Pub Date : 2025-04-08DOI: 10.1021/acssensors.4c03734
Hui Liu, Hongqiang Wang, Wenjing Mei, Xin Wang, Jiayu Sun, Xiaohai Yang, Qing Wang, Kemin Wang
The challenge of developing sensing platforms for the direct monitoring of targets within complex samples is well-recognized. To address this, a one-step electrochemical sensing detection platform was introduced, featuring an innovative Y-shaped DNA molecular pendulum design. The approach deviated from the conventional molecular pendulum mode by employing a split aptamer instead of a full one, thereby enabling the detection of small molecules and low-molecular-weight proteins. Three Y-shaped DNA molecular pendulum configurations were designed: the single-arm, the flexible double-arm, and the stable double-arm Y-shaped DNA molecular pendulum. The results revealed that the Y-shaped scaffold pendulum with a stable two-armed structure not only offered a broader detection range for target concentrations but also produced a more substantial electrical signal enhancement compared to other modes. This enhanced performance is attributed to the stable conformation of this design, which prolongs the time the probe takes to overcome fluid resistance and reach the electrode surface, leading to a more significant alteration in the electrical signal. The sensor can be utilized for one-step detection of enrofloxacin (ENR) in diluted samples (milk, artificial urine, and cosmetics), and its detection range (0.001–100 ng/mL) is fully compliant with the EU maximum residue levels (100 ng/mL) for ENR in milk. Additionally, the sensor can detect myoglobin (Myo) in artificial urine and serum by simply changing the recognized DNA strand. This work provided a simple, expandable idea for the detection of small molecules and low-molecular-weight proteins.
{"title":"Y-Shaped Deoxyribonucleic Acid Scaffold Pendulums: A One-Step Electrochemical Sensor","authors":"Hui Liu, Hongqiang Wang, Wenjing Mei, Xin Wang, Jiayu Sun, Xiaohai Yang, Qing Wang, Kemin Wang","doi":"10.1021/acssensors.4c03734","DOIUrl":"https://doi.org/10.1021/acssensors.4c03734","url":null,"abstract":"The challenge of developing sensing platforms for the direct monitoring of targets within complex samples is well-recognized. To address this, a one-step electrochemical sensing detection platform was introduced, featuring an innovative Y-shaped DNA molecular pendulum design. The approach deviated from the conventional molecular pendulum mode by employing a split aptamer instead of a full one, thereby enabling the detection of small molecules and low-molecular-weight proteins. Three Y-shaped DNA molecular pendulum configurations were designed: the single-arm, the flexible double-arm, and the stable double-arm Y-shaped DNA molecular pendulum. The results revealed that the Y-shaped scaffold pendulum with a stable two-armed structure not only offered a broader detection range for target concentrations but also produced a more substantial electrical signal enhancement compared to other modes. This enhanced performance is attributed to the stable conformation of this design, which prolongs the time the probe takes to overcome fluid resistance and reach the electrode surface, leading to a more significant alteration in the electrical signal. The sensor can be utilized for one-step detection of enrofloxacin (ENR) in diluted samples (milk, artificial urine, and cosmetics), and its detection range (0.001–100 ng/mL) is fully compliant with the EU maximum residue levels (100 ng/mL) for ENR in milk. Additionally, the sensor can detect myoglobin (Myo) in artificial urine and serum by simply changing the recognized DNA strand. This work provided a simple, expandable idea for the detection of small molecules and low-molecular-weight proteins.","PeriodicalId":24,"journal":{"name":"ACS Sensors","volume":"30 1","pages":""},"PeriodicalIF":8.9,"publicationDate":"2025-04-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143798328","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 : 2025-04-08DOI: 10.1021/acssensors.5c00334
Axel Camazzola, Elena Buglakova, Louis W. Perrin, Verena Rukes, Chan Cao
Biological nanopores have revolutionized DNA sequencing with their incredible advantages of long reads, high throughput, portability, and low material requirement. Despite numerous improvements, base calling remains challenging due to the influence of neighboring nucleobases at the reading site. One direction of development is exploring or designing new nanopores to improve base calling accuracy. Aerolysin is emerging as a powerful candidate, which can identify the subtle differences of detected molecules. However, not many studies focus on translating these advantages into DNA sequencing. Here, we used streptavidin to immobilize ssDNA inside an engineered aerolysin channel, which allows us to investigate its sensing regions, and the neighboring bases influence. By increasing the voltage, we eliminate the neighboring influence and reduce the k-mer size to one nucleobase. These findings hold great potential for improving the accuracy of nanopore DNA sequencing as well as aerolysin nanopore-based sequencing for other polymers.
