Temperature shifts associated with bat arousals during hibernation inhibit the growth of <i>Pseudogymnoascus destructans</i>
Bibliographic record
Abstract
Temperature is a critically important factor in many infectious disease systems, because it can regulate responses in both the host and the pathogen. White-nose syndrome (WNS) in bats is a severe infectious disease caused by the temperature-sensitive fungus, Pseudogymnoascus destructans ( Pd ). One feature of WNS is an increase in the frequency of arousal bouts (i.e. when bat body temperatures are elevated) in Pd -infected bats during hibernation. While several studies have proposed that increased frequency of arousals may play a role in the pathophysiology of WNS, it is unknown if the temperature fluctuations might mediate Pd growth. We hypothesized that exposure to a high frequency of elevated temperatures would reduce Pd growth due to thermal constraints on the pathogen. We simulated the thermal conditions for arousal bouts of uninfected and infected bats during hibernation (fluctuating from 8 to 25°C at two different rates) and quantified Pd growth in vitro . We found that increased exposure to high temperatures significantly reduced Pd growth. Because temperature is one of the most critical abiotic factors mediating host–pathogen interactions, resolving how Pd responds to fluctuating temperatures will provide insights for understanding WNS in bats and other fungal diseases.
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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".