c03751","DOIUrl":"https://doi.org/10.1021/acssensors.5c03751","url":null,"abstract":"The highly sensitive photoelectric detection of hydrogen (H2) at room temperature (RT) is highly desired, but it is crucial to boost •O2− generation by improving charge transfer and favorable O2 adsorption. Herein, we construct a novel all-organic polydopamine/poly(heptazine imide) (PDA/PHI) nanosheet heterojunction through in situ polymerization for photoelectric H2 detection. The optimized one exhibits high sensitivity (an ultralow detection limit of 500 ppm and a high gas response of 42.8% for 5000 ppm H2), along with good linearity from 500 to 5000 ppm, under 405 nm irradiation at RT based on the dynamic detection process. Moreover, good repeatability in 40 cycles, long-term stability (over 210 days), and high selectivity are confirmed. The outstanding performance is attributed to the efficient Z-scheme charge transfer and the promoted O2 adsorption for facilitating the •O2− species generation. Interestingly, the in situ μs-transient absorption spectra quantitatively reveal that the electron transfer efficiency (ETE) to the adsorbed O2 of the PDA/PHI heterojunction is changed from 68.0% to 31.1% after introducing H2, while the change rate of ETE is more pronounced than that of PHI. This study demonstrates great potential of all-organic heterojunctions for RT photoelectric detection and provides deep insight into the •O2− species and gas sensing property.","PeriodicalId":24,"journal":{"name":"ACS Sensors","volume":"42 1","pages":""},"PeriodicalIF":8.9,"publicationDate":"2026-03-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147346762","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 : 2026-03-04DOI: 10.1021/acssensors.5c04441
Dong Dinh,Guojun Shang,Lei Cai,Wai Ben Chan,Aiping Ma,Jiurong Li,Aimin Huang,Marie E. Louis,Fengbei Cen,Justin Eduardus Halim,Jiaxi Guo,Lidia Gebre,Qun Liu,Zeqi Li,Lefu Yang,Jin Luo,Susan Lu,Chuan-Jian Zhong
Early detection of lung cancer remains critical for improving patient survival, yet current imaging-based screening methods are costly, invasive, and limited in accessibility. Here, we present a fully integrated wireless breath sensing platform that combines nanostructured chemiresistive (NC) sensor arrays with an AI-driven Fuzzy logic-guided Genetic Algorithm (Fuzzy-GA) for optimized volatile organic compound (VOC) detection. The sensor array features nanoparticle structured interfaces, enabling selective VOC adsorption to generate unique breath patterns. Data are captured via a portable low-current multichannel electronics module with real-time wireless transmission. Fuzzy-GA optimization identifies the most informative sensors, reducing array size while maintaining high diagnostic performance. Breath samples from lung cancer patients (n = 35) and non-cancer participants (n = 47) were analyzed using multiple supervised machine learning models (KNN, SVM, Random Forest, XGBoost, and CNN). This represents the first application of Fuzzy-GA to optimize breath sensor arrays. The optimized system, validated using breath samples from lung cancer patients and non-lung cancer controls, achieved high classification accuracy (up to 96%) with reduced system complexity, lower cost, and improved scalability for real-world deployment. The platform offers a clinically viable, non-invasive diagnostic tool with potential for at-home monitoring and broader disease detection.
