Evidence map›Paper›PMID 28068315›Full record

ArticleNature methods2017

Hyperspectral phasor analysis enables multiplexed 5D in vivo imaging.

Francesco Cutrale, Vikas Trivedi, Le A Trinh, Chi-Li Chiu, John M Choi, Marcela S Artiga, Scott E Fraser

Abstract read
PubMed Publisher
In one paragraph

Article in Nature methods, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 86 papers.

0numbers the graph read from it
0cells of the map it votes in
86citing 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

86 citing papers in PubMed.

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26 more citing papers are in PubMed but not listed here.

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

7 authors.

Francesco CutraleTranslational Imaging Center, University of Southern California, Los Angeles, California, USA.
Vikas TrivediTranslational Imaging Center, University of Southern California, Los Angeles, California, USA.ORCID 0000-0003-0953-0553
Le A TrinhTranslational Imaging Center, University of Southern California, Los Angeles, California, USA.
Chi-Li ChiuLawrence J. Ellison Institute for Transformative Medicine, Center for Applied Molecular Medicine, University of Southern California, Los Angeles, California, USA.
John M ChoiTranslational Imaging Center, University of Southern California, Los Angeles, California, USA.
Marcela S ArtigaTranslational Imaging Center, University of Southern California, Los Angeles, California, USA.
Scott E FraserTranslational Imaging Center, University of Southern California, Los Angeles, California, USA.

Funding

Multiplex RNA imaging in single cells by superresolution microscopy& barcode FISHR01HD075605 · NICHD · CALIFORNIA INSTITUTE OF TECHNOLOGY · PI CAI, LONG, SOMLO, GEORGE NONE · 2012 to 2016
$4.1M
Positive Behavior Support and the Prevention of Adolescent ProblemsR01DA019037 · NIDA · UNIVERSITY OF OREGON · PI SPRAGUE, JEFFREY RICHARD · 2006 to 2010
$3.1M
NICHD NIH HHS R01 HD075605NIDA NIH HHS R01 DA019037
6 · The paper itself

Abstract

Time-lapse imaging of multiple labels is challenging for biological imaging as noise, photobleaching and phototoxicity compromise signal quality, while throughput can be limited by processing time. Here, we report software called Hyper-Spectral Phasors (HySP) for denoising and unmixing multiple spectrally overlapping fluorophores in a low signal-to-noise regime with fast analysis. We show that HySP enables unmixing of seven signals in time-lapse imaging of living zebrafish embryos.

Indexed as

SoftwareAnimalsAnimals, Genetically ModifiedColorEmbryo, NonmammalianFourier AnalysisGreen Fluorescent ProteinsImage Processing, Computer-AssistedTime-Lapse ImagingZebrafishGreen Fluorescent Proteins

Identifiers

PMID28068315

What OpenQuestion holds

Textmetadata
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.