Evidence map›Paper›PMID 36658278›Full record

ArticleNature methods2023

HyU: Hybrid Unmixing for longitudinal in vivo imaging of low signal-to-noise fluorescence.

Hsiao Ju Chiang, Daniel E S Koo, Masahiro Kitano, Sean Burkitt, Jay R Unruh, Cristina Zavaleta, Le A Trinh, Scott E Fraser, Francesco Cutrale

Abstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in Nature methods, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 16 papers.

0numbers the graph read from it
0cells of the map it votes in
16citing 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

16 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

9 authors.

Hsiao Ju Chiang *Translational Imaging Center, University of Southern California, Los Angeles, CA, USA.
Daniel E S Koo *Translational Imaging Center, University of Southern California, Los Angeles, CA, USA.
Masahiro KitanoTranslational Imaging Center, University of Southern California, Los Angeles, CA, USA.
Sean BurkittDepartment of Biomedical Engineering, University of Southern California, Los Angeles, CA, USA.ORCID http://orcid.org/0000-0002-3896-4089
Jay R UnruhStowers Institute for Medical Research, Kansas City, MO, USA.
Cristina ZavaletaDepartment of Biomedical Engineering, University of Southern California, Los Angeles, CA, USA.
Le A TrinhTranslational Imaging Center, University of Southern California, Los Angeles, CA, USA.
Scott E FraserTranslational Imaging Center, University of Southern California, Los Angeles, CA, USA.
Francesco CutraleTranslational Imaging Center, University of Southern California, Los Angeles, CA, USA. cutrale@usc.edu.ORCID http://orcid.org/0000-0003-0517-3069

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The expansion of fluorescence bioimaging toward more complex systems and geometries requires analytical tools capable of spanning widely varying timescales and length scales, cleanly separating multiple fluorescent labels and distinguishing these labels from background autofluorescence. Here we meet these challenging objectives for multispectral fluorescence microscopy, combining hyperspectral phasors and linear unmixing to create Hybrid Unmixing (HyU). HyU is efficient and robust, capable of quantitative signal separation even at low illumination levels. In dynamic imaging of developing zebrafish embryos and in mouse tissue, HyU was able to cleanly and efficiently unmix multiple fluorescent labels, even in demanding volumetric timelapse imaging settings. HyU permits high dynamic range imaging, allowing simultaneous imaging of bright exogenous labels and dim endogenous labels. This enables coincident studies of tagged components, cellular behaviors and cellular metabolism within the same specimen, providing more accurate insights into the orchestrated complexity of biological systems.

Indexed as

ZebrafishAnimalsMiceMicroscopy, Fluorescence

Identifiers

PMID36658278
PMCPMC9911352

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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.