Epidermal ‘alarm substance’ cells of fishes maintained by non-alarm functions: possible defence against pathogens, parasites and UVB radiation
Bibliographic record
Abstract
Many fishes possess specialized epidermal cells that are ruptured by the teeth of predators, thus reliably indicating the presence of an actively foraging predator. Understanding the evolution of these cells has intrigued evolutionary ecologists because the release of these alarm chemicals is not voluntary. Here, we show that predation pressure does not influence alarm cell production in fishes. Alarm cell production is stimulated by exposure to skin-penetrating pathogens (water moulds: Saprolegnia ferax and Saprolegnia parasitica), skin-penetrating parasites (larval trematodes: Teleorchis sp. and Uvulifer sp.) and correlated with exposure to UV radiation. Suppression of the immune system with environmentally relevant levels of Cd inhibits alarm cell production of fishes challenged with Saprolegnia. These data are the first evidence that alarm substance cells have an immune function against ubiquitous environmental challenges to epidermal integrity. Our results indicate that these specialized cells arose and are maintained by natural selection owing to selfish benefits unrelated to predator-prey interactions. Cell contents released when these cells are damaged in predator attacks have secondarily acquired an ecological role as alarm cues because selection favours receivers to detect and respond adaptively to public information about predation.
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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 | 0.000 | 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".