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Record W2954811831 · doi:10.1089/scd.2019.0111

Stirred Suspension Bioreactor Culture of Porcine Induced Pluripotent Stem Cells

2019· article· en· W2954811831 on OpenAlexafffund
Kyle Burrell, Rkia Dardari, Taylor Goldsmith, Derek Toms, D.A.F. Villagómez, W.A. King, Mark Ungrin, Franklin D. West, Ina Dobrinski

Bibliographic record

VenueStem Cells and Development · 2019
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicPluripotent Stem Cells Research
Canadian institutionsUniversity of GuelphUniversity of Calgary
FundersNational Institutes of HealthUniversity of Calgary
KeywordsInduced pluripotent stem cellBiologyRegenerative medicineCell cultureCell biologyStem cellSuspension cultureBioreactorCellCell typeChemically defined mediumEmbryonic stem cellBiotechnologyGeneticsIn vitroBotanyGene

Abstract

fetched live from OpenAlex

Induced pluripotent stem cells (iPSCs) are an attractive cell source for regenerative medicine and the development of therapies, as they can proliferate indefinitely under defined conditions and differentiate into any cell type in the body. Large-scale expansion of cells is limited in adherent culture, making it difficult to obtain adequate cell numbers for research. It has been previously shown that stirred suspension bioreactors (SSBs) can be used to culture mouse and human stem cells. Pigs are important preclinical models for stem cell research. Therefore, this study investigated the use of SSBs as an alternative culture method for the expansion of iPSCs. Using an established porcine iPSC (piPSC) line as well as a new cell line derived and characterized in the current study, we report that piPSCs can grow in SSB while maintaining characteristics of pluripotency and karyotypic stability similar to cells grown in traditional two-dimensional static culture. This culture method provides a suitable platform for scale-up of cell culture to provide adequate cell numbers for future research applications involving piPSCs.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.002
Threshold uncertainty score0.005

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0020.001

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.018
GPT teacher head0.236
Teacher spread0.219 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designBench or experimental
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations16
Published2019
Admission routes2
Has abstractyes

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