Evidence map›Paper›PMID 42738827›Full record

ArticleCells2026

Machine Learning-Driven Automated Culture Reveals Similar Performance of mTeSR+ and StemFlex in Human iP11N Pluripotent Stem Cells.

Aleksander A Bogoniewski, Melissa F Gonzalez, Rachel E Reyes, Susanna F Rivera, Cameron Taylor, Todd Schurr, Robert Damoiseaux, Gerald S Lipshutz

Abstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in Cells, 2026. 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.

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.

Aleksander A BogoniewskiDepartment of Molecular and Medical Pharmacology, David Geffen School of Medicine, University of California, Los Angeles (UCLA), Los Angeles, CA 90095, USA.
Melissa F GonzalezDepartment of Surgery, David Geffen School of Medicine, University of California, Los Angeles (UCLA), Los Angeles, CA 90024, USA.
Rachel E ReyesDepartment of Surgery, David Geffen School of Medicine, University of California, Los Angeles (UCLA), Los Angeles, CA 90024, USA.ORCID 0000-0002-3130-6390
Susanna F RiveraDepartment of Surgery, David Geffen School of Medicine, University of California, Los Angeles (UCLA), Los Angeles, CA 90024, USA.
Cameron TaylorCalifornia NanoSystems Institute, University of California, Los Angeles (UCLA), Los Angeles, CA 90095, USA.ORCID 0009-0008-6697-9166
Todd SchurrCalifornia NanoSystems Institute, University of California, Los Angeles (UCLA), Los Angeles, CA 90095, USA.ORCID 0009-0000-4216-6998
Robert DamoiseauxDepartment of Molecular and Medical Pharmacology, David Geffen School of Medicine, University of California, Los Angeles (UCLA), Los Angeles, CA 90095, USA.ORCID 0000-0002-7611-7534
Gerald S LipshutzDepartment of Molecular and Medical Pharmacology, David Geffen School of Medicine, University of California, Los Angeles (UCLA), Los Angeles, CA 90095, USA.

Funding

Women's CancersP30CA016042 · NCI · UNIVERSITY OF CALIFORNIA LOS ANGELES · PI Robert Damoiseaux · 1985 to 2026
$134.5M
Automated Cell Culture SystemS10OD038259 · OD · UNIVERSITY OF CALIFORNIA LOS ANGELES · PI DAMOISEAUX, ROBERT · 2025 to 2025
$1.9M
California Institute for Regenerative Medicine DISC2-14090NCI NIH HHS P30 CA016042NIH HHS S10 OD038259
6 · The paper itself

Abstract

Human induced pluripotent stem cells (hiPSCs) are powerful tools for disease modeling and therapeutic development, though their utility remains sensitive to operator-dependent variability and media formulation. Commercial stem cell media formulations, such as mTeSR+ and StemFlex, are designed to support robust pluripotent stem cell maintenance and improve reproducibility. While both are widely used, direct comparisons are limited. We evaluated mTeSR+ and StemFlex using the CellXpress.ai automated tissue culture platform in combination with IN Carta machine-learning-based image analysis to monitor and standardize feeding, passaging, and maintenance. Wild-type iP11N hiPSCs were cultured under standardized automated conditions with growth kinetics, immunocytochemical marker expression, and RT-qPCR assessment. Automated analysis revealed no significant differences in proliferation rates between the formulations; however, longitudinal image-based quantification identified statistically significant differences (<1%) in differentiated cell area fraction across the imaging period. Immunocytochemistry demonstrated comparable expression and localization of pluripotency-associated markers, and RT-qPCR analysis confirmed similar expression of stemness factors. These findings demonstrate that both media support comparable growth and maintenance of pluripotency under standardized automated conditions on iP11N wild-type stem cells in the short-term culture conditions analyzed. Additionally, these data highlight the value of automated imaging and machine-learning-based analysis in reducing operator-dependent variability and improving consistency in hiPSC culture, supporting its application in high-throughput stem cell research.

Indexed as

Cell Culture TechniquesInduced Pluripotent Stem CellsMachine LearningAutomationCell DifferentiationCell ProliferationHumansautomated cell culturehuman induced pluripotent stem cellsmachine learningstem cell culture media

Identifiers

PMID42738827
PMCPMC13565254

What OpenQuestion holds

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Registered trials

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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.