Hidden allies: how extracellular vesicles drive biofilm formation, stress adaptation, and host–immune interactions in human fungal pathogens
Bibliographic record
Abstract
Pathogenic fungi pose a significant threat to human health, especially given the rising incidence of invasive fungal infections and the emergence of drug-resistant strains. This requires the development of vaccines and the advancement of antifungal strategies. Recent studies have focused on the roles of fungal extracellular vesicles (EVs) in intercellular communication and host-pathogen interactions. EVs are nanosized, lipid membrane-bound particles that facilitate the transfer of proteins, lipids, and nucleic acids. Here, we review the multifaceted functions of EVs produced by different human fungal pathogens, highlighting their importance in the response of fungal cells to different environmental cues and their interactions with host immune cells. We summarize the current state of research on EVs and how leveraging this knowledge can lead to innovative approaches in vaccine development and antifungal treatment.
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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 | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".