Evidence map›Paper›PMID 31057860›Full record

ArticleMicrosystems & nanoengineering2017

High-throughput physical phenotyping of cell differentiation.

Jonathan Lin, Donghyuk Kim, Henry T Tse, Peter Tseng, Lillian Peng, Manjima Dhar, Saravanan Karumbayaram, Dino Di Carlo

Abstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in Microsystems & nanoengineering, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 25 papers.

0numbers the graph read from it
0cells of the map it votes in
25citing 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

25 citing papers in PubMed.

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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

8 authors.

Jonathan LinDepartment of Bioengineering, University of California, Los Angeles, CA 90095, USA.
Donghyuk KimDepartment of Bioengineering, University of California, Los Angeles, CA 90095, USA.
Henry T TseCytoVale Inc., 384 Oyster Point Boulevard #7 South, San Francisco, CA 94080, USA.
Peter TsengDepartment of Biomedical Engineering, Tufts University, Medford, MA 02155, USA.
Lillian PengDepartment of Bioengineering, University of California, Los Angeles, CA 90095, USA.
Manjima DharDepartment of Bioengineering, University of California, Los Angeles, CA 90095, USA.
Saravanan KarumbayaramEli and Edythe Broad Center of Regenerative Medicine and Stem Cell Research, Los Angeles, CA 90095, USA.
Dino Di CarloDepartment of Bioengineering, University of California, Los Angeles, CA 90095, USA.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

In this report, we present multiparameter deformability cytometry (m-DC), in which we explore a large set of parameters describing the physical phenotypes of pluripotent cells and their derivatives. m-DC utilizes microfluidic inertial focusing and hydrodynamic stretching of single cells in conjunction with high-speed video recording to realize high-throughput characterization of over 20 different cell motion and morphology-derived parameters. Parameters extracted from videos include size, deformability, deformation kinetics, and morphology. We train support vector machines that provide evidence that these additional physical measurements improve classification of induced pluripotent stem cells, mesenchymal stem cells, neural stem cells, and their derivatives compared to size and deformability alone. In addition, we utilize visual interactive stochastic neighbor embedding to visually map the high-dimensional physical phenotypic spaces occupied by these stem cells and their progeny and the pathways traversed during differentiation. This report demonstrates the potential of m-DC for improving understanding of physical differences that arise as cells differentiate and identifying cell subpopulations in a label-free manner. Ultimately, such approaches could broaden our understanding of subtle changes in cell phenotypes and their roles in human biology.

Indexed as

cell mechanicsdeformationdeformation kineticsmorphologyphysical phenotypestem cells

Identifiers

PMID31057860
PMCPMC6445007

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.