Combinatorial strategies for combating invasive fungal infections
Bibliographic record
Abstract
Invasive fungal infections are an important cause of human mortality and morbidity, particularly for immunocompromised populations. However, there remains a paucity of antifungal drug treatments available to combat these fungal pathogens. Further, antifungal compounds are plagued with problems such as host toxicity, fungistatic activity, and the emergence of drug resistance in pathogen populations. A promising therapeutic strategy to increase drug effectiveness and mitigate the emergence of drug resistance is through the use of combination drug therapy. In this review we describe the current arsenal of antifungals in medicine and elaborate on the benefits of combination therapy to expand our current antifungal drug repertoire. We examine those antifungal combinations that have shown potential against fungal pathogens and discuss strategies being employed to discover novel combination therapeutics, in particular combining antifungal agents with non-antifungal bioactive compounds. The findings summarized in this review highlight the promise of combinatorial strategies in combatting invasive mycoses.
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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 | 0.001 |
| Bibliometrics | 0.002 | 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 | 0.001 |
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".