Near-infrared hyperspectral microscopy of carbon nanotube photoluminescence enables 17-color imaging (Conference Presentation)

2016 ◽  
Author(s):  
Daniel A. Heller ◽  
Daniel Roxbury ◽  
Prakrit V. Jena ◽  
Ryan M. Williams ◽  
Balázs Enyedi ◽  
...  
Keyword(s):  
Carbon Nanotube ◽  
Near Infrared ◽  
Color Imaging

scholarly journals Spatiotemporal Intracellular Nitric Oxide Signaling Captured Using Internalized, Near-Infrared Fluorescent Carbon Nanotube Nanosensors

Nano Letters ◽  
2014 ◽  
Vol 14 (8) ◽  
pp. 4887-4894 ◽  
Author(s):  
Zachary W. Ulissi ◽  
Fatih Sen ◽  
Xun Gong ◽  
Selda Sen ◽  
Nicole Iverson ◽  
...  
Keyword(s):  
Nitric Oxide ◽  
Carbon Nanotube ◽  
Near Infrared ◽  
Nitric Oxide Signaling ◽  
Fluorescent Carbon

Single-Chirality Near-Infrared Carbon Nanotube Sub-Cellular Imaging and FRET Probes

Nano Letters ◽  
2021 ◽  
Author(s):  
Rachel Langenbacher ◽  
Januka Budhathoki-Uprety ◽  
Prakrit V. Jena ◽  
Daniel Roxbury ◽  
Jason Streit ◽  
...  
Keyword(s):  
Carbon Nanotube ◽  
Near Infrared ◽  
Cellular Imaging

scholarly journals Machine learning enables discovery of DNA-carbon nanotube sensors for serotonin

2021 ◽  
Author(s):  
Payam Kelich ◽  
Sanghwa Jeong ◽  
Nicole Navarro ◽  
Jaquesta Adams ◽  
Xiaoqi Sun ◽  
...  
Keyword(s):  
Machine Learning ◽  
Carbon Nanotube ◽  
Dna Sequences ◽  
Regression Models ◽  
Near Infrared ◽  
Optical Response ◽  
Support Vector ◽  
Single Walled Carbon Nanotube ◽  
Nir Fluorescence ◽  
Selective Evolution

AbstractDNA-wrapped single walled carbon nanotube (SWNT) conjugates have remarkable optical properties leading to their use in biosensing and imaging applications. A critical limitation in the development of DNA-SWNT sensors is the current inability to predict unique DNA sequences that confer a strong analyte-specific optical response to these sensors. Here, near-infrared (nIR) fluorescence response datasets for ~100 DNA-SWNT conjugates, narrowed down by a selective evolution protocol starting from a pool of ~1010 unique DNA-SWNT candidates, are used to train machine learning (ML) models to predict new unique DNA sequences with strong optical response to neurotransmitter serotonin. First, classifier models based on convolutional neural networks (CNN) are trained on sequence features to classify DNA ligands as either high response or low response to serotonin. Second, support vector machine (SVM) regression models are trained to predict relative optical response values for DNA sequences. Finally, we demonstrate with validation experiments that integrating the predictions of ensembles of the highest quality CNN classifiers and SVM regression models leads to the best predictions of both high and low response sequences. With our ML approaches, we discovered five new DNA-SWNT sensors with higher fluorescence intensity response to serotonin than obtained previously. Overall, the explored ML approaches introduce an important new tool to predict useful DNA sequences, which can be used for discovery of new DNA-based sensors and nanobiotechnologies.

scholarly journals Phenylboronic acid derivative-modified (6,5) single-wall carbon nanotube probes for detecting glucose and hydrogen peroxide

RSC Advances ◽  
2019 ◽  
Vol 9 (4) ◽  
pp. 2258-2267 ◽  
Author(s):  
Yunfan Qiao ◽  
Rushi Zhao ◽  
Min Zhang ◽  
Hongyang Zhang ◽  
Yuerong Wang ◽  
...  
Keyword(s):  
Hydrogen Peroxide ◽  
Carbon Nanotube ◽  
Acid Derivative ◽  
Near Infrared ◽  
Phenylboronic Acid ◽  
New Method ◽  
Fluorescence Probes ◽  
Single Wall Carbon Nanotube ◽  
Near Infrared Fluorescence ◽  
Single Wall Carbon

In this paper, we presented a new method for constructing near-infrared fluorescence probes and their applications in detecting glucose and hydrogen peroxide (H2O2).

A Luciferase/Single-Walled Carbon Nanotube Conjugate for Near-Infrared Fluorescent Detection of Cellular ATP

2010 ◽  
Vol 122 (8) ◽  
pp. 1498-1501 ◽  
Author(s):  
Jong-Ho Kim ◽  
Jin-Ho Ahn ◽  
Paul W. Barone ◽  
Hong Jin ◽  
Jingqing Zhang ◽  
...  
Keyword(s):  
Carbon Nanotube ◽  
Near Infrared ◽  
Fluorescent Detection ◽  
Single Walled Carbon Nanotube ◽  
Single Walled Carbon
Sign in / Sign up

Export Citation Format

Share Document