Zebrafish xenografts as a tool for <i>in vivo</i> studies on human cancer
Bibliographic record
Abstract
The zebrafish has become a powerful vertebrate model for genetic studies of embryonic development and organogenesis and increasingly for studies in cancer biology. Zebrafish facilitate the performance of reverse and forward genetic approaches, including mutagenesis and small molecule screens. Moreover, several studies report the feasibility of xenotransplanting human cells into zebrafish embryos and adult fish. This model provides a unique opportunity to monitor tumor-induced angiogenesis, invasiveness, and response to a range of treatments in vivo and in real time. Despite the high conservation of gene function between fish and humans, concern remains that potential differences in zebrafish tissue niches and/or missing microenvironmental cues could limit the relevance and translational utility of data obtained from zebrafish human cancer cell xenograft models. Here, we summarize current data on xenotransplantation of human cells into zebrafish, highlighting the advantages and limitations of this model in comparison to classical murine models of xenotransplantation.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".