scholarly journals Multilayered semiconducting polymer nanoparticles with enhanced NIR fluorescence for molecular imaging in cells, zebrafish and mice

2016 ◽  
Vol 7 (8) ◽  
pp. 5118-5125 ◽  
Author(s):  
Houjuan Zhu ◽  
Yuan Fang ◽  
Xu Zhen ◽  
Na Wei ◽  
Yu Gao ◽  
...  

Multilayered semiconducting polymer nanoparticles are developed forin vivoimaging of lymph nodes and tumors with a high signal-to-noise ratio.

2013 ◽  
Vol 4 (10) ◽  
pp. 2095 ◽  
Author(s):  
Claudio Vinegoni ◽  
Sungon Lee ◽  
Paolo Fumene Feruglio ◽  
Pasquina Marzola ◽  
Matthias Nahrendorf ◽  
...  

2021 ◽  
Vol 15 ◽  
Author(s):  
Thanet Pakpuwadon ◽  
Kiyotaka Sasagawa ◽  
Mark Christian Guinto ◽  
Yasumi Ohta ◽  
Makito Haruta ◽  
...  

In this study, we propose a complementary-metal-oxide-semiconductor (CMOS) image sensor with a self-resetting system demonstrating a high signal-to-noise ratio (SNR) to detect small intrinsic signals such as a hemodynamic reaction or neural activity in a mouse brain. The photodiode structure was modified from N-well/P-sub to P+/N-well/P-sub to increase the photodiode capacitance to reduce the number of self-resets required to decrease the unstable stage. Moreover, our new relay board was used for the first time. As a result, an effective SNR of over 70 dB was achieved within the same pixel size and fill factor. The unstable state was drastically reduced. Thus, we will be able to detect neural activity. With its compact size, this device has significant potential to become an intrinsic signal detector in freely moving animals. We also demonstrated in vivo imaging with image processing by removing additional noise from the self-reset operation.


RSC Advances ◽  
2019 ◽  
Vol 9 (71) ◽  
pp. 41431-41437 ◽  
Author(s):  
Shaolong Qi ◽  
Lubao Zhu ◽  
Xinyu Wang ◽  
Jianshi Du ◽  
Qingbiao Yang ◽  
...  

Near-infrared (NIR) fluorescent probes are widely employed in biological detection because of their lower damage to biological samples, low background interference, and high signal-to-noise ratio.


2021 ◽  
pp. 019459982110492
Author(s):  
Allan M. Henslee ◽  
Christopher R. Kaufmann ◽  
Matt D. Andrick ◽  
Parker T. Reineke ◽  
Viral D. Tejani ◽  
...  

Objective Electrocochleography (ECochG) is increasingly being used during cochlear implant (CI) surgery to detect and mitigate insertion-related intracochlear trauma, where a drop in ECochG signal has been shown to correlate with a decline in hearing outcomes. In this study, an ECochG-guided robotics-assisted CI insertion system was developed and characterized that provides controlled and consistent electrode array insertions while monitoring and adapting to real-time ECochG signals. Study Design Experimental research. Setting A research laboratory and animal testing facility. Methods A proof-of-concept benchtop study evaluated the ability of the system to detect simulated ECochG signal changes and robotically adapt the insertion. Additionally, the ECochG-guided insertion system was evaluated in a pilot in vivo sheep study to characterize the signal-to-noise ratio and amplitude of ECochG recordings during robotics-assisted insertions. The system comprises an electrode array insertion drive unit, an extracochlear recording electrode module, and a control console that interfaces with both components and the surgeon. Results The system exhibited a microvolt signal resolution and a response time <100 milliseconds after signal change detection, indicating that the system can detect changes and respond faster than a human. Additionally, animal results demonstrated that the system was capable of recording ECochG signals with a high signal-to-noise ratio and sufficient amplitude. Conclusion An ECochG-guided robotics-assisted CI insertion system can detect real-time drops in ECochG signals during electrode array insertions and immediately alter the insertion motion. The system may provide a surgeon the means to monitor and reduce CI insertion–related trauma beyond manual insertion techniques for improved CI hearing outcomes.


2014 ◽  
Vol 3 (8) ◽  
pp. 1292-1298 ◽  
Author(s):  
Kanyi Pu ◽  
Adam J. Shuhendler ◽  
Maija P. Valta ◽  
Lina Cui ◽  
Matthias Saar ◽  
...  

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