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Record W2195992255 · doi:10.3389/fvets.2015.00055

Equine Induced Pluripotent Stem Cells have a Reduced Tendon Differentiation Capacity Compared to Embryonic Stem Cells

2015· article· en· W2195992255 on OpenAlexaff
Emma P. Bavin, Olivia Eilers Smith, Arabella Baird, Lawrence C. Smith, Deborah J. Guest

Bibliographic record

VenueFrontiers in Veterinary Science · 2015
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicPluripotent Stem Cells Research
Canadian institutionsUniversité de Montréal
FundersHorserace Betting Levy Board
KeywordsEmbryonic stem cellStem cellInduced pluripotent stem cellCell biologyBiologyKOSRAnatomyGeneticsGene

Abstract

fetched live from OpenAlex

Tendon injuries occur commonly in horses and their repair through scar tissue formation predisposes horses to a high rate of re-injury. Pluripotent stem cells may provide a cell replacement therapy to improve tendon tissue regeneration and lower the frequency of re-injury. We have previously demonstrated that equine embryonic stem cells (ESCs) differentiate into the tendon cell lineage upon injection into the damaged horse tendon and can differentiate into functional tendon cells in vitro to generate artificial tendons. Induced pluripotent stem cells (iPSCs) have now been derived from horses but, to date, there are no reports on their ability to differentiate into tendon cells. As iPSCs can be produced from adult cell types, they provide a more accessible source of cells than ESCs, which require the use of horse embryos. The aim of this study was to compare tendon differentiation by ESCs and iPSCs produced through two independent methods. In two-dimensional differentiation assays, the iPSCs expressed tendon-associated genes and proteins, which were enhanced by the presence of transforming growth factor-β3. However, in three-dimensional (3D) differentiation assays, the iPSCs failed to differentiate into functional tendon cells and generate artificial tendons. These results demonstrate the utility of the 3D in vitro tendon assay for measuring tendon differentiation and the need for more detailed studies to be performed on equine iPSCs to identify and understand their epigenetic differences from pluripotent ESCs prior to their clinical application.

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)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
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 score0.013
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.001
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 head0.066
GPT teacher head0.289
Teacher spread0.223 · 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.

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

Citations54
Published2015
Admission routes1
Has abstractyes

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