{"title":"Eliminating the Interference of Neighboring Nucleobases in Aerolysin for Nanopore Sequencing","authors":"Axel Camazzola, Elena Buglakova, Louis W. Perrin, Verena Rukes, Chan Cao","doi":"10.1021/acssensors.5c00334","DOIUrl":"https://doi.org/10.1021/acssensors.5c00334","url":null,"abstract":"Biological nanopores have revolutionized DNA sequencing with their incredible advantages of long reads, high throughput, portability, and low material requirement. Despite numerous improvements, base calling remains challenging due to the influence of neighboring nucleobases at the reading site. One direction of development is exploring or designing new nanopores to improve base calling accuracy. Aerolysin is emerging as a powerful candidate, which can identify the subtle differences of detected molecules. However, not many studies focus on translating these advantages into DNA sequencing. Here, we used streptavidin to immobilize ssDNA inside an engineered aerolysin channel, which allows us to investigate its sensing regions, and the neighboring bases influence. By increasing the voltage, we eliminate the neighboring influence and reduce the k-mer size to one nucleobase. These findings hold great potential for improving the accuracy of nanopore DNA sequencing as well as aerolysin nanopore-based sequencing for other polymers.","PeriodicalId":24,"journal":{"name":"ACS Sensors","volume":"58 1","pages":""},"PeriodicalIF":8.9,"publicationDate":"2025-04-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143806137","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}
Early screening of individuals with high-risk lung nodules can significantly improve the prognosis of lung cancer patients, and accurate identification of lung nodule subtypes can provide guidance for medical treatment. Exhaled breath (EB) analysis via eNoses offers a quick and noninvasive approach, but current eNose technology lacks quality control and solid validation in large population studies. Herein, an eNose platform integrated with a metal ion-decorated graphene sensor array and a breath sampling accessory was established. EB samples from 427 healthy subjects and 2586 subjects with lung nodules, including various benign and malignant subtypes, were collected through the breath sampling accessory for quality control. The large-cohort clinical EB samples were analyzed by the eNose platform to acquire the cross-reactive resistance response. Breathprint analysis for high-risk lung nodules using SVM and age-matched training sets yielded strong and robust performance. Combined with baseline data, the model achieved an AUC of 0.93 (95% CI, 0.89–0.96) on the external test set, with 97% sensitivity and 73% specificity. Moreover, dimensionality reduction analysis of breathprints demonstrated separability across different lung nodule subtypes. This study demonstrates the reliability of the graphene eNose platform to identify high-risk lung nodules and classify lung nodule subtypes in a noninvasive and rapid method.
{"title":"Early Screening and Subtype Identification of High-Risk Lung Nodules via Breathprint by Graphene eNose Platform: A Large Cohort Study","authors":"Xingyu Zhu, Qiaofen Chen, Jiajing Sun, Lichen Zhang, Zhengwei Huang, Jingwei Xu, Haichuan Hu, Yuqi He, Zhao Chen, Xiaogang Ye, Xueyin Chen, Aotian Guo, Sheng Lu, Tao Shen, Jianmin Wu, Zhengfu He","doi":"10.1021/acssensors.5c00314","DOIUrl":"https://doi.org/10.1021/acssensors.5c00314","url":null,"abstract":"Early screening of individuals with high-risk lung nodules can significantly improve the prognosis of lung cancer patients, and accurate identification of lung nodule subtypes can provide guidance for medical treatment. Exhaled breath (EB) analysis via eNoses offers a quick and noninvasive approach, but current eNose technology lacks quality control and solid validation in large population studies. Herein, an eNose platform integrated with a metal ion-decorated graphene sensor array and a breath sampling accessory was established. EB samples from 427 healthy subjects and 2586 subjects with lung nodules, including various benign and malignant subtypes, were collected through the breath sampling accessory for quality control. The large-cohort clinical EB samples were analyzed by the eNose platform to acquire the cross-reactive resistance response. Breathprint analysis for high-risk lung nodules using SVM and age-matched training sets yielded strong and robust performance. Combined with baseline data, the model achieved an AUC of 0.93 (95% CI, 0.89–0.96) on the external test set, with 97% sensitivity and 73% specificity. Moreover, dimensionality reduction analysis of breathprints demonstrated separability across different lung nodule subtypes. This study demonstrates the reliability of the graphene eNose platform to identify high-risk lung nodules and classify lung nodule subtypes in a noninvasive and rapid method.","PeriodicalId":24,"journal":{"name":"ACS Sensors","volume":"60 1","pages":""},"PeriodicalIF":8.9,"publicationDate":"2025-04-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143798331","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 field of bioelectronics has