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Record W1924404458 · doi:10.1002/dvdy.24141

AP‐2α is required after lens vesicle formation to maintain lens integrity

2014· article· en· W1924404458 on OpenAlexafffund
Christine Kerr, Mizna Zaveri, Michael L. Robinson, Trevor Williams, Judith A. West‐Mays

Bibliographic record

VenueDevelopmental Dynamics · 2014
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicConnexins and lens biology
Canadian institutionsMcMaster University Medical Centre
FundersNational Eye InstituteFoundation Fighting Blindness
KeywordsBiologyLens (geology)Cell biologyVesicleAnatomyGenetics

Abstract

fetched live from OpenAlex

BACKGROUND: Transcription factors are critical in regulating lens development. The AP-2 family of transcription factors functions in differentiation, cell growth and apoptosis, and in lens and eye development. AP-2α, in particular, is important in early lens development, and when conditionally deleted at the placode stage defective separation of the lens vesicle from the surface ectoderm results. AP-2α's role during later stages of lens development is unknown. To address this, the MLR10-Cre transgene was used to delete AP-2α from the lens epithelium beginning at embryonic day (E) 10.5. RESULTS: The loss of AP-2α after lens vesicle separation resulted in morphological defects beginning at E18.5. By P4, a small highly vacuolated lens with a multilayered epithelium was evident in the MLR10-AP-2α mutants. Epithelial cells appeared elongated and expressed fiber cell specific βB1 and γ-crystallins. Epithelial cell polarity and lens cell adhesion was disrupted and accompanied by the misexpression of ZO-1, N-Cadherin, and β-catenin. Cell death was observed in the mutant lens epithelium between postnatal day (P) 14 and P30, and correlated with altered arrangements of cells within the epithelium. CONCLUSIONS: Our findings demonstrate that AP-2α continues to be required after lens vesicle separation to maintain a normal lens epithelial cell phenotype and overall lens integrity and to ensure correct fiber cell differentiation.

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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.570
Threshold uncertainty score0.698

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 head0.011
GPT teacher head0.229
Teacher spread0.218 · 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

Citations17
Published2014
Admission routes2
Has abstractyes

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