Evidence map›Paper›PMID 34035262›Full record

ArticleNature communications2021

Cellular lensing and near infrared fluorescent nanosensor arrays to enable chemical efflux cytometry.

Soo-Yeon Cho, Xun Gong, Volodymyr B Koman, Matthias Kuehne, Sun Jin Moon, Manki Son, Tedrick Thomas Salim Lew, Pavlo Gordiichuk, Xiaojia Jin, Hadley D Sikes and 1 more

Abstract read
In one paragraph

Article in Nature communications, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 10 papers.

0numbers the graph read from it
0cells of the map it votes in
10citing 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

10 citing papers in PubMed.

  1. Review
  2. Article
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  7. Review
  8. Article
  9. Review
  10. Lipid droplets as endogenous intracellular microlenses.Light, science & applications · 2021
    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

11 authors.

Soo-Yeon ChoDepartment of Chemical Engineering, Massachusetts Institute of Technology, Cambridge, MA, USA.ORCID 0000-0001-6294-1154
Xun GongDepartment of Chemical Engineering, Massachusetts Institute of Technology, Cambridge, MA, USA.
Volodymyr B KomanDepartment of Chemical Engineering, Massachusetts Institute of Technology, Cambridge, MA, USA.ORCID 0000-0001-8480-4003
Matthias KuehneDepartment of Chemical Engineering, Massachusetts Institute of Technology, Cambridge, MA, USA.ORCID 0000-0002-5096-7522
Sun Jin MoonDepartment of Chemical Engineering, Massachusetts Institute of Technology, Cambridge, MA, USA.
Manki SonDepartment of Chemical Engineering, Massachusetts Institute of Technology, Cambridge, MA, USA.
Tedrick Thomas Salim LewDepartment of Chemical Engineering, Massachusetts Institute of Technology, Cambridge, MA, USA.ORCID 0000-0002-4815-9921
Pavlo GordiichukDepartment of Chemical Engineering, Massachusetts Institute of Technology, Cambridge, MA, USA.
Xiaojia JinDepartment of Chemical Engineering, Massachusetts Institute of Technology, Cambridge, MA, USA.ORCID 0000-0002-0694-5799
Hadley D SikesDepartment of Chemical Engineering, Massachusetts Institute of Technology, Cambridge, MA, USA.ORCID 0000-0002-7096-138X
Michael S StranoDepartment of Chemical Engineering, Massachusetts Institute of Technology, Cambridge, MA, USA. strano@mit.edu.ORCID 0000-0003-2944-808X

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Nanosensors have proven to be powerful tools to monitor single cells, achieving spatiotemporal precision even at molecular level. However, there has not been way of extending this approach to statistically relevant numbers of living cells. Herein, we design and fabricate nanosensor array in microfluidics that addresses this limitation, creating a Nanosensor Chemical Cytometry (NCC). nIR fluorescent carbon nanotube array is integrated along microfluidic channel through which flowing cells is guided. We can utilize the flowing cell itself as highly informative Gaussian lenses projecting nIR profiles and extract rich information. This unique biophotonic waveguide allows for quantified cross-correlation of biomolecular information with various physical properties and creates label-free chemical cytometer for cellular heterogeneity measurement. As an example, the NCC can profile the immune heterogeneities of human monocyte populations at attomolar sensitivity in completely non-destructive and real-time manner with rate of ~600 cells/hr, highest range demonstrated to date for state-of-the-art chemical cytometry.

Indexed as

AlgorithmsBiological TransportBiosensing TechniquesB-LymphocytesCell LineFluorescent DyesHEK293 CellsHumansHuman Umbilical Vein Endothelial CellsHydrogen PeroxideMicrofluidicsNanotechnologyNanotubes, CarbonSpectrum Analysis, RamanU937 CellsFluorescent DyesHydrogen PeroxideNanotubes, Carbon

Identifiers

PMID34035262
PMCPMC8149711

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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.