witnessed significant advancements, offering practical solutions for personalized healthcare through the acquisition and analysis of skin-based physical, chemical, and electrophysiological signals. Despite these advancements, current bioelectronics face several challenges, including complex preparation procedures, poor skin adherence, susceptibility to motion artifacts, and limited personalization and reconfigurability capabilities. In this study, we introduce an innovative method for fabricating erasable bioelectronics on a flexible substrate coating adhered to the skin using a ballpoint pen without any postprocessing. Our approach yields devices that are thin, erasable, reconfigurable, dry-friction resistant, self-healing, and highly customizable. We demonstrate the multifunctionality of these on-skin bioelectronics through their application as strain sensors for motion monitoring, temperature and humidity sensors for breath monitoring, and heating elements for target point hyperthermia. The potential of our bioelectronics in personalized medicine is substantial, particularly in health monitoring. We provide a novel solution for achieving efficient and convenient personalized medical services, addressing the limitations of existing technologies and paving the way for next-generation wearable health devices.
{"title":"Erasable and Multifunctional On-Skin Bioelectronics Prepared by Direct Writing","authors":"Xintao Zhu, Wei Liu, Qinzhou Luo, Zhen Lv, Ligang Yao, Fanan Wei","doi":"10.1021/acssensors.4c03599","DOIUrl":"https://doi.org/10.1021/acssensors.4c03599","url":null,"abstract":"The field of bioelectronics has witnessed significant advancements, offering practical solutions for personalized healthcare through the acquisition and analysis of skin-based physical, chemical, and electrophysiological signals. Despite these advancements, current bioelectronics face several challenges, including complex preparation procedures, poor skin adherence, susceptibility to motion artifacts, and limited personalization and reconfigurability capabilities. In this study, we introduce an innovative method for fabricating erasable bioelectronics on a flexible substrate coating adhered to the skin using a ballpoint pen without any postprocessing. Our approach yields devices that are thin, erasable, reconfigurable, dry-friction resistant, self-healing, and highly customizable. We demonstrate the multifunctionality of these on-skin bioelectronics through their application as strain sensors for motion monitoring, temperature and humidity sensors for breath monitoring, and heating elements for target point hyperthermia. The potential of our bioelectronics in personalized medicine is substantial, particularly in health monitoring. We provide a novel solution for achieving efficient and convenient personalized medical services, addressing the limitations of existing technologies and paving the way for next-generation wearable health devices.","PeriodicalId":24,"journal":{"name":"ACS Sensors","volume":"244 1","pages":""},"PeriodicalIF":8.9,"publicationDate":"2025-04-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143798329","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 : 2025-04-07DOI: 10.1021/acssensors.5c00021
Xiaojing Zhang, Li Sin Wong, Zhenyuan Tang, Hangming Xiong, Jiaying Sun, Liubing Kong, Min Tu, Yanjie Hu, Yong Zhou, Wenwu Zhu, K. Jimmy Hsia, Hao Wan, Ping Wang
The COVID-19 pandemic has highlighted the importance of early screening and pathogen identification for the effective treatment of pneumonia. Exhaled breath condensate (EBC) provides a noninvasive and easily accessible method for early diagnosis of respiratory diseases, as it captures biomarkers from the airway lining fluid, offering a timely and reliable reflection of respiratory inflammation. Procalcitonin (PCT) is a biomarker widely used to assess infection type and severity, particularly for distinguishing between bacterial and nonbacterial pneumonia. However, detecting PCT especially in EBC is challenging due to its extremely low concentrations. In this work, we developed an ultrasensitive Love-type surface acoustic wave (Love-SAW) biosensor based on self-assembled gold nanoparticles on dendritic mesoporous silica nanoparticles (DMSN@AuNPs) with in situ amplification for PCT detection in EBC. Dendritic mesoporous silica nanoparticles (DMSNs), an emerging porous material with features of large surface area, high thermal stability, and ease of functionalization were employed to load a large amount of AuNPs that can spontaneously grow in situ to further enhance the sensing performance. An automatic detection system was also developed to integrate with the Love-SAW biosensor for multichannel detection of PCT in EBC for pneumonia screening. The DMSN@AuNPs based Love-SAW biosensor demonstrates remarkable performance with a detection range of 0.01–10 ng/mL and detection limit of 3.7 pg/mL, which is about 350 times higher than conventional AuNPs-based methods. These results validate the potential of DMSN@AuNPs based Love-SAW biosensors for ultrasensitive detection of low-concentration biomarkers, providing a promising platform for in vitro diagnostics.
