<i>Cryptococcus neoformans</i> Biofilm Formation and Quantification
Bibliographic record
Abstract
Cryptococcus neoformans is an opportunistic fungal pathogen that heads the Fungal Priority Pathogen List published by the World Health Organization (WHO) in 2022. This pathogen is a primary cause of death for immunocompromised individuals (e.g., those with HIV/AIDS, the elderly, immunotherapy recipients), causing approximately 118,000 deaths yearly worldwide. C. neoformans relies on virulence factors that include a polysaccharide capsule, melanin, extracellular enzymes, and thermotolerance to initiate and sustain host infection. Additionally, similar to other fungal pathogens (e.g., Candida albicans), C. neoformans may develop a biofilm organization linked to more persistent cryptococcal infections. Cryptococcal biofilms are highlighted in cases of cryptococcal meningitis, in which biofilm-like structures form that are highly resistant to host immune response and to antifungal therapies. In this regard, fungal biofilm formation has become an important area of study as a means to improve our understanding of the mechanisms regulating biofilm formation and infection and to advance the discovery of antibiofilm therapeutics. To assess biofilm properties and compare across treatments, quantification and evaluation of cell viability are important. Herein, we describe a standardized method to establish a cryptococcal biofilm and quantify total biomass and cell viability. © 2025 The Author(s). Current Protocols published by Wiley Periodicals LLC. Basic Protocol 1: Culturing and biofilm formation Basic Protocol 2: Biofilm quantification Alternate Protocol: Biofilm viability assay.
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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 | 0.002 | 0.003 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.023 | 0.020 |
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".