An α-Smooth Muscle Actin (acta2/αsma) Zebrafish Transgenic Line Marking Vascular Mural Cells and Visceral Smooth Muscle Cells
Bibliographic record
Abstract
Mural cells of the vascular system include vascular smooth muscle cells (SMCs) and pericytes whose role is to stabilize and/or provide contractility to blood vessels. One of the earliest markers of mural cell development in vertebrates is α smooth muscle actin (acta2; αsma), which is expressed by pericytes and SMCs. In vivo models of vascular mural cell development in zebrafish are currently lacking, therefore we developed two transgenic zebrafish lines driving expression of GFP or mCherry in acta2-expressing cells. These transgenic fish were used to trace the live development of mural cells in embryonic and larval transgenic zebrafish. acta2:EGFP transgenic animals show expression that largely mirrors native acta2 expression, with early pan-muscle expression starting at 24 hpf in the heart muscle, followed by skeletal and visceral muscle. At 3.5 dpf, expression in the bulbus arteriosus and ventral aorta marks the first expression in vascular smooth muscle. Over the next 10 days of development, the number of acta2:EGFP positive cells and the number of types of blood vessels associated with mural cells increases. Interestingly, the mural cells are not motile and remain in the same position once they express the acta2:EGFP transgene. Taken together, our data suggests that zebrafish mural cells develop relatively late, and have little mobility once they associate with vessels.
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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) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.007 | 0.002 |
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".