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Record W2945419690 · doi:10.14348/molcells.2018.0143

Maturation of Cardiomyocytes Derived from Human Pluripotent Stem Cells: <i>Current Strategies and Limitations</i>.

2018· review· en· W2945419690 on OpenAlexaff
Yanqing Jiang, Peter Park, Sangmin hong, Kiwon Ban

Bibliographic record

VenuePubMed · 2018
Typereview
Languageen
FieldMedicine
TopicTissue Engineering and Regenerative Medicine
Canadian institutionsHospital for Sick ChildrenUniversity of Toronto
FundersCity University of Hong Kong
KeywordsInduced pluripotent stem cellEmbryonic stem cellStem cellBiologyCell biologyHuman Induced Pluripotent Stem CellsNeuroscienceDrug discoveryComputational biologyBioinformaticsGenetics

Abstract

fetched live from OpenAlex

provides an unlimited resource for human CMs for a wide range of applications such as cell based cardiac repair, cardiac drug toxicology screening, and human cardiac disease modeling. However, their applicability is significantly limited by immature phenotypes. It has been well known that currently available CMs derived from hPSCs (hPSC-CMs) represent immature embryonic or fetal stage CMs and are functionally and structurally different from mature human CMs. To overcome this critical issue, several new approaches aiming to generate more mature hPSC-CMs have been developed. This review describes recent approaches to generate more mature hPSC-CMs including their scientific principles, advantages, and limitations.

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: Other design · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.989
Threshold uncertainty score0.943

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
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 head0.107
GPT teacher head0.297
Teacher spread0.190 · 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 designOther design
Domainnot available
GenreReview

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

Citations89
Published2018
Admission routes1
Has abstractyes

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