Bigh3 Is Upregulated in Regenerating Zebrafish Fin
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Zebrafish is a good model for studying regeneration because of the rapidity with which it occurs. Better understanding of this process may lead in the future to improvement of the regenerating capacity of humans. Signaling factors are the second largest category of genes, regulated during regeneration after the regulators of wound healing. Major developmental signaling pathways play a role in this multistep process, such as Bmp, Fgf, Notch, retinoic acid, Shh, and Wnt. In the present study, we focus on TGF-β-induced genes, bigh3 and bambia. Bigh3 encodes keratoepithelin, a protein first identified as an extracellular matrix protein reported to play a role in cell adhesion, as well as in cornea formation and osteogenesis. The expression of bigh3 in zebrafish fins has previously been reported. Here we demonstrate that tgf-b1 and tgf-b3 mRNA reacted with delay, first showing no regulation at 3 dpa, followed by upregulation at 4 and 5 dpa. Tgf-b1, tgf-2, and tgf-brII mRNA were back to normal levels at 10 dpa. Only tgf-b3 mRNA was still upregulated at that time. Bigh3 mRNA followed the upregulation of tgf-b1, while bambia mRNA behaved similarly to tgf-b2 mRNA. We show that upregulation of bigh3 and bambia mRNA correlated with the process of fin regeneration and regulation of TGF-b signaling, suggesting a new role for these proteins.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| 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 it