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Record W3200664720 · doi:10.3390/ijms221810001

Mechanistic Insights into Axenfeld–Rieger Syndrome from Zebrafish foxc1 and pitx2 Mutants

2021· review· en· W3200664720 on OpenAlexafffund
Curtis R. French

Bibliographic record

VenueInternational Journal of Molecular Sciences · 2021
Typereview
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicDevelopmental Biology and Gene Regulation
Canadian institutionsMemorial University of Newfoundland
FundersMemorial University of NewfoundlandGlaucoma Research Society of Canada
KeywordsZebrafishPITX2BiologyPhenotypeCraniofacialLoss functionTranscription factorGeneticsGeneTranscription (linguistics)BioinformaticsHomeobox

Abstract

fetched live from OpenAlex

Axenfeld–Rieger syndrome (ARS) encompasses a group of developmental disorders that affect the anterior segment of the eye, as well as systemic developmental defects in some patients. Malformation of the ocular anterior segment often leads to secondary glaucoma, while some patients also present with cardiovascular malformations, craniofacial and dental abnormalities and additional periumbilical skin. Genes that encode two transcription factors, FOXC1 and PITX2, account for almost half of known cases, while the genetic lesions in the remaining cases remain unresolved. Given the genetic similarity between zebrafish and humans, as well as robust antisense inhibition and gene editing technologies available for use in these animals, loss of function zebrafish models for ARS have been created and shed light on the mechanism(s) whereby mutations in these two transcription factors cause such a wide array of developmental phenotypes. This review summarizes the published phenotypes in zebrafish foxc1 and pitx2 loss of function models and discusses possible mechanisms that may be used to target pharmaceutical development and therapeutic interventions.

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: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.970
Threshold uncertainty score0.768

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
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 head0.310
Teacher spread0.293 · 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 designNot applicable
Domainnot available
GenreReview

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

Citations20
Published2021
Admission routes2
Has abstractyes

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