Evidence map›Paper›PMID 38351912›Full record

ArticleGene reports2024

Identification of RNA-based cell-type markers for stem-cell manufacturing systems with a statistical scoring function.

Yu Shi, Weilong Yang, Haishuang Lin, Li Han, Alyssa J Cai, Ravi Saraf, Yuguo Lei, Chi Zhang

Open access · hybridAbstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in Gene reports, 2024. 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, top 47% of its field
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, 0 citations in OpenAlex.

No citing paper in PubMed yet.

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 at 3 institutions in 1 country.

Yu ShiSchool of Biological Sciences, University of Nebraska, Lincoln, NE, USA.
Weilong YangSchool of Biological Sciences, University of Nebraska, Lincoln, NE, USA.
Haishuang LinDepartment of Chemical and Biomolecular Engineering, University of Nebraska, Lincoln, NE, USA.
Li HanDepartment of Biomedical Engineering, Pennsylvania State University, University Park, PA, USA.
Alyssa J CaiNewark Academy, 91 W S Orange Ave, Livingston, NJ, USA.
Ravi SarafDepartment of Chemical and Biomolecular Engineering, University of Nebraska, Lincoln, NE, USA.
Yuguo LeiDepartment of Biomedical Engineering, Pennsylvania State University, University Park, PA, USA.
Chi ZhangSchool of Biological Sciences, University of Nebraska, Lincoln, NE, USA.
University of Nebraska–Lincoln · USPennsylvania State University · USNewark Academy · US

Funding

A Single Conical Tube Device for Precision CAR-T Cells ManufacturingR33CA235326 · NCI · UNIVERSITY OF NEBRASKA LINCOLN · PI LEI, YUGUO · 2019 to 2021
$1.1M
An Enabling Technology for Human Cardiomyocyte ManufacturingR33HL163711 · NHLBI · PENNSYLVANIA STATE UNIVERSITY, THE · PI LEI, YUGUO · 2022 to 2023
$809k
Biofabricating Seminiferous Tubules for In Vitro SpermatogenesisR21HD114044 · NICHD · PENNSYLVANIA STATE UNIVERSITY, THE · PI LEI, YUGUO · 2023 to 2023
$414k
NCI NIH HHS R33 CA235326NHLBI NIH HHS R33 HL163711NICHD NIH HHS R21 HD114044
6 · The paper itself

Abstract

Cell-type biomarkers are useful in stem-cell manufacturing to monitor cell purity, quantity, and quality. However, the study on cell-type markers, specifically for stem cell manufacture, is limited. Emerging questions include which RNA transcripts can serve as biomarkers during stem cell culture and how to discover these biomarkers efficiently and precisely. We developed a scoring function system to identify RNA biomarkers with RNA-seq data for systems that have a limited number of cell types. We applied the method to two data sets, one for extracellular RNAs (ex-RNAs) and the other for intracellular microRNAs (miRNAs). The first data set has RNA-seq data of ex-RNAs from cell culture media for six different types of cells, including human embryonic stem cells. To get the RNA-seq data from intracellular miRNAs, we cultured three types of cells: human embryonic stem cells (H9), neural stem cells (NSC), hESC-derived endothelial cells (EC) and conducted small RNA-seq to their intracellular miRNAs. Using these data, we identified a set of ex-RNAs/smRNAs as candidates of biomarkers for different types of cells for cell manufacture. The validity of these findings was confirmed by the utilization of additional data sets and experimental procedures. We also used deep-learning-based prediction methods and simulated data to validate these discovered biomarkers.

Indexed as

Cell culture and purificationCell-type markersExtracellular RNAs (ex-RNAs)Intracellular microRNAs (miRNAs)

Identifiers

PMID38351912
PMCPMC10861185
OpenAlexW4389621658

What OpenQuestion holds

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LicenceCC BY-NC-ND
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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.