Evidence map›Paper›PMID 23592185›Full record

ReviewLab on a chip2013

Toward giga-pixel nanoscopy on a chip: a computational wide-field look at the nano-scale without the use of lenses.

Euan McLeod, Wei Luo, Onur Mudanyali, Alon Greenbaum, Aydogan Ozcan

Open access · greenAbstract readReview
In one paragraph

Review in Lab on a chip, 2013. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 17 papers.

0numbers the graph read from it
0cells of the map it votes in
17citing papers in PubMed
7.8field-weighted citation impact, top 2% 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

17 citing papers in PubMed, 55 citations in OpenAlex.

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  14. 0.5 gigapixel microscopy using a flatbed scanner.Biomedical optics express · 2013
    Article
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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

5 authors at 2 institutions in 1 country.

Euan McLeodElectrical Engineering Department, University of California, Los Angeles, CA 90095, USA.
Wei Luo
Onur Mudanyali
Alon Greenbaum
Aydogan Ozcan
University of California, Los Angeles · USCalifornia NanoSystems Institute · US

Funding

Towards Mega-Throughput, Label-free Genomics and Proteomics: Revolutionizing MicrDP2OD006427 · OD · UNIVERSITY OF CALIFORNIA LOS ANGELES · PI OZCAN, AYDOGAN · 2009 to 2009
$2.3M
NIH HHS DP2 OD006427NIH HHS DP2OD006427
6 · The paper itself

Abstract

The development of lensfree on-chip microscopy in the past decade has opened up various new possibilities for biomedical imaging across ultra-large fields of view using compact, portable, and cost-effective devices. However, until recently, its ability to resolve fine features and detect ultra-small particles has not rivalled the capabilities of the more expensive and bulky laboratory-grade optical microscopes. In this Frontier Review, we highlight the developments over the last two years that have enabled computational lensfree holographic on-chip microscopy to compete with and, in some cases, surpass conventional bright-field microscopy in its ability to image nano-scale objects across large fields of view, yielding giga-pixel phase and amplitude images. Lensfree microscopy has now achieved a numerical aperture as high as 0.92, with a spatial resolution as small as 225 nm across a large field of view e.g., >20 mm(2). Furthermore, the combination of lensfree microscopy with self-assembled nanolenses, forming nano-catenoid minimal surfaces around individual nanoparticles has boosted the image contrast to levels high enough to permit bright-field imaging of individual particles smaller than 100 nm. These capabilities support a number of new applications, including, for example, the detection and sizing of individual virus particles using field-portable computational on-chip microscopes.

Indexed as

Lab-On-A-Chip DevicesMicroscopyNanotechnology

Identifiers

PMID23592185
PMCPMC3813829
OpenAlexW2088920577

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.