Dorsomorphin Promotes Survival and Germline Competence of Zebrafish Spermatogonial Stem Cells in Culture
Bibliographic record
Abstract
Zebrafish spermatogonial cell cultures were established from Tg(piwil1:neo);Tg(piwil1:DsRed) transgenic fish using a zebrafish ovarian feeder cell line (OFC3) that was engineered to express zebrafish Lif, Fgf2 and Gdnf. Primary cultures, initiated from testes, were treated with G418 to eliminate the somatic cells and select for the piwil1:neo expressing spermatogonia. Addition of dorsomorphin, a Bmp type I receptor inhibitor, prolonged spermatogonial stem cell (SSC) survival in culture and enhanced germline transmission of the SSCs following transplantation into recipient larvae. In contrast, dorsomorphin inhibited the growth and survival of zebrafish female germline stem cells (FGSCs) in culture. In the presence of dorsomorphin, the spermatogonia continued to express the germ-cell markers dazl, dnd, nanos3, vasa and piwil1 and the spermatogonial markers plzf and sox17 for at least six weeks in culture. Transplantation experiments revealed that 6 week-old spermatogonial cell cultures maintained in the presence of dorsomorphin were able to successfully colonize the gonad in 18% of recipient larvae and produce functional gametes in the resulting adult chimeric fish. Germline transmission was not successful when the spermatogonia were cultured 6 weeks in the absence of dorsomorphin before transplantation. The results indicate that Bmp signaling is detrimental to SSCs but required for the survival of zebrafish FGSCs in culture. Manipulation of Bmp signaling could provide a strategy to optimize culture conditions of germline stem cells from other species.
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.
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".