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Record W2417007123 · doi:10.1007/978-1-62703-478-4_9

Directed Differentiation of Embryonic Stem Cells to the T-Lymphocyte Lineage

2013· article· en· W2417007123 on OpenAlexaff
Haydn C.-Y. Liang, Roxanne Holmes, Juan Carlos Zúñiga‐Pflücker

Bibliographic record

VenueMethods in molecular biology · 2013
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicZebrafish Biomedical Research Applications
Canadian institutionsUniversity of TorontoSunnybrook Health Science Centre
Fundersnot available
KeywordsHemangioblastCell biologyBiologyHaematopoiesisEmbryonic stem cellEmbryoid bodyStem cellStromal cellCellular differentiationBone marrowImmunologyAdult stem cellGeneticsCancer research

Abstract

fetched live from OpenAlex

Hematopoiesis is the highly regulated and complex process by which blood cells are formed. Hematopoiesis can be achieved in vitro by the differentiation of embryonic stem cells (ESCs) into hematopoietic lineage cells. Differentiation of ESCs initially gives rise to mesoderm colonies that go on to form hemangioblast cells, which possess endothelial and hematopoietic lineage potential. While the differentiation of several hematopoietic lineages from ESCs, such as erythrocytes and macrophages, can be easily recapitulated in vitro, T-cell differentiation requires additional Notch-dependent signals for their generation. Keeping with this, ESCs induced to differentiate with OP-9 cells, a bone marrow-derived stromal cell line, give rise to erythro-myeloid cells and B lymphocytes, while the expression of an appropriate Notch ligand, such as Delta-like 1, on OP-9 cells (OP9-DL1) is required to support the generation of T-cells in vitro. Here, we describe an updated and streamlined protocol for the generation of T-lineage cells from mouse ESCs cultured on OP9-DL1 cells. This approach can facilitate studies aimed to assess the effects of environmental and genetic manipulations at various stages of T-cell development.

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 categoriesnone
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 score0.142
Threshold uncertainty score0.418

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
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 integrity0.0000.000
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 head0.017
GPT teacher head0.365
Teacher spread0.348 · 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
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

Citations6
Published2013
Admission routes1
Has abstractyes

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