Columbia spotted frogs (<i>Rana luteiventris</i>) have characteristic skin microbiota that may be shaped by cutaneous skin peptides and the environment
Bibliographic record
Abstract
Global amphibian declines due to the fungal pathogen Batrachochytrium dendrobatidis (Bd) have led to questions about how amphibians defend themselves against skin diseases. A total of two amphibian defense mechanisms are antimicrobial peptides (AMPs), a component of amphibian innate immune defense and symbiotic skin bacteria, which can act in synergy. We characterized components of these factors in four populations of Columbia spotted frogs (Rana luteiventris) to investigate their role in disease defense. We surveyed the ability of their AMPs to inhibit Bd, skin bacterial community composition, skin metabolite profiles and presence and intensity of Bd infection. We found that AMPs from R. luteiventris inhibited Bd in bioassays, but inhibition did not correlate with Bd intensity on frogs. R. luteiventris had two prevalent and abundant core bacteria: Rhizobacter and Chryseobacterium. Rhizobacter relative abundance was negatively correlated with AMP's ability to inhibit Bd, but was not associated with Bd status itself. There was no relationship between metabolites and Bd. Bacterial communities and Bd differ by location, which suggests a strong environmental influence. R. luteiventris are dominated by consistent core bacteria, but also house transient bacteria that are site specific. Our emergent hypothesis is that host control and environmental factors shape the microbiota on R. luteiventris.
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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".