Andrej M. Savić, Marija Novičić, Vera Miler-Jerković, Olivera Djordjević, Ljubica Konstantinović
This study investigates the feasibility of a novel brain–computer interface (BCI) device designed for sensory training following stroke. The BCI system administers electrotactile stimuli to the user’s forearm, mirroring classical sensory training interventions. Concurrently, selective attention tasks are employed to modulate electrophysiological brain responses (somatosensory event-related potentials—sERPs), reflecting cortical excitability in related sensorimotor areas. The BCI identifies attention-induced changes in the brain’s reactions to stimulation in an online manner. The study protocol assesses the feasibility of online binary classification of selective attention focus in ten subacute stroke patients. Each experimental session includes a BCI training phase for data collection and classifier training, followed by a BCI test phase to evaluate online classification of selective tactile attention based on sERP. During online classification tests, patients complete 20 repetitions of selective attention tasks with feedback on attention focus recognition. Using a single electroencephalographic channel, attention classification accuracy ranges from 70% to 100% across all patients. The significance of this novel BCI paradigm lies in its ability to quantitatively measure selective tactile attention resources throughout the therapy session, introducing a top-down approach to classical sensory training interventions based on repeated neuromuscular electrical stimulation.
{"title":"Electrotactile BCI for Top-Down Somatosensory Training: Clinical Feasibility Trial of Online BCI Control in Subacute Stroke Patients","authors":"Andrej M. Savić, Marija Novičić, Vera Miler-Jerković, Olivera Djordjević, Ljubica Konstantinović","doi":"10.3390/bios14080368","DOIUrl":"https://doi.org/10.3390/bios14080368","url":null,"abstract":"This study investigates the feasibility of a novel brain–computer interface (BCI) device designed for sensory training following stroke. The BCI system administers electrotactile stimuli to the user’s forearm, mirroring classical sensory training interventions. Concurrently, selective attention tasks are employed to modulate electrophysiological brain responses (somatosensory event-related potentials—sERPs), reflecting cortical excitability in related sensorimotor areas. The BCI identifies attention-induced changes in the brain’s reactions to stimulation in an online manner. The study protocol assesses the feasibility of online binary classification of selective attention focus in ten subacute stroke patients. Each experimental session includes a BCI training phase for data collection and classifier training, followed by a BCI test phase to evaluate online classification of selective tactile attention based on sERP. During online classification tests, patients complete 20 repetitions of selective attention tasks with feedback on attention focus recognition. Using a single electroencephalographic channel, attention classification accuracy ranges from 70% to 100% across all patients. The significance of this novel BCI paradigm lies in its ability to quantitatively measure selective tactile attention resources throughout the therapy session, introducing a top-down approach to classical sensory training interventions based on repeated neuromuscular electrical stimulation.","PeriodicalId":100185,"journal":{"name":"Biosensors","volume":"3 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-07-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141864189","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Kai Hu, Weihong Yin, Yunhan Bai, Jiarui Zhang, Juxin Yin, Qiangyuan Zhu, Ying Mu
The detection of biomarkers (such as DNA, RNA, and protein) plays a vital role in medical diagnosis. The CRISPR-based biosensors utilize the CRISPR/Cas system for biometric recognition of targets and use biosensor strategy to read out biological signals without the employment of professional operations. Consequently, the CRISPR-based biosensors demonstrate great potential for the detection of biomarkers with high sensitivity and specificity. However, the signal readout still relies on specialized detectors, limiting its application in on-site detection for medical diagnosis. In this review, we summarize the principles and advances of the CRISPR-based biosensors with a focus on medical diagnosis. Then, we review the advantages and progress of CRISPR-based naked eye biosensors, which can realize diagnosis without additional detectors for signal readout. Finally, we discuss the challenges and further prospects for the development of CRISPR-based biosensors.
