Evidence map›Paper›PMID 28867926›Full record

ArticleJournal of the Society for Information Display2017

Quantum dot light emitting devices for photomedical applications.

Hao Chen, Juan He, Raymond Lanzafame, Istvan Stadler, Hamid El Hamidi, Hui Liu, Jonathan Celli, Michael R Hamblin, Yingying Huang, Emily Oakley and 4 more

Abstract read
In one paragraph

Article in Journal of the Society for Information Display, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 11 papers.

0numbers the graph read from it
0cells of the map it votes in
11citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

11 citing papers in PubMed.

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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

14 authors.

Hao ChenCollege of Optics and Photonics, University of Central Florida, Orlando, FL, USA., Nanoscience Technology Center, University of Central Florida, Orlando, FL, USA.
Juan HeCollege of Optics and Photonics, University of Central Florida, Orlando, FL, USA.
Raymond LanzafameRaymond J Lanzafame MD PLLC, Rochester, NY, USA., Laser Surgical Research Laboratory, Rochester General Hospital, Rochester, NY, USA.
Istvan StadlerLaser Surgical Research Laboratory, Rochester General Hospital, Rochester, NY, USA.
Hamid El HamidiDepartment of Physics, University of Massachusetts Boston, Boston, MA, USA.
Hui LiuDepartment of Physics, University of Massachusetts Boston, Boston, MA, USA.
Jonathan CelliDepartment of Physics, University of Massachusetts Boston, Boston, MA, USA.
Michael R HamblinHarvard Medical School, Wellman Center for Photomedicine, Boston, MA, USA.
Yingying HuangHarvard Medical School, Wellman Center for Photomedicine, Boston, MA, USA.
Emily OakleyRoswell Park Cancer Institute, Photodynamic Therapy Center, Buffalo, NY, USA.
Gal ShafirsteinRoswell Park Cancer Institute, Photodynamic Therapy Center, Buffalo, NY, USA.
Ho-Kyoon ChungITRC AMOLED Research Center, Sungkyunkwan University, Korea.
Shin-Tson WuCollege of Optics and Photonics, University of Central Florida, Orlando, FL, USA.
Yajie DongCollege of Optics and Photonics, University of Central Florida, Orlando, FL, USA., Nanoscience Technology Center, University of Central Florida, Orlando, FL, USA; Department of Materials Science and Engineering, University of Central Florida, Orlando, FL, USA.

Funding

Photodynamic Therapy of Localized InfectionsR01AI050875 · NIAID · MASSACHUSETTS GENERAL HOSPITAL · PI HAMBLIN, MICHAEL R · 2003 to 2017
$4.8M
Integrated Image-guided Dosimetry & Treatment Planning PDTR01CA193610 · NCI · ROSWELL PARK CANCER INSTITUTE CORP · PI SHAFIRSTEIN, GAL · 2016 to 2020
$2.5M
Low-cost Enabling Technology for Image-guided Photodynamic Therapy (PDT) of OralUH2CA189901 · NCI · MASSACHUSETTS GENERAL HOSPITAL · PI CELLI, JONATHAN P, HASAN, TAYYABA · 2014 to 2015
$995k
Mechanism-based therapies for pancreatic cancer informed by stromal microrheologyR00CA155045 · NCI · UNIVERSITY OF MASSACHUSETTS BOSTON · PI CELLI, JONATHAN P · 2013 to 2015
$708k
Synergistic Photodynamic Therapy for Catherer-Associated Urinary Tract InfectionsR21AI121700 · NIAID · MASSACHUSETTS GENERAL HOSPITAL · PI HAMBLIN, MICHAEL R · 2016 to 2017
$462k
NCI NIH HHS R00 CA155045NCI NIH HHS R01 CA193610NCI NIH HHS UH2 CA189901NIAID NIH HHS R01 AI050875NIAID NIH HHS R21 AI121700
6 · The paper itself

Abstract

While OLEDs have struggled to find a niche lighting application that can fully take advantage of their unique form factors as thin, flexible, lightweight and uniformly large-area luminaire, photomedical researchers have been in search of low-cost, effective illumination devices with such form factors that could facilitate widespread clinical applications of photodynamic therapy (PDT) or photobiomodulation (PBM). Although existing OLEDs with either fluorescent or phosphorescent emitters cannot achieve the required high power density at the right wavelength windows for photomedicine, the recently developed ultrabright and efficient deep red quantum dot light emitting devices (QLEDs) can nicely fit into this niche. Here, we report for the first time the in-vitro study to demonstrate that this QLED-based photomedical approach could increase cell metabolism over control systems for PBM and kill cancerous cells efficiently for PDT. The perspective of developing wavelength-specific, flexible QLEDs for two critical photomedical fields (wound repair and cancer treatment) will be presented with their potential impacts summarized. The work promises to generate flexible QLED-based light sources that could enable the widespread use and clinical acceptance of photomedical strategies including PDT and PBM.

Indexed as

photobiomodulationphotodynamic therapyphotomedicinequantum dot light emitting devices (QLEDs)

Identifiers

PMID28867926
PMCPMC5576728

What OpenQuestion holds

Textmetadata
LicenceTDM
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.