Subcellular and in-vivo Nano-Endoscopy View Full Text


Ontology type: schema:ScholarlyArticle      Open Access: True


Article Info

DATE

2016-12

AUTHORS

Surya Venkatasekhar Cheemalapati, John Winskas, Hao Wang, Karthik Konnaiyan, Arseny Zhdanov, Alison Roth, Swamy Rakesh Adapa, Andrew Deonarine, Mark Noble, Tuhin Das, Robert Gatenby, Sandy D Westerheide, Rays H Y Jiang, Anna Pyayt

ABSTRACT

Analysis of individual cells at the subcellular level is important for understanding diseases and accelerating drug discovery. Nanoscale endoscopes allow minimally invasive probing of individual cell interiors. Several such instruments have been presented previously, but they are either too complex to fabricate or require sophisticated external detectors because of low signal collection efficiency. Here we present a nanoendoscope that can locally excite fluorescence in labelled cell organelles and collect the emitted signal for spectral analysis. Finite Difference Time Domain (FDTD) simulations have shown that with an optimized nanoendoscope taper profile, the light emission and collection was localized within ~100 nm. This allows signal detection to be used for nano-photonic sensing of the proximity of fluorophores. Upon insertion into the individual organelles of living cells, the nanoendoscope was fabricated and resultant fluorescent signals collected. This included the signal collection from the nucleus of Acridine orange labelled human fibroblast cells, the nucleus of Hoechst stained live liver cells and the mitochondria of MitoTracker Red labelled MDA-MB-231 cells. The endoscope was also inserted into a live organism, the yellow fluorescent protein producing nematode Caenorhabditis elegans, and a fluorescent signal was collected. To our knowledge this is the first demonstration of in vivo, local fluorescence signal collection on the sub-organelle level. More... »

PAGES

34400

Identifiers

URI

http://scigraph.springernature.com/pub.10.1038/srep34400

DOI

http://dx.doi.org/10.1038/srep34400

DIMENSIONS

https://app.dimensions.ai/details/publication/pub.1015903987

PUBMED

https://www.ncbi.nlm.nih.gov/pubmed/27694854


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Download the RDF metadata as:  json-ld nt turtle xml License info

HOW TO GET THIS DATA PROGRAMMATICALLY:

JSON-LD is a popular format for linked data which is fully compatible with JSON.

curl -H 'Accept: application/ld+json' 'https://scigraph.springernature.com/pub.10.1038/srep34400'

N-Triples is a line-based linked data format ideal for batch operations.

curl -H 'Accept: application/n-triples' 'https://scigraph.springernature.com/pub.10.1038/srep34400'

Turtle is a human-readable linked data format.

curl -H 'Accept: text/turtle' 'https://scigraph.springernature.com/pub.10.1038/srep34400'

RDF/XML is a standard XML format for linked data.

curl -H 'Accept: application/rdf+xml' 'https://scigraph.springernature.com/pub.10.1038/srep34400'


 

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304 schema:name Department of Global Health, College of Public Health, University of South Florida, Tampa, FL 33647, USA.
305 IBIS Lab, Department of Chemical and Biomedical Engineering, University of South Florida, Tampa, FL 33647, USA.
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309 schema:name Departments of Radiology and Integrated Mathematical Oncology, Moffitt Cancer Center, Tampa FL 33612, USA.
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