{"title":"CRISPR-Based Biosensors for Medical Diagnosis: Readout from Detector-Dependence Detection Toward Naked Eye Detection","authors":"Kai Hu, Weihong Yin, Yunhan Bai, Jiarui Zhang, Juxin Yin, Qiangyuan Zhu, Ying Mu","doi":"10.3390/bios14080367","DOIUrl":"https://doi.org/10.3390/bios14080367","url":null,"abstract":"The detection of biomarkers (such as DNA, RNA, and protein) plays a vital role in medical diagnosis. The CRISPR-based biosensors utilize the CRISPR/Cas system for biometric recognition of targets and use biosensor strategy to read out biological signals without the employment of professional operations. Consequently, the CRISPR-based biosensors demonstrate great potential for the detection of biomarkers with high sensitivity and specificity. However, the signal readout still relies on specialized detectors, limiting its application in on-site detection for medical diagnosis. In this review, we summarize the principles and advances of the CRISPR-based biosensors with a focus on medical diagnosis. Then, we review the advantages and progress of CRISPR-based naked eye biosensors, which can realize diagnosis without additional detectors for signal readout. Finally, we discuss the challenges and further prospects for the development of CRISPR-based biosensors.","PeriodicalId":100185,"journal":{"name":"Biosensors","volume":"195 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-07-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141864338","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
This study presents and compares two methods for identifying the types of extracellular vesicles (EVs) from different cell lines. Through SDS-PAGE analysis, we discovered that the ratio of CD63 to CD81 in different EVs is consistent and distinct, making it a reliable characteristic for recognizing EVs secreted by cancer cells. However, the electrophoresis and imaging processes may introduce errors in the concentration values, especially at lower concentrations, rendering this method potentially less effective. An alternative approach involves the use of quartz crystal microbalance (QCM) and electroanalytical interdigitated electrode (IDT) biosensors for EV type identification and quantification. The QCM frequency shift caused by EVs is directly proportional to their concentration, while electroanalysis relies on measuring the curvature of the I−V curve as a distinguishing feature, which is also proportional to EV concentration. Linear regression lines for the QCM frequency shift and the electroanalysis curvature of various EV types are plotted separately, enabling the estimation of the corresponding concentration for an unknown EV type on the graphs. By intersecting the results from both biosensors, the unknown EV type can be identified. The biosensor analysis method proves to be an effective means of analyzing both the type and concentration of EVs from different cell lines.
本研究介绍并比较了两种识别不同细胞系细胞外囊泡 (EV) 类型的方法。通过 SDS-PAGE 分析，我们发现不同 EVs 中 CD63 与 CD81 的比例是一致且不同的，这使其成为识别癌细胞分泌的 EVs 的可靠特征。不过，电泳和成像过程可能会导致浓度值出现误差，尤其是在浓度较低的情况下，因此这种方法可能不太有效。另一种方法是使用石英晶体微天平（QCM）和电分析电极间（IDT）生物传感器来识别和量化 EV 类型。由 EV 引起的 QCM 频率偏移与 EV 浓度成正比，而电分析则依靠测量 I-V 曲线的曲率作为鉴别特征，该曲率也与 EV 浓度成正比。QCM 频率偏移和各种 EV 类型的电分析曲率的线性回归线分别绘制，这样就能在图形上估算出未知 EV 类型的相应浓度。将两个生物传感器的结果相交，就能确定未知的电动汽车类型。事实证明，生物传感器分析方法是分析来自不同细胞系的 EV 类型和浓度的有效手段。
{"title":"Identification and Quantification of Extracellular Vesicles: Comparison of SDS-PAGE Analysis and Biosensor Analysis with QCM and IDT Chips","authors":"Yaw-Jen Chang, Wen-Tung Yang, Cheng-Hsuan Lei","doi":"10.3390/bios14080366","DOIUrl":"https://doi.org/10.3390/bios14080366","url":null,"abstract":"This study presents and compares two methods for identifying the types of extracellular vesicles (EVs) from different cell lines. Through SDS-PAGE analysis, we discovered that the ratio of CD63 to CD81 in different EVs is consistent and distinct, making it a reliable characteristic for recognizing EVs secreted by cancer cells. However, the electrophoresis and imaging processes may introduce errors in the concentration values, especially at lower concentrations, rendering this method potentially less effective. An alternative approach involves the use of quartz crystal microbalance (QCM) and electroanalytical interdigitated electrode (IDT) biosensors for EV type identification and quantification. The QCM frequency shift caused by EVs is directly proportional to their concentration, while electroanalysis relies on measuring the curvature of the I−V curve as a distinguishing feature, which is also proportional to EV concentration. Linear regression lines for the QCM frequency shift and the electroanalysis curvature of various EV types are plotted separately, enabling the estimation of the corresponding concentration for an unknown EV type on the graphs. By intersecting the results from both biosensors, the unknown EV type can be identified. The biosensor analysis method proves to be an effective means of analyzing both the type and concentration of EVs from different cell lines.","PeriodicalId":100185,"journal":{"name":"Biosensors","volume":"74 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-07-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141774550","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Zengfu Guan, Jiaguo Yan, Haiyuan Yan, Bin Li, Lei Guo, Qiang Sun, Tie Geng, Xiaoxuan Guo, Lidong Liu, Wenqing Yan, Xin Wang
