Adaptation of Cryptococcus neoformans to Mammalian Hosts: Integrated Regulation of Metabolism and Virulence
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
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.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 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) | 0.000 | 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 it