Vasculogenesis and the Induction of Skeletogenic Condensations in the Avian Eye
Bibliographic record
Abstract
Blood vessels form via two distinct mechanisms: vasculogenesis, the formation of new blood vessels; and angiogenesis, the remodeling of preexisting blood vessels to form mature vasculature. Little research, however, focuses on the relationship between blood vessels and skeletogenic condensations, a key step in bone formation. Here, the development of the scleral ossicles in the chick begins with the induction of a neural crest-derived condensation at HH Stages 35 and 36 by overlying papillae in a 1:1 pattern. These papillae, which are epithelial thickenings of the conjunctiva, begin to form at HH Stage 30, following a distinct pattern. Nothing is currently known about their induction, or patterning. As the first papilla always forms above the ciliary artery, we mapped blood vessel development in the eye between HH Stages 28 and 36.5 using camera lucida drawings, fluorescence microscopy, and histology. Our results show that a blood vessel meshwork begins to form de novo once the ring of conjunctival papillae is complete (HH Stages 34 through 36) suggesting no direct correlation between these two events. We also observe an avascular zone beneath each conjunctival papilla, which is first visible at HH Stage 35, coinciding with the onset of induction of the skeletogenic condensations. Importantly, our findings suggest that remodeling of the vasculature and development of the avascular zones occurs at the same time as induction, but prior to the presence of the skeletogenic condensations of the intramembranous bones; this process is dissimilar to that documented for endochondral ossification in avian limb buds.
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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".