Brilacidin, a host defense peptide mimetic, potentiates ibrexafungerp antifungal activity against the human pathogenic fungus <i>Aspergillus fumigatus</i>
Bibliographic record
Abstract
ABSTRACT Aspergillus fumigatus is the primary etiological agent of aspergillosis. Here, we show that the host defense peptide mimetic brilacidin (BRI) can potentiate ibrexafungerp (IBX) against clinical isolates of A. fumigatus . BRI + IBX can inhibit the growth of A. fumigatus voriconazole- and caspofungin-resistant clinical isolates. BRI is a small molecule host defense peptide mimetic that has previously exhibited broad-spectrum immunomodulatory/anti-inflammatory activity against viruses, bacteria, and fungi. In vitro , combination of BRI + IBX plays a fungicidal role, increases the fungal cell permeability, decreases the fungal survival in the presence of A549 epithelial cells, and appears as a promising antifungal therapeutic alternative against A. fumigatus . IMPORTANCE Invasive fungal infections have a high mortality rate causing more deaths annually than tuberculosis or malaria. Aspergillus fumigatus causes a series of distinct invasive fungal infections have a high mortality rate causing more deaths annually than tuberculosis or malaria. A. fumigatus causes a spectrum of distinct clinical entities named aspergillosis, which the most severe form is the invasive pulmonary aspergillosis. There are few therapeutic options for treating aspergillosis and searching for new antifungal agents against this disease is very important. Here, we present brilacidin (BRI) as a synergizer o fibrexafungerp (IBX) against A. fumigatus . BRI is a small molecule host defense peptide mimetic that has previously exhibited broad-spectrum immunomodulatory/anti-inflammatory activity against bacteria and viruses. We propose the combination of BRI and IBX as a new antifungal combinatorial treatment against aspergillosis.
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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) | 0.002 | 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".