Making the right choice: testing the drivers of asymmetric infections within hosts and their consequences for pathology
Bibliographic record
Abstract
Despite the ubiquity of bilateral symmetry among animals, a long‐standing mystery centers on why parasites that infect paired organs often do so non‐randomly. Examples from diverse host and parasite taxa continue to accumulate, yet little is known about their causes or implications for host–parasite fitness. We combined field surveys, experimental infections, and parasite choice assays to evaluate both competing explanations for – and consequences of – asymmetric infections of amphibian kidneys by echinostome trematodes, which are widespread and potentially pathogenic infections of larval amphibians. Samples from 6001 hosts representing 26 species indicated that echinostome infections exhibit a consistent, right‐kidney bias, with ˜ 62% of parasites in the right kidney. This pattern could not be explained by variation in kidney size or total infection. Experimental infections of three anuran species reproduced this pattern, with 64% of infections in the right kidney, and indicated it was not the result of differential host or parasite mortality. Based on sequential infection experiments and parasite choice assays, we further showed that earlier infections did not affect the distribution of subsequently colonizing parasites and that echinostome cercariae followed host‐derived cues rather than exhibiting congenital ‘sidedness’. We advance the hypothesis that variation in the position of the right kidney along the anterior–posterior axis controls cue strength in the right nephric duct and thus determines parasite encystment. Correspondingly, anatomical measurements from a subset of larval amphibian hosts revealed that the relative position of the right kidney explained 83% of the variation in infection bias, with no additional contributions associated with kidney volume or host size. We also show that the degree of right‐kidney bias associated positively with host growth in experiments. Morphological asymmetries could therefore function as a unique form of tolerance to mitigate the consequences of infection, despite the oft‐cited costs of asymmetry for mate selection and enemy vulnerability.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.002 |
| 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 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".