肺癌的早期检测对于提高患者的生存率仍然至关重要，但目前基于成像的筛查方法成本高昂，具有侵入性，并且可及性有限。在这里，我们提出了一个完全集成的无线呼吸传感平台，该平台将纳米结构化学（NC）传感器阵列与人工智能驱动的模糊逻辑引导遗传算法（Fuzzy- ga）相结合，用于优化挥发性有机化合物（VOC）检测。传感器阵列具有纳米颗粒结构界面，使VOC选择性吸附产生独特的呼吸模式。数据通过具有实时无线传输的便携式低电流多通道电子模块捕获。模糊遗传优化识别信息最多的传感器，在保持高诊断性能的同时减少阵列尺寸。使用多监督机器学习模型（KNN， SVM, Random Forest， XGBoost和CNN）分析肺癌患者（n = 35）和非癌症参与者（n = 47）的呼吸样本。这是模糊遗传算法在呼吸传感器阵列优化中的首次应用。优化后的系统使用肺癌患者和非肺癌对照组的呼吸样本进行验证，实现了高分类准确率（高达96%），降低了系统复杂性，降低了成本，并提高了实际部署的可扩展性。该平台提供了一种临床可行的非侵入性诊断工具，具有在家监测和更广泛的疾病检测的潜力。
{"title":"Artificial Intelligence-Enhanced Optimization of Wireless Breath Sensor Arrays for Detection of Lung Cancer Using Fuzzy Logic-Guided Genetic Algorithm and Multimodal Machine Learning","authors":"Dong Dinh,Guojun Shang,Lei Cai,Wai Ben Chan,Aiping Ma,Jiurong Li,Aimin Huang,Marie E. Louis,Fengbei Cen,Justin Eduardus Halim,Jiaxi Guo,Lidia Gebre,Qun Liu,Zeqi Li,Lefu Yang,Jin Luo,Susan Lu,Chuan-Jian Zhong","doi":"10.1021/acssensors.5c04441","DOIUrl":"https://doi.org/10.1021/acssensors.5c04441","url":null,"abstract":"Early detection of lung cancer remains critical for improving patient survival, yet current imaging-based screening methods are costly, invasive, and limited in accessibility. Here, we present a fully integrated wireless breath sensing platform that combines nanostructured chemiresistive (NC) sensor arrays with an AI-driven Fuzzy logic-guided Genetic Algorithm (Fuzzy-GA) for optimized volatile organic compound (VOC) detection. The sensor array features nanoparticle structured interfaces, enabling selective VOC adsorption to generate unique breath patterns. Data are captured via a portable low-current multichannel electronics module with real-time wireless transmission. Fuzzy-GA optimization identifies the most informative sensors, reducing array size while maintaining high diagnostic performance. Breath samples from lung cancer patients (n = 35) and non-cancer participants (n = 47) were analyzed using multiple supervised machine learning models (KNN, SVM, Random Forest, XGBoost, and CNN). This represents the first application of Fuzzy-GA to optimize breath sensor arrays. The optimized system, validated using breath samples from lung cancer patients and non-lung cancer controls, achieved high classification accuracy (up to 96%) with reduced system complexity, lower cost, and improved scalability for real-world deployment. The platform offers a clinically viable, non-invasive diagnostic tool with potential for at-home monitoring and broader disease detection.","PeriodicalId":24,"journal":{"name":"ACS Sensors","volume":"28 1","pages":""},"PeriodicalIF":8.9,"publicationDate":"2026-03-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147346705","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 : 2026-03-03DOI: 10.1021/acssensors.5c04094
Jiawei Hu,Mingji Li,Xiuwei Xuan,Wei Li,Hongzhi Li,Cheng Liu,Cuiping Li,Hongji Li
Quantitative remote wound monitoring has the potential to shorten patient recovery time and alleviate the workload of healthcare professionals. In this study, a nitrogen-doped horizontally grown graphene (NHG) antenna sensor with a working frequency of 2.45 GHz was designed for wireless real-time monitoring of wounds. The sensor comprises 32 NHG microtubes (1 mm in diameter), a porous Cu radiation electrode, a polydimethylsiloxane substrate with a cylindrical channel array, and a Cu ground plane. Its novel structure enables body fluid and its temperature and pH value sensing by tracking dual signals, such as resonance frequency and return loss, thereby facilitating the identification of living organisms and real-time quantitative wound assessment. Notably, the NHG microtubes, which penetrate the Cu electrode and PDMS substrate, regulate the radiofrequency radiation field and enhance the monitoring sensitivity. The sensor exhibits a minimum fluid response volume of 25 μL, a temperature detection range of 34-43 °C, a resolution of 0.1 °C, and a response time of 20 s. Furthermore, the NHG antenna sensor reliably evaluated the pH value, volume, and area of the wound using a machine learning algorithm. The system was successfully validated for real-time monitoring of wound healing in mice and has been preliminarily applied to monitor wounds of various sizes and locations in human patients.
