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pmid: 31563616
Various animal models mimicking craniosynostosis have been developed, using mutant zebrafish and mouse. The aim of this paper is to review the different animal models for syndromic craniosynostosis and analyze what insights they have provided in our understanding of the pathophysiology of these conditions.The relevant literature for animal models of craniosynostosis was reviewed.Although few studies on craniosynostosis using zebrafish were published, this model appears useful in studying the suture formation mechanisms conserved across vertebrates. Conversely, several mouse models have been generated for the most common syndromic craniosynostoses, associated with mutations in FGFR1, FGFR2, FGFR3 and TWIST genes and also in MSX2, EFFNA, GLI3, FREM1, FGF3/4 genes. The mouse models have also been used to test pharmacological treatments to restore craniofacial growth.Several zebrafish and mouse models have been developed in recent decades. These animal models have been helpful for our understanding of normal and pathological craniofacial growth. Mouse models mimicking craniosynostoses can be easily used for the screening of drugs as therapeutic candidates.
[SDV] Life Sciences [q-bio], Craniosynostoses, Disease Models, Animal, Mutation, Animals, Humans
[SDV] Life Sciences [q-bio], Craniosynostoses, Disease Models, Animal, Mutation, Animals, Humans
citations This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically). | 17 | |
popularity This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network. | Top 10% | |
influence This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically). | Average | |
impulse This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network. | Top 10% |