White-Nose Syndrome Disrupts the Splenic Lipidome of Little Brown Bats (<i>Myotis lucifugus</i>) at Early Disease Stages
Bibliographic record
Abstract
White-nose syndrome (WNS)-positive little brown bats ( Myotis lucifugus ) may exhibit immune responses including increased cytokine and pro-inflammatory mediator gene levels. Bioactive lipid mediators (oxylipins) formed by enzymatic oxidation of polyunsaturated fatty acids can contribute to these immune responses, but have not been investigated in WNS pathophysiology. Nonenzymatic conversion of polyunsaturated fatty acids can also occur due to reactive oxygen species, however, these enantiomeric isomers will lack the same signaling properties. In this study, we performed a series of targeted lipidomic approaches on laboratory Pseudogymnoascus destructans -inoculated bats to assess changes in their splenic lipidome, including the formation of lipid mediators at early stages of WNS. Hepatic lipids previously identified were also resolved to a higher structural detail. We compared WNS-susceptible M. lucifugus to a WNS-resistant species, the big brown bat ( Eptesicus fuscus ). Altered splenic lipid levels were only observed in M. lucifugus . Differences in splenic free fatty acids included both omega-3 and omega-6 compounds. Increased levels of an enantiomeric monohydroxy DHA mixture were found, suggesting nonenzymatic formation. Changes in previously identified hepatic lipids were confined to omega-3 constituents. Together, these results suggest that increased oxidative stress, but not an inflammatory response, is occurring in bats at early stages of WNS that precedes fat depletion. These data have been submitted to metabolomics workbench and assigned a study number ST002304.
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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".