Evidence map›Paper›PMID 21731674›Full record

ArticlePloS one2011

An information theoretic, microfluidic-based single cell analysis permits identification of subpopulations among putatively homogeneous stem cells.

Jason P Glotzbach, Michael Januszyk, Ivan N Vial, Victor W Wong, Alexander Gelbard, Tomer Kalisky, Hariharan Thangarajah, Michael T Longaker, Stephen R Quake, Gilbert Chu and 1 more

Abstract read
In one paragraph

Article in PloS one, 2011. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 42 papers.

0numbers the graph read from it
0cells of the map it votes in
42citing 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

42 citing papers in PubMed.

  1. Endothelial-specific CXCL12 regulates neovascularization during tissue repair and tumor progression.FASEB journal : official publication of the Federation of American Societies for Experimental Biology · 2024
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  10. Isolation of CD248-expressing stromal vascular fraction for targeted improvement of wound healing.Wound repair and regeneration : official publication of the Wound Healing Society [and] the European Tissue Repair Society · 2017
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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

11 authors.

Jason P GlotzbachDepartment of Surgery, Stanford University School of Medicine, Stanford, California, United States of America.
Michael Januszyk
Ivan N Vial
Victor W Wong
Alexander Gelbard
Tomer Kalisky
Hariharan Thangarajah
Michael T Longaker
Stephen R Quake
Gilbert Chu
Geoffrey C Gurtner

Funding

POSTDOCTORAL TRAINING IN MEDICAL INFORMATION SCIENCEST15LM007033 · NLM · STANFORD UNIVERSITY · PI SYLVIA KATINA PLEVRITIS · 1985 to 2026
$25.5M
Reversal of Progenitor Cell Deficits in DiabetesR01DK074095 · NIDDK · UNIVERSITY OF ARIZONA · PI GURTNER, GEOFFREY C · 2005 to 2025
$6.4M
NIDDK NIH HHS 2 RO1 DK074095-07NIDDK NIH HHS F32DK088448-01NIDDK NIH HHS R01 DK074095NLM NIH HHS T15 LM007033
6 · The paper itself

Abstract

An incomplete understanding of the nature of heterogeneity within stem cell populations remains a major impediment to the development of clinically effective cell-based therapies. Transcriptional events within a single cell are inherently stochastic and can produce tremendous variability, even among genetically identical cells. It remains unclear how mammalian cellular systems overcome this intrinsic noisiness of gene expression to produce consequential variations in function, and what impact this has on the biologic and clinical relevance of highly 'purified' cell subgroups. To address these questions, we have developed a novel method combining microfluidic-based single cell analysis and information theory to characterize and predict transcriptional programs across hundreds of individual cells. Using this technique, we demonstrate that multiple subpopulations exist within a well-studied and putatively homogeneous stem cell population, murine long-term hematopoietic stem cells (LT-HSCs). These subgroups are defined by nonrandom patterns that are distinguishable from noise and are consistent with known functional properties of these cells. We anticipate that this analytic framework can also be applied to other cell types to elucidate the relationship between transcriptional and phenotypic variation.

Indexed as

Information TheoryAlgorithmsAnimalsCluster AnalysisFlow CytometryGene Expression RegulationHematopoietic Stem CellsMaleMiceMice, Inbred C57BLMicrofluidicsModels, BiologicalMultivariate AnalysisSingle-Cell AnalysisTime FactorsTranscription, Genetic

Identifiers

PMID21731674
PMCPMC3120839

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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.