Hepatic lipid signatures of little brown bats (Myotis lucifugus) and big brown bats (Eptesicus fuscus) at early stages of white-nose syndrome
Bibliographic record
Abstract
White-nose syndrome (WNS) is an emergent wildlife fungal disease of cave-dwelling, hibernating bats that has led to unprecedented mortalities throughout North America. A primary factor in WNS-associated bat mortality includes increased arousals from torpor and premature fat depletion during winter months. Details of species and sex-specific changes in lipid metabolism during WNS are poorly understood and may play an important role in the pathophysiology of the disease. Given the likely role of fat metabolism in WNS and the fact that the liver plays a crucial role in fatty acid distribution and lipid storage, we assessed hepatic lipid signatures of little brown bats (Myotis lucifugus) and big brown bats (Eptesicus fuscus) at an early stage of infection with the etiological agent, Pseudogymnoascus destructans (Pd). Differences in lipid profiles were detected at the species and sex level in the sham-inoculated treatment, most strikingly in higher hepatic triacylglyceride (TG) levels in E. fuscus females compared to males. Interestingly, several dominant TGs (storage lipids) decreased dramatically after Pd infection in both female M. lucifugus and E. fuscus. Increases in hepatic glycerophospholipid (structural lipid) levels were only observed in M. lucifugus, including two phosphatidylcholines (PC [32:1], PC [42:6]) and one phosphatidylglycerol (PG [34:1]). These results suggest that even at early stages of WNS, changes in hepatic lipid mobilization may occur and be species and sex specific. As pre-hibernation lipid reserves may aid in bat persistence and survival during WNS, these early perturbations to lipid metabolism could have important implications for management responses that aid in pre-hibernation fat storage.
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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".