Winter is coming–Temperature affects immune defenses and susceptibility to Batrachochytrium salamandrivorans
Bibliographic record
Abstract
Environmental temperature is a key factor driving various biological processes, including immune defenses and host-pathogen interactions. Here, we evaluated the effects of environmental temperature on the pathogenicity of the emerging fungal pathogen, Batrachochytrium salamandrivorans (Bsal), using controlled laboratory experiments, and measured components of host immune defense to identify regulating mechanisms. We found that adult and juvenile Notophthalmus viridescens died faster due to Bsal chytridiomycosis at 14°C than at 6 and 22°C. Pathogen replication rates, total available proteins on the skin, and microbiome composition likely drove these relationships. Temperature-dependent skin microbiome composition in our laboratory experiments matched seasonal trends in wild N. viridescens, adding validity to these results. We also found that hydrophobic peptide production after two months post-exposure to Bsal was reduced in infected animals compared to controls, perhaps due to peptide release earlier in infection or impaired granular gland function in diseased animals. Using our temperature-dependent susceptibility results, we performed a geographic analysis that revealed N. viridescens populations in the northeastern United States and southeastern Canada are at greatest risk for Bsal invasion, which shifted risk north compared to previous assessments. Our results indicate that environmental temperature will play a key role in the epidemiology of Bsal and provide evidence that temperature manipulations may be a viable disease management strategy.
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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".