{"title":"Contactless and Wireless Wound Monitoring Using Nitrogen-Doped Graphene Antenna Sensor.","authors":"Jiawei Hu,Mingji Li,Xiuwei Xuan,Wei Li,Hongzhi Li,Cheng Liu,Cuiping Li,Hongji Li","doi":"10.1021/acssensors.5c04094","DOIUrl":"https://doi.org/10.1021/acssensors.5c04094","url":null,"abstract":"Quantitative remote wound monitoring has the potential to shorten patient recovery time and alleviate the workload of healthcare professionals. In this study, a nitrogen-doped horizontally grown graphene (NHG) antenna sensor with a working frequency of 2.45 GHz was designed for wireless real-time monitoring of wounds. The sensor comprises 32 NHG microtubes (1 mm in diameter), a porous Cu radiation electrode, a polydimethylsiloxane substrate with a cylindrical channel array, and a Cu ground plane. Its novel structure enables body fluid and its temperature and pH value sensing by tracking dual signals, such as resonance frequency and return loss, thereby facilitating the identification of living organisms and real-time quantitative wound assessment. Notably, the NHG microtubes, which penetrate the Cu electrode and PDMS substrate, regulate the radiofrequency radiation field and enhance the monitoring sensitivity. The sensor exhibits a minimum fluid response volume of 25 μL, a temperature detection range of 34-43 °C, a resolution of 0.1 °C, and a response time of 20 s. Furthermore, the NHG antenna sensor reliably evaluated the pH value, volume, and area of the wound using a machine learning algorithm. The system was successfully validated for real-time monitoring of wound healing in mice and has been preliminarily applied to monitor wounds of various sizes and locations in human patients.","PeriodicalId":24,"journal":{"name":"ACS Sensors","volume":"45 1","pages":"XXX"},"PeriodicalIF":8.9,"publicationDate":"2026-03-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147346472","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}
A fundamental challenge in artificial photosynthesis and sensing is replicating nature's ability to direct energy flow away from destructive pathways. Here, we show that spatial confinement within bioinspired vesicles induces a deterministic charge-branching process between co-assembled porphyrin and carotenoid chromophores. This decouples the excited-state manifold, directing electrons toward the semiconductor for photoelectrochemical conversion while channeling radiative relaxation into a complementary fluorescence pathway. The two orthogonal signals, originating from a single binding event, provide built-in self-validation and effectively suppress false responses. Applied to serum amyloid A detection, the confined interface achieves sub-picogram sensitivity and robust signal stability in human serum. Data analysis confirms that the branched photocurrent dynamics quantitatively report analyte concentration. These findings identify confinement-induced charge branching as a molecular mechanism that enables adaptive and self-validating photoelectronic interfaces mimicking the feedback control of natural photosystems.
{"title":"Confinement-Induced Charge Branching in Bioinspired Vesicles Enables Self-Validated Photoelectrochemical Sensing.","authors":"Ruicheng Xu,Huayue Sun,Wei Yang,Yuji Zhang,Jérome Chauvin,Xue-Ji Zhang,Lei Huang,Serge Cosnier,Dan Shan","doi":"10.1021/acssensors.5c04601","DOIUrl":"https://doi.org/10.1021/acssensors.5c04601","url":null,"abstract":"A fundamental challenge in artificial photosynthesis and sensing is replicating nature's ability to direct energy flow away from destructive pathways. Here, we show that spatial confinement within bioinspired vesicles induces a deterministic charge-branching process between co-assembled porphyrin and carotenoid chromophores. This decouples the excited-state manifold, directing electrons toward the semiconductor for photoelectrochemical conversion while channeling radiative relaxation into a complementary fluorescence pathway. The two orthogonal signals, originating from a single binding event, provide built-in self-validation and effectively suppress false responses. Applied to serum amyloid A detection, the confined interface achieves sub-picogram sensitivity and robust signal stability in human serum. Data analysis confirms that the branched photocurrent dynamics quantitatively report analyte concentration. These findings identify confinement-induced charge branching as a molecular mechanism that enables adaptive and self-validating photoelectronic interfaces mimicking the feedback control of natural photosystems.","PeriodicalId":24,"journal":{"name":"ACS Sensors","volume":"1 1","pages":"XXX"},"PeriodicalIF":8.9,"publicationDate":"2026-03-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147346470","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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