Transmission of a common intestinal neoplasm in zebrafish by cohabitation
Bibliographic record
Abstract
Intestinal neoplasms are common in zebrafish (Danio rerio) research facilities. These tumours are most often seen in older fish and are classified as small cell carcinomas or adenocarcinomas. Affected fish populations always contain subpopulations with preneoplastic lesions, characterized by epithelial hyperplasia or inflammation. Previous observations indicated that these tumours are unlikely caused by diet, water quality or genetic background, suggesting an infectious aetiology. We performed five transmission experiments by exposure of naïve fish to affected donor fish by cohabitation or exposure to tank effluent water. Intestinal lesions were observed in recipient fish in all exposure groups, including transmissions from previous recipient fish, and moribund fish exhibited a higher prevalence of neoplasms. We found a single 16S rRNA sequence, most similar to Mycoplasma penetrans, to be highly enriched in the donors and exposed recipients compared to unexposed control fish. We further tracked the presence of the Mycoplasma sp. using a targeted PCR test on individual dissected intestines or faeces or tank faeces. Original donor and exposed fish populations were positive for Mycoplasma, while corresponding unexposed control fish were negative. This study indicates an infectious aetiology for these transmissible tumours of zebrafish and suggests a possible candidate agent of a Mycoplasma species.
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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 | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".