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Record W1965945615 · doi:10.1071/rdv26n1ab191

191 ROBUST GENERATION OF NEURAL STEM CELLS FROM PIG INDUCED PLURIPOTENT STEM CELLS FOR TRANSLATIONAL NEURAL REGENERATIVE MEDICINE

2013· article· en· W1965945615 on OpenAlexaboutno aff
Amalia Gallegos-Cárdenas, K. Wang, Erin T. Jordan, Rachel C. West, Franklin D. West, Jianwei Yang, Steven L. Stice

Bibliographic record

VenueReproduction Fertility and Development · 2013
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicPluripotent Stem Cells Research
Canadian institutionsnot available
Fundersnot available
KeywordsInduced pluripotent stem cellMatrigelNeural stem cellBiologyCell biologyRegenerative medicineEmbryonic stem cellStem cellMolecular biologyIn vitroBiochemistry

Abstract

fetched live from OpenAlex

The generation of pig induced pluripotent stem cells (iPSC) opened the possibility to evaluate autologous neural cell therapy as a viable option for human patients. However, it is necessary to demonstrate whether pig iPSC are capable of in vitro neural differentiation similar to human iPSC in order to perform in vitro and in vivo comparative studies. Multiple laboratories have generated pig iPSC that have been characterised using pluripotent markers such as SSEA4 and POU5F1. However, correlations of pluripotent marker expression profiles among iPSC lines and their neural differentiation potential has not been fully explored. Because neural rosettes (NR) are composed of neural stem cells, our goal was to demonstrate that NR from pig iPSC can be generated, isolated, and expanded in vitro from multiple porcine iPSC lines similar to human iPSC and that the level of pluripotency in the starting porcine iPSC population (POUF51 and SSEA4 expression) could influence NRs development. Three lines of pig iPSC L1, L2, and L3 were cultured on matrigel-coated plates in mTeSR1 medium (Stemcell Technologies Inc., Vancouver, BC, Canada) and passaged every 3 to 4 days. For neural induction (NI), pig iPSC were disaggregated using dispase and plated. After 24 h, cells were maintained in N2 media [77% DMEM/F12, 10 ng mL–1 bovine fibroblast growth factor (bFGF), and 1X N2] for 15 days. To evaluate the differentiation potential to neuron and glial cells, NR were isolated, expanded in vitro and cultured for three weeks in AB2 medium (AB2, 1X ANS, and 2 mM L-Glutamine). Immunostaining assays were performed to determine pluripotent (POU5F1 and SSEA4), tight junction (ZO1), neural epithelial (Pax6 and Sox1), neuron (Tuj1), astrocyte (GFAP), and oligodendrocyte (O4) marker expression. Line L2 (POU5F1high and SSEA4low) showed a high potential to form NR (6.3.5%, P < 0.05) in comparison to the other 2 lines L1 (POU5F1low and SSEA4low) and L3 (POU5F1low and SSEA4high) upon NI. The NR immunocytochemistry results from Line L2 showed the presence of Pax6+ and Sox1– NRs cells at day 9 post-neural induction and that ZO1 started to localise at the apical border of NRs. At day 13, NRs cells were Pax6+ and Sox1+, and ZO1 was localised to the lumen of NR. After isolation and culture in vitro, NR cells expressed transcription factors PLAGL1, DACH1, and OTX2 through 2 passages, but were not detected in later passages. However, rosette cytoarchitecture was present up until passage 7 and were still Pax6+/Sox1+. NRs at passage 2 were cryopreserved and upon thaw showed normal NR morphology and were Pax6+/Sox1+. To characterise the plasticity of NRs, cells were differentiated. Tuj1 expression was predominant after differentiation indicating a bias towards a neuron phenotype. These results demonstrate that L2 pig iPSC (POUF51high and SSEA4low) have a high potential to form NR and neural differentiation parallels human iPSC neurulation events. Porcine iPSC should be considered as a large animal model for determining the safety and efficacy of human iPSC neural cell therapies.

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation 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 score0.028
Threshold uncertainty score0.772

Codex and Gemma teacher scores by category

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 integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.079
GPT teacher head0.268
Teacher spread0.189 · 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 teacher head, 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

Citations0
Published2013
Admission routes1
Has abstractyes

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