Evidence map›Paper›PMID 30536717›Full record

ArticleCytometry. Part A : the journal of the International Society for Analytical Cytology2019

Label-Free Metabolic Classification of Single Cells in Droplets Using the Phasor Approach to Fluorescence Lifetime Imaging Microscopy.

Ning Ma, Gopakumar Kamalakshakurup, Mohammad Aghaamoo, Abraham P Lee, Michelle A Digman

Abstract read
In one paragraph

Article in Cytometry. Part A : the journal of the International Society for Analytical Cytology, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.

0numbers the graph read from it
0cells of the map it votes in
6citing 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

6 citing papers in PubMed.

  1. Review
  2. Article
  3. Review
  4. Droplets microfluidics platform-A tool for single cell research.Frontiers in bioengineering and biotechnology · 2023
    Review
  5. Article
  6. Review
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

5 authors.

Ning MaBiomedical Engineering Department, University of California, Irvine, California.
Gopakumar KamalakshakurupBiomedical Engineering Department, University of California, Irvine, California.
Mohammad AghaamooBiomedical Engineering Department, University of California, Irvine, California.
Abraham P LeeBiomedical Engineering Department, University of California, Irvine, California.
Michelle A DigmanBiomedical Engineering Department, University of California, Irvine, California.

Funding

University of California Health Participation in the National COVID Cohort Collaborative (N3C)UL1TR001414 · NCATS · UNIVERSITY OF CALIFORNIA-IRVINE · PI COOPER, DAN M, VILAIN, ERIC J. · 2015 to 2023
$35.1M
TRD4: Phasor analysisP41GM103540 · NIGMS · UNIVERSITY OF CALIFORNIA-IRVINE · PI GRATTON, ENRICO · 2012 to 2020
$12.5M
NCATS NIH HHS UL1 TR001414NIGMS NIH HHS P41 GM103540
6 · The paper itself

Abstract

Characterization of single cell metabolism is imperative for understanding subcellular functional and biochemical changes associated with healthy tissue development and the progression of numerous diseases. However, single-cell analysis often requires the use of fluorescent tags and cell lysis followed by genomic profiling to identify the cellular heterogeneity. Identifying individual cells in a noninvasive and label-free manner is crucial for the detection of energy metabolism which will discriminate cell types and most importantly critical for maintaining cell viability for further analysis. Here, we have developed a robust assay using the droplet microfluidic technology together with the phasor approach to fluorescence lifetime imaging microscopy to study cell heterogeneity within and among the leukemia cell lines (K-562 and Jurkat). We have extended these techniques to characterize metabolic differences between proliferating and quiescent cells-a critical step toward label-free single cancer cell dormancy research. The result suggests a droplet-based noninvasive and label-free method to distinguish individual cells based on their metabolic states, which could be used as an upstream phenotypic platform to correlate with genomic statistics. © 2018 International Society for Advancement of Cytometry.

Indexed as

Cell EncapsulationFibroblastsFluorescenceHumansJurkat CellsK562 CellsLeukemiaMicrofluidicsMicroscopy, FluorescenceNADNeoplastic Cells, CirculatingSingle-Cell AnalysisNADcirculating tumor cellsdroplet microfluidicsfluorescence lifetime imaging microscopymetabolismphasor analysisquiescent stagesingle cell analysis

Identifiers

PMID30536717
PMCPMC6613543

What OpenQuestion holds

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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.