Evidence map›Paper›PMID 26234416›Full record

ArticleScientific reports2015

Label-free single-cell protein quantification using a drop-based mix-and-read system.

Alireza Abbaspourrad, Huidan Zhang, Ye Tao, Naiwen Cui, Haruichi Asahara, Ying Zhou, Dongxian Yue, Stephan A Koehler, Lloyd W Ung, John Heyman and 4 more

Abstract read
In one paragraph

Article in Scientific reports, 2015. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 papers.

0numbers the graph read from it
0cells of the map it votes in
9citing 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

9 citing papers in PubMed.

  1. Single-molecule fluorescence methods for protein biomarker analysis.Analytical and bioanalytical chemistry · 2023
    Review
  2. Review
  3. Article
  4. Taking Systems Medicine to Heart.Circulation research · 2018
    Review
  5. Article
  6. Review
  7. Article
  8. Review
  9. Article
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.

Alireza AbbaspourradSchool of Engineering and Applied Sciences, Harvard University, Cambridge, MA 02138, USA.
Huidan Zhang1] School of Engineering and Applied Sciences, Harvard University, Cambridge, MA 02138, USA [2] Department of Cell Biology, Key Laboratory of Cell Biology, Ministry of Public Health, and Key Laboratory of Medical Cell Biology, Ministry of Education, China Medical University, Shenyang 110001, China.
Ye Tao1] School of Engineering and Applied Sciences, Harvard University, Cambridge, MA 02138, USA [2] School of Mechatronics Engineering, Harbin Institute of Technology, Harbin 150001, China.
Naiwen CuiSchool of Engineering and Applied Sciences, Harvard University, Cambridge, MA 02138, USA.
Haruichi AsaharaNew England Biolabs, Inc. 240 County Road, Ipswich, MA 01938, USA.
Ying ZhouNew England Biolabs, Inc. 240 County Road, Ipswich, MA 01938, USA.
Dongxian YueNew England Biolabs, Inc. 240 County Road, Ipswich, MA 01938, USA.
Stephan A Koehler1] School of Engineering and Applied Sciences, Harvard University, Cambridge, MA 02138, USA [2] Department of Physics, Harvard University, Cambridge, MA 02138, USA.
Lloyd W UngSchool of Engineering and Applied Sciences, Harvard University, Cambridge, MA 02138, USA.
John HeymanSchool of Engineering and Applied Sciences, Harvard University, Cambridge, MA 02138, USA.
Yukun RenSchool of Mechatronics Engineering, Harbin Institute of Technology, Harbin 150001, China.
Roy ZiblatSchool of Engineering and Applied Sciences, Harvard University, Cambridge, MA 02138, USA.
Shaorong ChongNew England Biolabs, Inc. 240 County Road, Ipswich, MA 01938, USA.
David A Weitz1] School of Engineering and Applied Sciences, Harvard University, Cambridge, MA 02138, USA [2] Department of Physics, Harvard University, Cambridge, MA 02138, USA.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Quantitative protein analysis of single cells is rarely achieved due to technical difficulties of detecting minute amounts of proteins present in one cell. We develop a mix-and-read assay for drop-based label-free protein analysis of single cells. This high-throughput method quantifies absolute, rather than relative, amounts of proteins and does not involve antibody labeling or mass spectrometry.

Identifiers

PMID26234416
PMCPMC4522677

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Registered trials

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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.