Evidence map›Paper›PMID 38718114›Full record

ArticleScience advances2024

Label-free metabolic optical biomarkers track stem cell fate transition in real time.

Hao Zhou, Irene Li, Charles S Bramlett, Bowen Wang, Jia Hao, Daniel P Yen, Yuta Ando, Scott E Fraser, Rong Lu, Keyue Shen

Abstract read
In one paragraph

Article in Science advances, 2024. 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. Article
  2. Review
  3. Review
  4. 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

10 authors.

Hao ZhouDepartment of Biomedical Engineering, University of Southern California, Los Angeles, CA 90089, USA.ORCID 0000-0002-3030-4270
Irene LiDepartment of Biomedical Engineering, University of Southern California, Los Angeles, CA 90089, USA.ORCID 0009-0001-5937-3878
Charles S BramlettDepartment of Stem Cell Biology and Regenerative Medicine, University of Southern California, Los Angeles, CA 90033, USA.ORCID 0000-0001-8663-1564
Bowen WangDepartment of Stem Cell Biology and Regenerative Medicine, University of Southern California, Los Angeles, CA 90033, USA.ORCID 0000-0002-2974-9790
Jia HaoDepartment of Biomedical Engineering, University of Southern California, Los Angeles, CA 90089, USA.
Daniel P YenDepartment of Biomedical Engineering, University of Southern California, Los Angeles, CA 90089, USA.ORCID 0000-0003-4101-9448
Yuta AndoDepartment of Biomedical Engineering, University of Southern California, Los Angeles, CA 90089, USA.
Scott E FraserDepartment of Biomedical Engineering, University of Southern California, Los Angeles, CA 90089, USA.ORCID 0000-0002-5377-0223
Rong LuDepartment of Biomedical Engineering, University of Southern California, Los Angeles, CA 90089, USA.ORCID 0000-0002-5151-9246
Keyue ShenDepartment of Biomedical Engineering, University of Southern California, Los Angeles, CA 90089, USA.ORCID 0000-0001-9605-1635

Funding

USC/NORRIS COMPREHENSIVE CANCER CENTER (CORE) SUPPORTP30CA014089 · NCI · UNIVERSITY OF SOUTHERN CALIFORNIA · PI MYLES G COCKBURN · 1985 to 2026
$181.4M
Investigating the heterogeneity and coordination of hematopoietic stem cells (Diversity Supplement)R35HL150826 · NHLBI · UNIVERSITY OF SOUTHERN CALIFORNIA · PI Rong Lu · 2020 to 2026
$6.8M
(PQ5) Microenvironmental Regulation of Mitochondrial Heterogeneity in Cancer MetastasisR01CA220012 · NCI · UNIVERSITY OF SOUTHERN CALIFORNIA · PI SHEN, KEYUE · 2019 to 2023
$2.2M
Using spatial, single-cell genomic recording to investigate age-associated clonal hematopoiesisR01AG080982 · NIA · UNIVERSITY OF SOUTHERN CALIFORNIA · PI MICHAEL B ELOWITZ, CARLOS LOIS · 2023 to 2026
$2.1M
Artificial Stromal Cell for Hematopoietic Stem Cell ExpansionR21EB024748 · NIBIB · UNIVERSITY OF SOUTHERN CALIFORNIA · PI SHEN, KEYUE · 2017 to 2019
$637k
NCI NIH HHS P30 CA014089NCI NIH HHS R01 CA220012NHLBI NIH HHS R35 HL150826NIA NIH HHS R01 AG080982NIBIB NIH HHS R21 EB024748
6 · The paper itself

Abstract

Tracking stem cell fate transition is crucial for understanding their development and optimizing biomanufacturing. Destructive single-cell methods provide a pseudotemporal landscape of stem cell differentiation but cannot monitor stem cell fate in real time. We established a metabolic optical metric using label-free fluorescence lifetime imaging microscopy (FLIM), feature extraction and machine learning-assisted analysis, for real-time cell fate tracking. From a library of 205 metabolic optical biomarker (MOB) features, we identified 56 associated with hematopoietic stem cell (HSC) differentiation. These features collectively describe HSC fate transition and detect its bifurcate lineage choice. We further derived a MOB score measuring the "metabolic stemness" of single cells and distinguishing their division patterns. This score reveals a distinct role of asymmetric division in rescuing stem cells with compromised metabolic stemness and a unique mechanism of PI3K inhibition in promoting ex vivo HSC maintenance. MOB profiling is a powerful tool for tracking stem cell fate transition and improving their biomanufacturing from a single-cell perspective.

Indexed as

BiomarkersCell DifferentiationCell LineageHematopoietic Stem CellsAnimalsCell TrackingHumansMiceMicroscopy, FluorescenceSingle-Cell AnalysisBiomarkers

Identifiers

PMID38718114
PMCPMC11078180

What OpenQuestion holds

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LicenceCC BY
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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.