With the rapid development of modern industry, it is urgently needed to measure the biotoxicity of complex chemicals. Microbial electrochemical biotoxicity sensors are an attractive technology; however, their application is usually limited by their stability and reusability after measurements. Here, we improve their performance by encapsulating the electroactive biofilm with polydopamine (PDA), and we evaluate the improvement by different concentrations of heavy metal ions (Cu2+, Ag+, and Fe3+) in terms of inhibition ratio (IR) and durability. Results indicate that the PDA-encapsulated sensor exhibits a more significant detection concentration than the control group, with a 3-fold increase for Cu2+ and a 1.5-fold increase for Ag+. Moreover, it achieves 15 more continuous toxicity tests than the control group, maintaining high electrochemical activity even after continuous toxicity impacts. Images from a confocal laser scanning microscope reveal that the PDA encapsulation protects the activity of the electroactive biofilm. The study, thus, demonstrates that PDA encapsulation is efficacious in improving the performance of microbial electrochemical biotoxicity sensors, which can extend its application to more complex media.
{"title":"Enhanced Stability and Detection Range of Microbial Electrochemical Biotoxicity Sensor by Polydopamine Encapsulation","authors":"Zengfu Guan, Jiaguo Yan, Haiyuan Yan, Bin Li, Lei Guo, Qiang Sun, Tie Geng, Xiaoxuan Guo, Lidong Liu, Wenqing Yan, Xin Wang","doi":"10.3390/bios14080365","DOIUrl":"https://doi.org/10.3390/bios14080365","url":null,"abstract":"With the rapid development of modern industry, it is urgently needed to measure the biotoxicity of complex chemicals. Microbial electrochemical biotoxicity sensors are an attractive technology; however, their application is usually limited by their stability and reusability after measurements. Here, we improve their performance by encapsulating the electroactive biofilm with polydopamine (PDA), and we evaluate the improvement by different concentrations of heavy metal ions (Cu2+, Ag+, and Fe3+) in terms of inhibition ratio (IR) and durability. Results indicate that the PDA-encapsulated sensor exhibits a more significant detection concentration than the control group, with a 3-fold increase for Cu2+ and a 1.5-fold increase for Ag+. Moreover, it achieves 15 more continuous toxicity tests than the control group, maintaining high electrochemical activity even after continuous toxicity impacts. Images from a confocal laser scanning microscope reveal that the PDA encapsulation protects the activity of the electroactive biofilm. The study, thus, demonstrates that PDA encapsulation is efficacious in improving the performance of microbial electrochemical biotoxicity sensors, which can extend its application to more complex media.","PeriodicalId":100185,"journal":{"name":"Biosensors","volume":"67 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-07-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141774458","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Yizhang Xue, Hangbing Liu, Ye Zhang, Weijun Yang, Huixin Li, Yuxuan Gong, Yubai Zhang, Bo Li, Chang Liu, Yi Li
Dexamethasone (Dex) is a widely used glucocorticoid in medical practice, with applications ranging from allergies and inflammation to cerebral edema and shock. Despite its therapeutic benefits, Dex is classified as a prohibited substance for athletes due to its potential performance-enhancing effects. Consequently, there is a critical need for a convenient and rapid detection platform to enable prompt and accurate testing of this drug. In this study, we propose a label-free Förster Resonance Energy Transfer (FRET) aptasensor platform for Dex detection utilizing conjugated polymers (CPs), cationic conjugated polymers (CCPs), and gene finder probes (GFs). The system operates by exploiting the electrostatic interactions between positively charged CCPs and negatively charged DNA, facilitating sensitive and specific Dex detection. The label-free FRET aptasensor platform demonstrated robust performance in detecting Dex, exhibiting high selectivity and sensitivity. The system effectively distinguished Dex from interfering molecules and achieved stable detection across a range of concentrations in a commonly used sports drink matrix. Overall, the label-free FRET Dex detection system offers a simple, cost-effective, and highly sensitive approach for detecting Dex in diverse sample matrices. Its simplicity and effectiveness make it a promising tool for anti-doping efforts and other applications requiring rapid and accurate Dex detection.
