Adaptation of Cryptococcus neoformans to Mammalian Hosts: Integrated Regulation of Metabolism and Virulence
Bibliographic record
Abstract
The basidiomycete fungus Cryptococcus neoformans infects humans via inhalation of desiccated yeast cells or spores from the environment. In the absence of effective immune containment, the initial pulmonary infection often spreads to the central nervous system to result in meningoencephalitis. The fungus must therefore make the transition from the environment to different mammalian niches that include the intracellular locale of phagocytic cells and extracellular sites in the lung, bloodstream, and central nervous system. Recent studies provide insights into mechanisms of adaptation during this transition that include the expression of antiphagocytic functions, the remodeling of central carbon metabolism, the expression of specific nutrient acquisition systems, and the response to hypoxia. Specific transcription factors regulate these functions as well as the expression of one or more of the major known virulence factors of C. neoformans. Therefore, virulence factor expression is to a large extent embedded in the regulation of a variety of functions needed for growth in mammalian hosts. In this regard, the complex integration of these processes is reminiscent of the master regulators of virulence in bacterial pathogens.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.002 |
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".