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Record W3093879773 · doi:10.1002/ar.24547

Cellular and molecular mechanisms in the development of a cleft lip and/or cleft palate; insights from zebrafish (<scp><i>Danio rerio</i></scp>)

2020· review· en· W3093879773 on OpenAlexaff
Devi Atukorallaya, Ravindra Kumar Ratnayake

Bibliographic record

VenueThe Anatomical Record · 2020
Typereview
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicCleft Lip and Palate Research
Canadian institutionsUniversity of ManitobaManitoba Health
Fundersnot available
KeywordsDanioZebrafishCell biologyBiologyAnatomyMedicineGeneticsGene

Abstract

fetched live from OpenAlex

Human cleft lip and/or palate (CLP) are immediately recognizable congenital abnormalities of the face. Lip and palate develop from facial primordia through the coordinated activities of ectodermal epithelium and neural crest cells (NCCs) derived from ectomesenchyme tissue. Subtle changes in the regulatory mechanisms of NCC or ectodermal epithelial cells can result in CLP. Genetic and environmental contributions or a combination of both play a significant role in the progression of CLP. Model organisms provide us with a wealth of information in understanding the pathophysiology and genetic etiology of this complex disease. Small teleost, zebrafish (Danio rerio) is one of the popular model in craniofacial developmental biology. The short generation time and large number of optically transparent, easily manipulated embryos increase the value of zebrafish to identify novel candidate genes and gene regulatory networks underlying craniofacial development. In addition, it is widely used to identify the mechanisms of environmental teratogens and in therapeutic drug screening. Here, we discuss the value of zebrafish as a model to understand epithelial and NCC induced ectomesenchymal cell activities during early palate morphogenesis and robustness of the zebrafish in modern research on identifying the genetic and environmental etiological factors of CLP.

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 categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.993
Threshold uncertainty score1.000

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 science0.0010.001
Research integrity0.0010.001
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 head0.027
GPT teacher head0.288
Teacher spread0.261 · 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.

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

Citations11
Published2020
Admission routes1
Has abstractyes

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