{"title":"Ultrasensitive Love-SAW Biosensor Based on Self-Assembled DMSN@AuNPs with In Situ Amplification for Detecting Biomarker Procalcitonin in Exhaled Breath Condensate","authors":"Xiaojing Zhang, Li Sin Wong, Zhenyuan Tang, Hangming Xiong, Jiaying Sun, Liubing Kong, Min Tu, Yanjie Hu, Yong Zhou, Wenwu Zhu, K. Jimmy Hsia, Hao Wan, Ping Wang","doi":"10.1021/acssensors.5c00021","DOIUrl":"https://doi.org/10.1021/acssensors.5c00021","url":null,"abstract":"The COVID-19 pandemic has highlighted the importance of early screening and pathogen identification for the effective treatment of pneumonia. Exhaled breath condensate (EBC) provides a noninvasive and easily accessible method for early diagnosis of respiratory diseases, as it captures biomarkers from the airway lining fluid, offering a timely and reliable reflection of respiratory inflammation. Procalcitonin (PCT) is a biomarker widely used to assess infection type and severity, particularly for distinguishing between bacterial and nonbacterial pneumonia. However, detecting PCT especially in EBC is challenging due to its extremely low concentrations. In this work, we developed an ultrasensitive Love-type surface acoustic wave (Love-SAW) biosensor based on self-assembled gold nanoparticles on dendritic mesoporous silica nanoparticles (DMSN@AuNPs) with in situ amplification for PCT detection in EBC. Dendritic mesoporous silica nanoparticles (DMSNs), an emerging porous material with features of large surface area, high thermal stability, and ease of functionalization were employed to load a large amount of AuNPs that can spontaneously grow in situ to further enhance the sensing performance. An automatic detection system was also developed to integrate with the Love-SAW biosensor for multichannel detection of PCT in EBC for pneumonia screening. The DMSN@AuNPs based Love-SAW biosensor demonstrates remarkable performance with a detection range of 0.01–10 ng/mL and detection limit of 3.7 pg/mL, which is about 350 times higher than conventional AuNPs-based methods. These results validate the potential of DMSN@AuNPs based Love-SAW biosensors for ultrasensitive detection of low-concentration biomarkers, providing a promising platform for in vitro diagnostics.","PeriodicalId":24,"journal":{"name":"ACS Sensors","volume":"217 1","pages":""},"PeriodicalIF":8.9,"publicationDate":"2025-04-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143789623","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 : 2025-04-07DOI: 10.1021/acssensors.4c03477
Mengfei Xu, Ziliang Song, Quan Peng, Qingda Xu, Zhiyuan Du, Tao Ruan, Bin Yang, Qingkun Liu, Xu Liu, Xumin Hou, Mu Qin, Jingquan Liu
Pulse field ablation (PFA) has become a popular technique for treating tens of millions of patients with atrial fibrillation, as it avoids many complications associated with traditional radiofrequency ablation. However, currently, limited studies have used millimeter-scale rigid electrodes modified from radiofrequency ablation to apply electrical pulses of thousands of volts without integrated sensing capabilities. Herein, we combine fractal microelectronics with biomedical catheters for low-voltage PFA, detection of electrode–tissue contact, and interventional electrocardiogram recording. The fractal configuration increases the ratio of the microelectrode insulating edge to area, which facilitates the transfer of current from the microelectrode to the tissue, increasing the ablation depth by 38.6% at 300 V (a 10-fold reduction compared to current technology). In vivo ablation experiments on living beagles successfully block electrical conduction, as demonstrated by voltage mapping and electrical pacing. More impressively, this study provides the first evidence that microelectrodes can selectively ablate cardiomyocytes without damaging nerves and blood vessels, greatly improving the safety of PFA. These results are essential for the clinical translation of PFA in the field of cardiac electrophysiology.
