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Record W2026519680 · doi:10.1242/dev.092866

Location of transient ectodermal progenitor potential in mouse development

2013· article· en· W2026519680 on OpenAlexafffund
Lingyu Li, Chang Liu, Steffen Biechele, Qingqing Zhu, Lu Song, Fredrik Lanner, Naihe Jing, Janet Rossant

Bibliographic record

VenueDevelopment · 2013
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicPluripotent Stem Cells Research
Canadian institutionsUniversity of TorontoHospital for Sick Children
FundersCanadian Institutes of Health ResearchHospital for Sick Children
KeywordsEctodermGerm layerBiologyEpiblastCell biologyEmbryogenesisEmbryonic stem cellInduced pluripotent stem cellAnatomyEmbryoGeneticsGastrulation

Abstract

fetched live from OpenAlex

Ectoderm is one of the three classic germ layers in the early mouse embryo, with the capacity to develop into both the central nervous system and epidermis. Because it is a transient phase of development with few molecular markers, the early ectoderm is the least understood germ layer in mouse embryonic development. In this work, we studied the differentiation potential of isolated ectoderm tissue in response to BMP signaling at various developmental stages (E6.5, E7.0 and E7.5), and identified a transient region in the anterior-proximal side of the embryo at E7.0 that possesses the ability to become neural or epidermal ectoderm in response to the absence or presence of BMP4, respectively. Furthermore, we demonstrated that inhibition of Nodal signaling could direct the pluripotent E6.5 epiblast cells towards ectoderm lineages during differentiation in explants in vitro. Our work not only improves our understanding of ectodermal layer development in early embryos, but also provides a framework for regenerative differentiation towards ectodermal tissues.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.002
Threshold uncertainty score0.007

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0020.001

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 head0.010
GPT teacher head0.232
Teacher spread0.222 · 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 source (direct Gemma or distilled Codex), 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

Citations64
Published2013
Admission routes2
Has abstractyes

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