The Influence Of Epidermal Fatty Acids On The Growth Of Pseudogymnoascus Destructans: The Fungus That Causes White-Nose Syndrome
Bibliographic record
Abstract
White-nose Syndrome (WNS), a disease causing over-winter mortality of hibernating bats, is caused by the psychrophilic fungus Pseudogymnoascus destructans (Pd) which was introduced to upstate New York in 2006. Cutaneous epidermal infection with Pd results in erosions and lesions in the epidermal wing tissue, which causes a decrease in torpor bouts typical of WNS. The little brown bat (Myotis lucifugus) is susceptible to Pd infection however the big brown bat (Eptesicus fuscus) has not shown increased WNS mortality despite equal exposure to Pd. As the epidermis is the site of infection epidermal analysis between the species is warranted. The mammalian epidermis contains free fatty acids (FFA), some of which have been shown to have antifungal properties as part of the innate mammalian immune system. Analysis of E. fuscus and M. lucifugus epidermal FFA, as well as pre- and late hibernation FFA analysis in M. lucifugus was performed. E. fuscus epidermis contains significantly greater levels of myristic acid and oleic acid and decreased levels of pentadecanoic and stearic acid levels compared to M. lucifugus. Pre- and late hibernation comparisons in M. lucifugus revealed significant differences in all FFA except palmitic acid. Laboratory propagation of Pd on different FFA media found that increased levels of unsaturated FFA, linoleic and oleic acid, inhibited Pd growth compared to saturated FFA. Pd colonies grown on media simulating FFA content of E. fuscus were significantly smaller than those grown on media resembling M. lucifugus. These results suggest the FFA content of bat epidermis could be useful in identifying which hibernating species may be more susceptible to Pd infection which will become important as Pd spreads throughout both Canada and the United States.
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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".