Functional and physiological resistance of crayfish to amphibian toxins: tetrodotoxin resistance in the white river crayfish (<i>Procambarus</i> <i>acutus</i>)
Bibliographic record
Abstract
Freshwater crayfish are reported to consume early life-history stages of a number of toxic amphibians. Although previous research indicates toxic amphibians are palatable to crayfish, the potential toxicity associated with consumption of toxic prey has been poorly described. We sought to characterise the supposed tetrodotoxin (TTX) resistance of freshwater crayfish, which have been observed to eat the eggs and larvae of toxic Taricha Gray, 1850 newts. White river crayfish (Procambarus acutus (Girard, 1852)) consumed 7.7 ± 4.0 Rough-skinned Newt (Taricha granulosa (Skilton, 1849)) eggs (mean ± SD) when offered 10 eggs in controlled feeding trials. Eggs were determined to contain a concentration of 1239 ± 571 ng (mean ± SD) of TTX. A dose-response assay was then performed to compare ingested doses with physiological TTX resistance. Crayfish were highly susceptible to TTX when administered as an intramuscular injection; TTX doses of 0.1 mass-adjusted mouse units were lethal to 100% of P. acutus crayfish. We established that while crayfish were capable consumers of highly toxic newt eggs, these decapods did not demonstrate physiological resistance to TTX. These findings suggest that crayfish have some functional resistance that renders them capable of consuming TTX-bearing prey despite a lack of physiological resistance to TTX.
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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".