Evidence map›Paper›PMID 28276489›Full record

ArticleScientific reports2017

Computational On-Chip Imaging of Nanoparticles and Biomolecules using Ultraviolet Light.

Mustafa Ugur Daloglu, Aniruddha Ray, Zoltan Gorocs, Matthew Xiong, Ravinder Malik, Gal Bitan, Euan McLeod, Aydogan Ozcan

Open access · goldAbstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in Scientific reports, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.

0numbers the graph read from it
0cells of the map it votes in
7citing papers in PubMed
3.1field-weighted citation impact, top 9% of its field
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

7 citing papers in PubMed, 19 citations in OpenAlex.

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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

8 authors at 3 institutions in 1 country.

Mustafa Ugur DalogluElectrical Engineering Department, University of California, Los Angeles, CA, 90095, USA.
Aniruddha RayElectrical Engineering Department, University of California, Los Angeles, CA, 90095, USA.
Zoltan GorocsElectrical Engineering Department, University of California, Los Angeles, CA, 90095, USA.
Matthew XiongElectrical Engineering Department, University of California, Los Angeles, CA, 90095, USA.
Ravinder MalikDepartment of Neurology, David Geffen School of Medicine, University of California, Los Angeles, CA, 90095, USA.
Gal BitanDepartment of Neurology, David Geffen School of Medicine, University of California, Los Angeles, CA, 90095, USA.
Euan McLeodCollege of Optical Sciences, University of Arizona, Tucson, AZ 85721, USA.
Aydogan OzcanElectrical Engineering Department, University of California, Los Angeles, CA, 90095, USA.
University of California, Los Angeles · USCalifornia NanoSystems Institute · USUniversity of Arizona · US

Funding

Howard Hughes Medical Institute
6 · The paper itself

Abstract

Significant progress in characterization of nanoparticles and biomolecules was enabled by the development of advanced imaging equipment with extreme spatial-resolution and sensitivity. To perform some of these analyses outside of well-resourced laboratories, it is necessary to create robust and cost-effective alternatives to existing high-end laboratory-bound imaging and sensing equipment. Towards this aim, we have designed a holographic on-chip microscope operating at an ultraviolet illumination wavelength (UV) of 266 nm. The increased forward scattering from nanoscale objects at this short wavelength has enabled us to detect individual sub-30 nm nanoparticles over a large field-of-view of >16 mm

Indexed as

Amyotrophic Lateral SclerosisLab-On-A-Chip DevicesNanoparticlesSuperoxide DismutaseHumansMicroscopy, UltravioletMolecular ImagingSuperoxide Dismutase

Identifiers

PMID28276489
PMCPMC5343455
OpenAlexW2591652477

What OpenQuestion holds

Textmetadata
LicenceCC BY
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.