{"title":"Catheter-Integrated Fractal Microelectronics for Low-Voltage Ablation and Minimally Invasive Sensing","authors":"Mengfei Xu, Ziliang Song, Quan Peng, Qingda Xu, Zhiyuan Du, Tao Ruan, Bin Yang, Qingkun Liu, Xu Liu, Xumin Hou, Mu Qin, Jingquan Liu","doi":"10.1021/acssensors.4c03477","DOIUrl":"https://doi.org/10.1021/acssensors.4c03477","url":null,"abstract":"Pulse field ablation (PFA) has become a popular technique for treating tens of millions of patients with atrial fibrillation, as it avoids many complications associated with traditional radiofrequency ablation. However, currently, limited studies have used millimeter-scale rigid electrodes modified from radiofrequency ablation to apply electrical pulses of thousands of volts without integrated sensing capabilities. Herein, we combine fractal microelectronics with biomedical catheters for low-voltage PFA, detection of electrode–tissue contact, and interventional electrocardiogram recording. The fractal configuration increases the ratio of the microelectrode insulating edge to area, which facilitates the transfer of current from the microelectrode to the tissue, increasing the ablation depth by 38.6% at 300 V (a 10-fold reduction compared to current technology). <i>In vivo</i> ablation experiments on living beagles successfully block electrical conduction, as demonstrated by voltage mapping and electrical pacing. More impressively, this study provides the first evidence that microelectrodes can selectively ablate cardiomyocytes without damaging nerves and blood vessels, greatly improving the safety of PFA. These results are essential for the clinical translation of PFA in the field of cardiac electrophysiology.","PeriodicalId":24,"journal":{"name":"ACS Sensors","volume":"37 1","pages":""},"PeriodicalIF":8.9,"publicationDate":"2025-04-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143789633","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 corneal permeability of an eye drop is crucial in drug delivery into the eye, but our understanding of drug migration through the cornea and drug distribution within the anterior chamber still requires improvement. To this end, we developed an electrochemical method using boron-doped diamond (BDD) to monitor real-time changes in the drug concentration in the anterior chamber. A needle-shaped BDD microelectrode, with a respective length and tip diameter of ∼200 and ∼40 μm, was used in the in vivo detection of brimonidine tartrate (BRM), which is a widely used antiglaucoma drug. We inserted the tip of the electrode into the right cornea of an anesthetized mouse. BRM was then administered to the right eye, resulting in the successful real-time monitoring of the changes in current. The recorded current reflected the combined reduction of BRM and dissolved oxygen within the anterior chamber. Based on the subtraction of the contribution of the oxygen, the BRM-specific reduction current increased immediately after administration, corresponding to 4.1 μM. Validation via liquid chromatography-tandem mass spectrometry confirmed the accuracy of this approach. Notably, the pharmacological effect of BRM, i.e., a reduced intraocular pressure, was observed 30 min after administration, lagging behind drug migration. These findings may provide valuable insights into the ocular pharmacokinetics of novel drugs and facilitate the development of more effective therapeutic approaches.
