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Record W1580908187 · doi:10.1007/978-1-60761-962-8_4

Functional Assays for Human Embryonic Stem Cell Pluripotency

2010· article· en· W1580908187 on OpenAlexaff
Michael D. O’Connor, Melanie Kardel, Connie J. Eaves

Bibliographic record

VenueMethods in molecular biology · 2010
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicPluripotent Stem Cells Research
Canadian institutionsBC Cancer Agency
Fundersnot available
KeywordsEmbryoid bodyEmbryonic stem cellCell biologyInduced pluripotent stem cellEctodermBiologyEndodermKOSRMesodermGerm layerStem cellAlkaline phosphataseCellular differentiationEmbryoEmbryogenesisGeneticsBiochemistry

Abstract

fetched live from OpenAlex

Realizing the potential that human embryonic stem cells (hESCs) hold, both for the advancement of biomedical science and the development of new treatments for many human disorders, will be greatly facilitated by the introduction of standardized methods for assessing and altering the biological properties of these cells. The 7-day in vitro alkaline phosphatase colony-forming cell (AP(+)-CFC) assay currently offers the most sensitive and specific method to quantify the frequency of undifferentiated cells present in a culture. In this regard, it is superior to any phenotypic assessment protocol. The AP(+)-CFC assay, thus, provides a valuable tool for monitoring the quality of hESC cultures, and also for evaluating quantitative changes in pluripotent cell numbers following manipulations that may affect the self-renewal and differentiation properties of the treated cells. Two other methods routinely used to evaluate hESC pluripotency involve either culturing the cells under conditions that promote the formation of nonadherent differentiating cell aggregates (termed embryoid bodies), or transplanting the cells into immunodeficient mice to obtain teratomas containing differentiated cells representative of endoderm, mesoderm, and ectoderm lineages.

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)0.002
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: Methods · Consensus signal: Methods
Teacher disagreement score0.052
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
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 science0.0010.000
Research integrity0.0010.000
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 head0.028
GPT teacher head0.375
Teacher spread0.346 · 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
GenreMethods

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

Citations35
Published2010
Admission routes1
Has abstractyes

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