Ecology of vertical tumor transmission in the freshwater cnidarian Hydra oligactis
Bibliographic record
Abstract
Transmissible tumors are increasingly regarded as a new form of parasitic life, but relatively little is known about the ecology and evolution of their interactions with their host. In this work, we provide new insights into transmission dynamics of vertically transmitted tumors in the freshwater cnidarian Hydra oligactis. First, we found tumoral hydra to be infectious at any age, regardless of whether they were in their asymptomatic or symptomatic phases, with the bacteriome composition remaining constant during both phases. Interestingly, tumor transmission increased with the number of tentacles, particularly for hydras with supernumerary tentacles. Additionally, tumors developed earlier in the offspring from parents with more advanced tumors. Furthermore, despite being direct descendants of tumoral polyps, some hydras never developed tumoral phenotype. The latter exhibited a distinct bacteriome composition, reduced lifespan and a lower tentacle number increase over time. Interestingly, the tumor phenotype expression in these hydras appears to be able to skip generations, as transmission occurred at any age from parents to offspring. We discuss these results in the context of current knowledge on the evolutionary ecology of host-transmissible tumor interactions as well as parasite-host interactions and suggest avenues for further research.
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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 | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| 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".