Dehydration does not drive host behavioural manipulation by hairworms
Bibliographic record
Abstract
Nematomorphs are parasitic worms of arthropods, which complete their life cycle via behavioural manipulation of their host so that they can enter water to find a mate. Although this behaviour is readily observed, the underlying mechanism is largely unknown; previously proposed hypotheses include an attraction to polarised light, increased erratic behaviour and dehydration-driven behaviour. Here, we investigated the 'Dehydration Hypothesis', which posits that nematomorphs either induce dehydration or mimic dehydration through biosynthetic changes to stimulate host water-seeking behaviour. House crickets, Acheta domesticus, were experimentally deprived of water and their behaviour compared to crickets infected with the nematomorph Paragordius varius. Both infected and dehydrated crickets were more likely to interact with water than uninfected, hydrated crickets. However, dehydrated crickets preferred to submerge their heads in the water compared to infected crickets which preferred to fully enter the water. Quantitative mass spectrometry of cricket haemolymph identified unique proteomic signatures of infection (27 differentially abundant proteins, infected cf. control) and dehydration (17 differentially abundant proteins, dehydrated cf. control). Our results indicate that dehydration is not a strong driving mechanism for behavioural manipulation by nematomorphs, but nevertheless infected and dehydrated share the increased tendency of dehydrated crickets to interact with water. Our data also provide new insights into the proteomic response during nematomorph infection. Notably, we observed a decrease in the cricket egg yolk protein vitellogenin and the carbohydrate digestion enzyme α-amylase, and an increase in abundance of the immune related hemocyanin protein family.
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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 | 0.001 |
| 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".