Evidence map›Paper›PMID 37398351›Full record

ArticlebioRxiv : the preprint server for biology2023

Optimizing Cell Therapy by Sorting Cells with High Extracellular Vesicle Secretion.

Doyeon Koo, Xiao Cheng, Shreya Udani, Dashuai Zhu, Junlang Li, Brian Hall, Natalie Tsubamoto, Shiqi Hu, Jina Ko, Ke Cheng and 1 more

Open access · greenAbstract readPreprint
PubMed Full text at PMC Publisher
In one paragraph

Article in bioRxiv : the preprint server for biology, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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

0 citing papers in PubMed, 9 citations in OpenAlex.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

11 authors at 5 institutions in 1 country.

Doyeon KooDepartment of Bioengineering, University of California, Los Angeles; Los Angeles, CA 90095, USA.
Xiao ChengJoint Department of Biomedical Engineering, University of North Carolina at Chapel Hill and North Carolina State University; Chapel Hill, NC 27599, and Raleigh, NC 27607, USA.
Shreya UdaniDepartment of Bioengineering, University of California, Los Angeles; Los Angeles, CA 90095, USA.
Dashuai ZhuJoint Department of Biomedical Engineering, University of North Carolina at Chapel Hill and North Carolina State University; Chapel Hill, NC 27599, and Raleigh, NC 27607, USA.
Junlang LiJoint Department of Biomedical Engineering, University of North Carolina at Chapel Hill and North Carolina State University; Chapel Hill, NC 27599, and Raleigh, NC 27607, USA.
Brian HallCytek Biosciences; Fremont, CA 94538, USA.
Natalie TsubamotoDepartment of Bioengineering, University of California, Los Angeles; Los Angeles, CA 90095, USA.
Shiqi HuJoint Department of Biomedical Engineering, University of North Carolina at Chapel Hill and North Carolina State University; Chapel Hill, NC 27599, and Raleigh, NC 27607, USA.
Jina KoDepartment of Pathology and Laboratory Medicine, University of Pennsylvania; Philadelphia, PA 19104, USA.
Ke ChengJoint Department of Biomedical Engineering, University of North Carolina at Chapel Hill and North Carolina State University; Chapel Hill, NC 27599, and Raleigh, NC 27607, USA.
Dino Di CarloDepartment of Bioengineering, University of California, Los Angeles; Los Angeles, CA 90095, USA.
University of North Carolina at Chapel Hill · USUniversity of California, Los Angeles · USCalifornia NanoSystems Institute · USCytel (United States) · USUniversity of Pennsylvania · US

Funding

Women's CancersP30CA016042 · NCI · UNIVERSITY OF CALIFORNIA LOS ANGELES · PI Robert Damoiseaux · 1985 to 2026
$134.5M
Harnessing Platelet-Endothelial Interactions for Stem Cell DeliveryR01HL144002 · NHLBI · NORTH CAROLINA STATE UNIVERSITY RALEIGH · PI Ke Cheng · 2019 to 2026
$4.5M
Hydrogel nanovial technology for single-cell sorting based on extracellular vesicle productionR21GM142174 · NIGMS · UNIVERSITY OF CALIFORNIA LOS ANGELES · PI DI CARLO, DINO · 2021 to 2022
$391k
NCI NIH HHS P30 CA016042NHLBI NIH HHS R01 HL144002NIGMS NIH HHS R21 GM142174
6 · The paper itself

Abstract

Critical challenges remain in clinical translation of extracellular vesicle (EV)-based therapeutics due to the absence of methods to enrich cells with high EV secretion. Current cell sorting methods are limited to surface markers that are uncorrelated to EV secretion or therapeutic potential. We developed a nanovial technology for enrichment of millions of single cells based on EV secretion. This approach was applied to select mesenchymal stem cells (MSCs) with high EV secretion as therapeutic cells for improving treatment. The selected MSCs exhibited distinct transcriptional profiles associated with EV biogenesis and vascular regeneration and maintained high levels of EV secretion after sorting and regrowth. In a mouse model of myocardial infarction, treatment with high-secreting MSCs improved heart functions compared to treatment with low-secreting MSCs. These findings highlight the therapeutic importance of EV secretion in regenerative cell therapies and suggest that selecting cells based on EV secretion could enhance therapeutic efficacy.

Indexed as

Extracellular vesiclesLab on a particleMesenchymal stromal cellsregenerative medicineSingle-cell analysis

Identifiers

PMID37398351
PMCPMC10312470
OpenAlexW4379196867

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC-ND
Read underepoch 390

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.