<i>Penicillium sanguifluum</i> ( <i>Penicillium</i> section <i>Citrina</i> ) as a source of dehydrocurvularin and its antifungal and antibacterial properties
Bibliographic record
Abstract
Antimicrobial resistance has a negative impact on people’s health and the economy. New resistance mechanisms are emerging, making the treatment of infections very challenging. Fungi are well known for their production of secondary metabolites during active cell growth. In this study, a strain of Penicillium sanguifluum (111-12) was isolated from Manitoba soil and investigated for antimicrobial properties of fungal secondary metabolites against pathogenic bacteria, and two fungal plant pathogens that are known for causing Dutch elm diseases and chestnut blight disease. Penicillium sanguifluum (111-12) produced dehydrocurvularin (C1) and 11-hydroxycurvularin (C2). C1 and C2 were examined for their antimicrobial properties and these compounds were combined with various antibiotics to evaluate their potentiation (adjuvant) properties. Promising results were obtained for C1 that decreased the minimum inhibitory concentrations of cefepime, ceftazidime, tobramycin, and amikacin against a clinical multidrug resistant strain of Pseudomonas aeruginosa (PA82). In addition, C1 and C2 showed no impact on the Galleria mellonella model regarding toxicity.
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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) | 0.000 | 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".