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Record W1507087895 · doi:10.1002/dvdy.24113

Fgfr signaling is required as the early eye field forms to promote later patterning and morphogenesis of the eye

2014· article· en· W1507087895 on OpenAlexafffund
Karen Atkinson‐Leadbeater, Carrie L. Hehr, Sarah McFarlane

Bibliographic record

VenueDevelopmental Dynamics · 2014
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicDevelopmental Biology and Gene Regulation
Canadian institutionsUniversity of CalgaryMount Royal University
FundersCanadian Institutes of Health ResearchAlberta Innovates - Health Solutions
KeywordsOptic vesicleEye developmentMorphogenesisOptic cup (embryology)BiologyFibroblast growth factorRetinaColobomaCell biologyAnatomyNeuroscienceGeneticsReceptorPhenotype

Abstract

fetched live from OpenAlex

BACKGROUND: A major step in eye morphogenesis is the transition from optic vesicle to optic cup, which occurs as a ventral groove forms along the base of the optic vesicle. A ventral gap in the eye, or coloboma, results when this groove fails to close. Extrinsic signals, such as fibroblast growth factors (Fgfs), play a critical role in the development and morphogenesis of the vertebrate eye. Whether these extrinsic signals are required throughout eye development, or within a defined critical period remains an unanswered question. RESULTS: Here we show that an early Fgf signal, required as the eye field is first emerging, drives eye morphogenesis. In addition to triggering coloboma, inhibition of this early Fgf signal results in defects in dorsal-ventral patterning of the neural retina, particularly in the nasal retina, and development of the periocular mesenchyme (POM). These processes are unaffected by inhibition of Fgfr signaling at later time points. CONCLUSIONS: We propose that Fgfs act within an early critical period as the eye field forms to promote development of the neural retina and POM, which subsequently drive eye morphogenesis.

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: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.073
Threshold uncertainty score0.340

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
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 science0.0000.000
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 head0.004
GPT teacher head0.216
Teacher spread0.212 · 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
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

Citations16
Published2014
Admission routes2
Has abstractyes

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