Evidence map›Paper›PMID 36451849›Full record

ArticleNature photonics2022

Stain-free identification of cell nuclei using tomographic phase microscopy in flow cytometry.

Daniele Pirone, Joowon Lim, Francesco Merola, Lisa Miccio, Martina Mugnano, Vittorio Bianco, Flora Cimmino, Feliciano Visconte, Annalaura Montella, Mario Capasso and 4 more

Open access · hybridAbstract read
In one paragraph

Article in Nature photonics, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 32 papers.

0numbers the graph read from it
0cells of the map it votes in
32citing papers in PubMed
15.7field-weighted citation impact, top 1% 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

32 citing papers in PubMed, 116 citations in OpenAlex.

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  16. Three-dimensional isotropic imaging of live suspension cells enabled by droplet microvortices.Proceedings of the National Academy of Sciences of the United States of America · 2024
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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 at 4 institutions in 2 countries.

Daniele PironeCNR-ISASI, Institute of Applied Sciences and Intelligent Systems "E. Caianiello", Via Campi Flegrei 34, 80078 Pozzuoli, Napoli, Italy.
Joowon LimEPFL, Ecole Polytechnique Fédérale de Lausanne, Optics Laboratory, CH-1015 Lausanne, Switzerland.
Francesco MerolaCNR-ISASI, Institute of Applied Sciences and Intelligent Systems "E. Caianiello", Via Campi Flegrei 34, 80078 Pozzuoli, Napoli, Italy.
Lisa MiccioCNR-ISASI, Institute of Applied Sciences and Intelligent Systems "E. Caianiello", Via Campi Flegrei 34, 80078 Pozzuoli, Napoli, Italy.
Martina MugnanoCNR-ISASI, Institute of Applied Sciences and Intelligent Systems "E. Caianiello", Via Campi Flegrei 34, 80078 Pozzuoli, Napoli, Italy.
Vittorio BiancoCNR-ISASI, Institute of Applied Sciences and Intelligent Systems "E. Caianiello", Via Campi Flegrei 34, 80078 Pozzuoli, Napoli, Italy.
Flora CimminoCEINGE - Advanced Biotechnologies, Via Gaetano Salvatore 486, 80131 Napoli, Italy.
Feliciano VisconteCEINGE - Advanced Biotechnologies, Via Gaetano Salvatore 486, 80131 Napoli, Italy.
Annalaura MontellaCEINGE - Advanced Biotechnologies, Via Gaetano Salvatore 486, 80131 Napoli, Italy.
Mario CapassoCEINGE - Advanced Biotechnologies, Via Gaetano Salvatore 486, 80131 Napoli, Italy.
Achille IolasconCEINGE - Advanced Biotechnologies, Via Gaetano Salvatore 486, 80131 Napoli, Italy.
Pasquale MemmoloCNR-ISASI, Institute of Applied Sciences and Intelligent Systems "E. Caianiello", Via Campi Flegrei 34, 80078 Pozzuoli, Napoli, Italy.
Demetri PsaltisEPFL, Ecole Polytechnique Fédérale de Lausanne, Optics Laboratory, CH-1015 Lausanne, Switzerland.
Pietro FerraroCNR-ISASI, Institute of Applied Sciences and Intelligent Systems "E. Caianiello", Via Campi Flegrei 34, 80078 Pozzuoli, Napoli, Italy.
Institute of Applied Science and Intelligent Systems · ITFederico II University Hospital · ITCeinge Biotecnologie Avanzate (Italy) · ITÉcole Polytechnique Fédérale de Lausanne · CH

Funding

Swiss National Science Foundation 188419
6 · The paper itself

Abstract

Quantitative Phase Imaging (QPI) has gained popularity in bioimaging because it can avoid the need for cell staining, which in some cases is difficult or impossible. However, as a result, QPI does not provide labelling of various specific intracellular structures. Here we show a novel computational segmentation method based on statistical inference that makes it possible for QPI techniques to identify the cell nucleus. We demonstrate the approach with refractive index tomograms of stain-free cells reconstructed through the tomographic phase microscopy in flow cytometry mode. In particular, by means of numerical simulations and two cancer cell lines, we demonstrate that the nucleus can be accurately distinguished within the stain-free tomograms. We show that our experimental results are consistent with confocal fluorescence microscopy (FM) data and microfluidic cytofluorimeter outputs. This is a significant step towards extracting specific three-dimensional intracellular structures directly from the phase-contrast data in a typical flow cytometry configuration.

Identifiers

PMID36451849
PMCPMC7613862
OpenAlexW4308885319

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.