{"title":"Real-Time In Vivo Monitoring of Eye Drop Concentration Using Boron-Doped Diamond Microelectrodes and Its Relevance to Drug Efficacy","authors":"Risa Ogawa, Genki Ogata, Reiko Yamagishi, Megumi Honjo, Makoto Aihara, Yasuaki Einaga","doi":"10.1021/acssensors.5c00220","DOIUrl":"https://doi.org/10.1021/acssensors.5c00220","url":null,"abstract":"The corneal permeability of an eye drop is crucial in drug delivery into the eye, but our understanding of drug migration through the cornea and drug distribution within the anterior chamber still requires improvement. To this end, we developed an electrochemical method using boron-doped diamond (BDD) to monitor real-time changes in the drug concentration in the anterior chamber. A needle-shaped BDD microelectrode, with a respective length and tip diameter of ∼200 and ∼40 μm, was used in the in vivo detection of brimonidine tartrate (BRM), which is a widely used antiglaucoma drug. We inserted the tip of the electrode into the right cornea of an anesthetized mouse. BRM was then administered to the right eye, resulting in the successful real-time monitoring of the changes in current. The recorded current reflected the combined reduction of BRM and dissolved oxygen within the anterior chamber. Based on the subtraction of the contribution of the oxygen, the BRM-specific reduction current increased immediately after administration, corresponding to 4.1 μM. Validation via liquid chromatography-tandem mass spectrometry confirmed the accuracy of this approach. Notably, the pharmacological effect of BRM, i.e., a reduced intraocular pressure, was observed 30 min after administration, lagging behind drug migration. These findings may provide valuable insights into the ocular pharmacokinetics of novel drugs and facilitate the development of more effective therapeutic approaches.","PeriodicalId":24,"journal":{"name":"ACS Sensors","volume":"92 1","pages":""},"PeriodicalIF":8.9,"publicationDate":"2025-04-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143798330","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 : 2025-04-06DOI: 10.1021/acssensors.4c03560
Jintai Deng, Wang Wan, Rui Sun, Qiuxuan Xia, Jing Yan, Jialu Sun, Xiaomeng Jia, Hao Jin, Xueqing Wang, Kun Guo, Man Li, Yu Liu
Aggrephagy in cells is defined as the degradation of intracellular aggregated proteins via the macroautophagy process. This process sequesters protein aggregates into autolysosomes, which bear characteristic viscous and acidic microenvironments. Limited protein aggregation sensors are environmentally compatible with the cellular aggrephagy process. Here, we report an acid-resistant and viscosity-sensitive proteome aggregation sensor to detect cellular aggrephagy in stressed cells and clinical samples. This sensor fluoresces upon selectively and ubiquitously binding to different aggregated proteins. Importantly, unlike other reported protein aggregation sensors, our probe offers unique acid-resistant fluorescence inside aggregated proteins, enabling its application in the acidic autolysosome microenvironment. In live cells under various stressed conditions, the optimal probe (A6) successfully detects aggregated proteome in autolysosomes, as validated by colocalization with a lysosomal tracker. Additionally, we demonstrate that the sensor can detect proteome aggregation in heat-stressed clinical tissue samples biopsied from cancer patients undergoing thermal perfusion treatment. Together, the reported acid-resistant and viscosity-sensitive protein aggregation sensor facilitates the detection of cellular aggrephagy by chemically matching its microenvironmental characteristics.
{"title":"Acid-Resistant and Viscosity-Sensitive Proteome Aggregation Sensor To Visualize Cellular Aggrephagy in Live Cells and Clinical Samples","authors":"Jintai Deng, Wang Wan, Rui Sun, Qiuxuan Xia, Jing Yan, Jialu Sun, Xiaomeng Jia, Hao Jin, Xueqing Wang, Kun Guo, Man Li, Yu Liu","doi":"10.1021/acssensors.4c03560","DOIUrl":"https://doi.org/10.1021/acssensors.4c03560","url":null,"abstract":"Aggrephagy in cells is defined as the degradation of intracellular aggregated proteins via the macroautophagy process. This process sequesters protein aggregates into autolysosomes, which bear characteristic viscous and acidic microenvironments. Limited protein aggregation sensors are environmentally compatible with the cellular aggrephagy process. Here, we report an acid-resistant and viscosity-sensitive proteome aggregation sensor to detect cellular aggrephagy in stressed cells and clinical samples. This sensor fluoresces upon selectively and ubiquitously binding to different aggregated proteins. Importantly, unlike other reported protein aggregation sensors, our probe offers unique acid-resistant fluorescence inside aggregated proteins, enabling its application in the acidic autolysosome microenvironment. In live cells under various stressed conditions, the optimal probe (A6) successfully detects aggregated proteome in autolysosomes, as validated by colocalization with a lysosomal tracker. Additionally, we demonstrate that the sensor can detect proteome aggregation in heat-stressed clinical tissue samples biopsied from cancer patients undergoing thermal perfusion treatment. Together, the reported acid-resistant and viscosity-sensitive protein aggregation sensor facilitates the detection of cellular aggrephagy by chemically matching its microenvironmental characteristics.","PeriodicalId":24,"journal":{"name":"ACS Sensors","volume":"18 1","pages":""},"PeriodicalIF":8.9,"publicationDate":"2025-04-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143789634","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 : 2025-04-05DOI: 10.1021/acssensors.5c00126
Madeline L. Honig, Philippe Bühlmann
