CRISPR-Cas12a-driven MXene-PEDOT:PSS piezoresistive wireless biosensor

Nano Energy ◽  
2021 ◽  
Vol 82 ◽  
pp. 105711
Author(s):  
Ruijin Zeng ◽  
Weijun Wang ◽  
Mingming Chen ◽  
Qing Wan ◽  
Caicheng Wang ◽  
...  
Keyword(s):  
2008 ◽  
Vol 144 (1) ◽  
pp. 38-47 ◽  
Author(s):  
Michael L. Johnson ◽  
Jiehui Wan ◽  
Shichu Huang ◽  
Zhongyang Cheng ◽  
Valery A. Petrenko ◽  
...  
Keyword(s):  

2019 ◽  
Vol 130 ◽  
pp. 360-366 ◽  
Author(s):  
Haiyun Wu ◽  
Ryosuke Shinoda ◽  
Masataka Murata ◽  
Haruto Matsumoto ◽  
Hitoshi Ohnuki ◽  
...  

Sensors ◽  
2019 ◽  
Vol 19 (7) ◽  
pp. 1518 ◽  
Author(s):  
Haiyun Wu ◽  
Yuzu Fujii ◽  
Toshiki Nakano ◽  
Takafumi Arimoto ◽  
Masataka Murata ◽  
...  

Wireless biosensor systems were developed in our lab for monitoring blood glucose concentrations in fish as an indicator of fish stress. However, uniform immobilization of the enzyme on the surface of the electrode is difficult, so the sensor response is typically reduced at a range of high glucose concentrations during the stress monitoring. In this study, we attempted to enhance sensor response by using a self-assembled monolayer-immobilized enzyme. Glucose oxidase was immobilized on a working electrode modified with a self-assembled monolayer. The proposed biosensor showed a good correlation between the output current and the glucose concentration range of 10–3500 mg dL−1 under an optimized working condition. The dynamic measurement range of this newly developed sensor is significantly improved, especially over a high concentration range, which helps the sensor to achieve better performance in dramatic changes in the stress response of fish. In addition, we used biological samples from test fish and obtained a good correlation coefficient between the sensor output current and the glucose concentration using a conventional method. The proposed wireless biosensor system was also applied to monitor fish stress responses in real time through different stressors and to obtain some precise data that reflect real fish stress responses.


IEEE Network ◽  
2006 ◽  
Vol 20 (3) ◽  
pp. 6-11 ◽  
Author(s):  
Yihan Li ◽  
S.S. Panwar
Keyword(s):  

Sensors ◽  
2012 ◽  
Vol 12 (5) ◽  
pp. 6269-6281 ◽  
Author(s):  
Kyoko Hibi ◽  
Kengo Hatanaka ◽  
Mai Takase ◽  
Huifeng Ren ◽  
Hideaki Endo

2020 ◽  
Vol 158 (6) ◽  
pp. S-560-S-561
Author(s):  
Marvin Ryou ◽  
Christopher C. Thompson

2011 ◽  
Vol 74 (1) ◽  
pp. 189-194.e1 ◽  
Author(s):  
Marvin Ryou ◽  
Alex Nemiroski ◽  
Dan Azagury ◽  
Sohail N. Shaikh ◽  
Michele B. Ryan ◽  
...  

2020 ◽  
Author(s):  
Srinivasan Murali ◽  
Francisco Rincon ◽  
Tiziano Cassina ◽  
Stephane Cook ◽  
Jean-Jacques Goy

BACKGROUND Continuous cardiac monitoring with wireless sensors is an attractive option for early detection of arrhythmia and conduction disturbances and the prevention of adverse events leading to patient deterioration. We present a new sensor design (SmartCardia), a wearable wireless biosensor patch, for continuous cardiac and oxygen saturation (SpO<sub>2</sub>) monitoring. OBJECTIVE This study aimed to test the clinical value of a new wireless sensor device (SmartCardia) and its usefulness in monitoring the heart rate (HR) and SpO<sub>2</sub> of patients. METHODS We performed an observational study and monitored the HR and SpO<sub>2</sub> of patients admitted to the intensive care unit (ICU). We compared the device under test (SmartCardia) with the ICU-grade monitoring system (Dräger-Healthcare). We defined optimal correlation between the gold standard and the wireless system as &lt;10% difference for HR and &lt;4% difference for SpO<sub>2</sub>. Data loss and discrepancy between the two systems were critically analyzed. RESULTS A total of 58 ICU patients (42 men and 16 women), with a mean age of 71 years (SD 11), were included in this study. A total of 13.49 (SD 5.53) hours per patient were recorded. This represents a total recorded period of 782.3 hours. The mean difference between the HR detected by the SmartCardia patch and the ICU monitor was 5.87 (SD 16.01) beats per minute (bias=–5.66, SD 16.09). For SpO<sub>2</sub>, the average difference was 3.54% (SD 3.86; bias=2.9, SD 4.36) for interpretable values. SmartCardia’s patch measures SpO<sub>2</sub> only under low-to-no activity conditions and otherwise does not report a value. Data loss and noninterpretable values of SpO<sub>2</sub> represented 26% (SD 24) of total measurements. CONCLUSIONS The SmartCardia device demonstrated clinically acceptable accuracy for HR and SpO<sub>2</sub> monitoring in ICU patients.


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