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Record W4391609510 · doi:10.3389/fcell.2024.1338070

Transforming growth factor beta signaling and craniofacial development: modeling human diseases in zebrafish

2024· article· en· W4391609510 on OpenAlexafffund
Sabrina C. Fox, Andrew J. Waskiewicz

Bibliographic record

VenueFrontiers in Cell and Developmental Biology · 2024
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicCraniofacial Disorders and Treatments
Canadian institutionsUniversity of Alberta
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsZebrafishCraniofacialCraniosynostosisNeural crestBiologyMorphogenesisCranial neural crestAnatomyNeuroscienceCell biologyGeneticsEmbryo

Abstract

fetched live from OpenAlex

Humans and other jawed vertebrates rely heavily on their craniofacial skeleton for eating, breathing, and communicating. As such, it is vital that the elements of the craniofacial skeleton develop properly during embryogenesis to ensure a high quality of life and evolutionary fitness. Indeed, craniofacial abnormalities, including cleft palate and craniosynostosis, represent some of the most common congenital abnormalities in newborns. Like many other organ systems, the development of the craniofacial skeleton is complex, relying on specification and migration of the neural crest, patterning of the pharyngeal arches, and morphogenesis of each skeletal element into its final form. These processes must be carefully coordinated and integrated. One way this is achieved is through the spatial and temporal deployment of cell signaling pathways. Recent studies conducted using the zebrafish model underscore the importance of the Transforming Growth Factor Beta (TGF-β) and Bone Morphogenetic Protein (BMP) pathways in craniofacial development. Although both pathways contain similar components, each pathway results in unique outcomes on a cellular level. In this review, we will cover studies conducted using zebrafish that show the necessity of these pathways in each stage of craniofacial development, starting with the induction of the neural crest, and ending with the morphogenesis of craniofacial elements. We will also cover human skeletal and craniofacial diseases and malformations caused by mutations in the components of these pathways (e.g., cleft palate, craniosynostosis, etc.) and the potential utility of zebrafish in studying the etiology of these diseases. We will also briefly cover the utility of the zebrafish model in joint development and biology and discuss the role of TGF-β/BMP signaling in these processes and the diseases that result from aberrancies in these pathways, including osteoarthritis and multiple synostoses syndrome. Overall, this review will demonstrate the critical roles of TGF-β/BMP signaling in craniofacial development and show the utility of the zebrafish model in development and disease.

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: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.461
Threshold uncertainty score0.816

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 head0.009
GPT teacher head0.227
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 designObservational
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

Citations11
Published2024
Admission routes2
Has abstractyes

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