Role of <i>Dlx</i> genes in craniofacial morphogenesis: <i>Dlx2</i> influences skeletal patterning by inducing ectomesenchymal aggregation in ovo
Bibliographic record
Abstract
Dlx homeodomain transcription factors are expressed in neural crest-derived mesenchyme of the pharyngeal arches and are required for patterning of the craniofacial skeleton. However, the cellular and molecular mechanisms by which Dlx factors control skeletogenesis in the facial primordia are unclear. We have investigated the function of Dlx2 and Dlx5 by sustained misexpression in ovo. We find that RCAS-Dlx2- and RCAS-Dlx5-infected avian embryos exhibit very similar patterns of local, stereotypical changes in skeletal development in the upper jaw. The changes include ectopic dermal bone along the jugal arch, and ectopic cartilages that develop between the quadrate and the trabecula. The ectopic cartilage associated with the trabecula is reminiscent of a normally occurring element in this region in some bird taxa. Analysis of the distribution of RCAS-Dlx2-infected cells suggests that Dlx2 induces aggregation of undifferentiated mesenchyme, which subsequently develops into the ectopic skeletal elements. Comparison of infected embryos with restricted or widespread misexpression, and of embryos in which Dlx genes were delivered to migratory or postmigratory neural crest, indicate that there are limited regions of competence in which the ectopic elements can arise. The site-specific differentiation program that the aggregates undergo may be dependent on local environmental signals. Our results suggest that Dlx factors mediate localization of ectomesenchymal subpopulations within the pharyngeal arches and in doing so define where skeletogenic condensations will arise. Consequently, variation in Dlx expression or activity may have influenced the morphology of jaw elements during vertebrate evolution.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".