Evidence map›Paper›PMID 31324741›Full record

ArticleProceedings of the National Academy of Sciences of the United States of America2019

Label-free chemical imaging flow cytometry by high-speed multicolor stimulated Raman scattering.

Yuta Suzuki, Koya Kobayashi, Yoshifumi Wakisaka, Dinghuan Deng, Shunji Tanaka, Chun-Jung Huang, Cheng Lei, Chia-Wei Sun, Hanqin Liu, Yasuhiro Fujiwaki and 24 more

Open access · bronzeAbstract read
In one paragraph

Article in Proceedings of the National Academy of Sciences of the United States of America, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 75 papers.

0numbers the graph read from it
0cells of the map it votes in
75citing papers in PubMed
26.3field-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

75 citing papers in PubMed, 205 citations in OpenAlex.

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  9. Live-cell omics with Raman spectroscopy.Microscopy (Oxford, England) · 2025
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  11. Article
  12. Article
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  14. Principle of Stimulated Raman Scattering Microscopy: Emerging at High Spatiotemporal Limits.The journal of physical chemistry. C, Nanomaterials and interfaces · 2025
    Article
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15 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

34 authors at 11 institutions in 4 countries.

Yuta SuzukiDepartment of Electrical Engineering and Information Systems, The University of Tokyo, 113-8656 Tokyo, Japan.
Koya KobayashiDepartment of Electrical Engineering and Information Systems, The University of Tokyo, 113-8656 Tokyo, Japan.
Yoshifumi WakisakaDepartment of Chemistry, The University of Tokyo, 113-0033 Tokyo, Japan.
Dinghuan DengDepartment of Electrical Engineering and Information Systems, The University of Tokyo, 113-8656 Tokyo, Japan.
Shunji TanakaDepartment of Electrical Engineering and Information Systems, The University of Tokyo, 113-8656 Tokyo, Japan.
Chun-Jung HuangDepartment of Photonics, National Chiao Tung University, 300 Hsinchu, Taiwan.
Cheng LeiDepartment of Chemistry, The University of Tokyo, 113-0033 Tokyo, Japan.
Chia-Wei SunDepartment of Photonics, National Chiao Tung University, 300 Hsinchu, Taiwan.
Hanqin LiuDepartment of Electrical Engineering and Information Systems, The University of Tokyo, 113-8656 Tokyo, Japan.
Yasuhiro FujiwakiDepartment of Electrical Engineering and Information Systems, The University of Tokyo, 113-8656 Tokyo, Japan.
Sangwook LeeDepartment of Chemistry, The University of Tokyo, 113-0033 Tokyo, Japan.
Akihiro IsozakiDepartment of Chemistry, The University of Tokyo, 113-0033 Tokyo, Japan.ORCID 0000-0003-0391-9832
Yusuke KasaiDepartment of Micro-Nano Mechanical Science and Engineering, Nagoya University, 464-8601 Nagoya, Japan.
Takeshi HayakawaDepartment of Precision Mechanics, Chuo University, 112-8551 Tokyo, Japan.
Shinya SakumaDepartment of Micro-Nano Mechanical Science and Engineering, Nagoya University, 464-8601 Nagoya, Japan.ORCID 0000-0002-4145-7264
Fumihito AraiDepartment of Micro-Nano Mechanical Science and Engineering, Nagoya University, 464-8601 Nagoya, Japan.
Kenichi KoizumiDepartment of Creative Informatics, The University of Tokyo, 113-0033 Tokyo, Japan.
Hiroshi TezukaDepartment of Creative Informatics, The University of Tokyo, 113-0033 Tokyo, Japan.
Mary InabaDepartment of Creative Informatics, The University of Tokyo, 113-0033 Tokyo, Japan.
Kei HirakiDepartment of Chemistry, The University of Tokyo, 113-0033 Tokyo, Japan.
Takuro ItoDepartment of Chemistry, The University of Tokyo, 113-0033 Tokyo, Japan.
Misa HaseDepartment of Chemistry, The University of Tokyo, 113-0033 Tokyo, Japan.
Satoshi MatsusakaDepartment of Gastroenterology, Cancer Institute Hospital, Japanese Foundation for Cancer Research, 135-8550 Tokyo, Japan.
Kiyotaka ShibaDivision of Protein Engineering, Cancer Institute, Japanese Foundation for Cancer Research, 135-8550 Tokyo, Japan.ORCID 0000-0001-6459-0204
Kanako SugaDivision of Protein Engineering, Cancer Institute, Japanese Foundation for Cancer Research, 135-8550 Tokyo, Japan.
Masako NishikawaDepartment of Clinical Laboratory Medicine, Graduate School of Medicine, The University of Tokyo, 113-0033 Tokyo, Japan.
Masahiro JonaDepartment of Clinical Laboratory Medicine, Graduate School of Medicine, The University of Tokyo, 113-0033 Tokyo, Japan.
Yutaka YatomiDepartment of Clinical Laboratory Medicine, Graduate School of Medicine, The University of Tokyo, 113-0033 Tokyo, Japan.
Yaxiaer YalikunCenter for Biosystems Dynamics Research, RIKEN, 565-0871 Osaka, Japan.
Yo TanakaCenter for Biosystems Dynamics Research, RIKEN, 565-0871 Osaka, Japan.ORCID 0000-0003-1034-5718
Takeaki SugimuraDepartment of Chemistry, The University of Tokyo, 113-0033 Tokyo, Japan.
Nao NittaDepartment of Chemistry, The University of Tokyo, 113-0033 Tokyo, Japan.
Keisuke GodaDepartment of Chemistry, The University of Tokyo, 113-0033 Tokyo, Japan.
Yasuyuki OzekiDepartment of Electrical Engineering and Information Systems, The University of Tokyo, 113-8656 Tokyo, Japan; ozeki@ee.t.u-tokyo.ac.jp.ORCID 0000-0002-9004-0799
The University of Tokyo · JPTokyo University of Information Sciences · JPJapan Science and Technology Agency · JPNagoya University · JPJapanese Foundation For Cancer Research · JPNational Yang Ming Chiao Tung University · TWRIKEN Center for Biosystems Dynamics Research · JPChuo University · JPUniversity of California, Los Angeles · USUniversity of Tsukuba · JPWuhan University · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Combining the strength of flow cytometry with fluorescence imaging and digital image analysis, imaging flow cytometry is a powerful tool in diverse fields including cancer biology, immunology, drug discovery, microbiology, and metabolic engineering. It enables measurements and statistical analyses of chemical, structural, and morphological phenotypes of numerous living cells to provide systematic insights into biological processes. However, its utility is constrained by its requirement of fluorescent labeling for phenotyping. Here we present label-free chemical imaging flow cytometry to overcome the issue. It builds on a pulse pair-resolved wavelength-switchable Stokes laser for the fastest-to-date multicolor stimulated Raman scattering (SRS) microscopy of fast-flowing cells on a 3D acoustic focusing microfluidic chip, enabling an unprecedented throughput of up to ∼140 cells/s. To show its broad utility, we use the SRS imaging flow cytometry with the aid of deep learning to study the metabolic heterogeneity of microalgal cells and perform marker-free cancer detection in blood.

Indexed as

Imaging, Three-DimensionalCell Line, TumorFlow CytometryHumansMicroalgaeSpectrum Analysis, RamanStaining and Labelingcancer cellsimaging flow cytometrymetabolite imagingmicroalgaestimulated Raman scattering

Identifiers

PMID31324741
PMCPMC6690022
OpenAlexW2963444747

What OpenQuestion holds

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LicenceCC BY-NC-ND
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.