{"title":"Label-Free and Ultra-Sensitive Detection of Dexamethasone Using a FRET Aptasensor Utilizing Cationic Conjugated Polymers","authors":"Yizhang Xue, Hangbing Liu, Ye Zhang, Weijun Yang, Huixin Li, Yuxuan Gong, Yubai Zhang, Bo Li, Chang Liu, Yi Li","doi":"10.3390/bios14080364","DOIUrl":"https://doi.org/10.3390/bios14080364","url":null,"abstract":"Dexamethasone (Dex) is a widely used glucocorticoid in medical practice, with applications ranging from allergies and inflammation to cerebral edema and shock. Despite its therapeutic benefits, Dex is classified as a prohibited substance for athletes due to its potential performance-enhancing effects. Consequently, there is a critical need for a convenient and rapid detection platform to enable prompt and accurate testing of this drug. In this study, we propose a label-free Förster Resonance Energy Transfer (FRET) aptasensor platform for Dex detection utilizing conjugated polymers (CPs), cationic conjugated polymers (CCPs), and gene finder probes (GFs). The system operates by exploiting the electrostatic interactions between positively charged CCPs and negatively charged DNA, facilitating sensitive and specific Dex detection. The label-free FRET aptasensor platform demonstrated robust performance in detecting Dex, exhibiting high selectivity and sensitivity. The system effectively distinguished Dex from interfering molecules and achieved stable detection across a range of concentrations in a commonly used sports drink matrix. Overall, the label-free FRET Dex detection system offers a simple, cost-effective, and highly sensitive approach for detecting Dex in diverse sample matrices. Its simplicity and effectiveness make it a promising tool for anti-doping efforts and other applications requiring rapid and accurate Dex detection.","PeriodicalId":100185,"journal":{"name":"Biosensors","volume":"351 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-07-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141774596","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Ke-Xin Jin, Jia Shen, Yi-Jing Wang, Yu Yang, Shuo-Hui Cao
Surface plasmon microscopy proves to be a potent tool for capturing interferometric scattering imaging data of individual particles at both micro and nanoscales, offering considerable potential for label-free analysis of bio-particles and bio-molecules such as exosomes, viruses, and bacteria. However, the manual analysis of acquired images remains a challenge, particularly when dealing with dense samples or strong background noise, common in practical measurements. Manual analysis is not only prone to errors but is also time-consuming, especially when handling a large volume of experimental images. Currently, automated methods for sensing and analysis of such data are lacking. In this paper, we develop an accelerated approach for surface plasmon microscopy imaging of individual particles based on combining the interference scattering model of single particle and deep learning processing. We create hybrid datasets by combining the theoretical simulation of particle images with the actual measurements. Subsequently, we construct a neural network utilizing the EfficientNet architecture. Our results demonstrate the effectiveness of this novel deep learning technique in classifying interferometric scattering images and identifying multiple particles under noisy conditions. This advancement paves the way for practical bio-applications through efficient automated particle analysis.
