Cancer and One Health: tumor-bearing individuals can act as super spreaders of symbionts in communities
Bibliographic record
Abstract
Recent theoretical advances in the One Health approach have suggested that cancer pathologies should be given greater consideration, as cancers often render their hosts more vulnerable to infectious agents, which could turn them into super spreaders within ecosystems. Although biologically plausible, this hypothesis has not yet been validated experimentally. Using a community of cnidarians of the Hydra genus (Hydra oligactis, Hydra viridissima, Hydra vulgaris) and a commensal ciliate species (Kerona pediculus) that colonizes them, we tested whether tumoral polyps of H. oligactis, compared to healthy ones, played an amplifying role in the number of ciliates, potentially resulting in a higher likelihood of infection for other community members through spillovers. Our results indicate that K. pediculus has a higher proliferation rate on tumoral polyps of H. oligactis than on healthy ones, which results in the infestation of other hydras. However, the magnitude of the spillover differed between recipient species. This study provides to our knowledge the first elements of proof of concept that tumoral individuals in communities could act as super spreaders of symbionts within and between species, and thus affect biotic interactions and dynamics in ecosystems.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.000 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".