The way upper limits of detection (LODs) are typically reported in the ion-selective electrode (ISE) literature is unfortunately outdated. It is well understood that the upper LOD of a polymeric-membrane ISE is limited by Donnan failure, that is, the transfer of primary ions along with interfering ions of the opposite charge sign (commonly referred to as counterions) from the sample into the sensing membrane. However, it is often difficult to compare upper LODs for ISEs from different sources. The majority of publications on ISEs describe Donnan failure for one type of counterion only, making it impossible for end users to predict the interference for other counterions. Moreover, linear ranges for ISEs based on different ionophores cannot be compared to one another when Donnan failure was reported for different counterions. To this end, we introduce here selectivity coefficients, KI,XpotX, for interfering counterions. Using this new concept, the primary ion activity at which Donnan failure occurs can be readily predicted from measured KI,XpotX values by the use of the uncomplicated expression aXzI/zx/KI,XpotX. Consistent with the intuition that many ISE users have for conventional selectivity coefficients, large KI,XpotX values are characteristic for counterions that interfere strongly. We show experimentally that trends as predicted by the phase boundary model for Donnan failure, such as the effects of counterion hydrophobicity and ionophore complex stability, are often accurately predicted with the KI,XpotX approach. However, there are notable exceptions when the underlying assumptions made by users do not apply, such as when counterions unexpectedly form aggregates with other species in the sensing membranes. The empirically measured KI,XpotX coefficients enable the discovery of such phenomena, opening a rational path to improving upper LODs and, thereby, linear response ranges.
{"title":"Ion-Selective Electrodes: Selectivity Coefficients for Interfering Ions of the Opposite Charge Sign","authors":"Madeline L. Honig, Philippe Bühlmann","doi":"10.1021/acssensors.5c00126","DOIUrl":"https://doi.org/10.1021/acssensors.5c00126","url":null,"abstract":"The way upper limits of detection (LODs) are typically reported in the ion-selective electrode (ISE) literature is unfortunately outdated. It is well understood that the upper LOD of a polymeric-membrane ISE is limited by Donnan failure, that is, the transfer of primary ions along with interfering ions of the opposite charge sign (commonly referred to as counterions) from the sample into the sensing membrane. However, it is often difficult to compare upper LODs for ISEs from different sources. The majority of publications on ISEs describe Donnan failure for one type of counterion only, making it impossible for end users to predict the interference for other counterions. Moreover, linear ranges for ISEs based on different ionophores cannot be compared to one another when Donnan failure was reported for different counterions. To this end, we introduce here selectivity coefficients, <i>K</i><sub><i>I</i>,<i>X</i></sub><sup>potX</sup>, for interfering counterions. Using this new concept, the primary ion activity at which Donnan failure occurs can be readily predicted from measured <i>K</i><sub><i>I</i>,<i>X</i></sub><sup>potX</sup> values by the use of the uncomplicated expression <i>a</i><sub>X</sub><sup><i>z</i><sub><i>I</i></sub>/<i>z</i><sub><i>x</i></sub></sup>/<i>K</i><sub><i>I</i>,<i>X</i></sub><sup>potX</sup>. Consistent with the intuition that many ISE users have for conventional selectivity coefficients, large <i>K</i><sub><i>I</i>,<i>X</i></sub><sup>potX</sup> values are characteristic for counterions that interfere strongly. We show experimentally that trends as predicted by the phase boundary model for Donnan failure, such as the effects of counterion hydrophobicity and ionophore complex stability, are often accurately predicted with the <i>K</i><sub><i>I</i>,<i>X</i></sub><sup>potX</sup> approach. However, there are notable exceptions when the underlying assumptions made by users do not apply, such as when counterions unexpectedly form aggregates with other species in the sensing membranes. The empirically measured <i>K</i><sub><i>I</i>,<i>X</i></sub><sup>potX</sup> coefficients enable the discovery of such phenomena, opening a rational path to improving upper LODs and, thereby, linear response ranges.","PeriodicalId":24,"journal":{"name":"ACS Sensors","volume":"37 1","pages":""},"PeriodicalIF":8.9,"publicationDate":"2025-04-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143783018","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 : 2025-04-04DOI: 10.1021/acssensors.4c03260
Che-Lun Chin, Chia-En Chang, Ling Chao
Raman spectroscopy in biological applications faces challenges due to complex spectra, characterized by peaks of varying widths and significant biological background noise. Convolutional neural networks (CNNs) are widely used for spectrum classification due to their ability to capture local peak features. In this study, we introduce a multiscale CNN designed to detect weak biomolecule signals and differentiate spectra with features that cannot be statistically distinguished. The approach is further enhanced by a new visualization technique tailored for multiscale spectral analysis, providing clear insights into classification results. Using the classification of cholera toxin B subunit (CTB)-treated versus untreated cell membrane samples, whose spectra cannot be statistically differentiated, the optimized multiscale CNN achieved superior performance compared to traditional machine learning methods and existing multiscale CNNs, with accuracy (99.22%), sensitivity (99.27%), specificity (99.16%), and precision (99.20%). Our new visualization method, based on gradients of activation maps with respect to class scores, generates saliency scores that capture sample variations, with decision-making relying on consistently identified peak features. By visualizing the effects of different kernel sizes, Grad-AM highlights features at varying scales, aligning closely with spectral features and enhancing CNN interpretability in complex biomolecular analysis. These advancements demonstrate the potential of our method to improve spectral analysis and reveal previously hidden peaks in complex biological environments.