{"title":"Enhanced Nanoparticle Recognition via Deep Learning-Accelerated Plasmonic Sensing","authors":"Ke-Xin Jin, Jia Shen, Yi-Jing Wang, Yu Yang, Shuo-Hui Cao","doi":"10.3390/bios14080363","DOIUrl":"https://doi.org/10.3390/bios14080363","url":null,"abstract":"Surface plasmon microscopy proves to be a potent tool for capturing interferometric scattering imaging data of individual particles at both micro and nanoscales, offering considerable potential for label-free analysis of bio-particles and bio-molecules such as exosomes, viruses, and bacteria. However, the manual analysis of acquired images remains a challenge, particularly when dealing with dense samples or strong background noise, common in practical measurements. Manual analysis is not only prone to errors but is also time-consuming, especially when handling a large volume of experimental images. Currently, automated methods for sensing and analysis of such data are lacking. In this paper, we develop an accelerated approach for surface plasmon microscopy imaging of individual particles based on combining the interference scattering model of single particle and deep learning processing. We create hybrid datasets by combining the theoretical simulation of particle images with the actual measurements. Subsequently, we construct a neural network utilizing the EfficientNet architecture. Our results demonstrate the effectiveness of this novel deep learning technique in classifying interferometric scattering images and identifying multiple particles under noisy conditions. This advancement paves the way for practical bio-applications through efficient automated particle analysis.","PeriodicalId":100185,"journal":{"name":"Biosensors","volume":"67 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-07-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141774551","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Aritra Nath Chattopadhyay, Mingdi Jiang, Jessa Marie V. Makabenta, Jungmi Park, Yingying Geng, Vincent Rotello
Opportunistic bacterial pathogens can evade the immune response by residing and reproducing within host immune cells, including macrophages. These intracellular infections provide reservoirs for pathogens that enhance the progression of infections and inhibit therapeutic strategies. Current sensing strategies for intracellular infections generally use immunosensing of specific biomarkers on the cell surface or polymerase chain reaction (PCR) of the corresponding nucleic acids, making detection difficult, time-consuming, and challenging to generalize. Intracellular infections can induce changes in macrophage glycosylation, providing a potential strategy for signature-based detection of intracellular infections. We report here the detection of bacterial infection in macrophages using a boronic acid (BA)-based pH-responsive polymer sensor array engineered to distinguish mammalian cell phenotypes by their cell surface glycosylation signatures. The sensor was able to discriminate between different infecting bacteria in minutes, providing a promising tool for diagnostic and screening applications.
{"title":"Nanosensor-Enabled Detection and Identification of Intracellular Bacterial Infections in Macrophages","authors":"Aritra Nath Chattopadhyay, Mingdi Jiang, Jessa Marie V. Makabenta, Jungmi Park, Yingying Geng, Vincent Rotello","doi":"10.3390/bios14080360","DOIUrl":"https://doi.org/10.3390/bios14080360","url":null,"abstract":"Opportunistic bacterial pathogens can evade the immune response by residing and reproducing within host immune cells, including macrophages. These intracellular infections provide reservoirs for pathogens that enhance the progression of infections and inhibit therapeutic strategies. Current sensing strategies for intracellular infections generally use immunosensing of specific biomarkers on the cell surface or polymerase chain reaction (PCR) of the corresponding nucleic acids, making detection difficult, time-consuming, and challenging to generalize. Intracellular infections can induce changes in macrophage glycosylation, providing a potential strategy for signature-based detection of intracellular infections. We report here the detection of bacterial infection in macrophages using a boronic acid (BA)-based pH-responsive polymer sensor array engineered to distinguish mammalian cell phenotypes by their cell surface glycosylation signatures. The sensor was able to discriminate between different infecting bacteria in minutes, providing a promising tool for diagnostic and screening applications.","PeriodicalId":100185,"journal":{"name":"Biosensors","volume":"15 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-07-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141774598","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Wearable sensors are important components, converting mechanical vibration energy into electrical signals or other forms of output, which are widely used in healthcare, disaster warning, and transportation. However, the reliance on batteries limits the portability of wearable sensors and hinders their application in the field of Internet of Things. To solve this problem, we designed a miniaturized high-performance hybrid nanogenerator (MHP-HNG), which combined the functions of triboelectric sensing and electromagnetic power generation as well as the advantages of miniaturization. By optimizing the design of TENG and EMG, the wearable sensor achieved a voltage output of 14.14 V and a power output of 49 mW. Based on the wireless optical communication and wireless communication technologies, the wearable sensor achieved the integration of sensing, communication, and self-powered function, which is expected to realize health monitoring, emergency warning, and rehabilitation assistance, and further extend the potential application value in the medical field.
