Synthetic Human Lactoferrin Peptide hLF(1-11) Shows Antifungal Activity and Synergism with Fluconazole and Anidulafungin Towards Candida albicans and Various Non-Albicans Candida Species, Including Candidozyma auris
Bibliographic record
Abstract
Introduction: Candidozyma auris (Cz. auris) has emerged globally, and diseases caused by it are associated with a mortality rate of 30–72%. This yeast is often multidrug-resistant and challenging to treat. A synthetic peptide, consisting of 11 amino acids of human lactoferrin (hLF1-11), offers a new therapy that is active against Candida albicans, non-albicans Candida yeasts, as well as Cz. auris. The current study examined the susceptibility of clinically relevant Candida species to hLF(1-11) in vitro and investigated the synergistic interaction of this peptide with fluconazole (FLU) and anidulafungin (ANI). Methods: Susceptibility of the yeasts to hLF(1-11) was tested with a microdilution method to determine minimum inhibitory concentrations (MICs). A total of 59 strains belonging to 16 species of Candida or Candidozyma were tested. The treatment cohort included 20 strains of Cz. auris originating from six different countries. Results: Mean MIC values of all susceptible strains ranged from 16.66 ± 6.46 μg/mL to 45.83 ± 10.21 μg/mL. There were no statistical differences in the susceptibility of hLF(1-11) for Cz. auris across geographic origins. In the combinatory tests, drugs acting together, the fractional inhibitory concentration indexes [FIC] < 1.0, showed a synergistic or additive effect on the efficacy of FLU and ANI when used in combination with hLF(1-11). [FIC] indexes 1–2 were interpreted as intermediate. MIC values in combinatory use were 1–2 titer steps lower than when used alone. Conclusions: hLF(1-11) inhibits the growth of yeasts that belong to the genus Candida, including Cz. auris. The combinatory use may be further investigated to treat infections caused by resistant yeasts.
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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 | 0.000 | 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".