生物应用中的拉曼光谱面临着复杂光谱的挑战，其特点是峰值宽度不一，生物背景噪声很大。卷积神经网络（CNN）能够捕捉局部峰值特征，因此被广泛用于光谱分类。在本研究中，我们引入了一种多尺度 CNN，旨在检测微弱的生物分子信号，并区分具有无法从统计学角度区分的特征的光谱。为多尺度光谱分析量身定制的新型可视化技术进一步增强了该方法，为分类结果提供了清晰的洞察力。通过对霍乱毒素 B 亚基（CTB）处理过与未处理过的细胞膜样本进行分类，优化的多尺度 CNN 在准确度（99.22%）、灵敏度（99.27%）、特异度（99.16%）和精确度（99.20%）方面均优于传统的机器学习方法和现有的多尺度 CNN。我们的新可视化方法基于激活图相对于类得分的梯度，可生成捕捉样本变化的显著性得分，决策制定依赖于一致识别的峰值特征。通过可视化不同内核大小的影响，Grad-AM 突出了不同尺度的特征，与光谱特征紧密结合，增强了复杂生物分子分析中 CNN 的可解释性。这些进步证明了我们的方法在改进光谱分析和揭示复杂生物环境中以前隐藏的峰值方面的潜力。
{"title":"Interpretable Multiscale Convolutional Neural Network for Classification and Feature Visualization of Weak Raman Spectra of Biomolecules at Cell Membranes","authors":"Che-Lun Chin, Chia-En Chang, Ling Chao","doi":"10.1021/acssensors.4c03260","DOIUrl":"https://doi.org/10.1021/acssensors.4c03260","url":null,"abstract":"Raman spectroscopy in biological applications faces challenges due to complex spectra, characterized by peaks of varying widths and significant biological background noise. Convolutional neural networks (CNNs) are widely used for spectrum classification due to their ability to capture local peak features. In this study, we introduce a multiscale CNN designed to detect weak biomolecule signals and differentiate spectra with features that cannot be statistically distinguished. The approach is further enhanced by a new visualization technique tailored for multiscale spectral analysis, providing clear insights into classification results. Using the classification of cholera toxin B subunit (CTB)-treated versus untreated cell membrane samples, whose spectra cannot be statistically differentiated, the optimized multiscale CNN achieved superior performance compared to traditional machine learning methods and existing multiscale CNNs, with accuracy (99.22%), sensitivity (99.27%), specificity (99.16%), and precision (99.20%). Our new visualization method, based on gradients of activation maps with respect to class scores, generates saliency scores that capture sample variations, with decision-making relying on consistently identified peak features. By visualizing the effects of different kernel sizes, Grad-AM highlights features at varying scales, aligning closely with spectral features and enhancing CNN interpretability in complex biomolecular analysis. These advancements demonstrate the potential of our method to improve spectral analysis and reveal previously hidden peaks in complex biological environments.","PeriodicalId":24,"journal":{"name":"ACS Sensors","volume":"6 1","pages":""},"PeriodicalIF":8.9,"publicationDate":"2025-04-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143783019","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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