可穿戴传感器是将机械振动能量转换为电信号或其他形式输出的重要组件，广泛应用于医疗保健、灾难预警和交通领域。然而，对电池的依赖限制了可穿戴传感器的便携性，阻碍了它们在物联网领域的应用。为了解决这一问题，我们设计了一种小型化高性能混合纳米发电机（MHP-HNG），它结合了三电传感和电磁发电的功能以及小型化的优势。通过优化 TENG 和 EMG 的设计，该可穿戴传感器实现了 14.14 V 的电压输出和 49 mW 的功率输出。基于无线光通信和无线通信技术，该可穿戴传感器实现了传感、通信和自供电功能的一体化，有望实现健康监测、应急预警和康复辅助等功能，进一步拓展在医疗领域的潜在应用价值。
{"title":"Wearable Sensors Based on Miniaturized High-Performance Hybrid Nanogenerator for Medical Health Monitoring","authors":"Jinjing Wu, Xiaobo Lin, Chengkai Yang, Sirui Yang, Chenning Liu, Yuanyuan Cao","doi":"10.3390/bios14080361","DOIUrl":"https://doi.org/10.3390/bios14080361","url":null,"abstract":"Wearable sensors are important components, converting mechanical vibration energy into electrical signals or other forms of output, which are widely used in healthcare, disaster warning, and transportation. However, the reliance on batteries limits the portability of wearable sensors and hinders their application in the field of Internet of Things. To solve this problem, we designed a miniaturized high-performance hybrid nanogenerator (MHP-HNG), which combined the functions of triboelectric sensing and electromagnetic power generation as well as the advantages of miniaturization. By optimizing the design of TENG and EMG, the wearable sensor achieved a voltage output of 14.14 V and a power output of 49 mW. Based on the wireless optical communication and wireless communication technologies, the wearable sensor achieved the integration of sensing, communication, and self-powered function, which is expected to realize health monitoring, emergency warning, and rehabilitation assistance, and further extend the potential application value in the medical field.","PeriodicalId":100185,"journal":{"name":"Biosensors","volume":"57 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-07-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141774599","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Merel Oeyen, Clément J. F. Heymann, Maarten Jacquemyn, Dirk Daelemans, Dominique Schols
Orthoflaviviruses cause a major threat to global public health, and no antiviral treatment is available yet. Zika virus (ZIKV) entry, together with many other viruses, is known to be enhanced by phosphatidylserine (PS) receptors such as T-cell immunoglobulin mucin domain protein 1 (TIM-1). In this study, we demonstrate for the first time, using cell-based electrical impedance (CEI) biosensing, that ZIKV entry is also enhanced by expression of CD300a, another PS receptor. Furthermore, inhibiting CD300a in immature monocyte-derived dendritic cells partially but significantly inhibits ZIKV replication. As we have previously demonstrated that CEI is a useful tool to study Orthoflavivirus infection in real time, we now use this technology to determine how these PS receptors influence the kinetics of in vitro ZIKV infection. Results show that ZIKV entry is highly sensitive to minor changes in TIM-1 expression, both after overexpression of TIM-1 in infection-resistant HEK293T cells, as well as after partial knockout of TIM-1 in susceptible A549 cells. These results are confirmed by quantification of viral copy number and viral infectivity, demonstrating that CEI is highly suited to study and compare virus-host interactions. Overall, the results presented here demonstrate the potential of targeting this universal viral entry pathway.
