Growth on Douglas fir media facilitates<i>Cryptococcus</i>virulence factor production and enhances fungal survival against environmental and immune stressors
Bibliographic record
Abstract
The yeasts Cryptococcus neoformans and Cryptococcus gattii are fungal pathogens that can be isolated from the environment, including the surfaces of many plants. Cryptococcus gattii caused an outbreak on Vancouver Island, British Columbia beginning in 1999 that has since spread to the Pacific Northwest of the United States. Coastal Douglas fir (Pseudotsuga menziesii) is an important lumber species and a major component of the ecosystems in this area. Previous research has explored Cryptococcus survival and mating on Douglas fir plants and plant-derived material, but no studies have been done on the production of cryptococcal virulence factors by cells grown on those media. Here, we investigated the effects of growth on Douglas fir-derived media on the production of the polysaccharide capsule and melanin, two of the most important cryptococcal virulence factors. We found that while the capsule was mostly unchanged by growth in Douglas fir media compared to cells grown in defined minimal media, Cryptococcus spp. can use substrates present in Douglas fir to synthesize functional and protective melanin. These results suggest mechanisms by which Cryptococcus species may survive in the environment and emphasize the need to explore how association with Douglas fir trees could affect its epidemiology for human cryptococcosis.
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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 | 0.001 | 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".