Perturbing the developing skull: using laser ablation to investigate the robustness of the infraorbital bones in zebrafish (Danio rerio)
Bibliographic record
Abstract
BACKGROUND: The development of the craniofacial skeleton from embryonic mesenchyme is a complex process that is not yet completely understood, particularly for intramembranous bones. This study investigates the development of the neural crest derived infraorbital (IO) bones of the zebrafish (Danio rerio) skull. Located under the orbit, the IO bones ossify in a set sequence and are closely associated with the lateral line system. We conducted skeletogenic condensation and neuromast laser ablation experiments followed by shape analyses in order to investigate the relationship between a developing IO bone and the formation of the IO series as well as to investigate the highly debated inductive potential of neuromasts for IO ossification. RESULTS: We demonstrate that when skeletogenic condensations recover from laser ablation, the resulting bone differs in shape compared to controls. Interestingly, neighbouring IO bones in the bone series are unaffected. In addition, we show that the amount of canal wall mineralization is significantly decreased following neuromast laser ablation at juvenile and larval stages. CONCLUSIONS: These results highlight the developmental robustness of the IO bones and provide direct evidence that canal neuromasts play a role in canal wall development in the head. Furthermore, we provide evidence that the IO bones may be two distinct developmental modules. The mechanisms underlying developmental robustness are rarely investigated and are important to increase our understanding of evolutionary developmental biology of the vertebrate skull.
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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 | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".