{"title":"The Role of TIM-1 and CD300a in Zika Virus Infection Investigated with Cell-Based Electrical Impedance","authors":"Merel Oeyen, Clément J. F. Heymann, Maarten Jacquemyn, Dirk Daelemans, Dominique Schols","doi":"10.3390/bios14080362","DOIUrl":"https://doi.org/10.3390/bios14080362","url":null,"abstract":"Orthoflaviviruses cause a major threat to global public health, and no antiviral treatment is available yet. Zika virus (ZIKV) entry, together with many other viruses, is known to be enhanced by phosphatidylserine (PS) receptors such as T-cell immunoglobulin mucin domain protein 1 (TIM-1). In this study, we demonstrate for the first time, using cell-based electrical impedance (CEI) biosensing, that ZIKV entry is also enhanced by expression of CD300a, another PS receptor. Furthermore, inhibiting CD300a in immature monocyte-derived dendritic cells partially but significantly inhibits ZIKV replication. As we have previously demonstrated that CEI is a useful tool to study Orthoflavivirus infection in real time, we now use this technology to determine how these PS receptors influence the kinetics of in vitro ZIKV infection. Results show that ZIKV entry is highly sensitive to minor changes in TIM-1 expression, both after overexpression of TIM-1 in infection-resistant HEK293T cells, as well as after partial knockout of TIM-1 in susceptible A549 cells. These results are confirmed by quantification of viral copy number and viral infectivity, demonstrating that CEI is highly suited to study and compare virus-host interactions. Overall, the results presented here demonstrate the potential of targeting this universal viral entry pathway.","PeriodicalId":100185,"journal":{"name":"Biosensors","volume":"49 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-07-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141774600","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Far-red fluorescent proteins (FPs) have emerged as indispensable tools in in vivo imaging, playing a pivotal role in elucidating fundamental mechanisms and addressing application issues in biotechnology and biomedical fields. Their ability for deep penetration, coupled with reduced light scattering and absorption, robust resistance to autofluorescence, and diminished phototoxicity, has positioned far-red biosensors at the forefront of non-invasive visualization techniques for observing intracellular activities and intercellular behaviors. In this review, far-red FPs and their applications in living systems are mainly discussed. Firstly, various far-red FPs, characterized by emission peaks spanning from 600 nm to 650 nm, are introduced. This is followed by a detailed presentation of the fundamental principles enabling far-red biosensors to detect biomolecules and environmental changes. Furthermore, the review accentuates the superiority of far-red FPs in multi-color imaging. In addition, significant emphasis is placed on the value of far-red FPs in improving imaging resolution, highlighting their great contribution to the advancement of in vivo imaging.
{"title":"Far-Red Fluorescent Proteins: Tools for Advancing In Vivo Imaging","authors":"Angyang Shang, Shuai Shao, Luming Zhao, Bo Liu","doi":"10.3390/bios14080359","DOIUrl":"https://doi.org/10.3390/bios14080359","url":null,"abstract":"Far-red fluorescent proteins (FPs) have emerged as indispensable tools in in vivo imaging, playing a pivotal role in elucidating fundamental mechanisms and addressing application issues in biotechnology and biomedical fields. Their ability for deep penetration, coupled with reduced light scattering and absorption, robust resistance to autofluorescence, and diminished phototoxicity, has positioned far-red biosensors at the forefront of non-invasive visualization techniques for observing intracellular activities and intercellular behaviors. In this review, far-red FPs and their applications in living systems are mainly discussed. Firstly, various far-red FPs, characterized by emission peaks spanning from 600 nm to 650 nm, are introduced. This is followed by a detailed presentation of the fundamental principles enabling far-red biosensors to detect biomolecules and environmental changes. Furthermore, the review accentuates the superiority of far-red FPs in multi-color imaging. In addition, significant emphasis is placed on the value of far-red FPs in improving imaging resolution, highlighting their great contribution to the advancement of in vivo imaging.","PeriodicalId":100185,"journal":{"name":"Biosensors","volume":"40 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-07-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141774601","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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